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app.py

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+# from langchain.llms import OpenAI
+# from dotenv import load_dotenv
+# load_dotenv()
+
+# import streamlit as st
+# import os
+
+# def get_openai_response(question):
+#     llm=OpenAI(openai_api_key=os.getenv("OPEN_API_KEY"),model_name="gpt-3.5-turbo",temperature=0.5)
+#     response=llm(question)
+#     return response
+    
+
+# ## initialize streamlit app
+
+# st.set_page_config(page_title="Q&A Demo")
+# st.header("Langchain Application")
+
+# input =st.text_input("Input: ",key="input")
+# response = get_openai_response(input)
+
+# submit=st.button("Ask the question")
+
+# if submit:
+#     st.subheader("The response is")
+#     st.write(response)
+
+from langchain.llms import OpenAI
+from dotenv import load_dotenv
+import streamlit as st
+import os
+import openai
+
+load_dotenv()
+
+openai.api_key = os.getenv("OPENAI_API_KEY")
+
+def get_openai_response(question):
+    response = openai.ChatCompletion.create(
+        model="gpt-3.5-turbo",
+        messages=[
+            {"role": "user", "content": question}
+        ]
+    )
+    return response.choices[0].message['content']
+
+## initialize streamlit app
+
+st.set_page_config(page_title="Q&A Demo")
+st.header("Langchain Application")
+
+input_text = st.text_input("Input: ", key="input")
+
+if st.button("Ask the question"):
+    response = get_openai_response(input_text)
+    st.subheader("The response is")
+    st.write(response)

requirements.txt

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+langchain
+langchain-community
+openai
+huggingface_hub
+python-dotenv
+streamlit