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()