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MakMemEng's starred repositories

promptfoo

Test your prompts, agents, and RAGs. Redteaming, pentesting, vulnerability scanning for LLMs. Improve your app's quality and catch problems. Compare performance of GPT, Claude, Gemini, Llama, and more. Simple declarative configs with command line and CI/CD integration.

Language:TypeScriptMIT378100

sfguide-data-crawler

Generate descriptions of Snowflake tables and views with LLMs

Language:PythonApache-2.0800

GIF

Government Interoperability Framework

CC0-1.012300

SliDEM-python

Python package for the SliDEM project

Language:PythonApache-2.01700

kitty

Cross-platform, fast, feature-rich, GPU based terminal

Language:PythonGPL-3.02319300

python-rye

This repository contains configurations to set up a Python development environment using VSCode's Dev Container feature. The environment includes Rye, uv, and Ruff.

Language:DockerfileMIT3400

mlx-examples

Examples in the MLX framework

Language:PythonMIT561900

PyMuPDF

PyMuPDF is a high performance Python library for data extraction, analysis, conversion & manipulation of PDF (and other) documents.

Language:PythonAGPL-3.0473900

How-to-load-PDF-files-into-Milvus-by-using-Spark

How to ingest and embed PDF files at scale using Spark for Retrieval Augmented Generation. We will walk through the steps required to set up the environment, install the necessary components, ingest PDF files into Milvus using Spark, and query the vector database for answers using OpenAI and Llama2

Language:Python300

vscode-dev-containers

NOTE: Most of the contents of this repository have been migrated to the new devcontainers GitHub org (https://github.com/devcontainers). See https://github.com/devcontainers/template-starter and https://github.com/devcontainers/feature-starter for information on creating your own!

Language:ShellMIT470200

pyspark-devcontainer

A simple VS Code devcontainer setup for local PySpark development

Language:Jupyter Notebook2800

try-pyspark

Pyspark（Jupyter Notebook）をDevcontainerで構築しています。直ぐにPyspark（Jupyter Notebook）を試すことができます。

Language:Jupyter NotebookMIT200

MeloTTS

High-quality multi-lingual text-to-speech library by MyShell.ai. Support English, Spanish, French, Chinese, Japanese and Korean.

Language:PythonMIT415500

aiortc

WebRTC and ORTC implementation for Python using asyncio

Language:PythonBSD-3-Clause406500

contoso-chat

This sample has the full End2End process of creating RAG application with Prompt Flow and AI Studio. It includes GPT 3.5 Turbo LLM application code, evaluations, deployment automation with AZD CLI, GitHub actions for evaluation and deployment and intent mapping for multiple LLM task mapping.

Language:Jupyter NotebookMIT38400