Open Source LLM Projects
Discover 269 open source LLM repositories from GitHub, each with an analysis of what it does, key features, use cases and alternatives. LLM projects here are most often combined with Python, AI Agents and AI. Last updated October 4, 2026.
269 repositories · updated October 4, 2026
TencentDB-Agent-Memory: Share Reusable Memory Across AI Agents
TencentDB Agent Memory is a team memory hub that turns conversations, documents, and code into reusable assets for AI agents. It suits teams that want agents to share curated context and skills across sessions and frameworks.
ludwig: Configure and Train AI Models with YAML
Ludwig is a Python framework for configuring, training, evaluating, and deploying AI models through declarative YAML rather than custom training loops. It suits teams that want one workflow for LLM fine-tuning, tabular prediction, and multimodal modeling.
lamini: Access the Lamini API from Python
Lamini is a Python client and SDK for working with Lamini's generative AI API. It suits developers who want to connect Python applications to Lamini without building API requests from scratch.
zero: Run a Local Terminal Coding Agent
Zero is a Go-based terminal coding agent that can inspect and edit repositories, run commands, and work with many hosted or local models. It suits developers who want scriptable coding assistance with local sessions and explicit controls over side effects.
xTuring: Fine-Tune and Run Personalized LLMs
xTuring is a Python library for preparing data, fine-tuning, evaluating, and running open-source language models locally or in a private cloud. It is aimed at developers who want model customization through a high-level API and methods such as LoRA and quantization.
torchtune: Fine-Tune and Post-Train Large Language Models
torchtune is a PyTorch library for configuring and running LLM post-training workflows, from supervised fine-tuning to preference optimization. It is aimed at developers who want editable recipes and model-specific configs, but is no longer actively maintained.
griptape: Build AI Agents and Workflows in Python
Griptape is a modular Python framework for building generative AI applications with tasks, agents, pipelines, and workflows. It suits developers who want to combine language models with tools, memory, and retrieval components through swappable integrations.
RouteLLM: Route LLM Requests to Balance Cost and Quality
RouteLLM is a Python framework for routing prompts between stronger, costlier models and cheaper alternatives. It helps teams manage the cost-quality tradeoff, serve requests through an OpenAI-compatible interface, and evaluate routing strategies.
simpleaichat: Build Python ChatGPT Apps with Minimal Code
simpleaichat is a Python library for building chat applications and workflows with OpenAI chat models. It offers conversation management, streaming, asynchronous calls, structured data, and custom tools through a compact interface.
llm-compressor: Compress Models for vLLM Inference
LLM Compressor applies post-training quantization and related model transformations to prepare Hugging Face models for vLLM deployment. It suits teams seeking smaller or more inference-efficient checkpoints, with support for multiple formats and large-model workflows.
LightLLM: Serve Large Language Models with a Python Framework
LightLLM is a Python framework for LLM inference and serving, designed for scalable deployment and fast generation. It suits teams operating model-serving systems and researchers building on inference components.
torchchat: Run PyTorch LLMs on Desktop, Server, and Mobile
torchchat is a PyTorch codebase for running and interacting with language models locally through Python, native C++ runners, and mobile apps. It supports several execution and export paths, but is no longer under active development.