app.py

import gradio as gr
import openai
import fitz  # PyMuPDF for PDF processing
import base64

# Store API Key
api_key = ""

# Function to update API Key
def set_api_key(key):
    global api_key
    api_key = key
    return "API Key Set Successfully!"

# Function to interact with OpenAI API using conversation history
def query_openai(messages, temperature, top_p, max_output_tokens):
    if not api_key:
        return ["Please enter your OpenAI API key first."], messages

    try:
        openai.api_key = api_key  # Set API Key dynamically

        # Ensure valid values for OpenAI parameters
        temperature = float(temperature) if temperature else 1.0
        top_p = float(top_p) if top_p else 1.0
        max_output_tokens = int(max_output_tokens) if max_output_tokens else 2048

        response = openai.ChatCompletion.create(
            model="gpt-4.5-preview",
            messages=messages,
            temperature=temperature,
            top_p=top_p,
            max_tokens=max_output_tokens
        )

        bot_response = response["choices"][0]["message"]["content"]
        messages.append({"role": "assistant", "content": bot_response})  # Store bot response in history

        return messages, messages  # Return updated conversation

    except Exception as e:
        return [f"Error: {str(e)}"], messages

# Image URL Chat
def image_url_chat(image_url, text_query, messages, temperature, top_p, max_output_tokens):
    if not image_url or not text_query:
        return ["Please provide an image URL and a query."], messages

    messages.append({"role": "user", "content": [
        {"type": "image_url", "image_url": {"url": image_url}},
        {"type": "text", "text": text_query}
    ]})
    return query_openai(messages, temperature, top_p, max_output_tokens)

# Text Chat
def text_chat(text_query, messages, temperature, top_p, max_output_tokens):
    if not text_query:
        return ["Please enter a query."], messages

    messages.append({"role": "user", "content": text_query})
    return query_openai(messages, temperature, top_p, max_output_tokens)

# Image Chat
def image_chat(image_file, text_query, messages, temperature, top_p, max_output_tokens):
    if image_file is None or not text_query:
        return ["Please upload an image and provide a query."], messages

    # Encode image as base64
    with open(image_file, "rb") as img:
        base64_image = base64.b64encode(img.read()).decode("utf-8")

    image_data = f"data:image/jpeg;base64,{base64_image}"

    messages.append({"role": "user", "content": [
        {"type": "image_url", "image_url": {"url": image_data}},
        {"type": "text", "text": text_query}
    ]})
    return query_openai(messages, temperature, top_p, max_output_tokens)

# PDF Chat
def pdf_chat(pdf_file, text_query, messages, temperature, top_p, max_output_tokens):
    if pdf_file is None or not text_query:
        return ["Please upload a PDF and provide a query."], messages

    doc = fitz.open(pdf_file)
    text = "\n".join([page.get_text("text") for page in doc][:5])  # Extract text from first 5 pages

    messages.append({"role": "user", "content": [
        {"type": "text", "text": text},
        {"type": "text", "text": text_query}
    ]})
    return query_openai(messages, temperature, top_p, max_output_tokens)

# Function to clear chat history and reset parameters
def clear_chat():
    return [], [], [], [], "", "", [], "", [], None, "", [], None, "", 1.0, 1.0, 2048

# Gradio UI Layout
with gr.Blocks() as demo:
    gr.Markdown("## GPT-4.5 Preview Conversational Chatbot")

    # API Key Input
    with gr.Row():
        api_key_input = gr.Textbox(label="Enter OpenAI API Key", type="password")
        api_key_button = gr.Button("Set API Key")
        api_key_output = gr.Textbox(label="API Key Status", interactive=False)

    with gr.Row():
        temperature = gr.Slider(0, 2, value=1.0, step=0.1, label="Temperature")
        top_p = gr.Slider(0, 1, value=1.0, step=0.1, label="Top-P")
        max_output_tokens = gr.Slider(0, 16384, value=2048, step=512, label="Max Output Tokens")

    with gr.Tabs():
        with gr.Tab("Image URL Chat"):
            image_url = gr.Textbox(label="Enter Image URL")
            image_query = gr.Textbox(label="Ask about the Image")
            image_url_output = gr.Chatbot(label="Conversation History", elem_id="chatbot1")
            image_url_button = gr.Button("Ask")

        with gr.Tab("Text Chat"):
            text_query = gr.Textbox(label="Enter your query")
            text_output = gr.Chatbot(label="Conversation History", elem_id="chatbot2")
            text_button = gr.Button("Ask")

        with gr.Tab("Image Chat"):
            image_upload = gr.File(label="Upload an Image", type="filepath")
            image_text_query = gr.Textbox(label="Ask about the uploaded image")
            image_output = gr.Chatbot(label="Conversation History", elem_id="chatbot3")
            image_button = gr.Button("Ask")

        with gr.Tab("PDF Chat"):
            pdf_upload = gr.File(label="Upload a PDF", type="filepath")
            pdf_text_query = gr.Textbox(label="Ask about the uploaded PDF")
            pdf_output = gr.Chatbot(label="Conversation History", elem_id="chatbot4")
            pdf_button = gr.Button("Ask")

    # Clear chat button
    clear_button = gr.Button("Clear Chat")

    # Chat Histories
    image_url_chat_history = gr.State([])
    text_chat_history = gr.State([])
    image_chat_history = gr.State([])
    pdf_chat_history = gr.State([])

    # Button Click Actions
    api_key_button.click(set_api_key, inputs=[api_key_input], outputs=[api_key_output])
    image_url_button.click(image_url_chat, [image_url, image_query, image_url_chat_history, temperature, top_p, max_output_tokens], [image_url_output, image_url_chat_history])
    text_button.click(text_chat, [text_query, text_chat_history, temperature, top_p, max_output_tokens], [text_output, text_chat_history])
    image_button.click(image_chat, [image_upload, image_text_query, image_chat_history, temperature, top_p, max_output_tokens], [image_output, image_chat_history])
    pdf_button.click(pdf_chat, [pdf_upload, pdf_text_query, pdf_chat_history, temperature, top_p, max_output_tokens], [pdf_output, pdf_chat_history])

    # Fix: Clear button resets all necessary fields correctly
    clear_button.click(
        clear_chat,
        outputs=[
            image_url_chat_history, text_chat_history, image_chat_history, pdf_chat_history,
            image_url, image_query, image_url_output, 
            text_query, text_output, 
            image_upload, image_text_query, image_output, 
            pdf_upload, pdf_text_query, pdf_output, 
            temperature, top_p, max_output_tokens
        ]
    )

# Launch Gradio App
if __name__ == "__main__":
    demo.launch()