app.py

import gradio as gr
import openai
import logging

# Initialize the logger with level INFO
logging.basicConfig(filename='conversation_history.log', level=logging.INFO)

# Initialize the conversation history
conversation_history = [
    {
        "role": "system",
        "content": "Your name is Joe Chip, a world class poker player..."
        "If you need more context ask for it."
        " ake sure you know what the effective stack is and whether its a cash game or mtt"
        "Concentrate more on GTO play rather than exploiting other players."
        "Consider blockers when applicable" 
        "Always discuss how to play your range, not just the hand in question"
        "Remember to keep your answers brief"
        "Only answer questions on poker topics"
    }
]

def setup_openai(api_key):
    openai.api_key = api_key
    return "API Key Set Successfully!"

def ask_joe(api_key, text):
    # set up the api_key
    setup_openai(api_key)

    # Add the user's message to the conversation history
    conversation_history.append({
        "role": "user",
        "content": text
    })
    
    # Use the conversation history as the input to the model
    response = openai.ChatCompletion.create(
        model="gpt-4", 
        messages=conversation_history,
        max_tokens=500, 
        temperature=0.3
    )
    
    # Extract the model's message from the response
    model_message = response.choices[0].message['content'].strip()
    
    # Add the model's message to the conversation history
    conversation_history.append({
        "role": "assistant",
        "content": model_message
    })

    # Log the conversation history
    logging.info(f'User: {text}')
    logging.info(f'AI: {model_message}')
    
    return model_message

iface = gr.Interface(fn=ask_joe, inputs=[gr.inputs.Textbox(label="OpenAI API Key"), gr.inputs.Textbox(label="Enter your question here. More detail = Better results")], outputs=gr.outputs.Textbox(label="Joe's Response"))


iface.launch()