app.py

# 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()