semsearchDbgUI.py

import weaviate
from weaviate.connect import ConnectionParams
from weaviate.classes.init import AdditionalConfig, Timeout

from sentence_transformers import SentenceTransformer
from langchain_community.document_loaders import BSHTMLLoader
from pathlib import Path
from lxml import html
import logging
from semantic_text_splitter import HuggingFaceTextSplitter
from tokenizers import Tokenizer
import json
import os
import re
import logging

import llama_cpp
from llama_cpp import Llama

import ipywidgets as widgets
from IPython.display import display, clear_output


logger = logging.getLogger(__name__)
logging.basicConfig(level=logging.INFO)



######################################################################
# MAINLINE
#
logger.info("#### MAINLINE ENTERED.")

#####################################################################
# Create UI widgets.
output_widget = widgets.Output()
with output_widget:
    print("### Create widgets entered.")

systemTextArea = widgets.Textarea(
    value='',
    placeholder='Enter System Prompt.',
    description='Sys Prompt: ',
    disabled=False,
    layout=widgets.Layout(width='300px', height='80px')
)

userTextArea = widgets.Textarea(
    value='',
    placeholder='Enter User Prompt.',
    description='User Prompt: ',
    disabled=False,
    layout=widgets.Layout(width='435px', height='110px')
)

ragPromptTextArea = widgets.Textarea(
    value='',
    placeholder='App generated prompt with RAG information.',
    description='RAG Prompt: ',
    disabled=False,
    layout=widgets.Layout(width='580px', height='180px')
)

responseTextArea = widgets.Textarea(
    value='',
    placeholder='LLM generated response.',
    description='LLM Resp: ',
    disabled=False,
    layout=widgets.Layout(width='780px', height='200px')
)

selectRag = widgets.Checkbox(
    value=False,
    description='Use RAG',
    disabled=False
)

submitButton = widgets.Button(
    description='Run Model.',
    disabled=False,
    button_style='', # 'success', 'info', 'warning', 'danger' or ''
    tooltip='Click',
    icon='check' # (FontAwesome names without the `fa-` prefix)
)


# Display UI
logger.debug("### Before displaying UI: ")
display(systemTextArea)
display(userTextArea)
display(ragPromptTextArea)
display(responseTextArea)
display(selectRag)
display(submitButton)

def runLLM(prompt):
    max_tokens = 1000
    temperature = 0.3
    top_p = 0.1
    echo = True
    stop = ["Q", "\n"]

    modelOutput = llm(
       prompt,
       max_tokens=max_tokens,
       temperature=temperature,
       top_p=top_p,
       echo=echo,
       stop=stop,
    )
    result = modelOutput["choices"][0]["text"].strip()
    return(result)

def setPrompt(pprompt,ragFlag):
    logger.info("\n### setPrompt() entered. ragFlag: ",ragFlag)
    if ragFlag:
        ragPrompt = getRagData(pprompt)
        userPrompt = pprompt + "\n" + ragPrompt
        prompt = userPrompt
        userPrompt = "Using this information: " + ragPrompt \
             + "process the following statement or question and produce a a response" \
             + intialPrompt
    else:
        userPrompt = pprompt
    #prompt = f""" <s> [INST] <<SYS>> {systemTextArea.value} </SYS>> Q: {userPrompt} A: [/INST]"""
    return userPrompt


def on_submitButton_clicked(b):
    with output_widget:
        clear_output(wait=True)
        ragPromptTextArea.value = ""
        responseTextArea.value = ""
        log.debug(f"### selectRag: {selectRag.value}")
        prompt = setPrompt(userTextArea.value,selectRag.value)
        log.debug("### prompt: " + prompt)
        runLLM(prompt)

logger.info("\n### Before calling submitButton.on_click().")
submitButton.on_click(on_submitButton_clicked)
display(output_widget)