mirror of
https://github.com/open-thought/reasoning-gym.git
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* feat: Add optional curriculum support to dataset registration and creation * docs: Add docstrings to create_curriculum() and register_dataset() * feat: Add curriculum configuration classes for CurriculumExperiment * feat: Add weight parameter to CurriculumAttributeConfig and use in DatasetSpec * refactor: Simplify CurriculumAttributeConfig with "*" attribute level support * test: Add unit tests for CurriculumExperiment class * feat: Add from_yaml() method to CurriculumExperimentConfig with unit test
170 lines
6.3 KiB
Python
170 lines
6.3 KiB
Python
"""FastAPI server implementation for Reasoning Gym."""
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import logging
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from fastapi import FastAPI, HTTPException
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from reasoning_gym.coaching.registry import ExperimentRegistry
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from reasoning_gym.composite import CompositeConfig, DatasetSpec
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from .config import ServerConfig
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from .middleware import APIKeyMiddleware
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from .models import (
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BatchEntry,
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BatchResponse,
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DatasetConfigUpdate,
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ExperimentCreate,
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ExperimentList,
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ExperimentResponse,
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ScoringRequest,
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ScoringResponse,
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)
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def create_app(config: ServerConfig) -> FastAPI:
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"""Create and configure the FastAPI application."""
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# Configure logging
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logging.basicConfig(level=config.log_level)
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logger = logging.getLogger(__name__)
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# Create FastAPI app
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app = FastAPI(title="Reasoning Gym Server")
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# Add middleware
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app.add_middleware(APIKeyMiddleware, api_key=config.api_key)
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# Initialize registry
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registry = ExperimentRegistry()
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@app.get("/health")
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async def health_check():
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"""Health check endpoint."""
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return {"status": "healthy"}
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@app.post("/experiments", response_model=ExperimentResponse)
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async def create_experiment(experiment: ExperimentCreate):
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"""Create a new experiment."""
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# Convert dict format to DatasetSpec list
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dataset_specs = []
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for name, spec in experiment.datasets.items():
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dataset_specs.append(DatasetSpec(name=name, weight=spec.get("weight", 1.0), config=spec.get("config", {})))
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config = CompositeConfig(size=experiment.size, seed=experiment.seed, datasets=dataset_specs)
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try:
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registry.register_experiment(experiment.name, config)
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except Exception as e:
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raise HTTPException(status_code=400, detail=str(e))
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return ExperimentResponse(
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name=experiment.name, size=experiment.size, seed=experiment.seed, datasets=experiment.datasets
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)
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@app.get("/experiments", response_model=ExperimentList)
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async def list_experiments():
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"""List all registered experiments."""
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return ExperimentList(experiments=registry.list_experiments())
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@app.delete("/experiments/{name}")
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async def delete_experiment(name: str):
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"""Delete an experiment."""
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if not registry.remove_experiment(name):
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raise HTTPException(status_code=404, detail=f"Experiment '{name}' not found")
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return {"status": "deleted"}
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@app.get("/experiments/{name}/batch", response_model=BatchResponse)
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async def generate_batch(name: str, base_index: int, batch_size: int):
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"""Generate a batch of raw entries"""
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# Validate parameters
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if base_index < 0:
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raise HTTPException(status_code=400, detail="base_index must be non-negative")
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if batch_size <= 0:
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raise HTTPException(status_code=400, detail="batch_size must be positive")
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experiment = registry.get_experiment(name)
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if not experiment:
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raise HTTPException(status_code=404, detail=f"Experiment '{name}' not found")
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try:
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entries = []
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for i in range(base_index, base_index + batch_size):
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entry = experiment.get_dataset_entry(i)
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# Create BatchEntry with minimal required data
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batch_entry = BatchEntry(
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question=entry["question"],
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entry_id=f"{entry['metadata']['entry_id']}",
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metadata=entry["metadata"],
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)
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entries.append(batch_entry)
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return BatchResponse(entries=entries)
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except Exception as e:
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raise HTTPException(status_code=400, detail=str(e))
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@app.post("/experiments/{name}/score", response_model=ScoringResponse)
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async def score_outputs(name: str, request: ScoringRequest):
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"""Score extracted answers"""
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experiment = registry.get_experiment(name)
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if not experiment:
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raise HTTPException(status_code=404, detail=f"Experiment '{name}' not found")
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try:
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scores = []
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entry_ids = []
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for item in request.answers:
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score = experiment.score_answer_with_id(item.answer, item.entry_id)
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scores.append(score)
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entry_ids.append(item.entry_id)
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return ScoringResponse(scores=scores, entry_ids=entry_ids)
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except Exception as e:
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raise HTTPException(status_code=400, detail=str(e))
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@app.get("/experiments/{name}/composite", response_model=ExperimentResponse)
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async def get_composite_config(name: str):
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"""Get composite configuration for an experiment."""
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experiment = registry.get_experiment(name)
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if not experiment:
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raise HTTPException(status_code=404, detail=f"Experiment '{name}' not found")
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# Convert internal config to API response format
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datasets = {}
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for ds_spec in experiment.config.datasets:
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dataset = experiment.composite.datasets[ds_spec.name]
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datasets[ds_spec.name] = {
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"weight": ds_spec.weight,
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"config": vars(dataset.config), # Get current config from dataset instance
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}
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return ExperimentResponse(
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name=name, size=experiment.config.size, seed=experiment.config.seed, datasets=datasets
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)
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@app.post("/experiments/{name}/composite/{dataset_name}")
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async def update_dataset_config(name: str, dataset_name: str, config_update: DatasetConfigUpdate):
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"""Update configuration for a specific dataset in the composite."""
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experiment = registry.get_experiment(name)
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if not experiment:
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raise HTTPException(status_code=404, detail=f"Experiment '{name}' not found")
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try:
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experiment.composite.update_dataset_config(dataset_name, config_update.config)
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return {"status": "updated"}
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except KeyError:
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raise HTTPException(status_code=404, detail=f"Dataset '{dataset_name}' not found in experiment")
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except Exception as e:
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raise HTTPException(status_code=400, detail=str(e))
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return app
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async def app(scope, receive, send):
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"""ASGI application that lazily creates the FastAPI app."""
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if not hasattr(app, "server_app"):
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app.server_app = create_app(ServerConfig())
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await app.server_app(scope, receive, send)
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