Upload app.py

app.py

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+##Q&A chatbot
+from langchain.llms import OpenAI
+from dotenv import load_dotenv
+load_dotenv() #take the environment variable from .env 
+import streamlit as st
+from langchain.chat_models import ChatOpenAI
+import os
+
+##function to load OpenAI model and get responses
+def got_openai_responses(question):
+    llm=OpenAI(openai_api_key=os.getenv("OPEN_API_KEY"),model_name="gpt-3.5-turbo-instruct",temperature=0.5)
+    response=llm(question)
+    return response
+   
+#initialize streamit app
+
+st.set_page_config(page_title="Q&A Demo")
+
+st.header("Langchain Application")
+    
+input=st.text_input("input :",key="input")
+    
+response=got_openai_responses(input)
+
+    
+submit=st.button("Ask the question")
+
+##if ask button is clicked
+
+
+if submit:
+       st.subheader("the Responses is")
+       st.write(response)
+'''import os
+import streamlit as st
+from dotenv import load_dotenv
+from langchain.chat_models import ChatOpenAI
+
+load_dotenv()  # load environment variables from .env
+
+# Function to get response from OpenAI
+def got_openai_responses(question):
+    llm = ChatOpenAI(openai_api_key=os.getenv("OPEN_API_KEY"), model_name="gpt-3.5-turbo", temperature=0.5)
+    response = llm.invoke(question)
+    return response.content if hasattr(response, "content") else response
+
+# Streamlit UI
+st.set_page_config(page_title="Q&A Demo")
+st.header("LangChain Chatbot")
+
+input = st.text_input("Ask your question:", key="input")
+submit = st.button("Ask")
+
+if submit and input:
+    response = got_openai_responses(input)
+    st.subheader("Response:")
+    st.write(response)'''
+
+