backend/routes/interview_api.py

import os
import uuid
import json
from flask import Blueprint, request, jsonify, url_for, current_app
from flask_login import login_required, current_user
from backend.models.database import db, Job, Application
from backend.services.interview_engine import (
    generate_first_question,
    edge_tts_to_file_sync,
    whisper_stt,
    evaluate_answer
)

interview_api = Blueprint("interview_api", __name__)

@interview_api.route("/start_interview", methods=["POST"])
@login_required
def start_interview():
    data = request.get_json()
    job_id = data.get("job_id")
    
    job = Job.query.get_or_404(job_id)
    application = Application.query.filter_by(
        user_id=current_user.id, 
        job_id=job_id
    ).first()
    
    if not application or not application.extracted_features:
        return jsonify({"error": "No application/profile data found."}), 400
    
    try:
        profile = json.loads(application.extracted_features)
    except:
        return jsonify({"error": "Invalid profile JSON"}), 500
    
    question = generate_first_question(profile, job)
    
    # Determine the static folder from the current app context.  Flask serves
    # files from ``current_app.static_folder`` and uses ``static_url_path``
    # when generating URLs.  If audio generation fails (for example because
    # network access is unavailable), we simply omit the audio file and allow
    # the frontend to fall back to text‑only mode.
    audio_dir = os.path.join(current_app.static_folder, "audio")
    os.makedirs(audio_dir, exist_ok=True)

    audio_filename = f"q_{uuid.uuid4().hex}.wav"
    audio_path = os.path.join(audio_dir, audio_filename)

    # Generate audio synchronously.  The function returns None on error.
    audio_out = edge_tts_to_file_sync(question, audio_path)

    response = {"question": question}
    if audio_out:
        # Use url_for to build the URL relative to the configured static folder.
        response["audio_url"] = url_for("static", filename=f"audio/{audio_filename}")
    return jsonify(response)

@interview_api.route("/transcribe_audio", methods=["POST"])
@login_required
def transcribe_audio():
    audio_file = request.files.get("audio")
    if not audio_file:
        return jsonify({"error": "No audio file received."}), 400
    
    # Create a temporary directory inside Flask's instance path.  Using the
    # instance path ensures that the folder is writable in environments like
    # Hugging Face Spaces, where the working directory may be read‑only.  The
    # instance path is configured in ``app.py`` to point at ``/tmp/flask_instance``.
    temp_dir = os.path.join(current_app.instance_path, "interview_temp")
    os.makedirs(temp_dir, exist_ok=True)

    filename = f"user_audio_{uuid.uuid4().hex}.wav"
    path = os.path.join(temp_dir, filename)
    audio_file.save(path)
    
    transcript = whisper_stt(path)
    
    # Clean up
    try:
        os.remove(path)
    except:
        pass
    
    return jsonify({"transcript": transcript})

@interview_api.route("/process_answer", methods=["POST"])
@login_required
def process_answer():
    data = request.get_json()
    answer = data.get("answer", "")
    question_idx = data.get("questionIndex", 0)
    
    # Generate next question (simplified for now).  In a full implementation this
    # would call a model such as groq_llm to generate a follow‑up question based
    # on the candidate's answer.
    next_question = f"Follow‑up question {question_idx + 2}: Can you elaborate on your experience with relevant technologies?"

    # Prepare audio output directory inside the app's static folder
    audio_dir = os.path.join(current_app.static_folder, "audio")
    os.makedirs(audio_dir, exist_ok=True)

    audio_filename = f"q_{uuid.uuid4().hex}.wav"
    audio_path = os.path.join(audio_dir, audio_filename)

    # Attempt to generate speech for the next question.  If audio generation
    # fails, ``audio_out`` will be None and we simply omit ``audioUrl`` in
    # the JSON response.
    audio_out = edge_tts_to_file_sync(next_question, audio_path)

    response = {
        "success": True,
        "nextQuestion": next_question,
        "evaluation": {
            "score": "medium",
            "feedback": "Good answer, but be more specific."
        },
        "isComplete": question_idx >= 2,
        "summary": []
    }
    if audio_out:
        response["audioUrl"] = url_for("static", filename=f"audio/{audio_filename}")
    return jsonify(response)