app.py

import gradio as gr
from llama_cpp import Llama
from huggingface_hub import hf_hub_download

# Fetch the model file from Hugging Face Hub
model_repo = "SupermanRX/moderateTherapistModel"  # Replace with your repo name
model_file = "model.gguf"  # Replace with your GGUF model file name in the repo

# Download the model file to the local environment
model_path = hf_hub_download(repo_id=model_repo, filename=model_file)

# Load the GGUF model
llm = Llama(model_path=model_path)

# Define the chatbot function
def chatbot(input_text):
    output = llm(prompt=input_text, max_tokens=200)
    return output['choices'][0]['text']

# Create Gradio interface
with gr.Blocks() as demo:
    chatbot_ui = gr.Chatbot()
    textbox = gr.Textbox(label="Type your message here:")
    submit = gr.Button("Send")

    # Handle user interaction
    def user_interaction(input_text, chat_history):
        response = chatbot(input_text)
        chat_history.append((input_text, response))
        return chat_history, ""

    submit.click(user_interaction, [textbox, chatbot_ui], [chatbot_ui, textbox])

demo.launch()