app.py

import gradio as gr
import os
import openai
from dotenv import load_dotenv

# Load environment variables
load_dotenv()
OPENAI_API_KEY = os.getenv("OPENAI_API_KEY")

# Initialize OpenAI client
openai.api_key = OPENAI_API_KEY
openai.api_base = "https://api.aimlapi.com/"

# Greeting function for Gradio
def greet(name):
    return f"Hello {name}!"

# OpenAI Chat Completion Function
def get_openai_response(user_content, model="o1-preview", max_tokens=500):
    try:
        chat_completion = openai.ChatCompletion.create(
            model=model,
            messages=[
                {"role": "user", "content": user_content}
            ],
            max_tokens=max_tokens
        )
        response = chat_completion.choices[0].message['content']
        return response
    except Exception as e:
        return f"An error occurred: {e}"

# Gradio interface
def openai_chat_interface(user_content, model, max_tokens):
    return get_openai_response(user_content, model, max_tokens)

# Define Gradio Interface
with gr.Blocks() as demo:
    gr.Markdown("# OpenAI Chat Completion & Greeting Interface")
    
    # Greeting section
    with gr.Row():
        gr.Markdown("### Greeting Section")
        greet_input = gr.Textbox(label="Enter your name")
        greet_output = gr.Textbox(label="Greeting Output")
        greet_button = gr.Button("Greet")
        greet_button.click(greet, inputs=greet_input, outputs=greet_output)
    
    # OpenAI Chat Completion Section
    with gr.Row():
        gr.Markdown("### OpenAI Chat Completion")
        user_input = gr.Textbox(label="Enter your message")
        model_input = gr.Radio(["o1-preview", "o1-mini"], label="Model Selection", value="o1-preview")
        max_tokens_input = gr.Slider(1, 7000, value=500, label="Max Tokens")
        openai_response = gr.Textbox(label="OpenAI Response")
        chat_button = gr.Button("Get OpenAI Response")
        chat_button.click(openai_chat_interface, 
                          inputs=[user_input, model_input, max_tokens_input], 
                          outputs=openai_response)

# Launch Gradio app
demo.launch()