""" FastAPI application for the Code Review Environment. Endpoints: POST /reset — start new episode POST /step — take an action GET /state — get episode state GET /health — health check GET /tasks — list all tasks + action schema POST /grader — grade a set of findings (stateless) POST /baseline — run keyword-heuristic baseline on all tasks WS /ws — persistent WebSocket session GET /docs — Swagger UI (auto-generated) """ from __future__ import annotations import sys import os sys.path.insert(0, os.path.dirname(os.path.dirname(os.path.abspath(__file__)))) import json import asyncio import dataclasses from typing import Optional, List, Dict, Any from fastapi import FastAPI, WebSocket, WebSocketDisconnect, HTTPException from fastapi.middleware.cors import CORSMiddleware from pydantic import BaseModel from models import ReviewAction, Issue from server.environment import CodeReviewEnvironment from server.graders import grade_episode, run_keyword_baseline from tasks.data import ALL_TASKS, TASK_IDS def _serialize(obj) -> dict: if dataclasses.is_dataclass(obj) and not isinstance(obj, type): d = dataclasses.asdict(obj) # asdict handles nested dataclasses and lists recursively return d if isinstance(obj, dict): return obj raise TypeError(f"Cannot serialize {type(obj)}") _env_instance = CodeReviewEnvironment() def _make_app() -> FastAPI: try: from openenv.core.env_server import create_fastapi_app base = create_fastapi_app(CodeReviewEnvironment) return base except Exception: pass _app = FastAPI( title="Code Review Environment", description=( "An OpenEnv environment for training AI agents to perform " "code review and security audits." ), version="1.0.0", ) _app.add_middleware( CORSMiddleware, allow_origins=["*"], allow_methods=["*"], allow_headers=["*"], ) @_app.get("/health") async def health(): return {"status": "healthy"} @_app.post("/reset") async def reset(body: dict = None): body = body or {} task_id = body.get("task_id") seed = body.get("seed") episode_id = body.get("episode_id") obs = _env_instance.reset(task_id=task_id, seed=seed, episode_id=episode_id) return _serialize(obs) @_app.post("/step") async def step(body: dict): action = ReviewAction.from_dict(body) obs = _env_instance.step(action) return _serialize(obs) @_app.get("/state") async def state(): return _serialize(_env_instance.state) @_app.websocket("/ws") async def websocket_endpoint(websocket: WebSocket): await websocket.accept() ws_env = CodeReviewEnvironment() try: while True: raw = await websocket.receive_text() msg = json.loads(raw) msg_type = msg.get("type", "") if msg_type == "reset": data = msg.get("data", {}) obs = ws_env.reset( task_id=data.get("task_id"), seed=data.get("seed"), episode_id=data.get("episode_id"), ) await websocket.send_text(json.dumps({ "type": "observation", "data": _serialize(obs), })) elif msg_type == "step": action = ReviewAction.from_dict(msg.get("data", {})) obs = ws_env.step(action) await websocket.send_text(json.dumps({ "type": "observation", "data": _serialize(obs), })) elif msg_type == "state": await websocket.send_text(json.dumps({ "type": "state", "data": _serialize(ws_env.state), })) elif msg_type == "close": break else: await websocket.send_text(json.dumps({ "type": "error", "data": f"Unknown message type: {msg_type}", })) except WebSocketDisconnect: pass except Exception as e: try: await websocket.send_text(json.dumps({"type": "error", "data": str(e)})) except Exception: pass return _app app = _make_app() @app.get("/tasks") async def list_tasks(): tasks_list = [] for task in ALL_TASKS.values(): tasks_list.append({ "task_id": task["task_id"], "difficulty": task["difficulty"], "description": task["description"], "language": task.get("language", "python"), "max_steps": task["max_steps"], "num_issues": len(task["ground_truth_issues"]), "files": list(task["code_files"].keys()), }) action_schema = { "type": "object", "description": "ReviewAction — one action per /step call", "required": ["action_type"], "properties": { "action_type": { "type": "string", "enum": ["flag_issue", "clear_flag", "request_hint", "submit_review"], "description": ( "flag_issue: mark a line as problematic. " "clear_flag: remove a previous flag. " "request_hint: get a hint (-0.01 reward). " "submit_review: end episode and receive final grade." ), }, "line_number": { "type": "integer", "description": "Line number of the issue (required for flag_issue / clear_flag)", }, "filename": { "type": "string", "description": "File where the issue is (required for flag_issue / clear_flag)", }, "issue_type": { "type": "string", "enum": ["bug", "security", "performance", "logic"], "description": "Category of issue (required for flag_issue)", }, "severity": { "type": "string", "enum": ["low", "medium", "high", "critical"], "description": "Severity level (required for flag_issue)", }, "description": { "type": "string", "description": "Human-readable description of the issue", }, "fix_suggestion": { "type": "string", "description": "Optional suggested fix", }, }, "examples": [ { "action_type": "flag_issue", "line_number": 6, "filename": "utils.py", "issue_type": "bug", "severity": "high", "description": "Off-by-one error in range()", "fix_suggestion": "Change range(len(numbers) + 1) to range(len(numbers))", }, {"action_type": "submit_review"}, ], } return { "tasks": tasks_list, "action_schema": action_schema, "total_tasks": len(tasks_list), } class GraderRequest(BaseModel): task_id: str flagged_issues: List[Dict[str, Any]] @app.post("/grader") async def run_grader(request: GraderRequest): task = ALL_TASKS.get(request.task_id) if not task: raise HTTPException( status_code=404, detail=f"Unknown task_id '{request.task_id}'. Valid: {TASK_IDS}", ) flagged = [Issue.from_dict(i) for i in request.flagged_issues] ground_truth = [Issue.from_dict(gt) for gt in task["ground_truth_issues"]] score = grade_episode(flagged, ground_truth) tp = sum( 1 for f in flagged if any( True for gt in ground_truth if abs(f.line_number - gt.line_number) <= 2 and f.filename == gt.filename ) ) return { "task_id": request.task_id, "difficulty": task["difficulty"], "score": score, "max_score": 1.0, "details": { "total_flagged": len(flagged), "true_positives": tp, "false_positives": len(flagged) - tp, "total_ground_truth": len(ground_truth), }, } @app.post("/baseline") async def run_baseline(): results = {} for task_id, task in ALL_TASKS.items(): findings = run_keyword_baseline(task) ground_truth = [Issue.from_dict(gt) for gt in task["ground_truth_issues"]] score = grade_episode(findings, ground_truth) results[task_id] = { "difficulty": task["difficulty"], "score": score, "findings_count": len(findings), "ground_truth_count": len(ground_truth), } overall = sum(r["score"] for r in results.values()) / len(results) return { "baseline_scores": results, "overall_average": round(overall, 4), "method": "keyword_heuristic", "note": ( "Run 'python baseline.py' with OPENAI_API_KEY for the LLM-based baseline. " "This endpoint uses a deterministic regex heuristic." ), } def main(): import uvicorn port = int(os.environ.get("PORT", 7860)) uvicorn.run("server.app:app", host="0.0.0.0", port=port) if __name__ == "__main__": main()