Update main.py

main.py

@@ -1,31 +1,55 @@
-from fastapi import FastAPI, File, UploadFile
-import easyocr
-import io
-from PIL import Image
-import numpy as np
-from business_card import llm_calling
-
-app = FastAPI()
-
-# Initialize EasyOCR reader
-reader = easyocr.Reader(['en', 'th'], gpu=False, model_storage_directory="./.EasyOCR")
-
-@app.post("/extract")
-async def extract_business_card(file: UploadFile = File(...)):
-    try:
-        # Read and decode image
-        image_data = await file.read()
-        image = Image.open(io.BytesIO(image_data))
-        image_np = np.array(image)
-
-        # OCR
-        ocr_result = reader.readtext(image_np, detail=0)
-        full_text = " ".join(ocr_result)
-
-        # Gemini LLM Extraction
-        extracted_data = llm_calling(full_text)
-
-        return {"status": "success", "data": extracted_data}
-    
-    except Exception as e:
-        return {"status": "error", "message": str(e)}
+import os
+from fastapi import FastAPI, File, UploadFile, HTTPException
+import easyocr
+import io
+from PIL import Image
+import numpy as np
+from business_card import llm_calling
+from pathlib import Path
+
+app = FastAPI(title="Business Card OCR Processor")
+
+# Create a writable directory path
+model_dir = os.path.join(os.getcwd(), "model_storage")
+os.makedirs(model_dir, exist_ok=True)
+
+# Initialize EasyOCR reader (with error handling)
+try:
+    reader = easyocr.Reader(
+        ['en', 'th'], 
+        gpu=False, 
+        model_storage_directory=model_dir,
+        download_enabled=True
+    )
+except Exception as e:
+    raise RuntimeError(f"Failed to initialize EasyOCR: {str(e)}")
+
+@app.post("/extract")
+async def extract_business_card(file: UploadFile = File(...)):
+    try:
+        # Validate file type
+        if not file.content_type.startswith('image/'):
+            raise HTTPException(status_code=400, detail="File must be an image")
+
+        # Read and decode image
+        image_data = await file.read()
+        image = Image.open(io.BytesIO(image_data))
+        image_np = np.array(image)
+
+        # OCR processing
+        ocr_result = reader.readtext(image_np, detail=0)
+        full_text = " ".join(ocr_result)
+
+        # Gemini LLM Extraction
+        extracted_data = llm_calling(full_text)
+
+        return {"status": "success", "data": extracted_data}
+    
+    except HTTPException:
+        raise
+    except Exception as e:
+        raise HTTPException(status_code=500, detail=str(e))
+
+@app.get("/health")
+async def health_check():
+    return {"status": "healthy"}