Delete lib/chatbot_custom/chatbot_local_docqa.py

lib/chatbot_custom/chatbot_local_docqa.py

@@ -1,101 +0,0 @@
-import os
-import streamlit as st
-from llama_index.core import VectorStoreIndex, SimpleDirectoryReader, ServiceContext, Document
-from llama_index.llms.openai import OpenAI
-import openai
-from pathlib import Path
-from dotenv import load_dotenv
-
-# Load environment variables
-load_dotenv(Path("../../.env"))
-openai.api_key = os.getenv("OPENAI_API_KEY")
-
-
-def initialize_session_state():
-    """Initialize the chat message history in session state."""
-    if "messages" not in st.session_state:
-        st.session_state.messages = [
-            {"role": "assistant", "content": f"Ask me a question about documents from {LOCAL_BRAIN_DATA} or from the Web."}
-        ]
-
-
-@st.cache_resource(show_spinner=False)
-def load_data(input_dir):
-    """Load and index documents from the specified directory."""
-    with st.spinner("Loading and indexing your docs – hang tight! This should take 1-2 minutes."):
-        reader = SimpleDirectoryReader(input_dir=input_dir, recursive=True)
-        docs = reader.load_data()
-        service_context = ServiceContext.from_defaults(
-            llm=OpenAI(
-                model="gpt-3.5-turbo",
-                temperature=0.5,
-                system_prompt=(
-                    "You are an expert on content & digital marketing and your job is to answer technical questions."
-                    "Assume that all questions are related to provided documents, as context."
-                    "Keep your answers technical and based on facts – do not hallucinate features."
-                )
-            )
-        )
-        index = VectorStoreIndex.from_documents(docs, service_context=service_context)
-        return index
-
-
-def display_chat_history():
-    """Display the chat message history."""
-    for message in st.session_state.messages:
-        with st.chat_message(message["role"]):
-            st.write(message["content"])
-
-
-def generate_response(prompt, chat_engine):
-    """Generate a response from the chat engine and update the chat history."""
-    if prompt:
-        st.session_state.messages.append({"role": "user", "content": prompt})
-        
-        with st.chat_message("assistant"):
-            with st.spinner("Thinking..."):
-                response = chat_engine.chat(prompt)
-                st.write(response.response)
-                st.session_state.messages.append({"role": "assistant", "content": response.response})
-
-
-def alwrity_chat_docqa():
-    """Main function to run the Streamlit app."""
-    st.header("Ask Alwrity 💬 📚")
-    initialize_session_state()
-    option = st.radio(
-        "Choose Data Source To Ask From:",
-        ("Ask Your Local Docs", "Ask Your PDFs", "Ask Your Videos", "Ask Your Audio Files")
-    )
-
-    if option == "Ask Your Local Docs":
-        input_dir = st.text_input("Enter the path to the folder:")
-        if input_dir:
-            st.session_state.input_dir = input_dir
-
-    elif option == "Ask Your PDFs":
-        pdf_file = st.file_uploader("Upload a PDF file or enter a URL:", type=["pdf"])
-        if pdf_file:
-            st.session_state.input_file = pdf_file
-
-    elif option == "Ask Your Videos":
-        video_dir = st.text_input("Enter the path to the video folder:")
-        if video_dir:
-            st.session_state.input_dir = video_dir
-
-    elif option == "Ask Your Audio Files":
-        audio_dir = st.text_input("Enter the path to the audio folder:")
-        if audio_dir:
-            st.session_state.input_dir = audio_dir
-
-    if 'input_dir' in st.session_state:
-        index = load_data(st.session_state.input_dir)
-        chat_engine = index.as_chat_engine(chat_mode="condense_question", verbose=True)
-        display_chat_history()
-        prompt = st.chat_input("Your question")
-        if st.session_state.messages[-1]["role"] != "assistant":
-            generate_response(prompt, chat_engine)
-    
-    elif 'input_file' in st.session_state:
-        # Handle PDF file or URL input here
-        st.write("Handling PDF file or URL input is not implemented yet.")