Aziz Alto iamaziz

Using local LLMs anywhere (in text editor) - example below with Obsidian

inspired by and adopted from LLM-automator.

Code example with mixtral

automator-llm-code.mp4

	from fasthtml import common as fh

	def df2fhtml(df: pd.DataFrame, with_headers: bool=True, **kwargs):
	cols = df.columns
	header = fh.Tr(*[fh.Th(fh.Label(col)) for col in cols])
	rows = [fh.Tr(*[fh.Td(df[col][i]) for col in cols]) for i in range(len(df))]
	return fh.Table(header if with_headers else '', rows, *kwargs)

	import torch
	from langchain_community.embeddings import (
	OpenAIEmbeddings,
	OllamaEmbeddings,
	HuggingFaceEmbeddings,
	HuggingFaceBgeEmbeddings
	)

	def embedding_func(selected_embedding: str = "HuggingFaceEmbeddings"):
	"""

	import os
	import json
	import datetime

	import streamlit as st
	from llama_index.llms import Ollama
	from llama_index.llms import ChatMessage
	# https://docs.llamaindex.ai/en/stable/examples/llm/ollama.html

	import sys
	from io import StringIO

	import streamlit as st # pip install streamlit
	from code_editor import code_editor # pip install streamlit_code_editor
	import ollama as ol # pip install ollama

	st.set_page_config(layout='wide')
	st.title('`Offline code completion`')

	""" To use: install Ollama (or LLM studio), clone OpenVoice, run this script in the OpenVoice directory
	git clone https://github.com/myshell-ai/OpenVoice
	cd OpenVoice
	git clone https://huggingface.co/myshell-ai/OpenVoice
	cp -r OpenVoice/* .
	pip install whisper pynput pyaudio streamlit ollama

	script source: https://x.com/Thom_Wolf/status/1758140066285658351?s=20
	"""