Spaces:
Runtime error
Runtime error
File size: 2,997 Bytes
8d27c3e 9e89374 bf11096 9e89374 8d27c3e 9e89374 8d27c3e bf11096 8d27c3e | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 | # 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 Data Wrangler Environment.
This module creates an HTTP server that exposes the DataWranglerEnvironment
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 fastapi.responses import RedirectResponse
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 DataWranglerAction, DataWranglerObservation
from .data_wrangler_environment import DataWranglerEnvironment
except (ImportError, ValueError, ModuleNotFoundError):
import sys
import os
sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), '..')))
from models import DataWranglerAction, DataWranglerObservation
from server.data_wrangler_environment import DataWranglerEnvironment
# Create the app with web interface and README integration
app = create_app(
DataWranglerEnvironment,
DataWranglerAction,
DataWranglerObservation,
env_name="data_wrangler",
max_concurrent_envs=int(os.getenv("MAX_CONCURRENT_ENVS", "4")),
)
@app.get("/", include_in_schema=False)
def root_redirect():
return RedirectResponse(url="/docs")
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 data_wrangler.server.app
Args:
host: Host address to bind to (default: "0.0.0.0")
port: Port number to listen on (default: 8000)
For production deployments, consider using uvicorn directly with
multiple workers:
uvicorn data_wrangler.server.app:app --workers 4
"""
import uvicorn
uvicorn.run(app, host=host, port=port)
if __name__ == '__main__':
# ensures openenv validate passes main() check
import argparse
parser = argparse.ArgumentParser()
parser.add_argument("--port", type=int, default=8000)
args = parser.parse_args()
if not args.port or args.port == 8000:
main()
else:
main(port=args.port)
|