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from fastapi import APIRouter, Depends, status, Query
from sqlalchemy.orm import Session
from typing import List, Optional
import uuid
from app.database import get_db
from app.dependencies import get_current_user
from app.models.user import User
from app.models.interview import Interview, InterviewResult
from app.schemas.interview import (
InterviewCreate,
InterviewResponse,
InterviewListItem,
InterviewResultResponse
)
from app.schemas.common import ResponseBase, PaginatedResponse
from app.services.interview_service import InterviewService
from app.core.exceptions import NotFoundException, BadRequestException
router = APIRouter()
@router.post("/create", response_model=InterviewResponse, status_code=status.HTTP_201_CREATED)
async def create_interview(
interview_data: InterviewCreate,
current_user: User = Depends(get_current_user),
db: Session = Depends(get_db)
):
"""
Create a new interview with AI-generated questions.
Steps:
1. Validate input (interview type, technologies, difficulty)
2. Use AI (Gemini) to generate relevant questions
3. Save interview to database with status='draft'
4. Return interview with questions
The interview can then be started via WebSocket endpoint.
"""
interview = InterviewService.create_interview(db, current_user.id, interview_data)
return interview
@router.get("/list", response_model=List[InterviewListItem])
async def list_interviews(
status: Optional[str] = Query(None, regex="^(draft|in_progress|completed|abandoned)$"),
current_user: User = Depends(get_current_user),
db: Session = Depends(get_db)
):
"""
Get all interviews for the current user.
Optional filter by status:
- draft: Interview created but not started
- in_progress: Interview currently active
- completed: Interview finished
- abandoned: Interview started but not completed
"""
interviews = InterviewService.get_user_interviews(db, current_user.id, status)
return interviews
@router.get("/{interview_id}", response_model=InterviewResponse)
async def get_interview(
interview_id: uuid.UUID,
current_user: User = Depends(get_current_user),
db: Session = Depends(get_db)
):
"""
Get details of a specific interview including questions.
Use this to preview questions before starting the interview.
"""
interview = InterviewService.get_interview(db, interview_id, current_user.id)
return interview
@router.delete("/{interview_id}", response_model=ResponseBase)
async def delete_interview(
interview_id: uuid.UUID,
current_user: User = Depends(get_current_user),
db: Session = Depends(get_db)
):
"""
Delete an interview.
Can only delete interviews with status='draft'.
Completed interviews cannot be deleted to maintain records.
"""
InterviewService.delete_interview(db, interview_id, current_user.id)
return ResponseBase(
success=True,
message="Interview deleted successfully"
)
@router.post("/{interview_id}/regenerate-questions", response_model=InterviewResponse)
async def regenerate_questions(
interview_id: uuid.UUID,
current_user: User = Depends(get_current_user),
db: Session = Depends(get_db)
):
"""
Regenerate questions for a draft interview.
Useful if the user is not satisfied with the generated questions.
Can only regenerate for interviews with status='draft'.
"""
interview = InterviewService.get_interview(db, interview_id, current_user.id)
if interview.status != "draft":
raise BadRequestException("Can only regenerate questions for draft interviews")
# Generate new questions
new_questions = InterviewService.generate_questions(
interview_type=interview.interview_type,
target_role=interview.target_role,
technologies=interview.technologies,
difficulty=interview.difficulty,
num_questions=interview.num_questions
)
# Update interview
interview.questions = new_questions
db.commit()
db.refresh(interview)
return interview
@router.get("/{interview_id}/result", response_model=InterviewResultResponse)
async def get_interview_result(
interview_id: uuid.UUID,
current_user: User = Depends(get_current_user),
db: Session = Depends(get_db)
):
"""
Get the result of a completed interview.
Includes:
- Overall score
- Summary and feedback
- Strengths and improvement areas
- Complete transcript
- AI remarks
"""
# Verify interview belongs to user
interview = InterviewService.get_interview(db, interview_id, current_user.id)
if interview.status != "completed":
raise BadRequestException("Interview is not completed yet")
# Get result
result = db.query(InterviewResult).filter(
InterviewResult.interview_id == interview_id
).first()
if not result:
raise NotFoundException("Interview result not found")
return result
@router.get("/{interview_id}/transcript", response_model=dict)
async def get_interview_transcript(
interview_id: uuid.UUID,
current_user: User = Depends(get_current_user),
db: Session = Depends(get_db)
):
"""
Get the full Q&A transcript of a completed interview.
Returns array of:
- Question number
- Question text
- Answer text
- Score
- Feedback
- Time taken
"""
interview = InterviewService.get_interview(db, interview_id, current_user.id)
if interview.status != "completed":
raise BadRequestException("Interview is not completed yet")
result = db.query(InterviewResult).filter(
InterviewResult.interview_id == interview_id
).first()
if not result:
raise NotFoundException("Interview result not found")
return {
"interview_id": str(interview_id),
"interview_type": interview.interview_type,
"target_role": interview.target_role,
"transcript": result.transcript
}
@router.get("/stats/summary", response_model=dict)
async def get_interview_stats(
current_user: User = Depends(get_current_user),
db: Session = Depends(get_db)
):
"""
Get user's overall interview statistics.
Includes:
- Total interviews
- Completed interviews
- Average score
- Improvement trend
"""
# Get all completed interviews
completed_interviews = db.query(Interview).filter(
Interview.user_id == current_user.id,
Interview.status == "completed"
).all()
if not completed_interviews:
return {
"total_interviews": 0,
"completed_interviews": 0,
"average_score": 0,
"highest_score": 0,
"lowest_score": 0,
"recent_scores": []
}
# Get results
interview_ids = [i.id for i in completed_interviews]
results = db.query(InterviewResult).filter(
InterviewResult.interview_id.in_(interview_ids)
).all()
scores = [r.overall_score for r in results]
# Get recent 5 scores for trend
recent_results = sorted(results, key=lambda x: x.created_at, reverse=True)[:5]
recent_scores = [
{
"score": r.overall_score,
"date": r.created_at.isoformat(),
"interview_type": next((i.interview_type for i in completed_interviews if i.id == r.interview_id), "unknown")
}
for r in recent_results
]
return {
"total_interviews": len(completed_interviews),
"completed_interviews": len(results),
"average_score": sum(scores) / len(scores) if scores else 0,
"highest_score": max(scores) if scores else 0,
"lowest_score": min(scores) if scores else 0,
"recent_scores": recent_scores
}
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