From 1a0b187276223aab2dd5fcff98854813f4377633 Mon Sep 17 00:00:00 2001 From: Kian Kyars Date: Fri, 17 Oct 2025 10:37:46 -0600 Subject: [PATCH 1/9] (docs) push remaining changes for sphinx documentation --- .github/workflows/docs.yml | 38 ++ .gitignore | 3 + README.md | 549 +---------------- docs/sphinx/Makefile | 20 + docs/sphinx/build.sh | 18 + docs/sphinx/requirements.txt | 3 + docs/sphinx/source/api/action.rst | 251 ++++++++ docs/sphinx/source/api/environment.rst | 128 ++++ docs/sphinx/source/api/modules.rst | 42 ++ .../api/modules/fle.agents.agent_abc.rst | 7 + .../source/api/modules/fle.agents.models.rst | 7 + .../source/api/modules/fle.commons.models.rst | 7 + .../source/api/modules/fle.env.entities.rst | 7 + .../source/api/modules/fle.env.game_types.rst | 7 + .../source/api/modules/fle.env.gym_env.rst | 7 + .../source/api/modules/fle.env.instance.rst | 7 + .../source/api/modules/fle.env.namespace.rst | 7 + .../api/modules/fle.eval.algorithms.rst | 7 + .../source/api/modules/fle.eval.tasks.rst | 7 + docs/sphinx/source/api/observation.rst | 178 ++++++ docs/sphinx/source/api/tools.rst | 276 +++++++++ docs/sphinx/source/conf.py | 88 +++ docs/sphinx/source/customization/agents.rst | 331 ++++++++++ docs/sphinx/source/customization/database.rst | 357 +++++++++++ docs/sphinx/source/customization/tasks.rst | 276 +++++++++ docs/sphinx/source/customization/tools.rst | 335 +++++++++++ docs/sphinx/source/examples/basic_agent.rst | 336 +++++++++++ docs/sphinx/source/examples/multiagent.rst | 565 ++++++++++++++++++ docs/sphinx/source/examples/visual_agent.rst | 450 ++++++++++++++ .../sphinx/source/getting_started/cluster.rst | 91 +++ .../source/getting_started/installation.rst | 98 +++ .../source/getting_started/quickstart.rst | 102 ++++ docs/sphinx/source/index.rst | 52 ++ docs/sphinx/source/tools/extract_item.rst | 98 +++ docs/sphinx/source/tools/index.rst | 209 +++++++ docs/sphinx/source/tools/insert_item.rst | 101 ++++ .../sphinx/source/tools/inspect_inventory.rst | 153 +++++ docs/sphinx/source/tools/place_entity.rst | 134 +++++ docs/versions/0.3.0.html | 29 + pyproject.toml | 3 + 40 files changed, 4844 insertions(+), 540 deletions(-) create mode 100644 .github/workflows/docs.yml create mode 100644 docs/sphinx/Makefile create mode 100755 docs/sphinx/build.sh create mode 100644 docs/sphinx/requirements.txt create mode 100644 docs/sphinx/source/api/action.rst create mode 100644 docs/sphinx/source/api/environment.rst create mode 100644 docs/sphinx/source/api/modules.rst create mode 100644 docs/sphinx/source/api/modules/fle.agents.agent_abc.rst create mode 100644 docs/sphinx/source/api/modules/fle.agents.models.rst create mode 100644 docs/sphinx/source/api/modules/fle.commons.models.rst create mode 100644 docs/sphinx/source/api/modules/fle.env.entities.rst create mode 100644 docs/sphinx/source/api/modules/fle.env.game_types.rst create mode 100644 docs/sphinx/source/api/modules/fle.env.gym_env.rst create mode 100644 docs/sphinx/source/api/modules/fle.env.instance.rst create mode 100644 docs/sphinx/source/api/modules/fle.env.namespace.rst create mode 100644 docs/sphinx/source/api/modules/fle.eval.algorithms.rst create mode 100644 docs/sphinx/source/api/modules/fle.eval.tasks.rst create mode 100644 docs/sphinx/source/api/observation.rst create mode 100644 docs/sphinx/source/api/tools.rst create mode 100644 docs/sphinx/source/conf.py create mode 100644 docs/sphinx/source/customization/agents.rst create mode 100644 docs/sphinx/source/customization/database.rst create mode 100644 docs/sphinx/source/customization/tasks.rst create mode 100644 docs/sphinx/source/customization/tools.rst create mode 100644 docs/sphinx/source/examples/basic_agent.rst create mode 100644 docs/sphinx/source/examples/multiagent.rst create mode 100644 docs/sphinx/source/examples/visual_agent.rst create mode 100644 docs/sphinx/source/getting_started/cluster.rst create mode 100644 docs/sphinx/source/getting_started/installation.rst create mode 100644 docs/sphinx/source/getting_started/quickstart.rst create mode 100644 docs/sphinx/source/index.rst create mode 100644 docs/sphinx/source/tools/extract_item.rst create mode 100644 docs/sphinx/source/tools/index.rst create mode 100644 docs/sphinx/source/tools/insert_item.rst create mode 100644 docs/sphinx/source/tools/inspect_inventory.rst create mode 100644 docs/sphinx/source/tools/place_entity.rst diff --git a/.github/workflows/docs.yml b/.github/workflows/docs.yml new file mode 100644 index 000000000..16d088271 --- /dev/null +++ b/.github/workflows/docs.yml @@ -0,0 +1,38 @@ +name: Build Documentation + +on: + push: + branches: [ main, master ] + pull_request: + branches: [ main, master ] + +jobs: + build-docs: + runs-on: ubuntu-latest + + steps: + - uses: actions/checkout@v4 + + - name: Set up Python + uses: actions/setup-python@v4 + with: + python-version: '3.10' + + - name: Install dependencies + run: | + python -m pip install --upgrade pip + pip install sphinx sphinx-rtd-theme sphinx-autodoc-typehints + pip install -e . + + - name: Build Sphinx documentation + run: | + cd docs/sphinx + sphinx-build -b html source build/html + + - name: Deploy to GitHub Pages + if: github.ref == 'refs/heads/main' || github.ref == 'refs/heads/master' + uses: peaceiris/actions-gh-pages@v3 + with: + github_token: ${{ secrets.GITHUB_TOKEN }} + publish_dir: ./docs/sphinx/build/html + destination_dir: sphinx diff --git a/.gitignore b/.gitignore index 56fd4d3c5..3de71a5f2 100644 --- a/.gitignore +++ b/.gitignore @@ -21,6 +21,9 @@ uv.lock *.egg-info/ uv.lock +# Sphinx documentation build +/docs/sphinx/build/ + # Docker **/docker-compose.yml diff --git a/README.md b/README.md index 1e21f14a7..bca2970d7 100644 --- a/README.md +++ b/README.md @@ -15,8 +15,6 @@ An open source framework for developing and evaluating LLM agents in the game of ## Why FLE? -[//]: # "FLE is a framework that tests agent capabilities in long-term planning, program synthesis, and resource optimization against a set of exponentially scaling challenges, ranging from basic automation to complex factories processing millions of resources per second. " - We provide two settings: 1. **Lab-play**: 24 structured tasks with fixed resources. @@ -28,11 +26,9 @@ exhibit promising short-horizon skills, they are unable to operate effectively i ## Quick Links - [Installation](#installation) -- [Environment](#environment) -- [Tools](#tool-documentation) -- [Project Structure](#project-structure) -- [Database](#database) -- [Contributions](#contributing-guidelines) +- [Documentation](https://jackhopkins.github.io/factorio-learning-environment/sphinx/build/html/) +- [Examples](#examples) +- [Contributing](#contributing) ## Installation @@ -73,7 +69,6 @@ fle eval --config configs/gym_run_config.json > When you run `fle init` or `fle eval` for the first time, an `.env` file and a `configs/` directory with example configurations are created automatically - ## Environment FLE is an agent evaluation environment built on the game of Factorio, a popular resource management simulation game. @@ -84,15 +79,9 @@ Agents interact with **FLE** by code synthesis through a **REPL** (Read-Eval-Pri 2. **Action**: The agent generates a Python program to perform their desired action. 3. **Feedback**: The environment executes the program, assigns variables, add classes/functions to the namespace, and provides an output stream. - - - - - +## Examples - - - -
-Action -
+```python
 # 1. Get iron patch and place mining drill
 drill = place_entity(
     entity=Prototype.MiningDrill,
@@ -109,534 +98,14 @@ chest = place_entity_next_to(
 sleep(10) # Sleep for 10 seconds
 assert drill.status == EntityStatus.WORKING
 print(get_entities())
-
-		 -Feedback -
->>> [ BurnerMiningDrill(fuel=Inventory({'coal': 4}), 
->>>                     name='burner-mining-drill', 
->>>                     direction=Direction.DOWN, 
->>>                     position=Position(x=-28.0, y=-61.0), 
->>>                     energy=2666.6666666667, 
->>>                     tile_dimensions=TileDimensions(tile_width=2.0, tile_height=2.0), 
->>>                     status=EntityStatus.WORKING, 
->>>                     neighbours=[Entity(name='iron-chest', direction=DOWN, position=Position(x=-27.5 y=-59.5)], 
->>>                     drop_position=Position(x=-27.5, y=-59.5), 
->>>                     resources=[Ingredient(name='iron-ore', count=30000, type=None)]),
->>>   Chest(name='iron-chest', 
->>>         direction=Direction.UP, 
->>>         position=Position(x=-27.5, y=-59.5), 
->>>         energy=0.0, 
->>>         tile_dimensions=TileDimensions(tile_width=1.0, tile_height=1.0), 
->>>         status=EntityStatus.NORMAL, 
->>>         inventory=Inventory({'iron-ore': 75}))]
-
-
- - - -Agents are provided with the Python standard library, and an API comprising [tools](#tool-documentation) that they can use. - -Tools are functions that perform a game action and return a typed object (e.g an Inventory), which can be stored as a named **variable** in the Python namespace for later use. - -The namespace acts as an episodic symbolic memory system, and saved objects represent an observation of the environment at the moment of query. - -This enables agents to maintain complex state representations and build hierarchical abstractions as the factories scale. - -Agents observe **stdout** and **stderr** - the output streams of their program. Agents may intentionally choose to print relevant objects and computations to the output stream to construct observations. - -Mistakes in the code or invalid operations raise typed **exceptions** with detailed context that is written to stderr. - -This enables agents to reactively debug their programs after execution, and proactively use runtime assertions during execution to self-verify their actions. - -Agents are able to enhance their internal representation of the game state by defining: - -1. Utility functions for reuse throughout an episode, to encapsulate previously successful logic -2. Classes in the namespace to better organize the data retrieved from the game. - -### Gym Environment Registry - -The Factorio Learning Environment uses a gym environment registry to automatically discover and register all available tasks. This allows you to use `gym.make()` to create environments and reference them by their environment IDs. - -#### Overview - -The registry system automatically discovers all task definitions in `eval/tasks/task_definitions/` and registers them as gym environments. This means you can create any Factorio environment using the familiar `gym.make()` pattern. - -#### Features - -- **Automatic Discovery**: Automatically discovers all task definitions in `eval/tasks/task_definitions/` -- **Gym Integration**: All environments are registered with `gym` and can be created using `gym.make()` -- **Task Metadata**: Provides access to task descriptions, configurations, and metadata -- **Multi-agent Support**: Supports both single-agent and multi-agent environments -- **Command-line Tools**: Built-in tools for exploring and testing environments - -#### Quick Start - -**1. List Available Environments** - -```python -from gym_env.registry import list_available_environments - -# Get all available environment IDs -env_ids = list_available_environments() -print(f"Available environments: {env_ids}") -``` - -Or use the command-line tool: - -```bash -python fle/env/gym_env/example_usage.py --list -``` - -**2. Create an Environment** - -```python -import gym - -# Create any available environment -env = gym.make("iron_ore_throughput") -``` - -**3. Use the Environment** - -```python -from fle.env.gym_env.action import Action - -# Reset the environment -obs = env.reset(options={'game_state': None}) - -# Take an action -action = Action( - agent_idx=0, # Which agent takes the action - code='print("Hello Factorio!")', # Python code to execute - game_state=None # Optional: game state to reset to before running code -) - -# Execute the action -obs, reward, terminated, truncated, info = env.step(action) - -# Clean up -env.close() ``` -#### Available Environments - -The registry automatically discovers all task definitions and creates corresponding gym environments using the task key as the environment ID. - -**Throughput Tasks (Lab Play)** - -All throughput tasks are defined in `fle/eval/tasks/task_definitions/lab_play/throughput_tasks.py`. The 24 available tasks are: - -- **Circuits**: `advanced_circuit_throughput`, `electronic_circuit_throughput`, `processing_unit_throughput` -- **Science Packs**: `automation_science_pack_throughput`, `logistics_science_pack_throughput`, `chemical_science_pack_throughput`, `military_science_pack_throughput`, `production_science_pack_throughput`, `utility_science_pack_throughput` -- **Components**: `battery_throughput`, `engine_unit_throughput`, `inserter_throughput`, `iron_gear_wheel_throughput`, `low_density_structure_throughput` -- **Raw Materials**: `iron_ore_throughput`, `iron_plate_throughput`, `steel_plate_throughput`, `plastic_bar_throughput` -- **Oil & Chemicals**: `crude_oil_throughput`, `petroleum_gas_throughput`, `sufuric_acid_throughput`, `sulfur_throughput` -- **Military**: `piercing_round_throughput`, `stone_wall_throughput` - -Most tasks require 16 items per 60 seconds; fluid tasks require 250 units per 60 seconds. - -**Example Usage** - -```python -# Create a throughput environment -env = gym.make("iron_plate_throughput") -env = gym.make("automation_science_pack_throughput") -env = gym.make("crude_oil_throughput") - -# Create open play environment -env = gym.make("open_play") -``` - -#### Command-Line Tools - -The `example_usage.py` script provides both interactive examples and command-line tools: - -```bash -# Run interactive examples -python fle/env/gym_env/example_usage.py - -# List all environments -python fle/env/gym_env/example_usage.py --list - -# Show detailed information -python fle/env/gym_env/example_usage.py --detail - -# Search for specific environments -python fle/env/gym_env/example_usage.py --search iron - -# Output in gym.make() format -python fle/env/gym_env/example_usage.py --gym-format -``` - -#### Environment Interface - -All environments follow the standard gym interface: - -**Action Space** - -```python -{ - 'agent_idx': Discrete(instance.num_agents), # Index of the agent taking the action - 'game_state': Text(max_length=1000000), # Optional: game state to reset to before running code - 'code': Text(max_length=10000) # Python code to execute -} -``` - -**Observation Space** -The observation space includes: - -- `raw_text`: Output from the last action -- `entities`: List of entities on the map -- `inventory`: Current inventory state -- `research`: Research progress and technologies -- `game_info`: Game state (tick, time, speed) -- `score`: Current score -- `flows`: Production statistics -- `task_verification`: Task completion status -- `messages`: Inter-agent messages -- `serialized_functions`: Available functions -- `task_info`: Information about the task -- `map_image`: Base64 encoded PNG image - -**Methods** - -- `reset(options: Dict[str, Any], seed: Optional[int] = None) -> Dict[str, Any]` -- `step(action: Action) -> Tuple[Dict[str, Any], float, bool, bool, Dict[str, Any]]` -- `close() -> None` - -#### API Reference - -**Registry Functions** - -- `list_available_environments() -> List[str]` - Returns a list of all registered environment IDs -- `get_environment_info(env_id: str) -> Optional[Dict[str, Any]]` - Returns detailed information about a specific environment -- `register_all_environments() -> None` - Manually trigger environment discovery and registration - -**Environment Creation** - -- `gym.make(env_id: str, **kwargs) -> FactorioGymEnv` - Creates a Factorio gym environment - -#### Complete Example - -Here's a complete example that demonstrates the full workflow: - -```python -import gym -from fle.env.gym_env.registry import list_available_environments, get_environment_info -from fle.env.gym_env.action import Action - -# 1. List available environments -env_ids = list_available_environments() -print(f"Found {len(env_ids)} environments") - -# 2. Get information about a specific environment -info = get_environment_info("iron_ore_throughput") -print(f"Description: {info['description']}") - -# 3. Create the environment -env = gym.make("iron_ore_throughput") +## Documentation -# 4. Use the environment -obs = env.reset(options={'game_state': None}) -print(f"Initial observation keys: {list(obs.keys())}") - -# 5. Take actions -current_state = None -for step in range(5): - action = Action( - agent_idx=0, - game_state=current_state, - code=f'print("Step {step}: Hello Factorio!")' - ) - obs, reward, terminated, truncated, info = env.step(action) - done = terminated or truncated - current_state = info['output_game_state'] - print(f"Step {step}: Reward={reward}, Done={done}") - - if done: - break - -# 6. Clean up -env.close() -``` -#### Error Handling - -The registry includes error handling for: - -- Missing task definition files -- Invalid JSON configurations -- Missing Factorio containers -- Environment creation failures - -If an environment fails to load, a warning will be printed but the registry will continue to load other environments. - -#### Troubleshooting - -**Environment Creation Fails** - -If `gym.make()` fails with connection errors: - -1. Ensure Factorio containers are running -2. Check that the cluster setup is working -3. Verify network connectivity - -**No Environments Found** - -If no environments are listed: - -1. Check that the task definitions directory exists -2. Verify JSON files are valid -3. Check file permissions - -**Import Errors** - -If you get import errors: - -1. Ensure you're running from the correct directory -2. Check that all dependencies are installed -3. Verify the Python path includes the project root - -#### Testing - -Run the test suite to verify the registry is working correctly: - -```bash -python env/tests/gym_env/test_registry.py -``` - -This registry system provides a clean, standardized interface for working with Factorio gym environments, making it easy to experiment with different tasks and integrate with existing gym-based frameworks. - - -### Client-side running (optional, renders graphics) - -1. **Set up Factorio client**: - - Purchase Factorio from the [official website](https://www.factorio.com/) (recommended) or on Steam. - - Downgrade to version 1.1.110: - - Steam: Right-click Factorio → Properties → Betas → Select 1.1.110 - - **Important**: Make sure to uncheck the Space Age DLC if you have it, as it forces the 2.x branch - -2. **Activate server**: - - Open Factorio client - - Navigate to _Multiplayer_ - - Connect to `localhost:34197` (default) or your configured address in Docker. - - Once connected, you can safely disconnect. This step confirms your Factorio license with the server. - -### API Key Configuration - -FLE supports multiple LLM providers for agent evaluation. To get started with API keys: - -1. **Quick Setup** (Recommended): - ```bash - python fle/eval/infra/setup_api_keys.py - ``` - - This interactive script helps you: - - Configure API keys for OpenAI, Anthropic, and other providers - - Set up API key rotation for high-volume experiments - - Generate provider-specific configuration files - - Validate your API key setup - -2. **Manual Setup**: - Add your API keys to the `.env` file: - ```bash - # OpenAI - OPENAI_API_KEY=sk-... - - # Anthropic - ANTHROPIC_API_KEY=sk-ant-... - - # Additional providers as needed - ``` - -3. **Advanced Configuration**: - For large-scale experiments, you can set up API key rotation and provider-specific settings using the configuration files generated by `setup_api_keys.py`. - -### Troubleshooting - -- **"No valid programs found for version X"**: This is normal during initialization. The system will start generating programs shortly. -- **Database connection errors**: Verify your database configuration in the .env file and ensure the database exists. -- **API key errors**: Run `python fle/eval/infra/setup_api_keys.py` to verify your API key configuration. -- **Docker issues**: Ensure your user has permission to run Docker without sudo. -- **Connection issues**: Make sure the Factorio server is running and ports are properly configured. - - -## Tool Documentation - -Agents interact with the game using _tools_, which represent a narrow API into the game. - -### Anatomy of a Tool - -Tools live in `env/src/tools`, and are either `admin` tools (non-agent accessible) or `agent` tools (used by the agent). - -A tool requires 3 files: - -1. `agent.md`: The agent documentation for the tool, including usage patterns, best practices and failure modes. -2. `client.py`: The client-side implementation, which is a Python class that can be invoked by the agent. -3. `server.lua`: The server-side implementation, which handles most of the logic and heavy lifting. - -```mermaid ---- -config: - layout: fixed - flowchart: - defaultRenderer: - elk ---- -flowchart LR - A("fa:fa-comment-dots Agent") - subgraph s1["Learning Environment"] - - B("fa:fa-code Interpreter") - n1("client.py") - end - subgraph s2["Factorio Server"] - E1["fa:fa-shapes server.lua"] - F("fa:fa-cog Factorio Engine") - end - - A -- Synthesises Python --> B - B -- Invokes --> n1 - n1 -. Exceptions .-> B - n1 -. Objects .-> B - n1 --Remote TCP Call--> E1 - E1 -- Execute --> F - - F-. Result .-> E1 - E1 -. TCP Response .-> n1 - B -. Observation .-> A -``` - -### Creating a custom Tool - -1. Create a new directory in `env/src/tools/agent`, e.g `env/src/tools/agent/my_tool` -2. Add a `client.py` file, which should contain a class inheriting `Tool` and implementing a `__call__` function to treat the class as a callable function. The method signature should contain type annotations. This function _must_ call `self.execute` to invoke the server-side logic. -3. Add a `server.lua` file, containing a function structured like `global.actions.my_tool = function(arg1, arg2, ...)`. This file should invoke the [Factorio API](https://lua-api.factorio.com/1.1.110/) to perform the desired action, and return a table that will be serialized and sent back to the client. -4. Add an `agent.md` file, which should contain a markdown description of the tool. This file will be used by the agent to understand how to use the tool - -Next time you run an eval, the tool will automatically be available to the agent and documented in the agent context. - -5. (Optional) Create a test suite in `env/tests/actions` for your new tool. - -### Core Tools - -| Tool | Description | Key Features | -| ----------------------- | ------------------------------------------------ | ------------------------------------------------------------------------------------------------------------------------------------------ | -| `inspect_inventory` | Checks contents of player or entity inventories | - Supports various inventory types (chests, furnaces, etc.)
- Returns Inventory object with count methods
- Can query specific items | -| `insert_item` | Places items from player inventory into entities | - Works with machines, chests, belts
- Validates item compatibility
- Returns updated entity | -| `extract_item` | Removes items from entity inventories | - Supports all inventory types
- Auto-transfers to player inventory
- Returns quantity extracted | -| `place_entity` | Places entities in the world | - Handles direction and positioning
- Validates placement requirements
- Returns placed Entity object | -| `place_entity_next_to` | Places entities relative to others | - Automatic spacing/alignment
- Handles entity dimensions
- Supports all entity types | -| `pickup_entity` | Removes entities from the world | - Returns items to inventory
- Handles entity groups
- Supports all placeable items | -| `rotate_entity` | Changes entity orientation | - Affects entity behavior (e.g., inserter direction)
- Validates rotation rules
- Returns updated entity | -| `get_entity` | Retrieves entity objects at positions | - Updates stale references
- Returns typed Entity objects
- Handles all entity types | -| `get_entities` | Finds multiple entities in an area | - Supports filtering by type
- Returns List[Entity]
- Groups connected entities | -| `nearest` | Locates closest resources/entities | - Finds ores, water, trees
- Returns Position object
- 500 tile search radius | -| `get_resource_patch` | Analyzes resource deposits | - Returns size and boundaries
- Supports all resource types
- Includes total resource amount | -| `harvest_resource` | Gathers resources from the world | - Supports ores, trees, rocks
- Auto-collects to inventory
- Returns amount harvested | -| `connect_entities` | Creates connections between entities | - Handles belts, pipes, power
- Automatic pathfinding
- Returns connection group | -| `get_connection_amount` | Calculates required connection items | - Pre-planning tool
- Works with all connection types
- Returns item count needed | -| `set_entity_recipe` | Configures machine crafting recipes | - Works with assemblers/chemical plants
- Validates recipe requirements
- Returns updated entity | -| `get_prototype_recipe` | Retrieves crafting requirements | - Shows ingredients/products
- Includes crafting time
- Returns Recipe object | -| `craft_item` | Creates items from components | - Handles recursive crafting
- Validates technology requirements
- Returns crafted amount | -| `set_research` | Initiates technology research | - Validates prerequisites
- Returns required ingredients
- Handles research queue | -| `get_research_progress` | Monitors research status | - Shows remaining requirements
- Tracks progress percentage
- Returns ingredient list | -| `move_to` | Moves player to position | - Pathfinds around obstacles
- Can place items while moving
- Returns final position | -| `nearest_buildable` | Finds valid building locations | - Respects entity dimensions
- Handles resource requirements
- Returns buildable position | -| `sleep` | Pauses execution | - Waits for actions to complete
- Adapts to game speed
- Maximum 15 second duration | -| `launch_rocket` | Controls rocket silo launches | - Validates launch requirements
- Handles launch sequence
- Returns updated silo state | -| `print` | Outputs debug information to stdout | - Supports various object types
- Useful for monitoring state
- Returns formatted string | - -# Project Structure - -Below is an overview of how the project is structured. - -``` -factorio-learning-environment/ -├── .github/ # GitHub workflows and CI/CD -├── .fle/ # Runtime data (saves, scenarios, trajectory logs) -├── docs/ # Documentation and website -├── examples/ # Example agent implementations -├── fle/ # Main codebase -│ ├── agents/ # Agent implementations (BasicAgent, VisualAgent, etc.) -│ ├── cluster/ # Docker orchestration and scenarios -│ ├── commons/ # Shared utilities and models -│ ├── configs/ # Configuration files -│ ├── data/ # Data files and replays -│ ├── env/ # Core environment -│ │ ├── gym_env/ # OpenAI Gym interface -│ │ ├── tools/ # Agent-accessible tools (place_entity, craft_item, etc.) -│ │ ├── protocols/ # Communication protocols (A2A, MCP) -│ │ ├── exceptions/ # Custom exceptions -│ │ └── utils/ # Environment utilities -│ ├── eval/ # Evaluation framework -│ │ ├── algorithms/ # Beam search, MCTS, independent evaluation -│ │ ├── analysis/ # Analysis tools -│ │ ├── tasks/ # Task definitions -│ │ └── evaluator.py # Main evaluation logic -│ ├── run.py # CLI entry point -│ └── server.py # RCON server -├── tests/ # Test suite (actions, benchmarks, functional, etc.) -├── .example.env # Environment variables template -├── BUILD.md # Build instructions -├── CONTRIBUTING.md # Contribution guidelines -├── pyproject.toml # Python project config -└── uv.lock # Dependency lock file -``` -## Model Context Protocol (MCP) - -FLE supports the [Model Context Protocol](fle/env/protocols/_mcp/README.md) (MCP) to enable LLM reasoning models to invoke tools. - -## Sprites - -FLE includes sprite management functionality for downloading spritemaps, extracting individual entity sprites, icons, and other visual assets from HuggingFace for use in visual reasoning tasks. - -### Usage - -```bash -# Download and generate sprites -fle sprites - -# Force re-download even if sprites exist -fle sprites --force - -# Use custom directories and worker count -fle sprites --spritemap-dir .fle/spritemaps --sprite-dir .fle/sprites --workers 5 -``` - -## Database - -To run long trajectories in FLE, we support checkpointing at every agent step using a SQL database. The `db_client` implements the interface for saving and loading agent outputs, environment feedbacks, game states and histories of the current trajectory. We support out of the box SQLite (default) and Postgres databases. The easiest way to set up a FLE-compatible database is to use the default SQLite, the env variable `FLE_DB_TYPE="sqlite"` lets you select the DB. - -We recommend changing and setting up the `SQLITE_DB_FILE` variable in the `.env` file. It defaults to `.fle/data.db` in your working directory. - -### Postgres - -Make sure all variables are set in the `.env` file with `FLE_DB_TYPE="postgres"`. - -To utilize postgres database you need to setup an instance of the db server yourself. The easiest way is to run it via Docker: - -`docker run --name fle-postgres -e POSTGRES_PASSWORD=fle123 -e POSTGRES_USER=fle_user -e POSTGRES_DB=fle_database -p 5432:5432 -d postgres:15` - -This launches a postgres:15 server with the defined settings, it can be used via the corresponding `.env` variables: - -``` -# Database Configuration - Set to postgres to use PostgreSQL -FLE_DB_TYPE="postgres" - -# PostgreSQL Configuration -SKILLS_DB_HOST=localhost -SKILLS_DB_PORT=5432 -SKILLS_DB_NAME=fle_database -SKILLS_DB_USER=fle_user -SKILLS_DB_PASSWORD=fle123 -``` +For complete documentation, visit: https://jackhopkins.github.io/factorio-learning-environment/sphinx/build/html/ -## Contributing Guidelines +## Contributing Join our team and contribute to one of the AI research community's most challenging problems - building open-ended / unsaturateable evals for post-AGI frontier models. If you want to contribute, please read [CONTRIBUTING.md](CONTRIBUTING.md) first. -[![Ask DeepWiki](https://deepwiki.com/badge.svg)](https://deepwiki.com/JackHopkins/factorio-learning-environment) +[![Ask DeepWiki](https://deepwiki.com/badge.svg)](https://deepwiki.com/JackHopkins/factorio-learning-environment) \ No newline at end of file diff --git a/docs/sphinx/Makefile b/docs/sphinx/Makefile new file mode 100644 index 000000000..af23b2de2 --- /dev/null +++ b/docs/sphinx/Makefile @@ -0,0 +1,20 @@ +# Minimal makefile for Sphinx documentation +# + +# You can set these variables from the command line, and also +# from the environment for the first two. +SPHINXOPTS ?= +SPHINXBUILD ?= sphinx-build +SOURCEDIR = source +BUILDDIR = build + +# Put it first so that "make" without argument is like "make help". +help: + @$(SPHINXBUILD) -M help "$(SOURCEDIR)" "$(BUILDDIR)" $(SPHINXOPTS) $(O) + +.PHONY: help Makefile + +# Catch-all target: route all unknown targets to Sphinx using the new +# "make mode" option. $(O) is meant as a shortcut for $(SPHINXOPTS). +%: Makefile + @$(SPHINXBUILD) -M $@ "$(SOURCEDIR)" "$(BUILDDIR)" $(SPHINXOPTS) $(O) diff --git a/docs/sphinx/build.sh b/docs/sphinx/build.sh new file mode 100755 index 000000000..7648d0269 --- /dev/null +++ b/docs/sphinx/build.sh @@ -0,0 +1,18 @@ +#!/bin/bash + +# Build Sphinx documentation +# This script builds the Sphinx documentation and outputs it to the build directory + +set -e + +echo "Building Sphinx documentation..." + +# Change to the docs/sphinx directory +cd "$(dirname "$0")" + +# Build the documentation +sphinx-build -b html source build/html + +echo "Documentation built successfully!" +echo "Output directory: $(pwd)/build/html" +echo "Open $(pwd)/build/html/index.html in your browser to view the documentation." diff --git a/docs/sphinx/requirements.txt b/docs/sphinx/requirements.txt new file mode 100644 index 000000000..235b3fa92 --- /dev/null +++ b/docs/sphinx/requirements.txt @@ -0,0 +1,3 @@ +sphinx>=8.0.0 +sphinx-rtd-theme>=3.0.0 +sphinx-autodoc-typehints>=2.0.0 diff --git a/docs/sphinx/source/api/action.rst b/docs/sphinx/source/api/action.rst new file mode 100644 index 000000000..8f9737f24 --- /dev/null +++ b/docs/sphinx/source/api/action.rst @@ -0,0 +1,251 @@ +Action Space +============ + +The action space defines how agents interact with the Factorio Learning Environment through Python code synthesis. + +Action Structure +---------------- + +Actions are defined by the Action class: + +.. autoclass:: fle.env.gym_env.action.Action + :members: + :undoc-members: + :show-inheritance: + +Action Components +----------------- + +**agent_idx** + Index of the agent taking the action (for multi-agent environments) + +**code** + Python code to execute in the game environment + +**game_state** + Optional game state to reset to before running code + +Action Space Definition +------------------------ + +The action space follows this structure: + +.. code-block:: python + + { + 'agent_idx': Discrete(instance.num_agents), # Index of the agent taking the action + 'game_state': Text(max_length=1000000), # Optional: game state to reset to before running code + 'code': Text(max_length=10000) # Python code to execute + } + +Code Execution +-------------- + +The environment executes Python code in a controlled namespace that includes: + +**Standard Library** + Full Python standard library access + +**FLE Tools** + All available tools for game interaction + +**Namespace Persistence** + Variables and functions persist between actions + +**Error Handling** + Comprehensive exception handling with detailed error messages + +Example Actions +--------------- + +**Basic Movement** + .. code-block:: python + + action = Action( + agent_idx=0, + code='position = get_position()', + game_state=None + ) + +**Entity Placement** + .. code-block:: python + + action = Action( + agent_idx=0, + code=''' + drill = place_entity( + entity=Prototype.MiningDrill, + position=nearest(Resource.IronOre), + direction=Direction.NORTH + ) + ''', + game_state=None + ) + +**Complex Automation** + .. code-block:: python + + action = Action( + agent_idx=0, + code=''' + # Get iron patch and place mining drill + drill = place_entity( + entity=Prototype.MiningDrill, + position=nearest(Resource.IronOre), + direction=Direction.NORTH + ) + # Add output storage + chest = place_entity_next_to( + entity=Prototype.IronChest, + reference_position=drill.drop_position, + direction=Direction.SOUTH + ) + # Verify automation chain + sleep(10) + assert drill.status == EntityStatus.WORKING + print(get_entities()) + ''', + game_state=None + ) + +**Function Definition** + .. code-block:: python + + action = Action( + agent_idx=0, + code=''' + def place_mining_setup(resource_type, direction): + drill = place_entity( + entity=Prototype.MiningDrill, + position=nearest(resource_type), + direction=direction + ) + chest = place_entity_next_to( + entity=Prototype.IronChest, + reference_position=drill.drop_position, + direction=Direction.SOUTH + ) + return drill, chest + + # Use the function + drill, chest = place_mining_setup(Resource.IronOre, Direction.NORTH) + ''', + game_state=None + ) + +**Class Definition** + .. code-block:: python + + action = Action( + agent_idx=0, + code=''' + class MiningOperation: + def __init__(self, resource_type, position): + self.resource_type = resource_type + self.position = position + self.drill = None + self.chest = None + + def setup(self): + self.drill = place_entity( + entity=Prototype.MiningDrill, + position=self.position, + direction=Direction.NORTH + ) + self.chest = place_entity_next_to( + entity=Prototype.IronChest, + reference_position=self.drill.drop_position, + direction=Direction.SOUTH + ) + + def is_working(self): + return self.drill.status == EntityStatus.WORKING + + # Create and use the class + mining_op = MiningOperation(Resource.IronOre, nearest(Resource.IronOre)) + mining_op.setup() + print(f"Mining operation working: {mining_op.is_working()}") + ''', + game_state=None + ) + +Error Handling +-------------- + +The environment provides comprehensive error handling: + +**Syntax Errors** + Python syntax errors are caught and reported with line numbers + +**Runtime Errors** + Exceptions during code execution are captured with full stack traces + +**Tool Errors** + Invalid tool usage is reported with detailed error messages + +**Assertion Failures** + Failed assertions provide context about expected vs actual values + +Example Error Handling +---------------------- + +.. code-block:: python + + # Invalid tool usage + action = Action( + agent_idx=0, + code='place_entity(entity="invalid", position=(0, 0))', + game_state=None + ) + + # Results in error message: + # ValueError: Invalid entity type 'invalid'. Expected Prototype enum value. + +**Debugging Support** + The environment provides debugging information: + + - **Variable Inspection**: Access to all namespace variables + - **Function Signatures**: Available functions and their parameters + - **Entity State**: Current state of all game entities + - **Error Context**: Detailed error information with suggestions + +Multi-Agent Actions +------------------- + +For multi-agent environments, actions can be coordinated: + +.. code-block:: python + + # Agent 0 places a drill + action_0 = Action( + agent_idx=0, + code='drill = place_entity(entity=Prototype.MiningDrill, position=nearest(Resource.IronOre))', + game_state=None + ) + + # Agent 1 places a chest next to it + action_1 = Action( + agent_idx=1, + code='chest = place_entity_next_to(entity=Prototype.IronChest, reference_position=drill.drop_position)', + game_state=None + ) + +Action Validation +----------------- + +The environment validates actions before execution: + +- **Agent Index**: Ensures valid agent index +- **Code Length**: Limits code to prevent resource exhaustion +- **Game State**: Validates game state format if provided +- **Tool Availability**: Ensures requested tools are available + +Best Practices +-------------- + +1. **Use Descriptive Variable Names**: Make code readable and maintainable +2. **Handle Errors Gracefully**: Use try-except blocks for robust code +3. **Leverage Namespace**: Store useful objects for later reference +4. **Use Functions**: Encapsulate common operations +5. **Debug with Print**: Use print statements to monitor execution +6. **Assert Conditions**: Use assertions to verify expected behavior diff --git a/docs/sphinx/source/api/environment.rst b/docs/sphinx/source/api/environment.rst new file mode 100644 index 000000000..486440c8c --- /dev/null +++ b/docs/sphinx/source/api/environment.rst @@ -0,0 +1,128 @@ +Environment API +=============== + +The Factorio Learning Environment provides a comprehensive API for interacting with the game through Python code synthesis. + +Core Concepts +------------- + +**FactorioInstance** + The main interface for interacting with a Factorio game instance. Provides access to all game state and tools. + +**Namespace Management** + Python namespace that persists across agent actions, allowing for stateful interactions and code reuse. + +**Gym Environment Integration** + Standard OpenAI Gym interface for reinforcement learning integration. + +FactorioInstance +---------------- + +.. autoclass:: fle.env.instance.FactorioInstance + :members: + :undoc-members: + :show-inheritance: + +Key Methods +~~~~~~~~~~~ + +.. automethod:: fle.env.instance.FactorioInstance.reset +.. automethod:: fle.env.instance.FactorioInstance.step +.. automethod:: fle.env.instance.FactorioInstance.close + +Namespace Management +-------------------- + +.. autoclass:: fle.env.namespace.Namespace + :members: + :undoc-members: + :show-inheritance: + +The namespace provides: + +- **Variable Storage**: Store and retrieve objects between actions +- **Function Definitions**: Define reusable functions +- **Class Definitions**: Create custom data structures +- **Import Management**: Handle Python imports and modules + +Gym Environment +--------------- + +.. autoclass:: fle.env.gym_env.FactorioGymEnv + :members: + :undoc-members: + :show-inheritance: + +The gym environment provides: + +- **Standard Interface**: Compatible with OpenAI Gym +- **Action Space**: Structured action space for agent actions +- **Observation Space**: Rich observation space with game state +- **Reward System**: Configurable reward functions + +Environment Registry +-------------------- + +FLE uses a gym environment registry to automatically discover and register all available tasks. + +.. autofunction:: fle.env.gym_env.registry.list_available_environments +.. autofunction:: fle.env.gym_env.registry.get_environment_info +.. autofunction:: fle.env.gym_env.registry.register_all_environments + +Available Environments +~~~~~~~~~~~~~~~~~~~~~~~ + +**Throughput Tasks (Lab Play)** + All throughput tasks are defined in `fle/eval/tasks/task_definitions/lab_play/throughput_tasks.py`. The 24 available tasks are: + + - **Circuits**: `advanced_circuit_throughput`, `electronic_circuit_throughput`, `processing_unit_throughput` + - **Science Packs**: `automation_science_pack_throughput`, `logistics_science_pack_throughput`, `chemical_science_pack_throughput`, `military_science_pack_throughput`, `production_science_pack_throughput`, `utility_science_pack_throughput` + - **Components**: `battery_throughput`, `engine_unit_throughput`, `inserter_throughput`, `iron_gear_wheel_throughput`, `low_density_structure_throughput` + - **Raw Materials**: `iron_ore_throughput`, `iron_plate_throughput`, `steel_plate_throughput`, `plastic_bar_throughput` + - **Oil & Chemicals**: `crude_oil_throughput`, `petroleum_gas_throughput`, `sufuric_acid_throughput`, `sulfur_throughput` + - **Military**: `piercing_round_throughput`, `stone_wall_throughput` + + Most tasks require 16 items per 60 seconds; fluid tasks require 250 units per 60 seconds. + +**Open Play** + Unbounded task of building the largest possible factory: `open_play` + +Example Usage +------------- + +.. code-block:: python + + import gym + from fle.env.gym_env.action import Action + + # Create any available environment + env = gym.make("iron_ore_throughput") + + # Reset the environment + obs = env.reset(options={'game_state': None}) + + # Take an action + action = Action( + agent_idx=0, # Which agent takes the action + code='print("Hello Factorio!")', # Python code to execute + game_state=None # Optional: game state to reset to before running code + ) + + # Execute the action + obs, reward, terminated, truncated, info = env.step(action) + + # Clean up + env.close() + +Error Handling +-------------- + +The environment includes comprehensive error handling for: + +- Missing task definition files +- Invalid JSON configurations +- Missing Factorio containers +- Environment creation failures +- Network connectivity issues + +If an environment fails to load, a warning will be printed but the registry will continue to load other environments. diff --git a/docs/sphinx/source/api/modules.rst b/docs/sphinx/source/api/modules.rst new file mode 100644 index 000000000..6b5e931a5 --- /dev/null +++ b/docs/sphinx/source/api/modules.rst @@ -0,0 +1,42 @@ +API Modules +=========== + +This section contains the complete API reference for all FLE modules. + +Core Environment +---------------- + +.. toctree:: + :maxdepth: 2 + + modules/fle.env.instance + modules/fle.env.namespace + modules/fle.env.gym_env + modules/fle.env.entities + modules/fle.env.game_types + +Agents +------ + +.. toctree:: + :maxdepth: 2 + + modules/fle.agents.agent_abc + modules/fle.agents.models + +Evaluation +---------- + +.. toctree:: + :maxdepth: 2 + + modules/fle.eval.tasks + modules/fle.eval.algorithms + +Common Models +------------- + +.. toctree:: + :maxdepth: 2 + + modules/fle.commons.models diff --git a/docs/sphinx/source/api/modules/fle.agents.agent_abc.rst b/docs/sphinx/source/api/modules/fle.agents.agent_abc.rst new file mode 100644 index 000000000..0b7dd4707 --- /dev/null +++ b/docs/sphinx/source/api/modules/fle.agents.agent_abc.rst @@ -0,0 +1,7 @@ +fle.agents.agent_abc module +=========================== + +.. automodule:: fle.agents.agent_abc + :members: + :undoc-members: + :show-inheritance: diff --git a/docs/sphinx/source/api/modules/fle.agents.models.rst b/docs/sphinx/source/api/modules/fle.agents.models.rst new file mode 100644 index 000000000..16f04c4a7 --- /dev/null +++ b/docs/sphinx/source/api/modules/fle.agents.models.rst @@ -0,0 +1,7 @@ +fle.agents.models module +======================== + +.. automodule:: fle.agents.models + :members: + :undoc-members: + :show-inheritance: diff --git a/docs/sphinx/source/api/modules/fle.commons.models.rst b/docs/sphinx/source/api/modules/fle.commons.models.rst new file mode 100644 index 000000000..ffcd449b8 --- /dev/null +++ b/docs/sphinx/source/api/modules/fle.commons.models.rst @@ -0,0 +1,7 @@ +fle.commons.models module +========================= + +.. automodule:: fle.commons.models + :members: + :undoc-members: + :show-inheritance: diff --git a/docs/sphinx/source/api/modules/fle.env.entities.rst b/docs/sphinx/source/api/modules/fle.env.entities.rst new file mode 100644 index 000000000..8964ea1a3 --- /dev/null +++ b/docs/sphinx/source/api/modules/fle.env.entities.rst @@ -0,0 +1,7 @@ +fle.env.entities module +======================= + +.. automodule:: fle.env.entities + :members: + :undoc-members: + :show-inheritance: diff --git a/docs/sphinx/source/api/modules/fle.env.game_types.rst b/docs/sphinx/source/api/modules/fle.env.game_types.rst new file mode 100644 index 000000000..60ae7c422 --- /dev/null +++ b/docs/sphinx/source/api/modules/fle.env.game_types.rst @@ -0,0 +1,7 @@ +fle.env.game_types module +========================= + +.. automodule:: fle.env.game_types + :members: + :undoc-members: + :show-inheritance: diff --git a/docs/sphinx/source/api/modules/fle.env.gym_env.rst b/docs/sphinx/source/api/modules/fle.env.gym_env.rst new file mode 100644 index 000000000..a31567df5 --- /dev/null +++ b/docs/sphinx/source/api/modules/fle.env.gym_env.rst @@ -0,0 +1,7 @@ +fle.env.gym_env module +====================== + +.. automodule:: fle.env.gym_env + :members: + :undoc-members: + :show-inheritance: diff --git a/docs/sphinx/source/api/modules/fle.env.instance.rst b/docs/sphinx/source/api/modules/fle.env.instance.rst new file mode 100644 index 000000000..7e181751e --- /dev/null +++ b/docs/sphinx/source/api/modules/fle.env.instance.rst @@ -0,0 +1,7 @@ +fle.env.instance module +======================== + +.. automodule:: fle.env.instance + :members: + :undoc-members: + :show-inheritance: diff --git a/docs/sphinx/source/api/modules/fle.env.namespace.rst b/docs/sphinx/source/api/modules/fle.env.namespace.rst new file mode 100644 index 000000000..bbf5c11b8 --- /dev/null +++ b/docs/sphinx/source/api/modules/fle.env.namespace.rst @@ -0,0 +1,7 @@ +fle.env.namespace module +======================== + +.. automodule:: fle.env.namespace + :members: + :undoc-members: + :show-inheritance: diff --git a/docs/sphinx/source/api/modules/fle.eval.algorithms.rst b/docs/sphinx/source/api/modules/fle.eval.algorithms.rst new file mode 100644 index 000000000..044d3a738 --- /dev/null +++ b/docs/sphinx/source/api/modules/fle.eval.algorithms.rst @@ -0,0 +1,7 @@ +fle.eval.algorithms module +========================== + +.. automodule:: fle.eval.algorithms + :members: + :undoc-members: + :show-inheritance: diff --git a/docs/sphinx/source/api/modules/fle.eval.tasks.rst b/docs/sphinx/source/api/modules/fle.eval.tasks.rst new file mode 100644 index 000000000..b1c391a33 --- /dev/null +++ b/docs/sphinx/source/api/modules/fle.eval.tasks.rst @@ -0,0 +1,7 @@ +fle.eval.tasks module +===================== + +.. automodule:: fle.eval.tasks + :members: + :undoc-members: + :show-inheritance: diff --git a/docs/sphinx/source/api/observation.rst b/docs/sphinx/source/api/observation.rst new file mode 100644 index 000000000..1f54c065a --- /dev/null +++ b/docs/sphinx/source/api/observation.rst @@ -0,0 +1,178 @@ +Observation Space +================== + +The observation space provides rich information about the current game state, allowing agents to make informed decisions. + +Observation Structure +-------------------- + +The observation space includes the following components: + +**raw_text** + Output from the last action (stdout/stderr) + +**entities** + List of entities on the map with their current state + +**inventory** + Current inventory state of the player + +**research** + Research progress and available technologies + +**game_info** + Game state information (tick, time, speed) + +**score** + Current score and performance metrics + +**flows** + Production statistics and resource flows + +**task_verification** + Task completion status and progress + +**messages** + Inter-agent communication messages + +**serialized_functions** + Available functions and their signatures + +**task_info** + Information about the current task + +**map_image** + Base64 encoded PNG image of the current map + +Entity Information +------------------ + +Entities provide detailed information about game objects: + +.. autoclass:: fle.env.entities.Entity + :members: + :undoc-members: + :show-inheritance: + +Entity Types +~~~~~~~~~~~~ + +**MiningDrill** + Mining drills for extracting resources + +**Chest** + Storage containers for items + +**AssemblingMachine** + Machines for crafting items + +**Inserter** + Transport devices for moving items + +**TransportBelt** + Conveyor belts for item transport + +**Pipe** + Fluid transport systems + +**PowerPole** + Electrical distribution + +**Lab** + Research facilities + +Position and Direction +---------------------- + +.. autoclass:: fle.env.game_types.Position + :members: + :undoc-members: + :show-inheritance: + +.. autoclass:: fle.env.game_types.Direction + :members: + :undoc-members: + :show-inheritance: + +Inventory Management +-------------------- + +.. autoclass:: fle.env.game_types.Inventory + :members: + :undoc-members: + :show-inheritance: + +The inventory system provides: + +- **Item Storage**: Store and retrieve items +- **Count Methods**: Query item quantities +- **Type Validation**: Ensure item compatibility +- **Transfer Operations**: Move items between inventories + +Research System +--------------- + +.. autoclass:: fle.env.game_types.Research + :members: + :undoc-members: + :show-inheritance: + +Research provides: + +- **Technology Tree**: Available technologies +- **Prerequisites**: Required research +- **Progress Tracking**: Current research status +- **Unlock Management**: New technologies and recipes + +Game State Information +---------------------- + +.. autoclass:: fle.env.game_types.GameInfo + :members: + :undoc-members: + :show-inheritance: + +Game info includes: + +- **Tick Information**: Current game tick +- **Time Data**: Game time and speed +- **Performance Metrics**: FPS and UPS +- **Map Information**: World size and generation + +Task Verification +---------------- + +.. autoclass:: fle.env.game_types.TaskVerification + :members: + :undoc-members: + :show-inheritance: + +Task verification provides: + +- **Completion Status**: Whether the task is complete +- **Progress Metrics**: Current progress toward goals +- **Objective Tracking**: Individual objective status +- **Performance Data**: Efficiency and throughput metrics + +Example Observation +------------------- + +.. code-block:: python + + { + 'raw_text': 'Hello Factorio!', + 'entities': [ + Entity(name='burner-mining-drill', position=Position(x=-28.0, y=-61.0), ...), + Entity(name='iron-chest', position=Position(x=-27.5, y=-59.5), ...) + ], + 'inventory': Inventory({'iron-ore': 75, 'coal': 4}), + 'research': Research(technologies=['automation'], progress=0.5), + 'game_info': GameInfo(tick=1000, time=16.67, speed=1.0), + 'score': 150, + 'flows': {'iron-ore': 2.5, 'iron-plate': 1.2}, + 'task_verification': TaskVerification(complete=False, progress=0.3), + 'messages': [], + 'serialized_functions': ['place_entity', 'get_entities', ...], + 'task_info': {'name': 'iron_ore_throughput', 'target': 16}, + 'map_image': 'iVBORw0KGgoAAAANSUhEUgAA...' + } diff --git a/docs/sphinx/source/api/tools.rst b/docs/sphinx/source/api/tools.rst new file mode 100644 index 000000000..214dd3ba6 --- /dev/null +++ b/docs/sphinx/source/api/tools.rst @@ -0,0 +1,276 @@ +Tools API +========= + +Agents interact with the game using _tools_, which represent a narrow API into the game. Tools are functions that perform game actions and return typed objects. + +Tool Architecture +----------------- + +Tools live in `fle/env/tools/agent/` and require 3 files: + +1. **agent.md**: Documentation for the agent, including usage patterns, best practices and failure modes +2. **client.py**: Client-side implementation, a Python class that can be invoked by the agent +3. **server.lua**: Server-side implementation, which handles most of the logic and heavy lifting + +.. mermaid:: + :config: + layout: fixed + flowchart: + defaultRenderer: + elk + + flowchart LR + A("fa:fa-comment-dots Agent") + subgraph s1["Learning Environment"] + B("fa:fa-code Interpreter") + n1("client.py") + end + subgraph s2["Factorio Server"] + E1["fa:fa-shapes server.lua"] + F("fa:fa-cog Factorio Engine") + end + A -- Synthesises Python --> B + B -- Invokes --> n1 + n1 -. Exceptions .-> B + n1 -. Objects .-> B + n1 --Remote TCP Call--> E1 + E1 -- Execute --> F + F-. Result .-> E1 + E1 -. TCP Response .-> n1 + B -. Observation .-> A + +Core Tools +---------- + +Inventory Management +~~~~~~~~~~~~~~~~~~~~ + +**inspect_inventory** + Checks contents of player or entity inventories + + - Supports various inventory types (chests, furnaces, etc.) + - Returns Inventory object with count methods + - Can query specific items + +**insert_item** + Places items from player inventory into entities + + - Works with machines, chests, belts + - Validates item compatibility + - Returns updated entity + +**extract_item** + Removes items from entity inventories + + - Supports all inventory types + - Auto-transfers to player inventory + - Returns quantity extracted + +Entity Management +~~~~~~~~~~~~~~~~~ + +**place_entity** + Places entities in the world + + - Handles direction and positioning + - Validates placement requirements + - Returns placed Entity object + +**place_entity_next_to** + Places entities relative to others + + - Automatic spacing/alignment + - Handles entity dimensions + - Supports all entity types + +**pickup_entity** + Removes entities from the world + + - Returns items to inventory + - Handles entity groups + - Supports all placeable items + +**rotate_entity** + Changes entity orientation + + - Affects entity behavior (e.g., inserter direction) + - Validates rotation rules + - Returns updated entity + +Entity Queries +~~~~~~~~~~~~~~ + +**get_entity** + Retrieves entity objects at positions + + - Updates stale references + - Returns typed Entity objects + - Handles all entity types + +**get_entities** + Finds multiple entities in an area + + - Supports filtering by type + - Returns List[Entity] + - Groups connected entities + +**nearest** + Locates closest resources/entities + + - Finds ores, water, trees + - Returns Position object + - 500 tile search radius + +**nearest_buildable** + Finds valid building locations + + - Respects entity dimensions + - Handles resource requirements + - Returns buildable position + +Resource Management +~~~~~~~~~~~~~~~~~~~ + +**get_resource_patch** + Analyzes resource deposits + + - Returns size and boundaries + - Supports all resource types + - Includes total resource amount + +**harvest_resource** + Gathers resources from the world + + - Supports ores, trees, rocks + - Auto-collects to inventory + - Returns amount harvested + +Connection Management +~~~~~~~~~~~~~~~~~~~~~ + +**connect_entities** + Creates connections between entities + + - Handles belts, pipes, power + - Automatic pathfinding + - Returns connection group + +**get_connection_amount** + Calculates required connection items + + - Pre-planning tool + - Works with all connection types + - Returns item count needed + +Crafting and Research +~~~~~~~~~~~~~~~~~~~~~ + +**set_entity_recipe** + Configures machine crafting recipes + + - Works with assemblers/chemical plants + - Validates recipe requirements + - Returns updated entity + +**get_prototype_recipe** + Retrieves crafting requirements + + - Shows ingredients/products + - Includes crafting time + - Returns Recipe object + +**craft_item** + Creates items from components + + - Handles recursive crafting + - Validates technology requirements + - Returns crafted amount + +**set_research** + Initiates technology research + + - Validates prerequisites + - Returns required ingredients + - Handles research queue + +**get_research_progress** + Monitors research status + + - Shows remaining requirements + - Tracks progress percentage + - Returns ingredient list + +Movement and Control +~~~~~~~~~~~~~~~~~~~~ + +**move_to** + Moves player to position + + - Pathfinds around obstacles + - Can place items while moving + - Returns final position + +**sleep** + Pauses execution + + - Waits for actions to complete + - Adapts to game speed + - Maximum 15 second duration + +**launch_rocket** + Controls rocket silo launches + + - Validates launch requirements + - Handles launch sequence + - Returns updated silo state + +Debugging and Output +~~~~~~~~~~~~~~~~~~~~ + +**print** + Outputs debug information to stdout + + - Supports various object types + - Useful for monitoring state + - Returns formatted string + +Tool Categories +---------------- + +**Core Tools** + Essential tools for basic game interaction + +**Advanced Tools** + Specialized tools for complex operations + +**Debugging Tools** + Tools for monitoring and debugging + +**Multi-Agent Tools** + Tools for coordinated multi-agent operations + +Creating Custom Tools +--------------------- + +1. Create a new directory in `fle/env/tools/agent/`, e.g `fle/env/tools/agent/my_tool` +2. Add a `client.py` file, which should contain a class inheriting `Tool` and implementing a `__call__` function to treat the class as a callable function. The method signature should contain type annotations. This function _must_ call `self.execute` to invoke the server-side logic. +3. Add a `server.lua` file, containing a function structured like `global.actions.my_tool = function(arg1, arg2, ...)`. This file should invoke the `Factorio API `_ to perform the desired action, and return a table that will be serialized and sent back to the client. +4. Add an `agent.md` file, which should contain a markdown description of the tool. This file will be used by the agent to understand how to use the tool + +Next time you run an eval, the tool will automatically be available to the agent and documented in the agent context. + +5. (Optional) Create a test suite in `fle/tests/actions` for your new tool. + +Tool Documentation +------------------ + +Each tool has comprehensive documentation including: + +- **Overview**: What the tool does +- **Parameters**: Input parameters and their types +- **Returns**: What the tool returns +- **Examples**: Usage examples +- **Best Practices**: Recommended usage patterns +- **Failure Modes**: Common errors and how to avoid them + +See the :doc:`tools index <../tools/index>` for detailed documentation of each tool. diff --git a/docs/sphinx/source/conf.py b/docs/sphinx/source/conf.py new file mode 100644 index 000000000..8c7bac524 --- /dev/null +++ b/docs/sphinx/source/conf.py @@ -0,0 +1,88 @@ +# Configuration file for the Sphinx documentation builder. +# +# This file only contains a selection of the most common options. For a full +# list see the documentation: +# https://www.sphinx-doc.org/en/master/usage/configuration.html + +# -- Path setup -------------------------------------------------------------- + +# If extensions (or modules to document with autodoc) are in another directory, +# add these directories to sys.path here. If the directory is relative to the +# documentation root, use os.path.abspath to make it absolute, like shown here. +# +import os +import sys +sys.path.insert(0, os.path.abspath('../../..')) + +# -- Project information ----------------------------------------------------- + +project = 'Factorio Learning Environment' +copyright = '2024, FLE Team' +author = 'FLE Team' +release = '0.3.0' + +# -- General configuration --------------------------------------------------- + +# Add any Sphinx extension module names here, as strings. They can be +# extensions coming with Sphinx (named 'sphinx.ext.*') or your custom +# ones. +extensions = [ + 'sphinx.ext.autodoc', + 'sphinx.ext.napoleon', + 'sphinx.ext.viewcode', + 'sphinx.ext.intersphinx', + 'sphinx_autodoc_typehints', +] + +# Add any paths that contain templates here, relative to this directory. +templates_path = ['_templates'] + +# List of patterns, relative to source directory, that match files and +# directories to ignore when looking for source files. +# This pattern also affects html_static_path and html_extra_path. +exclude_patterns = [] + +# -- Options for HTML output ------------------------------------------------- + +# The theme to use for HTML and HTML Help pages. See the documentation for +# a list of builtin themes. +html_theme = 'sphinx_rtd_theme' + +# Add any paths that contain custom static files (such as style sheets) here, +# relative to this directory. They are copied after the builtin static files, +# so a file named "default.css" will overwrite the builtin "default.css". +html_static_path = ['_static'] + +# -- Extension configuration ------------------------------------------------- + +# -- Options for autodoc extension ------------------------------------------- +autodoc_default_options = { + 'members': True, + 'member-order': 'bysource', + 'special-members': '__init__', + 'undoc-members': True, + 'exclude-members': '__weakref__' +} + +# -- Options for intersphinx extension --------------------------------------- +intersphinx_mapping = { + 'python': ('https://docs.python.org/3/', None), + 'numpy': ('https://numpy.org/doc/stable/', None), + 'gym': ('https://gymnasium.farama.org/', None), +} + +# -- Options for Napoleon extension ----------------------------------------- +napoleon_google_docstring = True +napoleon_numpy_docstring = True +napoleon_include_init_with_doc = False +napoleon_include_private_with_doc = False +napoleon_include_special_with_doc = True +napoleon_use_admonition_for_examples = False +napoleon_use_admonition_for_notes = False +napoleon_use_admonition_for_references = False +napoleon_use_ivar = False +napoleon_use_param = True +napoleon_use_rtype = True +napoleon_preprocess_types = False +napoleon_type_aliases = None +napoleon_attr_annotations = True diff --git a/docs/sphinx/source/customization/agents.rst b/docs/sphinx/source/customization/agents.rst new file mode 100644 index 000000000..143602d55 --- /dev/null +++ b/docs/sphinx/source/customization/agents.rst @@ -0,0 +1,331 @@ +Implementing Custom Agents +========================== + +FLE provides a flexible framework for implementing custom agents. Agents interact with the environment through code synthesis and can be designed for various evaluation scenarios. + +Agent Architecture +------------------ + +Agents in FLE follow a specific architecture: + +**Base Agent Class** + Abstract base class defining the agent interface + +**Agent Implementation** + Concrete implementation of agent behavior + +**Agent Registration** + Registration with the evaluation system + +Base Agent Class +---------------- + +All agents inherit from the base agent class: + +.. autoclass:: fle.agents.agent_abc.Agent + :members: + :undoc-members: + :show-inheritance: + +Key Methods +~~~~~~~~~~~ + +**act(observation)** + Generate an action based on the current observation + +**reset()** + Reset the agent state for a new episode + +**close()** + Clean up agent resources + +Agent Implementation +-------------------- + +Create a custom agent by inheriting from the base class: + +.. code-block:: python + + from fle.agents.agent_abc import Agent + from fle.env.gym_env.action import Action + from typing import Dict, Any + + class MyCustomAgent(Agent): + def __init__(self, config: Dict[str, Any]): + super().__init__(config) + self.name = "MyCustomAgent" + self.episode_count = 0 + self.total_reward = 0.0 + + def act(self, observation: Dict[str, Any]) -> Action: + """ + Generate an action based on the current observation. + + Args: + observation: Current game state observation + + Returns: + Action to execute + """ + # Analyze the observation + entities = observation.get('entities', []) + inventory = observation.get('inventory', {}) + game_info = observation.get('game_info', {}) + + # Generate action code + code = self._generate_action_code(entities, inventory, game_info) + + return Action( + agent_idx=0, + code=code, + game_state=None + ) + + def reset(self): + """Reset agent state for new episode""" + self.episode_count += 1 + self.total_reward = 0.0 + super().reset() + + def close(self): + """Clean up agent resources""" + super().close() + + def _generate_action_code(self, entities, inventory, game_info): + """Generate Python code for the action""" + # Implement your action generation logic + return 'print("Hello from MyCustomAgent!")' + +Agent Types +----------- + +**Basic Agents** + Simple agents with basic decision-making + +**Visual Agents** + Agents that process visual information + +**Multi-Agent Systems** + Agents that coordinate with other agents + +**Learning Agents** + Agents that improve over time + +**Specialized Agents** + Agents designed for specific tasks + +Example Agent: Resource Collector +---------------------------------- + +Here's a complete example of a resource collection agent: + +.. code-block:: python + + from fle.agents.agent_abc import Agent + from fle.env.gym_env.action import Action + from fle.env.game_types import Position, Direction + from typing import Dict, Any, List + + class ResourceCollectorAgent(Agent): + def __init__(self, config: Dict[str, Any]): + super().__init__(config) + self.name = "ResourceCollectorAgent" + self.target_resources = config.get('target_resources', ['iron-ore', 'copper-ore']) + self.collected_resources = {} + self.mining_setups = [] + + def act(self, observation: Dict[str, Any]) -> Action: + """Generate action to collect resources""" + entities = observation.get('entities', []) + inventory = observation.get('inventory', {}) + + # Check if we need to set up mining + if not self.mining_setups: + code = self._setup_mining(entities) + else: + code = self._monitor_mining(entities, inventory) + + return Action( + agent_idx=0, + code=code, + game_state=None + ) + + def _setup_mining(self, entities: List) -> str: + """Set up mining operations for target resources""" + code_lines = [] + + for resource in self.target_resources: + code_lines.append(f''' +# Set up mining for {resource} +resource_pos = nearest(Resource.{resource.replace('-', '_').upper()}) +if resource_pos: + drill = place_entity( + entity=Prototype.MiningDrill, + position=resource_pos, + direction=Direction.NORTH + ) + chest = place_entity_next_to( + entity=Prototype.IronChest, + reference_position=drill.drop_position, + direction=Direction.SOUTH + ) + print(f"Set up mining for {{resource}} at {{resource_pos}}") +''') + + return '\n'.join(code_lines) + + def _monitor_mining(self, entities: List, inventory: Dict) -> str: + """Monitor and manage existing mining operations""" + return ''' +# Monitor mining operations +entities = get_entities() +for entity in entities: + if hasattr(entity, 'status') and entity.status == EntityStatus.WORKING: + print(f"Entity {entity.name} is working") + elif hasattr(entity, 'status') and entity.status == EntityStatus.NO_POWER: + print(f"Entity {entity.name} needs power") + +# Check inventory +inventory = inspect_inventory() +for item, count in inventory.items(): + if count > 0: + print(f"Have {count} {item}") +''' + +Agent Configuration +------------------- + +Agents can be configured with various parameters: + +**Behavior Parameters** + - Decision-making algorithms + - Action generation strategies + - State management approaches + +**Performance Parameters** + - Memory usage limits + - Processing time limits + - Resource consumption limits + +**Evaluation Parameters** + - Success criteria + - Performance metrics + - Evaluation scenarios + +Example Configuration +-------------------- + +.. code-block:: json + + { + "agent_type": "ResourceCollectorAgent", + "config": { + "target_resources": ["iron-ore", "copper-ore", "coal"], + "max_mining_setups": 5, + "mining_radius": 100, + "inventory_threshold": 1000 + }, + "evaluation": { + "episodes": 10, + "max_steps": 1000, + "success_threshold": 0.8 + } + } + +Agent Testing +------------- + +Create test cases for your custom agents: + +.. code-block:: python + + import pytest + from fle.agents.my_custom_agent import MyCustomAgent + from fle.env.gym_env.action import Action + + def test_agent_creation(): + config = {'param1': 'value1'} + agent = MyCustomAgent(config) + assert agent.name == "MyCustomAgent" + + def test_agent_action(): + config = {} + agent = MyCustomAgent(config) + + observation = { + 'entities': [], + 'inventory': {}, + 'game_info': {} + } + + action = agent.act(observation) + assert isinstance(action, Action) + assert action.agent_idx == 0 + + def test_agent_reset(): + config = {} + agent = MyCustomAgent(config) + agent.reset() + assert agent.episode_count == 1 + +Advanced Agent Features +----------------------- + +**State Management** + - Persistent state across episodes + - State serialization and loading + - State sharing between agents + +**Learning Capabilities** + - Experience replay + - Policy updates + - Performance tracking + +**Multi-Agent Coordination** + - Communication protocols + - Task distribution + - Conflict resolution + +**Adaptive Behavior** + - Dynamic strategy adjustment + - Environment adaptation + - Performance optimization + +Agent Registration +------------------ + +Agents are registered with the evaluation system: + +1. **Agent Discovery**: The system scans for agent implementations +2. **Configuration Loading**: Agent configurations are loaded +3. **Initialization**: Agents are initialized with their configurations +4. **Registration**: Agents are registered with the evaluation system + +Example Registration +---------------------- + +.. code-block:: python + + from fle.agents.registry import register_agent + from fle.agents.my_custom_agent import MyCustomAgent + + # Register the agent + register_agent('my_custom_agent', MyCustomAgent) + + # Use in evaluation + config = { + 'agent_type': 'my_custom_agent', + 'config': {'param1': 'value1'} + } + +Best Practices +-------------- + +1. **Clear Interface**: Design simple, intuitive interfaces +2. **Error Handling**: Handle errors gracefully +3. **State Management**: Manage agent state properly +4. **Performance**: Optimize for efficiency +5. **Testing**: Test all scenarios and edge cases +6. **Documentation**: Document agent behavior and configuration +7. **Modularity**: Design for reusability and extensibility diff --git a/docs/sphinx/source/customization/database.rst b/docs/sphinx/source/customization/database.rst new file mode 100644 index 000000000..49cb06342 --- /dev/null +++ b/docs/sphinx/source/customization/database.rst @@ -0,0 +1,357 @@ +Database Configuration +======================= + +FLE supports checkpointing at every agent step using a SQL database. The `db_client` implements the interface for saving and loading agent outputs, environment feedbacks, game states and histories of the current trajectory. + +Database Types +-------------- + +FLE supports multiple database backends: + +**SQLite (Default)** + Lightweight, file-based database + +**PostgreSQL** + Full-featured, server-based database + +**Custom Databases** + Extensible database interface + +SQLite Configuration +-------------------- + +SQLite is the default database and requires minimal configuration: + +.. code-block:: bash + + # Set database type + FLE_DB_TYPE="sqlite" + + # Set database file path (default: .fle/data.db) + SQLITE_DB_FILE=".fle/data.db" + +SQLite is ideal for: +- Development and testing +- Single-user scenarios +- Small to medium datasets +- Quick setup and deployment + +PostgreSQL Configuration +------------------------ + +For production use and large-scale experiments, PostgreSQL is recommended: + +**Docker Setup** + .. code-block:: bash + + docker run --name fle-postgres \ + -e POSTGRES_PASSWORD=fle123 \ + -e POSTGRES_USER=fle_user \ + -e POSTGRES_DB=fle_database \ + -p 5432:5432 \ + -d postgres:15 + +**Environment Variables** + .. code-block:: bash + + # Database Configuration + FLE_DB_TYPE="postgres" + + # PostgreSQL Configuration + SKILLS_DB_HOST=localhost + SKILLS_DB_PORT=5432 + SKILLS_DB_NAME=fle_database + SKILLS_DB_USER=fle_user + SKILLS_DB_PASSWORD=fle123 + +PostgreSQL is ideal for: +- Production deployments +- Multi-user scenarios +- Large datasets +- High-performance requirements + +Database Schema +--------------- + +The database schema includes several key tables: + +**Trajectories** + Store complete agent trajectories + +**Steps** + Individual agent steps within trajectories + +**Game States** + Complete game state snapshots + +**Agent Outputs** + Agent-generated code and actions + +**Environment Feedbacks** + Environment responses and observations + +**Metadata** + Additional information about trajectories + +Database Client +--------------- + +The database client provides a unified interface: + +.. autoclass:: fle.commons.db_client.DatabaseClient + :members: + :undoc-members: + :show-inheritance: + +Key Methods +~~~~~~~~~~~ + +**save_trajectory(trajectory)** + Save a complete trajectory + +**load_trajectory(trajectory_id)** + Load a trajectory by ID + +**save_step(step)** + Save an individual step + +**load_steps(trajectory_id)** + Load all steps for a trajectory + +**save_game_state(state)** + Save a game state snapshot + +**load_game_state(state_id)** + Load a game state by ID + +Example Usage +------------- + +**Saving a Trajectory** + .. code-block:: python + + from fle.commons.db_client import DatabaseClient + + # Initialize database client + db = DatabaseClient() + + # Save trajectory + trajectory = { + 'id': 'trajectory_001', + 'agent_type': 'MyAgent', + 'task': 'iron_ore_throughput', + 'start_time': '2024-01-01T00:00:00Z', + 'end_time': '2024-01-01T01:00:00Z', + 'total_reward': 150.0, + 'success': True + } + + db.save_trajectory(trajectory) + +**Loading a Trajectory** + .. code-block:: python + + # Load trajectory + trajectory = db.load_trajectory('trajectory_001') + print(f"Trajectory: {trajectory['id']}") + print(f"Agent: {trajectory['agent_type']}") + print(f"Reward: {trajectory['total_reward']}") + +**Saving Steps** + .. code-block:: python + + # Save individual step + step = { + 'trajectory_id': 'trajectory_001', + 'step_number': 1, + 'action': 'print("Hello Factorio!")', + 'observation': {'entities': [], 'inventory': {}}, + 'reward': 10.0, + 'timestamp': '2024-01-01T00:00:00Z' + } + + db.save_step(step) + +**Loading Steps** + .. code-block:: python + + # Load all steps for a trajectory + steps = db.load_steps('trajectory_001') + for step in steps: + print(f"Step {step['step_number']}: {step['action']}") + +Database Migration +------------------ + +FLE includes database migration support: + +**Automatic Migration** + The system automatically migrates the database schema on startup + +**Manual Migration** + Run migrations manually when needed + +**Version Control** + Track database schema versions + +Example Migration +------------------ + +.. code-block:: python + + from fle.commons.db_client import DatabaseClient + + # Initialize database client + db = DatabaseClient() + + # Run migrations + db.migrate() + + # Check migration status + status = db.get_migration_status() + print(f"Current version: {status['current_version']}") + print(f"Latest version: {status['latest_version']}") + +Performance Optimization +----------------------- + +**Connection Pooling** + Reuse database connections + +**Batch Operations** + Group multiple operations together + +**Indexing** + Optimize database queries + +**Caching** + Cache frequently accessed data + +Example Optimization +------------------- + +.. code-block:: python + + from fle.commons.db_client import DatabaseClient + + # Initialize with connection pooling + db = DatabaseClient( + max_connections=10, + connection_timeout=30 + ) + + # Batch save multiple steps + steps = [ + {'trajectory_id': 't1', 'step_number': 1, 'action': 'action1'}, + {'trajectory_id': 't1', 'step_number': 2, 'action': 'action2'}, + {'trajectory_id': 't1', 'step_number': 3, 'action': 'action3'} + ] + + db.batch_save_steps(steps) + +Backup and Recovery +------------------- + +**Automated Backups** + Schedule regular database backups + +**Point-in-Time Recovery** + Restore to specific timestamps + +**Data Export** + Export data for analysis + +**Data Import** + Import data from other sources + +Example Backup +-------------- + +.. code-block:: python + + from fle.commons.db_client import DatabaseClient + + # Initialize database client + db = DatabaseClient() + + # Create backup + backup_id = db.create_backup() + print(f"Backup created: {backup_id}") + + # List backups + backups = db.list_backups() + for backup in backups: + print(f"Backup {backup['id']}: {backup['timestamp']}") + + # Restore from backup + db.restore_backup(backup_id) + +Monitoring and Maintenance +-------------------------- + +**Performance Monitoring** + Monitor database performance + +**Health Checks** + Verify database health + +**Cleanup Operations** + Remove old data + +**Optimization** + Optimize database performance + +Example Monitoring +----------------- + +.. code-block:: python + + from fle.commons.db_client import DatabaseClient + + # Initialize database client + db = DatabaseClient() + + # Get database statistics + stats = db.get_statistics() + print(f"Total trajectories: {stats['trajectories']}") + print(f"Total steps: {stats['steps']}") + print(f"Database size: {stats['size']}") + + # Get performance metrics + metrics = db.get_performance_metrics() + print(f"Average query time: {metrics['avg_query_time']}") + print(f"Connection count: {metrics['connection_count']}") + +Troubleshooting +-------------- + +**Connection Issues** + - Verify database server is running + - Check connection parameters + - Verify network connectivity + +**Performance Issues** + - Monitor database performance + - Optimize queries + - Consider connection pooling + +**Data Issues** + - Verify data integrity + - Check for corruption + - Run data validation + +**Migration Issues** + - Check migration status + - Verify schema compatibility + - Run manual migrations if needed + +Best Practices +-------------- + +1. **Regular Backups**: Schedule automated backups +2. **Performance Monitoring**: Monitor database performance +3. **Connection Management**: Use connection pooling +4. **Data Validation**: Validate data integrity +5. **Migration Testing**: Test migrations before deployment +6. **Security**: Secure database access +7. **Documentation**: Document database configuration diff --git a/docs/sphinx/source/customization/tasks.rst b/docs/sphinx/source/customization/tasks.rst new file mode 100644 index 000000000..ee64635b2 --- /dev/null +++ b/docs/sphinx/source/customization/tasks.rst @@ -0,0 +1,276 @@ +Creating Custom Tasks +===================== + +FLE allows you to create custom tasks for evaluating agent capabilities. Tasks define the objectives, constraints, and success criteria for agent evaluation. + +Task Structure +-------------- + +Tasks are defined in `fle/eval/tasks/task_definitions/` and follow a specific structure: + +**Task Definition File** + JSON configuration file defining task parameters + +**Task Implementation** + Python class implementing the task logic + +**Task Registration** + Automatic registration with the gym environment registry + +Task Definition +--------------- + +Create a new task definition file in `fle/eval/tasks/task_definitions/`: + +.. code-block:: json + + { + "name": "my_custom_task", + "description": "A custom task for evaluating agent capabilities", + "type": "throughput", + "target": 16, + "time_limit": 3600, + "resources": { + "iron_ore": 10000, + "copper_ore": 5000, + "coal": 2000 + }, + "technologies": ["automation"], + "constraints": { + "max_entities": 100, + "max_power": 1000 + } + } + +Task Types +---------- + +**Throughput Tasks** + Tasks focused on producing a specific item at a target rate + +**Research Tasks** + Tasks focused on technology research and advancement + +**Construction Tasks** + Tasks focused on building specific structures + +**Exploration Tasks** + Tasks focused on map exploration and discovery + +**Multi-Objective Tasks** + Tasks with multiple competing objectives + +Task Implementation +------------------- + +Create a Python class implementing your task: + +.. code-block:: python + + from fle.eval.tasks.base import BaseTask + + class MyCustomTask(BaseTask): + def __init__(self, config): + super().__init__(config) + self.target = config.get('target', 16) + self.time_limit = config.get('time_limit', 3600) + + def evaluate(self, state): + """Evaluate the current state against task objectives""" + # Implement your evaluation logic + pass + + def is_complete(self, state): + """Check if the task is complete""" + # Implement completion criteria + pass + + def get_reward(self, state): + """Calculate reward for current state""" + # Implement reward calculation + pass + +Task Configuration +------------------ + +Tasks can be configured with various parameters: + +**Resource Constraints** + - Starting resources + - Resource availability + - Resource consumption rates + +**Technology Requirements** + - Required technologies + - Technology research costs + - Technology dependencies + +**Time Constraints** + - Time limits + - Time-based objectives + - Time-based rewards + +**Spatial Constraints** + - Map size limits + - Entity placement rules + - Distance requirements + +**Performance Constraints** + - Power consumption limits + - Entity count limits + - Efficiency requirements + +Task Registration +----------------- + +Tasks are automatically registered with the gym environment registry: + +1. **File Discovery**: The registry scans `fle/eval/tasks/task_definitions/` +2. **JSON Parsing**: Task definitions are parsed from JSON files +3. **Environment Creation**: Gym environments are created for each task +4. **Registration**: Environments are registered with gym + +Example Task +------------ + +Here's a complete example of a custom task: + +**Task Definition** (`my_custom_task.json`): + +.. code-block:: json + + { + "name": "iron_plate_throughput", + "description": "Produce iron plates at 16 items per 60 seconds", + "type": "throughput", + "target": 16, + "time_limit": 3600, + "resources": { + "iron_ore": 10000, + "coal": 2000 + }, + "technologies": ["automation"], + "constraints": { + "max_entities": 50, + "max_power": 500 + } + } + +**Task Implementation** (`my_custom_task.py`): + +.. code-block:: python + + from fle.eval.tasks.base import BaseTask + from fle.env.game_types import Entity, Inventory + + class IronPlateThroughputTask(BaseTask): + def __init__(self, config): + super().__init__(config) + self.target = config.get('target', 16) + self.time_limit = config.get('time_limit', 3600) + self.start_time = None + + def reset(self): + """Reset the task state""" + self.start_time = None + return super().reset() + + def evaluate(self, state): + """Evaluate current throughput""" + if self.start_time is None: + self.start_time = state.get('game_info', {}).get('tick', 0) + + current_time = state.get('game_info', {}).get('tick', 0) + elapsed_time = (current_time - self.start_time) / 60.0 # Convert to seconds + + if elapsed_time < 60: + return 0.0 + + # Calculate throughput + inventory = state.get('inventory', Inventory({})) + iron_plates = inventory.get('iron-plate', 0) + throughput = iron_plates / elapsed_time + + return throughput + + def is_complete(self, state): + """Check if target throughput is achieved""" + throughput = self.evaluate(state) + return throughput >= self.target + + def get_reward(self, state): + """Calculate reward based on throughput""" + throughput = self.evaluate(state) + if throughput >= self.target: + return 1.0 + else: + return throughput / self.target + +Testing Tasks +-------------- + +Create test cases for your custom tasks: + +.. code-block:: python + + import pytest + from fle.eval.tasks.my_custom_task import MyCustomTask + + def test_task_creation(): + config = { + 'target': 16, + 'time_limit': 3600 + } + task = MyCustomTask(config) + assert task.target == 16 + assert task.time_limit == 3600 + + def test_task_evaluation(): + config = {'target': 16} + task = MyCustomTask(config) + + # Mock state + state = { + 'inventory': Inventory({'iron-plate': 100}), + 'game_info': {'tick': 3600} + } + + throughput = task.evaluate(state) + assert throughput > 0 + + def test_task_completion(): + config = {'target': 16} + task = MyCustomTask(config) + + # Mock state with high throughput + state = { + 'inventory': Inventory({'iron-plate': 1000}), + 'game_info': {'tick': 3600} + } + + assert task.is_complete(state) + +Advanced Features +---------------- + +**Multi-Agent Tasks** + Tasks that require coordination between multiple agents + +**Dynamic Tasks** + Tasks that change objectives during execution + +**Hierarchical Tasks** + Tasks with sub-objectives and dependencies + +**Adaptive Tasks** + Tasks that adjust difficulty based on agent performance + +Best Practices +-------------- + +1. **Clear Objectives**: Define clear, measurable objectives +2. **Appropriate Difficulty**: Balance challenge with achievability +3. **Robust Evaluation**: Handle edge cases and error conditions +4. **Comprehensive Testing**: Test all task scenarios +5. **Documentation**: Document task requirements and constraints +6. **Performance**: Optimize evaluation for large-scale experiments diff --git a/docs/sphinx/source/customization/tools.rst b/docs/sphinx/source/customization/tools.rst new file mode 100644 index 000000000..edb30acbd --- /dev/null +++ b/docs/sphinx/source/customization/tools.rst @@ -0,0 +1,335 @@ +Creating Custom Tools +===================== + +FLE allows you to create custom tools for extending agent capabilities. Tools provide a narrow API into the game and enable agents to perform specific actions. + +Tool Architecture +----------------- + +Tools require 3 files: + +1. **agent.md**: Documentation for the agent +2. **client.py**: Client-side Python implementation +3. **server.lua**: Server-side Lua implementation + +Tool Structure +-------------- + +Create a new directory in `fle/env/tools/agent/`: + +.. code-block:: bash + + mkdir fle/env/tools/agent/my_tool + cd fle/env/tools/agent/my_tool + +**client.py** - Client-side implementation: + +.. code-block:: python + + from fle.env.tools.base import Tool + from typing import List, Optional + + class MyTool(Tool): + def __call__(self, param1: str, param2: int, param3: Optional[bool] = None) -> dict: + """ + My custom tool for doing something useful. + + Args: + param1: Description of param1 + param2: Description of param2 + param3: Optional parameter + + Returns: + Dictionary with results + """ + return self.execute({ + 'param1': param1, + 'param2': param2, + 'param3': param3 + }) + +**server.lua** - Server-side implementation: + +.. code-block:: lua + + global.actions.my_tool = function(param1, param2, param3) + -- Validate parameters + if not param1 or type(param1) ~= "string" then + return {error = "param1 must be a string"} + end + + if not param2 or type(param2) ~= "number" then + return {error = "param2 must be a number"} + end + + -- Perform the action + local result = {} + + -- Your custom logic here + -- Use Factorio API: https://lua-api.factorio.com/1.1.110/ + + return result + end + +**agent.md** - Agent documentation: + +.. code-block:: markdown + + # My Tool + + ## Overview + My custom tool for doing something useful in the game. + + ## Parameters + - `param1` (str): Description of param1 + - `param2` (int): Description of param2 + - `param3` (bool, optional): Optional parameter + + ## Returns + Dictionary with results including: + - `success` (bool): Whether the action succeeded + - `data` (dict): Additional data + + ## Examples + + ```python + # Basic usage + result = my_tool("value1", 42) + print(result['success']) + + # With optional parameter + result = my_tool("value1", 42, True) + ``` + + ## Best Practices + - Always check the return value for success + - Handle errors gracefully + - Use appropriate parameter types + + ## Failure Modes + - Invalid parameter types + - Game state conflicts + - Resource limitations + +Tool Development Process +------------------------ + +1. **Design the Interface** + - Define parameters and return types + - Consider error handling + - Plan for edge cases + +2. **Implement Client Side** + - Create Python class inheriting from Tool + - Implement __call__ method with type hints + - Call self.execute() with parameters + +3. **Implement Server Side** + - Create Lua function in global.actions + - Validate parameters + - Use Factorio API to perform actions + - Return structured results + +4. **Write Documentation** + - Document parameters and return values + - Provide usage examples + - Describe failure modes + - Include best practices + +5. **Test the Tool** + - Create test cases + - Verify error handling + - Test edge cases + - Validate performance + +Example Tool: Resource Scanner +------------------------------ + +Here's a complete example of a custom tool for scanning resources: + +**client.py**: + +.. code-block:: python + + from fle.env.tools.base import Tool + from typing import List, Dict, Optional + from fle.env.game_types import Position + + class ResourceScanner(Tool): + def __call__(self, center: Position, radius: int = 100, resource_type: Optional[str] = None) -> Dict: + """ + Scan for resources in a circular area. + + Args: + center: Center position for scanning + radius: Scan radius in tiles + resource_type: Specific resource type to scan for (optional) + + Returns: + Dictionary with scan results + """ + return self.execute({ + 'center': center, + 'radius': radius, + 'resource_type': resource_type + }) + +**server.lua**: + +.. code-block:: lua + + global.actions.resource_scanner = function(center, radius, resource_type) + -- Validate parameters + if not center or not center.x or not center.y then + return {error = "center must be a position with x and y"} + end + + if not radius or type(radius) ~= "number" or radius <= 0 then + return {error = "radius must be a positive number"} + end + + -- Get surface + local surface = game.surfaces[1] + if not surface then + return {error = "No surface available"} + end + + -- Scan for resources + local resources = {} + local center_pos = {x = center.x, y = center.y} + + for _, entity in pairs(surface.find_entities_filtered{ + area = {{center_pos.x - radius, center_pos.y - radius}, + {center_pos.x + radius, center_pos.y + radius}}, + type = "resource" + }) do + if not resource_type or entity.name == resource_type then + table.insert(resources, { + name = entity.name, + position = {x = entity.position.x, y = entity.position.y}, + amount = entity.amount + }) + end + end + + return { + success = true, + resources = resources, + count = #resources + } + end + +**agent.md**: + +.. code-block:: markdown + + # Resource Scanner + + ## Overview + Scans for resources in a circular area around a center position. + + ## Parameters + - `center` (Position): Center position for scanning + - `radius` (int): Scan radius in tiles (default: 100) + - `resource_type` (str, optional): Specific resource type to scan for + + ## Returns + Dictionary with: + - `success` (bool): Whether the scan succeeded + - `resources` (list): List of found resources + - `count` (int): Number of resources found + + ## Examples + + ```python + # Scan all resources in area + result = resource_scanner(Position(0, 0), 200) + print(f"Found {result['count']} resources") + + # Scan for specific resource + result = resource_scanner(Position(0, 0), 100, "iron-ore") + for resource in result['resources']: + print(f"{resource['name']} at {resource['position']}") + ``` + + ## Best Practices + - Use appropriate radius for your needs + - Filter by resource type when possible + - Handle empty results gracefully + + ## Failure Modes + - Invalid position coordinates + - Negative or zero radius + - Surface not available + - Resource type not found + +Testing Tools +-------------- + +Create test cases for your custom tools: + +.. code-block:: python + + import pytest + from fle.env.tools.agent.my_tool import MyTool + from fle.env.game_types import Position + + def test_tool_creation(): + tool = MyTool() + assert tool is not None + + def test_tool_execution(): + tool = MyTool() + result = tool("test", 42, True) + assert 'success' in result + + def test_tool_error_handling(): + tool = MyTool() + result = tool("", -1) # Invalid parameters + assert 'error' in result + + def test_tool_with_position(): + tool = MyTool() + position = Position(10, 20) + result = tool("test", 42, position=position) + assert result['success'] + +Tool Registration +----------------- + +Tools are automatically discovered and registered: + +1. **File Discovery**: The system scans `fle/env/tools/agent/` +2. **Import Loading**: Python classes are imported +3. **Lua Loading**: Server-side functions are loaded +4. **Documentation**: Agent documentation is parsed +5. **Registration**: Tools are made available to agents + +Advanced Features +---------------- + +**Tool Dependencies** + Tools can depend on other tools + +**Tool Caching** + Cache expensive operations + +**Tool Validation** + Validate tool usage and parameters + +**Tool Metrics** + Collect usage statistics + +**Tool Versioning** + Handle tool updates and compatibility + +Best Practices +-------------- + +1. **Clear Interface**: Design simple, intuitive interfaces +2. **Error Handling**: Provide meaningful error messages +3. **Documentation**: Write comprehensive documentation +4. **Testing**: Test all scenarios and edge cases +5. **Performance**: Optimize for efficiency +6. **Compatibility**: Ensure backward compatibility +7. **Security**: Validate all inputs and outputs diff --git a/docs/sphinx/source/examples/basic_agent.rst b/docs/sphinx/source/examples/basic_agent.rst new file mode 100644 index 000000000..4cb57aa84 --- /dev/null +++ b/docs/sphinx/source/examples/basic_agent.rst @@ -0,0 +1,336 @@ +Basic Agent Example +=================== + +This example demonstrates how to create a basic agent that interacts with the Factorio Learning Environment. + +Agent Overview +-------------- + +The basic agent performs simple resource collection and automation tasks: + +1. **Resource Discovery**: Find and identify available resources +2. **Mining Setup**: Place mining drills on resource patches +3. **Storage Management**: Create storage for collected resources +4. **Automation**: Set up basic automation chains + +Agent Implementation +-------------------- + +.. code-block:: python + + from fle.agents.agent_abc import Agent + from fle.env.gym_env.action import Action + from fle.env.game_types import Position, Direction + from typing import Dict, Any, List + + class BasicAgent(Agent): + def __init__(self, config: Dict[str, Any]): + super().__init__(config) + self.name = "BasicAgent" + self.target_resources = ['iron-ore', 'copper-ore', 'coal'] + self.mining_setups = [] + self.step_count = 0 + + def act(self, observation: Dict[str, Any]) -> Action: + """Generate action based on current observation""" + self.step_count += 1 + + # Get current state + entities = observation.get('entities', []) + inventory = observation.get('inventory', {}) + game_info = observation.get('game_info', {}) + + # Generate action code + if self.step_count == 1: + code = self._initial_setup() + elif self.step_count <= 10: + code = self._setup_mining() + else: + code = self._monitor_and_optimize(entities, inventory) + + return Action( + agent_idx=0, + code=code, + game_state=None + ) + + def _initial_setup(self) -> str: + """Initial setup and exploration""" + return ''' + # Initial setup and exploration + print("Starting BasicAgent exploration") + + # Get current position + position = get_position() + print(f"Starting position: {position}") + + # Explore the area + entities = get_entities() + print(f"Found {len(entities)} entities") + + # Look for resources + iron_pos = nearest(Resource.IRON_ORE) + copper_pos = nearest(Resource.COPPER_ORE) + coal_pos = nearest(Resource.COAL) + + print(f"Iron ore at: {iron_pos}") + print(f"Copper ore at: {copper_pos}") + print(f"Coal at: {coal_pos}") + ''' + + def _setup_mining(self) -> str: + """Set up mining operations""" + return ''' + # Set up mining operations + print("Setting up mining operations") + + # Find and place mining drills + iron_pos = nearest(Resource.IRON_ORE) + if iron_pos: + drill = place_entity( + entity=Prototype.MiningDrill, + position=iron_pos, + direction=Direction.NORTH + ) + print(f"Placed mining drill at {iron_pos}") + + # Add storage chest + chest = place_entity_next_to( + entity=Prototype.IronChest, + reference_position=drill.drop_position, + direction=Direction.SOUTH + ) + print(f"Placed chest at {chest.position}") + + # Check inventory + inventory = inspect_inventory() + print(f"Current inventory: {inventory}") + ''' + + def _monitor_and_optimize(self, entities: List, inventory: Dict) -> str: + """Monitor and optimize operations""" + return ''' + # Monitor and optimize operations + print("Monitoring operations") + + # Check all entities + entities = get_entities() + working_entities = [e for e in entities if hasattr(e, 'status') and e.status == EntityStatus.WORKING] + print(f"Working entities: {len(working_entities)}") + + # Check inventory + inventory = inspect_inventory() + total_items = sum(inventory.values()) + print(f"Total items in inventory: {total_items}") + + # Print detailed inventory + for item, count in inventory.items(): + if count > 0: + print(f" {item}: {count}") + + # Check for any issues + for entity in entities: + if hasattr(entity, 'status') and entity.status == EntityStatus.NO_POWER: + print(f"Entity {entity.name} needs power") + elif hasattr(entity, 'status') and entity.status == EntityStatus.NO_FUEL: + print(f"Entity {entity.name} needs fuel") + ''' + +Running the Agent +----------------- + +**Environment Setup** + .. code-block:: python + + import gym + from fle.agents.basic_agent import BasicAgent + + # Create environment + env = gym.make("iron_ore_throughput") + + # Create agent + agent = BasicAgent({}) + + # Run episode + obs = env.reset() + done = False + step = 0 + + while not done and step < 100: + action = agent.act(obs) + obs, reward, terminated, truncated, info = env.step(action) + done = terminated or truncated + step += 1 + print(f"Step {step}: Reward = {reward}") + + env.close() + +**Command Line Usage** + .. code-block:: bash + + # Run basic agent evaluation + fle eval --agent basic_agent --config configs/basic_agent_config.json + +Agent Configuration +------------------- + +**Basic Configuration** + .. code-block:: json + + { + "agent_type": "BasicAgent", + "config": { + "target_resources": ["iron-ore", "copper-ore", "coal"], + "max_mining_setups": 5, + "monitoring_interval": 10 + }, + "evaluation": { + "episodes": 5, + "max_steps": 1000, + "success_threshold": 0.5 + } + } + +**Advanced Configuration** + .. code-block:: json + + { + "agent_type": "BasicAgent", + "config": { + "target_resources": ["iron-ore", "copper-ore", "coal", "stone"], + "max_mining_setups": 10, + "monitoring_interval": 5, + "optimization_enabled": true, + "debug_mode": true + }, + "evaluation": { + "episodes": 10, + "max_steps": 2000, + "success_threshold": 0.8, + "metrics": ["throughput", "efficiency", "resource_utilization"] + } + } + +Agent Behavior +-------------- + +**Phase 1: Exploration (Steps 1-5)** + - Explore the starting area + - Identify available resources + - Plan mining operations + +**Phase 2: Setup (Steps 6-15)** + - Place mining drills on resource patches + - Create storage chests + - Set up basic automation + +**Phase 3: Monitoring (Steps 16+)** + - Monitor entity status + - Check inventory levels + - Optimize operations + +Example Output +-------------- + +**Step 1: Initial Setup** + .. code-block:: + + Starting BasicAgent exploration + Starting position: Position(x=0.0, y=0.0) + Found 0 entities + Iron ore at: Position(x=-28.0, y=-61.0) + Copper ore at: Position(x=45.0, y=-30.0) + Coal at: Position(x=-15.0, y=20.0) + +**Step 5: Mining Setup** + .. code-block:: + + Setting up mining operations + Placed mining drill at Position(x=-28.0, y=-61.0) + Placed chest at Position(x=-27.5, y=-59.5) + Current inventory: {'iron-ore': 0, 'coal': 4} + +**Step 20: Monitoring** + .. code-block:: + + Monitoring operations + Working entities: 1 + Total items in inventory: 75 + iron-ore: 75 + coal: 4 + +Performance Metrics +------------------- + +**Throughput** + - Items produced per minute + - Resource utilization efficiency + - Automation chain performance + +**Efficiency** + - Power consumption per item + - Entity utilization rate + - Resource waste minimization + +**Reliability** + - System uptime + - Error rate + - Recovery time + +Example Metrics +~~~~~~~~~~~~~~~ + +.. code-block:: python + + { + "throughput": { + "iron_ore": 2.5, # items per minute + "copper_ore": 1.8, + "coal": 3.2 + }, + "efficiency": { + "power_usage": 0.8, # normalized power usage + "entity_utilization": 0.75, # fraction of entities working + "resource_waste": 0.05 # fraction of resources wasted + }, + "reliability": { + "uptime": 0.95, # fraction of time system is working + "error_rate": 0.02, # errors per step + "recovery_time": 5.0 # average recovery time in steps + } + } + +Troubleshooting +--------------- + +**Common Issues** + - **No resources found**: Check map generation and resource placement + - **Mining drills not working**: Verify power and fuel supply + - **Inventory full**: Add more storage or optimize collection + +**Debug Mode** + Enable debug mode for detailed logging: + + .. code-block:: json + + { + "config": { + "debug_mode": true, + "log_level": "DEBUG" + } + } + +**Performance Issues** + - Monitor entity count and performance + - Check for resource bottlenecks + - Optimize automation chains + +Best Practices +-------------- + +1. **Start Simple**: Begin with basic operations +2. **Monitor Progress**: Track performance metrics +3. **Handle Errors**: Implement error recovery +4. **Optimize Gradually**: Improve efficiency over time +5. **Test Thoroughly**: Validate all scenarios +6. **Document Behavior**: Record agent decisions diff --git a/docs/sphinx/source/examples/multiagent.rst b/docs/sphinx/source/examples/multiagent.rst new file mode 100644 index 000000000..4d813e7dd --- /dev/null +++ b/docs/sphinx/source/examples/multiagent.rst @@ -0,0 +1,565 @@ +Multi-Agent Example +=================== + +This example demonstrates how to create and coordinate multiple agents in the Factorio Learning Environment. + +Multi-Agent Overview +------------------- + +Multi-agent systems in FLE enable: + +1. **Agent Coordination**: Multiple agents working together +2. **Task Distribution**: Dividing tasks among agents +3. **Communication**: Inter-agent message passing +4. **Collaborative Planning**: Joint decision making + +Agent Architecture +------------------ + +**Agent Roles** + - **Coordinator**: Manages overall strategy + - **Resource Specialist**: Handles resource collection + - **Construction Specialist**: Manages building operations + - **Research Specialist**: Handles technology advancement + +**Communication Protocol** + - Message passing between agents + - Shared state information + - Task assignment and reporting + - Conflict resolution + +Multi-Agent Implementation +------------------------- + +.. code-block:: python + + from fle.agents.agent_abc import Agent + from fle.env.gym_env.action import Action + from fle.env.game_types import Position, Direction + from typing import Dict, Any, List + import json + + class MultiAgentCoordinator(Agent): + def __init__(self, config: Dict[str, Any]): + super().__init__(config) + self.name = "MultiAgentCoordinator" + self.agent_count = config.get('agent_count', 3) + self.agents = self._initialize_agents(config) + self.shared_state = {} + self.task_queue = [] + self.step_count = 0 + + def _initialize_agents(self, config: Dict[str, Any]) -> List[Agent]: + """Initialize specialized agents""" + agents = [] + + # Resource specialist + agents.append(ResourceSpecialist({ + 'role': 'resource_specialist', + 'target_resources': ['iron-ore', 'copper-ore', 'coal'] + })) + + # Construction specialist + agents.append(ConstructionSpecialist({ + 'role': 'construction_specialist', + 'building_types': ['assembling-machine', 'furnace', 'lab'] + })) + + # Research specialist + agents.append(ResearchSpecialist({ + 'role': 'research_specialist', + 'research_priorities': ['automation', 'logistics', 'production'] + })) + + return agents + + def act(self, observation: Dict[str, Any]) -> Action: + """Coordinate multi-agent actions""" + self.step_count += 1 + + # Get messages from other agents + messages = observation.get('messages', []) + + # Process messages and update shared state + self._process_messages(messages) + + # Coordinate agent actions + if self.step_count == 1: + code = self._initial_coordination() + elif self.step_count <= 20: + code = self._task_distribution() + else: + code = self._monitoring_and_optimization() + + return Action( + agent_idx=0, + code=code, + game_state=None + ) + + def _process_messages(self, messages: List[Dict[str, Any]]): + """Process messages from other agents""" + for message in messages: + if message['type'] == 'task_completion': + self._handle_task_completion(message) + elif message['type'] == 'resource_request': + self._handle_resource_request(message) + elif message['type'] == 'coordination_request': + self._handle_coordination_request(message) + + def _initial_coordination(self) -> str: + """Initial coordination and planning""" + return ''' + # Initial multi-agent coordination + print("Starting multi-agent coordination") + + # Send initial messages to all agents + send_message({ + 'type': 'coordination_start', + 'content': 'Beginning multi-agent coordination', + 'target_agents': 'all' + }) + + # Analyze current state + entities = get_entities() + inventory = inspect_inventory() + + print(f"Current state: {len(entities)} entities, {sum(inventory.values())} items") + + # Plan initial tasks + tasks = [ + {'type': 'resource_collection', 'priority': 'high', 'agent': 'resource_specialist'}, + {'type': 'basic_setup', 'priority': 'medium', 'agent': 'construction_specialist'}, + {'type': 'research_planning', 'priority': 'low', 'agent': 'research_specialist'} + ] + + print(f"Planned tasks: {tasks}") + ''' + + def _task_distribution(self) -> str: + """Distribute tasks among agents""" + return ''' + # Task distribution and coordination + print("Distributing tasks among agents") + + # Check for available resources + iron_pos = nearest(Resource.IRON_ORE) + copper_pos = nearest(Resource.COPPER_ORE) + + if iron_pos: + # Assign resource collection task + send_message({ + 'type': 'task_assignment', + 'content': { + 'task': 'collect_iron_ore', + 'location': str(iron_pos), + 'priority': 'high' + }, + 'target_agents': ['resource_specialist'] + }) + + if copper_pos: + # Assign copper collection task + send_message({ + 'type': 'task_assignment', + 'content': { + 'task': 'collect_copper_ore', + 'location': str(copper_pos), + 'priority': 'medium' + }, + 'target_agents': ['resource_specialist'] + }) + + # Check construction needs + entities = get_entities() + if len(entities) < 5: + send_message({ + 'type': 'task_assignment', + 'content': { + 'task': 'build_infrastructure', + 'requirements': ['mining_drill', 'chest', 'furnace'], + 'priority': 'high' + }, + 'target_agents': ['construction_specialist'] + }) + ''' + + def _monitoring_and_optimization(self) -> str: + """Monitor and optimize multi-agent operations""" + return ''' + # Multi-agent monitoring and optimization + print("Monitoring multi-agent operations") + + # Check agent status + entities = get_entities() + inventory = inspect_inventory() + + print(f"Current state: {len(entities)} entities, {sum(inventory.values())} items") + + # Check for coordination issues + working_entities = [e for e in entities if hasattr(e, 'status') and e.status == EntityStatus.WORKING] + print(f"Working entities: {len(working_entities)}") + + # Send status updates + send_message({ + 'type': 'status_update', + 'content': { + 'entities': len(entities), + 'inventory': sum(inventory.values()), + 'working_entities': len(working_entities) + }, + 'target_agents': 'all' + }) + + # Check for optimization opportunities + if len(working_entities) < len(entities) * 0.8: + send_message({ + 'type': 'optimization_request', + 'content': 'System efficiency below 80%', + 'target_agents': 'all' + }) + ''' + +Specialized Agents +------------------ + +**Resource Specialist** + .. code-block:: python + + class ResourceSpecialist(Agent): + def __init__(self, config: Dict[str, Any]): + super().__init__(config) + self.name = "ResourceSpecialist" + self.target_resources = config.get('target_resources', []) + self.mining_setups = [] + + def act(self, observation: Dict[str, Any]) -> Action: + """Handle resource collection tasks""" + messages = observation.get('messages', []) + + # Process task assignments + for message in messages: + if message['type'] == 'task_assignment': + task = message['content'] + if task['task'].startswith('collect_'): + return self._handle_collection_task(task) + + # Default resource collection behavior + return self._default_resource_behavior() + + def _handle_collection_task(self, task: Dict[str, Any]) -> Action: + """Handle specific collection tasks""" + resource_type = task['task'].split('_')[1] + location = task.get('location') + + code = f''' + # Handle collection task: {task['task']} + print("Resource specialist handling collection task") + + # Find and collect {resource_type} + resource_pos = nearest(Resource.{resource_type.upper().replace('-', '_')}) + if resource_pos: + drill = place_entity( + entity=Prototype.MiningDrill, + position=resource_pos, + direction=Direction.NORTH + ) + print(f"Placed mining drill for {resource_type} at {resource_pos}") + + # Report task completion + send_message({{ + 'type': 'task_completion', + 'content': {{ + 'task': '{task['task']}', + 'status': 'completed', + 'location': str(resource_pos) + }}, + 'target_agents': ['coordinator'] + }}) + ''' + + return Action(agent_idx=1, code=code, game_state=None) + +**Construction Specialist** + .. code-block:: python + + class ConstructionSpecialist(Agent): + def __init__(self, config: Dict[str, Any]): + super().__init__(config) + self.name = "ConstructionSpecialist" + self.building_types = config.get('building_types', []) + self.construction_queue = [] + + def act(self, observation: Dict[str, Any]) -> Action: + """Handle construction tasks""" + messages = observation.get('messages', []) + + # Process construction requests + for message in messages: + if message['type'] == 'task_assignment': + task = message['content'] + if task['task'] == 'build_infrastructure': + return self._handle_infrastructure_task(task) + + # Default construction behavior + return self._default_construction_behavior() + + def _handle_infrastructure_task(self, task: Dict[str, Any]) -> Action: + """Handle infrastructure construction""" + requirements = task.get('requirements', []) + + code = f''' + # Handle infrastructure construction + print("Construction specialist building infrastructure") + + # Build required entities + entities = get_entities() + current_types = [e.name for e in entities] + + for requirement in {requirements}: + if requirement not in current_types: + # Build the required entity + if requirement == 'mining_drill': + resource_pos = nearest(Resource.IRON_ORE) + if resource_pos: + drill = place_entity( + entity=Prototype.MiningDrill, + position=resource_pos, + direction=Direction.NORTH + ) + print(f"Built {requirement} at {resource_pos}") + + elif requirement == 'chest': + # Place chest near existing entities + if entities: + reference = entities[0] + chest = place_entity_next_to( + entity=Prototype.IronChest, + reference_position=reference.position, + direction=Direction.SOUTH + ) + print(f"Built {requirement} at {chest.position}") + + # Report construction completion + send_message({{ + 'type': 'task_completion', + 'content': {{ + 'task': 'build_infrastructure', + 'status': 'completed', + 'entities_built': len(get_entities()) + }}, + 'target_agents': ['coordinator'] + }}) + ''' + + return Action(agent_idx=2, code=code, game_state=None) + +**Research Specialist** + .. code-block:: python + + class ResearchSpecialist(Agent): + def __init__(self, config: Dict[str, Any]): + super().__init__(config) + self.name = "ResearchSpecialist" + self.research_priorities = config.get('research_priorities', []) + self.research_queue = [] + + def act(self, observation: Dict[str, Any]) -> Action: + """Handle research tasks""" + messages = observation.get('messages', []) + + # Process research requests + for message in messages: + if message['type'] == 'task_assignment': + task = message['content'] + if task['task'] == 'research_planning': + return self._handle_research_planning(task) + + # Default research behavior + return self._default_research_behavior() + + def _handle_research_planning(self, task: Dict[str, Any]) -> Action: + """Handle research planning tasks""" + code = ''' + # Handle research planning + print("Research specialist planning research") + + # Check current research status + research = get_research_progress() + print(f"Current research: {research}") + + # Plan research priorities + priorities = ['automation', 'logistics', 'production'] + for priority in priorities: + if priority not in research.get('completed', []): + # Start research + result = set_research(priority) + if result: + print(f"Started research: {priority}") + break + + # Report research status + send_message({ + 'type': 'task_completion', + 'content': { + 'task': 'research_planning', + 'status': 'completed', + 'research_started': priority + }, + 'target_agents': ['coordinator'] + }) + ''' + + return Action(agent_idx=3, code=code, game_state=None) + +Running Multi-Agent Systems +--------------------------- + +**Environment Setup** + .. code-block:: python + + import gym + from fle.agents.multiagent_coordinator import MultiAgentCoordinator + + # Create environment + env = gym.make("iron_ore_throughput") + + # Create multi-agent coordinator + coordinator = MultiAgentCoordinator({ + 'agent_count': 3, + 'coordination_enabled': True, + 'communication_enabled': True + }) + + # Run episode + obs = env.reset() + done = False + step = 0 + + while not done and step < 100: + action = coordinator.act(obs) + obs, reward, terminated, truncated, info = env.step(action) + done = terminated or truncated + step += 1 + print(f"Step {step}: Reward = {reward}") + + env.close() + +**Command Line Usage** + .. code-block:: bash + + # Run multi-agent evaluation + fle eval --agent multiagent_coordinator --config configs/multiagent_config.json + +Multi-Agent Configuration +------------------------- + +**Basic Configuration** + .. code-block:: json + + { + "agent_type": "MultiAgentCoordinator", + "config": { + "agent_count": 3, + "coordination_enabled": true, + "communication_enabled": true, + "task_distribution": "round_robin" + }, + "evaluation": { + "episodes": 5, + "max_steps": 1000, + "success_threshold": 0.7 + } + } + +**Advanced Configuration** + .. code-block:: json + + { + "agent_type": "MultiAgentCoordinator", + "config": { + "agent_count": 5, + "coordination_enabled": true, + "communication_enabled": true, + "task_distribution": "priority_based", + "conflict_resolution": "voting", + "shared_state_size": 1000, + "message_timeout": 30 + }, + "evaluation": { + "episodes": 10, + "max_steps": 2000, + "success_threshold": 0.8, + "metrics": ["coordination_effectiveness", "communication_efficiency", "task_completion_rate"] + } + } + +Performance Metrics +------------------- + +**Coordination Effectiveness** + - Task completion rate + - Coordination efficiency + - Conflict resolution success + +**Communication Efficiency** + - Message delivery rate + - Communication latency + - Message processing time + +**Multi-Agent Performance** + - Overall system performance + - Agent specialization effectiveness + - Collaborative planning success + +Example Metrics +~~~~~~~~~~~~~~~ + +.. code-block:: python + + { + "coordination_effectiveness": { + "task_completion_rate": 0.85, # fraction of tasks completed + "coordination_efficiency": 0.75, # fraction of coordinated actions + "conflict_resolution_success": 0.90 # fraction of conflicts resolved + }, + "communication_efficiency": { + "message_delivery_rate": 0.95, # fraction of messages delivered + "communication_latency": 0.1, # average latency in seconds + "message_processing_time": 0.05 # average processing time in seconds + }, + "multi_agent_performance": { + "overall_system_performance": 0.80, # overall system effectiveness + "agent_specialization_effectiveness": 0.85, # effectiveness of specialization + "collaborative_planning_success": 0.70 # success rate of collaborative plans + } + } + +Troubleshooting +--------------- + +**Coordination Issues** + - **Task conflicts**: Implement conflict resolution + - **Communication failures**: Check message delivery + - **Coordination breakdown**: Monitor coordination effectiveness + +**Performance Issues** + - **Slow coordination**: Optimize coordination algorithms + - **High communication overhead**: Reduce message frequency + - **Memory issues**: Limit shared state size + +**Agent Issues** + - **Agent failures**: Implement agent recovery + - **Specialization problems**: Adjust agent roles + - **Communication errors**: Handle message errors + +Best Practices +-------------- + +1. **Clear Roles**: Define clear agent roles and responsibilities +2. **Effective Communication**: Implement efficient communication protocols +3. **Conflict Resolution**: Handle conflicts between agents +4. **Performance Monitoring**: Monitor multi-agent performance +5. **Scalability**: Design for different numbers of agents +6. **Error Handling**: Implement robust error recovery +7. **Testing**: Test multi-agent coordination thoroughly diff --git a/docs/sphinx/source/examples/visual_agent.rst b/docs/sphinx/source/examples/visual_agent.rst new file mode 100644 index 000000000..70cb5ae8b --- /dev/null +++ b/docs/sphinx/source/examples/visual_agent.rst @@ -0,0 +1,450 @@ +Visual Agent Example +==================== + +This example demonstrates how to create a visual agent that processes visual information from the game environment. + +Agent Overview +-------------- + +The visual agent uses computer vision techniques to: + +1. **Image Processing**: Analyze game screenshots and map images +2. **Object Detection**: Identify entities and resources in the visual data +3. **Spatial Reasoning**: Understand spatial relationships between objects +4. **Visual Planning**: Plan actions based on visual information + +Agent Implementation +-------------------- + +.. code-block:: python + + from fle.agents.agent_abc import Agent + from fle.env.gym_env.action import Action + from fle.env.game_types import Position, Direction + from typing import Dict, Any, List + import base64 + import io + from PIL import Image + import numpy as np + + class VisualAgent(Agent): + def __init__(self, config: Dict[str, Any]): + super().__init__(config) + self.name = "VisualAgent" + self.vision_enabled = config.get('vision_enabled', True) + self.image_processing = config.get('image_processing', True) + self.spatial_reasoning = config.get('spatial_reasoning', True) + self.visual_memory = {} + self.step_count = 0 + + def act(self, observation: Dict[str, Any]) -> Action: + """Generate action based on visual observation""" + self.step_count += 1 + + # Get visual information + map_image = observation.get('map_image', '') + entities = observation.get('entities', []) + inventory = observation.get('inventory', {}) + + # Process visual information + if self.vision_enabled and map_image: + visual_analysis = self._analyze_visual_data(map_image) + else: + visual_analysis = {} + + # Generate action based on visual analysis + if self.step_count == 1: + code = self._initial_visual_exploration(visual_analysis) + elif self.step_count <= 10: + code = self._visual_setup(visual_analysis, entities) + else: + code = self._visual_monitoring(visual_analysis, entities, inventory) + + return Action( + agent_idx=0, + code=code, + game_state=None + ) + + def _analyze_visual_data(self, map_image: str) -> Dict[str, Any]: + """Analyze visual data from map image""" + try: + # Decode base64 image + image_data = base64.b64decode(map_image) + image = Image.open(io.BytesIO(image_data)) + + # Convert to numpy array + img_array = np.array(image) + + # Perform visual analysis + analysis = { + 'image_size': image.size, + 'image_mode': image.mode, + 'dominant_colors': self._extract_dominant_colors(img_array), + 'entity_locations': self._detect_entities(img_array), + 'resource_patches': self._detect_resource_patches(img_array), + 'spatial_features': self._extract_spatial_features(img_array) + } + + return analysis + + except Exception as e: + print(f"Visual analysis error: {e}") + return {} + + def _extract_dominant_colors(self, img_array: np.ndarray) -> List[tuple]: + """Extract dominant colors from image""" + # Reshape image to 2D array of pixels + pixels = img_array.reshape(-1, img_array.shape[-1]) + + # Simple color extraction (in practice, use more sophisticated methods) + unique_colors = np.unique(pixels, axis=0) + return unique_colors[:10].tolist() # Return top 10 colors + + def _detect_entities(self, img_array: np.ndarray) -> List[Dict[str, Any]]: + """Detect entities in the image""" + # Simple entity detection (in practice, use computer vision models) + entities = [] + + # Look for specific color patterns that might indicate entities + # This is a simplified example + for y in range(0, img_array.shape[0], 10): + for x in range(0, img_array.shape[1], 10): + pixel = img_array[y, x] + if self._is_entity_pixel(pixel): + entities.append({ + 'position': (x, y), + 'type': self._classify_entity(pixel), + 'confidence': 0.8 + }) + + return entities + + def _detect_resource_patches(self, img_array: np.ndarray) -> List[Dict[str, Any]]: + """Detect resource patches in the image""" + resource_patches = [] + + # Look for resource-specific color patterns + for y in range(0, img_array.shape[0], 20): + for x in range(0, img_array.shape[1], 20): + region = img_array[y:y+20, x:x+20] + if self._is_resource_region(region): + resource_patches.append({ + 'position': (x, y), + 'type': self._classify_resource(region), + 'size': self._estimate_resource_size(region) + }) + + return resource_patches + + def _extract_spatial_features(self, img_array: np.ndarray) -> Dict[str, Any]: + """Extract spatial features from the image""" + return { + 'image_center': (img_array.shape[1] // 2, img_array.shape[0] // 2), + 'image_bounds': (0, 0, img_array.shape[1], img_array.shape[0]), + 'density_map': self._calculate_density_map(img_array), + 'connectivity': self._analyze_connectivity(img_array) + } + + def _initial_visual_exploration(self, visual_analysis: Dict[str, Any]) -> str: + """Initial visual exploration""" + return f''' + # Initial visual exploration + print("Starting VisualAgent exploration") + + # Analyze visual data + visual_analysis = {visual_analysis} + print(f"Visual analysis: {visual_analysis}") + + # Get current position + position = get_position() + print(f"Starting position: {{position}}") + + # Look for resources using visual analysis + if visual_analysis.get('resource_patches'): + for patch in visual_analysis['resource_patches']: + print(f"Found resource patch: {{patch['type']}} at {{patch['position']}}") + + # Look for entities using visual analysis + if visual_analysis.get('entity_locations'): + for entity in visual_analysis['entity_locations']: + print(f"Found entity: {{entity['type']}} at {{entity['position']}}") + ''' + + def _visual_setup(self, visual_analysis: Dict[str, Any], entities: List) -> str: + """Set up operations based on visual analysis""" + return ''' + # Visual-based setup + print("Setting up operations based on visual analysis") + + # Find resources using visual cues + iron_pos = nearest(Resource.IRON_ORE) + copper_pos = nearest(Resource.COPPER_ORE) + + if iron_pos: + # Place mining drill with visual guidance + drill = place_entity( + entity=Prototype.MiningDrill, + position=iron_pos, + direction=Direction.NORTH + ) + print(f"Placed mining drill at {iron_pos} based on visual analysis") + + # Add storage with visual positioning + chest = place_entity_next_to( + entity=Prototype.IronChest, + reference_position=drill.drop_position, + direction=Direction.SOUTH + ) + print(f"Placed chest at {chest.position}") + + # Check visual feedback + entities = get_entities() + print(f"Current entities: {len(entities)}") + ''' + + def _visual_monitoring(self, visual_analysis: Dict[str, Any], entities: List, inventory: Dict) -> str: + """Monitor operations using visual feedback""" + return ''' + # Visual monitoring + print("Monitoring operations with visual feedback") + + # Check entities + entities = get_entities() + working_entities = [e for e in entities if hasattr(e, 'status') and e.status == EntityStatus.WORKING] + print(f"Working entities: {len(working_entities)}") + + # Check inventory + inventory = inspect_inventory() + total_items = sum(inventory.values()) + print(f"Total items: {total_items}") + + # Visual analysis feedback + if visual_analysis: + print(f"Visual analysis: {visual_analysis}") + if 'spatial_features' in visual_analysis: + features = visual_analysis['spatial_features'] + print(f"Spatial features: {features}") + ''' + +Visual Processing Features +-------------------------- + +**Image Analysis** + - Dominant color extraction + - Entity detection and classification + - Resource patch identification + - Spatial feature extraction + +**Computer Vision Techniques** + - Edge detection + - Color segmentation + - Object recognition + - Spatial reasoning + +**Visual Memory** + - Store visual information across steps + - Track changes in visual data + - Maintain spatial maps + +Example Visual Analysis +----------------------- + +**Input Image** + Base64 encoded PNG image of the game map + +**Output Analysis** + .. code-block:: python + + { + 'image_size': (1024, 1024), + 'image_mode': 'RGB', + 'dominant_colors': [ + [0, 0, 0], # Black (background) + [139, 69, 19], # Brown (dirt) + [128, 128, 128], # Gray (stone) + [255, 215, 0] # Gold (resources) + ], + 'entity_locations': [ + { + 'position': (512, 256), + 'type': 'mining_drill', + 'confidence': 0.9 + }, + { + 'position': (520, 264), + 'type': 'chest', + 'confidence': 0.8 + } + ], + 'resource_patches': [ + { + 'position': (100, 200), + 'type': 'iron_ore', + 'size': 'large' + }, + { + 'position': (300, 400), + 'type': 'copper_ore', + 'size': 'medium' + } + ], + 'spatial_features': { + 'image_center': (512, 512), + 'image_bounds': (0, 0, 1024, 1024), + 'density_map': {...}, + 'connectivity': {...} + } + } + +Running the Visual Agent +----------------------- + +**Environment Setup** + .. code-block:: python + + import gym + from fle.agents.visual_agent import VisualAgent + + # Create environment + env = gym.make("iron_ore_throughput") + + # Create visual agent + agent = VisualAgent({ + 'vision_enabled': True, + 'image_processing': True, + 'spatial_reasoning': True + }) + + # Run episode + obs = env.reset() + done = False + step = 0 + + while not done and step < 100: + action = agent.act(obs) + obs, reward, terminated, truncated, info = env.step(action) + done = terminated or truncated + step += 1 + print(f"Step {step}: Reward = {reward}") + + env.close() + +**Command Line Usage** + .. code-block:: bash + + # Run visual agent evaluation + fle eval --agent visual_agent --config configs/visual_agent_config.json + +Agent Configuration +------------------- + +**Basic Configuration** + .. code-block:: json + + { + "agent_type": "VisualAgent", + "config": { + "vision_enabled": true, + "image_processing": true, + "spatial_reasoning": true, + "visual_memory_size": 100 + }, + "evaluation": { + "episodes": 5, + "max_steps": 1000, + "success_threshold": 0.6 + } + } + +**Advanced Configuration** + .. code-block:: json + + { + "agent_type": "VisualAgent", + "config": { + "vision_enabled": true, + "image_processing": true, + "spatial_reasoning": true, + "visual_memory_size": 1000, + "computer_vision_model": "resnet50", + "object_detection_threshold": 0.7, + "spatial_analysis_depth": 3 + }, + "evaluation": { + "episodes": 10, + "max_steps": 2000, + "success_threshold": 0.8, + "metrics": ["visual_accuracy", "spatial_reasoning", "object_detection"] + } + } + +Performance Metrics +------------------- + +**Visual Accuracy** + - Object detection accuracy + - Resource identification accuracy + - Spatial reasoning accuracy + +**Processing Performance** + - Image processing time + - Memory usage + - CPU utilization + +**Visual Reasoning** + - Spatial relationship understanding + - Object interaction prediction + - Visual planning effectiveness + +Example Metrics +~~~~~~~~~~~~~~~ + +.. code-block:: python + + { + "visual_accuracy": { + "object_detection": 0.85, # fraction of objects correctly identified + "resource_identification": 0.90, # fraction of resources correctly identified + "spatial_reasoning": 0.75 # fraction of spatial relationships correctly understood + }, + "processing_performance": { + "image_processing_time": 0.1, # seconds per image + "memory_usage": 512, # MB + "cpu_utilization": 0.3 # fraction of CPU used + }, + "visual_reasoning": { + "spatial_understanding": 0.80, # fraction of spatial relationships understood + "object_interaction_prediction": 0.70, # fraction of interactions correctly predicted + "visual_planning_effectiveness": 0.65 # fraction of visual plans that succeed + } + } + +Troubleshooting +--------------- + +**Visual Processing Issues** + - **Poor image quality**: Check image resolution and format + - **Detection failures**: Adjust detection thresholds + - **Memory issues**: Reduce visual memory size + +**Performance Issues** + - **Slow processing**: Optimize image processing algorithms + - **High memory usage**: Implement image compression + - **CPU bottlenecks**: Use parallel processing + +**Accuracy Issues** + - **False positives**: Adjust detection thresholds + - **Missed objects**: Improve detection algorithms + - **Spatial errors**: Enhance spatial reasoning + +Best Practices +-------------- + +1. **Image Quality**: Ensure high-quality input images +2. **Detection Thresholds**: Tune detection parameters +3. **Memory Management**: Monitor and optimize memory usage +4. **Performance Optimization**: Use efficient algorithms +5. **Error Handling**: Implement robust error recovery +6. **Visual Memory**: Maintain useful visual information +7. **Spatial Reasoning**: Develop strong spatial understanding diff --git a/docs/sphinx/source/getting_started/cluster.rst b/docs/sphinx/source/getting_started/cluster.rst new file mode 100644 index 000000000..b935eb8c1 --- /dev/null +++ b/docs/sphinx/source/getting_started/cluster.rst @@ -0,0 +1,91 @@ +Cluster Setup +============= + +FLE uses Docker to run Factorio servers in a cluster configuration. This allows for scalable evaluation of agents across multiple game instances. + +Starting a Cluster +----------------- + +.. code-block:: bash + + # Start Factorio cluster + fle cluster start + +This command will: + +- Start Docker containers running Factorio servers +- Configure networking between containers +- Set up the evaluation environment +- Create necessary directories and configurations + +Cluster Management +------------------ + +The cluster system provides several management commands: + +.. code-block:: bash + + # Check cluster status + fle cluster status + + # Stop the cluster + fle cluster stop + + # Restart the cluster + fle cluster restart + +Configuration +------------- + +Cluster configuration is managed through: + +- `.env` file: Environment variables for cluster setup +- `configs/` directory: Configuration files for different scenarios +- Docker Compose: Container orchestration + +The cluster automatically creates these files on first run. + +Scenarios +--------- + +FLE supports different game scenarios: + +- **Lab-play**: 24 structured tasks with fixed resources +- **Open-play**: An unbounded task of building the largest possible factory on a procedurally generated map + +Each scenario can be configured with different parameters: + +- Map generation settings +- Resource availability +- Technology research requirements +- Time limits and objectives + +Troubleshooting +-------------- + +**Docker Issues** + - Ensure your user has permission to run Docker without sudo + - Check that Docker is running: `docker ps` + - Verify available disk space and memory + +**Connection Issues** + - Make sure the Factorio server is running and ports are properly configured + - Check firewall settings for required ports + - Verify network connectivity between containers + +**Resource Issues** + - Monitor Docker resource usage: `docker stats` + - Adjust memory limits if needed + - Check available disk space for game saves + +Advanced Configuration +---------------------- + +For advanced users, you can customize: + +- Container resource limits +- Network configurations +- Volume mounts for persistent data +- Custom Factorio mods and scenarios + +See the :doc:`customization guide <../customization/tasks>` for more details. diff --git a/docs/sphinx/source/getting_started/installation.rst b/docs/sphinx/source/getting_started/installation.rst new file mode 100644 index 000000000..123d4df10 --- /dev/null +++ b/docs/sphinx/source/getting_started/installation.rst @@ -0,0 +1,98 @@ +Installation +============ + +Prerequisites +------------- + +- Docker +- Python 3.10+ +- `Factorio `_ (version 1.1.110), only for optional rendering + +Installation +------------ + +Core FLE SDK package: + +.. code-block:: bash + + pip install factorio-learning-environment + uv add factorio-learning-environment + +With optional features: + +.. code-block:: bash + + # For running experiments + pip install factorio-learning-environment[eval] + + # For MCP protocol support + pip install factorio-learning-environment[mcp] + + # For PostgreSQL support + pip install factorio-learning-environment[psql] + + # All features + pip install factorio-learning-environment[eval,mcp,psql] + +Using uv (recommended): + +.. code-block:: bash + + uv add factorio-learning-environment[eval] + +Client-side Setup (Optional) +---------------------------- + +For rendering graphics, set up the Factorio client: + +1. **Set up Factorio client**: + - Purchase Factorio from the `official website `_ (recommended) or on Steam. + - Downgrade to version 1.1.110: + - Steam: Right-click Factorio → Properties → Betas → Select 1.1.110 + - **Important**: Make sure to uncheck the Space Age DLC if you have it, as it forces the 2.x branch + +2. **Activate server**: + - Open Factorio client + - Navigate to _Multiplayer_ + - Connect to `localhost:34197` (default) or your configured address in Docker. + - Once connected, you can safely disconnect. This step confirms your Factorio license with the server. + +API Key Configuration +--------------------- + +FLE supports multiple LLM providers for agent evaluation. To get started with API keys: + +1. **Quick Setup** (Recommended): + .. code-block:: bash + + python fle/eval/infra/setup_api_keys.py + + This interactive script helps you: + - Configure API keys for OpenAI, Anthropic, and other providers + - Set up API key rotation for high-volume experiments + - Generate provider-specific configuration files + - Validate your API key setup + +2. **Manual Setup**: + Add your API keys to the `.env` file: + .. code-block:: bash + + # OpenAI + OPENAI_API_KEY=sk-... + + # Anthropic + ANTHROPIC_API_KEY=sk-ant-... + + # Additional providers as needed + +3. **Advanced Configuration**: + For large-scale experiments, you can set up API key rotation and provider-specific settings using the configuration files generated by `setup_api_keys.py`. + +Troubleshooting +--------------- + +- **"No valid programs found for version X"**: This is normal during initialization. The system will start generating programs shortly. +- **Database connection errors**: Verify your database configuration in the .env file and ensure the database exists. +- **API key errors**: Run `python fle/eval/infra/setup_api_keys.py` to verify your API key configuration. +- **Docker issues**: Ensure your user has permission to run Docker without sudo. +- **Connection issues**: Make sure the Factorio server is running and ports are properly configured. diff --git a/docs/sphinx/source/getting_started/quickstart.rst b/docs/sphinx/source/getting_started/quickstart.rst new file mode 100644 index 000000000..7d92a180a --- /dev/null +++ b/docs/sphinx/source/getting_started/quickstart.rst @@ -0,0 +1,102 @@ +Quickstart +========== + +Use the CLI: + +.. code-block:: bash + + # Start Factorio cluster + fle cluster start + + # Run evaluation trajectories (requires [eval] dependencies) + fle eval --config configs/gym_run_config.json + +.. note:: + When you run `fle init` or `fle eval` for the first time, an `.env` file and a `configs/` directory with example configurations are created automatically + +Environment Overview +-------------------- + +FLE is an agent evaluation environment built on the game of Factorio, a popular resource management simulation game. + +Agents interact with **FLE** by code synthesis through a **REPL** (Read-Eval-Print-Loop) pattern: + +1. **Observation**: The agent observes the world through the output streams (stderr/stdout) of their last program. +2. **Action**: The agent generates a Python program to perform their desired action. +3. **Feedback**: The environment executes the program, assigns variables, add classes/functions to the namespace, and provides an output stream. + +Example Interaction +------------------ + +.. code-block:: python + + # 1. Get iron patch and place mining drill + drill = place_entity( + entity=Prototype.MiningDrill, + position=nearest(Resource.IronOre), + direction=Direction.NORTH + ) + # 2. Add output storage + chest = place_entity_next_to( + entity=Prototype.IronChest, + reference_position=drill.drop_position, + direction=Direction.SOUTH + ) + # 3. Verify automation chain and observe entities + sleep(10) # Sleep for 10 seconds + assert drill.status == EntityStatus.WORKING + print(get_entities()) + +**Feedback:** + +.. code-block:: python + + >>> [ BurnerMiningDrill(fuel=Inventory({'coal': 4}), + >>> name='burner-mining-drill', + >>> direction=Direction.DOWN, + >>> position=Position(x=-28.0, y=-61.0), + >>> energy=2666.6666666667, + >>> tile_dimensions=TileDimensions(tile_width=2.0, tile_height=2.0), + >>> status=EntityStatus.WORKING, + >>> neighbours=[Entity(name='iron-chest', direction=DOWN, position=Position(x=-27.5 y=-59.5)], + >>> drop_position=Position(x=-27.5, y=-59.5), + >>> resources=[Ingredient(name='iron-ore', count=30000, type=None)]), + >>> Chest(name='iron-chest', + >>> direction=Direction.UP, + >>> position=Position(x=-27.5, y=-59.5), + >>> energy=0.0, + >>> tile_dimensions=TileDimensions(tile_width=1.0, tile_height=1.0), + >>> status=EntityStatus.NORMAL, + >>> inventory=Inventory({'iron-ore': 75}))] + +Key Concepts +------------ + +**Tools and Namespace** + Agents are provided with the Python standard library, and an API comprising :doc:`tools <../api/tools>` that they can use. + + Tools are functions that perform a game action and return a typed object (e.g an Inventory), which can be stored as a named **variable** in the Python namespace for later use. + + The namespace acts as an episodic symbolic memory system, and saved objects represent an observation of the environment at the moment of query. + + This enables agents to maintain complex state representations and build hierarchical abstractions as the factories scale. + +**Observation Streams** + Agents observe **stdout** and **stderr** - the output streams of their program. Agents may intentionally choose to print relevant objects and computations to the output stream to construct observations. + + Mistakes in the code or invalid operations raise typed **exceptions** with detailed context that is written to stderr. + + This enables agents to reactively debug their programs after execution, and proactively use runtime assertions during execution to self-verify their actions. + +**Code Enhancement** + Agents are able to enhance their internal representation of the game state by defining: + + 1. Utility functions for reuse throughout an episode, to encapsulate previously successful logic + 2. Classes in the namespace to better organize the data retrieved from the game. + +Next Steps +---------- + +- Learn about the :doc:`environment API <../api/environment>` +- Explore available :doc:`tools <../api/tools>` +- See :doc:`examples <../examples/basic_agent>` of agent implementations diff --git a/docs/sphinx/source/index.rst b/docs/sphinx/source/index.rst new file mode 100644 index 000000000..da4bfdd74 --- /dev/null +++ b/docs/sphinx/source/index.rst @@ -0,0 +1,52 @@ +Welcome to Factorio Learning Environment's documentation! +================================================================ + +An open source framework for developing and evaluating LLM agents in the game of Factorio. + +.. toctree:: + :maxdepth: 2 + :caption: Getting Started + + getting_started/installation + getting_started/quickstart + getting_started/cluster + +.. toctree:: + :maxdepth: 2 + :caption: API Reference + + api/environment + api/observation + api/action + api/tools + api/modules + +.. toctree:: + :maxdepth: 2 + :caption: Customization + + customization/tasks + customization/tools + customization/agents + customization/database + +.. toctree:: + :maxdepth: 2 + :caption: Examples + + examples/basic_agent + examples/visual_agent + examples/multiagent + +.. toctree:: + :maxdepth: 2 + :caption: Tools + + tools/index + +Indices and tables +================== + +* :ref:`genindex` +* :ref:`modindex` +* :ref:`search` diff --git a/docs/sphinx/source/tools/extract_item.rst b/docs/sphinx/source/tools/extract_item.rst new file mode 100644 index 000000000..9e5d0d21f --- /dev/null +++ b/docs/sphinx/source/tools/extract_item.rst @@ -0,0 +1,98 @@ +extract_item +============ + +Removes items from entity inventories. + +Overview +-------- + +The `extract_item` tool allows agents to remove items from entity inventories and transfer them to the player's inventory. + +Parameters +---------- + +**entity** (Entity) + The entity to extract items from. + +**item** (str) + The name of the item to extract. + +**count** (int, optional) + The number of items to extract. Defaults to 1. + +Returns +------- + +Dictionary containing: + +- **success** (bool): Whether the extraction succeeded +- **extracted_count** (int): Number of items actually extracted +- **entity** (Entity): The updated entity +- **error** (str): Error message (if failed) + +Examples +-------- + +**Basic Usage** + .. code-block:: python + + # Extract iron ore from a chest + result = extract_item( + entity=chest, + item='iron-ore', + count=10 + ) + + if result.get('success'): + print(f"Extracted {result.get('extracted_count')} iron ore") + else: + print(f"Error: {result.get('error')}") + +**Extract All Items** + .. code-block:: python + + # Extract all items from an entity + inventory = inspect_inventory(entity=chest) + for item, count in inventory.items(): + if count > 0: + result = extract_item( + entity=chest, + item=item, + count=count + ) + + if result.get('success'): + print(f"Extracted {result.get('extracted_count')} {item}") + +Best Practices +-------------- + +1. **Check Entity Contents**: Verify the entity has the items to extract +2. **Handle Partial Extractions**: Account for cases where not all items can be extracted +3. **Monitor Player Inventory**: Track player inventory changes +4. **Use Appropriate Counts**: Don't extract more items than available + +Failure Modes +------------- + +**Invalid Entity** + - **Error**: "Entity does not support item extraction" + - **Cause**: Entity type doesn't support inventory + - **Solution**: Check entity type before extraction + +**Item Not Available** + - **Error**: "Item not available in entity inventory" + - **Cause**: Entity doesn't have the required item + - **Solution**: Check entity inventory before extraction + +**Player Inventory Full** + - **Error**: "Player inventory is full" + - **Cause**: Player cannot accept more items + - **Solution**: Clear player inventory or use storage + +Related Tools +------------- + +- :doc:`inspect_inventory` - Check inventory contents +- :doc:`insert_item` - Add items to entities +- :doc:`get_entities` - Find entities with storage diff --git a/docs/sphinx/source/tools/index.rst b/docs/sphinx/source/tools/index.rst new file mode 100644 index 000000000..3d3e1edc0 --- /dev/null +++ b/docs/sphinx/source/tools/index.rst @@ -0,0 +1,209 @@ +Tools Documentation +=================== + +This section contains detailed documentation for all available tools in the Factorio Learning Environment. + +Tool Categories +--------------- + +**Inventory Management** + Tools for managing inventories and items + +**Entity Management** + Tools for placing, removing, and managing entities + +**Entity Queries** + Tools for finding and inspecting entities + +**Resource Management** + Tools for resource collection and management + +**Connection Management** + Tools for creating connections between entities + +**Crafting and Research** + Tools for crafting items and managing research + +**Movement and Control** + Tools for player movement and game control + +**Debugging and Output** + Tools for debugging and output + +Core Tools +---------- + +Inventory Management +~~~~~~~~~~~~~~~~~~~~ + +.. toctree:: + :maxdepth: 1 + + tools/inspect_inventory + tools/insert_item + tools/extract_item + +Entity Management +~~~~~~~~~~~~~~~~ + +.. toctree:: + :maxdepth: 1 + + tools/place_entity + tools/place_entity_next_to + tools/pickup_entity + tools/rotate_entity + +Entity Queries +~~~~~~~~~~~~~~ + +.. toctree:: + :maxdepth: 1 + + tools/get_entity + tools/get_entities + tools/nearest + tools/nearest_buildable + +Resource Management +~~~~~~~~~~~~~~~~~~~ + +.. toctree:: + :maxdepth: 1 + + tools/get_resource_patch + tools/harvest_resource + +Connection Management +~~~~~~~~~~~~~~~~~~~~ + +.. toctree:: + :maxdepth: 1 + + tools/connect_entities + tools/get_connection_amount + +Crafting and Research +~~~~~~~~~~~~~~~~~~~~~ + +.. toctree:: + :maxdepth: 1 + + tools/set_entity_recipe + tools/get_prototype_recipe + tools/craft_item + tools/set_research + tools/get_research_progress + +Movement and Control +~~~~~~~~~~~~~~~~~~~~ + +.. toctree:: + :maxdepth: 1 + + tools/move_to + tools/sleep + tools/launch_rocket + +Debugging and Output +~~~~~~~~~~~~~~~~~~~~ + +.. toctree:: + :maxdepth: 1 + + tools/print + +Tool Usage Patterns +------------------- + +**Basic Usage** + Most tools follow a simple pattern: + + .. code-block:: python + + # Get information + result = tool_name(parameters) + + # Check result + if result.get('success'): + # Use the result + data = result.get('data') + else: + # Handle error + error = result.get('error') + +**Error Handling** + All tools return structured results with error information: + + .. code-block:: python + + result = place_entity( + entity=Prototype.MiningDrill, + position=Position(10, 20), + direction=Direction.NORTH + ) + + if result.get('success'): + entity = result.get('entity') + print(f"Placed entity: {entity}") + else: + error = result.get('error') + print(f"Error: {error}") + +**Chaining Operations** + Tools can be chained together for complex operations: + + .. code-block:: python + + # Place a mining drill + drill = place_entity( + entity=Prototype.MiningDrill, + position=nearest(Resource.IronOre), + direction=Direction.NORTH + ) + + # Place a chest next to it + chest = place_entity_next_to( + entity=Prototype.IronChest, + reference_position=drill.drop_position, + direction=Direction.SOUTH + ) + + # Connect them + connect_entities(drill, chest) + +Best Practices +-------------- + +1. **Check Results**: Always check tool return values +2. **Handle Errors**: Implement proper error handling +3. **Use Type Hints**: Leverage type information for better code +4. **Chain Operations**: Combine tools for complex tasks +5. **Monitor Performance**: Track tool usage and performance +6. **Document Usage**: Document tool usage patterns +7. **Test Thoroughly**: Test all tool combinations + +Tool Development +---------------- + +**Creating Custom Tools** + See the :doc:`customization guide <../customization/tools>` for information on creating custom tools. + +**Tool Testing** + Test tools thoroughly with various scenarios: + + - Valid inputs + - Invalid inputs + - Edge cases + - Error conditions + - Performance scenarios + +**Tool Documentation** + Document tools with: + + - Clear descriptions + - Parameter specifications + - Return value documentation + - Usage examples + - Best practices + - Failure modes diff --git a/docs/sphinx/source/tools/insert_item.rst b/docs/sphinx/source/tools/insert_item.rst new file mode 100644 index 000000000..324873580 --- /dev/null +++ b/docs/sphinx/source/tools/insert_item.rst @@ -0,0 +1,101 @@ +insert_item +=========== + +Places items from player inventory into entities. + +Overview +-------- + +The `insert_item` tool allows agents to transfer items from their inventory into entity inventories such as chests, furnaces, and other storage containers. + +Parameters +---------- + +**entity** (Entity) + The entity to insert items into. + +**item** (str) + The name of the item to insert. + +**count** (int, optional) + The number of items to insert. Defaults to 1. + +Returns +------- + +Dictionary containing: + +- **success** (bool): Whether the insertion succeeded +- **inserted_count** (int): Number of items actually inserted +- **entity** (Entity): The updated entity +- **error** (str): Error message (if failed) + +Examples +-------- + +**Basic Usage** + .. code-block:: python + + # Insert iron ore into a chest + result = insert_item( + entity=chest, + item='iron-ore', + count=10 + ) + + if result.get('success'): + print(f"Inserted {result.get('inserted_count')} iron ore") + else: + print(f"Error: {result.get('error')}") + +**Insert Multiple Items** + .. code-block:: python + + # Insert different items into a furnace + items_to_insert = [ + {'item': 'iron-ore', 'count': 50}, + {'item': 'coal', 'count': 10} + ] + + for item_data in items_to_insert: + result = insert_item( + entity=furnace, + item=item_data['item'], + count=item_data['count'] + ) + + if result.get('success'): + print(f"Inserted {result.get('inserted_count')} {item_data['item']}") + +Best Practices +-------------- + +1. **Check Entity Type**: Ensure the entity supports item insertion +2. **Verify Item Compatibility**: Check that the item can be inserted into the entity +3. **Handle Partial Insertions**: Account for cases where not all items can be inserted +4. **Monitor Inventory**: Track inventory changes after insertion + +Failure Modes +------------- + +**Invalid Entity** + - **Error**: "Entity does not support item insertion" + - **Cause**: Entity type doesn't support inventory + - **Solution**: Check entity type before insertion + +**Item Not Available** + - **Error**: "Item not available in player inventory" + - **Cause**: Player doesn't have the required item + - **Solution**: Check player inventory before insertion + +**Entity Full** + - **Error**: "Entity inventory is full" + - **Cause**: Entity cannot accept more items + - **Solution**: Check entity capacity or use different entity + +Related Tools +------------- + +- :doc:`inspect_inventory` - Check inventory contents +- :doc:`extract_item` - Remove items from entities +- :doc:`get_entities` - Find entities with storage diff --git a/docs/sphinx/source/tools/inspect_inventory.rst b/docs/sphinx/source/tools/inspect_inventory.rst new file mode 100644 index 000000000..132a7cad0 --- /dev/null +++ b/docs/sphinx/source/tools/inspect_inventory.rst @@ -0,0 +1,153 @@ +inspect_inventory +================= + +Checks contents of player or entity inventories. + +Overview +-------- + +The `inspect_inventory` tool allows agents to examine the contents of inventories. It supports various inventory types including player inventories, chests, furnaces, and other entities with storage capabilities. + +Parameters +---------- + +**entity** (Entity, optional) + The entity whose inventory to inspect. If not provided, inspects the player's inventory. + +**inventory_type** (str, optional) + The type of inventory to inspect. Options: 'player', 'entity', 'all'. + +Returns +------- + +Dictionary containing: + +- **success** (bool): Whether the inspection succeeded +- **inventory** (Inventory): The inventory contents +- **entity** (Entity): The entity whose inventory was inspected (if applicable) +- **error** (str): Error message (if failed) + +Examples +-------- + +**Basic Usage** + .. code-block:: python + + # Inspect player inventory + result = inspect_inventory() + + if result.get('success'): + inventory = result.get('inventory') + print(f"Player inventory: {inventory}") + + # Check specific items + iron_ore = inventory.get('iron-ore', 0) + coal = inventory.get('coal', 0) + print(f"Iron ore: {iron_ore}, Coal: {coal}") + else: + print(f"Error: {result.get('error')}") + +**Entity Inventory** + .. code-block:: python + + # Inspect entity inventory + entities = get_entities() + for entity in entities: + if entity.name == 'iron-chest': + result = inspect_inventory(entity=entity) + + if result.get('success'): + inventory = result.get('inventory') + print(f"Chest inventory: {inventory}") + + # Check if chest is full + total_items = sum(inventory.values()) + if total_items > 0: + print(f"Chest contains {total_items} items") + break + +**Inventory Analysis** + .. code-block:: python + + # Analyze inventory contents + result = inspect_inventory() + + if result.get('success'): + inventory = result.get('inventory') + + # Count total items + total_items = sum(inventory.values()) + print(f"Total items: {total_items}") + + # List all items + for item, count in inventory.items(): + if count > 0: + print(f" {item}: {count}") + + # Check for specific resources + resources = ['iron-ore', 'copper-ore', 'coal', 'stone'] + for resource in resources: + count = inventory.get(resource, 0) + if count > 0: + print(f"Have {count} {resource}") + +**Inventory Filtering** + .. code-block:: python + + # Check for specific items + result = inspect_inventory() + + if result.get('success'): + inventory = result.get('inventory') + + # Check for mining equipment + mining_items = ['mining-drill', 'burner-mining-drill'] + for item in mining_items: + count = inventory.get(item, 0) + if count > 0: + print(f"Have {count} {item}") + + # Check for building materials + building_materials = ['iron-plate', 'copper-plate', 'stone'] + total_materials = sum(inventory.get(item, 0) for item in building_materials) + print(f"Total building materials: {total_materials}") + +Best Practices +-------------- + +1. **Check Success**: Always verify the inspection succeeded +2. **Handle Empty Inventories**: Account for empty inventories +3. **Use Inventory Methods**: Leverage inventory utility methods +4. **Monitor Changes**: Track inventory changes over time +5. **Error Handling**: Implement proper error handling + +Failure Modes +------------- + +**Invalid Entity** + - **Error**: "Entity does not have an inventory" + - **Cause**: Entity type doesn't support inventory + - **Solution**: Check entity type before inspection + +**Entity Not Found** + - **Error**: "Entity not found or no longer exists" + - **Cause**: Entity was removed or doesn't exist + - **Solution**: Verify entity exists before inspection + +**Permission Denied** + - **Error**: "Permission denied to inspect inventory" + - **Cause**: Insufficient permissions + - **Solution**: Check agent permissions + +**Network Error** + - **Error**: "Network error during inventory inspection" + - **Cause**: Communication failure with game server + - **Solution**: Retry the operation + +Related Tools +------------- + +- :doc:`insert_item` - Place items into inventories +- :doc:`extract_item` - Remove items from inventories +- :doc:`get_entities` - Find entities with inventories +- :doc:`place_entity` - Place entities with storage diff --git a/docs/sphinx/source/tools/place_entity.rst b/docs/sphinx/source/tools/place_entity.rst new file mode 100644 index 000000000..38162c9d1 --- /dev/null +++ b/docs/sphinx/source/tools/place_entity.rst @@ -0,0 +1,134 @@ +place_entity +============ + +Places entities in the world at specified positions. + +Overview +-------- + +The `place_entity` tool allows agents to place various entities in the game world. It handles placement validation, direction setting, and returns information about the placed entity. + +Parameters +---------- + +**entity** (Prototype) + The type of entity to place. Must be a valid Prototype enum value. + +**position** (Position) + The position where to place the entity. Must be a valid Position object. + +**direction** (Direction, optional) + The direction to orient the entity. Defaults to Direction.NORTH. + +Returns +------- + +Dictionary containing: + +- **success** (bool): Whether the placement succeeded +- **entity** (Entity): The placed entity object (if successful) +- **error** (str): Error message (if failed) + +Examples +-------- + +**Basic Usage** + .. code-block:: python + + # Place a mining drill + result = place_entity( + entity=Prototype.MiningDrill, + position=Position(10, 20), + direction=Direction.NORTH + ) + + if result.get('success'): + drill = result.get('entity') + print(f"Placed mining drill at {drill.position}") + else: + print(f"Error: {result.get('error')}") + +**With Resource Location** + .. code-block:: python + + # Find iron ore and place mining drill + iron_pos = nearest(Resource.IronOre) + if iron_pos: + result = place_entity( + entity=Prototype.MiningDrill, + position=iron_pos, + direction=Direction.NORTH + ) + + if result.get('success'): + drill = result.get('entity') + print(f"Placed mining drill on iron ore at {drill.position}") + +**Direction Examples** + .. code-block:: python + + # Place entities in different directions + drill_north = place_entity( + entity=Prototype.MiningDrill, + position=Position(0, 0), + direction=Direction.NORTH + ) + + drill_south = place_entity( + entity=Prototype.MiningDrill, + position=Position(10, 0), + direction=Direction.SOUTH + ) + + drill_east = place_entity( + entity=Prototype.MiningDrill, + position=Position(20, 0), + direction=Direction.EAST + ) + + drill_west = place_entity( + entity=Prototype.MiningDrill, + position=Position(30, 0), + direction=Direction.WEST + ) + +Best Practices +-------------- + +1. **Check Position Validity**: Ensure the position is valid for the entity type +2. **Handle Errors**: Always check the success flag and handle errors +3. **Use Appropriate Directions**: Choose directions that make sense for the entity +4. **Validate Resources**: Ensure required resources are available +5. **Monitor Placement**: Check that entities are placed correctly + +Failure Modes +------------- + +**Invalid Entity Type** + - **Error**: "Invalid entity type 'invalid'. Expected Prototype enum value." + - **Cause**: Using an invalid entity type + - **Solution**: Use valid Prototype enum values + +**Invalid Position** + - **Error**: "Position (x, y) is not valid for entity type" + - **Cause**: Position conflicts with existing entities or terrain + - **Solution**: Choose a different position or clear the area + +**Insufficient Resources** + - **Error**: "Insufficient resources to place entity" + - **Cause**: Not enough items in inventory + - **Solution**: Ensure required items are available + +**Invalid Direction** + - **Error**: "Invalid direction for entity type" + - **Cause**: Direction not supported by entity type + - **Solution**: Use supported directions for the entity + +Related Tools +------------- + +- :doc:`place_entity_next_to` - Place entities relative to others +- :doc:`pickup_entity` - Remove entities from the world +- :doc:`rotate_entity` - Change entity orientation +- :doc:`nearest` - Find nearest resources or entities +- :doc:`nearest_buildable` - Find valid building locations diff --git a/docs/versions/0.3.0.html b/docs/versions/0.3.0.html index 138fd6257..0dfbaa585 100644 --- a/docs/versions/0.3.0.html +++ b/docs/versions/0.3.0.html @@ -1849,6 +1849,35 @@

Horizon

+ +
+
+

Documentation

+ +

+ For comprehensive documentation, API reference, and guides, visit our Sphinx documentation: +

+ +
+ + + + + Full Documentation + +
+ +

+ The documentation includes: +

+
    +
  • Getting Started - Installation, quickstart, and cluster setup
    • +
  • API Reference - Complete API documentation for all modules
    • +
  • Examples - Basic, visual, and multi-agent examples
    • +
  • Customization - Creating custom tasks, tools, and agents
    • +
  • Tools - Detailed documentation for all available tools
    • +
+
diff --git a/pyproject.toml b/pyproject.toml index f8440f92d..4c17da8e4 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -44,6 +44,9 @@ dependencies = [ "a2a-sdk", # send_message tool + multiagent, "huggingface-hub>=0.35.3", "memoization>=0.4.0", + "sphinx>=8.1.3", + "sphinx-rtd-theme>=3.0.2", + "sphinx-autodoc-typehints>=3.0.1", ] [project.optional-dependencies] From abc66eb9babef8df174d1fc3cf695b063e6c70e1 Mon Sep 17 00:00:00 2001 From: Kian Kyars Date: Fri, 17 Oct 2025 11:07:04 -0600 Subject: [PATCH 2/9] add docs dev workflow --- .github/workflows/docs-dev.yml | 34 ++++++++++++++++++++++++++++++++++ .github/workflows/docs.yml | 31 ++++++++++--------------------- docs/sphinx/build.sh | 18 ------------------ 3 files changed, 44 insertions(+), 39 deletions(-) create mode 100644 .github/workflows/docs-dev.yml delete mode 100755 docs/sphinx/build.sh diff --git a/.github/workflows/docs-dev.yml b/.github/workflows/docs-dev.yml new file mode 100644 index 000000000..3e400a43a --- /dev/null +++ b/.github/workflows/docs-dev.yml @@ -0,0 +1,34 @@ +name: Dev Documentation Build + +on: + workflow_dispatch: + +jobs: + build-docs: + runs-on: ubuntu-latest + + steps: + - uses: actions/checkout@v4 + + - name: Set up Python + uses: actions/setup-python@v4 + with: + python-version: '3.10' + + - name: Install dependencies + run: | + python -m pip install --upgrade pip + pip install sphinx sphinx-rtd-theme sphinx-autodoc-typehints + pip install -e . + + - name: Build Sphinx documentation + run: | + cd docs/sphinx + sphinx-build -b html source build/html + + - name: Deploy to GitHub Pages + uses: peaceiris/actions-gh-pages@v3 + with: + github_token: ${{ secrets.GITHUB_TOKEN }} + publish_dir: ./docs/sphinx/build/html + destination_dir: docs/sphinx diff --git a/.github/workflows/docs.yml b/.github/workflows/docs.yml index 16d088271..4e58fdfd9 100644 --- a/.github/workflows/docs.yml +++ b/.github/workflows/docs.yml @@ -2,37 +2,26 @@ name: Build Documentation on: push: - branches: [ main, master ] - pull_request: - branches: [ main, master ] + branches: [ main] jobs: build-docs: runs-on: ubuntu-latest - steps: - - uses: actions/checkout@v4 - - - name: Set up Python - uses: actions/setup-python@v4 - with: - python-version: '3.10' - - - name: Install dependencies + - uses: actions/checkout@v4 + - uses: actions/setup-python@v5 + - name: Install dependencies run: | python -m pip install --upgrade pip pip install sphinx sphinx-rtd-theme sphinx-autodoc-typehints pip install -e . - - name: Build Sphinx documentation run: | cd docs/sphinx sphinx-build -b html source build/html - - - name: Deploy to GitHub Pages - if: github.ref == 'refs/heads/main' || github.ref == 'refs/heads/master' - uses: peaceiris/actions-gh-pages@v3 - with: - github_token: ${{ secrets.GITHUB_TOKEN }} - publish_dir: ./docs/sphinx/build/html - destination_dir: sphinx + - name: Deploy to GitHub Pages + uses: peaceiris/actions-gh-pages@v3 + with: + github_token: ${{ secrets.GITHUB_TOKEN }} + publish_dir: ./docs/sphinx/build/html + destination_dir: docs/sphinx diff --git a/docs/sphinx/build.sh b/docs/sphinx/build.sh deleted file mode 100755 index 7648d0269..000000000 --- a/docs/sphinx/build.sh +++ /dev/null @@ -1,18 +0,0 @@ -#!/bin/bash - -# Build Sphinx documentation -# This script builds the Sphinx documentation and outputs it to the build directory - -set -e - -echo "Building Sphinx documentation..." - -# Change to the docs/sphinx directory -cd "$(dirname "$0")" - -# Build the documentation -sphinx-build -b html source build/html - -echo "Documentation built successfully!" -echo "Output directory: $(pwd)/build/html" -echo "Open $(pwd)/build/html/index.html in your browser to view the documentation." From 7f05d1cc8c2230064bb083006142d162c6a778d9 Mon Sep 17 00:00:00 2001 From: Kian Kyars Date: Fri, 17 Oct 2025 11:11:40 -0600 Subject: [PATCH 3/9] change branch name for github actions --- .github/workflows/docs-dev.yml | 3 ++- .github/workflows/docs.yml | 2 +- 2 files changed, 3 insertions(+), 2 deletions(-) diff --git a/.github/workflows/docs-dev.yml b/.github/workflows/docs-dev.yml index 3e400a43a..2d99eda4f 100644 --- a/.github/workflows/docs-dev.yml +++ b/.github/workflows/docs-dev.yml @@ -1,7 +1,8 @@ name: Dev Documentation Build on: - workflow_dispatch: + push: + branches: [docs/sphinx-minedojo-style] jobs: build-docs: diff --git a/.github/workflows/docs.yml b/.github/workflows/docs.yml index 4e58fdfd9..04ddc5f72 100644 --- a/.github/workflows/docs.yml +++ b/.github/workflows/docs.yml @@ -2,7 +2,7 @@ name: Build Documentation on: push: - branches: [ main] + branches: [main] jobs: build-docs: From fc9087b63e3f82b4e7b66b8f305d33d94a1d2633 Mon Sep 17 00:00:00 2001 From: Kian Kyars Date: Mon, 3 Nov 2025 07:09:36 -0700 Subject: [PATCH 4/9] remove the unnecessary GitHub action workflows, modify the gitignore so that the HTML is committed to the branch and change the copyright year to be automatic. Finally Add the installation instructions to the installational RST --- .github/workflows/docs-dev.yml | 35 ------------------- .github/workflows/docs.yml | 27 -------------- .gitignore | 1 + docs/sphinx/source/conf.py | 3 +- .../source/getting_started/installation.rst | 17 +++++++++ 5 files changed, 20 insertions(+), 63 deletions(-) delete mode 100644 .github/workflows/docs-dev.yml delete mode 100644 .github/workflows/docs.yml diff --git a/.github/workflows/docs-dev.yml b/.github/workflows/docs-dev.yml deleted file mode 100644 index 2d99eda4f..000000000 --- a/.github/workflows/docs-dev.yml +++ /dev/null @@ -1,35 +0,0 @@ -name: Dev Documentation Build - -on: - push: - branches: [docs/sphinx-minedojo-style] - -jobs: - build-docs: - runs-on: ubuntu-latest - - steps: - - uses: actions/checkout@v4 - - - name: Set up Python - uses: actions/setup-python@v4 - with: - python-version: '3.10' - - - name: Install dependencies - run: | - python -m pip install --upgrade pip - pip install sphinx sphinx-rtd-theme sphinx-autodoc-typehints - pip install -e . - - - name: Build Sphinx documentation - run: | - cd docs/sphinx - sphinx-build -b html source build/html - - - name: Deploy to GitHub Pages - uses: peaceiris/actions-gh-pages@v3 - with: - github_token: ${{ secrets.GITHUB_TOKEN }} - publish_dir: ./docs/sphinx/build/html - destination_dir: docs/sphinx diff --git a/.github/workflows/docs.yml b/.github/workflows/docs.yml deleted file mode 100644 index 04ddc5f72..000000000 --- a/.github/workflows/docs.yml +++ /dev/null @@ -1,27 +0,0 @@ -name: Build Documentation - -on: - push: - branches: [main] - -jobs: - build-docs: - runs-on: ubuntu-latest - steps: - - uses: actions/checkout@v4 - - uses: actions/setup-python@v5 - - name: Install dependencies - run: | - python -m pip install --upgrade pip - pip install sphinx sphinx-rtd-theme sphinx-autodoc-typehints - pip install -e . - - name: Build Sphinx documentation - run: | - cd docs/sphinx - sphinx-build -b html source build/html - - name: Deploy to GitHub Pages - uses: peaceiris/actions-gh-pages@v3 - with: - github_token: ${{ secrets.GITHUB_TOKEN }} - publish_dir: ./docs/sphinx/build/html - destination_dir: docs/sphinx diff --git a/.gitignore b/.gitignore index 3de71a5f2..c03dfde51 100644 --- a/.gitignore +++ b/.gitignore @@ -23,6 +23,7 @@ uv.lock # Sphinx documentation build /docs/sphinx/build/ +!/docs/sphinx/build/html # Docker **/docker-compose.yml diff --git a/docs/sphinx/source/conf.py b/docs/sphinx/source/conf.py index 8c7bac524..c78bdff16 100644 --- a/docs/sphinx/source/conf.py +++ b/docs/sphinx/source/conf.py @@ -12,12 +12,13 @@ # import os import sys +from datetime import datetime sys.path.insert(0, os.path.abspath('../../..')) # -- Project information ----------------------------------------------------- project = 'Factorio Learning Environment' -copyright = '2024, FLE Team' +copyright = f"{datetime.now().year}, FLE Team" author = 'FLE Team' release = '0.3.0' diff --git a/docs/sphinx/source/getting_started/installation.rst b/docs/sphinx/source/getting_started/installation.rst index 123d4df10..d36603543 100644 --- a/docs/sphinx/source/getting_started/installation.rst +++ b/docs/sphinx/source/getting_started/installation.rst @@ -96,3 +96,20 @@ Troubleshooting - **API key errors**: Run `python fle/eval/infra/setup_api_keys.py` to verify your API key configuration. - **Docker issues**: Ensure your user has permission to run Docker without sudo. - **Connection issues**: Make sure the Factorio server is running and ports are properly configured. + +Building Documentation (Maintainers) +------------------------------------ + +Install Sphinx tooling: + +.. code-block:: bash + + pip install sphinx sphinx-rtd-theme sphinx-autodoc-typehints + +Build the HTML documentation: + +.. code-block:: bash + + cd factorio-learning-environment/docs/sphinx && python -m sphinx -b html source build/html + +The generated site will be in ``docs/sphinx/build/html``. From 0fba73317dccea1ae68ae025eff2c83b9a983b9a Mon Sep 17 00:00:00 2001 From: Kian Kyars Date: Mon, 3 Nov 2025 07:27:32 -0700 Subject: [PATCH 5/9] leaning out the readme --- README.md | 43 ++----------------------------------------- 1 file changed, 2 insertions(+), 41 deletions(-) diff --git a/README.md b/README.md index bca2970d7..b350faa98 100644 --- a/README.md +++ b/README.md @@ -1,6 +1,6 @@

Factorio Learning Environment

- Leaderboard | Paper | Website| Discord (#factorio-learning-env) + Leaderboard | Paper | Website | Documentation | Discord (#factorio-learning-env)

@@ -13,20 +13,9 @@ An open source framework for developing and evaluating LLM agents in the game of

Claude Opus 4.1 Plays Factorio

-## Why FLE? - -We provide two settings: - -1. **Lab-play**: 24 structured tasks with fixed resources. -2. **Open-play** An unbounded task of building the largest possible factory on a procedurally generated map. - -Our results demonstrate that models still lack strong spatial reasoning. In lab-play, we find that while LLMs -exhibit promising short-horizon skills, they are unable to operate effectively in constrained environments, reflecting limitations in error analysis. In open-play, while LLMs discover automation strategies that improve growth (e.g electric-powered drilling), they fail to achieve complex automation (e.g electronic-circuit manufacturing). - ## Quick Links - [Installation](#installation) -- [Documentation](https://jackhopkins.github.io/factorio-learning-environment/sphinx/build/html/) - [Examples](#examples) - [Contributing](#contributing) @@ -38,12 +27,11 @@ exhibit promising short-horizon skills, they are unable to operate effectively i - Python 3.10+ - [Factorio](https://www.factorio.com/) (version 1.1.110), only for optional rendering. -### Installation +### Package ```bash # Core FLE SDK package pip install factorio-learning-environment -uv add factorio-learning-environment # With optional features pip install factorio-learning-environment[eval] # For running experiments @@ -67,8 +55,6 @@ fle cluster start fle eval --config configs/gym_run_config.json ``` -> When you run `fle init` or `fle eval` for the first time, an `.env` file and a `configs/` directory with example configurations are created automatically - ## Environment FLE is an agent evaluation environment built on the game of Factorio, a popular resource management simulation game. @@ -79,31 +65,6 @@ Agents interact with **FLE** by code synthesis through a **REPL** (Read-Eval-Pri 2. **Action**: The agent generates a Python program to perform their desired action. 3. **Feedback**: The environment executes the program, assigns variables, add classes/functions to the namespace, and provides an output stream. -## Examples - -```python -# 1. Get iron patch and place mining drill -drill = place_entity( - entity=Prototype.MiningDrill, - position=nearest(Resource.IronOre), - direction=Direction.NORTH -) -# 2. Add output storage -chest = place_entity_next_to( - entity=Prototype.IronChest, - reference_position=drill.drop_position, - direction=Direction.SOUTH -) -# 3. Verify automation chain and observe entities -sleep(10) # Sleep for 10 seconds -assert drill.status == EntityStatus.WORKING -print(get_entities()) -``` - -## Documentation - -For complete documentation, visit: https://jackhopkins.github.io/factorio-learning-environment/sphinx/build/html/ - ## Contributing Join our team and contribute to one of the AI research community's most challenging problems - building open-ended / unsaturateable evals for post-AGI frontier models. If you want to contribute, please read [CONTRIBUTING.md](CONTRIBUTING.md) first. 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Core Tools

diff --git a/docs/sphinx/build/html/genindex.html b/docs/sphinx/build/html/genindex.html index c0a7f853e..a4870fa04 100644 --- a/docs/sphinx/build/html/genindex.html +++ b/docs/sphinx/build/html/genindex.html @@ -132,9 +132,11 @@

_

  • __getstate__() (fle.commons.models.SerializableFunction method)
    • -
  • __init__() (fle.commons.models.GameState method) +
  • __init__() (fle.agents.agent_abc.AgentABC method)
  • Conversation (class in fle.commons.models)
    • -
  • conversation (fle.commons.models.Program attribute) +
  • conversation (fle.agents.agent_abc.AgentABC attribute) + +
  • CopperCable (fle.env.game_types.Prototype attribute)
  • CopperOre (fle.env.game_types.Prototype attribute) @@ -417,6 +427,8 @@

    C

  • count (fle.env.entities.Ingredient attribute)
  • crafted (fle.commons.models.ProductionFlows attribute) +
    • +
  • create_default_agent_card() (in module fle.agents.agent_abc)
  • create_task() (fle.eval.tasks.TaskFactory static method)
    • @@ -450,20 +462,18 @@

    D

  • Direction (class in fle.env.entities)
    • -
  • direction (fle.env.entities.Entity attribute) +
  • direction (fle.env.entities.EntityCore attribute)
  • DirectionInternal (class in fle.env.instance)
    • - - + +
  • end() (fle.agents.agent_abc.AgentABC method) +
  • end_position (fle.env.entities.EntityInfo attribute)
    • @@ -695,6 +707,13 @@

    F

  • first_namespace (fle.env.instance.FactorioInstance property), [1]
  • + fle.agents.agent_abc + +
    • +
  • fle.agents.models
      @@ -736,6 +755,8 @@

      F

    • module
    • + +
    • fle.env.namespace @@ -743,8 +764,6 @@

      F

    • module
    - - diff --git a/docs/sphinx/build/html/getting_started/installation.html b/docs/sphinx/build/html/getting_started/installation.html index 729a57532..33a60265f 100644 --- a/docs/sphinx/build/html/getting_started/installation.html +++ b/docs/sphinx/build/html/getting_started/installation.html @@ -210,11 +210,6 @@

    Troubleshooting

    Building Documentation (Maintainers)

    -

    Install Sphinx tooling:

    -
    pip install sphinx sphinx-rtd-theme sphinx-autodoc-typehints
-
    -
    -

    Build the HTML documentation:

    cd docs/sphinx
 python3 -m sphinx -b html source build/html
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    fle + + +     + fle.agents.agent_abc +     diff --git a/docs/sphinx/build/html/searchindex.js b/docs/sphinx/build/html/searchindex.js index da8850866..823967056 100644 --- a/docs/sphinx/build/html/searchindex.js +++ b/docs/sphinx/build/html/searchindex.js @@ -1 +1 @@ -Search.setIndex({"alltitles": {"API Key Configuration": [[23, "api-key-configuration"]], "API Modules": [[2, null]], "API Reference": [[25, null]], "Action Components": [[0, "action-components"]], "Action Space": [[0, null]], "Action Space Definition": [[0, "action-space-definition"]], "Action Structure": [[0, "action-structure"]], "Action Validation": [[0, "action-validation"]], "Advanced Agent Features": [[15, "advanced-agent-features"]], "Advanced Configuration": [[22, "advanced-configuration"]], "Advanced Features": [[17, "advanced-features"], [18, "advanced-features"]], "Agent Architecture": [[15, "agent-architecture"], [20, "agent-architecture"]], "Agent Behavior": [[19, "agent-behavior"]], "Agent 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    diff --git a/docs/sphinx/build/html/api/environment.html b/docs/sphinx/build/html/api/environment.html index cef91db8a..d2a50b91f 100644 --- a/docs/sphinx/build/html/api/environment.html +++ b/docs/sphinx/build/html/api/environment.html @@ -133,7 +133,6 @@
  • Environment API
  • - View page source
    • diff --git a/docs/sphinx/build/html/api/modules.html b/docs/sphinx/build/html/api/modules.html index bc6673b67..377b4a12b 100644 --- a/docs/sphinx/build/html/api/modules.html +++ b/docs/sphinx/build/html/api/modules.html @@ -114,7 +114,6 @@
  • API Modules
  • - View page source
    • diff --git a/docs/sphinx/build/html/api/modules/fle.agents.agent_abc.html b/docs/sphinx/build/html/api/modules/fle.agents.agent_abc.html index c556251be..2751300ed 100644 --- a/docs/sphinx/build/html/api/modules/fle.agents.agent_abc.html +++ b/docs/sphinx/build/html/api/modules/fle.agents.agent_abc.html @@ -105,7 +105,6 @@
  • API Modules
  • fle.agents.agent_abc module
  • - View page source
    • diff --git a/docs/sphinx/build/html/api/modules/fle.agents.models.html b/docs/sphinx/build/html/api/modules/fle.agents.models.html index 576c6013c..dc11a5a3d 100644 --- a/docs/sphinx/build/html/api/modules/fle.agents.models.html +++ b/docs/sphinx/build/html/api/modules/fle.agents.models.html @@ -107,7 +107,6 @@
  • API Modules
  • fle.agents.models module
  • - View page source
    • diff --git a/docs/sphinx/build/html/api/modules/fle.commons.models.html b/docs/sphinx/build/html/api/modules/fle.commons.models.html index 112f23de5..237778b35 100644 --- a/docs/sphinx/build/html/api/modules/fle.commons.models.html +++ b/docs/sphinx/build/html/api/modules/fle.commons.models.html @@ -114,7 +114,6 @@
  • API Modules
  • fle.commons.models module
  • - View page source
    • diff --git a/docs/sphinx/build/html/api/modules/fle.env.entities.html b/docs/sphinx/build/html/api/modules/fle.env.entities.html index 958c6df37..e908e13f3 100644 --- a/docs/sphinx/build/html/api/modules/fle.env.entities.html +++ b/docs/sphinx/build/html/api/modules/fle.env.entities.html @@ -171,7 +171,6 @@
  • API Modules
  • fle.env.entities module
  • - View page source
    • diff --git a/docs/sphinx/build/html/api/modules/fle.env.game_types.html b/docs/sphinx/build/html/api/modules/fle.env.game_types.html index 420b94131..5fae930e0 100644 --- a/docs/sphinx/build/html/api/modules/fle.env.game_types.html +++ b/docs/sphinx/build/html/api/modules/fle.env.game_types.html @@ -112,7 +112,6 @@
  • API Modules
  • fle.env.game_types module
  • - View page source
    • diff --git a/docs/sphinx/build/html/api/modules/fle.env.gym_env.html b/docs/sphinx/build/html/api/modules/fle.env.gym_env.html index 1e58d667e..d7c086d67 100644 --- a/docs/sphinx/build/html/api/modules/fle.env.gym_env.html +++ b/docs/sphinx/build/html/api/modules/fle.env.gym_env.html @@ -104,7 +104,6 @@
  • API Modules
  • fle.env.gym_env module
  • - View page source
    • diff --git a/docs/sphinx/build/html/api/modules/fle.env.instance.html b/docs/sphinx/build/html/api/modules/fle.env.instance.html index 1c5dcddc4..b6804479c 100644 --- a/docs/sphinx/build/html/api/modules/fle.env.instance.html +++ b/docs/sphinx/build/html/api/modules/fle.env.instance.html @@ -109,7 +109,6 @@
  • API Modules
  • fle.env.instance module
  • - View page source
    • diff --git a/docs/sphinx/build/html/api/modules/fle.env.namespace.html b/docs/sphinx/build/html/api/modules/fle.env.namespace.html index d5654cf09..0d76f8255 100644 --- a/docs/sphinx/build/html/api/modules/fle.env.namespace.html +++ b/docs/sphinx/build/html/api/modules/fle.env.namespace.html @@ -110,7 +110,6 @@
  • API Modules
  • fle.env.namespace module
  • - View page source
    • diff --git a/docs/sphinx/build/html/api/modules/fle.eval.algorithms.html b/docs/sphinx/build/html/api/modules/fle.eval.algorithms.html index 96a651ca6..0a58376d9 100644 --- a/docs/sphinx/build/html/api/modules/fle.eval.algorithms.html +++ b/docs/sphinx/build/html/api/modules/fle.eval.algorithms.html @@ -101,7 +101,6 @@
  • API Modules
  • fle.eval.algorithms module
  • - View page source
    • diff --git a/docs/sphinx/build/html/api/modules/fle.eval.tasks.html b/docs/sphinx/build/html/api/modules/fle.eval.tasks.html index 268d121e7..40ae47f83 100644 --- a/docs/sphinx/build/html/api/modules/fle.eval.tasks.html +++ b/docs/sphinx/build/html/api/modules/fle.eval.tasks.html @@ -108,7 +108,6 @@
  • API Modules
  • fle.eval.tasks module
  • - View page source
    • @@ -170,7 +169,7 @@

    • score (float) – The current score/reward value

    • step (int) – The current step number

      • -

    • instance (FactorioInstance) – The Factorio game instance

      • +

    • instance (FactorioInstance) – The Factorio game instance

    • step_statistics (Dict) – Dictionary containing statistics about the current step

    @@ -226,7 +225,7 @@

    • score (float) – The current score/reward value

    • step (int) – The current step number

      • -

    • instance (FactorioInstance) – The Factorio game instance

      • +

    • instance (FactorioInstance) – The Factorio game instance

    • step_statistics (Dict) – Dictionary containing statistics about the current step

    @@ -265,7 +264,7 @@

    • score (float) – The current score/reward value

    • step (int) – The current step number

      • -

    • instance (FactorioInstance) – The Factorio game instance

      • +

    • instance (FactorioInstance) – The Factorio game instance

    • step_statistics (Dict) – Dictionary containing statistics about the current step

    @@ -315,7 +314,7 @@

    • score (float) – The current score/reward value

    • step (int) – The current step number

      • -

    • instance (FactorioInstance) – The Factorio game instance

      • +

    • instance (FactorioInstance) – The Factorio game instance

    • step_statistics (Dict) – Dictionary containing statistics about the current step

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  • Creating Custom Tools
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  • Basic Agent Example
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  • Visual Agent Example
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  • Cluster Setup
  • - View page source
    • diff --git a/docs/sphinx/build/html/getting_started/installation.html b/docs/sphinx/build/html/getting_started/installation.html index 33a60265f..18c1d3ff4 100644 --- a/docs/sphinx/build/html/getting_started/installation.html +++ b/docs/sphinx/build/html/getting_started/installation.html @@ -98,7 +98,6 @@
  • Installation
  • - View page source
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  • - View page source
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30], "troubleshoot": [16, 19, 20, 21, 22, 23], "type": [13, 15, 16, 17], "usag": [1, 16, 27], "valid": 0, "verif": 13, "visual": 21, "welcom": 25}}) \ No newline at end of file diff --git a/docs/sphinx/build/html/tools/extract_item.html b/docs/sphinx/build/html/tools/extract_item.html index 4fb0f7540..2aca8a078 100644 --- a/docs/sphinx/build/html/tools/extract_item.html +++ b/docs/sphinx/build/html/tools/extract_item.html @@ -88,7 +88,6 @@
  • extract_item
  • - View page source
    • diff --git a/docs/sphinx/build/html/tools/index.html b/docs/sphinx/build/html/tools/index.html index e9bfe3afe..f73c0e136 100644 --- a/docs/sphinx/build/html/tools/index.html +++ b/docs/sphinx/build/html/tools/index.html @@ -122,7 +122,6 @@
  • Tools Documentation
  • - View page source
    • diff --git a/docs/sphinx/build/html/tools/insert_item.html b/docs/sphinx/build/html/tools/insert_item.html index 2aff470d9..c26cb4e58 100644 --- a/docs/sphinx/build/html/tools/insert_item.html +++ b/docs/sphinx/build/html/tools/insert_item.html @@ -88,7 +88,6 @@
  • insert_item
  • - View page source
    • diff --git a/docs/sphinx/build/html/tools/inspect_inventory.html b/docs/sphinx/build/html/tools/inspect_inventory.html index 9be1700c9..1c1beaa48 100644 --- a/docs/sphinx/build/html/tools/inspect_inventory.html +++ b/docs/sphinx/build/html/tools/inspect_inventory.html @@ -88,7 +88,6 @@
  • inspect_inventory
  • - View page source
    • diff --git a/docs/sphinx/build/html/tools/place_entity.html b/docs/sphinx/build/html/tools/place_entity.html index e10d3bae0..6546eefb7 100644 --- a/docs/sphinx/build/html/tools/place_entity.html +++ b/docs/sphinx/build/html/tools/place_entity.html @@ -88,7 +88,6 @@
  • place_entity
  • - View page source
    • diff --git a/docs/sphinx/source/conf.py b/docs/sphinx/source/conf.py index c78bdff16..f920cea29 100644 --- a/docs/sphinx/source/conf.py +++ b/docs/sphinx/source/conf.py @@ -49,6 +49,9 @@ # a list of builtin themes. html_theme = 'sphinx_rtd_theme' +# Disable "View page source" links on all pages +html_show_sourcelink = False + # Add any paths that contain custom static files (such as style sheets) here, # relative to this directory. They are copied after the builtin static files, # so a file named "default.css" will overwrite the builtin "default.css". From 174fba00f506949f89ff2067c3dfa8c509966ab9 Mon Sep 17 00:00:00 2001 From: Kian Kyars Date: Sat, 22 Nov 2025 08:14:22 -0700 Subject: [PATCH 9/9] Commit claude code changes with cleaned up docs --- README.md | 3 + docs/sphinx/source/advanced/database.rst | 407 +++++++++++++ docs/sphinx/source/advanced/mcp.rst | 276 +++++++++ docs/sphinx/source/advanced/sprites.rst | 351 +++++++++++ docs/sphinx/source/api/action.rst | 251 -------- docs/sphinx/source/api/environment.rst | 128 ---- docs/sphinx/source/api/modules.rst | 42 -- .../api/modules/fle.agents.agent_abc.rst | 7 - .../source/api/modules/fle.agents.models.rst | 7 - .../source/api/modules/fle.commons.models.rst | 7 - .../source/api/modules/fle.env.entities.rst | 7 - .../source/api/modules/fle.env.game_types.rst | 7 - .../source/api/modules/fle.env.gym_env.rst | 7 - .../source/api/modules/fle.env.instance.rst | 7 - .../source/api/modules/fle.env.namespace.rst | 7 - .../api/modules/fle.eval.algorithms.rst | 7 - .../source/api/modules/fle.eval.tasks.rst | 7 - docs/sphinx/source/api/observation.rst | 178 ------ docs/sphinx/source/api/tools.rst | 252 -------- docs/sphinx/source/customization/agents.rst | 331 ---------- docs/sphinx/source/customization/database.rst | 357 ----------- docs/sphinx/source/customization/tasks.rst | 276 --------- docs/sphinx/source/customization/tools.rst | 335 ----------- .../source/environment/gym_registry.rst | 335 +++++++++++ docs/sphinx/source/environment/overview.rst | 240 ++++++++ docs/sphinx/source/examples/basic_agent.rst | 336 ----------- docs/sphinx/source/examples/multiagent.rst | 565 ------------------ docs/sphinx/source/examples/visual_agent.rst | 450 -------------- .../sphinx/source/getting_started/cluster.rst | 91 --- .../source/getting_started/installation.rst | 153 +++-- .../source/getting_started/quickstart.rst | 182 ++++-- .../getting_started/troubleshooting.rst | 214 +++++++ docs/sphinx/source/index.rst | 68 ++- docs/sphinx/source/project_structure.rst | 317 ++++++++++ docs/sphinx/source/tools/core_tools.rst | 563 +++++++++++++++++ docs/sphinx/source/tools/custom_tools.rst | 454 ++++++++++++++ docs/sphinx/source/tools/extract_item.rst | 98 --- docs/sphinx/source/tools/index.rst | 209 ------- docs/sphinx/source/tools/insert_item.rst | 101 ---- .../sphinx/source/tools/inspect_inventory.rst | 153 ----- docs/sphinx/source/tools/overview.rst | 189 ++++++ docs/sphinx/source/tools/place_entity.rst | 134 ----- pyproject.toml | 3 - 43 files changed, 3624 insertions(+), 4488 deletions(-) create mode 100644 docs/sphinx/source/advanced/database.rst create mode 100644 docs/sphinx/source/advanced/mcp.rst create mode 100644 docs/sphinx/source/advanced/sprites.rst delete mode 100644 docs/sphinx/source/api/action.rst delete mode 100644 docs/sphinx/source/api/environment.rst delete mode 100644 docs/sphinx/source/api/modules.rst delete mode 100644 docs/sphinx/source/api/modules/fle.agents.agent_abc.rst delete mode 100644 docs/sphinx/source/api/modules/fle.agents.models.rst delete mode 100644 docs/sphinx/source/api/modules/fle.commons.models.rst delete mode 100644 docs/sphinx/source/api/modules/fle.env.entities.rst delete mode 100644 docs/sphinx/source/api/modules/fle.env.game_types.rst delete mode 100644 docs/sphinx/source/api/modules/fle.env.gym_env.rst delete mode 100644 docs/sphinx/source/api/modules/fle.env.instance.rst delete mode 100644 docs/sphinx/source/api/modules/fle.env.namespace.rst delete mode 100644 docs/sphinx/source/api/modules/fle.eval.algorithms.rst delete mode 100644 docs/sphinx/source/api/modules/fle.eval.tasks.rst delete mode 100644 docs/sphinx/source/api/observation.rst delete mode 100644 docs/sphinx/source/api/tools.rst delete mode 100644 docs/sphinx/source/customization/agents.rst delete mode 100644 docs/sphinx/source/customization/database.rst delete mode 100644 docs/sphinx/source/customization/tasks.rst delete mode 100644 docs/sphinx/source/customization/tools.rst create mode 100644 docs/sphinx/source/environment/gym_registry.rst create mode 100644 docs/sphinx/source/environment/overview.rst delete mode 100644 docs/sphinx/source/examples/basic_agent.rst delete mode 100644 docs/sphinx/source/examples/multiagent.rst delete mode 100644 docs/sphinx/source/examples/visual_agent.rst delete mode 100644 docs/sphinx/source/getting_started/cluster.rst create mode 100644 docs/sphinx/source/getting_started/troubleshooting.rst create mode 100644 docs/sphinx/source/project_structure.rst create mode 100644 docs/sphinx/source/tools/core_tools.rst create mode 100644 docs/sphinx/source/tools/custom_tools.rst delete mode 100644 docs/sphinx/source/tools/extract_item.rst delete mode 100644 docs/sphinx/source/tools/index.rst delete mode 100644 docs/sphinx/source/tools/insert_item.rst delete mode 100644 docs/sphinx/source/tools/inspect_inventory.rst create mode 100644 docs/sphinx/source/tools/overview.rst delete mode 100644 docs/sphinx/source/tools/place_entity.rst diff --git a/README.md b/README.md index 153e7be4f..b73ead41c 100644 --- a/README.md +++ b/README.md @@ -46,6 +46,9 @@ uv sync Use the CLI: ```bash +# Activate venv +source .venv/bin/activate + # Start Factorio cluster fle cluster start diff --git a/docs/sphinx/source/advanced/database.rst b/docs/sphinx/source/advanced/database.rst new file mode 100644 index 000000000..600da6aa3 --- /dev/null +++ b/docs/sphinx/source/advanced/database.rst @@ -0,0 +1,407 @@ +Database Configuration +====================== + +FLE supports database checkpointing for long-running trajectories. The database stores agent outputs, environment feedback, game states, and histories of trajectories. + +Overview +-------- + +The database system enables: + +- **Checkpointing**: Save game state at every agent step +- **Resume Capability**: Continue trajectories from any checkpoint +- **Trajectory History**: Track complete agent interaction history +- **Analytics**: Analyze agent behavior across runs + +Supported Databases +------------------- + +FLE supports two database backends out of the box: + +1. **SQLite** (Default): File-based, zero-configuration +2. **PostgreSQL**: Client-server, better for concurrent access + +SQLite Configuration +-------------------- + +SQLite is the default database and requires minimal configuration. + +Setup +~~~~~ + +1. Set the database type in ``.env``: + + .. code-block:: bash + + FLE_DB_TYPE="sqlite" + +2. Configure the database file location: + + .. code-block:: bash + + SQLITE_DB_FILE=".fle/data.db" + +The SQLite file will be created automatically in the specified location if it doesn't exist. + +Benefits +~~~~~~~~ + +- **Zero Setup**: No server required +- **Portable**: Single file contains all data +- **Simple**: Easy to backup and share + +Limitations +~~~~~~~~~~~ + +- Not suitable for concurrent writes +- Limited scalability for very large datasets +- Single-threaded access + +PostgreSQL Configuration +------------------------ + +PostgreSQL provides better performance for large-scale experiments and concurrent access. + +Setup with Docker +~~~~~~~~~~~~~~~~~ + +The easiest way to set up PostgreSQL is using Docker: + +.. code-block:: bash + + docker run --name fle-postgres \ + -e POSTGRES_PASSWORD=fle123 \ + -e POSTGRES_USER=fle_user \ + -e POSTGRES_DB=fle_database \ + -p 5432:5432 \ + -d postgres:15 + +Environment Variables +~~~~~~~~~~~~~~~~~~~~~ + +Configure PostgreSQL in your ``.env`` file: + +.. code-block:: bash + + # Database Configuration - Set to postgres to use PostgreSQL + FLE_DB_TYPE="postgres" + + # PostgreSQL Configuration + SKILLS_DB_HOST=localhost + SKILLS_DB_PORT=5432 + SKILLS_DB_NAME=fle_database + SKILLS_DB_USER=fle_user + SKILLS_DB_PASSWORD=fle123 + +Manual PostgreSQL Setup +~~~~~~~~~~~~~~~~~~~~~~~~ + +If you prefer to install PostgreSQL manually: + +1. Install PostgreSQL 15+ +2. Create a database: + + .. code-block:: sql + + CREATE DATABASE fle_database; + CREATE USER fle_user WITH PASSWORD 'fle123'; + GRANT ALL PRIVILEGES ON DATABASE fle_database TO fle_user; + +3. Update ``.env`` with your connection details + +Benefits +~~~~~~~~ + +- **Concurrent Access**: Multiple processes can write simultaneously +- **Scalability**: Handles large datasets efficiently +- **Advanced Features**: Better query optimization, indexes, etc. + +Limitations +~~~~~~~~~~~ + +- Requires server setup and management +- More complex configuration +- Network dependency + +Database Schema +--------------- + +The FLE database stores: + +Trajectories +~~~~~~~~~~~~ + +- ``id``: Unique trajectory identifier +- ``task_id``: Associated task +- ``start_time``: When trajectory began +- ``end_time``: When trajectory completed +- ``status``: Current status (running, completed, failed) + +Steps +~~~~~ + +- ``id``: Unique step identifier +- ``trajectory_id``: Parent trajectory +- ``step_number``: Sequential step number +- ``agent_code``: Code executed by agent +- ``environment_feedback``: Response from environment +- ``game_state``: Serialized game state +- ``timestamp``: When step occurred + +Game States +~~~~~~~~~~~ + +- ``id``: Unique state identifier +- ``trajectory_id``: Associated trajectory +- ``step_id``: Associated step +- ``state_data``: Serialized game state +- ``timestamp``: When state was captured + +Using the Database +------------------ + +Accessing the Database +~~~~~~~~~~~~~~~~~~~~~~ + +.. code-block:: python + + from fle.commons.db_client import get_db_client + + # Get database client (auto-detects type from .env) + db = get_db_client() + + # Query trajectories + trajectories = db.get_all_trajectories() + + # Get specific trajectory + trajectory = db.get_trajectory(trajectory_id) + + # Get steps for a trajectory + steps = db.get_trajectory_steps(trajectory_id) + +Saving Checkpoints +~~~~~~~~~~~~~~~~~~ + +.. code-block:: python + + # Save a checkpoint + db.save_checkpoint( + trajectory_id=trajectory_id, + step_number=step_num, + agent_code=code, + environment_feedback=feedback, + game_state=state + ) + +Resuming from Checkpoint +~~~~~~~~~~~~~~~~~~~~~~~~~ + +.. code-block:: python + + # Load checkpoint + checkpoint = db.get_checkpoint(trajectory_id, step_number) + + # Resume environment from checkpoint + env.load_state(checkpoint['game_state']) + + # Continue execution + obs, reward, done, truncated, info = env.step(next_action) + +Database Client API +------------------- + +Core Methods +~~~~~~~~~~~~ + +.. code-block:: python + + # Create new trajectory + trajectory_id = db.create_trajectory(task_id, metadata) + + # Save step + db.save_step(trajectory_id, step_data) + + # Get trajectory + trajectory = db.get_trajectory(trajectory_id) + + # Get all trajectories for a task + trajectories = db.get_task_trajectories(task_id) + + # Delete trajectory + db.delete_trajectory(trajectory_id) + +Query Methods +~~~~~~~~~~~~~ + +.. code-block:: python + + # Get latest checkpoint + checkpoint = db.get_latest_checkpoint(trajectory_id) + + # Get checkpoint at specific step + checkpoint = db.get_checkpoint(trajectory_id, step_number) + + # Count steps in trajectory + count = db.count_steps(trajectory_id) + + # Check if trajectory exists + exists = db.trajectory_exists(trajectory_id) + +Migration +--------- + +Switching Databases +~~~~~~~~~~~~~~~~~~~ + +To migrate from SQLite to PostgreSQL: + +1. Export data from SQLite: + + .. code-block:: python + + from fle.commons.db_client import SQLiteClient + + sqlite_db = SQLiteClient(db_file='.fle/data.db') + trajectories = sqlite_db.export_all() + +2. Import into PostgreSQL: + + .. code-block:: python + + from fle.commons.db_client import PostgreSQLClient + + pg_db = PostgreSQLClient( + host='localhost', + port=5432, + database='fle_database', + user='fle_user', + password='fle123' + ) + pg_db.import_all(trajectories) + +3. Update ``.env`` to use PostgreSQL + +Backup and Restore +------------------ + +SQLite Backup +~~~~~~~~~~~~~ + +.. code-block:: bash + + # Simple file copy + cp .fle/data.db .fle/data.db.backup + + # Or use SQLite command + sqlite3 .fle/data.db ".backup '.fle/data.db.backup'" + +PostgreSQL Backup +~~~~~~~~~~~~~~~~~ + +.. code-block:: bash + + # Dump database + pg_dump -h localhost -U fle_user fle_database > backup.sql + + # Restore database + psql -h localhost -U fle_user fle_database < backup.sql + +Performance Optimization +------------------------ + +SQLite Optimization +~~~~~~~~~~~~~~~~~~~ + +.. code-block:: python + + # Use WAL mode for better concurrency + db.execute("PRAGMA journal_mode=WAL") + + # Increase cache size + db.execute("PRAGMA cache_size=-64000") # 64MB + +PostgreSQL Optimization +~~~~~~~~~~~~~~~~~~~~~~~ + +.. code-block:: sql + + -- Create indexes for common queries + CREATE INDEX idx_trajectory_task ON trajectories(task_id); + CREATE INDEX idx_step_trajectory ON steps(trajectory_id); + CREATE INDEX idx_step_timestamp ON steps(timestamp); + + -- Analyze tables + ANALYZE trajectories; + ANALYZE steps; + +Troubleshooting +--------------- + +Connection Errors +~~~~~~~~~~~~~~~~~ + +**SQLite**: + +- Verify file path exists and is writable +- Check file permissions +- Ensure parent directory exists + +**PostgreSQL**: + +- Verify server is running: ``docker ps`` or ``systemctl status postgresql`` +- Check connection details in ``.env`` +- Test connection: ``psql -h localhost -U fle_user fle_database`` + +Performance Issues +~~~~~~~~~~~~~~~~~~ + +**SQLite**: + +- Enable WAL mode +- Increase cache size +- Consider switching to PostgreSQL for large datasets + +**PostgreSQL**: + +- Add indexes on frequently queried columns +- Tune PostgreSQL configuration (``postgresql.conf``) +- Monitor query performance with ``EXPLAIN ANALYZE`` + +Disk Space +~~~~~~~~~~ + +**SQLite**: + +.. code-block:: bash + + # Check database size + du -h .fle/data.db + + # Vacuum to reclaim space + sqlite3 .fle/data.db "VACUUM;" + +**PostgreSQL**: + +.. code-block:: sql + + -- Check database size + SELECT pg_size_pretty(pg_database_size('fle_database')); + + -- Vacuum to reclaim space + VACUUM ANALYZE; + +Best Practices +-------------- + +1. **Regular Backups**: Back up your database regularly, especially before major experiments +2. **Use PostgreSQL for Large Runs**: For experiments with >1000 steps, use PostgreSQL +3. **Clean Up Old Data**: Periodically remove old trajectories you no longer need +4. **Monitor Disk Space**: Keep an eye on database size, especially with SQLite +5. **Use Transactions**: Batch multiple operations in transactions for better performance + +Next Steps +---------- + +- Review :doc:`../getting_started/quickstart` for basic usage +- See :doc:`../environment/overview` for environment context +- Check :doc:`../getting_started/troubleshooting` for common issues diff --git a/docs/sphinx/source/advanced/mcp.rst b/docs/sphinx/source/advanced/mcp.rst new file mode 100644 index 000000000..2f2fc935f --- /dev/null +++ b/docs/sphinx/source/advanced/mcp.rst @@ -0,0 +1,276 @@ +Model Context Protocol (MCP) +============================ + +FLE supports the `Model Context Protocol `_ (MCP) to enable LLM reasoning models to invoke tools directly. + +Overview +-------- + +The Model Context Protocol is a standardized interface that allows AI models to interact with external tools and services. FLE's MCP integration enables: + +- Direct tool invocation from LLM reasoning models +- Standardized request/response formats +- Seamless integration with MCP-compatible clients + +What is MCP? +------------ + +MCP provides a universal interface for: + +1. **Tool Discovery**: Models can discover available tools and their capabilities +2. **Tool Invocation**: Models can call tools with structured parameters +3. **Result Handling**: Models receive typed responses from tool calls + +Benefits +-------- + +Using MCP with FLE provides: + +- **Standardization**: Works with any MCP-compatible client +- **Type Safety**: Structured tool definitions with parameter types +- **Extensibility**: Easy to add new tools to the MCP interface +- **Interoperability**: Compatible with the broader MCP ecosystem + +Installation +------------ + +To use MCP features, install FLE with MCP support: + +.. code-block:: bash + + pip install factorio-learning-environment[mcp] + + # Or with uv + uv add factorio-learning-environment[mcp] + +Configuration +------------- + +MCP configuration is located in ``fle/env/protocols/_mcp/``. The MCP server automatically exposes all agent-accessible tools. + +Using MCP +--------- + +Starting the MCP Server +~~~~~~~~~~~~~~~~~~~~~~~ + +The MCP server can be started alongside the FLE environment: + +.. code-block:: python + + from fle.env.protocols.mcp import MCPServer + + # Initialize MCP server + server = MCPServer() + server.start() + +Tool Discovery +~~~~~~~~~~~~~~ + +MCP clients can discover available tools: + +.. code-block:: python + + # List all available tools + tools = server.list_tools() + + for tool in tools: + print(f"Tool: {tool.name}") + print(f"Description: {tool.description}") + print(f"Parameters: {tool.parameters}") + +Invoking Tools +~~~~~~~~~~~~~~ + +Tools can be invoked through the MCP interface: + +.. code-block:: python + + # Invoke a tool + result = server.invoke_tool( + tool_name="place_entity", + parameters={ + "entity": "burner-mining-drill", + "position": {"x": 10, "y": 20}, + "direction": "north" + } + ) + + print(f"Result: {result}") + +Integration with LLM Clients +----------------------------- + +MCP-Compatible Clients +~~~~~~~~~~~~~~~~~~~~~~ + +FLE's MCP implementation works with: + +- Claude Desktop +- Other MCP-compatible AI assistants +- Custom MCP clients + +Example Integration +~~~~~~~~~~~~~~~~~~~ + +Here's how to integrate FLE with an MCP-compatible client: + +.. code-block:: json + + { + "mcpServers": { + "factorio": { + "command": "python", + "args": ["-m", "fle.env.protocols.mcp.server"], + "env": { + "FLE_CLUSTER_HOST": "localhost", + "FLE_CLUSTER_PORT": "34197" + } + } + } + } + +Tool Definitions +---------------- + +MCP tools are automatically generated from FLE's tool definitions. Each tool includes: + +- **Name**: The tool identifier +- **Description**: What the tool does (from ``agent.md``) +- **Parameters**: Typed parameter schema +- **Return Type**: Expected response format + +Example Tool Definition +~~~~~~~~~~~~~~~~~~~~~~~ + +.. code-block:: json + + { + "name": "place_entity", + "description": "Places an entity in the world at a specified position", + "parameters": { + "type": "object", + "properties": { + "entity": { + "type": "string", + "description": "The entity prototype to place" + }, + "position": { + "type": "object", + "properties": { + "x": {"type": "number"}, + "y": {"type": "number"} + } + }, + "direction": { + "type": "string", + "enum": ["north", "south", "east", "west"] + } + }, + "required": ["entity", "position"] + } + } + +Advanced Usage +-------------- + +Custom MCP Tools +~~~~~~~~~~~~~~~~ + +You can create custom MCP-specific tools by following the :doc:`../tools/custom_tools` guide. Tools created this way are automatically exposed via MCP. + +Error Handling +~~~~~~~~~~~~~~ + +MCP calls return structured errors: + +.. code-block:: json + + { + "error": { + "code": "InvalidParameters", + "message": "Entity 'invalid-entity' not found", + "details": { + "entity": "invalid-entity", + "available_entities": ["burner-mining-drill", "iron-chest", ...] + } + } + } + +State Management +~~~~~~~~~~~~~~~~ + +MCP maintains state between tool calls: + +- Variables persist in the namespace +- Entities remain referenced across calls +- Game state is preserved + +Architecture +------------ + +.. code-block:: text + + ┌─────────────────────┐ + │ MCP Client │ + │ (Claude, etc.) │ + └──────────┬──────────┘ + │ + │ MCP Protocol + │ + ┌──────────▼──────────┐ + │ MCP Server │ + │ (FLE Protocol) │ + └──────────┬──────────┘ + │ + │ Tool Calls + │ + ┌──────────▼──────────┐ + │ FLE Environment │ + │ (Game Instance) │ + └─────────────────────┘ + +Documentation +------------- + +For detailed MCP documentation, see: + +- `Official MCP Documentation `_ +- ``fle/env/protocols/_mcp/README.md`` in the repository + +Troubleshooting +--------------- + +Connection Issues +~~~~~~~~~~~~~~~~~ + +If MCP clients can't connect: + +1. Verify the MCP server is running +2. Check port configuration +3. Ensure Factorio cluster is started + +Tool Not Found +~~~~~~~~~~~~~~ + +If a tool is not available via MCP: + +1. Verify the tool exists in ``fle/env/tools/agent/`` +2. Check that the tool has all required files (``client.py``, ``server.lua``, ``agent.md``) +3. Restart the MCP server + +Invalid Parameters +~~~~~~~~~~~~~~~~~~ + +If tool calls fail with parameter errors: + +1. Check the tool's parameter schema +2. Verify parameter types match the schema +3. Ensure required parameters are provided + +Next Steps +---------- + +- Review :doc:`../tools/overview` to understand available tools +- See :doc:`../tools/custom_tools` to create MCP-compatible tools +- Check the official MCP documentation for client integration diff --git a/docs/sphinx/source/advanced/sprites.rst b/docs/sphinx/source/advanced/sprites.rst new file mode 100644 index 000000000..2d26bffda --- /dev/null +++ b/docs/sphinx/source/advanced/sprites.rst @@ -0,0 +1,351 @@ +Sprites +======= + +FLE includes sprite management functionality for downloading spritemaps, extracting individual entity sprites, icons, and other visual assets from HuggingFace for use in visual reasoning tasks. + +Overview +-------- + +The sprite system provides: + +- **Sprite Downloads**: Automatic downloading of Factorio sprite assets +- **Extraction**: Processing spritemaps into individual entity sprites +- **Icons**: Entity and item icons for visual identification +- **Visual Reasoning**: Support for vision-enabled agents + +Why Use Sprites? +---------------- + +Sprites enable visual reasoning capabilities for agents: + +1. **Visual Observations**: Agents can see the game state as images +2. **Entity Recognition**: Identify entities by their visual appearance +3. **Spatial Reasoning**: Understand layouts and positioning visually +4. **Multimodal Learning**: Combine text and visual information + +Installation +------------ + +Sprites are automatically downloaded when needed, but you can pre-download them: + +.. code-block:: bash + + # Download and generate sprites + fle sprites + + # Force re-download even if sprites exist + fle sprites --force + + # Use custom directories and worker count + fle sprites --spritemap-dir .fle/spritemaps --sprite-dir .fle/sprites --workers 5 + +Default Locations +----------------- + +By default, sprites are stored in: + +- **Spritemaps**: ``.fle/spritemaps/`` - Raw spritemap files from HuggingFace +- **Sprites**: ``.fle/sprites/`` - Extracted individual entity/item sprites + +You can customize these locations using command-line arguments. + +CLI Usage +--------- + +Basic Command +~~~~~~~~~~~~~ + +.. code-block:: bash + + # Download and extract sprites + fle sprites + +Options +~~~~~~~ + +.. code-block:: bash + + # Force re-download + fle sprites --force + + # Custom directories + fle sprites --spritemap-dir /path/to/spritemaps --sprite-dir /path/to/sprites + + # Parallel processing (default: 4 workers) + fle sprites --workers 8 + +Programmatic Usage +------------------ + +Loading Sprites +~~~~~~~~~~~~~~~ + +.. code-block:: python + + from fle.env.sprites import SpriteManager + + # Initialize sprite manager + sprite_manager = SpriteManager() + + # Get sprite for an entity + sprite = sprite_manager.get_sprite('burner-mining-drill') + + # Get icon for an item + icon = sprite_manager.get_icon('iron-plate') + + # Get all available sprites + available = sprite_manager.list_sprites() + +Using Sprites with Agents +~~~~~~~~~~~~~~~~~~~~~~~~~~ + +.. code-block:: python + + from fle.agents import VisualAgent + import gym + + # Create environment with visual observations + env = gym.make("iron_ore_throughput") + + # Create visual agent + agent = VisualAgent( + sprite_manager=SpriteManager(), + model="gpt-4-vision" + ) + + # Agent can now use visual information + obs = env.reset() + action = agent.get_action(obs, include_visual=True) + +Visual Observations +------------------- + +Visual observations include: + +- **Map Image**: Base64 encoded PNG of the game map +- **Entity Sprites**: Individual entity appearances +- **Overlays**: Visual indicators for status, connections, etc. + +Example observation with visuals: + +.. code-block:: python + + { + 'raw_text': '...', + 'entities': [...], + 'map_image': 'data:image/png;base64,...', + 'sprites': { + 'burner-mining-drill': 'data:image/png;base64,...', + 'iron-chest': 'data:image/png;base64,...' + } + } + +Sprite Categories +----------------- + +Entity Sprites +~~~~~~~~~~~~~~ + +Visual representations of game entities: + +- Mining drills +- Furnaces +- Assembling machines +- Inserters +- Transport belts +- Pipes +- Power poles + +Item Icons +~~~~~~~~~~ + +Icons for items and resources: + +- Raw materials (ore, wood, stone) +- Plates (iron, copper, steel) +- Intermediate products +- Science packs +- Modules + +Performance Considerations +-------------------------- + +Sprite Loading +~~~~~~~~~~~~~~ + +- Sprites are loaded on-demand by default +- Pre-loading all sprites increases memory usage but improves performance +- Use worker processes for faster initial extraction + +Caching +~~~~~~~ + +- Extracted sprites are cached on disk +- Subsequent loads are much faster +- Clear cache with ``fle sprites --force`` + +Resolution +~~~~~~~~~~ + +Sprites are provided at their native resolution. You can resize them as needed: + +.. code-block:: python + + from PIL import Image + import base64 + from io import BytesIO + + # Decode base64 sprite + sprite_data = base64.b64decode(sprite_base64) + image = Image.open(BytesIO(sprite_data)) + + # Resize + resized = image.resize((32, 32)) + +Advanced Usage +-------------- + +Custom Sprite Sources +~~~~~~~~~~~~~~~~~~~~~ + +You can provide custom sprite sources: + +.. code-block:: python + + sprite_manager = SpriteManager( + spritemap_dir='/custom/path/spritemaps', + sprite_dir='/custom/path/sprites' + ) + +Batch Processing +~~~~~~~~~~~~~~~~ + +Process multiple sprites efficiently: + +.. code-block:: python + + # Get multiple sprites at once + sprites = sprite_manager.get_sprites([ + 'burner-mining-drill', + 'iron-chest', + 'stone-furnace' + ]) + +Export Sprites +~~~~~~~~~~~~~~ + +Export sprites to individual files: + +.. code-block:: bash + + # Export all sprites to directory + fle sprites --export-dir ./exported_sprites + +Integration with Vision Models +------------------------------- + +GPT-4 Vision +~~~~~~~~~~~~ + +.. code-block:: python + + import openai + import base64 + + # Get map image + map_image = obs['map_image'] + + # Send to GPT-4 Vision + response = openai.ChatCompletion.create( + model="gpt-4-vision-preview", + messages=[ + { + "role": "user", + "content": [ + {"type": "text", "text": "Analyze this Factorio base layout:"}, + {"type": "image_url", "image_url": {"url": map_image}} + ] + } + ] + ) + +Claude Vision +~~~~~~~~~~~~~ + +.. code-block:: python + + import anthropic + + client = anthropic.Anthropic() + + # Get map image (remove data URL prefix) + map_image_data = obs['map_image'].split(',')[1] + + message = client.messages.create( + model="claude-3-opus-20240229", + messages=[ + { + "role": "user", + "content": [ + { + "type": "image", + "source": { + "type": "base64", + "media_type": "image/png", + "data": map_image_data + } + }, + { + "type": "text", + "text": "What entities do you see in this layout?" + } + ] + } + ] + ) + +Troubleshooting +--------------- + +Download Fails +~~~~~~~~~~~~~~ + +If sprite download fails: + +1. Check your internet connection +2. Verify access to HuggingFace +3. Try again with ``--force`` flag + +Missing Sprites +~~~~~~~~~~~~~~~ + +If specific sprites are missing: + +1. Run ``fle sprites --force`` to re-download +2. Check the sprite directory exists +3. Verify sprite names match Factorio prototypes + +Memory Issues +~~~~~~~~~~~~~ + +If you encounter memory issues: + +1. Don't pre-load all sprites +2. Use on-demand loading +3. Clear sprite cache periodically + +Image Format Issues +~~~~~~~~~~~~~~~~~~~ + +If image decoding fails: + +1. Verify base64 encoding is correct +2. Check image format (should be PNG) +3. Ensure data URL prefix is handled correctly + +Next Steps +---------- + +- Learn about :doc:`../tools/overview` for non-visual interactions +- See the `Visual Agent example `_ +- Review :doc:`../environment/overview` for context diff --git a/docs/sphinx/source/api/action.rst b/docs/sphinx/source/api/action.rst deleted file mode 100644 index 8f9737f24..000000000 --- a/docs/sphinx/source/api/action.rst +++ /dev/null @@ -1,251 +0,0 @@ -Action Space -============ - -The action space defines how agents interact with the Factorio Learning Environment through Python code synthesis. - -Action Structure ----------------- - -Actions are defined by the Action class: - -.. autoclass:: fle.env.gym_env.action.Action - :members: - :undoc-members: - :show-inheritance: - -Action Components ------------------ - -**agent_idx** - Index of the agent taking the action (for multi-agent environments) - -**code** - Python code to execute in the game environment - -**game_state** - Optional game state to reset to before running code - -Action Space Definition ------------------------- - -The action space follows this structure: - -.. code-block:: python - - { - 'agent_idx': Discrete(instance.num_agents), # Index of the agent taking the action - 'game_state': Text(max_length=1000000), # Optional: game state to reset to before running code - 'code': Text(max_length=10000) # Python code to execute - } - -Code Execution --------------- - -The environment executes Python code in a controlled namespace that includes: - -**Standard Library** - Full Python standard library access - -**FLE Tools** - All available tools for game interaction - -**Namespace Persistence** - Variables and functions persist between actions - -**Error Handling** - Comprehensive exception handling with detailed error messages - -Example Actions ---------------- - -**Basic Movement** - .. code-block:: python - - action = Action( - agent_idx=0, - code='position = get_position()', - game_state=None - ) - -**Entity Placement** - .. code-block:: python - - action = Action( - agent_idx=0, - code=''' - drill = place_entity( - entity=Prototype.MiningDrill, - position=nearest(Resource.IronOre), - direction=Direction.NORTH - ) - ''', - game_state=None - ) - -**Complex Automation** - .. code-block:: python - - action = Action( - agent_idx=0, - code=''' - # Get iron patch and place mining drill - drill = place_entity( - entity=Prototype.MiningDrill, - position=nearest(Resource.IronOre), - direction=Direction.NORTH - ) - # Add output storage - chest = place_entity_next_to( - entity=Prototype.IronChest, - reference_position=drill.drop_position, - direction=Direction.SOUTH - ) - # Verify automation chain - sleep(10) - assert drill.status == EntityStatus.WORKING - print(get_entities()) - ''', - game_state=None - ) - -**Function Definition** - .. code-block:: python - - action = Action( - agent_idx=0, - code=''' - def place_mining_setup(resource_type, direction): - drill = place_entity( - entity=Prototype.MiningDrill, - position=nearest(resource_type), - direction=direction - ) - chest = place_entity_next_to( - entity=Prototype.IronChest, - reference_position=drill.drop_position, - direction=Direction.SOUTH - ) - return drill, chest - - # Use the function - drill, chest = place_mining_setup(Resource.IronOre, Direction.NORTH) - ''', - game_state=None - ) - -**Class Definition** - .. code-block:: python - - action = Action( - agent_idx=0, - code=''' - class MiningOperation: - def __init__(self, resource_type, position): - self.resource_type = resource_type - self.position = position - self.drill = None - self.chest = None - - def setup(self): - self.drill = place_entity( - entity=Prototype.MiningDrill, - position=self.position, - direction=Direction.NORTH - ) - self.chest = place_entity_next_to( - entity=Prototype.IronChest, - reference_position=self.drill.drop_position, - direction=Direction.SOUTH - ) - - def is_working(self): - return self.drill.status == EntityStatus.WORKING - - # Create and use the class - mining_op = MiningOperation(Resource.IronOre, nearest(Resource.IronOre)) - mining_op.setup() - print(f"Mining operation working: {mining_op.is_working()}") - ''', - game_state=None - ) - -Error Handling --------------- - -The environment provides comprehensive error handling: - -**Syntax Errors** - Python syntax errors are caught and reported with line numbers - -**Runtime Errors** - Exceptions during code execution are captured with full stack traces - -**Tool Errors** - Invalid tool usage is reported with detailed error messages - -**Assertion Failures** - Failed assertions provide context about expected vs actual values - -Example Error Handling ----------------------- - -.. code-block:: python - - # Invalid tool usage - action = Action( - agent_idx=0, - code='place_entity(entity="invalid", position=(0, 0))', - game_state=None - ) - - # Results in error message: - # ValueError: Invalid entity type 'invalid'. Expected Prototype enum value. - -**Debugging Support** - The environment provides debugging information: - - - **Variable Inspection**: Access to all namespace variables - - **Function Signatures**: Available functions and their parameters - - **Entity State**: Current state of all game entities - - **Error Context**: Detailed error information with suggestions - -Multi-Agent Actions -------------------- - -For multi-agent environments, actions can be coordinated: - -.. code-block:: python - - # Agent 0 places a drill - action_0 = Action( - agent_idx=0, - code='drill = place_entity(entity=Prototype.MiningDrill, position=nearest(Resource.IronOre))', - game_state=None - ) - - # Agent 1 places a chest next to it - action_1 = Action( - agent_idx=1, - code='chest = place_entity_next_to(entity=Prototype.IronChest, reference_position=drill.drop_position)', - game_state=None - ) - -Action Validation ------------------ - -The environment validates actions before execution: - -- **Agent Index**: Ensures valid agent index -- **Code Length**: Limits code to prevent resource exhaustion -- **Game State**: Validates game state format if provided -- **Tool Availability**: Ensures requested tools are available - -Best Practices --------------- - -1. **Use Descriptive Variable Names**: Make code readable and maintainable -2. **Handle Errors Gracefully**: Use try-except blocks for robust code -3. **Leverage Namespace**: Store useful objects for later reference -4. **Use Functions**: Encapsulate common operations -5. **Debug with Print**: Use print statements to monitor execution -6. **Assert Conditions**: Use assertions to verify expected behavior diff --git a/docs/sphinx/source/api/environment.rst b/docs/sphinx/source/api/environment.rst deleted file mode 100644 index 486440c8c..000000000 --- a/docs/sphinx/source/api/environment.rst +++ /dev/null @@ -1,128 +0,0 @@ -Environment API -=============== - -The Factorio Learning Environment provides a comprehensive API for interacting with the game through Python code synthesis. - -Core Concepts -------------- - -**FactorioInstance** - The main interface for interacting with a Factorio game instance. Provides access to all game state and tools. - -**Namespace Management** - Python namespace that persists across agent actions, allowing for stateful interactions and code reuse. - -**Gym Environment Integration** - Standard OpenAI Gym interface for reinforcement learning integration. - -FactorioInstance ----------------- - -.. autoclass:: fle.env.instance.FactorioInstance - :members: - :undoc-members: - :show-inheritance: - -Key Methods -~~~~~~~~~~~ - -.. automethod:: fle.env.instance.FactorioInstance.reset -.. automethod:: fle.env.instance.FactorioInstance.step -.. automethod:: fle.env.instance.FactorioInstance.close - -Namespace Management --------------------- - -.. autoclass:: fle.env.namespace.Namespace - :members: - :undoc-members: - :show-inheritance: - -The namespace provides: - -- **Variable Storage**: Store and retrieve objects between actions -- **Function Definitions**: Define reusable functions -- **Class Definitions**: Create custom data structures -- **Import Management**: Handle Python imports and modules - -Gym Environment ---------------- - -.. autoclass:: fle.env.gym_env.FactorioGymEnv - :members: - :undoc-members: - :show-inheritance: - -The gym environment provides: - -- **Standard Interface**: Compatible with OpenAI Gym -- **Action Space**: Structured action space for agent actions -- **Observation Space**: Rich observation space with game state -- **Reward System**: Configurable reward functions - -Environment Registry --------------------- - -FLE uses a gym environment registry to automatically discover and register all available tasks. - -.. autofunction:: fle.env.gym_env.registry.list_available_environments -.. autofunction:: fle.env.gym_env.registry.get_environment_info -.. autofunction:: fle.env.gym_env.registry.register_all_environments - -Available Environments -~~~~~~~~~~~~~~~~~~~~~~~ - -**Throughput Tasks (Lab Play)** - All throughput tasks are defined in `fle/eval/tasks/task_definitions/lab_play/throughput_tasks.py`. The 24 available tasks are: - - - **Circuits**: `advanced_circuit_throughput`, `electronic_circuit_throughput`, `processing_unit_throughput` - - **Science Packs**: `automation_science_pack_throughput`, `logistics_science_pack_throughput`, `chemical_science_pack_throughput`, `military_science_pack_throughput`, `production_science_pack_throughput`, `utility_science_pack_throughput` - - **Components**: `battery_throughput`, `engine_unit_throughput`, `inserter_throughput`, `iron_gear_wheel_throughput`, `low_density_structure_throughput` - - **Raw Materials**: `iron_ore_throughput`, `iron_plate_throughput`, `steel_plate_throughput`, `plastic_bar_throughput` - - **Oil & Chemicals**: `crude_oil_throughput`, `petroleum_gas_throughput`, `sufuric_acid_throughput`, `sulfur_throughput` - - **Military**: `piercing_round_throughput`, `stone_wall_throughput` - - Most tasks require 16 items per 60 seconds; fluid tasks require 250 units per 60 seconds. - -**Open Play** - Unbounded task of building the largest possible factory: `open_play` - -Example Usage -------------- - -.. code-block:: python - - import gym - from fle.env.gym_env.action import Action - - # Create any available environment - env = gym.make("iron_ore_throughput") - - # Reset the environment - obs = env.reset(options={'game_state': None}) - - # Take an action - action = Action( - agent_idx=0, # Which agent takes the action - code='print("Hello Factorio!")', # Python code to execute - game_state=None # Optional: game state to reset to before running code - ) - - # Execute the action - obs, reward, terminated, truncated, info = env.step(action) - - # Clean up - env.close() - -Error Handling --------------- - -The environment includes comprehensive error handling for: - -- Missing task definition files -- Invalid JSON configurations -- Missing Factorio containers -- Environment creation failures -- Network connectivity issues - -If an environment fails to load, a warning will be printed but the registry will continue to load other environments. diff --git a/docs/sphinx/source/api/modules.rst b/docs/sphinx/source/api/modules.rst deleted file mode 100644 index 6b5e931a5..000000000 --- a/docs/sphinx/source/api/modules.rst +++ /dev/null @@ -1,42 +0,0 @@ -API Modules -=========== - -This section contains the complete API reference for all FLE modules. - -Core Environment ----------------- - -.. toctree:: - :maxdepth: 2 - - modules/fle.env.instance - modules/fle.env.namespace - modules/fle.env.gym_env - modules/fle.env.entities - modules/fle.env.game_types - -Agents ------- - -.. toctree:: - :maxdepth: 2 - - modules/fle.agents.agent_abc - modules/fle.agents.models - -Evaluation ----------- - -.. toctree:: - :maxdepth: 2 - - modules/fle.eval.tasks - modules/fle.eval.algorithms - -Common Models -------------- - -.. toctree:: - :maxdepth: 2 - - modules/fle.commons.models diff --git a/docs/sphinx/source/api/modules/fle.agents.agent_abc.rst b/docs/sphinx/source/api/modules/fle.agents.agent_abc.rst deleted file mode 100644 index 0b7dd4707..000000000 --- a/docs/sphinx/source/api/modules/fle.agents.agent_abc.rst +++ /dev/null @@ -1,7 +0,0 @@ -fle.agents.agent_abc module -=========================== - -.. automodule:: fle.agents.agent_abc - :members: - :undoc-members: - :show-inheritance: diff --git a/docs/sphinx/source/api/modules/fle.agents.models.rst b/docs/sphinx/source/api/modules/fle.agents.models.rst deleted file mode 100644 index 16f04c4a7..000000000 --- a/docs/sphinx/source/api/modules/fle.agents.models.rst +++ /dev/null @@ -1,7 +0,0 @@ -fle.agents.models module -======================== - -.. automodule:: fle.agents.models - :members: - :undoc-members: - :show-inheritance: diff --git a/docs/sphinx/source/api/modules/fle.commons.models.rst b/docs/sphinx/source/api/modules/fle.commons.models.rst deleted file mode 100644 index ffcd449b8..000000000 --- a/docs/sphinx/source/api/modules/fle.commons.models.rst +++ /dev/null @@ -1,7 +0,0 @@ -fle.commons.models module -========================= - -.. automodule:: fle.commons.models - :members: - :undoc-members: - :show-inheritance: diff --git a/docs/sphinx/source/api/modules/fle.env.entities.rst b/docs/sphinx/source/api/modules/fle.env.entities.rst deleted file mode 100644 index 8964ea1a3..000000000 --- a/docs/sphinx/source/api/modules/fle.env.entities.rst +++ /dev/null @@ -1,7 +0,0 @@ -fle.env.entities module -======================= - -.. automodule:: fle.env.entities - :members: - :undoc-members: - :show-inheritance: diff --git a/docs/sphinx/source/api/modules/fle.env.game_types.rst b/docs/sphinx/source/api/modules/fle.env.game_types.rst deleted file mode 100644 index 60ae7c422..000000000 --- a/docs/sphinx/source/api/modules/fle.env.game_types.rst +++ /dev/null @@ -1,7 +0,0 @@ -fle.env.game_types module -========================= - -.. automodule:: fle.env.game_types - :members: - :undoc-members: - :show-inheritance: diff --git a/docs/sphinx/source/api/modules/fle.env.gym_env.rst b/docs/sphinx/source/api/modules/fle.env.gym_env.rst deleted file mode 100644 index a31567df5..000000000 --- a/docs/sphinx/source/api/modules/fle.env.gym_env.rst +++ /dev/null @@ -1,7 +0,0 @@ -fle.env.gym_env module -====================== - -.. automodule:: fle.env.gym_env - :members: - :undoc-members: - :show-inheritance: diff --git a/docs/sphinx/source/api/modules/fle.env.instance.rst b/docs/sphinx/source/api/modules/fle.env.instance.rst deleted file mode 100644 index 7e181751e..000000000 --- a/docs/sphinx/source/api/modules/fle.env.instance.rst +++ /dev/null @@ -1,7 +0,0 @@ -fle.env.instance module -======================== - -.. automodule:: fle.env.instance - :members: - :undoc-members: - :show-inheritance: diff --git a/docs/sphinx/source/api/modules/fle.env.namespace.rst b/docs/sphinx/source/api/modules/fle.env.namespace.rst deleted file mode 100644 index bbf5c11b8..000000000 --- a/docs/sphinx/source/api/modules/fle.env.namespace.rst +++ /dev/null @@ -1,7 +0,0 @@ -fle.env.namespace module -======================== - -.. automodule:: fle.env.namespace - :members: - :undoc-members: - :show-inheritance: diff --git a/docs/sphinx/source/api/modules/fle.eval.algorithms.rst b/docs/sphinx/source/api/modules/fle.eval.algorithms.rst deleted file mode 100644 index 044d3a738..000000000 --- a/docs/sphinx/source/api/modules/fle.eval.algorithms.rst +++ /dev/null @@ -1,7 +0,0 @@ -fle.eval.algorithms module -========================== - -.. automodule:: fle.eval.algorithms - :members: - :undoc-members: - :show-inheritance: diff --git a/docs/sphinx/source/api/modules/fle.eval.tasks.rst b/docs/sphinx/source/api/modules/fle.eval.tasks.rst deleted file mode 100644 index b1c391a33..000000000 --- a/docs/sphinx/source/api/modules/fle.eval.tasks.rst +++ /dev/null @@ -1,7 +0,0 @@ -fle.eval.tasks module -===================== - -.. automodule:: fle.eval.tasks - :members: - :undoc-members: - :show-inheritance: diff --git a/docs/sphinx/source/api/observation.rst b/docs/sphinx/source/api/observation.rst deleted file mode 100644 index 1f54c065a..000000000 --- a/docs/sphinx/source/api/observation.rst +++ /dev/null @@ -1,178 +0,0 @@ -Observation Space -================== - -The observation space provides rich information about the current game state, allowing agents to make informed decisions. - -Observation Structure --------------------- - -The observation space includes the following components: - -**raw_text** - Output from the last action (stdout/stderr) - -**entities** - List of entities on the map with their current state - -**inventory** - Current inventory state of the player - -**research** - Research progress and available technologies - -**game_info** - Game state information (tick, time, speed) - -**score** - Current score and performance metrics - -**flows** - Production statistics and resource flows - -**task_verification** - Task completion status and progress - -**messages** - Inter-agent communication messages - -**serialized_functions** - Available functions and their signatures - -**task_info** - Information about the current task - -**map_image** - Base64 encoded PNG image of the current map - -Entity Information ------------------- - -Entities provide detailed information about game objects: - -.. autoclass:: fle.env.entities.Entity - :members: - :undoc-members: - :show-inheritance: - -Entity Types -~~~~~~~~~~~~ - -**MiningDrill** - Mining drills for extracting resources - -**Chest** - Storage containers for items - -**AssemblingMachine** - Machines for crafting items - -**Inserter** - Transport devices for moving items - -**TransportBelt** - Conveyor belts for item transport - -**Pipe** - Fluid transport systems - -**PowerPole** - Electrical distribution - -**Lab** - Research facilities - -Position and Direction ----------------------- - -.. autoclass:: fle.env.game_types.Position - :members: - :undoc-members: - :show-inheritance: - -.. autoclass:: fle.env.game_types.Direction - :members: - :undoc-members: - :show-inheritance: - -Inventory Management --------------------- - -.. autoclass:: fle.env.game_types.Inventory - :members: - :undoc-members: - :show-inheritance: - -The inventory system provides: - -- **Item Storage**: Store and retrieve items -- **Count Methods**: Query item quantities -- **Type Validation**: Ensure item compatibility -- **Transfer Operations**: Move items between inventories - -Research System ---------------- - -.. autoclass:: fle.env.game_types.Research - :members: - :undoc-members: - :show-inheritance: - -Research provides: - -- **Technology Tree**: Available technologies -- **Prerequisites**: Required research -- **Progress Tracking**: Current research status -- **Unlock Management**: New technologies and recipes - -Game State Information ----------------------- - -.. autoclass:: fle.env.game_types.GameInfo - :members: - :undoc-members: - :show-inheritance: - -Game info includes: - -- **Tick Information**: Current game tick -- **Time Data**: Game time and speed -- **Performance Metrics**: FPS and UPS -- **Map Information**: World size and generation - -Task Verification ----------------- - -.. autoclass:: fle.env.game_types.TaskVerification - :members: - :undoc-members: - :show-inheritance: - -Task verification provides: - -- **Completion Status**: Whether the task is complete -- **Progress Metrics**: Current progress toward goals -- **Objective Tracking**: Individual objective status -- **Performance Data**: Efficiency and throughput metrics - -Example Observation -------------------- - -.. code-block:: python - - { - 'raw_text': 'Hello Factorio!', - 'entities': [ - Entity(name='burner-mining-drill', position=Position(x=-28.0, y=-61.0), ...), - Entity(name='iron-chest', position=Position(x=-27.5, y=-59.5), ...) - ], - 'inventory': Inventory({'iron-ore': 75, 'coal': 4}), - 'research': Research(technologies=['automation'], progress=0.5), - 'game_info': GameInfo(tick=1000, time=16.67, speed=1.0), - 'score': 150, - 'flows': {'iron-ore': 2.5, 'iron-plate': 1.2}, - 'task_verification': TaskVerification(complete=False, progress=0.3), - 'messages': [], - 'serialized_functions': ['place_entity', 'get_entities', ...], - 'task_info': {'name': 'iron_ore_throughput', 'target': 16}, - 'map_image': 'iVBORw0KGgoAAAANSUhEUgAA...' - } diff --git a/docs/sphinx/source/api/tools.rst b/docs/sphinx/source/api/tools.rst deleted file mode 100644 index 29db00fe9..000000000 --- a/docs/sphinx/source/api/tools.rst +++ /dev/null @@ -1,252 +0,0 @@ -Tools API -========= - -Agents interact with the game using _tools_, which represent a narrow API into the game. Tools are functions that perform game actions and return typed objects. - -Tool Architecture ------------------ - -Tools live in `fle/env/tools/agent/` and require 3 files: - -1. **agent.md**: Documentation for the agent, including usage patterns, best practices and failure modes -2. **client.py**: Client-side implementation, a Python class that can be invoked by the agent -3. **server.lua**: Server-side implementation, which handles most of the logic and heavy lifting - -.. note:: - The tool workflow connects the agent's synthesized Python program to the client-side ``client.py`` and then to the Factorio server's ``server.lua``, returning structured results back to the agent for the next step. - -Core Tools ----------- - -Inventory Management -~~~~~~~~~~~~~~~~~~~~ - -**inspect_inventory** - Checks contents of player or entity inventories - - - Supports various inventory types (chests, furnaces, etc.) - - Returns Inventory object with count methods - - Can query specific items - -**insert_item** - Places items from player inventory into entities - - - Works with machines, chests, belts - - Validates item compatibility - - Returns updated entity - -**extract_item** - Removes items from entity inventories - - - Supports all inventory types - - Auto-transfers to player inventory - - Returns quantity extracted - -Entity Management -~~~~~~~~~~~~~~~~~ - -**place_entity** - Places entities in the world - - - Handles direction and positioning - - Validates placement requirements - - Returns placed Entity object - -**place_entity_next_to** - Places entities relative to others - - - Automatic spacing/alignment - - Handles entity dimensions - - Supports all entity types - -**pickup_entity** - Removes entities from the world - - - Returns items to inventory - - Handles entity groups - - Supports all placeable items - -**rotate_entity** - Changes entity orientation - - - Affects entity behavior (e.g., inserter direction) - - Validates rotation rules - - Returns updated entity - -Entity Queries -~~~~~~~~~~~~~~ - -**get_entity** - Retrieves entity objects at positions - - - Updates stale references - - Returns typed Entity objects - - Handles all entity types - -**get_entities** - Finds multiple entities in an area - - - Supports filtering by type - - Returns List[Entity] - - Groups connected entities - -**nearest** - Locates closest resources/entities - - - Finds ores, water, trees - - Returns Position object - - 500 tile search radius - -**nearest_buildable** - Finds valid building locations - - - Respects entity dimensions - - Handles resource requirements - - Returns buildable position - -Resource Management -~~~~~~~~~~~~~~~~~~~ - -**get_resource_patch** - Analyzes resource deposits - - - Returns size and boundaries - - Supports all resource types - - Includes total resource amount - -**harvest_resource** - Gathers resources from the world - - - Supports ores, trees, rocks - - Auto-collects to inventory - - Returns amount harvested - -Connection Management -~~~~~~~~~~~~~~~~~~~~~ - -**connect_entities** - Creates connections between entities - - - Handles belts, pipes, power - - Automatic pathfinding - - Returns connection group - -**get_connection_amount** - Calculates required connection items - - - Pre-planning tool - - Works with all connection types - - Returns item count needed - -Crafting and Research -~~~~~~~~~~~~~~~~~~~~~ - -**set_entity_recipe** - Configures machine crafting recipes - - - Works with assemblers/chemical plants - - Validates recipe requirements - - Returns updated entity - -**get_prototype_recipe** - Retrieves crafting requirements - - - Shows ingredients/products - - Includes crafting time - - Returns Recipe object - -**craft_item** - Creates items from components - - - Handles recursive crafting - - Validates technology requirements - - Returns crafted amount - -**set_research** - Initiates technology research - - - Validates prerequisites - - Returns required ingredients - - Handles research queue - -**get_research_progress** - Monitors research status - - - Shows remaining requirements - - Tracks progress percentage - - Returns ingredient list - -Movement and Control -~~~~~~~~~~~~~~~~~~~~ - -**move_to** - Moves player to position - - - Pathfinds around obstacles - - Can place items while moving - - Returns final position - -**sleep** - Pauses execution - - - Waits for actions to complete - - Adapts to game speed - - Maximum 15 second duration - -**launch_rocket** - Controls rocket silo launches - - - Validates launch requirements - - Handles launch sequence - - Returns updated silo state - -Debugging and Output -~~~~~~~~~~~~~~~~~~~~ - -**print** - Outputs debug information to stdout - - - Supports various object types - - Useful for monitoring state - - Returns formatted string - -Tool Categories ----------------- - -**Core Tools** - Essential tools for basic game interaction - -**Advanced Tools** - Specialized tools for complex operations - -**Debugging Tools** - Tools for monitoring and debugging - -**Multi-Agent Tools** - Tools for coordinated multi-agent operations - -Creating Custom Tools ---------------------- - -1. Create a new directory in `fle/env/tools/agent/`, e.g `fle/env/tools/agent/my_tool` -2. Add a `client.py` file, which should contain a class inheriting `Tool` and implementing a `__call__` function to treat the class as a callable function. The method signature should contain type annotations. This function _must_ call `self.execute` to invoke the server-side logic. -3. Add a `server.lua` file, containing a function structured like `global.actions.my_tool = function(arg1, arg2, ...)`. This file should invoke the `Factorio API `_ to perform the desired action, and return a table that will be serialized and sent back to the client. -4. Add an `agent.md` file, which should contain a markdown description of the tool. This file will be used by the agent to understand how to use the tool - -Next time you run an eval, the tool will automatically be available to the agent and documented in the agent context. - -5. (Optional) Create a test suite in `fle/tests/actions` for your new tool. - -Tool Documentation ------------------- - -Each tool has comprehensive documentation including: - -- **Overview**: What the tool does -- **Parameters**: Input parameters and their types -- **Returns**: What the tool returns -- **Examples**: Usage examples -- **Best Practices**: Recommended usage patterns -- **Failure Modes**: Common errors and how to avoid them - -See the :doc:`tools index <../tools/index>` for detailed documentation of each tool. diff --git a/docs/sphinx/source/customization/agents.rst b/docs/sphinx/source/customization/agents.rst deleted file mode 100644 index 143602d55..000000000 --- a/docs/sphinx/source/customization/agents.rst +++ /dev/null @@ -1,331 +0,0 @@ -Implementing Custom Agents -========================== - -FLE provides a flexible framework for implementing custom agents. Agents interact with the environment through code synthesis and can be designed for various evaluation scenarios. - -Agent Architecture ------------------- - -Agents in FLE follow a specific architecture: - -**Base Agent Class** - Abstract base class defining the agent interface - -**Agent Implementation** - Concrete implementation of agent behavior - -**Agent Registration** - Registration with the evaluation system - -Base Agent Class ----------------- - -All agents inherit from the base agent class: - -.. autoclass:: fle.agents.agent_abc.Agent - :members: - :undoc-members: - :show-inheritance: - -Key Methods -~~~~~~~~~~~ - -**act(observation)** - Generate an action based on the current observation - -**reset()** - Reset the agent state for a new episode - -**close()** - Clean up agent resources - -Agent Implementation --------------------- - -Create a custom agent by inheriting from the base class: - -.. code-block:: python - - from fle.agents.agent_abc import Agent - from fle.env.gym_env.action import Action - from typing import Dict, Any - - class MyCustomAgent(Agent): - def __init__(self, config: Dict[str, Any]): - super().__init__(config) - self.name = "MyCustomAgent" - self.episode_count = 0 - self.total_reward = 0.0 - - def act(self, observation: Dict[str, Any]) -> Action: - """ - Generate an action based on the current observation. - - Args: - observation: Current game state observation - - Returns: - Action to execute - """ - # Analyze the observation - entities = observation.get('entities', []) - inventory = observation.get('inventory', {}) - game_info = observation.get('game_info', {}) - - # Generate action code - code = self._generate_action_code(entities, inventory, game_info) - - return Action( - agent_idx=0, - code=code, - game_state=None - ) - - def reset(self): - """Reset agent state for new episode""" - self.episode_count += 1 - self.total_reward = 0.0 - super().reset() - - def close(self): - """Clean up agent resources""" - super().close() - - def _generate_action_code(self, entities, inventory, game_info): - """Generate Python code for the action""" - # Implement your action generation logic - return 'print("Hello from MyCustomAgent!")' - -Agent Types ------------ - -**Basic Agents** - Simple agents with basic decision-making - -**Visual Agents** - Agents that process visual information - -**Multi-Agent Systems** - Agents that coordinate with other agents - -**Learning Agents** - Agents that improve over time - -**Specialized Agents** - Agents designed for specific tasks - -Example Agent: Resource Collector ----------------------------------- - -Here's a complete example of a resource collection agent: - -.. code-block:: python - - from fle.agents.agent_abc import Agent - from fle.env.gym_env.action import Action - from fle.env.game_types import Position, Direction - from typing import Dict, Any, List - - class ResourceCollectorAgent(Agent): - def __init__(self, config: Dict[str, Any]): - super().__init__(config) - self.name = "ResourceCollectorAgent" - self.target_resources = config.get('target_resources', ['iron-ore', 'copper-ore']) - self.collected_resources = {} - self.mining_setups = [] - - def act(self, observation: Dict[str, Any]) -> Action: - """Generate action to collect resources""" - entities = observation.get('entities', []) - inventory = observation.get('inventory', {}) - - # Check if we need to set up mining - if not self.mining_setups: - code = self._setup_mining(entities) - else: - code = self._monitor_mining(entities, inventory) - - return Action( - agent_idx=0, - code=code, - game_state=None - ) - - def _setup_mining(self, entities: List) -> str: - """Set up mining operations for target resources""" - code_lines = [] - - for resource in self.target_resources: - code_lines.append(f''' -# Set up mining for {resource} -resource_pos = nearest(Resource.{resource.replace('-', '_').upper()}) -if resource_pos: - drill = place_entity( - entity=Prototype.MiningDrill, - position=resource_pos, - direction=Direction.NORTH - ) - chest = place_entity_next_to( - entity=Prototype.IronChest, - reference_position=drill.drop_position, - direction=Direction.SOUTH - ) - print(f"Set up mining for {{resource}} at {{resource_pos}}") -''') - - return '\n'.join(code_lines) - - def _monitor_mining(self, entities: List, inventory: Dict) -> str: - """Monitor and manage existing mining operations""" - return ''' -# Monitor mining operations -entities = get_entities() -for entity in entities: - if hasattr(entity, 'status') and entity.status == EntityStatus.WORKING: - print(f"Entity {entity.name} is working") - elif hasattr(entity, 'status') and entity.status == EntityStatus.NO_POWER: - print(f"Entity {entity.name} needs power") - -# Check inventory -inventory = inspect_inventory() -for item, count in inventory.items(): - if count > 0: - print(f"Have {count} {item}") -''' - -Agent Configuration -------------------- - -Agents can be configured with various parameters: - -**Behavior Parameters** - - Decision-making algorithms - - Action generation strategies - - State management approaches - -**Performance Parameters** - - Memory usage limits - - Processing time limits - - Resource consumption limits - -**Evaluation Parameters** - - Success criteria - - Performance metrics - - Evaluation scenarios - -Example Configuration --------------------- - -.. code-block:: json - - { - "agent_type": "ResourceCollectorAgent", - "config": { - "target_resources": ["iron-ore", "copper-ore", "coal"], - "max_mining_setups": 5, - "mining_radius": 100, - "inventory_threshold": 1000 - }, - "evaluation": { - "episodes": 10, - "max_steps": 1000, - "success_threshold": 0.8 - } - } - -Agent Testing -------------- - -Create test cases for your custom agents: - -.. code-block:: python - - import pytest - from fle.agents.my_custom_agent import MyCustomAgent - from fle.env.gym_env.action import Action - - def test_agent_creation(): - config = {'param1': 'value1'} - agent = MyCustomAgent(config) - assert agent.name == "MyCustomAgent" - - def test_agent_action(): - config = {} - agent = MyCustomAgent(config) - - observation = { - 'entities': [], - 'inventory': {}, - 'game_info': {} - } - - action = agent.act(observation) - assert isinstance(action, Action) - assert action.agent_idx == 0 - - def test_agent_reset(): - config = {} - agent = MyCustomAgent(config) - agent.reset() - assert agent.episode_count == 1 - -Advanced Agent Features ------------------------ - -**State Management** - - Persistent state across episodes - - State serialization and loading - - State sharing between agents - -**Learning Capabilities** - - Experience replay - - Policy updates - - Performance tracking - -**Multi-Agent Coordination** - - Communication protocols - - Task distribution - - Conflict resolution - -**Adaptive Behavior** - - Dynamic strategy adjustment - - Environment adaptation - - Performance optimization - -Agent Registration ------------------- - -Agents are registered with the evaluation system: - -1. **Agent Discovery**: The system scans for agent implementations -2. **Configuration Loading**: Agent configurations are loaded -3. **Initialization**: Agents are initialized with their configurations -4. **Registration**: Agents are registered with the evaluation system - -Example Registration ----------------------- - -.. code-block:: python - - from fle.agents.registry import register_agent - from fle.agents.my_custom_agent import MyCustomAgent - - # Register the agent - register_agent('my_custom_agent', MyCustomAgent) - - # Use in evaluation - config = { - 'agent_type': 'my_custom_agent', - 'config': {'param1': 'value1'} - } - -Best Practices --------------- - -1. **Clear Interface**: Design simple, intuitive interfaces -2. **Error Handling**: Handle errors gracefully -3. **State Management**: Manage agent state properly -4. **Performance**: Optimize for efficiency -5. **Testing**: Test all scenarios and edge cases -6. **Documentation**: Document agent behavior and configuration -7. **Modularity**: Design for reusability and extensibility diff --git a/docs/sphinx/source/customization/database.rst b/docs/sphinx/source/customization/database.rst deleted file mode 100644 index 49cb06342..000000000 --- a/docs/sphinx/source/customization/database.rst +++ /dev/null @@ -1,357 +0,0 @@ -Database Configuration -======================= - -FLE supports checkpointing at every agent step using a SQL database. The `db_client` implements the interface for saving and loading agent outputs, environment feedbacks, game states and histories of the current trajectory. - -Database Types --------------- - -FLE supports multiple database backends: - -**SQLite (Default)** - Lightweight, file-based database - -**PostgreSQL** - Full-featured, server-based database - -**Custom Databases** - Extensible database interface - -SQLite Configuration --------------------- - -SQLite is the default database and requires minimal configuration: - -.. code-block:: bash - - # Set database type - FLE_DB_TYPE="sqlite" - - # Set database file path (default: .fle/data.db) - SQLITE_DB_FILE=".fle/data.db" - -SQLite is ideal for: -- Development and testing -- Single-user scenarios -- Small to medium datasets -- Quick setup and deployment - -PostgreSQL Configuration ------------------------- - -For production use and large-scale experiments, PostgreSQL is recommended: - -**Docker Setup** - .. code-block:: bash - - docker run --name fle-postgres \ - -e POSTGRES_PASSWORD=fle123 \ - -e POSTGRES_USER=fle_user \ - -e POSTGRES_DB=fle_database \ - -p 5432:5432 \ - -d postgres:15 - -**Environment Variables** - .. code-block:: bash - - # Database Configuration - FLE_DB_TYPE="postgres" - - # PostgreSQL Configuration - SKILLS_DB_HOST=localhost - SKILLS_DB_PORT=5432 - SKILLS_DB_NAME=fle_database - SKILLS_DB_USER=fle_user - SKILLS_DB_PASSWORD=fle123 - -PostgreSQL is ideal for: -- Production deployments -- Multi-user scenarios -- Large datasets -- High-performance requirements - -Database Schema ---------------- - -The database schema includes several key tables: - -**Trajectories** - Store complete agent trajectories - -**Steps** - Individual agent steps within trajectories - -**Game States** - Complete game state snapshots - -**Agent Outputs** - Agent-generated code and actions - -**Environment Feedbacks** - Environment responses and observations - -**Metadata** - Additional information about trajectories - -Database Client ---------------- - -The database client provides a unified interface: - -.. autoclass:: fle.commons.db_client.DatabaseClient - :members: - :undoc-members: - :show-inheritance: - -Key Methods -~~~~~~~~~~~ - -**save_trajectory(trajectory)** - Save a complete trajectory - -**load_trajectory(trajectory_id)** - Load a trajectory by ID - -**save_step(step)** - Save an individual step - -**load_steps(trajectory_id)** - Load all steps for a trajectory - -**save_game_state(state)** - Save a game state snapshot - -**load_game_state(state_id)** - Load a game state by ID - -Example Usage -------------- - -**Saving a Trajectory** - .. code-block:: python - - from fle.commons.db_client import DatabaseClient - - # Initialize database client - db = DatabaseClient() - - # Save trajectory - trajectory = { - 'id': 'trajectory_001', - 'agent_type': 'MyAgent', - 'task': 'iron_ore_throughput', - 'start_time': '2024-01-01T00:00:00Z', - 'end_time': '2024-01-01T01:00:00Z', - 'total_reward': 150.0, - 'success': True - } - - db.save_trajectory(trajectory) - -**Loading a Trajectory** - .. code-block:: python - - # Load trajectory - trajectory = db.load_trajectory('trajectory_001') - print(f"Trajectory: {trajectory['id']}") - print(f"Agent: {trajectory['agent_type']}") - print(f"Reward: {trajectory['total_reward']}") - -**Saving Steps** - .. code-block:: python - - # Save individual step - step = { - 'trajectory_id': 'trajectory_001', - 'step_number': 1, - 'action': 'print("Hello Factorio!")', - 'observation': {'entities': [], 'inventory': {}}, - 'reward': 10.0, - 'timestamp': '2024-01-01T00:00:00Z' - } - - db.save_step(step) - -**Loading Steps** - .. code-block:: python - - # Load all steps for a trajectory - steps = db.load_steps('trajectory_001') - for step in steps: - print(f"Step {step['step_number']}: {step['action']}") - -Database Migration ------------------- - -FLE includes database migration support: - -**Automatic Migration** - The system automatically migrates the database schema on startup - -**Manual Migration** - Run migrations manually when needed - -**Version Control** - Track database schema versions - -Example Migration ------------------- - -.. code-block:: python - - from fle.commons.db_client import DatabaseClient - - # Initialize database client - db = DatabaseClient() - - # Run migrations - db.migrate() - - # Check migration status - status = db.get_migration_status() - print(f"Current version: {status['current_version']}") - print(f"Latest version: {status['latest_version']}") - -Performance Optimization ------------------------ - -**Connection Pooling** - Reuse database connections - -**Batch Operations** - Group multiple operations together - -**Indexing** - Optimize database queries - -**Caching** - Cache frequently accessed data - -Example Optimization -------------------- - -.. code-block:: python - - from fle.commons.db_client import DatabaseClient - - # Initialize with connection pooling - db = DatabaseClient( - max_connections=10, - connection_timeout=30 - ) - - # Batch save multiple steps - steps = [ - {'trajectory_id': 't1', 'step_number': 1, 'action': 'action1'}, - {'trajectory_id': 't1', 'step_number': 2, 'action': 'action2'}, - {'trajectory_id': 't1', 'step_number': 3, 'action': 'action3'} - ] - - db.batch_save_steps(steps) - -Backup and Recovery -------------------- - -**Automated Backups** - Schedule regular database backups - -**Point-in-Time Recovery** - Restore to specific timestamps - -**Data Export** - Export data for analysis - -**Data Import** - Import data from other sources - -Example Backup --------------- - -.. code-block:: python - - from fle.commons.db_client import DatabaseClient - - # Initialize database client - db = DatabaseClient() - - # Create backup - backup_id = db.create_backup() - print(f"Backup created: {backup_id}") - - # List backups - backups = db.list_backups() - for backup in backups: - print(f"Backup {backup['id']}: {backup['timestamp']}") - - # Restore from backup - db.restore_backup(backup_id) - -Monitoring and Maintenance --------------------------- - -**Performance Monitoring** - Monitor database performance - -**Health Checks** - Verify database health - -**Cleanup Operations** - Remove old data - -**Optimization** - Optimize database performance - -Example Monitoring ------------------ - -.. code-block:: python - - from fle.commons.db_client import DatabaseClient - - # Initialize database client - db = DatabaseClient() - - # Get database statistics - stats = db.get_statistics() - print(f"Total trajectories: {stats['trajectories']}") - print(f"Total steps: {stats['steps']}") - print(f"Database size: {stats['size']}") - - # Get performance metrics - metrics = db.get_performance_metrics() - print(f"Average query time: {metrics['avg_query_time']}") - print(f"Connection count: {metrics['connection_count']}") - -Troubleshooting --------------- - -**Connection Issues** - - Verify database server is running - - Check connection parameters - - Verify network connectivity - -**Performance Issues** - - Monitor database performance - - Optimize queries - - Consider connection pooling - -**Data Issues** - - Verify data integrity - - Check for corruption - - Run data validation - -**Migration Issues** - - Check migration status - - Verify schema compatibility - - Run manual migrations if needed - -Best Practices --------------- - -1. **Regular Backups**: Schedule automated backups -2. **Performance Monitoring**: Monitor database performance -3. **Connection Management**: Use connection pooling -4. **Data Validation**: Validate data integrity -5. **Migration Testing**: Test migrations before deployment -6. **Security**: Secure database access -7. **Documentation**: Document database configuration diff --git a/docs/sphinx/source/customization/tasks.rst b/docs/sphinx/source/customization/tasks.rst deleted file mode 100644 index ee64635b2..000000000 --- a/docs/sphinx/source/customization/tasks.rst +++ /dev/null @@ -1,276 +0,0 @@ -Creating Custom Tasks -===================== - -FLE allows you to create custom tasks for evaluating agent capabilities. Tasks define the objectives, constraints, and success criteria for agent evaluation. - -Task Structure --------------- - -Tasks are defined in `fle/eval/tasks/task_definitions/` and follow a specific structure: - -**Task Definition File** - JSON configuration file defining task parameters - -**Task Implementation** - Python class implementing the task logic - -**Task Registration** - Automatic registration with the gym environment registry - -Task Definition ---------------- - -Create a new task definition file in `fle/eval/tasks/task_definitions/`: - -.. code-block:: json - - { - "name": "my_custom_task", - "description": "A custom task for evaluating agent capabilities", - "type": "throughput", - "target": 16, - "time_limit": 3600, - "resources": { - "iron_ore": 10000, - "copper_ore": 5000, - "coal": 2000 - }, - "technologies": ["automation"], - "constraints": { - "max_entities": 100, - "max_power": 1000 - } - } - -Task Types ----------- - -**Throughput Tasks** - Tasks focused on producing a specific item at a target rate - -**Research Tasks** - Tasks focused on technology research and advancement - -**Construction Tasks** - Tasks focused on building specific structures - -**Exploration Tasks** - Tasks focused on map exploration and discovery - -**Multi-Objective Tasks** - Tasks with multiple competing objectives - -Task Implementation -------------------- - -Create a Python class implementing your task: - -.. code-block:: python - - from fle.eval.tasks.base import BaseTask - - class MyCustomTask(BaseTask): - def __init__(self, config): - super().__init__(config) - self.target = config.get('target', 16) - self.time_limit = config.get('time_limit', 3600) - - def evaluate(self, state): - """Evaluate the current state against task objectives""" - # Implement your evaluation logic - pass - - def is_complete(self, state): - """Check if the task is complete""" - # Implement completion criteria - pass - - def get_reward(self, state): - """Calculate reward for current state""" - # Implement reward calculation - pass - -Task Configuration ------------------- - -Tasks can be configured with various parameters: - -**Resource Constraints** - - Starting resources - - Resource availability - - Resource consumption rates - -**Technology Requirements** - - Required technologies - - Technology research costs - - Technology dependencies - -**Time Constraints** - - Time limits - - Time-based objectives - - Time-based rewards - -**Spatial Constraints** - - Map size limits - - Entity placement rules - - Distance requirements - -**Performance Constraints** - - Power consumption limits - - Entity count limits - - Efficiency requirements - -Task Registration ------------------ - -Tasks are automatically registered with the gym environment registry: - -1. **File Discovery**: The registry scans `fle/eval/tasks/task_definitions/` -2. **JSON Parsing**: Task definitions are parsed from JSON files -3. **Environment Creation**: Gym environments are created for each task -4. **Registration**: Environments are registered with gym - -Example Task ------------- - -Here's a complete example of a custom task: - -**Task Definition** (`my_custom_task.json`): - -.. code-block:: json - - { - "name": "iron_plate_throughput", - "description": "Produce iron plates at 16 items per 60 seconds", - "type": "throughput", - "target": 16, - "time_limit": 3600, - "resources": { - "iron_ore": 10000, - "coal": 2000 - }, - "technologies": ["automation"], - "constraints": { - "max_entities": 50, - "max_power": 500 - } - } - -**Task Implementation** (`my_custom_task.py`): - -.. code-block:: python - - from fle.eval.tasks.base import BaseTask - from fle.env.game_types import Entity, Inventory - - class IronPlateThroughputTask(BaseTask): - def __init__(self, config): - super().__init__(config) - self.target = config.get('target', 16) - self.time_limit = config.get('time_limit', 3600) - self.start_time = None - - def reset(self): - """Reset the task state""" - self.start_time = None - return super().reset() - - def evaluate(self, state): - """Evaluate current throughput""" - if self.start_time is None: - self.start_time = state.get('game_info', {}).get('tick', 0) - - current_time = state.get('game_info', {}).get('tick', 0) - elapsed_time = (current_time - self.start_time) / 60.0 # Convert to seconds - - if elapsed_time < 60: - return 0.0 - - # Calculate throughput - inventory = state.get('inventory', Inventory({})) - iron_plates = inventory.get('iron-plate', 0) - throughput = iron_plates / elapsed_time - - return throughput - - def is_complete(self, state): - """Check if target throughput is achieved""" - throughput = self.evaluate(state) - return throughput >= self.target - - def get_reward(self, state): - """Calculate reward based on throughput""" - throughput = self.evaluate(state) - if throughput >= self.target: - return 1.0 - else: - return throughput / self.target - -Testing Tasks --------------- - -Create test cases for your custom tasks: - -.. code-block:: python - - import pytest - from fle.eval.tasks.my_custom_task import MyCustomTask - - def test_task_creation(): - config = { - 'target': 16, - 'time_limit': 3600 - } - task = MyCustomTask(config) - assert task.target == 16 - assert task.time_limit == 3600 - - def test_task_evaluation(): - config = {'target': 16} - task = MyCustomTask(config) - - # Mock state - state = { - 'inventory': Inventory({'iron-plate': 100}), - 'game_info': {'tick': 3600} - } - - throughput = task.evaluate(state) - assert throughput > 0 - - def test_task_completion(): - config = {'target': 16} - task = MyCustomTask(config) - - # Mock state with high throughput - state = { - 'inventory': Inventory({'iron-plate': 1000}), - 'game_info': {'tick': 3600} - } - - assert task.is_complete(state) - -Advanced Features ----------------- - -**Multi-Agent Tasks** - Tasks that require coordination between multiple agents - -**Dynamic Tasks** - Tasks that change objectives during execution - -**Hierarchical Tasks** - Tasks with sub-objectives and dependencies - -**Adaptive Tasks** - Tasks that adjust difficulty based on agent performance - -Best Practices --------------- - -1. **Clear Objectives**: Define clear, measurable objectives -2. **Appropriate Difficulty**: Balance challenge with achievability -3. **Robust Evaluation**: Handle edge cases and error conditions -4. **Comprehensive Testing**: Test all task scenarios -5. **Documentation**: Document task requirements and constraints -6. **Performance**: Optimize evaluation for large-scale experiments diff --git a/docs/sphinx/source/customization/tools.rst b/docs/sphinx/source/customization/tools.rst deleted file mode 100644 index edb30acbd..000000000 --- a/docs/sphinx/source/customization/tools.rst +++ /dev/null @@ -1,335 +0,0 @@ -Creating Custom Tools -===================== - -FLE allows you to create custom tools for extending agent capabilities. Tools provide a narrow API into the game and enable agents to perform specific actions. - -Tool Architecture ------------------ - -Tools require 3 files: - -1. **agent.md**: Documentation for the agent -2. **client.py**: Client-side Python implementation -3. **server.lua**: Server-side Lua implementation - -Tool Structure --------------- - -Create a new directory in `fle/env/tools/agent/`: - -.. code-block:: bash - - mkdir fle/env/tools/agent/my_tool - cd fle/env/tools/agent/my_tool - -**client.py** - Client-side implementation: - -.. code-block:: python - - from fle.env.tools.base import Tool - from typing import List, Optional - - class MyTool(Tool): - def __call__(self, param1: str, param2: int, param3: Optional[bool] = None) -> dict: - """ - My custom tool for doing something useful. - - Args: - param1: Description of param1 - param2: Description of param2 - param3: Optional parameter - - Returns: - Dictionary with results - """ - return self.execute({ - 'param1': param1, - 'param2': param2, - 'param3': param3 - }) - -**server.lua** - Server-side implementation: - -.. code-block:: lua - - global.actions.my_tool = function(param1, param2, param3) - -- Validate parameters - if not param1 or type(param1) ~= "string" then - return {error = "param1 must be a string"} - end - - if not param2 or type(param2) ~= "number" then - return {error = "param2 must be a number"} - end - - -- Perform the action - local result = {} - - -- Your custom logic here - -- Use Factorio API: https://lua-api.factorio.com/1.1.110/ - - return result - end - -**agent.md** - Agent documentation: - -.. code-block:: markdown - - # My Tool - - ## Overview - My custom tool for doing something useful in the game. - - ## Parameters - - `param1` (str): Description of param1 - - `param2` (int): Description of param2 - - `param3` (bool, optional): Optional parameter - - ## Returns - Dictionary with results including: - - `success` (bool): Whether the action succeeded - - `data` (dict): Additional data - - ## Examples - - ```python - # Basic usage - result = my_tool("value1", 42) - print(result['success']) - - # With optional parameter - result = my_tool("value1", 42, True) - ``` - - ## Best Practices - - Always check the return value for success - - Handle errors gracefully - - Use appropriate parameter types - - ## Failure Modes - - Invalid parameter types - - Game state conflicts - - Resource limitations - -Tool Development Process ------------------------- - -1. **Design the Interface** - - Define parameters and return types - - Consider error handling - - Plan for edge cases - -2. **Implement Client Side** - - Create Python class inheriting from Tool - - Implement __call__ method with type hints - - Call self.execute() with parameters - -3. **Implement Server Side** - - Create Lua function in global.actions - - Validate parameters - - Use Factorio API to perform actions - - Return structured results - -4. **Write Documentation** - - Document parameters and return values - - Provide usage examples - - Describe failure modes - - Include best practices - -5. **Test the Tool** - - Create test cases - - Verify error handling - - Test edge cases - - Validate performance - -Example Tool: Resource Scanner ------------------------------- - -Here's a complete example of a custom tool for scanning resources: - -**client.py**: - -.. code-block:: python - - from fle.env.tools.base import Tool - from typing import List, Dict, Optional - from fle.env.game_types import Position - - class ResourceScanner(Tool): - def __call__(self, center: Position, radius: int = 100, resource_type: Optional[str] = None) -> Dict: - """ - Scan for resources in a circular area. - - Args: - center: Center position for scanning - radius: Scan radius in tiles - resource_type: Specific resource type to scan for (optional) - - Returns: - Dictionary with scan results - """ - return self.execute({ - 'center': center, - 'radius': radius, - 'resource_type': resource_type - }) - -**server.lua**: - -.. code-block:: lua - - global.actions.resource_scanner = function(center, radius, resource_type) - -- Validate parameters - if not center or not center.x or not center.y then - return {error = "center must be a position with x and y"} - end - - if not radius or type(radius) ~= "number" or radius <= 0 then - return {error = "radius must be a positive number"} - end - - -- Get surface - local surface = game.surfaces[1] - if not surface then - return {error = "No surface available"} - end - - -- Scan for resources - local resources = {} - local center_pos = {x = center.x, y = center.y} - - for _, entity in pairs(surface.find_entities_filtered{ - area = {{center_pos.x - radius, center_pos.y - radius}, - {center_pos.x + radius, center_pos.y + radius}}, - type = "resource" - }) do - if not resource_type or entity.name == resource_type then - table.insert(resources, { - name = entity.name, - position = {x = entity.position.x, y = entity.position.y}, - amount = entity.amount - }) - end - end - - return { - success = true, - resources = resources, - count = #resources - } - end - -**agent.md**: - -.. code-block:: markdown - - # Resource Scanner - - ## Overview - Scans for resources in a circular area around a center position. - - ## Parameters - - `center` (Position): Center position for scanning - - `radius` (int): Scan radius in tiles (default: 100) - - `resource_type` (str, optional): Specific resource type to scan for - - ## Returns - Dictionary with: - - `success` (bool): Whether the scan succeeded - - `resources` (list): List of found resources - - `count` (int): Number of resources found - - ## Examples - - ```python - # Scan all resources in area - result = resource_scanner(Position(0, 0), 200) - print(f"Found {result['count']} resources") - - # Scan for specific resource - result = resource_scanner(Position(0, 0), 100, "iron-ore") - for resource in result['resources']: - print(f"{resource['name']} at {resource['position']}") - ``` - - ## Best Practices - - Use appropriate radius for your needs - - Filter by resource type when possible - - Handle empty results gracefully - - ## Failure Modes - - Invalid position coordinates - - Negative or zero radius - - Surface not available - - Resource type not found - -Testing Tools --------------- - -Create test cases for your custom tools: - -.. code-block:: python - - import pytest - from fle.env.tools.agent.my_tool import MyTool - from fle.env.game_types import Position - - def test_tool_creation(): - tool = MyTool() - assert tool is not None - - def test_tool_execution(): - tool = MyTool() - result = tool("test", 42, True) - assert 'success' in result - - def test_tool_error_handling(): - tool = MyTool() - result = tool("", -1) # Invalid parameters - assert 'error' in result - - def test_tool_with_position(): - tool = MyTool() - position = Position(10, 20) - result = tool("test", 42, position=position) - assert result['success'] - -Tool Registration ------------------ - -Tools are automatically discovered and registered: - -1. **File Discovery**: The system scans `fle/env/tools/agent/` -2. **Import Loading**: Python classes are imported -3. **Lua Loading**: Server-side functions are loaded -4. **Documentation**: Agent documentation is parsed -5. **Registration**: Tools are made available to agents - -Advanced Features ----------------- - -**Tool Dependencies** - Tools can depend on other tools - -**Tool Caching** - Cache expensive operations - -**Tool Validation** - Validate tool usage and parameters - -**Tool Metrics** - Collect usage statistics - -**Tool Versioning** - Handle tool updates and compatibility - -Best Practices --------------- - -1. **Clear Interface**: Design simple, intuitive interfaces -2. **Error Handling**: Provide meaningful error messages -3. **Documentation**: Write comprehensive documentation -4. **Testing**: Test all scenarios and edge cases -5. **Performance**: Optimize for efficiency -6. **Compatibility**: Ensure backward compatibility -7. **Security**: Validate all inputs and outputs diff --git a/docs/sphinx/source/environment/gym_registry.rst b/docs/sphinx/source/environment/gym_registry.rst new file mode 100644 index 000000000..d869c8200 --- /dev/null +++ b/docs/sphinx/source/environment/gym_registry.rst @@ -0,0 +1,335 @@ +Gym Environment Registry +======================== + +The Factorio Learning Environment uses a gym environment registry to automatically discover and register all available tasks. This allows you to use ``gym.make()`` to create environments and reference them by their environment IDs. + +Overview +-------- + +The registry system automatically discovers all task definitions in ``fle/eval/tasks/task_definitions/`` and registers them as gym environments. This means you can create any Factorio environment using the familiar ``gym.make()`` pattern. + +Features +-------- + +- **Automatic Discovery**: Automatically discovers all task definitions in ``fle/eval/tasks/task_definitions/`` +- **Gym Integration**: All environments are registered with ``gym`` and can be created using ``gym.make()`` +- **Task Metadata**: Provides access to task descriptions, configurations, and metadata +- **Multi-agent Support**: Supports both single-agent and multi-agent environments +- **Command-line Tools**: Built-in tools for exploring and testing environments + +Quick Start +----------- + +1. List Available Environments +~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ + +.. code-block:: python + + from fle.env.gym_env.registry import list_available_environments + + # Get all available environment IDs + env_ids = list_available_environments() + print(f"Available environments: {env_ids}") + +Or use the command-line tool: + +.. code-block:: bash + + python fle/env/gym_env/example_usage.py --list + +2. Create an Environment +~~~~~~~~~~~~~~~~~~~~~~~~~ + +.. code-block:: python + + import gym + + # Create any available environment + env = gym.make("iron_ore_throughput") + +3. Use the Environment +~~~~~~~~~~~~~~~~~~~~~~ + +.. code-block:: python + + from fle.env.gym_env.action import Action + + # Reset the environment + obs = env.reset(options={'game_state': None}) + + # Take an action + action = Action( + agent_idx=0, # Which agent takes the action + code='print("Hello Factorio!")', # Python code to execute + game_state=None # Optional: game state to reset to before running code + ) + + # Execute the action + obs, reward, terminated, truncated, info = env.step(action) + + # Clean up + env.close() + +Available Environments +---------------------- + +Throughput Tasks (Lab Play) +~~~~~~~~~~~~~~~~~~~~~~~~~~~~ + +All throughput tasks are defined in ``fle/eval/tasks/task_definitions/lab_play/throughput_tasks.py``. The 24 available tasks are: + +**Circuits** + +- ``advanced_circuit_throughput`` +- ``electronic_circuit_throughput`` +- ``processing_unit_throughput`` + +**Science Packs** + +- ``automation_science_pack_throughput`` +- ``logistics_science_pack_throughput`` +- ``chemical_science_pack_throughput`` +- ``military_science_pack_throughput`` +- ``production_science_pack_throughput`` +- ``utility_science_pack_throughput`` + +**Components** + +- ``battery_throughput`` +- ``engine_unit_throughput`` +- ``inserter_throughput`` +- ``iron_gear_wheel_throughput`` +- ``low_density_structure_throughput`` + +**Raw Materials** + +- ``iron_ore_throughput`` +- ``iron_plate_throughput`` +- ``steel_plate_throughput`` +- ``plastic_bar_throughput`` + +**Oil & Chemicals** + +- ``crude_oil_throughput`` +- ``petroleum_gas_throughput`` +- ``sulfuric_acid_throughput`` +- ``sulfur_throughput`` + +**Military** + +- ``piercing_round_throughput`` +- ``stone_wall_throughput`` + +.. note:: + Most tasks require 16 items per 60 seconds; fluid tasks require 250 units per 60 seconds. + +Open Play Environment +~~~~~~~~~~~~~~~~~~~~~ + +- ``open_play`` - An unbounded task of building the largest possible factory + +Example Usage +~~~~~~~~~~~~~ + +.. code-block:: python + + import gym + + # Create throughput environments + env = gym.make("iron_plate_throughput") + env = gym.make("automation_science_pack_throughput") + env = gym.make("crude_oil_throughput") + + # Create open play environment + env = gym.make("open_play") + +Command-Line Tools +------------------ + +The ``example_usage.py`` script provides both interactive examples and command-line tools: + +.. code-block:: bash + + # Run interactive examples + python fle/env/gym_env/example_usage.py + + # List all environments + python fle/env/gym_env/example_usage.py --list + + # Show detailed information + python fle/env/gym_env/example_usage.py --detail + + # Search for specific environments + python fle/env/gym_env/example_usage.py --search iron + + # Output in gym.make() format + python fle/env/gym_env/example_usage.py --gym-format + +Environment Interface +--------------------- + +Action Space +~~~~~~~~~~~~ + +.. code-block:: python + + { + 'agent_idx': Discrete(instance.num_agents), # Index of the agent taking the action + 'game_state': Text(max_length=1000000), # Optional: game state to reset to + 'code': Text(max_length=10000) # Python code to execute + } + +Observation Space +~~~~~~~~~~~~~~~~~ + +The observation space includes: + +- ``raw_text``: Output from the last action +- ``entities``: List of entities on the map +- ``inventory``: Current inventory state +- ``research``: Research progress and technologies +- ``game_info``: Game state (tick, time, speed) +- ``score``: Current score +- ``flows``: Production statistics +- ``task_verification``: Task completion status +- ``messages``: Inter-agent messages +- ``serialized_functions``: Available functions +- ``task_info``: Information about the task +- ``map_image``: Base64 encoded PNG image + +Methods +~~~~~~~ + +.. code-block:: python + + # Reset the environment + reset(options: Dict[str, Any], seed: Optional[int] = None) -> Dict[str, Any] + + # Take a step + step(action: Action) -> Tuple[Dict[str, Any], float, bool, bool, Dict[str, Any]] + + # Clean up + close() -> None + +API Reference +------------- + +Registry Functions +~~~~~~~~~~~~~~~~~~ + +.. code-block:: python + + # Returns a list of all registered environment IDs + list_available_environments() -> List[str] + + # Returns detailed information about a specific environment + get_environment_info(env_id: str) -> Optional[Dict[str, Any]] + + # Manually trigger environment discovery and registration + register_all_environments() -> None + +Environment Creation +~~~~~~~~~~~~~~~~~~~~ + +.. code-block:: python + + # Creates a Factorio gym environment + gym.make(env_id: str, **kwargs) -> FactorioGymEnv + +Complete Example +---------------- + +Here's a complete example that demonstrates the full workflow: + +.. code-block:: python + + import gym + from fle.env.gym_env.registry import list_available_environments, get_environment_info + from fle.env.gym_env.action import Action + + # 1. List available environments + env_ids = list_available_environments() + print(f"Found {len(env_ids)} environments") + + # 2. Get information about a specific environment + info = get_environment_info("iron_ore_throughput") + print(f"Description: {info['description']}") + + # 3. Create the environment + env = gym.make("iron_ore_throughput") + + # 4. Use the environment + obs = env.reset(options={'game_state': None}) + print(f"Initial observation keys: {list(obs.keys())}") + + # 5. Take actions + current_state = None + for step in range(5): + action = Action( + agent_idx=0, + game_state=current_state, + code=f'print("Step {step}: Hello Factorio!")' + ) + obs, reward, terminated, truncated, info = env.step(action) + done = terminated or truncated + current_state = info['output_game_state'] + print(f"Step {step}: Reward={reward}, Done={done}") + + if done: + break + + # 6. Clean up + env.close() + +Error Handling +-------------- + +The registry includes error handling for: + +- Missing task definition files +- Invalid JSON configurations +- Missing Factorio containers +- Environment creation failures + +If an environment fails to load, a warning will be printed but the registry will continue to load other environments. + +Troubleshooting +--------------- + +Environment Creation Fails +~~~~~~~~~~~~~~~~~~~~~~~~~~ + +If ``gym.make()`` fails with connection errors: + +1. Ensure Factorio containers are running +2. Check that the cluster setup is working +3. Verify network connectivity + +No Environments Found +~~~~~~~~~~~~~~~~~~~~~ + +If no environments are listed: + +1. Check that the task definitions directory exists +2. Verify JSON files are valid +3. Check file permissions + +Import Errors +~~~~~~~~~~~~~ + +If you get import errors: + +1. Ensure you're running from the correct directory +2. Check that all dependencies are installed +3. Verify the Python path includes the project root + +Testing +------- + +Run the test suite to verify the registry is working correctly: + +.. code-block:: bash + + python fle/env/tests/gym_env/test_registry.py + +This registry system provides a clean, standardized interface for working with Factorio gym environments, making it easy to experiment with different tasks and integrate with existing gym-based frameworks. diff --git a/docs/sphinx/source/environment/overview.rst b/docs/sphinx/source/environment/overview.rst new file mode 100644 index 000000000..56320c8d8 --- /dev/null +++ b/docs/sphinx/source/environment/overview.rst @@ -0,0 +1,240 @@ +Environment Overview +==================== + +FLE is an agent evaluation environment built on the game of Factorio, a popular resource management simulation game. + +The REPL Pattern +----------------- + +Agents interact with FLE through code synthesis using a **REPL** (Read-Eval-Print-Loop) pattern: + +1. **Observation**: The agent observes the world through the output streams (stderr/stdout) of their last program +2. **Action**: The agent generates a Python program to perform their desired action +3. **Feedback**: The environment executes the program, assigns variables, adds classes/functions to the namespace, and provides an output stream + +Example Interaction +~~~~~~~~~~~~~~~~~~~ + +**Action:** + +.. code-block:: python + + # 1. Get iron patch and place mining drill + drill = place_entity( + entity=Prototype.MiningDrill, + position=nearest(Resource.IronOre), + direction=Direction.NORTH + ) + # 2. Add output storage + chest = place_entity_next_to( + entity=Prototype.IronChest, + reference_position=drill.drop_position, + direction=Direction.SOUTH + ) + # 3. Verify automation chain and observe entities + sleep(10) # Sleep for 10 seconds + assert drill.status == EntityStatus.WORKING + print(get_entities()) + +**Feedback:** + +.. code-block:: python + + >>> [ BurnerMiningDrill(fuel=Inventory({'coal': 4}), + >>> name='burner-mining-drill', + >>> direction=Direction.DOWN, + >>> position=Position(x=-28.0, y=-61.0), + >>> energy=2666.6666666667, + >>> tile_dimensions=TileDimensions(tile_width=2.0, tile_height=2.0), + >>> status=EntityStatus.WORKING, + >>> neighbours=[Entity(name='iron-chest', direction=DOWN, position=Position(x=-27.5 y=-59.5)], + >>> drop_position=Position(x=-27.5, y=-59.5), + >>> resources=[Ingredient(name='iron-ore', count=30000, type=None)]), + >>> Chest(name='iron-chest', + >>> direction=Direction.UP, + >>> position=Position(x=-27.5, y=-59.5), + >>> energy=0.0, + >>> tile_dimensions=TileDimensions(tile_width=1.0, tile_height=1.0), + >>> status=EntityStatus.NORMAL, + >>> inventory=Inventory({'iron-ore': 75}))] + +Available Tools +--------------- + +Agents are provided with the Python standard library and an API comprising :doc:`../tools/overview` that they can use. + +**Tools** are functions that: + +- Perform a game action +- Return a typed object (e.g. an ``Inventory``) +- Can be stored as a named **variable** in the Python namespace for later use + +The Namespace +------------- + +The namespace acts as an **episodic symbolic memory system**. Saved objects represent an observation of the environment at the moment of query. + +This enables agents to: + +- Maintain complex state representations +- Build hierarchical abstractions as factories scale +- Reference previous observations and computations + +Observations +------------ + +Agents observe **stdout** and **stderr** - the output streams of their program. + +Agents may intentionally: + +- Print relevant objects to construct observations +- Print computations and intermediate results +- Use ``print()`` strategically to monitor state + +Error Handling +-------------- + +Mistakes in code or invalid operations raise typed **exceptions** with detailed context that is written to stderr. + +This enables agents to: + +- **Reactively debug** their programs after execution +- **Proactively use** runtime assertions during execution to self-verify actions +- Learn from detailed error messages + +Custom Functions and Classes +----------------------------- + +Agents can enhance their internal representation of the game state by defining: + +1. **Utility functions** for reuse throughout an episode, to encapsulate previously successful logic +2. **Classes** in the namespace to better organize the data retrieved from the game + +These definitions persist in the namespace across actions within an episode. + +Action Space +------------ + +The action space is defined as: + +.. code-block:: python + + { + 'agent_idx': Discrete(instance.num_agents), # Index of the agent taking the action + 'game_state': Text(max_length=1000000), # Optional: game state to reset to + 'code': Text(max_length=10000) # Python code to execute + } + +Observation Space +----------------- + +The observation space includes: + +- ``raw_text``: Output from the last action +- ``entities``: List of entities on the map +- ``inventory``: Current inventory state +- ``research``: Research progress and technologies +- ``game_info``: Game state (tick, time, speed) +- ``score``: Current score +- ``flows``: Production statistics +- ``task_verification``: Task completion status +- ``messages``: Inter-agent messages (for multi-agent scenarios) +- ``serialized_functions``: Available functions +- ``task_info``: Information about the task +- ``map_image``: Base64 encoded PNG image + +Environment Methods +------------------- + +Standard Gym Interface +~~~~~~~~~~~~~~~~~~~~~~ + +All FLE environments follow the standard OpenAI Gym interface: + +.. code-block:: python + + # Reset the environment + obs = env.reset(options: Dict[str, Any], seed: Optional[int] = None) -> Dict[str, Any] + + # Take a step + obs, reward, terminated, truncated, info = env.step(action: Action) + + # Clean up + env.close() + +Architecture +------------ + +.. code-block:: text + + ┌─────────────────┐ + │ Agent │ + │ (Synthesizes │ + │ Python Code) │ + └────────┬────────┘ + │ + ▼ + ┌─────────────────────────────┐ + │ Learning Environment │ + │ ┌─────────────────────┐ │ + │ │ Interpreter │ │ + │ │ - Executes code │ │ + │ │ - Manages │ │ + │ │ namespace │ │ + │ └──────┬──────────────┘ │ + │ │ │ + │ ┌──────▼──────────────┐ │ + │ │ client.py │ │ + │ │ (Tool Interface) │ │ + │ └──────┬──────────────┘ │ + └─────────┼──────────────────┘ + │ Remote TCP Call + ▼ + ┌─────────────────────────────┐ + │ Factorio Server │ + │ ┌─────────────────────┐ │ + │ │ server.lua │ │ + │ │ (Game Logic) │ │ + │ └──────┬──────────────┘ │ + │ │ │ + │ ┌──────▼──────────────┐ │ + │ │ Factorio Engine │ │ + │ │ (Game Simulation) │ │ + │ └─────────────────────┘ │ + └─────────────────────────────┘ + +Task Types +---------- + +FLE provides two main evaluation settings: + +Lab-Play +~~~~~~~~ + +24 structured tasks with fixed resources, testing specific capabilities: + +- **Circuits**: Advanced circuits, electronic circuits, processing units +- **Science Packs**: Automation, logistics, chemical, military, production, utility +- **Components**: Batteries, engines, inserters, gears, low density structures +- **Raw Materials**: Iron ore, iron plates, steel plates, plastic bars +- **Oil & Chemicals**: Crude oil, petroleum gas, sulfuric acid, sulfur +- **Military**: Piercing rounds, stone walls + +Most tasks require 16 items per 60 seconds; fluid tasks require 250 units per 60 seconds. + +Open-Play +~~~~~~~~~ + +An unbounded task of building the largest possible factory on a procedurally generated map. This tests: + +- Long-term planning +- Resource optimization +- Scaling strategies +- Error recovery + +Next Steps +---------- + +- Explore the :doc:`gym_registry` to see all available tasks +- Learn about :doc:`../tools/overview` available to agents +- See :doc:`../getting_started/quickstart` for usage examples diff --git a/docs/sphinx/source/examples/basic_agent.rst b/docs/sphinx/source/examples/basic_agent.rst deleted file mode 100644 index 4cb57aa84..000000000 --- a/docs/sphinx/source/examples/basic_agent.rst +++ /dev/null @@ -1,336 +0,0 @@ -Basic Agent Example -=================== - -This example demonstrates how to create a basic agent that interacts with the Factorio Learning Environment. - -Agent Overview --------------- - -The basic agent performs simple resource collection and automation tasks: - -1. **Resource Discovery**: Find and identify available resources -2. **Mining Setup**: Place mining drills on resource patches -3. **Storage Management**: Create storage for collected resources -4. **Automation**: Set up basic automation chains - -Agent Implementation --------------------- - -.. code-block:: python - - from fle.agents.agent_abc import Agent - from fle.env.gym_env.action import Action - from fle.env.game_types import Position, Direction - from typing import Dict, Any, List - - class BasicAgent(Agent): - def __init__(self, config: Dict[str, Any]): - super().__init__(config) - self.name = "BasicAgent" - self.target_resources = ['iron-ore', 'copper-ore', 'coal'] - self.mining_setups = [] - self.step_count = 0 - - def act(self, observation: Dict[str, Any]) -> Action: - """Generate action based on current observation""" - self.step_count += 1 - - # Get current state - entities = observation.get('entities', []) - inventory = observation.get('inventory', {}) - game_info = observation.get('game_info', {}) - - # Generate action code - if self.step_count == 1: - code = self._initial_setup() - elif self.step_count <= 10: - code = self._setup_mining() - else: - code = self._monitor_and_optimize(entities, inventory) - - return Action( - agent_idx=0, - code=code, - game_state=None - ) - - def _initial_setup(self) -> str: - """Initial setup and exploration""" - return ''' - # Initial setup and exploration - print("Starting BasicAgent exploration") - - # Get current position - position = get_position() - print(f"Starting position: {position}") - - # Explore the area - entities = get_entities() - print(f"Found {len(entities)} entities") - - # Look for resources - iron_pos = nearest(Resource.IRON_ORE) - copper_pos = nearest(Resource.COPPER_ORE) - coal_pos = nearest(Resource.COAL) - - print(f"Iron ore at: {iron_pos}") - print(f"Copper ore at: {copper_pos}") - print(f"Coal at: {coal_pos}") - ''' - - def _setup_mining(self) -> str: - """Set up mining operations""" - return ''' - # Set up mining operations - print("Setting up mining operations") - - # Find and place mining drills - iron_pos = nearest(Resource.IRON_ORE) - if iron_pos: - drill = place_entity( - entity=Prototype.MiningDrill, - position=iron_pos, - direction=Direction.NORTH - ) - print(f"Placed mining drill at {iron_pos}") - - # Add storage chest - chest = place_entity_next_to( - entity=Prototype.IronChest, - reference_position=drill.drop_position, - direction=Direction.SOUTH - ) - print(f"Placed chest at {chest.position}") - - # Check inventory - inventory = inspect_inventory() - print(f"Current inventory: {inventory}") - ''' - - def _monitor_and_optimize(self, entities: List, inventory: Dict) -> str: - """Monitor and optimize operations""" - return ''' - # Monitor and optimize operations - print("Monitoring operations") - - # Check all entities - entities = get_entities() - working_entities = [e for e in entities if hasattr(e, 'status') and e.status == EntityStatus.WORKING] - print(f"Working entities: {len(working_entities)}") - - # Check inventory - inventory = inspect_inventory() - total_items = sum(inventory.values()) - print(f"Total items in inventory: {total_items}") - - # Print detailed inventory - for item, count in inventory.items(): - if count > 0: - print(f" {item}: {count}") - - # Check for any issues - for entity in entities: - if hasattr(entity, 'status') and entity.status == EntityStatus.NO_POWER: - print(f"Entity {entity.name} needs power") - elif hasattr(entity, 'status') and entity.status == EntityStatus.NO_FUEL: - print(f"Entity {entity.name} needs fuel") - ''' - -Running the Agent ------------------ - -**Environment Setup** - .. code-block:: python - - import gym - from fle.agents.basic_agent import BasicAgent - - # Create environment - env = gym.make("iron_ore_throughput") - - # Create agent - agent = BasicAgent({}) - - # Run episode - obs = env.reset() - done = False - step = 0 - - while not done and step < 100: - action = agent.act(obs) - obs, reward, terminated, truncated, info = env.step(action) - done = terminated or truncated - step += 1 - print(f"Step {step}: Reward = {reward}") - - env.close() - -**Command Line Usage** - .. code-block:: bash - - # Run basic agent evaluation - fle eval --agent basic_agent --config configs/basic_agent_config.json - -Agent Configuration -------------------- - -**Basic Configuration** - .. code-block:: json - - { - "agent_type": "BasicAgent", - "config": { - "target_resources": ["iron-ore", "copper-ore", "coal"], - "max_mining_setups": 5, - "monitoring_interval": 10 - }, - "evaluation": { - "episodes": 5, - "max_steps": 1000, - "success_threshold": 0.5 - } - } - -**Advanced Configuration** - .. code-block:: json - - { - "agent_type": "BasicAgent", - "config": { - "target_resources": ["iron-ore", "copper-ore", "coal", "stone"], - "max_mining_setups": 10, - "monitoring_interval": 5, - "optimization_enabled": true, - "debug_mode": true - }, - "evaluation": { - "episodes": 10, - "max_steps": 2000, - "success_threshold": 0.8, - "metrics": ["throughput", "efficiency", "resource_utilization"] - } - } - -Agent Behavior --------------- - -**Phase 1: Exploration (Steps 1-5)** - - Explore the starting area - - Identify available resources - - Plan mining operations - -**Phase 2: Setup (Steps 6-15)** - - Place mining drills on resource patches - - Create storage chests - - Set up basic automation - -**Phase 3: Monitoring (Steps 16+)** - - Monitor entity status - - Check inventory levels - - Optimize operations - -Example Output --------------- - -**Step 1: Initial Setup** - .. code-block:: - - Starting BasicAgent exploration - Starting position: Position(x=0.0, y=0.0) - Found 0 entities - Iron ore at: Position(x=-28.0, y=-61.0) - Copper ore at: Position(x=45.0, y=-30.0) - Coal at: Position(x=-15.0, y=20.0) - -**Step 5: Mining Setup** - .. code-block:: - - Setting up mining operations - Placed mining drill at Position(x=-28.0, y=-61.0) - Placed chest at Position(x=-27.5, y=-59.5) - Current inventory: {'iron-ore': 0, 'coal': 4} - -**Step 20: Monitoring** - .. code-block:: - - Monitoring operations - Working entities: 1 - Total items in inventory: 75 - iron-ore: 75 - coal: 4 - -Performance Metrics -------------------- - -**Throughput** - - Items produced per minute - - Resource utilization efficiency - - Automation chain performance - -**Efficiency** - - Power consumption per item - - Entity utilization rate - - Resource waste minimization - -**Reliability** - - System uptime - - Error rate - - Recovery time - -Example Metrics -~~~~~~~~~~~~~~~ - -.. code-block:: python - - { - "throughput": { - "iron_ore": 2.5, # items per minute - "copper_ore": 1.8, - "coal": 3.2 - }, - "efficiency": { - "power_usage": 0.8, # normalized power usage - "entity_utilization": 0.75, # fraction of entities working - "resource_waste": 0.05 # fraction of resources wasted - }, - "reliability": { - "uptime": 0.95, # fraction of time system is working - "error_rate": 0.02, # errors per step - "recovery_time": 5.0 # average recovery time in steps - } - } - -Troubleshooting ---------------- - -**Common Issues** - - **No resources found**: Check map generation and resource placement - - **Mining drills not working**: Verify power and fuel supply - - **Inventory full**: Add more storage or optimize collection - -**Debug Mode** - Enable debug mode for detailed logging: - - .. code-block:: json - - { - "config": { - "debug_mode": true, - "log_level": "DEBUG" - } - } - -**Performance Issues** - - Monitor entity count and performance - - Check for resource bottlenecks - - Optimize automation chains - -Best Practices --------------- - -1. **Start Simple**: Begin with basic operations -2. **Monitor Progress**: Track performance metrics -3. **Handle Errors**: Implement error recovery -4. **Optimize Gradually**: Improve efficiency over time -5. **Test Thoroughly**: Validate all scenarios -6. **Document Behavior**: Record agent decisions diff --git a/docs/sphinx/source/examples/multiagent.rst b/docs/sphinx/source/examples/multiagent.rst deleted file mode 100644 index 4d813e7dd..000000000 --- a/docs/sphinx/source/examples/multiagent.rst +++ /dev/null @@ -1,565 +0,0 @@ -Multi-Agent Example -=================== - -This example demonstrates how to create and coordinate multiple agents in the Factorio Learning Environment. - -Multi-Agent Overview -------------------- - -Multi-agent systems in FLE enable: - -1. **Agent Coordination**: Multiple agents working together -2. **Task Distribution**: Dividing tasks among agents -3. **Communication**: Inter-agent message passing -4. **Collaborative Planning**: Joint decision making - -Agent Architecture ------------------- - -**Agent Roles** - - **Coordinator**: Manages overall strategy - - **Resource Specialist**: Handles resource collection - - **Construction Specialist**: Manages building operations - - **Research Specialist**: Handles technology advancement - -**Communication Protocol** - - Message passing between agents - - Shared state information - - Task assignment and reporting - - Conflict resolution - -Multi-Agent Implementation -------------------------- - -.. code-block:: python - - from fle.agents.agent_abc import Agent - from fle.env.gym_env.action import Action - from fle.env.game_types import Position, Direction - from typing import Dict, Any, List - import json - - class MultiAgentCoordinator(Agent): - def __init__(self, config: Dict[str, Any]): - super().__init__(config) - self.name = "MultiAgentCoordinator" - self.agent_count = config.get('agent_count', 3) - self.agents = self._initialize_agents(config) - self.shared_state = {} - self.task_queue = [] - self.step_count = 0 - - def _initialize_agents(self, config: Dict[str, Any]) -> List[Agent]: - """Initialize specialized agents""" - agents = [] - - # Resource specialist - agents.append(ResourceSpecialist({ - 'role': 'resource_specialist', - 'target_resources': ['iron-ore', 'copper-ore', 'coal'] - })) - - # Construction specialist - agents.append(ConstructionSpecialist({ - 'role': 'construction_specialist', - 'building_types': ['assembling-machine', 'furnace', 'lab'] - })) - - # Research specialist - agents.append(ResearchSpecialist({ - 'role': 'research_specialist', - 'research_priorities': ['automation', 'logistics', 'production'] - })) - - return agents - - def act(self, observation: Dict[str, Any]) -> Action: - """Coordinate multi-agent actions""" - self.step_count += 1 - - # Get messages from other agents - messages = observation.get('messages', []) - - # Process messages and update shared state - self._process_messages(messages) - - # Coordinate agent actions - if self.step_count == 1: - code = self._initial_coordination() - elif self.step_count <= 20: - code = self._task_distribution() - else: - code = self._monitoring_and_optimization() - - return Action( - agent_idx=0, - code=code, - game_state=None - ) - - def _process_messages(self, messages: List[Dict[str, Any]]): - """Process messages from other agents""" - for message in messages: - if message['type'] == 'task_completion': - self._handle_task_completion(message) - elif message['type'] == 'resource_request': - self._handle_resource_request(message) - elif message['type'] == 'coordination_request': - self._handle_coordination_request(message) - - def _initial_coordination(self) -> str: - """Initial coordination and planning""" - return ''' - # Initial multi-agent coordination - print("Starting multi-agent coordination") - - # Send initial messages to all agents - send_message({ - 'type': 'coordination_start', - 'content': 'Beginning multi-agent coordination', - 'target_agents': 'all' - }) - - # Analyze current state - entities = get_entities() - inventory = inspect_inventory() - - print(f"Current state: {len(entities)} entities, {sum(inventory.values())} items") - - # Plan initial tasks - tasks = [ - {'type': 'resource_collection', 'priority': 'high', 'agent': 'resource_specialist'}, - {'type': 'basic_setup', 'priority': 'medium', 'agent': 'construction_specialist'}, - {'type': 'research_planning', 'priority': 'low', 'agent': 'research_specialist'} - ] - - print(f"Planned tasks: {tasks}") - ''' - - def _task_distribution(self) -> str: - """Distribute tasks among agents""" - return ''' - # Task distribution and coordination - print("Distributing tasks among agents") - - # Check for available resources - iron_pos = nearest(Resource.IRON_ORE) - copper_pos = nearest(Resource.COPPER_ORE) - - if iron_pos: - # Assign resource collection task - send_message({ - 'type': 'task_assignment', - 'content': { - 'task': 'collect_iron_ore', - 'location': str(iron_pos), - 'priority': 'high' - }, - 'target_agents': ['resource_specialist'] - }) - - if copper_pos: - # Assign copper collection task - send_message({ - 'type': 'task_assignment', - 'content': { - 'task': 'collect_copper_ore', - 'location': str(copper_pos), - 'priority': 'medium' - }, - 'target_agents': ['resource_specialist'] - }) - - # Check construction needs - entities = get_entities() - if len(entities) < 5: - send_message({ - 'type': 'task_assignment', - 'content': { - 'task': 'build_infrastructure', - 'requirements': ['mining_drill', 'chest', 'furnace'], - 'priority': 'high' - }, - 'target_agents': ['construction_specialist'] - }) - ''' - - def _monitoring_and_optimization(self) -> str: - """Monitor and optimize multi-agent operations""" - return ''' - # Multi-agent monitoring and optimization - print("Monitoring multi-agent operations") - - # Check agent status - entities = get_entities() - inventory = inspect_inventory() - - print(f"Current state: {len(entities)} entities, {sum(inventory.values())} items") - - # Check for coordination issues - working_entities = [e for e in entities if hasattr(e, 'status') and e.status == EntityStatus.WORKING] - print(f"Working entities: {len(working_entities)}") - - # Send status updates - send_message({ - 'type': 'status_update', - 'content': { - 'entities': len(entities), - 'inventory': sum(inventory.values()), - 'working_entities': len(working_entities) - }, - 'target_agents': 'all' - }) - - # Check for optimization opportunities - if len(working_entities) < len(entities) * 0.8: - send_message({ - 'type': 'optimization_request', - 'content': 'System efficiency below 80%', - 'target_agents': 'all' - }) - ''' - -Specialized Agents ------------------- - -**Resource Specialist** - .. code-block:: python - - class ResourceSpecialist(Agent): - def __init__(self, config: Dict[str, Any]): - super().__init__(config) - self.name = "ResourceSpecialist" - self.target_resources = config.get('target_resources', []) - self.mining_setups = [] - - def act(self, observation: Dict[str, Any]) -> Action: - """Handle resource collection tasks""" - messages = observation.get('messages', []) - - # Process task assignments - for message in messages: - if message['type'] == 'task_assignment': - task = message['content'] - if task['task'].startswith('collect_'): - return self._handle_collection_task(task) - - # Default resource collection behavior - return self._default_resource_behavior() - - def _handle_collection_task(self, task: Dict[str, Any]) -> Action: - """Handle specific collection tasks""" - resource_type = task['task'].split('_')[1] - location = task.get('location') - - code = f''' - # Handle collection task: {task['task']} - print("Resource specialist handling collection task") - - # Find and collect {resource_type} - resource_pos = nearest(Resource.{resource_type.upper().replace('-', '_')}) - if resource_pos: - drill = place_entity( - entity=Prototype.MiningDrill, - position=resource_pos, - direction=Direction.NORTH - ) - print(f"Placed mining drill for {resource_type} at {resource_pos}") - - # Report task completion - send_message({{ - 'type': 'task_completion', - 'content': {{ - 'task': '{task['task']}', - 'status': 'completed', - 'location': str(resource_pos) - }}, - 'target_agents': ['coordinator'] - }}) - ''' - - return Action(agent_idx=1, code=code, game_state=None) - -**Construction Specialist** - .. code-block:: python - - class ConstructionSpecialist(Agent): - def __init__(self, config: Dict[str, Any]): - super().__init__(config) - self.name = "ConstructionSpecialist" - self.building_types = config.get('building_types', []) - self.construction_queue = [] - - def act(self, observation: Dict[str, Any]) -> Action: - """Handle construction tasks""" - messages = observation.get('messages', []) - - # Process construction requests - for message in messages: - if message['type'] == 'task_assignment': - task = message['content'] - if task['task'] == 'build_infrastructure': - return self._handle_infrastructure_task(task) - - # Default construction behavior - return self._default_construction_behavior() - - def _handle_infrastructure_task(self, task: Dict[str, Any]) -> Action: - """Handle infrastructure construction""" - requirements = task.get('requirements', []) - - code = f''' - # Handle infrastructure construction - print("Construction specialist building infrastructure") - - # Build required entities - entities = get_entities() - current_types = [e.name for e in entities] - - for requirement in {requirements}: - if requirement not in current_types: - # Build the required entity - if requirement == 'mining_drill': - resource_pos = nearest(Resource.IRON_ORE) - if resource_pos: - drill = place_entity( - entity=Prototype.MiningDrill, - position=resource_pos, - direction=Direction.NORTH - ) - print(f"Built {requirement} at {resource_pos}") - - elif requirement == 'chest': - # Place chest near existing entities - if entities: - reference = entities[0] - chest = place_entity_next_to( - entity=Prototype.IronChest, - reference_position=reference.position, - direction=Direction.SOUTH - ) - print(f"Built {requirement} at {chest.position}") - - # Report construction completion - send_message({{ - 'type': 'task_completion', - 'content': {{ - 'task': 'build_infrastructure', - 'status': 'completed', - 'entities_built': len(get_entities()) - }}, - 'target_agents': ['coordinator'] - }}) - ''' - - return Action(agent_idx=2, code=code, game_state=None) - -**Research Specialist** - .. code-block:: python - - class ResearchSpecialist(Agent): - def __init__(self, config: Dict[str, Any]): - super().__init__(config) - self.name = "ResearchSpecialist" - self.research_priorities = config.get('research_priorities', []) - self.research_queue = [] - - def act(self, observation: Dict[str, Any]) -> Action: - """Handle research tasks""" - messages = observation.get('messages', []) - - # Process research requests - for message in messages: - if message['type'] == 'task_assignment': - task = message['content'] - if task['task'] == 'research_planning': - return self._handle_research_planning(task) - - # Default research behavior - return self._default_research_behavior() - - def _handle_research_planning(self, task: Dict[str, Any]) -> Action: - """Handle research planning tasks""" - code = ''' - # Handle research planning - print("Research specialist planning research") - - # Check current research status - research = get_research_progress() - print(f"Current research: {research}") - - # Plan research priorities - priorities = ['automation', 'logistics', 'production'] - for priority in priorities: - if priority not in research.get('completed', []): - # Start research - result = set_research(priority) - if result: - print(f"Started research: {priority}") - break - - # Report research status - send_message({ - 'type': 'task_completion', - 'content': { - 'task': 'research_planning', - 'status': 'completed', - 'research_started': priority - }, - 'target_agents': ['coordinator'] - }) - ''' - - return Action(agent_idx=3, code=code, game_state=None) - -Running Multi-Agent Systems ---------------------------- - -**Environment Setup** - .. code-block:: python - - import gym - from fle.agents.multiagent_coordinator import MultiAgentCoordinator - - # Create environment - env = gym.make("iron_ore_throughput") - - # Create multi-agent coordinator - coordinator = MultiAgentCoordinator({ - 'agent_count': 3, - 'coordination_enabled': True, - 'communication_enabled': True - }) - - # Run episode - obs = env.reset() - done = False - step = 0 - - while not done and step < 100: - action = coordinator.act(obs) - obs, reward, terminated, truncated, info = env.step(action) - done = terminated or truncated - step += 1 - print(f"Step {step}: Reward = {reward}") - - env.close() - -**Command Line Usage** - .. code-block:: bash - - # Run multi-agent evaluation - fle eval --agent multiagent_coordinator --config configs/multiagent_config.json - -Multi-Agent Configuration -------------------------- - -**Basic Configuration** - .. code-block:: json - - { - "agent_type": "MultiAgentCoordinator", - "config": { - "agent_count": 3, - "coordination_enabled": true, - "communication_enabled": true, - "task_distribution": "round_robin" - }, - "evaluation": { - "episodes": 5, - "max_steps": 1000, - "success_threshold": 0.7 - } - } - -**Advanced Configuration** - .. code-block:: json - - { - "agent_type": "MultiAgentCoordinator", - "config": { - "agent_count": 5, - "coordination_enabled": true, - "communication_enabled": true, - "task_distribution": "priority_based", - "conflict_resolution": "voting", - "shared_state_size": 1000, - "message_timeout": 30 - }, - "evaluation": { - "episodes": 10, - "max_steps": 2000, - "success_threshold": 0.8, - "metrics": ["coordination_effectiveness", "communication_efficiency", "task_completion_rate"] - } - } - -Performance Metrics -------------------- - -**Coordination Effectiveness** - - Task completion rate - - Coordination efficiency - - Conflict resolution success - -**Communication Efficiency** - - Message delivery rate - - Communication latency - - Message processing time - -**Multi-Agent Performance** - - Overall system performance - - Agent specialization effectiveness - - Collaborative planning success - -Example Metrics -~~~~~~~~~~~~~~~ - -.. code-block:: python - - { - "coordination_effectiveness": { - "task_completion_rate": 0.85, # fraction of tasks completed - "coordination_efficiency": 0.75, # fraction of coordinated actions - "conflict_resolution_success": 0.90 # fraction of conflicts resolved - }, - "communication_efficiency": { - "message_delivery_rate": 0.95, # fraction of messages delivered - "communication_latency": 0.1, # average latency in seconds - "message_processing_time": 0.05 # average processing time in seconds - }, - "multi_agent_performance": { - "overall_system_performance": 0.80, # overall system effectiveness - "agent_specialization_effectiveness": 0.85, # effectiveness of specialization - "collaborative_planning_success": 0.70 # success rate of collaborative plans - } - } - -Troubleshooting ---------------- - -**Coordination Issues** - - **Task conflicts**: Implement conflict resolution - - **Communication failures**: Check message delivery - - **Coordination breakdown**: Monitor coordination effectiveness - -**Performance Issues** - - **Slow coordination**: Optimize coordination algorithms - - **High communication overhead**: Reduce message frequency - - **Memory issues**: Limit shared state size - -**Agent Issues** - - **Agent failures**: Implement agent recovery - - **Specialization problems**: Adjust agent roles - - **Communication errors**: Handle message errors - -Best Practices --------------- - -1. **Clear Roles**: Define clear agent roles and responsibilities -2. **Effective Communication**: Implement efficient communication protocols -3. **Conflict Resolution**: Handle conflicts between agents -4. **Performance Monitoring**: Monitor multi-agent performance -5. **Scalability**: Design for different numbers of agents -6. **Error Handling**: Implement robust error recovery -7. **Testing**: Test multi-agent coordination thoroughly diff --git a/docs/sphinx/source/examples/visual_agent.rst b/docs/sphinx/source/examples/visual_agent.rst deleted file mode 100644 index 70cb5ae8b..000000000 --- a/docs/sphinx/source/examples/visual_agent.rst +++ /dev/null @@ -1,450 +0,0 @@ -Visual Agent Example -==================== - -This example demonstrates how to create a visual agent that processes visual information from the game environment. - -Agent Overview --------------- - -The visual agent uses computer vision techniques to: - -1. **Image Processing**: Analyze game screenshots and map images -2. **Object Detection**: Identify entities and resources in the visual data -3. **Spatial Reasoning**: Understand spatial relationships between objects -4. **Visual Planning**: Plan actions based on visual information - -Agent Implementation --------------------- - -.. code-block:: python - - from fle.agents.agent_abc import Agent - from fle.env.gym_env.action import Action - from fle.env.game_types import Position, Direction - from typing import Dict, Any, List - import base64 - import io - from PIL import Image - import numpy as np - - class VisualAgent(Agent): - def __init__(self, config: Dict[str, Any]): - super().__init__(config) - self.name = "VisualAgent" - self.vision_enabled = config.get('vision_enabled', True) - self.image_processing = config.get('image_processing', True) - self.spatial_reasoning = config.get('spatial_reasoning', True) - self.visual_memory = {} - self.step_count = 0 - - def act(self, observation: Dict[str, Any]) -> Action: - """Generate action based on visual observation""" - self.step_count += 1 - - # Get visual information - map_image = observation.get('map_image', '') - entities = observation.get('entities', []) - inventory = observation.get('inventory', {}) - - # Process visual information - if self.vision_enabled and map_image: - visual_analysis = self._analyze_visual_data(map_image) - else: - visual_analysis = {} - - # Generate action based on visual analysis - if self.step_count == 1: - code = self._initial_visual_exploration(visual_analysis) - elif self.step_count <= 10: - code = self._visual_setup(visual_analysis, entities) - else: - code = self._visual_monitoring(visual_analysis, entities, inventory) - - return Action( - agent_idx=0, - code=code, - game_state=None - ) - - def _analyze_visual_data(self, map_image: str) -> Dict[str, Any]: - """Analyze visual data from map image""" - try: - # Decode base64 image - image_data = base64.b64decode(map_image) - image = Image.open(io.BytesIO(image_data)) - - # Convert to numpy array - img_array = np.array(image) - - # Perform visual analysis - analysis = { - 'image_size': image.size, - 'image_mode': image.mode, - 'dominant_colors': self._extract_dominant_colors(img_array), - 'entity_locations': self._detect_entities(img_array), - 'resource_patches': self._detect_resource_patches(img_array), - 'spatial_features': self._extract_spatial_features(img_array) - } - - return analysis - - except Exception as e: - print(f"Visual analysis error: {e}") - return {} - - def _extract_dominant_colors(self, img_array: np.ndarray) -> List[tuple]: - """Extract dominant colors from image""" - # Reshape image to 2D array of pixels - pixels = img_array.reshape(-1, img_array.shape[-1]) - - # Simple color extraction (in practice, use more sophisticated methods) - unique_colors = np.unique(pixels, axis=0) - return unique_colors[:10].tolist() # Return top 10 colors - - def _detect_entities(self, img_array: np.ndarray) -> List[Dict[str, Any]]: - """Detect entities in the image""" - # Simple entity detection (in practice, use computer vision models) - entities = [] - - # Look for specific color patterns that might indicate entities - # This is a simplified example - for y in range(0, img_array.shape[0], 10): - for x in range(0, img_array.shape[1], 10): - pixel = img_array[y, x] - if self._is_entity_pixel(pixel): - entities.append({ - 'position': (x, y), - 'type': self._classify_entity(pixel), - 'confidence': 0.8 - }) - - return entities - - def _detect_resource_patches(self, img_array: np.ndarray) -> List[Dict[str, Any]]: - """Detect resource patches in the image""" - resource_patches = [] - - # Look for resource-specific color patterns - for y in range(0, img_array.shape[0], 20): - for x in range(0, img_array.shape[1], 20): - region = img_array[y:y+20, x:x+20] - if self._is_resource_region(region): - resource_patches.append({ - 'position': (x, y), - 'type': self._classify_resource(region), - 'size': self._estimate_resource_size(region) - }) - - return resource_patches - - def _extract_spatial_features(self, img_array: np.ndarray) -> Dict[str, Any]: - """Extract spatial features from the image""" - return { - 'image_center': (img_array.shape[1] // 2, img_array.shape[0] // 2), - 'image_bounds': (0, 0, img_array.shape[1], img_array.shape[0]), - 'density_map': self._calculate_density_map(img_array), - 'connectivity': self._analyze_connectivity(img_array) - } - - def _initial_visual_exploration(self, visual_analysis: Dict[str, Any]) -> str: - """Initial visual exploration""" - return f''' - # Initial visual exploration - print("Starting VisualAgent exploration") - - # Analyze visual data - visual_analysis = {visual_analysis} - print(f"Visual analysis: {visual_analysis}") - - # Get current position - position = get_position() - print(f"Starting position: {{position}}") - - # Look for resources using visual analysis - if visual_analysis.get('resource_patches'): - for patch in visual_analysis['resource_patches']: - print(f"Found resource patch: {{patch['type']}} at {{patch['position']}}") - - # Look for entities using visual analysis - if visual_analysis.get('entity_locations'): - for entity in visual_analysis['entity_locations']: - print(f"Found entity: {{entity['type']}} at {{entity['position']}}") - ''' - - def _visual_setup(self, visual_analysis: Dict[str, Any], entities: List) -> str: - """Set up operations based on visual analysis""" - return ''' - # Visual-based setup - print("Setting up operations based on visual analysis") - - # Find resources using visual cues - iron_pos = nearest(Resource.IRON_ORE) - copper_pos = nearest(Resource.COPPER_ORE) - - if iron_pos: - # Place mining drill with visual guidance - drill = place_entity( - entity=Prototype.MiningDrill, - position=iron_pos, - direction=Direction.NORTH - ) - print(f"Placed mining drill at {iron_pos} based on visual analysis") - - # Add storage with visual positioning - chest = place_entity_next_to( - entity=Prototype.IronChest, - reference_position=drill.drop_position, - direction=Direction.SOUTH - ) - print(f"Placed chest at {chest.position}") - - # Check visual feedback - entities = get_entities() - print(f"Current entities: {len(entities)}") - ''' - - def _visual_monitoring(self, visual_analysis: Dict[str, Any], entities: List, inventory: Dict) -> str: - """Monitor operations using visual feedback""" - return ''' - # Visual monitoring - print("Monitoring operations with visual feedback") - - # Check entities - entities = get_entities() - working_entities = [e for e in entities if hasattr(e, 'status') and e.status == EntityStatus.WORKING] - print(f"Working entities: {len(working_entities)}") - - # Check inventory - inventory = inspect_inventory() - total_items = sum(inventory.values()) - print(f"Total items: {total_items}") - - # Visual analysis feedback - if visual_analysis: - print(f"Visual analysis: {visual_analysis}") - if 'spatial_features' in visual_analysis: - features = visual_analysis['spatial_features'] - print(f"Spatial features: {features}") - ''' - -Visual Processing Features --------------------------- - -**Image Analysis** - - Dominant color extraction - - Entity detection and classification - - Resource patch identification - - Spatial feature extraction - -**Computer Vision Techniques** - - Edge detection - - Color segmentation - - Object recognition - - Spatial reasoning - -**Visual Memory** - - Store visual information across steps - - Track changes in visual data - - Maintain spatial maps - -Example Visual Analysis ------------------------ - -**Input Image** - Base64 encoded PNG image of the game map - -**Output Analysis** - .. code-block:: python - - { - 'image_size': (1024, 1024), - 'image_mode': 'RGB', - 'dominant_colors': [ - [0, 0, 0], # Black (background) - [139, 69, 19], # Brown (dirt) - [128, 128, 128], # Gray (stone) - [255, 215, 0] # Gold (resources) - ], - 'entity_locations': [ - { - 'position': (512, 256), - 'type': 'mining_drill', - 'confidence': 0.9 - }, - { - 'position': (520, 264), - 'type': 'chest', - 'confidence': 0.8 - } - ], - 'resource_patches': [ - { - 'position': (100, 200), - 'type': 'iron_ore', - 'size': 'large' - }, - { - 'position': (300, 400), - 'type': 'copper_ore', - 'size': 'medium' - } - ], - 'spatial_features': { - 'image_center': (512, 512), - 'image_bounds': (0, 0, 1024, 1024), - 'density_map': {...}, - 'connectivity': {...} - } - } - -Running the Visual Agent ------------------------ - -**Environment Setup** - .. code-block:: python - - import gym - from fle.agents.visual_agent import VisualAgent - - # Create environment - env = gym.make("iron_ore_throughput") - - # Create visual agent - agent = VisualAgent({ - 'vision_enabled': True, - 'image_processing': True, - 'spatial_reasoning': True - }) - - # Run episode - obs = env.reset() - done = False - step = 0 - - while not done and step < 100: - action = agent.act(obs) - obs, reward, terminated, truncated, info = env.step(action) - done = terminated or truncated - step += 1 - print(f"Step {step}: Reward = {reward}") - - env.close() - -**Command Line Usage** - .. code-block:: bash - - # Run visual agent evaluation - fle eval --agent visual_agent --config configs/visual_agent_config.json - -Agent Configuration -------------------- - -**Basic Configuration** - .. code-block:: json - - { - "agent_type": "VisualAgent", - "config": { - "vision_enabled": true, - "image_processing": true, - "spatial_reasoning": true, - "visual_memory_size": 100 - }, - "evaluation": { - "episodes": 5, - "max_steps": 1000, - "success_threshold": 0.6 - } - } - -**Advanced Configuration** - .. code-block:: json - - { - "agent_type": "VisualAgent", - "config": { - "vision_enabled": true, - "image_processing": true, - "spatial_reasoning": true, - "visual_memory_size": 1000, - "computer_vision_model": "resnet50", - "object_detection_threshold": 0.7, - "spatial_analysis_depth": 3 - }, - "evaluation": { - "episodes": 10, - "max_steps": 2000, - "success_threshold": 0.8, - "metrics": ["visual_accuracy", "spatial_reasoning", "object_detection"] - } - } - -Performance Metrics -------------------- - -**Visual Accuracy** - - Object detection accuracy - - Resource identification accuracy - - Spatial reasoning accuracy - -**Processing Performance** - - Image processing time - - Memory usage - - CPU utilization - -**Visual Reasoning** - - Spatial relationship understanding - - Object interaction prediction - - Visual planning effectiveness - -Example Metrics -~~~~~~~~~~~~~~~ - -.. code-block:: python - - { - "visual_accuracy": { - "object_detection": 0.85, # fraction of objects correctly identified - "resource_identification": 0.90, # fraction of resources correctly identified - "spatial_reasoning": 0.75 # fraction of spatial relationships correctly understood - }, - "processing_performance": { - "image_processing_time": 0.1, # seconds per image - "memory_usage": 512, # MB - "cpu_utilization": 0.3 # fraction of CPU used - }, - "visual_reasoning": { - "spatial_understanding": 0.80, # fraction of spatial relationships understood - "object_interaction_prediction": 0.70, # fraction of interactions correctly predicted - "visual_planning_effectiveness": 0.65 # fraction of visual plans that succeed - } - } - -Troubleshooting ---------------- - -**Visual Processing Issues** - - **Poor image quality**: Check image resolution and format - - **Detection failures**: Adjust detection thresholds - - **Memory issues**: Reduce visual memory size - -**Performance Issues** - - **Slow processing**: Optimize image processing algorithms - - **High memory usage**: Implement image compression - - **CPU bottlenecks**: Use parallel processing - -**Accuracy Issues** - - **False positives**: Adjust detection thresholds - - **Missed objects**: Improve detection algorithms - - **Spatial errors**: Enhance spatial reasoning - -Best Practices --------------- - -1. **Image Quality**: Ensure high-quality input images -2. **Detection Thresholds**: Tune detection parameters -3. **Memory Management**: Monitor and optimize memory usage -4. **Performance Optimization**: Use efficient algorithms -5. **Error Handling**: Implement robust error recovery -6. **Visual Memory**: Maintain useful visual information -7. **Spatial Reasoning**: Develop strong spatial understanding diff --git a/docs/sphinx/source/getting_started/cluster.rst b/docs/sphinx/source/getting_started/cluster.rst deleted file mode 100644 index b935eb8c1..000000000 --- a/docs/sphinx/source/getting_started/cluster.rst +++ /dev/null @@ -1,91 +0,0 @@ -Cluster Setup -============= - -FLE uses Docker to run Factorio servers in a cluster configuration. This allows for scalable evaluation of agents across multiple game instances. - -Starting a Cluster ------------------ - -.. code-block:: bash - - # Start Factorio cluster - fle cluster start - -This command will: - -- Start Docker containers running Factorio servers -- Configure networking between containers -- Set up the evaluation environment -- Create necessary directories and configurations - -Cluster Management ------------------- - -The cluster system provides several management commands: - -.. code-block:: bash - - # Check cluster status - fle cluster status - - # Stop the cluster - fle cluster stop - - # Restart the cluster - fle cluster restart - -Configuration -------------- - -Cluster configuration is managed through: - -- `.env` file: Environment variables for cluster setup -- `configs/` directory: Configuration files for different scenarios -- Docker Compose: Container orchestration - -The cluster automatically creates these files on first run. - -Scenarios ---------- - -FLE supports different game scenarios: - -- **Lab-play**: 24 structured tasks with fixed resources -- **Open-play**: An unbounded task of building the largest possible factory on a procedurally generated map - -Each scenario can be configured with different parameters: - -- Map generation settings -- Resource availability -- Technology research requirements -- Time limits and objectives - -Troubleshooting --------------- - -**Docker Issues** - - Ensure your user has permission to run Docker without sudo - - Check that Docker is running: `docker ps` - - Verify available disk space and memory - -**Connection Issues** - - Make sure the Factorio server is running and ports are properly configured - - Check firewall settings for required ports - - Verify network connectivity between containers - -**Resource Issues** - - Monitor Docker resource usage: `docker stats` - - Adjust memory limits if needed - - Check available disk space for game saves - -Advanced Configuration ----------------------- - -For advanced users, you can customize: - -- Container resource limits -- Network configurations -- Volume mounts for persistent data -- Custom Factorio mods and scenarios - -See the :doc:`customization guide <../customization/tasks>` for more details. diff --git a/docs/sphinx/source/getting_started/installation.rst b/docs/sphinx/source/getting_started/installation.rst index c8a3484ad..01f78b09b 100644 --- a/docs/sphinx/source/getting_started/installation.rst +++ b/docs/sphinx/source/getting_started/installation.rst @@ -4,105 +4,136 @@ Installation Prerequisites ------------- -- Docker -- Python 3.10+ -- `Factorio `_ (version 1.1.110), only for optional rendering +Before installing FLE, ensure you have: -Installation ------------- +- **Docker**: Required for running Factorio server instances +- **Python 3.10+**: The minimum Python version supported +- **Factorio** (version 1.1.110): Only needed for optional rendering with graphics + +Installation Methods +-------------------- + +Core Installation +~~~~~~~~~~~~~~~~~ -Core FLE SDK package: +Install the core FLE SDK package: .. code-block:: bash + # Using pip pip install factorio-learning-environment + + # Using uv (recommended) uv add factorio-learning-environment -With optional features: +Installation with Optional Features +~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ + +FLE provides several optional feature sets: .. code-block:: bash # For running experiments pip install factorio-learning-environment[eval] - - # For MCP protocol support + + # For MCP protocol support pip install factorio-learning-environment[mcp] - + # For PostgreSQL support pip install factorio-learning-environment[psql] - - # All features - pip install factorio-learning-environment[eval,mcp,psql] - -Using uv (recommended): -.. code-block:: bash + # Install all features + pip install factorio-learning-environment[eval,mcp,psql] + # Using uv (recommended) uv add factorio-learning-environment[eval] Client-side Setup (Optional) ----------------------------- +----------------------------- + +For rendering Factorio with graphics, you need to set up a Factorio client: + +1. **Purchase and Install Factorio** + + - Purchase from the `official website `_ (recommended) or on Steam + - Download and install the game + +2. **Downgrade to Version 1.1.110** -For rendering graphics, set up the Factorio client: + - **Steam**: Right-click Factorio → Properties → Betas → Select ``1.1.110`` + - **Important**: Uncheck the Space Age DLC if you have it, as it forces the 2.x branch -1. **Set up Factorio client**: - - Purchase Factorio from the `official website `_ (recommended) or on Steam. - - Downgrade to version 1.1.110: - - Steam: Right-click Factorio → Properties → Betas → Select 1.1.110 - - **Important**: Make sure to uncheck the Space Age DLC if you have it, as it forces the 2.x branch +3. **Activate Server License** -2. **Activate server**: - - Open Factorio client - - Navigate to _Multiplayer_ - - Connect to `localhost:34197` (default) or your configured address in Docker. - - Once connected, you can safely disconnect. This step confirms your Factorio license with the server. + - Open the Factorio client + - Navigate to *Multiplayer* + - Connect to ``localhost:34197`` (default) or your configured address in Docker + - Once connected, you can safely disconnect. This step confirms your Factorio license with the server. API Key Configuration --------------------- -FLE supports multiple LLM providers for agent evaluation. To get started with API keys: +FLE supports multiple LLM providers for agent evaluation. -1. **Quick Setup** (Recommended): - .. code-block:: bash +Quick Setup (Recommended) +~~~~~~~~~~~~~~~~~~~~~~~~~~ - python fle/eval/infra/setup_api_keys.py +Use the interactive setup script: - This interactive script helps you: - - Configure API keys for OpenAI, Anthropic, and other providers - - Set up API key rotation for high-volume experiments - - Generate provider-specific configuration files - - Validate your API key setup +.. code-block:: bash + + python fle/eval/infra/setup_api_keys.py + +This script helps you: + +- Configure API keys for OpenAI, Anthropic, and other providers +- Set up API key rotation for high-volume experiments +- Generate provider-specific configuration files +- Validate your API key setup + +Manual Setup +~~~~~~~~~~~~ + +Add your API keys to the ``.env`` file: + +.. code-block:: bash -2. **Manual Setup**: - Add your API keys to the `.env` file: - .. code-block:: bash + # OpenAI + OPENAI_API_KEY=sk-... - # OpenAI - OPENAI_API_KEY=sk-... - - # Anthropic - ANTHROPIC_API_KEY=sk-ant-... - - # Additional providers as needed + # Anthropic + ANTHROPIC_API_KEY=sk-ant-... -3. **Advanced Configuration**: - For large-scale experiments, you can set up API key rotation and provider-specific settings using the configuration files generated by `setup_api_keys.py`. + # Additional providers as needed -Troubleshooting ---------------- +Advanced Configuration +~~~~~~~~~~~~~~~~~~~~~~ -- **"No valid programs found for version X"**: This is normal during initialization. The system will start generating programs shortly. -- **Database connection errors**: Verify your database configuration in the .env file and ensure the database exists. -- **API key errors**: Run `python fle/eval/infra/setup_api_keys.py` to verify your API key configuration. -- **Docker issues**: Ensure your user has permission to run Docker without sudo. -- **Connection issues**: Make sure the Factorio server is running and ports are properly configured. +For large-scale experiments, you can set up API key rotation and provider-specific settings using the configuration files generated by ``setup_api_keys.py``. -Building Documentation (Maintainers) ------------------------------------- +Initial Setup +------------- + +When you run ``fle init`` or ``fle eval`` for the first time: + +- An ``.env`` file is automatically created +- A ``configs/`` directory with example configurations is created + +Verification +------------ + +Verify your installation by starting the Factorio cluster: .. code-block:: bash - cd docs/sphinx - python3 -m sphinx -b html source build/html + # Start Factorio cluster + fle cluster start + + # Run evaluation trajectories (requires [eval] dependencies) + fle eval --config configs/gym_run_config.json + +Next Steps +---------- -The generated site will be in ``factorio-learning-environment/docs/sphinx/build/html``. +- Continue to :doc:`quickstart` to learn how to use FLE +- See :doc:`troubleshooting` if you encounter issues diff --git a/docs/sphinx/source/getting_started/quickstart.rst b/docs/sphinx/source/getting_started/quickstart.rst index 7d92a180a..657ad6c11 100644 --- a/docs/sphinx/source/getting_started/quickstart.rst +++ b/docs/sphinx/source/getting_started/quickstart.rst @@ -1,32 +1,72 @@ Quickstart ========== -Use the CLI: +This guide will get you up and running with FLE in minutes. + +CLI Commands +------------ + +Starting the Factorio Cluster +~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ .. code-block:: bash # Start Factorio cluster fle cluster start - + +Running Evaluations +~~~~~~~~~~~~~~~~~~~ + +.. code-block:: bash + # Run evaluation trajectories (requires [eval] dependencies) fle eval --config configs/gym_run_config.json .. note:: - When you run `fle init` or `fle eval` for the first time, an `.env` file and a `configs/` directory with example configurations are created automatically + When you run ``fle init`` or ``fle eval`` for the first time, an ``.env`` file and a ``configs/`` directory with example configurations are created automatically. + +Basic Usage Example +------------------- + +Here's a complete example demonstrating how to use FLE with the Gym interface: + +.. code-block:: python + + import gym + from fle.env.gym_env.action import Action + + # Create an environment + env = gym.make("iron_ore_throughput") + + # Reset the environment + obs = env.reset(options={'game_state': None}) + + # Take an action + action = Action( + agent_idx=0, # Which agent takes the action + code='print("Hello Factorio!")', # Python code to execute + game_state=None # Optional: game state to reset to before running code + ) + + # Execute the action + obs, reward, terminated, truncated, info = env.step(action) + + # Clean up + env.close() -Environment Overview --------------------- +Understanding the REPL Pattern +------------------------------- -FLE is an agent evaluation environment built on the game of Factorio, a popular resource management simulation game. +Agents interact with FLE through a **REPL** (Read-Eval-Print-Loop) pattern: -Agents interact with **FLE** by code synthesis through a **REPL** (Read-Eval-Print-Loop) pattern: +1. **Observation**: The agent observes the world through the output streams (stderr/stdout) of their last program +2. **Action**: The agent generates a Python program to perform their desired action +3. **Feedback**: The environment executes the program and provides an output stream -1. **Observation**: The agent observes the world through the output streams (stderr/stdout) of their last program. -2. **Action**: The agent generates a Python program to perform their desired action. -3. **Feedback**: The environment executes the program, assigns variables, add classes/functions to the namespace, and provides an output stream. +Example Action-Feedback Cycle +~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ -Example Interaction ------------------- +**Action:** .. code-block:: python @@ -51,52 +91,104 @@ Example Interaction .. code-block:: python - >>> [ BurnerMiningDrill(fuel=Inventory({'coal': 4}), - >>> name='burner-mining-drill', - >>> direction=Direction.DOWN, - >>> position=Position(x=-28.0, y=-61.0), - >>> energy=2666.6666666667, - >>> tile_dimensions=TileDimensions(tile_width=2.0, tile_height=2.0), - >>> status=EntityStatus.WORKING, - >>> neighbours=[Entity(name='iron-chest', direction=DOWN, position=Position(x=-27.5 y=-59.5)], - >>> drop_position=Position(x=-27.5, y=-59.5), + >>> [ BurnerMiningDrill(fuel=Inventory({'coal': 4}), + >>> name='burner-mining-drill', + >>> direction=Direction.DOWN, + >>> position=Position(x=-28.0, y=-61.0), + >>> energy=2666.6666666667, + >>> tile_dimensions=TileDimensions(tile_width=2.0, tile_height=2.0), + >>> status=EntityStatus.WORKING, + >>> neighbours=[Entity(name='iron-chest', direction=DOWN, position=Position(x=-27.5 y=-59.5)], + >>> drop_position=Position(x=-27.5, y=-59.5), >>> resources=[Ingredient(name='iron-ore', count=30000, type=None)]), - >>> Chest(name='iron-chest', - >>> direction=Direction.UP, - >>> position=Position(x=-27.5, y=-59.5), - >>> energy=0.0, - >>> tile_dimensions=TileDimensions(tile_width=1.0, tile_height=1.0), - >>> status=EntityStatus.NORMAL, + >>> Chest(name='iron-chest', + >>> direction=Direction.UP, + >>> position=Position(x=-27.5, y=-59.5), + >>> energy=0.0, + >>> tile_dimensions=TileDimensions(tile_width=1.0, tile_height=1.0), + >>> status=EntityStatus.NORMAL, >>> inventory=Inventory({'iron-ore': 75}))] -Key Concepts ------------- +Listing Available Environments +------------------------------- + +.. code-block:: python + + from fle.env.gym_env.registry import list_available_environments + + # Get all available environment IDs + env_ids = list_available_environments() + print(f"Available environments: {env_ids}") + +Or use the command-line tool: + +.. code-block:: bash + + python fle/env/gym_env/example_usage.py --list -**Tools and Namespace** - Agents are provided with the Python standard library, and an API comprising :doc:`tools <../api/tools>` that they can use. +Creating Different Environments +-------------------------------- + +.. code-block:: python + + import gym + + # Create throughput environments + env = gym.make("iron_plate_throughput") + env = gym.make("automation_science_pack_throughput") + env = gym.make("crude_oil_throughput") + + # Create open play environment + env = gym.make("open_play") + +Complete Workflow Example +-------------------------- + +Here's a complete example demonstrating the full workflow: + +.. code-block:: python - Tools are functions that perform a game action and return a typed object (e.g an Inventory), which can be stored as a named **variable** in the Python namespace for later use. + import gym + from fle.env.gym_env.registry import list_available_environments, get_environment_info + from fle.env.gym_env.action import Action - The namespace acts as an episodic symbolic memory system, and saved objects represent an observation of the environment at the moment of query. + # 1. List available environments + env_ids = list_available_environments() + print(f"Found {len(env_ids)} environments") - This enables agents to maintain complex state representations and build hierarchical abstractions as the factories scale. + # 2. Get information about a specific environment + info = get_environment_info("iron_ore_throughput") + print(f"Description: {info['description']}") -**Observation Streams** - Agents observe **stdout** and **stderr** - the output streams of their program. Agents may intentionally choose to print relevant objects and computations to the output stream to construct observations. + # 3. Create the environment + env = gym.make("iron_ore_throughput") - Mistakes in the code or invalid operations raise typed **exceptions** with detailed context that is written to stderr. + # 4. Use the environment + obs = env.reset(options={'game_state': None}) + print(f"Initial observation keys: {list(obs.keys())}") - This enables agents to reactively debug their programs after execution, and proactively use runtime assertions during execution to self-verify their actions. + # 5. Take actions + current_state = None + for step in range(5): + action = Action( + agent_idx=0, + game_state=current_state, + code=f'print("Step {step}: Hello Factorio!")' + ) + obs, reward, terminated, truncated, info = env.step(action) + done = terminated or truncated + current_state = info['output_game_state'] + print(f"Step {step}: Reward={reward}, Done={done}") -**Code Enhancement** - Agents are able to enhance their internal representation of the game state by defining: + if done: + break - 1. Utility functions for reuse throughout an episode, to encapsulate previously successful logic - 2. Classes in the namespace to better organize the data retrieved from the game. + # 6. Clean up + env.close() Next Steps ---------- -- Learn about the :doc:`environment API <../api/environment>` -- Explore available :doc:`tools <../api/tools>` -- See :doc:`examples <../examples/basic_agent>` of agent implementations +- Learn about the :doc:`../environment/overview` and how agents interact with it +- Explore the :doc:`../tools/overview` available to agents +- Check out the :doc:`../environment/gym_registry` for available tasks diff --git a/docs/sphinx/source/getting_started/troubleshooting.rst b/docs/sphinx/source/getting_started/troubleshooting.rst new file mode 100644 index 000000000..361ea19b4 --- /dev/null +++ b/docs/sphinx/source/getting_started/troubleshooting.rst @@ -0,0 +1,214 @@ +Troubleshooting +=============== + +This page addresses common issues you may encounter when using FLE. + +Common Issues +------------- + +"No valid programs found for version X" +~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ + +**Symptom**: You see this message during initialization. + +**Solution**: This is normal during initialization. The system will start generating programs shortly. No action needed. + +Database Connection Errors +~~~~~~~~~~~~~~~~~~~~~~~~~~~ + +**Symptom**: Errors connecting to the database when running evaluations. + +**Solution**: + +1. Verify your database configuration in the ``.env`` file +2. Ensure the database exists +3. For SQLite: Check that the directory for the database file exists +4. For PostgreSQL: Verify the database server is running + +API Key Errors +~~~~~~~~~~~~~~ + +**Symptom**: Authentication errors when running agent evaluations. + +**Solution**: + +1. Run the API key setup script: + + .. code-block:: bash + + python fle/eval/infra/setup_api_keys.py + +2. Verify your API keys are correctly set in the ``.env`` file +3. Check that you're using the correct provider (OpenAI, Anthropic, etc.) + +Docker Issues +~~~~~~~~~~~~~ + +**Symptom**: Permission denied or Docker connection errors. + +**Solution**: + +1. Ensure Docker is installed and running +2. Verify your user has permission to run Docker without sudo: + + .. code-block:: bash + + sudo usermod -aG docker $USER + +3. Log out and log back in for the group change to take effect +4. Test Docker access: + + .. code-block:: bash + + docker ps + +Connection Issues +~~~~~~~~~~~~~~~~~ + +**Symptom**: Cannot connect to Factorio server. + +**Solution**: + +1. Make sure the Factorio server is running: + + .. code-block:: bash + + fle cluster start + +2. Check that ports are properly configured +3. Verify Docker containers are running: + + .. code-block:: bash + + docker ps + +4. Check Docker logs for errors: + + .. code-block:: bash + + docker logs + +Environment Creation Fails +~~~~~~~~~~~~~~~~~~~~~~~~~~~ + +**Symptom**: ``gym.make()`` fails with connection errors. + +**Solution**: + +1. Ensure Factorio containers are running +2. Check that the cluster setup is working +3. Verify network connectivity + +No Environments Found +~~~~~~~~~~~~~~~~~~~~~ + +**Symptom**: ``list_available_environments()`` returns an empty list. + +**Solution**: + +1. Check that the task definitions directory exists +2. Verify JSON files in ``fle/eval/tasks/task_definitions/`` are valid +3. Check file permissions +4. Ensure you're running from the correct directory + +Import Errors +~~~~~~~~~~~~~ + +**Symptom**: ``ModuleNotFoundError`` or import errors. + +**Solution**: + +1. Ensure you're running from the correct directory +2. Check that all dependencies are installed: + + .. code-block:: bash + + pip install factorio-learning-environment[eval] + +3. Verify the Python path includes the project root +4. Try reinstalling the package: + + .. code-block:: bash + + pip install --force-reinstall factorio-learning-environment + +Space Age DLC Issues +~~~~~~~~~~~~~~~~~~~~ + +**Symptom**: Factorio client is on version 2.x instead of 1.1.110. + +**Solution**: + +1. Open Steam library +2. Right-click Factorio → Properties +3. Navigate to DLC section +4. **Uncheck Space Age DLC** (this forces the 2.x branch) +5. Go to Betas tab +6. Select version ``1.1.110`` + +Testing Your Installation +-------------------------- + +Run the test suite to verify everything is working: + +.. code-block:: bash + + # Test the gym registry + python fle/env/tests/gym_env/test_registry.py + + # List available environments + python fle/env/gym_env/example_usage.py --list + + # Run with detailed output + python fle/env/gym_env/example_usage.py --detail + +Getting Help +------------ + +If you continue to experience issues: + +1. Check the `GitHub Issues `_ +2. Join the `Discord (#factorio-learning-env) `_ +3. Review the :doc:`../project_structure` to understand the codebase layout + +Debugging Tips +-------------- + +Enable Verbose Logging +~~~~~~~~~~~~~~~~~~~~~~~ + +Set environment variables for more detailed output: + +.. code-block:: bash + + export FLE_LOG_LEVEL=DEBUG + +Check Docker Logs +~~~~~~~~~~~~~~~~~ + +View logs from Factorio containers: + +.. code-block:: bash + + # List running containers + docker ps + + # View logs for a specific container + docker logs + + # Follow logs in real-time + docker logs -f + +Verify Environment Variables +~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ + +Check that your ``.env`` file is properly loaded: + +.. code-block:: python + + import os + from dotenv import load_dotenv + + load_dotenv() + print(os.getenv('OPENAI_API_KEY')) # Should show your API key (masked) + print(os.getenv('FLE_DB_TYPE')) # Should show sqlite or postgres diff --git a/docs/sphinx/source/index.rst b/docs/sphinx/source/index.rst index da4bfdd74..affbba0e0 100644 --- a/docs/sphinx/source/index.rst +++ b/docs/sphinx/source/index.rst @@ -1,7 +1,35 @@ -Welcome to Factorio Learning Environment's documentation! -================================================================ +Factorio Learning Environment +============================== -An open source framework for developing and evaluating LLM agents in the game of Factorio. +.. raw:: html + +

    + Leaderboard | + Paper | + Website | + Discord (#factorio-learning-env) +

    + +An open source framework for developing and evaluating LLM agents in the game of `Factorio `_. + +.. raw:: html + +

    + + +

    +

    Claude Opus 4.1 Plays Factorio

    + +Why FLE? +-------- + +We provide two settings: + +1. **Lab-play**: 24 structured tasks with fixed resources. +2. **Open-play**: An unbounded task of building the largest possible factory on a procedurally generated map. + +Our results demonstrate that models still lack strong spatial reasoning. In lab-play, we find that while LLMs +exhibit promising short-horizon skills, they are unable to operate effectively in constrained environments, reflecting limitations in error analysis. In open-play, while LLMs discover automation strategies that improve growth (e.g electric-powered drilling), they fail to achieve complex automation (e.g electronic-circuit manufacturing). .. toctree:: :maxdepth: 2 @@ -9,40 +37,36 @@ An open source framework for developing and evaluating LLM agents in the game of getting_started/installation getting_started/quickstart - getting_started/cluster + getting_started/troubleshooting .. toctree:: :maxdepth: 2 - :caption: API Reference + :caption: Environment - api/environment - api/observation - api/action - api/tools - api/modules + environment/overview + environment/gym_registry .. toctree:: :maxdepth: 2 - :caption: Customization + :caption: Tools - customization/tasks - customization/tools - customization/agents - customization/database + tools/overview + tools/core_tools + tools/custom_tools .. toctree:: :maxdepth: 2 - :caption: Examples + :caption: Advanced Topics - examples/basic_agent - examples/visual_agent - examples/multiagent + advanced/mcp + advanced/sprites + advanced/database .. toctree:: - :maxdepth: 2 - :caption: Tools + :maxdepth: 1 + :caption: Reference - tools/index + project_structure Indices and tables ================== diff --git a/docs/sphinx/source/project_structure.rst b/docs/sphinx/source/project_structure.rst new file mode 100644 index 000000000..d165cd55a --- /dev/null +++ b/docs/sphinx/source/project_structure.rst @@ -0,0 +1,317 @@ +Project Structure +================= + +This page provides an overview of the FLE codebase organization. + +Directory Layout +---------------- + +.. code-block:: text + + factorio-learning-environment/ + ├── .github/ # GitHub workflows and CI/CD + ├── .fle/ # Runtime data (saves, scenarios, trajectory logs) + ├── docs/ # Documentation and website + ├── examples/ # Example agent implementations + ├── fle/ # Main codebase + │ ├── agents/ # Agent implementations + │ ├── cluster/ # Docker orchestration and scenarios + │ ├── commons/ # Shared utilities and models + │ ├── configs/ # Configuration files + │ ├── data/ # Data files and replays + │ ├── env/ # Core environment + │ ├── eval/ # Evaluation framework + │ ├── run.py # CLI entry point + │ └── server.py # RCON server + ├── tests/ # Test suite + ├── .example.env # Environment variables template + ├── BUILD.md # Build instructions + ├── CONTRIBUTING.md # Contribution guidelines + ├── pyproject.toml # Python project config + └── uv.lock # Dependency lock file + +Core Directories +---------------- + +fle/agents/ +~~~~~~~~~~~ + +Agent implementations including: + +- ``BasicAgent``: Simple text-based agent +- ``VisualAgent``: Vision-enabled agent +- ``MultiAgent``: Multi-agent coordination +- Base classes and interfaces + +**Key Files:** + +- ``agent_abc.py``: Abstract base class for agents +- ``models.py``: Agent configuration models + +fle/cluster/ +~~~~~~~~~~~~ + +Docker orchestration and scenario management: + +- Factorio server containers +- Docker Compose configurations +- Scenario definitions +- Server management utilities + +**Key Files:** + +- ``docker-compose.yml``: Container orchestration +- ``scenarios/``: Pre-built game scenarios + +fle/commons/ +~~~~~~~~~~~~ + +Shared utilities and models used across the codebase: + +- Data models (Position, Entity, Inventory, etc.) +- Utility functions +- Constants and enumerations +- Database client interface + +**Key Files:** + +- ``models.py``: Core data models +- ``db_client.py``: Database abstraction layer +- ``utils.py``: Helper functions + +fle/env/ +~~~~~~~~ + +Core environment implementation: + +.. code-block:: text + + env/ + ├── gym_env/ # OpenAI Gym interface + │ ├── action.py # Action definitions + │ ├── observation.py # Observation space + │ ├── registry.py # Environment registry + │ └── gym_env.py # Main gym environment + ├── tools/ # Agent-accessible tools + │ ├── agent/ # Agent tools + │ └── admin/ # Admin tools + ├── protocols/ # Communication protocols + │ ├── _mcp/ # Model Context Protocol + │ └── a2a/ # Agent-to-Agent protocol + ├── exceptions/ # Custom exceptions + ├── entities.py # Entity definitions + ├── instance.py # Game instance management + └── namespace.py # Python namespace management + +**Key Components:** + +- **gym_env/**: Standard gym interface for RL frameworks +- **tools/**: All agent-callable functions +- **protocols/**: Communication layer implementations +- **exceptions/**: Typed exceptions for error handling + +fle/eval/ +~~~~~~~~~ + +Evaluation framework for running experiments: + +.. code-block:: text + + eval/ + ├── algorithms/ # Search algorithms + │ ├── beam_search.py # Beam search implementation + │ ├── mcts.py # Monte Carlo Tree Search + │ └── independent.py # Independent evaluation + ├── analysis/ # Analysis tools + ├── tasks/ # Task definitions + │ └── task_definitions/ # JSON task configs + │ ├── lab_play/ # Structured tasks + │ └── open_play/ # Open-ended tasks + ├── infra/ # Infrastructure + │ ├── setup_api_keys.py # API key configuration + │ └── cluster_manager.py # Cluster management + └── evaluator.py # Main evaluation logic + +**Key Files:** + +- ``evaluator.py``: Runs agent evaluations +- ``tasks/task_definitions/``: Task configurations +- ``algorithms/``: Search and optimization algorithms + +tests/ +~~~~~~ + +Comprehensive test suite: + +.. code-block:: text + + tests/ + ├── actions/ # Tool tests + ├── benchmarks/ # Performance benchmarks + ├── functional/ # End-to-end tests + ├── gym_env/ # Gym interface tests + └── integration/ # Integration tests + +Configuration Files +------------------- + +pyproject.toml +~~~~~~~~~~~~~~ + +Python project configuration: + +- Package metadata +- Dependencies +- Optional feature groups (``[eval]``, ``[mcp]``, ``[psql]``) +- Build system configuration + +.env +~~~~ + +Environment variables (created from ``.example.env``): + +- API keys (OpenAI, Anthropic, etc.) +- Database configuration +- Cluster settings +- Feature flags + +Key Modules +----------- + +fle/run.py +~~~~~~~~~~ + +CLI entry point providing commands: + +- ``fle cluster start``: Start Factorio cluster +- ``fle eval``: Run evaluations +- ``fle sprites``: Manage sprites +- ``fle init``: Initialize configuration + +fle/server.py +~~~~~~~~~~~~~ + +RCON server for communicating with Factorio instances: + +- Handles tool invocations +- Manages game state +- Executes Lua commands + +fle/env/instance.py +~~~~~~~~~~~~~~~~~~~ + +Manages individual Factorio game instances: + +- Instance lifecycle +- State management +- Connection handling +- Resource cleanup + +fle/env/namespace.py +~~~~~~~~~~~~~~~~~~~~ + +Python namespace management for agent code: + +- Variable storage +- Function definitions +- Class definitions +- Namespace isolation + +Data Flow +--------- + +.. code-block:: text + + Agent + │ + ├─> Synthesizes Python Code + │ + ▼ + Environment (gym_env) + │ + ├─> Interprets Code + │ + ├─> Executes Tools (client.py) + │ │ + │ ├─> Calls server.py (RCON) + │ │ │ + │ │ ├─> Executes server.lua + │ │ │ │ + │ │ │ └─> Factorio Engine + │ │ │ + │ │ └─> Returns Results + │ │ + │ └─> Returns Typed Objects + │ + ├─> Updates Namespace + │ + └─> Returns Observation + │ + └─> Agent + +Important Files +--------------- + +Core Environment +~~~~~~~~~~~~~~~~ + +- ``fle/env/gym_env/gym_env.py``: Main gym environment +- ``fle/env/instance.py``: Game instance management +- ``fle/env/namespace.py``: Python namespace handling + +Tools System +~~~~~~~~~~~~ + +- ``fle/env/tools/tool.py``: Base tool class +- ``fle/env/tools/agent/**/client.py``: Tool implementations +- ``fle/server.py``: Server-side execution + +Registry & Tasks +~~~~~~~~~~~~~~~~ + +- ``fle/env/gym_env/registry.py``: Environment registry +- ``fle/eval/tasks/task_definitions/``: Task JSON files +- ``fle/eval/evaluator.py``: Evaluation orchestration + +Development Workflow +-------------------- + +Adding a New Tool +~~~~~~~~~~~~~~~~~ + +1. Create directory: ``fle/env/tools/agent/my_tool/`` +2. Add ``client.py``, ``server.lua``, ``agent.md`` +3. Create test: ``tests/actions/test_my_tool.py`` +4. Tool is automatically discovered + +Adding a New Task +~~~~~~~~~~~~~~~~~ + +1. Create JSON file: ``fle/eval/tasks/task_definitions/my_task.json`` +2. Task is automatically registered +3. Access via: ``gym.make("my_task")`` + +Running Tests +~~~~~~~~~~~~~ + +.. code-block:: bash + + # Run all tests + pytest tests/ + + # Run specific test file + pytest tests/actions/test_place_entity.py + + # Run with coverage + pytest --cov=fle tests/ + +Building Documentation +~~~~~~~~~~~~~~~~~~~~~~ + +.. code-block:: bash + + cd docs/sphinx + make html + + # View docs + open build/html/index.html \ No newline at end of file diff --git a/docs/sphinx/source/tools/core_tools.rst b/docs/sphinx/source/tools/core_tools.rst new file mode 100644 index 000000000..e17d58675 --- /dev/null +++ b/docs/sphinx/source/tools/core_tools.rst @@ -0,0 +1,563 @@ +Core Tools Reference +==================== + +This page provides a comprehensive reference for all core tools available to agents. + +Inventory Management +-------------------- + +inspect_inventory +~~~~~~~~~~~~~~~~~ + +Checks contents of player or entity inventories. + +**Features:** + +- Supports various inventory types (chests, furnaces, etc.) +- Returns ``Inventory`` object with count methods +- Can query specific items + +**Example:** + +.. code-block:: python + + # Check player inventory + inventory = inspect_inventory() + print(f"Iron plates: {inventory['iron-plate']}") + + # Check entity inventory + chest = get_entity(Prototype.IronChest, position) + inventory = inspect_inventory(chest) + +insert_item +~~~~~~~~~~~ + +Places items from player inventory into entities. + +**Features:** + +- Works with machines, chests, belts +- Validates item compatibility +- Returns updated entity + +**Example:** + +.. code-block:: python + + # Insert coal into a furnace + furnace = get_entity(Prototype.StoneFurnace, furnace_position) + insert_item(Prototype.Coal, furnace, quantity=10) + +extract_item +~~~~~~~~~~~~ + +Removes items from entity inventories. + +**Features:** + +- Supports all inventory types +- Auto-transfers to player inventory +- Returns quantity extracted + +**Example:** + +.. code-block:: python + + # Extract iron plates from a chest + chest = get_entity(Prototype.IronChest, chest_position) + extracted = extract_item(Prototype.IronPlate, chest, quantity=50) + print(f"Extracted {extracted} iron plates") + +Entity Manipulation +------------------- + +place_entity +~~~~~~~~~~~~ + +Places entities in the world. + +**Features:** + +- Handles direction and positioning +- Validates placement requirements +- Returns placed ``Entity`` object + +**Example:** + +.. code-block:: python + + # Place a mining drill + drill = place_entity( + entity=Prototype.MiningDrill, + position=Position(x=10, y=20), + direction=Direction.NORTH + ) + +place_entity_next_to +~~~~~~~~~~~~~~~~~~~~ + +Places entities relative to others. + +**Features:** + +- Automatic spacing/alignment +- Handles entity dimensions +- Supports all entity types + +**Example:** + +.. code-block:: python + + # Place a chest next to a drill + chest = place_entity_next_to( + entity=Prototype.IronChest, + reference_position=drill.drop_position, + direction=Direction.SOUTH + ) + +pickup_entity +~~~~~~~~~~~~~ + +Removes entities from the world. + +**Features:** + +- Returns items to inventory +- Handles entity groups +- Supports all placeable items + +**Example:** + +.. code-block:: python + + # Pick up a mining drill + drill = get_entity(Prototype.BurnerMiningDrill, position) + pickup_entity(drill) + +rotate_entity +~~~~~~~~~~~~~ + +Changes entity orientation. + +**Features:** + +- Affects entity behavior (e.g., inserter direction) +- Validates rotation rules +- Returns updated entity + +**Example:** + +.. code-block:: python + + # Rotate an inserter to face a different direction + inserter = get_entity(Prototype.Inserter, position) + rotate_entity(inserter, Direction.EAST) + +get_entity +~~~~~~~~~~ + +Retrieves entity objects at positions. + +**Features:** + +- Updates stale references +- Returns typed ``Entity`` objects +- Handles all entity types + +**Example:** + +.. code-block:: python + + # Get a chest at a specific position + chest = get_entity(Prototype.IronChest, Position(x=10, y=20)) + +get_entities +~~~~~~~~~~~~ + +Finds multiple entities in an area. + +**Features:** + +- Supports filtering by type +- Returns ``List[Entity]`` +- Groups connected entities + +**Example:** + +.. code-block:: python + + # Get all entities + entities = get_entities() + + # Get entities by type + drills = get_entities(prototype=Prototype.BurnerMiningDrill) + +Resource Operations +------------------- + +nearest +~~~~~~~ + +Locates closest resources/entities. + +**Features:** + +- Finds ores, water, trees +- Returns ``Position`` object +- 500 tile search radius + +**Example:** + +.. code-block:: python + + # Find nearest iron ore + iron_position = nearest(Resource.IronOre) + + # Find nearest water + water_position = nearest(Resource.Water) + +get_resource_patch +~~~~~~~~~~~~~~~~~~ + +Analyzes resource deposits. + +**Features:** + +- Returns size and boundaries +- Supports all resource types +- Includes total resource amount + +**Example:** + +.. code-block:: python + + # Get information about an iron ore patch + patch = get_resource_patch(Resource.IronOre, position) + print(f"Patch size: {patch.size}") + print(f"Total iron: {patch.amount}") + +harvest_resource +~~~~~~~~~~~~~~~~ + +Gathers resources from the world. + +**Features:** + +- Supports ores, trees, rocks +- Auto-collects to inventory +- Returns amount harvested + +**Example:** + +.. code-block:: python + + # Harvest iron ore manually + iron_position = nearest(Resource.IronOre) + harvested = harvest_resource(iron_position, quantity=50) + +Connections +----------- + +connect_entities +~~~~~~~~~~~~~~~~ + +Creates connections between entities. + +**Features:** + +- Handles belts, pipes, power +- Automatic pathfinding +- Returns connection group + +**Example:** + +.. code-block:: python + + # Connect a drill to a chest with a transport belt + connection = connect_entities( + drill.drop_position, + chest.position, + connection_type=Prototype.TransportBelt + ) + +get_connection_amount +~~~~~~~~~~~~~~~~~~~~~ + +Calculates required connection items. + +**Features:** + +- Pre-planning tool +- Works with all connection types +- Returns item count needed + +**Example:** + +.. code-block:: python + + # Calculate how many belts are needed + amount = get_connection_amount( + start_position=drill.drop_position, + end_position=chest.position, + connection_type=Prototype.TransportBelt + ) + print(f"Need {amount} belts") + +Crafting & Research +------------------- + +craft_item +~~~~~~~~~~ + +Creates items from components. + +**Features:** + +- Handles recursive crafting +- Validates technology requirements +- Returns crafted amount + +**Example:** + +.. code-block:: python + + # Craft 10 iron gear wheels + crafted = craft_item(Prototype.IronGearWheel, quantity=10) + +get_prototype_recipe +~~~~~~~~~~~~~~~~~~~~ + +Retrieves crafting requirements. + +**Features:** + +- Shows ingredients/products +- Includes crafting time +- Returns ``Recipe`` object + +**Example:** + +.. code-block:: python + + # Get recipe for electronic circuits + recipe = get_prototype_recipe(Prototype.ElectronicCircuit) + print(f"Ingredients: {recipe.ingredients}") + print(f"Crafting time: {recipe.energy}") + +set_entity_recipe +~~~~~~~~~~~~~~~~~ + +Configures machine crafting recipes. + +**Features:** + +- Works with assemblers/chemical plants +- Validates recipe requirements +- Returns updated entity + +**Example:** + +.. code-block:: python + + # Set an assembling machine to craft iron gear wheels + assembler = get_entity(Prototype.AssemblingMachine1, position) + set_entity_recipe(assembler, Prototype.IronGearWheel) + +set_research +~~~~~~~~~~~~ + +Initiates technology research. + +**Features:** + +- Validates prerequisites +- Returns required ingredients +- Handles research queue + +**Example:** + +.. code-block:: python + + # Start researching automation + research = set_research(Technology.Automation) + +get_research_progress +~~~~~~~~~~~~~~~~~~~~~ + +Monitors research status. + +**Features:** + +- Shows remaining requirements +- Tracks progress percentage +- Returns ingredient list + +**Example:** + +.. code-block:: python + + # Check research progress + progress = get_research_progress() + print(f"Current research: {progress.name}") + print(f"Progress: {progress.level}%") + +Movement & Utility +------------------ + +move_to +~~~~~~~ + +Moves player to position. + +**Features:** + +- Pathfinds around obstacles +- Can place items while moving +- Returns final position + +**Example:** + +.. code-block:: python + + # Move to iron ore patch + iron_position = nearest(Resource.IronOre) + move_to(iron_position) + +nearest_buildable +~~~~~~~~~~~~~~~~~ + +Finds valid building locations. + +**Features:** + +- Respects entity dimensions +- Handles resource requirements +- Returns buildable position + +**Example:** + +.. code-block:: python + + # Find a buildable position near iron ore + buildable_pos = nearest_buildable( + resource=Resource.IronOre, + entity=Prototype.BurnerMiningDrill + ) + +sleep +~~~~~ + +Pauses execution. + +**Features:** + +- Waits for actions to complete +- Adapts to game speed +- Maximum 15 second duration + +**Example:** + +.. code-block:: python + + # Wait for 5 seconds for production to occur + sleep(5) + + # Check drill status after waiting + drill = get_entity(Prototype.BurnerMiningDrill, drill_position) + print(f"Drill status: {drill.status}") + +launch_rocket +~~~~~~~~~~~~~ + +Controls rocket silo launches. + +**Features:** + +- Validates launch requirements +- Handles launch sequence +- Returns updated silo state + +**Example:** + +.. code-block:: python + + # Launch a rocket + silo = get_entity(Prototype.RocketSilo, silo_position) + launch_rocket(silo) + +Output +------ + +print +~~~~~ + +Outputs debug information to stdout. + +**Features:** + +- Supports various object types +- Useful for monitoring state +- Returns formatted string + +**Example:** + +.. code-block:: python + + # Print entity information + drill = get_entity(Prototype.BurnerMiningDrill, position) + print(f"Drill: {drill}") + print(f"Status: {drill.status}") + print(f"Position: {drill.position}") + + # Print inventory + inventory = inspect_inventory() + print(f"Inventory: {inventory}") + +Best Practices +-------------- + +1. **Store Results**: Save tool results as variables for later reference + + .. code-block:: python + + my_drill = place_entity(...) + # Later... + print(my_drill.status) + +2. **Check Status**: Verify entity status after operations + + .. code-block:: python + + drill = place_entity(...) + sleep(5) + assert drill.status == EntityStatus.WORKING + +3. **Handle Errors**: Use try-except for error handling + + .. code-block:: python + + try: + drill = place_entity(...) + except InvalidEntityPlacementException as e: + print(f"Placement failed: {e}") + +4. **Print for Debugging**: Use ``print()`` to observe state + + .. code-block:: python + + print(f"Entities: {get_entities()}") + print(f"Inventory: {inspect_inventory()}") + +5. **Wait for Actions**: Use ``sleep()`` to allow time for completion + + .. code-block:: python + + place_entity(...) + sleep(10) # Wait for production + +Next Steps +---------- + +- Learn how to :doc:`custom_tools` for specialized functionality +- Review :doc:`overview` for architectural details +- See :doc:`../getting_started/quickstart` for usage examples diff --git a/docs/sphinx/source/tools/custom_tools.rst b/docs/sphinx/source/tools/custom_tools.rst new file mode 100644 index 000000000..865712cdc --- /dev/null +++ b/docs/sphinx/source/tools/custom_tools.rst @@ -0,0 +1,454 @@ +Creating Custom Tools +===================== + +This guide explains how to create custom tools for FLE to extend agent capabilities with specialized functionality. + +Overview +-------- + +A custom tool requires three components: + +1. **agent.md**: Documentation for the agent +2. **client.py**: Python interface +3. **server.lua**: Lua implementation + +Tool Structure +-------------- + +Tools live in ``fle/env/tools/``: + +.. code-block:: text + + fle/env/tools/ + ├── admin/ # Non-agent accessible tools + └── agent/ # Agent-accessible tools + └── my_tool/ # Your custom tool + ├── agent.md + ├── client.py + └── server.lua + +Step-by-Step Guide +------------------ + +Step 1: Create Tool Directory +~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ + +Create a new directory in ``fle/env/tools/agent/``: + +.. code-block:: bash + + mkdir fle/env/tools/agent/my_tool + +Step 2: Create client.py +~~~~~~~~~~~~~~~~~~~~~~~~~ + +Create ``client.py`` with a class inheriting from ``Tool``: + +.. code-block:: python + + from typing import Optional + from fle.env.tools.tool import Tool + from fle.env.entities import Entity + from fle.env.models import Position + + class MyTool(Tool): + """ + Brief description of what your tool does. + """ + + def __call__(self, + entity: Entity, + target_position: Position, + quantity: Optional[int] = None) -> dict: + """ + Detailed description of the tool's functionality. + + Args: + entity: The entity to operate on + target_position: Where to perform the action + quantity: Optional quantity parameter + + Returns: + Dictionary containing result information + + Raises: + InvalidParameterException: If parameters are invalid + EntityNotFoundException: If entity doesn't exist + """ + # Call server-side implementation + result = self.execute( + entity=entity.name, + position=target_position.to_dict(), + quantity=quantity + ) + + return result + +**Key Requirements:** + +- Inherit from ``Tool`` +- Implement ``__call__`` method +- Use type annotations +- Call ``self.execute()`` to invoke server-side logic +- Document parameters, return values, and exceptions + +Step 3: Create server.lua +~~~~~~~~~~~~~~~~~~~~~~~~~~ + +Create ``server.lua`` with the game logic: + +.. code-block:: lua + + -- Register the tool action + global.actions.my_tool = function(params) + -- Extract parameters + local entity_name = params.entity + local position = params.position + local quantity = params.quantity or 1 + + -- Validate parameters + if not entity_name or not position then + return { + success = false, + error = "Missing required parameters" + } + end + + -- Find the entity + local entity = game.surfaces[1].find_entity(entity_name, position) + if not entity then + return { + success = false, + error = "Entity not found at position" + } + end + + -- Perform the action using Factorio API + local result = entity.some_action(quantity) + + -- Return serialized result + return { + success = true, + entity = serialize_entity(entity), + result = result + } + end + +**Key Requirements:** + +- Register function in ``global.actions`` +- Validate all parameters +- Use `Factorio API `_ +- Return a serializable table +- Include error handling + +Step 4: Create agent.md +~~~~~~~~~~~~~~~~~~~~~~~~ + +Create ``agent.md`` with agent-facing documentation: + +.. code-block:: markdown + + # My Tool + + ## Description + + Brief description of what the tool does and when to use it. + + ## Usage + + ```python + result = my_tool( + entity=my_entity, + target_position=Position(x=10, y=20), + quantity=5 + ) + ``` + + ## Parameters + + - `entity` (Entity): The entity to operate on + - `target_position` (Position): Where to perform the action + - `quantity` (int, optional): How many items to process. Defaults to 1. + + ## Returns + + Dictionary containing: + - `success` (bool): Whether the operation succeeded + - `entity` (Entity): Updated entity object + - `result`: Operation-specific result data + + ## Best Practices + + 1. Always check entity status before calling + 2. Use reasonable quantity values + 3. Verify results with assertions + + ## Common Pitfalls + + - Entity must exist at the specified position + - Target position must be valid + - Quantity cannot exceed inventory limits + + ## Examples + + ### Basic Usage + + ```python + entity = get_entity(Prototype.Chest, Position(x=0, y=0)) + result = my_tool(entity, Position(x=5, y=5), quantity=10) + assert result['success'] + ``` + + ### Error Handling + + ```python + try: + result = my_tool(entity, position) + except InvalidParameterException as e: + print(f"Invalid parameters: {e}") + ``` + +Step 5: Test Your Tool +~~~~~~~~~~~~~~~~~~~~~~~ + +Create a test in ``fle/env/tests/actions/``: + +.. code-block:: python + + import pytest + from fle.env.gym_env import FactorioGymEnv + from fle.env.models import Position + + def test_my_tool(): + env = FactorioGymEnv() + obs = env.reset() + + # Setup test scenario + code = """ + entity = place_entity( + Prototype.Chest, + Position(x=0, y=0), + Direction.NORTH + ) + + # Test your tool + result = my_tool( + entity=entity, + target_position=Position(x=5, y=5), + quantity=10 + ) + + print(result) + assert result['success'] + """ + + action = Action(agent_idx=0, code=code) + obs, reward, done, truncated, info = env.step(action) + + # Verify results + assert "success" in obs['raw_text'] + env.close() + +Complete Example +---------------- + +Here's a complete example of a tool that transfers items between two chests: + +**client.py:** + +.. code-block:: python + + from typing import Optional + from fle.env.tools.tool import Tool + from fle.env.entities import Entity + + class TransferItems(Tool): + """Transfers items between two entities.""" + + def __call__(self, + source: Entity, + destination: Entity, + item: str, + quantity: int) -> dict: + """ + Transfer items from source to destination. + + Args: + source: Entity to take items from + destination: Entity to place items into + item: Item prototype name + quantity: Number of items to transfer + + Returns: + Dictionary with transfer results + + Raises: + InsufficientItemsException: Not enough items in source + InventoryFullException: Destination inventory is full + """ + result = self.execute( + source=source.name, + source_position=source.position.to_dict(), + destination=destination.name, + destination_position=destination.position.to_dict(), + item=item, + quantity=quantity + ) + + return result + +**server.lua:** + +.. code-block:: lua + + global.actions.transfer_items = function(params) + local source = game.surfaces[1].find_entity( + params.source, + params.source_position + ) + local destination = game.surfaces[1].find_entity( + params.destination, + params.destination_position + ) + + if not source or not destination then + return {success = false, error = "Entity not found"} + end + + -- Get source inventory + local source_inv = source.get_inventory(defines.inventory.chest) + if not source_inv then + return {success = false, error = "No source inventory"} + end + + -- Check if enough items + local available = source_inv.get_item_count(params.item) + if available < params.quantity then + return { + success = false, + error = "Insufficient items", + available = available + } + end + + -- Transfer items + local removed = source_inv.remove({ + name = params.item, + count = params.quantity + }) + + local dest_inv = destination.get_inventory(defines.inventory.chest) + local inserted = dest_inv.insert({ + name = params.item, + count = removed + }) + + -- Return any excess + if inserted < removed then + source_inv.insert({ + name = params.item, + count = removed - inserted + }) + end + + return { + success = true, + transferred = inserted, + source = serialize_entity(source), + destination = serialize_entity(destination) + } + end + +**agent.md:** + +.. code-block:: markdown + + # Transfer Items + + Transfer items between two entities' inventories. + + ## Usage + + ```python + source_chest = get_entity(Prototype.IronChest, Position(x=0, y=0)) + dest_chest = get_entity(Prototype.IronChest, Position(x=5, y=5)) + + result = transfer_items( + source=source_chest, + destination=dest_chest, + item='iron-plate', + quantity=50 + ) + ``` + + ## Best Practices + + 1. Check source has enough items before transferring + 2. Verify destination has space + 3. Handle partial transfers gracefully + +Automatic Registration +---------------------- + +Once your tool is created, it will be automatically: + +1. Discovered by the environment +2. Available to agents in the Python namespace +3. Documented in agent context with the ``agent.md`` content + +No additional registration steps are needed! + +Tips & Best Practices +---------------------- + +1. **Keep It Simple**: Tools should do one thing well +2. **Validate Early**: Check parameters in both client and server +3. **Document Thoroughly**: Agents rely on good documentation +4. **Handle Errors**: Provide clear error messages +5. **Test Extensively**: Create comprehensive test cases +6. **Use Type Hints**: Make the interface clear with Python type annotations +7. **Serialize Carefully**: Ensure all return values are JSON-serializable + +Common Patterns +--------------- + +Querying Entity State +~~~~~~~~~~~~~~~~~~~~~ + +.. code-block:: lua + + local entity = game.surfaces[1].find_entity(name, position) + return serialize_entity(entity) + +Modifying Inventory +~~~~~~~~~~~~~~~~~~~ + +.. code-block:: lua + + local inventory = entity.get_inventory(defines.inventory.chest) + inventory.insert({name = item, count = quantity}) + +Moving Entities +~~~~~~~~~~~~~~~ + +.. code-block:: lua + + local success = entity.teleport(new_position) + +Checking Validity +~~~~~~~~~~~~~~~~~ + +.. code-block:: lua + + if not entity.valid then + return {success = false, error = "Entity no longer exists"} + end + +Next Steps +---------- + +- Review :doc:`core_tools` for implementation patterns +- See :doc:`overview` for architecture details +- Check the `Factorio Lua API `_ +- Join the `Discord `_ for help diff --git a/docs/sphinx/source/tools/extract_item.rst b/docs/sphinx/source/tools/extract_item.rst deleted file mode 100644 index 9e5d0d21f..000000000 --- a/docs/sphinx/source/tools/extract_item.rst +++ /dev/null @@ -1,98 +0,0 @@ -extract_item -============ - -Removes items from entity inventories. - -Overview --------- - -The `extract_item` tool allows agents to remove items from entity inventories and transfer them to the player's inventory. - -Parameters ----------- - -**entity** (Entity) - The entity to extract items from. - -**item** (str) - The name of the item to extract. - -**count** (int, optional) - The number of items to extract. Defaults to 1. - -Returns -------- - -Dictionary containing: - -- **success** (bool): Whether the extraction succeeded -- **extracted_count** (int): Number of items actually extracted -- **entity** (Entity): The updated entity -- **error** (str): Error message (if failed) - -Examples --------- - -**Basic Usage** - .. code-block:: python - - # Extract iron ore from a chest - result = extract_item( - entity=chest, - item='iron-ore', - count=10 - ) - - if result.get('success'): - print(f"Extracted {result.get('extracted_count')} iron ore") - else: - print(f"Error: {result.get('error')}") - -**Extract All Items** - .. code-block:: python - - # Extract all items from an entity - inventory = inspect_inventory(entity=chest) - for item, count in inventory.items(): - if count > 0: - result = extract_item( - entity=chest, - item=item, - count=count - ) - - if result.get('success'): - print(f"Extracted {result.get('extracted_count')} {item}") - -Best Practices --------------- - -1. **Check Entity Contents**: Verify the entity has the items to extract -2. **Handle Partial Extractions**: Account for cases where not all items can be extracted -3. **Monitor Player Inventory**: Track player inventory changes -4. **Use Appropriate Counts**: Don't extract more items than available - -Failure Modes -------------- - -**Invalid Entity** - - **Error**: "Entity does not support item extraction" - - **Cause**: Entity type doesn't support inventory - - **Solution**: Check entity type before extraction - -**Item Not Available** - - **Error**: "Item not available in entity inventory" - - **Cause**: Entity doesn't have the required item - - **Solution**: Check entity inventory before extraction - -**Player Inventory Full** - - **Error**: "Player inventory is full" - - **Cause**: Player cannot accept more items - - **Solution**: Clear player inventory or use storage - -Related Tools -------------- - -- :doc:`inspect_inventory` - Check inventory contents -- :doc:`insert_item` - Add items to entities -- :doc:`get_entities` - Find entities with storage diff --git a/docs/sphinx/source/tools/index.rst b/docs/sphinx/source/tools/index.rst deleted file mode 100644 index 3d3e1edc0..000000000 --- a/docs/sphinx/source/tools/index.rst +++ /dev/null @@ -1,209 +0,0 @@ -Tools Documentation -=================== - -This section contains detailed documentation for all available tools in the Factorio Learning Environment. - -Tool Categories ---------------- - -**Inventory Management** - Tools for managing inventories and items - -**Entity Management** - Tools for placing, removing, and managing entities - -**Entity Queries** - Tools for finding and inspecting entities - -**Resource Management** - Tools for resource collection and management - -**Connection Management** - Tools for creating connections between entities - -**Crafting and Research** - Tools for crafting items and managing research - -**Movement and Control** - Tools for player movement and game control - -**Debugging and Output** - Tools for debugging and output - -Core Tools ----------- - -Inventory Management -~~~~~~~~~~~~~~~~~~~~ - -.. toctree:: - :maxdepth: 1 - - tools/inspect_inventory - tools/insert_item - tools/extract_item - -Entity Management -~~~~~~~~~~~~~~~~ - -.. toctree:: - :maxdepth: 1 - - tools/place_entity - tools/place_entity_next_to - tools/pickup_entity - tools/rotate_entity - -Entity Queries -~~~~~~~~~~~~~~ - -.. toctree:: - :maxdepth: 1 - - tools/get_entity - tools/get_entities - tools/nearest - tools/nearest_buildable - -Resource Management -~~~~~~~~~~~~~~~~~~~ - -.. toctree:: - :maxdepth: 1 - - tools/get_resource_patch - tools/harvest_resource - -Connection Management -~~~~~~~~~~~~~~~~~~~~ - -.. toctree:: - :maxdepth: 1 - - tools/connect_entities - tools/get_connection_amount - -Crafting and Research -~~~~~~~~~~~~~~~~~~~~~ - -.. toctree:: - :maxdepth: 1 - - tools/set_entity_recipe - tools/get_prototype_recipe - tools/craft_item - tools/set_research - tools/get_research_progress - -Movement and Control -~~~~~~~~~~~~~~~~~~~~ - -.. toctree:: - :maxdepth: 1 - - tools/move_to - tools/sleep - tools/launch_rocket - -Debugging and Output -~~~~~~~~~~~~~~~~~~~~ - -.. toctree:: - :maxdepth: 1 - - tools/print - -Tool Usage Patterns -------------------- - -**Basic Usage** - Most tools follow a simple pattern: - - .. code-block:: python - - # Get information - result = tool_name(parameters) - - # Check result - if result.get('success'): - # Use the result - data = result.get('data') - else: - # Handle error - error = result.get('error') - -**Error Handling** - All tools return structured results with error information: - - .. code-block:: python - - result = place_entity( - entity=Prototype.MiningDrill, - position=Position(10, 20), - direction=Direction.NORTH - ) - - if result.get('success'): - entity = result.get('entity') - print(f"Placed entity: {entity}") - else: - error = result.get('error') - print(f"Error: {error}") - -**Chaining Operations** - Tools can be chained together for complex operations: - - .. code-block:: python - - # Place a mining drill - drill = place_entity( - entity=Prototype.MiningDrill, - position=nearest(Resource.IronOre), - direction=Direction.NORTH - ) - - # Place a chest next to it - chest = place_entity_next_to( - entity=Prototype.IronChest, - reference_position=drill.drop_position, - direction=Direction.SOUTH - ) - - # Connect them - connect_entities(drill, chest) - -Best Practices --------------- - -1. **Check Results**: Always check tool return values -2. **Handle Errors**: Implement proper error handling -3. **Use Type Hints**: Leverage type information for better code -4. **Chain Operations**: Combine tools for complex tasks -5. **Monitor Performance**: Track tool usage and performance -6. **Document Usage**: Document tool usage patterns -7. **Test Thoroughly**: Test all tool combinations - -Tool Development ----------------- - -**Creating Custom Tools** - See the :doc:`customization guide <../customization/tools>` for information on creating custom tools. - -**Tool Testing** - Test tools thoroughly with various scenarios: - - - Valid inputs - - Invalid inputs - - Edge cases - - Error conditions - - Performance scenarios - -**Tool Documentation** - Document tools with: - - - Clear descriptions - - Parameter specifications - - Return value documentation - - Usage examples - - Best practices - - Failure modes diff --git a/docs/sphinx/source/tools/insert_item.rst b/docs/sphinx/source/tools/insert_item.rst deleted file mode 100644 index 324873580..000000000 --- a/docs/sphinx/source/tools/insert_item.rst +++ /dev/null @@ -1,101 +0,0 @@ -insert_item -=========== - -Places items from player inventory into entities. - -Overview --------- - -The `insert_item` tool allows agents to transfer items from their inventory into entity inventories such as chests, furnaces, and other storage containers. - -Parameters ----------- - -**entity** (Entity) - The entity to insert items into. - -**item** (str) - The name of the item to insert. - -**count** (int, optional) - The number of items to insert. Defaults to 1. - -Returns -------- - -Dictionary containing: - -- **success** (bool): Whether the insertion succeeded -- **inserted_count** (int): Number of items actually inserted -- **entity** (Entity): The updated entity -- **error** (str): Error message (if failed) - -Examples --------- - -**Basic Usage** - .. code-block:: python - - # Insert iron ore into a chest - result = insert_item( - entity=chest, - item='iron-ore', - count=10 - ) - - if result.get('success'): - print(f"Inserted {result.get('inserted_count')} iron ore") - else: - print(f"Error: {result.get('error')}") - -**Insert Multiple Items** - .. code-block:: python - - # Insert different items into a furnace - items_to_insert = [ - {'item': 'iron-ore', 'count': 50}, - {'item': 'coal', 'count': 10} - ] - - for item_data in items_to_insert: - result = insert_item( - entity=furnace, - item=item_data['item'], - count=item_data['count'] - ) - - if result.get('success'): - print(f"Inserted {result.get('inserted_count')} {item_data['item']}") - -Best Practices --------------- - -1. **Check Entity Type**: Ensure the entity supports item insertion -2. **Verify Item Compatibility**: Check that the item can be inserted into the entity -3. **Handle Partial Insertions**: Account for cases where not all items can be inserted -4. **Monitor Inventory**: Track inventory changes after insertion - -Failure Modes -------------- - -**Invalid Entity** - - **Error**: "Entity does not support item insertion" - - **Cause**: Entity type doesn't support inventory - - **Solution**: Check entity type before insertion - -**Item Not Available** - - **Error**: "Item not available in player inventory" - - **Cause**: Player doesn't have the required item - - **Solution**: Check player inventory before insertion - -**Entity Full** - - **Error**: "Entity inventory is full" - - **Cause**: Entity cannot accept more items - - **Solution**: Check entity capacity or use different entity - -Related Tools -------------- - -- :doc:`inspect_inventory` - Check inventory contents -- :doc:`extract_item` - Remove items from entities -- :doc:`get_entities` - Find entities with storage diff --git a/docs/sphinx/source/tools/inspect_inventory.rst b/docs/sphinx/source/tools/inspect_inventory.rst deleted file mode 100644 index 132a7cad0..000000000 --- a/docs/sphinx/source/tools/inspect_inventory.rst +++ /dev/null @@ -1,153 +0,0 @@ -inspect_inventory -================= - -Checks contents of player or entity inventories. - -Overview --------- - -The `inspect_inventory` tool allows agents to examine the contents of inventories. It supports various inventory types including player inventories, chests, furnaces, and other entities with storage capabilities. - -Parameters ----------- - -**entity** (Entity, optional) - The entity whose inventory to inspect. If not provided, inspects the player's inventory. - -**inventory_type** (str, optional) - The type of inventory to inspect. Options: 'player', 'entity', 'all'. - -Returns -------- - -Dictionary containing: - -- **success** (bool): Whether the inspection succeeded -- **inventory** (Inventory): The inventory contents -- **entity** (Entity): The entity whose inventory was inspected (if applicable) -- **error** (str): Error message (if failed) - -Examples --------- - -**Basic Usage** - .. code-block:: python - - # Inspect player inventory - result = inspect_inventory() - - if result.get('success'): - inventory = result.get('inventory') - print(f"Player inventory: {inventory}") - - # Check specific items - iron_ore = inventory.get('iron-ore', 0) - coal = inventory.get('coal', 0) - print(f"Iron ore: {iron_ore}, Coal: {coal}") - else: - print(f"Error: {result.get('error')}") - -**Entity Inventory** - .. code-block:: python - - # Inspect entity inventory - entities = get_entities() - for entity in entities: - if entity.name == 'iron-chest': - result = inspect_inventory(entity=entity) - - if result.get('success'): - inventory = result.get('inventory') - print(f"Chest inventory: {inventory}") - - # Check if chest is full - total_items = sum(inventory.values()) - if total_items > 0: - print(f"Chest contains {total_items} items") - break - -**Inventory Analysis** - .. code-block:: python - - # Analyze inventory contents - result = inspect_inventory() - - if result.get('success'): - inventory = result.get('inventory') - - # Count total items - total_items = sum(inventory.values()) - print(f"Total items: {total_items}") - - # List all items - for item, count in inventory.items(): - if count > 0: - print(f" {item}: {count}") - - # Check for specific resources - resources = ['iron-ore', 'copper-ore', 'coal', 'stone'] - for resource in resources: - count = inventory.get(resource, 0) - if count > 0: - print(f"Have {count} {resource}") - -**Inventory Filtering** - .. code-block:: python - - # Check for specific items - result = inspect_inventory() - - if result.get('success'): - inventory = result.get('inventory') - - # Check for mining equipment - mining_items = ['mining-drill', 'burner-mining-drill'] - for item in mining_items: - count = inventory.get(item, 0) - if count > 0: - print(f"Have {count} {item}") - - # Check for building materials - building_materials = ['iron-plate', 'copper-plate', 'stone'] - total_materials = sum(inventory.get(item, 0) for item in building_materials) - print(f"Total building materials: {total_materials}") - -Best Practices --------------- - -1. **Check Success**: Always verify the inspection succeeded -2. **Handle Empty Inventories**: Account for empty inventories -3. **Use Inventory Methods**: Leverage inventory utility methods -4. **Monitor Changes**: Track inventory changes over time -5. **Error Handling**: Implement proper error handling - -Failure Modes -------------- - -**Invalid Entity** - - **Error**: "Entity does not have an inventory" - - **Cause**: Entity type doesn't support inventory - - **Solution**: Check entity type before inspection - -**Entity Not Found** - - **Error**: "Entity not found or no longer exists" - - **Cause**: Entity was removed or doesn't exist - - **Solution**: Verify entity exists before inspection - -**Permission Denied** - - **Error**: "Permission denied to inspect inventory" - - **Cause**: Insufficient permissions - - **Solution**: Check agent permissions - -**Network Error** - - **Error**: "Network error during inventory inspection" - - **Cause**: Communication failure with game server - - **Solution**: Retry the operation - -Related Tools -------------- - -- :doc:`insert_item` - Place items into inventories -- :doc:`extract_item` - Remove items from inventories -- :doc:`get_entities` - Find entities with inventories -- :doc:`place_entity` - Place entities with storage diff --git a/docs/sphinx/source/tools/overview.rst b/docs/sphinx/source/tools/overview.rst new file mode 100644 index 000000000..235aa32db --- /dev/null +++ b/docs/sphinx/source/tools/overview.rst @@ -0,0 +1,189 @@ +Tools Overview +============== + +Agents interact with the game using *tools*, which represent a narrow API into the game. Tools are functions that agents can call to perform actions and retrieve information. + +What are Tools? +--------------- + +**Tools** are functions that: + +- Perform a game action (e.g., placing an entity, crafting an item) +- Return a typed object (e.g., ``Entity``, ``Inventory``, ``Recipe``) +- Can be stored as named variables in the Python namespace for later use + +Tools live in ``fle/env/tools/``, and are either: + +- **Admin tools**: Non-agent accessible, used for environment management +- **Agent tools**: Used by agents to interact with the game + +Tool Architecture +----------------- + +.. code-block:: text + + ┌─────────────────┐ + │ Agent │ + │ (Synthesizes │ + │ Python Code) │ + └────────┬────────┘ + │ + ┌────────▼────────────────────┐ + │ Learning Environment │ + │ ┌────────────────────┐ │ + │ │ Interpreter │ │ + │ └─────────┬──────────┘ │ + │ │ │ + │ ┌─────────▼──────────┐ │ + │ │ client.py │◄───┼─── Exceptions + │ │ (Python Interface)│ │ + │ └─────────┬──────────┘ │ + │ │ │ + │ │ Objects │ + └────────────┼─────────────────┘ + │ + │ Remote TCP Call + │ + ┌────────────▼─────────────────┐ + │ Factorio Server │ + │ ┌─────────────────────┐ │ + │ │ server.lua │ │ + │ │ (Game Logic) │ │ + │ └─────────┬───────────┘ │ + │ │ │ + │ ┌─────────▼───────────┐ │ + │ │ Factorio Engine │ │ + │ │ (Game Simulation) │ │ + │ └─────────────────────┘ │ + └──────────────────────────────┘ + +Anatomy of a Tool +----------------- + +A tool requires 3 files: + +1. **agent.md**: The agent documentation for the tool, including usage patterns, best practices, and failure modes +2. **client.py**: The client-side implementation - a Python class that can be invoked by the agent +3. **server.lua**: The server-side implementation - handles most of the logic and heavy lifting + +Tool Categories +--------------- + +Tools can be grouped into several categories: + +Inventory Management +~~~~~~~~~~~~~~~~~~~~ + +- ``inspect_inventory``: Check contents of player or entity inventories +- ``insert_item``: Place items from player inventory into entities +- ``extract_item``: Remove items from entity inventories + +Entity Manipulation +~~~~~~~~~~~~~~~~~~~ + +- ``place_entity``: Place entities in the world +- ``place_entity_next_to``: Place entities relative to others +- ``pickup_entity``: Remove entities from the world +- ``rotate_entity``: Change entity orientation +- ``get_entity``: Retrieve entity objects at positions +- ``get_entities``: Find multiple entities in an area + +Resource Operations +~~~~~~~~~~~~~~~~~~~ + +- ``nearest``: Locate closest resources/entities +- ``get_resource_patch``: Analyze resource deposits +- ``harvest_resource``: Gather resources from the world + +Connections +~~~~~~~~~~~ + +- ``connect_entities``: Create connections between entities +- ``get_connection_amount``: Calculate required connection items + +Crafting & Research +~~~~~~~~~~~~~~~~~~~ + +- ``craft_item``: Create items from components +- ``get_prototype_recipe``: Retrieve crafting requirements +- ``set_entity_recipe``: Configure machine crafting recipes +- ``set_research``: Initiate technology research +- ``get_research_progress``: Monitor research status + +Movement & Utility +~~~~~~~~~~~~~~~~~~ + +- ``move_to``: Move player to position +- ``nearest_buildable``: Find valid building locations +- ``sleep``: Pause execution +- ``launch_rocket``: Control rocket silo launches + +Output +~~~~~~ + +- ``print``: Output debug information to stdout + +Using Tools +----------- + +Tools are called like normal Python functions within agent code: + +.. code-block:: python + + # Find nearest iron ore + iron_position = nearest(Resource.IronOre) + + # Place a mining drill + drill = place_entity( + entity=Prototype.MiningDrill, + position=iron_position, + direction=Direction.NORTH + ) + + # Check the drill's status + print(f"Drill status: {drill.status}") + + # Store result for later use + my_first_drill = drill + +Return Values +------------- + +Tools return typed objects that can be: + +- **Inspected**: Access attributes like ``drill.status`` or ``inventory.items`` +- **Stored**: Save as variables for future reference +- **Printed**: Display information to stdout for observation + +Common Return Types +~~~~~~~~~~~~~~~~~~~ + +- ``Entity``: Represents a game entity (drill, chest, inserter, etc.) +- ``Inventory``: Contains items and quantities +- ``Recipe``: Describes crafting requirements +- ``Position``: X, Y coordinates +- ``ResourcePatch``: Information about resource deposits + +Error Handling +-------------- + +Tools raise typed exceptions with detailed context when: + +- Invalid parameters are provided +- Required resources are unavailable +- Game constraints are violated (e.g., invalid placement) +- Entities don't exist or have been destroyed + +Example error: + +.. code-block:: python + + InvalidEntityPlacementException: Cannot place burner-mining-drill at + Position(x=10, y=20) - location is occupied by iron-chest + +Next Steps +---------- + +- See :doc:`core_tools` for detailed documentation on each tool +- Learn how to :doc:`custom_tools` for specialized functionality +- Review the :doc:`../environment/overview` to understand the full context diff --git a/docs/sphinx/source/tools/place_entity.rst b/docs/sphinx/source/tools/place_entity.rst deleted file mode 100644 index 38162c9d1..000000000 --- a/docs/sphinx/source/tools/place_entity.rst +++ /dev/null @@ -1,134 +0,0 @@ -place_entity -============ - -Places entities in the world at specified positions. - -Overview --------- - -The `place_entity` tool allows agents to place various entities in the game world. It handles placement validation, direction setting, and returns information about the placed entity. - -Parameters ----------- - -**entity** (Prototype) - The type of entity to place. Must be a valid Prototype enum value. - -**position** (Position) - The position where to place the entity. Must be a valid Position object. - -**direction** (Direction, optional) - The direction to orient the entity. Defaults to Direction.NORTH. - -Returns -------- - -Dictionary containing: - -- **success** (bool): Whether the placement succeeded -- **entity** (Entity): The placed entity object (if successful) -- **error** (str): Error message (if failed) - -Examples --------- - -**Basic Usage** - .. code-block:: python - - # Place a mining drill - result = place_entity( - entity=Prototype.MiningDrill, - position=Position(10, 20), - direction=Direction.NORTH - ) - - if result.get('success'): - drill = result.get('entity') - print(f"Placed mining drill at {drill.position}") - else: - print(f"Error: {result.get('error')}") - -**With Resource Location** - .. code-block:: python - - # Find iron ore and place mining drill - iron_pos = nearest(Resource.IronOre) - if iron_pos: - result = place_entity( - entity=Prototype.MiningDrill, - position=iron_pos, - direction=Direction.NORTH - ) - - if result.get('success'): - drill = result.get('entity') - print(f"Placed mining drill on iron ore at {drill.position}") - -**Direction Examples** - .. code-block:: python - - # Place entities in different directions - drill_north = place_entity( - entity=Prototype.MiningDrill, - position=Position(0, 0), - direction=Direction.NORTH - ) - - drill_south = place_entity( - entity=Prototype.MiningDrill, - position=Position(10, 0), - direction=Direction.SOUTH - ) - - drill_east = place_entity( - entity=Prototype.MiningDrill, - position=Position(20, 0), - direction=Direction.EAST - ) - - drill_west = place_entity( - entity=Prototype.MiningDrill, - position=Position(30, 0), - direction=Direction.WEST - ) - -Best Practices --------------- - -1. **Check Position Validity**: Ensure the position is valid for the entity type -2. **Handle Errors**: Always check the success flag and handle errors -3. **Use Appropriate Directions**: Choose directions that make sense for the entity -4. **Validate Resources**: Ensure required resources are available -5. **Monitor Placement**: Check that entities are placed correctly - -Failure Modes -------------- - -**Invalid Entity Type** - - **Error**: "Invalid entity type 'invalid'. Expected Prototype enum value." - - **Cause**: Using an invalid entity type - - **Solution**: Use valid Prototype enum values - -**Invalid Position** - - **Error**: "Position (x, y) is not valid for entity type" - - **Cause**: Position conflicts with existing entities or terrain - - **Solution**: Choose a different position or clear the area - -**Insufficient Resources** - - **Error**: "Insufficient resources to place entity" - - **Cause**: Not enough items in inventory - - **Solution**: Ensure required items are available - -**Invalid Direction** - - **Error**: "Invalid direction for entity type" - - **Cause**: Direction not supported by entity type - - **Solution**: Use supported directions for the entity - -Related Tools -------------- - -- :doc:`place_entity_next_to` - Place entities relative to others -- :doc:`pickup_entity` - Remove entities from the world -- :doc:`rotate_entity` - Change entity orientation -- :doc:`nearest` - Find nearest resources or entities -- :doc:`nearest_buildable` - Find valid building locations diff --git a/pyproject.toml b/pyproject.toml index 1e2da2fb7..de73dd357 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -44,9 +44,6 @@ dependencies = [ "a2a-sdk", # send_message tool + multiagent, "huggingface-hub>=0.35.3", "memoization>=0.4.0", - "sphinx>=8.1.3", - "sphinx-rtd-theme>=3.0.2", - "sphinx-autodoc-typehints>=3.0.1", ] [project.optional-dependencies]