Reverse Dependencies of vllm

The following projects have a declared dependency on vllm:

• achatbot — An open source chat bot for voice (and multimodal) assistants
• ai-researcher — AI-powered research paper generation and review
• airoboros — Updated and improved implementation of the self-instruct system.
• aitutor-assessmentkit — AITutor-AssessmentKit is the first open-source toolkit designed to evaluate the pedagogical performance of AI tutors in student mistake remediation tasks. With the growing capabilities of large language models (LLMs), this library provides a systematic approach to assess their teaching potential across multiple dimensions in educational dialogues.
• alexandrainst_ragger — A repository for general-purpose RAG applications.
• alpaca-eval — AlpacaEval : An Automatic Evaluator of Instruction-following Models
• arctic-training — Snowflake LLM training library
• ares-ai — ARES is an advanced evaluation framework for Retrieval-Augmented Generation (RAG) systems,
• async-chat-engine — An asynchronous chat engine using vLLM with a async producer-consumer pattern.
• auralis — This is a faster implementation for TTS models, to be used in highly async environment
• autobiasdetector — tools for detecting bias patterns of LLMs
• bentoml-unsloth — BentoML: The easiest way to serve AI apps and models
• bespokelabs-curator — Bespoke Labs Curator
• bigcodebench — "Evaluation package for BigCodeBench"
• bisheng-pybackend-libs — libraries for bisheng rt pybackend
• bl-vanna — Generate SQL queries from natural language
• bonito-llm — A lightweight library for generating synthetic instruction tuning datasets for your data without GPT.
• caai-vllm-tools — A tool that allows you to use the OpenAI API with vLLM generate function
• chatbot-kernel — A Jupyter kernel using LLM models from Huggingface
• ck-vanna — Generate SQL queries from natural language
• claim-processor — Claim Processor provides automatic checking pipeline for detecting fine-grained hallucinations generated by Large Language Models.
• clemcore — The cLLM (chat-optimized Large Language Model, 'clem') framework tests such models' ability to engage in games, that is, rule-constituted activities played using language.
• codemmlu — CodeMMLU Evaluator: A framework for evaluating language models on CodeMMLU benchmark.
• dbgpt-acc-auto — Add your description here
• dblcsgen — DBLC Fast Structured Generation
• decoding — Composable inference algorithms with LLMs and programmable logic
• deepseek-coder — Deepseek Coder running locally in the terminal.
• dev-laiser — LAiSER (Leveraging Artificial Intelligence for Skill Extraction & Research) is a tool designed to help learners, educators, and employers extract and share trusted information about skills. It uses a fine-tuned language model to extract raw skill keywords from text, then aligns them with a predefined taxonomy. You can find more technical details in the project’s paper.md and an overview in the README.md.
• DiLLeMa — This repository contains a docker-compose file that can be used to run a Ray cluster on a single machine
• distilabel — Distilabel is an AI Feedback (AIF) framework for building datasets with and for LLMs.
• easyvllm — Easy to use lightweight vllm tool with special support for Large Reasoning Model (LRM).
• enova — enova
• enova-instrumentation-llmo — llmo instrumentation for OpenTelemetry
• EuroEval — The robust European language model benchmark.
• evalplus — "EvalPlus for rigourous evaluation of LLM-synthesized code"
• expert-score — The implementation of the ExPerT score.
• factory-sdk — factory SDK
• faster-translate — A high-performance translation library using CTTranslate2 and vLLM.
• flashrag-dev — A library for efficient Retrieval-Augmented Generation research
• flexeval — no summary
• flexrag — A RAG Framework for Information Retrieval and Generation.
• flow-judge — A small yet powerful LM Judge
• fm-optimized-inference — no summary
• fmbench — Benchmark performance of **any Foundation Model (FM)** deployed on **any AWS Generative AI service**, be it **Amazon SageMaker**, **Amazon Bedrock**, **Amazon EKS**, or **Amazon EC2**. The FMs could be deployed on these platforms either directly through `FMbench`, or, if they are already deployed then also they could be benchmarked through the **Bring your own endpoint** mode supported by `FMBench`.
• formatron — Formatron empowers everyone to control the output format of language models with minimal overhead.
• formless — Handwritten + image OCR.
• ftts — 语音合成推理引擎
• galadriel-node — no summary
• geniusrise-text — Text bolts for geniusrise
• genlm-backend — no summary
• genomeocean — A Python library for GenomeOcean inference and fine-tuning.
• gptdb — GPT-DB is an experimental open-source project that uses localized GPT large models to interact with your data and environment. With this solution, you can be assured that there is no risk of data leakage, and your data is 100% private and secure.
• gpustack — GPUStack
• greaterprompt — A Gradient-based Prompt Optimizer for Text Generation
• halitefn — Acceleration framework for Human Alignment Learning
• happy-vllm — happy_vllm is a REST API for vLLM, production ready
• heliumos.bixi — An open platform for load large language model.
• heliumos-bixi-completions — An open platform for load large language model.
• hermitd — llm-powered shell assistant daemon
• hipporag — A powerful graph-based RAG framework that enables LLMs to identify and leverage connections within new knowledge for improved retrieval.
• hypogenic — A package for generating and evaluating hypotheses.
• imitater — no summary
• jailbreakbench — An Open Robustness Benchmark for Jailbreaking Language Models
• kani-ext-vllm — vLLM backend for kani
• lagent — A lightweight framework for building LLM-based agents
• laiser — LAiSER (Leveraging Artificial Intelligence for Skill Extraction & Research) is a tool designed to help learners, educators, and employers extract and share trusted information about skills. It uses a fine-tuned language model to extract raw skill keywords from text, then aligns them with a predefined taxonomy. You can find more technical details in the project’s paper.md and an overview in the README.md.
• langcheck — Simple, Pythonic building blocks to evaluate LLM-based applications
• lazyllm — A Low-code Development Tool For Building Multi-agent LLMs Applications.
• lazyllm-beta — A Low-code Development Tool For Building Multi-agent LLMs Applications.
• lazyllm-llamafactory — Easy-to-use LLM fine-tuning framework
• lighteval — A lightweight and configurable evaluation package
• lita — LLM Integrated Testing & Analysis
• llama-cookbook — Llama-cookbook is a companion project to the Llama models. It's goal is to provide examples to quickly get started with fine-tuning for domain adaptation and how to run inference for the fine-tuned models.
• llama-recipes — This is a compatibility package to keep projects build on llama-recipes compatible with the new name llama-cookbook. If you're updating your project or starting a new one please use llama-cookbook package
• llamafactory — Unified Efficient Fine-Tuning of 100+ LLMs
• llamafactory-songlab — Easy-to-use LLM fine-tuning framework
• llamp — LLAMP - Large Language Model for Planning
• llm-engines — A unified inference engine for large language models (LLMs) including open-source models (VLLM, SGLang, Together) and commercial models (OpenAI, Mistral, Claude).
• llm-optimized-inference — no summary
• llm-serve — An LLM inference solution to quickly deploy productive LLM service
• llmesh — HPE LLM Agentic Tool Mesh Platform is an innovative platform designed to streamline and enhance the use of AI in various applications. It serves as a central hub to orchestrate 'Intelligent Plugins,' optimizing AI interactions and processes.
• llmformat — Format LLM language by using LALR(1) grammar. Supports JSON, XML, etc.
• llmlite — A library helps to chat with all kinds of LLMs consistently.
• llmsanitize — LLMSanitize: a package to detect contamination in LLMs
• llmtuner — Easy-to-use LLM fine-tuning framework
• llumnix — Efficient and easy multi-instance LLM serving
• lm-eval — A framework for evaluating language models
• lmcache-vllm — lmcache_vllm: LMCache's wrapper for vllm
• logits-processor-zoo — A collection of LogitsProcessors to customize and enhance LLM behavior for specific tasks.
• markdrop — A comprehensive PDF processing toolkit that converts PDFs to markdown with advanced AI-powered features for image and table analysis. Supports local files and URLs, preserves document structure, extracts high-quality images, detects tables using advanced ML models, and generates detailed content descriptions using multiple LLM providers including OpenAI and Google's Gemini.
• mergekit — Tools for merging pre-trained large language models
• mergekitty — Tools for merging pre-trained large language models
• mgpu — no summary
• mirage-bench — A RAG-based benchmark for multilingual question answering.
• mostlyai-engine — Synthetic Data Engine
• mw-python-sdk — ModelWhale Python SDK
• nearai — Near AI CLI
• nextai-star — An open platform for training, serving, and evaluating large language model based chatbots by next ai
• nomiracl — Multilingual Relevance Assessment for RAG Applications
• nvidia-lm-eval — A framework for evaluating language models - packaged by NVIDIA