Update main.py

main.py

@@ -1,58 +1,39 @@
-import logging
-from fastapi import FastAPI, UploadFile, File, HTTPException
+from fastapi import FastAPI, UploadFile, File, Form, HTTPException
 from fastapi.middleware.cors import CORSMiddleware
-from parser_logic import extract_text_from_stream, parse_resume_with_ai
+from parser_logic import extract_text_from_stream, analyze_resume
+import logging
 
-# Configure Logging
 logging.basicConfig(level=logging.INFO)
 logger = logging.getLogger(__name__)
 
-app = FastAPI(title="Resume Parser API", version="1.0.0")
+app = FastAPI()
 
-# CORS Middleware (Crucial for production when frontend/backend are on different ports/domains)
 app.add_middleware(
     CORSMiddleware,
-    allow_origins=["*"],  # In strict production, replace "*" with specific frontend domain
-    allow_credentials=True,
+    allow_origins=["*"],
     allow_methods=["POST"],
     allow_headers=["*"],
 )
 
-MAX_FILE_SIZE = 5 * 1024 * 1024  # 5 MB limit
-
-@app.post("/process-resume")
-async def process_resume(file: UploadFile = File(...)):
-    """
-    Endpoint to process PDF resumes.
-    Validates file type and size, then processes in-memory.
-    """
+@app.post("/analyze")
+async def process_resume(
+    file: UploadFile = File(...),
+    job_description: str = Form(None)  # Optional form field
+):
     if file.content_type != "application/pdf":
-        raise HTTPException(status_code=400, detail="Invalid file type. Only PDF is allowed.")
-
+        raise HTTPException(400, "Invalid file type. Only PDF allowed.")
+    
     try:
-        # Read file into memory (Async read)
-        file_content = await file.read()
-        
-        # Validation: Check file size
-        if len(file_content) > MAX_FILE_SIZE:
-            raise HTTPException(status_code=413, detail="File too large. Max size is 5MB.")
-
-        logger.info(f"Processing file: {file.filename} ({len(file_content)} bytes)")
-
-        # Extract text (CPU bound task, but fast enough for small PDFs to run synchronously here)
-        # For very heavy loads, this should be offloaded to a background task (Celery/RQ)
-        raw_text = extract_text_from_stream(file_content)
-        
-        if not raw_text.strip():
-            raise HTTPException(status_code=400, detail="Could not extract text. PDF might be image-based.")
-
-        # AI Processing
-        structured_result = parse_resume_with_ai(raw_text)
+        content = await file.read()
+        text = extract_text_from_stream(content)
         
-        return structured_result
+        if not text.strip():
+            raise HTTPException(400, "PDF text extraction failed.")
+            
+        # Pass both text and JD to the logic
+        result = analyze_resume(text, job_description)
+        return result
         
-    except HTTPException as he:
-        raise he
     except Exception as e:
-        logger.error(f"Unexpected Error: {e}")
-        raise HTTPException(status_code=500, detail="Internal Server Error")
+        logger.error(f"Server Error: {e}")
+        raise HTTPException(500, str(e))