app.py

import gradio as gr
import requests
import os

API_TOKEN = os.getenv('API_TOKEN')
API_URL = "https://api-inference.huggingface.co/models/nasa-impact/nasa-smd-ibm-v0.1"
headers = {"Authorization": f"Bearer {API_TOKEN}"}

def query(payload):
	response = requests.post(API_URL, headers=headers, json=payload)
	return response.json()

def get_model_output(input_text):

    payload = {
        "inputs": input_text
    }
    #output = query({"inputs": "The answer to the universe is <mask>.", })
    output = query(payload)
    results = []
    for item in output:
        sequence = item.get('sequence', '')
        score = item.get('score', 0)
        results.append(f"{sequence} (Score: {score:.4f})")
    return "\n".join(results)
    

# Define Gradio interface

article_text = """

### Notes:

### Possible Demo Apps:

1. **Data Cleaning and Imputation**
2. **Content Generation and Brainstorming**
3. **Code Completion and Documentation**

"""
demo = gr.Interface(
    fn=get_model_output,
    inputs=gr.Textbox(lines=2, label="Input with mask token", placeholder="Enter a sentence with <mask> to fill..."),
    outputs="text",  # Display the output as JSON to inspect the response structure
    title="nasa-smd-ibm-v0.1 Model Output",
    description="NASA SMD Indus model response (Fill Mask).",
    article=article_text
)

# Launch the interface
demo.launch()