# 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 Kernel Env Environment.

This module creates an HTTP server that exposes the KernelEnvironment
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

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 KernelAction, KernelObservation
    from .kernel_env_environment import KernelEnvironment
except ImportError:
    from models import KernelAction, KernelObservation
    from server.kernel_env_environment import KernelEnvironment


class _QuietClientDisconnect:
    """openenv's /ws handler calls websocket.close() after the client already left; uvicorn then logs a
    full 'Exception in ASGI application' traceback per episode. Harmless, so drop it for websockets."""

    def __init__(self, app):
        self.app = app

    async def __call__(self, scope, receive, send):
        from starlette.websockets import WebSocketDisconnect

        try:
            await self.app(scope, receive, send)
        except WebSocketDisconnect:
            if scope["type"] != "websocket":
                raise


# Create the app with web interface and README integration
app = create_app(
    KernelEnvironment,
    KernelAction,
    KernelObservation,
    env_name="kernel_env",
    # sessions mostly wait on the LLM; GPU evals are serialized by the shared Evaluator pool
    max_concurrent_envs=int(os.environ.get("KERNEL_ENV_MAX_SESSIONS", "64")),
)
app.add_middleware(_QuietClientDisconnect)


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 kernel_env.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 kernel_env.server.app:app --workers 4
    """
    import uvicorn

    uvicorn.run(app, host=host, port=port)


if __name__ == "__main__":
    import argparse

    parser = argparse.ArgumentParser()
    parser.add_argument("--port", type=int, default=8000)
    args = parser.parse_args()
    main(port=args.port)