Orami01 commited on
Commit
fe58fe8
·
1 Parent(s): e4a5ec9

Update app.py

Browse files
Files changed (1) hide show
  1. app.py +8 -11
app.py CHANGED
@@ -12,6 +12,11 @@ from langchain.document_loaders.csv_loader import CSVLoader
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  # Allow users to upload a CSV file
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  uploaded_file = st.sidebar.file_uploader("Upload your Data", type="csv")
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  if uploaded_file:
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  # Initialize the CSVLoader to load the uploaded CSV file
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  import tempfile
@@ -19,24 +24,16 @@ if uploaded_file:
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  tmp_file.write(uploaded_file.getvalue())
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  tmp_file_path = tmp_file.name
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  loader = CSVLoader(file_path=tmp_file_path, encoding="utf-8", csv_args={'delimiter': ','})
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  data = loader.load()
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  db.save_local(DB_FAISS_PATH)
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  llm = load_llm()
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- # Display the title of the web page
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- st.title("Chat with CSV using open source LLM Inference Point 🦙🦜")
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- # Display a markdown message with additional information
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- st.markdown("<h3 style='text-align: center; color: white;'>Built by <a href='https://github.com/AIAnytime'>AI Anytime with ❤️ </a></h3>", unsafe_allow_html=True)
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-
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- # Initialize the CSVLoader to load the uploaded CSV file
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- data = loader.load()
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- db.save_local(DB_FAISS_PATH)
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- llm = load_llm()
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-
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- chain = ConversationalRetrievalChain.from_llm(llm=llm, retriever=db.as_retriever())
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  def conversational_chat(query):
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  # Maintain and display the chat history
 
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  # Allow users to upload a CSV file
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  uploaded_file = st.sidebar.file_uploader("Upload your Data", type="csv")
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+ # Display the title of the web page
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+ st.title("Chat with CSV using open source LLM Inference Point 🦙🦜")
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+ # Display a markdown message with additional information
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+ st.markdown("<h3 style='text-align: center; color: white;'>Built by <a href='https://github.com/AIAnytime'>AI Anytime with ❤️ </a></h3>", unsafe_allow_html=True)
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+
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  if uploaded_file:
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  # Initialize the CSVLoader to load the uploaded CSV file
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  import tempfile
 
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  tmp_file.write(uploaded_file.getvalue())
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  tmp_file_path = tmp_file.name
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+ # Initialize the CSVLoader to load the uploaded CSV file
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  loader = CSVLoader(file_path=tmp_file_path, encoding="utf-8", csv_args={'delimiter': ','})
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  data = loader.load()
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  db.save_local(DB_FAISS_PATH)
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  llm = load_llm()
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+ chain = ConversationalRetrievalChain.from_llm(llm=llm, retriever=db.as_retriever())
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+
 
 
 
 
 
 
 
 
 
 
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  def conversational_chat(query):
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  # Maintain and display the chat history