from fastapi import FastAPI, HTTPException
from pydantic import BaseModel
from ocr_pdf_mcp.pdf_utils import get_pdf_info
from ocr_pdf_mcp.ocr_worker import process_ocr_pdf
from ocr_pdf_mcp.pdf_text_extractor import extract_text_from_pdf
from ocr_pdf_mcp.config import Config
import time
import os
import logging
# Setup logging
logging.basicConfig(level=logging.INFO)
logger = logging.getLogger(__name__)
app = FastAPI(title="OCR PDF MCP", description="OCR PDF Processing API")
class PDFRequest(BaseModel):
path: str
@app.get("/")
def root():
"""Root endpoint"""
return {"message": "OCR PDF MCP API", "status": "running"}
@app.get("/health")
def health_check():
"""Health check endpoint"""
return {
"status": "healthy",
"tesseract_path": Config.TESSERACT_PATH,
"tesseract_available": os.path.exists(Config.TESSERACT_PATH)
}
@app.post("/analyze_pdf")
def analyze_pdf(request: PDFRequest):
"""Analyze PDF file with OCR or digital text extraction"""
start = time.time()
try:
# Check if file exists
if not os.path.exists(request.path):
raise HTTPException(status_code=404, detail=f"File not found: {request.path}")
logger.info(f"Processing file: {request.path}")
# Get PDF info
info = get_pdf_info(request.path)
logger.info(f"PDF info: {info}")
# Process based on type
if info["is_scanned"]:
logger.info("Processing with OCR...")
pages = process_ocr_pdf(request.path)
else:
logger.info("Extracting digital text...")
pages = extract_text_from_pdf(request.path)
processing_time = round(time.time() - start, 2)
logger.info(f"Processing completed in {processing_time}s")
return {
"file": os.path.basename(request.path),
"total_pages": info["total_pages"],
"mode": "ocr" if info["is_scanned"] else "digital",
"pages": pages,
"processing_time": processing_time
}
except Exception as e:
logger.error(f"Error processing {request.path}: {str(e)}")
raise HTTPException(status_code=500, detail=str(e))
if __name__ == "__main__":
import uvicorn
uvicorn.run("ocr_pdf_mcp.main:app", host="0.0.0.0", port=Config.PORT, reload=True)
