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# 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()