app.py

import gradio as gr

from langchain_core.messages import HumanMessage, SystemMessage
from langchain_huggingface import HuggingFaceEndpoint, ChatHuggingFace

import os
HF_Hub_API_token = os.environ.get('HF_Hub_API_token', None)

llm = HuggingFaceEndpoint(
    repo_id="mistralai/Mistral-7B-Instruct-v0.2",
    task="text-generation",
    max_new_tokens=128,
    do_sample=False,
    repetition_penalty=1.03,
    huggingfacehub_api_token=HF_Hub_API_token
)

chat_model = ChatHuggingFace(llm=llm)

MAX_LEN = 100
def gen_prompt1(title):
    prompt1 = title
    formatted_str = ''
    if len(title) > 0:
        messages = [HumanMessage(content=prompt1),]
        res = chat_model.invoke(messages)
        # censure
        for s in res.content.split('\n'):
            if len(s) > MAX_LEN:
                s = s[:MAX_LEN] + " (...)"
            formatted_str += s + '\n'

        return formatted_str #res.content

example_title = "Mary had a little lamb"

demo = gr.Interface(
    fn=gen_prompt1,
    inputs=gr.Textbox(label = "Introduction", show_label=True),
    outputs=["text"],
    examples=[example_title]
)

demo.launch()