app.py

from gpt_index import SimpleDirectoryReader, GPTListIndex, GPTSimpleVectorIndex, LLMPredictor, PromptHelper
from langchain import OpenAI
import gradio as gr
import sys
import os
import datetime

os.environ["OPENAI_API_KEY"] = 'SECRET'


def get_index(index_file_path):
    if os.path.exists(index_file_path):
        return GPTSimpleVectorIndex.load_from_disk(index_file_path)
    else:
        print(f"Error: '{index_file_path}' does not exist.")
        sys.exit()


def chatbot(input_text, mentioned_person='Mediation teacher John Haynes'):
    index = get_index('index.json')
    prompt = f"{mentioned_person}: {input_text}\n\n At the end of your answer, if you think appropriate, please ask a provocative question. Start it with a polite phrase such as - I wonder what you think...-."
    response = index.query(prompt, response_mode="compact")

    
    # Save chat log
    current_time = datetime.datetime.now()
    current_time_str = current_time.strftime("%Y-%m-%d_%H-%M-%S")
    chat_log_filename = f"{current_time_str}.txt"
    chat_log_filepath = os.path.join('docs/chathistory', chat_log_filename)
    with open(chat_log_filepath, "w") as f:
        f.write(f"Chat started at {current_time_str}\n\n")
        f.write(f"User: {input_text}\n")
        f.write(f"Chatbot: {response.response}\n\n")
    
    return response.response
    

with open("docs/about/descript.txt", "r") as f:
    description = f.read()

iface = gr.Interface(fn=chatbot,
                     inputs=gr.inputs.Textbox(lines=5, label="Enter your question"),
                     outputs=gr.outputs.Textbox(label="Chatbot Response"),
                     title="AI Chatbot trained on J. Haynes mediation material, v0.1",
                     description=description)

iface.launch(share=True)