endpoints.py

from fastapi import APIRouter, HTTPException, UploadFile, File, Form
from pydantic import BaseModel
from typing import List, Literal, Optional
import os
import tempfile
from pathlib import Path

router = APIRouter()

from rag import get_smart_rag_response
from ocr_service import get_ocr_service
class Message(BaseModel):
    role: Literal["user", "assistant"]
    content: str

class QueryRequest(BaseModel):
    query: str
    conversation_history: List[Message] = []

class QueryResponse(BaseModel):
    query: str
    response: str
    source: str

# OCR-specific models
class OCRResponse(BaseModel):
    success: bool
    extracted_text: Optional[str] = None
    markdown_text: Optional[str] = None
    error: Optional[str] = None
    image_path: Optional[str] = None
    model_used: Optional[str] = None

class OCRQueryRequest(BaseModel):
    query: str
    conversation_history: List[Message] = []
    extracted_text: str

@router.post("/query/")
async def query_rag_system(request: QueryRequest):
    try:
        # Convert Pydantic models to dicts for processing
        history = [msg.dict() for msg in request.conversation_history]
        response, source = await get_smart_rag_response(request.query, history)
        return QueryResponse(
            query=request.query,
            response=response,
            source=source
        )
    except Exception as e:
        raise HTTPException(status_code=500, detail=str(e))

# OCR Endpoints
@router.post("/ocr/extract-text/", response_model=OCRResponse)
async def extract_text_from_image(
    file: UploadFile = File(...),
    prompt: Optional[str] = Form(None)
):
    """
    Extract text from uploaded image using DeepSeek OCR
    """
    try:
        # Validate file type
        if not file.content_type.startswith('image/'):
            raise HTTPException(status_code=400, detail="File must be an image")
        
        # Create temporary file
        with tempfile.NamedTemporaryFile(delete=False, suffix=Path(file.filename).suffix) as temp_file:
            content = await file.read()
            temp_file.write(content)
            temp_file_path = temp_file.name
        
        try:
            # Get OCR service and extract text
            ocr_service = get_ocr_service()
            result = ocr_service.extract_text_from_image(temp_file_path, prompt)
            
            return OCRResponse(**result)
            
        finally:
            # Clean up temporary file
            if os.path.exists(temp_file_path):
                os.unlink(temp_file_path)
                
    except Exception as e:
        raise HTTPException(status_code=500, detail=str(e))

@router.post("/ocr/extract-with-grounding/", response_model=OCRResponse)
async def extract_text_with_grounding(
    file: UploadFile = File(...),
    target_text: Optional[str] = Form(None)
):
    """
    Extract text with grounding capabilities (locate specific text)
    """
    try:
        if not file.content_type.startswith('image/'):
            raise HTTPException(status_code=400, detail="File must be an image")
        
        with tempfile.NamedTemporaryFile(delete=False, suffix=Path(file.filename).suffix) as temp_file:
            content = await file.read()
            temp_file.write(content)
            temp_file_path = temp_file.name
        
        try:
            ocr_service = get_ocr_service()
            result = ocr_service.extract_text_with_grounding(temp_file_path, target_text)
            
            return OCRResponse(**result)
            
        finally:
            if os.path.exists(temp_file_path):
                os.unlink(temp_file_path)
                
    except Exception as e:
        raise HTTPException(status_code=500, detail=str(e))

@router.post("/ocr/convert-to-markdown/", response_model=OCRResponse)
async def convert_image_to_markdown(file: UploadFile = File(...)):
    """
    Convert document image to markdown format
    """
    try:
        if not file.content_type.startswith('image/'):
            raise HTTPException(status_code=400, detail="File must be an image")
        
        with tempfile.NamedTemporaryFile(delete=False, suffix=Path(file.filename).suffix) as temp_file:
            content = await file.read()
            temp_file.write(content)
            temp_file_path = temp_file.name
        
        try:
            ocr_service = get_ocr_service()
            result = ocr_service.convert_to_markdown(temp_file_path)
            
            return OCRResponse(**result)
            
        finally:
            if os.path.exists(temp_file_path):
                os.unlink(temp_file_path)
                
    except Exception as e:
        raise HTTPException(status_code=500, detail=str(e))

@router.post("/ocr/query/", response_model=QueryResponse)
async def query_with_ocr_text(request: OCRQueryRequest):
    """
    Query the RAG system with OCR extracted text
    """
    try:
        # Combine the original query with extracted text
        combined_query = f"{request.query}\n\nExtracted text from image:\n{request.extracted_text}"
        
        # Convert conversation history
        history = [msg.dict() for msg in request.conversation_history]
        
        # Get RAG response
        response, source = await get_smart_rag_response(combined_query, history)
        
        return QueryResponse(
            query=request.query,
            response=response,
            source=f"{source} (OCR-enhanced)"
        )
        
    except Exception as e:
        raise HTTPException(status_code=500, detail=str(e))