downloadable excel

app.py

@@ -1,5 +1,5 @@
 from fastapi import FastAPI, File, UploadFile, Response, HTTPException
-from fastapi.responses import JSONResponse, FileResponse
+from fastapi.responses import JSONResponse, FileResponse, StreamingResponse
 from fastapi.middleware.cors import CORSMiddleware
 from PIL import Image
 import io
@@ -210,8 +210,115 @@ class Prediction(BaseModel):
     detected_text: Optional[str]
     image_url: Optional[str]
     image_path: Optional[str]
-    
+
 
+@app.post("/generate-excel/")
+async def generate_excel(predictions: List[Prediction]):
+    print('Generate excel called')
+
+    # Create an Excel workbook
+    workbook = Workbook()
+    sheet = workbook.active
+    sheet.title = "Predictions"
+
+    # Add headers
+    headers = ["Category", "Confidence", "Predicted Brand", "Price", "Image URL", "Details", "Detected Text"]
+    sheet.append(headers)
+
+    # Add prediction rows (skipping for brevity)
+
+    # Set header style and alignment
+    for cell in sheet[1]:
+        cell.alignment = Alignment(horizontal="center", vertical="center", wrap_text=True)
+    sheet.row_dimensions[1].height = 30  # Adjust header row height
+
+    # Set column widths based on data type
+    column_widths = {
+        "A": 20,  # Category
+        "B": 15,  # Confidence
+        "C": 40,  # Predicted Brand
+        "D": 15,  # Price
+        "E": 50,  # Image URL
+        "F": 30,  # Details 
+        "G": 30   # Detected Text
+    }
+    for col, width in column_widths.items():
+        sheet.column_dimensions[col].width = width
+
+    # Add prediction rows
+    for idx, prediction in enumerate(predictions):
+        row_index = idx + 2  # Start from the second row
+
+        # Add data to the row
+        sheet.append([
+            prediction.category,
+            prediction.confidence,
+            prediction.predicted_brand,
+            prediction.price,
+            prediction.image_url,
+            prediction.details,
+            prediction.detected_text,
+            
+        ])
+
+        # Adjust row height for multiline text
+        sheet.row_dimensions[row_index].height = 180  # Default height for rows
+
+        # Wrap text in all cells of the row
+        for col_idx in range(1, 8):  # Columns A to G
+            cell = sheet.cell(row=row_index, column=col_idx)
+            cell.alignment = Alignment(wrap_text=True, vertical="top")
+
+        if prediction.image_url:
+            try:
+                response = requests.get(prediction.image_url)
+                img = ExcelImage(BytesIO(response.content))
+                img.width, img.height = 160, 160  # Resize image to fit into the cell
+                img_cell = f"G{row_index}"  # Image column
+                sheet.add_image(img, img_cell)
+            except requests.exceptions.RequestException as e:
+                print(f"Error downloading image: {e}")
+
+        # # Add image if the path exists
+        # if os.path.exists(prediction.image_path):
+        #     img = ExcelImage(prediction.image_path)
+        #     img.width, img.height = 160, 160  # Resize image to fit into the cell
+        #     img_cell = f"G{row_index}"  # Image column
+        #     sheet.add_image(img, img_cell)
+
+
+    # Save the Excel file to a temporary path
+    excel_file_path = "/predictions_with_images.xlsx"
+    workbook.save(excel_file_path)
+
+     # Upload the Excel file to File.io
+    with open(excel_file_path, 'rb') as file:
+        response = requests.post('https://file.io/', files={'file': file})
+        response_data = response.json()
+
+    # Check if upload was successful
+    if response.status_code == 200:
+        file_url = response_data['link']
+        print(file_url)
+        return JSONResponse(content={"download_link": file_url})
+    else:
+        return JSONResponse(status_code=500, content={"error": "File upload failed"})
+
+@app.get("/download-excel/")
+async def download_excel(url: str):
+    try:
+        # Download the file from File.io using the provided URL
+        response = requests.get(url)
+        response.raise_for_status()  # Check for request errors
+        
+        # Return the file as a streaming response
+        return StreamingResponse(BytesIO(response.content), media_type="application/vnd.openxmlformats-officedocument.spreadsheetml.sheet")
+    
+    except requests.exceptions.RequestException as e:
+        print(f"Error downloading the file: {e}")
+        return {"error": "File download failed"}
+    
+'''
 @app.post("/generate-excel/")
 async def generate_excel(predictions: List[Prediction]):
     print('Generate excel called')
@@ -363,7 +470,7 @@ async def generate_excel(predictions: List[Prediction]):
         filename="predictions_with_images.xlsx"
     )
 '''
-
+'''
 @app.post("/generate-excel/")
 async def generate_excel(predictions: list):
     print('Generate excel called')