app.py

import streamlit as st
from llmware.prompts import Prompt
import io, os, re
import PyPDF2

def register_gguf_model():

    prompter = Prompt()
    your_model_name = "llama"
    hf_repo_name = "TheBloke/Llama-2-7B-Chat-GGUF"
    model_file = "llama-2-7b-chat.Q3_K_M.gguf"
    print("registering models")
    prompter.model_catalog.register_gguf_model(your_model_name,hf_repo_name, model_file, prompt_wrapper="open_chat")
    your_model_name = "open_gpt4"
    hf_repo_name = "TheBloke/Open_Gpt4_8x7B-GGUF"
    model_file = "open_gpt4_8x7b.Q3_K_M.gguf"
    prompter.model_catalog.register_gguf_model(your_model_name,hf_repo_name, model_file, prompt_wrapper="open_chat")
    your_model_name = "phi2"
    hf_repo_name = "TheBloke/phi-2-GGUF"
    model_file = "phi-2.Q3_K_M.gguf"
    prompter.model_catalog.register_gguf_model(your_model_name,hf_repo_name, model_file, prompt_wrapper="open_chat")
    your_model_name = "mistral"
    hf_repo_name = "TheBloke/Mistral-7B-Instruct-v0.2-GGUF"
    model_file = "mistral-7b-instruct-v0.2.Q3_K_M.gguf"
    prompter.model_catalog.register_gguf_model(your_model_name,hf_repo_name, model_file, prompt_wrapper="open_chat")
    return prompter

def main():
    st.title("BetterZila RAG Enabled LLM")
    with st.spinner("Registering Models for use..."):
        prompter = register_gguf_model()
    
    data_path = "data/"
    
    st.sidebar.subheader("Select Model")
    model_name = st.sidebar.selectbox("Select Model", ["llama", "open_gpt4", "phi2", "mistral"])
    with st.spinner("Loading Model..."):
        prompter.load_model(model_name)
    st.success("Model Loaded!")
    
    queries = ['Can you give me an example from history where the enemy was crushed totally from the book?', "What's the point of making myself less accessible?", "Can you tell me the story of Queen Elizabeth I from this 48 laws of power book?"]
    
    st.subheader("Query")

    with st.spinner("Loading PDF file..."):
        for file in os.listdir(data_path):
            if file.endswith(".pdf"):
                print("Found PDF file: ", file)
                pdf_file = file
                break
    print("loading Source...")
    source = prompter.add_source_document(data_path, pdf_file, query=None)

    for query in queries:
        st.subheader(f"Query: {query}")
        with st.spinner("Generating response..."):
            responses = prompter.prompt_with_source(query, prompt_name="just_the_facts", temperature=0.3)
            
            for r, response in enumerate(responses):
                st.write(query)
                st.write(re.sub("[\n]", " ", response["llm_response"]).strip())

    st.success("Responses generated!")

    # for query in queries:
    #     st.subheader(f"Query: {query}")
    #     with st.spinner("Generating response..."):
    #         for file in os.listdir(data_path):
    #             if file.endswith(".pdf"):
    #                 print("Found PDF file: ", file)
    #                 print("loading Source...")
    #                 source = prompter.add_source_document(data_path, file, query=None)
    #                 print("generating response...")
    #                 responses = prompter.prompt_with_source(query, prompt_name="just_the_facts", temperature=0.3)
    #                 print("response generated!")
    #                 for r, response in enumerate(responses):
    #                     print(query, ":", re.sub("[\n]"," ", response["llm_response"]).strip())
    #                 prompter.clear_source_materials()
    #                 st.write(query)
    #                 st.write(re.sub("[\n]"," ", response["llm_response"]).strip())
    #     st.success("Response generated!")
        
if __name__ == "__main__":
    main()