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import streamlit as st
from langchain.llms import HuggingFaceHub
from langchain.chains import LLMChain
from langchain.prompts import PromptTemplate
#Function to return the response
def generate_answer(query):
llm = HuggingFaceHub(
repo_id = "google/flan-t5-xxl",
model_kwargs={"temperature": 0.7, "max_length": 64,"max_new_tokens":512}
)
template = """Question: {query}
Answer: Let's think step by step.
"""
PromptTemplate(template=template, input_variables=["query"])
llm_chain = LLMChain(prompt=prompt, llm=llm)
result = llm_chain.run(query)
return result
#App UI starts here
st.set_page_config(page_title = "LangChain Demo", page_icon = ":robot:")
st.header("LangChain Demo")
#Gets User Input
def get_text():
input_text = st.text_input("You: ", key="input")
return input_text
user_input = get_text()
response = generate_answer(user_input)
submit = st.button("Generate")
#If the button clicked
if submit:
st.subheader("Answer: ")
st.write(response)
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