A Python library for extracting structured information from unstructured text using LLMs with precise source grounding and interactive visualization.
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A guidance language for controlling large language models.
How Python does AI. Agents, realtime voice, image generation, embeddings. Every model, every interface, typed end to end.
- agent-framework
- pydantic
- python
- genai
The Generative UI framework
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
- ai
- genkit
- vector-database
- embedders
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
- chatgpt
- chatgpt-api
- gpt-3
- gpt-3-prompts
The Ruby AI framework.
A language for constraint-guided and efficient LLM programming.
- chatgpt
- huggingface
- language-model
- programming-language
Python package for easily interfacing with chat apps, with robust features and minimal code complexity.
🤖 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
🤖Self-Modifying Framework from the Future 🔮 World's First AMS
Local typed decisions, contrastive data curation, and model evaluation.
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
- ai
- data-extraction
- document-intelligence
- generative-ai
Turn any LLM into a Jev-style decision model: typed decisions, real probabilities, no training. (continue updating, welcome any issue and PR request)
- calibration
- decision-model
- jev
- jev-model
Go AI SDK, the Go way. One unified API across 21+ providers. Streaming, structured output, MCP support, stdlib only. Go AI SDK for AI applications inspired by Vercel AI SDK.
The production agent framework for Go — type-safe agents, structured output, multi-provider streaming, guardrails, and multi-agent orchestration with zero core dependencies.