iamaziz

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)

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

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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

iamaziz

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

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

iamaziz

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