Update app.py

app.py

@@ -1,12 +1,9 @@
-from fastapi import FastAPI, HTTPException
+from fastapi import FastAPI, HTTPException, UploadFile, File, Form
 from fastapi.middleware.cors import CORSMiddleware
 from pydantic import BaseModel
 import base64
-import io
-from PIL import Image
 import uvicorn
 import os
-import json
 from dotenv import load_dotenv
 from typing import List
 
@@ -18,6 +15,7 @@ app = FastAPI(
     title="Receipt Scanner API",
     root_path="/" if not HF_SPACE_URL else HF_SPACE_URL
 )
+# app = FastAPI()
 # Configure CORS to allow requests from your React app
 app.add_middleware(
     CORSMiddleware,
@@ -27,10 +25,6 @@ app.add_middleware(
     allow_headers=["*"],
 )
 
-# Data model for the request
-class ImageRequest(BaseModel):
-    images: List[str]  # Changed from single image to list of images
-
 # Data model for the response
 class ReceiptItem(BaseModel):
     name: str
@@ -43,6 +37,9 @@ class ReceiptResponse(BaseModel):
     total: float
     items: list[ReceiptItem]
 
+class ImageData(BaseModel):
+    images: List[str]
+
 # Initialize the receipt agent
 receipt_scanner = receipt_agent()
 
@@ -51,9 +48,6 @@ def format_receipt_data(agent_response):
     """
     Format the receipt data from the LangGraph agent to match our API response format
     """
-    # Create directory for storing receipt data if it doesn't exist
-    # os.makedirs('new_receipt_data', exist_ok=True)
-    
     # Ensure we have values for all our fields
     store = agent_response.get('loc_name', '')
     date = agent_response.get('date', '')
@@ -104,24 +98,36 @@ def scan_receipt(images):
         }
 
 @app.post("/api/scan")
-async def process_receipt(request: ImageRequest):
+async def process_receipt(
+    images: list[UploadFile] = File(...)
+
+):
     try:
-        # Process each image in the list
-        processed_images = []
-        for image_data in request.images:
-            if "base64," in image_data:
-                image_data = image_data.split(",")[1]
-            processed_images.append(image_data)
-        
-        # Process all images with the LangGraph receipt scanner
-        result = scan_receipt(processed_images)
+        base64_images = []
+        for i in images:
+            print(f"Processing file: {i.filename}")
+            # Read the file content
+            contents = await i.read()
+            print(f"File size: {len(contents)} bytes")
+            
+            # Convert to base64 without trying to decode as UTF-8
+            base64_image = base64.b64encode(contents).decode('utf-8')
+            base64_images.append(base64_image)
+
+        print("Sending image to receipt scanner...")
+        # Process image with the LangGraph receipt scanner
+        result = scan_receipt(base64_images)
+        print("Receipt scanning completed successfully")
         
         # Return the result
         return result
     
     except Exception as e:
         print(f"API error: {str(e)}")
-        raise HTTPException(status_code=500, detail=f"Error processing images: {str(e)}")
+        import traceback
+        print(f"Traceback: {traceback.format_exc()}")
+        raise HTTPException(status_code=500, detail=f"Error processing image: {str(e)}")
+
 @app.get("/")
 async def root():
     return {
@@ -131,6 +137,8 @@ async def root():
             "health": "/health"
         }
     }
+
+
 # Health check endpoint
 @app.get("/health")
 async def health_check():
@@ -142,9 +150,6 @@ if not os.getenv('google_api_key'):
     print("WARNING: google_api_key not found in environment variables")
     print("Please ensure you have set up your .env file with the Google API key")
 
-# Create directory for storing receipt data if it doesn't exist
-# os.makedirs('new_receipt_data', exist_ok=True)
-
 if __name__ == "__main__":
     # Get port from environment variable or default to 8000
     port = int(os.environ.get("PORT", 8000))