Coder19/interview_system

1from fastapi import APIRouter, WebSocket, HTTPException2from interview.app.services.interview import InterviewService3from typing import Dict, Any4from pydantic import BaseModel5import json6 7class AnswerRequest(BaseModel):8    answer: str9 10interview_router = APIRouter()11interview_service = InterviewService()  # No API key needed here anymore as it's handled in OpenAI service12 13# WebSocket endpoint for real-time voice communication14@interview_router.websocket("/ws")15async def websocket_endpoint(websocket: WebSocket):16    await websocket.accept()17    18    try:19        await interview_service.start_interview(websocket)20        21        # Main interview loop22        while True:23            try:24                message = await websocket.receive_text()25                data = json.loads(message)26                27                if data['type'] == 'user_response':28                    await interview_service.handle_user_response(data['text'])29                elif data['type'] == 'video_frame':30                    await interview_service.handle_video_frame(data['data'])31                elif data['type'] == 'audio_data':32                    await interview_service.handle_audio_data(data['data'])33                elif data['type'] == 'typing_data':34                    await interview_service.handle_typing_data(data['data'])35            except RuntimeError as e:36                # WebSocket was closed by the client37                print(f"WebSocket closed by client: {e}")38                break39            except Exception as e:40                print(f"Error processing message: {e}")41                try:42                    await websocket.send_json({43                        "type": "error",44                        "text": "An error occurred processing your message. Please try again."45                    })46                except:47                    break  # Exit if we can't communicate with the client48                49    except Exception as e:50        print(f"Error in websocket endpoint: {e}")51    finally:52        await interview_service.cleanup()53 54# REST API endpoints for non-WebSocket interactions55@interview_router.post("/start")56async def start_interview() -> Dict[str, Any]:57    """Start a new interview session"""58    try:59        return {"status": "success", "message": "Interview session started"}60    except Exception as e:61        raise HTTPException(status_code=500, detail=str(e))62 63@interview_router.post("/answer")64async def submit_answer(request: AnswerRequest) -> Dict[str, Any]:65    """Submit an answer to the current question"""66    try:67        response = await interview_service.handle_user_response(request.answer)68        return {69            "status": "success",70            "message": "Answer processed successfully",71            "next_question": response72        }73    except Exception as e:74        raise HTTPException(status_code=500, detail=str(e))75 76@interview_router.get("/status")77async def get_interview_status() -> Dict[str, Any]:78    """Get the current status of the interview"""79    try:80        # You might want to add interview status tracking in InterviewService81        return {82            "status": "success",83            "is_active": True,  # This should come from interview service84            "current_phase": "technical_questions"  # This should come from interview service85        }86    except Exception as e:87        raise HTTPException(status_code=500, detail=str(e))88 89@interview_router.post("/end")90async def end_interview() -> Dict[str, Any]:91    """End the current interview session"""92    try:93        await interview_service.cleanup()94        return {95            "status": "success",96            "message": "Interview session ended successfully"97        }98    except Exception as e:99        raise HTTPException(status_code=500, detail=str(e))100 101@interview_router.get("/feedback")102async def get_interview_feedback() -> Dict[str, Any]:103    """Get feedback for the completed interview"""104    try:105        feedback = await interview_service.analyze_interview()106        return {107            "status": "success",108            "feedback": feedback109        }110    except Exception as e:111        raise HTTPException(status_code=500, detail=str(e))