Latitude is an open-source observability tool for AI agents. It helps identify failures, dispatch coding agents to fix issues, and verify fixes using real traces. The platform is available on GitHub.
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layer is a command-line tool for neural network inference, following the Unix philosophy. It enables users to perform inference from the command line. The project is open-source and hosted on GitHub.
libonnx is a lightweight, portable pure C99 ONNX inference engine for embedded devices with hardware acceleration support. Its .c and .h files can be dropped into a project and compiled with it. Models are loaded from a file into a context, and inference runs on input tensors via onnx_run. It is based on ONNX version v1.17.0 with opset 24 support, and some operators are not implemented.
The Libra Toolkit is a collection of algorithms for learning and inference with discrete probabilistic models, including Bayesian networks, Markov networks, dependency networks, sum-product networks and arithmetic circuits. Each algorithm is implemented as a command-line program with consistent options and file formats, and all methods are written in OCaml.
LiteLLM is an open-source library that provides a single, unified interface to call over 100 LLMs using the OpenAI format. It includes a Python SDK whose completion() function uses the same arguments across providers and returns responses in the OpenAI Chat Completions format, plus a self-hosted gateway with virtual keys, cost tracking and an admin UI.
A hub of integrations for LlamaIndex including data loaders, tools, vector databases, LLMs and more.
LLM App is an open-source project providing ready-to-run cloud templates for retrieval-augmented generation (RAG), AI pipelines and enterprise search with live data. It is Docker-friendly and designed to stay synchronized with data sources including Sharepoint, Google Drive, S3, Kafka, PostgreSQL and real-time data APIs, hosted by pathwaycom on GitHub.
LLMKube is a Kubernetes operator for self-hosted large language model inference across heterogeneous GPU fleets supporting NVIDIA CUDA, AMD Vulkan, and Apple Silicon Metal. It supports runtimes including llama.cpp, vLLM, TGI, and mlx-server, offers multi-GPU sharding, model caching, and OpenAI-compatible endpoints. It is licensed under Apache-2.0 and designed for homelab and on-prem fleet deployment, and is actively developed.
A tool that generates consolidated llms.txt text files from websites for LLM training and inference, powered by Firecrawl. The site states the API is being deprecated in favor of the main endpoints and will no longer be maintained after June 30, 2025, though the endpoint remains active.
Open-source project that provides machine-learning models, research, training resources, or evaluation tools.
Lunary is an observability and prompt management platform for LLM-based applications. It provides chatbot analytics, agent tracing, prompt templates, topic classification, PII masking and feedback tracking. A self-hostable option is offered. The Team cloud plan costs $20 per user per month, billed monthly, and payment is required to activate a workspace.
Mastra is a TypeScript AI framework for building agents and AI applications. It includes built-in memory, tool support, MCP compatibility, and observability features to support development from prototype to production. The framework also offers workflow tools, agent factory functionality, cloud deployment servers, and an agent builder for evaluation and iteration.
Bifrost is an open-source AI gateway for LLMs, MCP and agents, offered by Maxim AI. It provides routing, governance, guardrails and observability, and is described as a drop-in replacement for AI SDKs. Enterprise adds features such as SSO, RBAC, adaptive load balancing, cluster mode and in-VPC deployment, free for 14 days.
A platform for deploying and serving machine learning models.
Metorial is an agentic infrastructure platform for AI-native companies. It provides a single unified platform for employees, AI agents, and AI clients to connect tools and skills, with built-in governance, access control, and tracing capabilities. The platform supports development of customer-facing agents, internal assistants, and scalable AI workforces.
Milvus is open source vector database for production AI, written in Go and C++, scalable and blazing fast for billions of embedding vectors.
MindSpore is an open source deep learning training and inference framework that could be used for mobile, edge, and cloud computing scenarios. Its source code is hosted in the mindspore-ai/mindspore repository on GitHub.
Full-stack AI platform focused on multimodal agents and consumer-scale deployment.
Mirascope is a project labeled the LLM Anti-Framework that provides one unified interface for using frontier LLMs. Its examples show calling LLMs with a decorator, getting structured output via Pydantic models, and building an agent with tools. It is organized as a monorepo with Python and TypeScript implementations plus documentation.
MLEM is an open source tool designed to package, serve, and deploy machine learning models on any platform. The project's primary repository is currently archived, with maintainers noting plans to resurrect it in the future.
MLflow is an open source AI engineering platform for agents, LLMs, and ML models. It provides tools for debugging, evaluating, monitoring, and optimizing AI applications, including tracing, evaluation metrics, prompt management, an AI gateway, and an agent server. The project is released under the Apache 2.0 license.
MLReef is an open source ML-Ops platform for collaborating, reproducing and sharing machine learning work. The repository notes it is no longer supported or updated there, with work continuing on GitLab. Described sections include data management with versioned data hosting, containerized code repositories, experiment tracking and ML pipelines on Kubernetes, cloud or bare metal.
MLRun is an open source MLOps platform for building and managing continuous machine learning applications across their lifecycle. It integrates with development and CI/CD environments to automate the delivery of production data, ML pipelines, and online applications.
Open-source project that supports deploying, serving, monitoring, or operating AI and machine-learning systems.