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RAG Web UI is an intelligent dialogue system based on RAG (Retrieval-Augmented Generation) technology.

Open-source deep-learning framework for building, training, and fine-tuning deep learning models using state-of-the-art Physics-ML methods

Open-source tools for prompt testing and experimentation, with support for both LLMs (e.g. OpenAI, LLaMA) and vector databases (e.g. Chroma, Weaviate, LanceDB).

An open-source visual programming environment for battle-testing prompts to LLMs.

🦜💬 Web app for interacting with any LangGraph agent (PY & TS) via a chat interface.

A framework for prompt tuning using Intent-based Prompt Calibration

Distributed LLM inference. Connect home devices into a powerful cluster to accelerate LLM inference. More devices means faster inference.

RamaLama is an open-source developer tool that simplifies the local serving of AI models from any source and facilitates their use for inference in production, all through the familiar language of containers.

Deepnote is a drop-in replacement for Jupyter with an AI-first design, sleek UI, new blocks, and native data integrations. Use Python, R, and SQL locally in your favorite IDE, then scale to Deepnote cloud for real-time collaboration, Deepnote agent, and deployable data apps. https://deepnote.com/

Elegant easy-to-use neural networks + scientific computing in JAX. https://docs.kidger.site/equinox/

PyTorch native quantization and sparsity for training and inference

Data manipulation and transformation for audio signal processing, powered by PyTorch

llama.cpp fork with additional SOTA quants and improved performance

Infinity is a high-throughput, low-latency serving engine for text-embeddings, reranking models, clip, clap and colpali

Holistic Evaluation of Language Models (HELM) is an open source Python framework created by the Center for Research on Foundation Models (CRFM) at Stanford for holistic, reproducible and transparent evaluation of foundation models, including large language models (LLMs) and multimodal models.

The hub for EleutherAI's work on interpretability and learning dynamics

Stateful agents that are like people, with memory, identity, and the ability to learn and adapt

A training framework for Stable Baselines3 reinforcement learning agents, with hyperparameter optimization and pre-trained agents included.

A comprehensive set of fairness metrics for datasets and machine learning models, explanations for these metrics, and algorithms to mitigate bias in datasets and models.

The pretty much "official" DSPy framework for Typescript

Ruler — apply the same rules to all coding agents

pingcap/autoflow is a Graph RAG based and conversational knowledge base tool built with TiDB Serverless Vector Storage. Demo: https://tidb.ai

PentestAgent is an AI agent framework for black-box security testing, supporting bug bounty, red-team, and penetration testing workflows.

A library for debugging/inspecting machine learning classifiers and explaining their predictions

Minimalistic large language model 3D-parallelism training

Probabilistic programming with NumPy powered by JAX for autograd and JIT compilation to GPU/TPU/CPU.

Kubernetes-native Job Queueing

The code used to train and run inference with the ColVision models, e.g. ColPali, ColQwen2, and ColSmol.

nanoflann: a C++11 header-only library for Nearest Neighbor (NN) search with KD-trees

Open source platform for AI Engineering: OpenTelemetry-native LLM Observability, GPU Monitoring, Guardrails, Evaluations, Prompt Management, Vault, Playground. 🚀💻 Integrates with 50+ LLM Providers, VectorDBs, Agent Frameworks and GPUs.