app.py

import gradio as gr

def greet(text):

    from langchain.chat_models import ChatOllama
    from langchain.document_loaders import WebBaseLoader
    from langchain.chains.summarize import load_summarize_chain
    
    loader = WebBaseLoader("https://lilianweng.github.io/posts/2023-06-23-agent/")
    docs = loader.load()
    
    llm = ChatOpenAI(temperature=0, model_name="gpt-3.5-turbo-16k")
    chain = load_summarize_chain(llm, chain_type="stuff")
    
    chain.run(docs)

    from langchain.chains.llm import LLMChain
    from langchain.prompts import PromptTemplate
    from langchain.chains.combine_documents.stuff import StuffDocumentsChain
    
    # Define prompt
    prompt_template = """Write a concise summary of the following:
    "{text}"
    CONCISE SUMMARY:"""
    prompt = PromptTemplate.from_template(prompt_template)
    
    # Define LLM chain
    llm = ChatOllama(temperature=0, model_name="falcon:7b-instruct")
    llm_chain = LLMChain(llm=llm, prompt=prompt)
    
    # Define StuffDocumentsChain
    stuff_chain = StuffDocumentsChain(
        llm_chain=llm_chain, document_variable_name="text"
    )
    
    docs = loader.load()
    summary = stuff_chain.run(docs)
    
    return summary

with gr.Blocks() as demo:
    text = gr.Textbox(label="Text")
    summary = gr.Textbox(label="Summary")
    greet_btn = gr.Button("Submit")
    greet_btn.click(fn=greet, inputs=text, outputs=summary, api_name="greet")

demo.launch()