discover · compare · collections · requirements · contribute · feed · watching · stats · help with your tokens
bentoml/BentoML
The easiest way to serve AI apps and models - Build Model Inference APIs, Job queues, LLM apps, Multi-model pipelines, and more!
History and source changes · Reports and owner responses · Compare
Similar
- liguodongiot/llm-action
本项目旨在分享大模型相关技术原理以及实战经验（大模型工程化、大模型应用落地）
Why this match
topics llm, llm-inference, llm-serving; language differs: Python → HTML
- tensorzero/tensorzero
TensorZero is an open-source LLMOps platform that unifies an LLM gateway, observability, evaluation, optimization, and experimentation.
Why this match
topics deep-learning, generative-ai, llm; language differs: Python → Rust
- jina-ai/serve
☁️ Build multimodal AI applications with cloud-native stack
Why this match
topics deep-learning, generative-ai, llmops
- amitness/learning
A log of things I'm learning
Why this match
topics deep-learning, generative-ai, machine-learning; license differs: Apache-2.0 → MIT
- zenml-io/mcp-zenml
MCP server to connect an MCP client (Cursor, Claude Desktop etc) with your ZenML MLOps and LLMOps pipelines
Why this match
topics llmops, mlops; license differs: Apache-2.0 → MIT
- evidentlyai/evidently
Evidently is an open-source ML and LLM observability framework. Evaluate, test, and monitor any AI-powered system or data pipeline. From tabular data to Gen AI. 100+ metrics.
Why this match
topics generative-ai, llm, llmops; language differs: Python → Jupyter Notebook
- ray-project/ray
Ray is an AI compute engine. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.
Why this match
topics deep-learning, llm, llm-inference
- bentoml/OpenLLM
Run any open-source LLMs, such as DeepSeek and Llama, as OpenAI compatible API endpoint in the cloud.
Why this match
topics llm, llm-inference, llm-serving