iamaziz

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

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

iamaziz

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

iamaziz

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`')

iamaziz

iamaziz

iamaziz

iamaziz

""" 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
"""

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

iamaziz

import re
import subprocess


def _parse_names(data: str) -> list[str]:
    """
    Parses names from a multi-line string where each line contains a name and other details.

    Parameters:
    data (str): A multi-line string containing names and other details.

iamaziz

# basedk on: https://github.com/joaomdmoura/crewAI#getting-started
from crewai import Agent, Task, Crew
from langchain_community.llms import Ollama
from langchain_community.tools import DuckDuckGoSearchRun


# -- model
# ollama_llm = Ollama(model="arabic_deepseek-llm")
# ollama_llm = Ollama(model="arabic_notux")
ollama_llm = Ollama(model="arabic_mixtral")