Update app.py

app.py

@@ -1,8 +1,12 @@
-from openai import OpenAI
-from langchain import OpenAI
+from transformers import pipeline
+
+import streamlit as st
+
 
-# from transformers import pipeline
 
+from langchain.llms import OpenAI
+
+# from dotenv import load_dotenv
 import os
 
 # take environment variables from .env
@@ -14,73 +18,32 @@ import streamlit as st
 
 
 def get_openai_response(question):
-    llm = OpenAI(
-        openai_api_key=os.getenv("OPEN_API_KEY"),
-        model_name="gpt-3.5-turbo-instruct",
-        temperature=0.6,
-    )
-    response = llm(question)
+    # llm = OpenAI(
+    #     openai_api_key=os.getenv("OPEN_API_KEY"),
+    #     model_name="gpt-3.5-turbo-instruct",
+    #     temperature=0.6,
+    # )
+    response = pipeline("summarization", model="stevhliu/my_awesome_billsum_model")
+    # response = llm(question)
     return response
     # modify with chain and other stuff
 
 
 ## streamlit app
 
-st.set_page_config(page_title="QandA Demo")
-st.header("QandA - Langchain Application")
-st.write("UPDATE: This app uses the 'gpt-3.5-turbo-instruct' model through Langchain to answer queries")
+st.set_page_config(page_title="Trail Demo")
+st.header("Sample")
+st.write("UPDATE: This app uses the 'gpt-3.5-turbo-instruct' model through Langchain")
 
 
-input = st.text_input("Enter your query: ", key=input)
-response = get_openai_response(input)
+# input = st.text_input("Enter your query: ", key=input)
+uploaded_file = st.file_uploader('Choose your .pdf file', type="pdf")
+if uploaded_file is not None:
+    df = extract_data(uploaded_file)
+response = get_openai_response(df)
 
 
 submit = st.button("Generate")
 if submit:
     st.subheader("The response is")
-    st.write(response)
-
-# pip install langchain
-
-# from langchain.llms import OpenAI
-
-# # from dotenv import load_dotenv
-# import os
-
-# # take environment variables from .env
-# # load_dotenv()
-
-# import streamlit as st
-
-# # load OpenAI model and get a response
-
-
-# def get_openai_response(question):
-#     llm = OpenAI(
-#         openai_api_key=os.getenv("OPEN_API_KEY"),
-#         model_name="gpt-3.5-turbo-instruct",
-#         temperature=0.6,
-#     )
-#     response = llm(question)
-#     return response
-#     # modify with chain and other stuff
-
-
-# ## streamlit app
-
-# st.set_page_config(page_title="Trail Demo")
-# st.header("Sample")
-# st.write("UPDATE: This app uses the 'gpt-3.5-turbo-instruct' model through Langchain")
-
-
-# # input = st.text_input("Enter your query: ", key=input)
-# uploaded_file = st.file_uploader('Choose your .pdf file', type="pdf")
-# if uploaded_file is not None:
-#     df = extract_data(uploaded_file)
-# response = get_openai_response(df)
-
-
-# submit = st.button("Generate")
-# if submit:
-#     st.subheader("The response is")
-#     st.write(response)
+    st.write(response)