AI and Agents

Call 100+ LLMs using OpenAI format.

Building applications with LLMs through composability.

A framework that lets you easily use pre-trained transformer models for NLP, vision, and audio tasks.

Low-level orchestration framework for building stateful, long-running LLM agents.

A high-performance serving framework for large language models and multimodal models.

Anthropic's Python SDK for building AI agents on Claude Code's harness — custom tools, in-process MCP servers, hooks.

A library for extracting structured data from LLMs, powered by Pydantic.

OpenAI's framework for building and managing AI agents.

A framework for orchestrating role-playing autonomous AI agents for collaborative task solving.

A library for parameter-efficient fine-tuning of large pretrained models.

A Python agent framework for building generative AI applications with structured schemas.

A library that provides pre-trained diffusion models for generating and editing images, audio, and video.

A general-purpose automatic speech recognition model trained on 680k hours of multilingual and multitask supervised data.

A framework for programming, not prompting, language models.

A data framework for your LLM application.

A high-throughput and memory-efficient inference and serving engine for LLMs.

An intelligent memory layer for AI agents enabling personalized interactions.

Python library and CLI tool for converting text to speech using Google Translate TTS.

A library for faster LLM fine-tuning and training with reduced memory usage.

Run and fine-tune large language models on Apple Silicon with MLX.

A context database for AI agents that unifies memory, resources, and skills.

Industrial-grade speech recognition toolkit with 170x realtime speed, 50+ languages, speaker diarization, and emotion detection.

An adaptive personal AI assistant that grows with you.

A graph-native context and knowledge layer for AI agents with reasoning, provenance, and governance.

A framework for fine-tuning and post-training large language models.

Lightweight ONNX text-to-speech library with small CPU-friendly models.

A family of open-source voice AI models from Microsoft for text-to-speech and long-form speech recognition.

Python-friendly security skills for auditing, testing, and safer backend development.

Python-focused engineering skills for code review, debugging, and backend workflows.

Django backend agent skills for Django, DRF, Celery, and Django-specific code review.