Create app.py

app.py

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+import openpyxl
+from PIL import Image, ImageDraw, ImageFont
+import base64
+import requests
+import gradio as gr
+
+# OpenAI API Key
+api_key = "sk-formanas-HAa5ntPi5XvOa0B2QpwTT3BlbkFJz4fYVfwl8inxMenGKluJ"
+
+# Function to encode the image
+def encode_image(image_path):
+    with open(image_path, "rb") as image_file:
+        return base64.b64encode(image_file.read()).decode('utf-8')
+
+def take_screenshot_of_cells(file_path, sheet_name, start_cell, end_cell, query):
+    # Load the workbook and the specified sheet
+    workbook = openpyxl.load_workbook(file_path)
+    sheet = workbook[sheet_name]
+    
+    # Get the coordinates of the start and end cells
+    start_col, start_row = openpyxl.utils.cell.coordinate_to_tuple(start_cell)
+    end_col, end_row = openpyxl.utils.cell.coordinate_to_tuple(end_cell)
+    
+    # Calculate the number of rows and columns
+    num_cols = end_col - start_col + 1
+    num_rows = end_row - start_row + 1
+    
+    # Set the width and height of each cell (you can adjust these values as needed)
+    cell_width = 100
+    cell_height = 30
+    
+    # Create a blank image with the calculated size
+    image_width = cell_width * num_cols
+    image_height = cell_height * num_rows
+    image = Image.new('RGB', (image_width, image_height), 'white')
+    draw = ImageDraw.Draw(image)
+    
+    # Load a font (you may need to specify the path to a font file on your system)
+    font = ImageFont.load_default()
+    
+    # Draw the cells and their content
+    for row in range(num_rows):
+        for col in range(num_cols):
+            cell_value = sheet.cell(row=start_row + row, column=start_col + col).value
+            x0 = col * cell_width
+            y0 = row * cell_height
+            x1 = x0 + cell_width
+            y1 = y0 + cell_height
+            
+            # Draw the cell border
+            draw.rectangle([x0, y0, x1, y1], outline='black')
+            
+            # Draw the cell value
+            if cell_value is not None:
+                draw.text((x0 + 5, y0 + 5), str(cell_value), fill='black', font=font)
+    
+    # Save the image
+    output_image_path = 'screenshot.png'
+    image.save(output_image_path)
+
+    # Encode the image to base64
+    base64_image = encode_image(output_image_path)
+    
+    # Send the image to the OpenAI API
+    headers = {
+        "Content-Type": "application/json",
+        "Authorization": f"Bearer {api_key}"
+    }
+
+    payload = {
+        "model": "gpt-4o",  # Assuming the model name is 'gpt-4-vision'
+        "messages": [
+            {
+                "role": "user",
+                "content": [
+                    {
+                        "type": "text",
+                        "text": query
+                    },
+                    {
+                        "type": "image_url",
+                        "image_url": {
+                            "url": f"data:image/jpeg;base64,{base64_image}"
+                        }
+                    }
+                ]
+            }
+        ],
+        "max_tokens": 300
+    }
+
+    response = requests.post("https://api.openai.com/v1/chat/completions", headers=headers, json=payload)
+    response=response.json()
+    return response['choices'][0]['message']['content']
+
+def gradio_interface(excel_file, sheet_name, start_cell, end_cell, query):
+    return take_screenshot_of_cells(excel_file.name, sheet_name, start_cell, end_cell, query)
+
+# Create Gradio Interface
+inputs = [
+    gr.File(label="Upload Excel File"),
+    gr.Textbox(label="Sheet Name"),
+    gr.Textbox(label="Start Cell"),
+    gr.Textbox(label="End Cell"),
+    gr.Textbox(label="Query")
+]
+
+outputs = gr.Textbox(label="Output")
+
+gr.Interface(fn=gradio_interface, inputs=inputs, outputs=outputs, title="Excel Screenshot Analyzer").launch()