Update app.py

app.py

@@ -1,69 +1,12 @@
 import streamlit as st
-from PyPDF2 import PdfReader
-from langchain.text_splitter import CharacterTextSplitter
-from langchain.embeddings.openai import OpenAIEmbeddings
-from langchain.vectorstores import FAISS
-from langchain.chains.question_answering import load_qa_chain
-from langchain.llms import OpenAI
-from langchain.callbacks import get_openai_callback
 import os
-import openai
-from streamlit_chat import message
 
 
 def main():
-    OPENAI_API_KEY = st.text_input("Input your OpenAI API key", "")
-    os.environ["OPENAI_API_KEY"] = OPENAI_API_KEY
-    # st.header("Ask your PDF 💬")
-    
-    # upload file
-    pdf = st.file_uploader("Upload your PDF", type="pdf")
-    
-    # extract the text
-    if pdf is not None:
-      pdf_reader = PdfReader(pdf)
-      text = ""
-      for page in pdf_reader.pages:
-        text += page.extract_text()
-        
-      # split into chunks
-      text_splitter = CharacterTextSplitter(
-        separator="\n",
-        chunk_size=1000,
-        chunk_overlap=200,
-        length_function=len
-      )
-      chunks = text_splitter.split_text(text)
-      
-      # create embeddings
-      embeddings = OpenAIEmbeddings()
-      knowledge_base = FAISS.from_texts(chunks, embeddings)
-        
-      if 'generated' not in st.session_state:
-          st.session_state['generated'] = []
-      if 'past' not in st.session_state:
-          st.session_state['past'] = []
-      
-      # show user input
-      user_question = st.text_input("Ask a question about your PDF:")
-      if user_question:
-        docs = knowledge_base.similarity_search(user_question)
-        
-        llm = OpenAI()
-        chain = load_qa_chain(llm, chain_type="stuff")
-        with get_openai_callback() as cb:
-          response = chain.run(input_documents=docs, question=user_question)
-          print(cb)
-           
-        #st.write(response)
-        st.session_state.past.append(user_question)
-        st.session_state.generated.append(response)
-          
-      if st.session_state['generated']:
-        for i in range(len(st.session_state['generated'])-1, -1, -1):
-            message(st.session_state["generated"][i], key=str(i))
-            message(st.session_state['past'][i], is_user=True, key=str(i) + '_user')
-    
+    LLM_model = st.selectbox("Model",("OpenAI",
+                                    "TODO: ADD MORE..."))
+    if LLM_model == OpenAI":
+        openai_pdf()
 
 if __name__ == '__main__':
     main()