app.py

import gradio as gr
import requests
import os

API_URL = "https://api-inference.huggingface.co/models/bigscience/bloom"
HF_TOKEN = os.environ["HF_TOKEN"]
headers = {"Authorization": f"Bearer {HF_TOKEN}"}

def get_results(prompt):
    json_ = {"inputs": prompt,
            "parameters":
            {
            "top_p": 0.9,
            "typical_p":0.2,
          "temperature": 0.8,
          "max_new_tokens": 250,
          "return_full_text": True
          }, "options": 
              {
              "use_cache": True,
              "wait_for_model":True
              },}
    try:
        response = requests.post(API_URL, headers=headers, json=json_)
        output = response.json()
        output_tmp = output[0]['generated_text']
    except:
        output_tmp = "Not able to work"
    return output_tmp     


def learn_goals(topic, text):
    prompt = "Topic: " + topic + '\n'
    prompt = prompt + text + '\n'
    prompt = prompt + """Some examples of learning goals from above are:
    1. The student will be able to"""
    
    return get_results(prompt)
     

topic = gr.Textbox(lines = 1, placeholder="Topic")
text = gr.Textbox(lines = 5, placeholder="Text")

iface = gr.Interface(fn=learn_goals, inputs=[topic, text], outputs="text")
iface.launch()