import gradio as gr
from transformers import pipeline
import os

# Retrieve the Hugging Face API token from environment variables
hf_token = os.getenv("HF_TOKEN")

if not hf_token:
    raise ValueError("API token is not set. Please set the HF_TOKEN environment variable in Space Settings.")

def authenticate_and_generate(message, history, system_message, max_tokens, temperature, top_p):
    try:
        # Initialize the text-generation pipeline with the provided token
        # Test with a known public model
        text_generator = pipeline("text-generation", model="gpt2", use_auth_token=hf_token)
        
        # Ensure that system_message is a string
        system_message = str(system_message)
        
        # Construct the prompt with system message, history, and user input
        history_str = "\n".join([f"User: {str(msg[0])}\nAssistant: {str(msg[1])}" for msg in history if isinstance(msg, (tuple, list)) and len(msg) == 2])
        prompt = system_message + "\n" + history_str
        prompt += f"\nUser: {message}\nAssistant:"

        # Generate a response using the model
        response = text_generator(prompt, max_length=max_tokens, temperature=temperature, top_p=top_p, do_sample=True, truncation=True)

        # Extract the generated text from the response list
        assistant_response = response[0]['generated_text']
        # Optionally trim the assistant response if it includes the prompt again
        assistant_response = assistant_response.split("Assistant:", 1)[-1].strip()
        return assistant_response

    except Exception as e:
        return str(e)  # Return the error message for debugging

athena = gr.ChatInterface(
    fn=authenticate_and_generate,
    additional_inputs=[
        gr.Textbox(
            value="""
            You are a marketing-minded content writer for Plan.com (a UK telecommunications company).
            You will be provided a bullet-point list of guidelines from which to generate an article to be published in the company News section of the website. 
            Please follow these guidelines:
            - Always speak using British English expressions, syntax, and spelling.
            - Make the articles engaging and fun, but also professional and informative.
            To provide relevant contextual information about the company, please source information from the following websites:
            - https://plan.com/our-story
            - https://plan.com/products-services
            - https://plan.com/features/productivity-and-performance
            - https://plan.com/features/security-and-connectivity
            - https://plan.com/features/connectivity-and-cost
            """,
            label="System message"
        ),
        gr.Slider(minimum=1, maximum=4096, value=512, step=1, label="Max new tokens"),
        gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature"),
        gr.Slider(minimum=0.1, maximum=1.0, value=0.95, step=0.05, label="Top-p (nucleus sampling)"),
    ],
)

if __name__ == "__main__":
    athena.launch()