How Python does AI. Agents, realtime voice, image generation, embeddings. Every model, every interface, typed end to end.
- agent-framework
- pydantic
- python
- genai
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How Python does AI. Agents, realtime voice, image generation, embeddings. Every model, every interface, typed end to end.
The Generative UI framework
Structured Outputs
structured outputs for llms
An Application Framework for AI Engineering
Adding guardrails to large language models.
Open-source framework for building agentic apps in JavaScript, Go, Dart, and Python, built and used in production by Google
an ambient intelligence library
Semantic ifs from open models, on a 3090 at home. Independent; not affiliated with Jev or TypeSafe.
A Bulletproof Way to Generate Structured JSON from Language Models
Prompt Engineering | Prompt Versioning | Use GPT or other prompt based models to get structured output. Join our discord for Prompt-Engineering, LLMs and other latest research
The Ruby AI framework.
A language for constraint-guided and efficient LLM programming.
🤖 Type-safe, provider-agnostic TypeScript AI SDK for streaming chat, tool calling, agents, and multimodal apps across OpenAI, Anthropic, Gemini, React, Vue, Svelte, and Solid.
The pretty much "official" DSPy framework for Typescript
Seamlessly integrate LLMs as Python functions
🤖Self-Modifying Framework from the Future 🔮 World's First AMS
Instant, controllable, local pre-trained AI models in Rust
Run a 1-billion parameter LLM on a $10 board with 256MB RAM
Run AI models locally on your machine with node.js bindings for llama.cpp. Enforce a JSON schema on the model output on the generation level
Extract structured data and insights from documents using LLMs and decision models
AICI: Prompts as (Wasm) Programs
Enforce the output format (JSON Schema, Regex etc) of a language model
Fast, Flexible and Portable Structured Generation