Update app.py

app.py

@@ -8,109 +8,6 @@ from langchain_chroma import Chroma
 from langchain.chains import ConversationalRetrievalChain
 from langchain_openai import OpenAIEmbeddings, ChatOpenAI
 
-# # Initialize embedding function here
-# embedding_function = OpenAIEmbeddings()
-
-# # Updated cbfs class with dynamic database selection
-# class cbfs:
-#     def __init__(self, persist_directory):
-#         self.chat_history = []
-#         self.answer = ""
-#         self.db_query = ""
-#         self.db_response = []
-#         self.panels = []
-#         # Initialize Chroma and the ConversationalRetrievalChain with the chosen database
-#         db = Chroma(persist_directory=persist_directory, embedding_function=embedding_function)
-#         retriever = db.as_retriever(search_type="similarity", search_kwargs={"k": 3})
-#         self.qa = ConversationalRetrievalChain.from_llm(
-#             llm=ChatOpenAI(model_name="gpt-3.5-turbo", temperature=0),
-#             retriever=retriever,
-#             return_source_documents=True,
-#             return_generated_question=True,
-#         )
-
-#     def convchain(self, query):
-#         if not query:
-#             return [("User", ""), ("ChatBot", "")]
-#         result = self.qa.invoke({"question": query, "chat_history": self.chat_history})
-#         self.chat_history.append((query, result["answer"]))
-#         self.db_query = result["generated_question"]
-#         self.db_response = result["source_documents"]
-#         self.answer = result['answer']
-#         self.panels.append(["User", query])  # Ensure this is a list of two strings
-#         self.panels.append(["ChatBot", self.answer])  # Ensure this is a list of two strings
-#         return self.panels
-
-#     def clr_history(self):
-#         self.chat_history = []
-#         self.panels = []
-#         return self.panels  # Clear the chatbot display
-
-# # Create Gradio interface functions
-# def initialize_cbfs(db_choice):
-#     """Initialize cbfs object based on the database selection and clear history."""
-#     if db_choice == "Governance Documents":
-#         return cbfs(persist_directory='docs/chroma_eg/')
-#     elif db_choice == "Faculty Handbook":
-#         return cbfs(persist_directory='docs/chroma_hb/')
-#     else:
-#         return None
-
-# def chat_history(query, db_choice, cb):
-#     """Handles chat submissions. Reminds the user to select a document if none is selected."""
-#     if db_choice is None:
-#         return [("ChatBot", "Please select a document from the dropdown menu before submitting your query.")], ""
-#     else:
-#         return cb.convchain(query), ""  # Clear input box by returning empty string
-
-# # def clear_history(cb):
-# #     cb.clr_history()
-# #     return [], ""
-
-# def clear_history(cb):
-#     if cb is None:  # Check if cbfs instance is None
-#         return [], ""  # No error message, simply clear the UI components
-#     else:
-#         cb.clr_history()
-#         return [], ""
-
-
-# # Create Gradio UI layout
-# with gr.Blocks() as demo:
-#     gr.Markdown("# ISU-Economics Policy and Rules ChatBot")
-
-#     with gr.Row():
-#         db_choice = gr.Dropdown(["Governance Documents", "Faculty Handbook"], label="Select Document", scale=1)
-#         button_clearhistory = gr.Button("Clear History", scale=1)
-
-#     with gr.Row():
-#         inp = gr.Textbox(placeholder="Enter text here…", scale=8)
-#         button_submit = gr.Button("Submit", scale=1)
-
-#     output = gr.Chatbot()
-
-#     # Initialize cbfs instance
-#     cbfs_instance = gr.State(initialize_cbfs(db_choice.value))
-
-#     # Update cbfs_instance and clear chat history when the dropdown value changes
-#     def update_cbfs_and_clear_history(db_choice):
-#         new_cbfs = initialize_cbfs(db_choice)
-#         new_cbfs.clr_history()
-#         return new_cbfs, [], ""  # Clear the chatbot display and input box
-
-#     db_choice.change(
-#         fn=update_cbfs_and_clear_history,
-#         inputs=db_choice,
-#         outputs=[cbfs_instance, output, inp]
-#     )
-
-#     # Define interactions
-#     inp.submit(fn=chat_history, inputs=[inp, db_choice, cbfs_instance], outputs=[output, inp])
-#     button_submit.click(fn=chat_history, inputs=[inp, db_choice, cbfs_instance], outputs=[output, inp])
-#     button_clearhistory.click(fn=clear_history, inputs=cbfs_instance, outputs=[output, inp])
-
-# # Launch the Gradio app
-# demo.launch()
 
 import os
 import openai