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| # Q&A Chatbot | |
| import os | |
| from langchain.llms import OpenAI | |
| from dotenv import load_dotenv | |
| import streamlit as st | |
| load_dotenv() | |
| # Function to load OpenAI model and get responses | |
| def get_openai_response(question): | |
| llm = OpenAI(openai_api_key = os.getenv("OPEN_API_KEY"), model_name = "text-davinci-003", temperature = 0.5) | |
| response = llm(question) | |
| return response | |
| # Initialize streamlit app | |
| st.set_page_config(page_title= "Q&A Demo") | |
| st.header("Langchain Application") | |
| # Get user input | |
| input = st.text_input("Input: ", key= input) | |
| response = get_openai_response(input) | |
| # How we got the input here: | |
| # 1. Sent the 'input' to the get_openai_response function | |
| # 2. OpenAI model was loaded with get_openai_response function, and calls for response using llm | |
| # (Instead of llm, we can also use predict message, predict functionality) | |
| # (We can also use chain or PromptTemplate instead of LLM) | |
| submit = st.button("Ask the question") | |
| # If the above 'ask' button is clicked - | |
| if submit: # Means if submit is true | |
| st.subheader("The response is ") | |
| st.write(response) | |