Jawad138 commited on
Commit
7ac9f20
·
verified ·
1 Parent(s): 384fb80

Update app.py

Browse files
Files changed (1) hide show
  1. app.py +8 -9
app.py CHANGED
@@ -11,11 +11,9 @@ from langchain.document_loaders import TextLoader
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  from langchain.document_loaders import Docx2txtLoader
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  from langchain.callbacks.streaming_stdout import StreamingStdOutCallbackHandler
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  import os
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- from dotenv import load_dotenv
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  import tempfile
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- load_dotenv()
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-
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  def initialize_session_state():
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  if 'history' not in st.session_state:
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  st.session_state['history'] = []
@@ -26,11 +24,13 @@ def initialize_session_state():
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  if 'past' not in st.session_state:
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  st.session_state['past'] = ["Hey! 👋"]
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  def conversation_chat(query, chain, history):
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  result = chain({"question": query, "chat_history": history})
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  history.append((query, result["answer"]))
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  return result["answer"]
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  def display_chat_history(chain):
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  reply_container = st.container()
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  container = st.container()
@@ -53,9 +53,8 @@ def display_chat_history(chain):
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  message(st.session_state["past"][i], is_user=True, key=str(i) + '_user', avatar_style="thumbs")
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  message(st.session_state["generated"][i], key=str(i), avatar_style="fun-emoji")
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  def create_conversational_chain(vector_store):
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- load_dotenv()
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-
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  replicate_api_token = "r8_MgTUrfPJIluDoXUhG7JXuPAYr6PonOW4BJCj0"
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  os.environ["REPLICATE_API_TOKEN"] = replicate_api_token
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@@ -69,12 +68,12 @@ def create_conversational_chain(vector_store):
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  memory = ConversationBufferMemory(memory_key="chat_history", return_messages=True)
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  chain = ConversationalRetrievalChain.from_llm(llm=llm, chain_type='stuff',
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- retriever=vector_store.as_retriever(search_kwargs={"k": 2}),
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- memory=memory)
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  return chain
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  def main():
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- load_dotenv()
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  initialize_session_state()
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  st.title("Chat With Your Doc")
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  st.sidebar.title("Document Processing")
@@ -110,4 +109,4 @@ def main():
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  display_chat_history(chain)
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  if __name__ == "__main__":
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- main()
 
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  from langchain.document_loaders import Docx2txtLoader
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  from langchain.callbacks.streaming_stdout import StreamingStdOutCallbackHandler
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  import os
 
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  import tempfile
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+ # Initialize session state
 
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  def initialize_session_state():
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  if 'history' not in st.session_state:
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  st.session_state['history'] = []
 
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  if 'past' not in st.session_state:
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  st.session_state['past'] = ["Hey! 👋"]
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+ # Conversation chat function
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  def conversation_chat(query, chain, history):
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  result = chain({"question": query, "chat_history": history})
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  history.append((query, result["answer"]))
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  return result["answer"]
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+ # Display chat history
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  def display_chat_history(chain):
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  reply_container = st.container()
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  container = st.container()
 
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  message(st.session_state["past"][i], is_user=True, key=str(i) + '_user', avatar_style="thumbs")
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  message(st.session_state["generated"][i], key=str(i), avatar_style="fun-emoji")
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+ # Create conversational chain
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  def create_conversational_chain(vector_store):
 
 
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  replicate_api_token = "r8_MgTUrfPJIluDoXUhG7JXuPAYr6PonOW4BJCj0"
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  os.environ["REPLICATE_API_TOKEN"] = replicate_api_token
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  memory = ConversationBufferMemory(memory_key="chat_history", return_messages=True)
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  chain = ConversationalRetrievalChain.from_llm(llm=llm, chain_type='stuff',
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+ retriever=vector_store.as_retriever(search_kwargs={"k": 2}),
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+ memory=memory)
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  return chain
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+ # Main function
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  def main():
 
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  initialize_session_state()
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  st.title("Chat With Your Doc")
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  st.sidebar.title("Document Processing")
 
109
  display_chat_history(chain)
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  if __name__ == "__main__":
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+ main()