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import os | |
import streamlit as st | |
from dotenv import load_dotenv | |
from langchain_openai import OpenAI # Ensure this import is correct for your setup | |
# Load environment variables | |
load_dotenv() | |
# Initialize the OpenAI object with your API key | |
api_key = os.getenv('OPEN_API_KEY') # Make sure you have this in your .env file | |
llm = OpenAI(api_key=api_key) | |
os.environ["OPENAI_API_KEY"]=os.getenv("OPENAI_API_KEY") | |
##LAngsmith Tracking | |
os.environ['LANGCHAIN_TRACING_V2']="true" | |
os.environ['LANGCHAIN_API_KEY']=os.getenv("LANGCHAIN_API_KEY") | |
def get_openai_response(question): | |
model_id = "gpt-3.5-turbo" # Ensure this is a valid model ID | |
# response = llm.create_completion(prompt=question, model=model_id) # Adjust according to actual method signature | |
llm=OpenAI(openai_api_key=os.environ["OPEN_API_KEY"],temperature=0.6) | |
response=llm(question) | |
return response | |
st.set_page_config(page_title="Q&A Demo") | |
st.header("Chat Open For All") | |
user_input = st.text_input("Input:", key="input") # Changed variable name from 'input' to 'user_input' | |
submit = st.button("Ask the question") | |
if submit and user_input: # Check if 'submit' is pressed and 'user_input' is not empty | |
response = get_openai_response(user_input) | |
st.subheader("The Response is:") | |
st.write(response) # Adjust based on how the response is structured | |