import gradio as gr
from groq import Groq
import os

api_key = os.getenv("Historia")

# Initialize the Groq client with the API key
client = Groq(api_key = api_key)

# Function to interact with the Llama 3.1 model
def teach_history(user_input):
    completion = client.chat.completions.create(
        model="llama-3.1-70b-versatile",
        messages=[
            {
                "role": "system",
                "content": "You are an experienced historian with wide and deep knowledge in world history. You are a professor of history with 30 years of experience."
            },
            {
                "role": "user",
                "content": user_input
            }
        ],
        temperature=0.8,
        max_tokens=4096,
        top_p=1,
        stream=True,
        stop=None,
    )
    
    response = ""
    for chunk in completion:
        response += chunk.choices[0].delta.content or ""
    
    return response

# Gradio Blocks interface
with gr.Blocks() as demo:
    #gr.Markdown("# Historia")
    #gr.Markdown("### Learn History with a Knowledgeable Historian")
    gr.Markdown("<h1 style='text-align: center;'>Historia</h1>")
    gr.Markdown("<h3 style='text-align: center;'>Learn History with a Knowledgeable Historian</h3>")
    
    with gr.Row():
        with gr.Column():
            output = gr.Textbox(label="Response", lines=10)
            user_input = gr.Textbox(label="Enter your question or topic")
            submit_button = gr.Button("Submit")
    
    submit_button.click(fn=teach_history, inputs=user_input, outputs=output)

demo.launch()