import google.generativeai as genai
import gradio as gr
import numpy as np
import PIL.Image
import io

genai.configure(api_key="AIzaSyAj-b3sO_wUguMdpXWScxKzMHxb8C5cels")

def ImageChat(image, prompt):
    # Check image file and convert to a PIL Image object
    if isinstance(image, np.ndarray):
        img = PIL.Image.fromarray(image)
    else:
        try:
            img = PIL.Image.open(image)
        except (AttributeError, IOError) as e:
            return f"Invalid image provided. Please provide a valid image file. Error: {e}"

    # Load model
    model = genai.GenerativeModel("gemini-pro-vision")

    # Combine the provided prompt with the custom prompt
    combined_prompt = f"{prompt}\n\n{custom_prompt}"

    # Generate response
    try:
        response = model.generate_content([combined_prompt, img])
        if not response or not response.text:
            return "No valid response received. The response might have been blocked."

        # Add rich formatting to the output
        formatted_response = response.text.replace("\n", "<br>").replace(":", ":</b>").replace("\n", "<br><b>")
        formatted_response = f"<b>{formatted_response}"
        return formatted_response
    except ValueError as e:
        return f"Error in generating response: {e}"

app = gr.Interface(
    fn=ImageChat,
    inputs=[gr.Image(label="Upload Stock Chart Image"), gr.Text(label="Prompt")],
    outputs=gr.HTML(label="Analysis Response"),
    title="Stock Chart Analysis",
    theme=gr.themes.Soft()
)

app.launch()