# Copyright (c) Meta Platforms, Inc. and affiliates. # All rights reserved. # # This source code is licensed under the BSD-style license found in the # LICENSE file in the root directory of this source tree. """ FastAPI application for the Explainer Env Environment. This module creates an HTTP server that exposes the ExplainerEnvironment over HTTP and WebSocket endpoints, compatible with EnvClient. Endpoints: - POST /reset: Reset the environment - POST /step: Execute an action - GET /state: Get current environment state - GET /schema: Get action/observation schemas - WS /ws: WebSocket endpoint for persistent sessions Usage: # Development (with auto-reload): uvicorn server.app:app --reload --host 0.0.0.0 --port 8000 # Production: uvicorn server.app:app --host 0.0.0.0 --port 8000 --workers 4 # Or run directly: python -m server.app """ import os from contextlib import asynccontextmanager try: from openenv.core.env_server.http_server import create_app except Exception as e: # pragma: no cover raise ImportError("openenv is required for the web interface. Install dependencies with '\n uv sync\n'") from e try: from ..models import ExplainerAction, ExplainerObservation from ..research.retrieval import EMBEDDING_CACHE_DIR, EMBEDDING_MODEL_NAME, preload_embedding_model from .explainer_env_environment import ExplainerEnvironment except ImportError: from models import ExplainerAction, ExplainerObservation from research.retrieval import EMBEDDING_CACHE_DIR, EMBEDDING_MODEL_NAME, preload_embedding_model from server.explainer_env_environment import ExplainerEnvironment def _build_dashboard_tab(*_args, **_kwargs): """Return the project dashboard as an OpenEnv custom web-interface tab.""" try: from ..dashboard import build_ui except ImportError: # pragma: no cover - supports uvicorn server.app:app from dashboard import build_ui return build_ui() # Serve the dashboard from the same FastAPI service by default. OpenEnv only # attaches gradio_builder when its web interface is enabled. os.environ.setdefault("ENABLE_WEB_INTERFACE", "true") # Create the app with web interface, README integration, and the dashboard tab. app = create_app( ExplainerEnvironment, ExplainerAction, ExplainerObservation, env_name="explainer_env", max_concurrent_envs=4, # parallel training rollouts gradio_builder=_build_dashboard_tab, ) _base_lifespan = app.router.lifespan_context @asynccontextmanager async def _lifespan(app_instance): """Block startup until the embedding model is downloaded and initialized.""" preload_embedding_model() print( f"Embedding model ready: {EMBEDDING_MODEL_NAME} " f"(cache={EMBEDDING_CACHE_DIR})", flush=True, ) async with _base_lifespan(app_instance): yield app.router.lifespan_context = _lifespan def main(host: str = "0.0.0.0", port: int = 8000): """ Entry point for direct execution via uv run or python -m. This function enables running the server without Docker: uv run --project . server uv run --project . server --port 8001 python -m explainer_env.server.app Args: host: Host address to bind to (default: "0.0.0.0") port: Port number to listen on (default: 8000) """ import uvicorn uvicorn.run(app, host=host, port=port) if __name__ == "__main__": main()