{"data":{"slug":"tensorchord-awesome-llmops","name":"Awesome-LLMOps","tagline":"An awesome & curated list of best LLMOps tools for developers","github_url":"https://github.com/tensorchord/Awesome-LLMOps","owner":"tensorchord","repo":"Awesome-LLMOps","owner_avatar_url":"https://avatars.githubusercontent.com/u/100543303?v=4","primary_language":"Shell","stars":5915,"forks":993,"topics":["ai-development-tools","awesome-list","llmops","mlops"],"archived":false,"github_pushed_at":"2026-05-21T09:12:50+00:00","maintenance_label":"Slowing","stars_delta_30d":28,"url":"https://www.graphcanon.com/tools/tensorchord-awesome-llmops","markdown_url":"https://www.graphcanon.com/tools/tensorchord-awesome-llmops.md","api_url":"https://www.graphcanon.com/api/graphcanon/tools/tensorchord-awesome-llmops","graph_url":"https://www.graphcanon.com/api/graphcanon/graph?tool=tensorchord-awesome-llmops","description":"An awesome & curated list of best LLMOps tools for developers","homepage_url":null,"license":"CC0-1.0","open_issues":247,"watchers":79,"ai_summary":"A comprehensive curated list that covers a wide range of categories within the LLM and MLOps ecosystem, including frameworks, serving methods, security aspects, training processes, data handling, large scale deployment strategies, performance optimization techniques, AutoML solutions, optimizations in model management, federated learning approaches, and even specific models for various domains like CV, Audio, Robotics.","readme_excerpt":"# Awesome LLMOps\n\n<a href=\"https://discord.gg/KqswhpVgdU\"><img alt=\"discord invitation link\" src=\"https://img.shields.io/discord/974584200327991326?style=flat&logo=discord&cacheSeconds=60\"></a>\n<a href=\"https://awesome.re\"><img src=\"https://awesome.re/badge-flat2.svg\"></a>\n\nAn awesome & curated list of the best LLMOps tools for developers.\n\n> [!NOTE]\n> Contributions are most welcome, please adhere to the [contribution guidelines](contributing.md).\n\n## Table of Contents\n\n- [Awesome LLMOps](#awesome-llmops)\n  - [Table of Contents](#table-of-contents)\n  - [Model](#model)\n    - [Large Language Model](#large-language-model)\n    - [CV Foundation Model](#cv-foundation-model)\n    - [Audio Foundation Model](#audio-foundation-model)\n    - [Robotics Foundation Model](#robotics-foundation-model)\n  - [Serving](#serving)\n    - [Large Model Serving](#large-model-serving)\n    - [Frameworks/Servers for Serving](#frameworksservers-for-serving)\n  - [Security](#security)\n    - [Frameworks for LLM security](#frameworks-for-llm-security)\n    - [Observability](#observability)\n  - [LLMOps](#llmops)\n  - [Search](#search)\n    - [Vector search](#vector-search)\n  - [Code AI](#code-ai)\n  - [Training](#training)\n    - [IDEs and Workspaces](#ides-and-workspaces)\n    - [Foundation Model Fine Tuning](#foundation-model-fine-tuning)\n    - [Frameworks for Training](#frameworks-for-training)\n    - [Experiment Tracking](#experiment-tracking)\n    - [Visualization](#visualization)\n    - [Model Editing](#model-editing)\n  - [Data](#data)\n    - [Data Management](#data-management)\n    - [Data Storage](#data-storage)\n    - [Data Tracking](#data-tracking)\n    - [Feature Engineering](#feature-engineering)\n    - [Data/Feature enrichment](#datafeature-enrichment)\n  - [Large Scale Deployment](#large-scale-deployment)\n    - [ML Platforms](#ml-platforms)\n    - [Workflow](#workflow)\n    - [Scheduling](#scheduling)\n    - [Model Management](#model-management)\n  - [Performance](#performance)\n    - [ML Compiler](#ml-compiler)\n    - [Profiling](#profiling)\n  - [AutoML](#automl)\n  - [Optimizations](#optimizations)\n  - [Federated ML](#federated-ml)\n  - [Awesome Lists](#awesome-lists)\n\n\n\n## Model\n\n### Large Language Model\n\n| Project                                                                 | Details                                                                                                                                                                                    | Repository                                                                                                |\n| ----------------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ | --------------------------------------------------------------------------------------------------------- |\n| [Alpaca](https://github.com/tatsu-lab/stanford_alpaca)                  | Code and documentation to train Stanford's Alpaca models, and generate the data.                                                                                                           |       |\n| [BELLE](https://github.com/LianjiaTech/BELLE)                           | A 7B Large Language Model fine-tune by 34B Chinese Character Corpus, based on LLaMA and Alpaca.                                                                                            |               |\n| [Bloom](https://github.com/bigscience-workshop/model_card)              | BigScience Large Open-science Open-access Multilingual Language Model                                                                                                                      |  |\n| [dolly](https://github.com/databrickslabs/dolly)                        | Databricks’ Dolly, a large language model trained on the Databricks Machine Learning Platform","github_created_at":"2022-04-15T01:56:44+00:00","created_at":"2026-07-07T17:42:02.207298+00:00","updated_at":"2026-08-20T12:01:40.503586+00:00","categories":[{"slug":"computer-vision","name":"Computer Vision","url":"https://www.graphcanon.com/categories/computer-vision","markdown_url":"https://www.graphcanon.com/categories/computer-vision.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/computer-vision"},{"slug":"data-retrieval","name":"Data & Retrieval","url":"https://www.graphcanon.com/categories/data-retrieval","markdown_url":"https://www.graphcanon.com/categories/data-retrieval.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/data-retrieval"},{"slug":"evaluation-observability","name":"Evaluation & Observability","url":"https://www.graphcanon.com/categories/evaluation-observability","markdown_url":"https://www.graphcanon.com/categories/evaluation-observability.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/evaluation-observability"},{"slug":"inference-serving","name":"Inference & Serving","url":"https://www.graphcanon.com/categories/inference-serving","markdown_url":"https://www.graphcanon.com/categories/inference-serving.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/inference-serving"},{"slug":"llm-frameworks","name":"LLM Frameworks","url":"https://www.graphcanon.com/categories/llm-frameworks","markdown_url":"https://www.graphcanon.com/categories/llm-frameworks.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/llm-frameworks"},{"slug":"model-training","name":"Model Training","url":"https://www.graphcanon.com/categories/model-training","markdown_url":"https://www.graphcanon.com/categories/model-training.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/model-training"},{"slug":"speech-audio","name":"Speech & Audio","url":"https://www.graphcanon.com/categories/speech-audio","markdown_url":"https://www.graphcanon.com/categories/speech-audio.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/speech-audio"}],"tags":[{"slug":"ai-development-tools","name":"ai-development-tools"},{"slug":"awesome-list","name":"awesome-list"},{"slug":"llmops","name":"llmops"},{"slug":"mlops","name":"mlops"}],"trust":{"provenance":{"is_fork":false,"github_id":481805419,"owner_type":"Organization","methodology":"github_public_v1","parent_repo":null,"near_duplicate_slugs":[]},"computed_at":"2026-08-20T12:01:39.753Z","maintenance":{"label":"Slowing","score":36,"methodology":"github_public_v1","releases_90d":0,"days_since_push":91,"last_release_at":null,"stars_delta_30d":28,"open_issues_delta_30d":66},"security_summary":{"status":"no_lockfile","scanner":null,"low_count":0,"high_count":0,"last_scan_at":"2026-07-11T11:19:56.896Z","medium_count":0,"scan_profile":"none","critical_count":0}},"capability_facts":{"scan":{"source":"repo_scan","observed_at":"2026-08-20T12:01:40.220Z"},"languages":{"value":["shell"],"source":"github.language","observed_at":"2026-08-20T12:01:40.220Z"},"license_spdx":{"value":"CC0-1.0","source":"github.license","observed_at":"2026-08-20T12:01:40.220Z"}},"decision_facts":{"hosting":null,"pricing":null,"requirements":null,"constraints":null,"when_to_use":["- When you need a comprehensive directory of tools specifically focused on LLM development, training, fine-tuning, and management.","- If your projects involve multiple stages of the LLMOps lifecycle and you require categorized resources to streamline different phases.","- For accessing detailed lists covering specific areas such as model serving frameworks, security measures for LLMs, and data storage solutions."],"when_not_to_use":["- When you are looking for a hands-on platform or framework for developing and deploying models rather than just a resource list.","- If your focus is on general artificial intelligence development that includes areas beyond LLMOps like image processing, robotics, or federated learning without the need for LLM-specific resources."],"source":"enrich:decision_facts","observed_at":"2026-07-11T02:26:54.343Z"},"constraint_facets":null,"decision_summary":[{"label":"Adopt for","value":"Awesome-LLMOps is a curated list tailored for developers working with Large Language Models (LLMs), providing resources for model training, serving, evaluation, deployment, and more."}]}}