| import streamlit as st | |
| import os | |
| from langchain import PromptTemplate, HuggingFaceHub, LLMChain | |
| x = st.slider('Select a value') | |
| st.write(x, 'squared is', x * x) | |
| # https://cobusgreyling.medium.com/langchain-creating-large-language-model-llm-applications-via-huggingface-192423883a74 | |
| # !pip install langchain[all] | |
| template = """Question: {question} | |
| Answer: Let's think step by step.""" | |
| prompt = PromptTemplate(template=template, input_variables=["question"]) | |
| llm=HuggingFaceHub(repo_id="google/flan-t5-xl", model_kwargs={"temperature":1e-10}) | |
| question = "When was Google founded?" | |
| # print(llm.run(question)) | |
| # d=LLMChain(llm=llm,prompt=prompt) | |
| st.write("out",LLMChain.run(question)) |