app.py

import requests
import streamlit as st
import os
from huggingface_hub import InferenceClient

API_URL = 'https://qe55p8afio98s0u3.us-east-1.aws.endpoints.huggingface.cloud'
API_KEY = os.getenv('API_KEY')

headers = {
    "Authorization": f"Bearer {API_KEY}",
    "Content-Type": "application/json"
}

# Prompt Set of Examples:
prompt = f"Write instructions to teach anyone to write a discharge plan. List the entities, features and relationships to CCDA and FHIR objects in boldface."

def StreamLLMChatResponse(prompt):
    endpoint_url = API_URL
    hf_token = API_KEY
    client = InferenceClient(endpoint_url, token=hf_token)
    gen_kwargs = dict(
        max_new_tokens=512,
        top_k=30,
        top_p=0.9,
        temperature=0.2,
        repetition_penalty=1.02,
        stop_sequences=["\nUser:", "<|endoftext|>", "</s>"],
    )
    stream = client.text_generation(prompt, stream=True, details=True, **gen_kwargs)
    report=[]
    res_box = st.empty()
    collected_chunks=[]
    collected_messages=[]
    for r in stream:
        if r.token.special:
            continue
        if r.token.text in gen_kwargs["stop_sequences"]:
            break
        collected_chunks.append(r.token.text)
        chunk_message = r.token.text
        collected_messages.append(chunk_message)

        try:
            report.append(r.token.text)
            if len(r.token.text) > 0:
                result="".join(report).strip()
                res_box.markdown(f'*{result}*')
        except:
            st.write(' ')

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

def get_output(prompt):
    return query({"inputs": prompt})

def main():
    st.title("Medical Llama Test Bench with Inference Endpoints Llama 7B")
    prompt = f"Write instructions to teach anyone to write a discharge plan. List the entities, features and relationships to CCDA and FHIR objects in boldface."
    example_input = st.text_input("Enter your example text:", value=prompt)

    if st.button("Run Prompt With Dr Llama"):
        StreamLLMChatResponse(example_input)

if __name__ == "__main__":
    main()