Create app.py

app.py

@@ -0,0 +1,82 @@
+# Import the necessary libraries
+import gradio as gr
+import openai
+import base64
+from PIL import Image
+import io
+import requests
+import os
+
+# Consider using environment variables or a configuration file for API keys.
+# WARNING: Do not hardcode API keys in your code, especially if sharing or using version control.
+openai.api_key = os.getenv('OPENAI_API_KEY')
+if openai.api_key is None:
+    raise ValueError("Please set the OPENAI_API_KEY environment variable.")
+
+# Function to encode the image to base64
+def encode_image_to_base64(image):
+    buffered = io.BytesIO()
+    image.save(buffered, format="JPEG")
+    img_str = base64.b64encode(buffered.getvalue()).decode('utf-8')
+    return img_str
+
+# Function to send the image to the OpenAI API and get a response
+def ask_openai_with_image(image):
+    # Encode the uploaded image to base64
+    base64_image = encode_image_to_base64(image)
+    
+    # Create the payload with the base64 encoded image
+    payload = {
+        "model": "gpt-4-vision-preview",
+        "messages": [
+            {
+                "role": "user",
+                "content": [
+                    {
+                        "type": "text",
+                        "text": "I've uploaded an image and I'd like to know what it depicts and any interesting details you can provide."
+                    },
+                    {
+                        "type": "image_url",
+                        "image_url": f"data:image/jpeg;base64,{base64_image}"
+                    }
+                ]
+            }
+        ],
+        "max_tokens": 4095
+    }
+    
+    # Send the request to the OpenAI API
+    response = requests.post(
+        "https://api.openai.com/v1/chat/completions",
+        headers={"Authorization": f"Bearer {openai.api_key}"},
+        json=payload
+    )
+    
+    # Check if the request was successful
+    if response.status_code == 200:
+        response_json = response.json()
+        print("Response JSON:", response_json)  # Print the raw response JSON
+        try:
+            # Attempt to extract the content text
+            return response_json["choices"][0]["message"]["content"]
+        except Exception as e:
+            # If there is an error in the JSON structure, print it
+            print("Error in JSON structure:", e)
+            print("Full JSON response:", response_json)
+            return "Error processing the image response."
+    else:
+        # If an error occurred, return the error message
+        return f"Error: {response.text}"
+
+# Create a Gradio interface
+iface = gr.Interface(
+    fn=ask_openai_with_image,
+    inputs=gr.Image(type="pil"),
+    outputs="text",
+    title="GPT-4 with Vision",
+    description="Upload an image and get a description from GPT-4 with Vision."
+)
+
+# Launch the app
+iface.launch()