app.py

import os
import gradio as gr
import requests

# Retrieve the API token from environment variables
api_token = os.getenv("MODEL_REPO_ID")
if not api_token:
    raise ValueError("MODEL_REPO_ID token not found. Please set the API_TOKEN environment variable.")

# Hugging Face Inference API Details
API_URL = "https://api-inference.huggingface.co/models/meta-llama/Llama-3.2-1B-Instruct"
HEADERS = {"Authorization": f"Bearer {MODEL_REPO_ID}"}


def generate_exegesis(passage):
    if not passage.strip():
        return "Please enter a Bible passage."
    
    prompt = f"You are a professional Bible Scholar, Provide a detailed exegesis of the following biblical verse, including: The original Greek text and transliteration with Word-by-word analysis with meanings. Historical and cultural context. Theological significance. for:\n\n{passage}\n\nExegesis:"
    
    payload = {
        "inputs": prompt,
        "parameters": {
            "max_length": 250,
            "temperature": 0.7,
            "do_sample": True
        }
    }
    
    try:
        response = requests.post(API_URL, headers=HEADERS, json=payload)
        response.raise_for_status()  # Raise an error for bad responses (4xx, 5xx)
        result = response.json()
        
        if isinstance(result, list) and len(result) > 0:
            return result[0].get("generated_text", "Error: No response from model.")
        else:
            return "Error: Unexpected response format."
    except requests.exceptions.RequestException as e:
        return f"API Error: {e}"

# Gradio interface
demo = gr.Interface(
    fn=generate_exegesis,
    inputs=gr.Textbox(label="Enter Bible Passage", placeholder="e.g., John 3:16"),
    outputs=gr.Textbox(label="Exegesis Commentary"),
    title="JR Study Bible",
    description="Enter a Bible passage to receive insightful exegesis commentary using the Hugging Face API."
)

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