A Python library for extracting structured information from unstructured text using LLMs with precise source grounding and interactive visualization.
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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
Structured Outputs
- generative-ai
- llms
- prompt-engineering
- symbolic-ai
structured outputs for llms
- openai
- python
- pydantic-v2
- openai-functions
an ambient intelligence library
Repair malformed JSON from LLMs, APIs, logs, and user input in Python.
The Ruby AI framework.
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
Unified LLM API, structured data outputs with LLMs, and agent SDK - in PHP
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.
Structured outputs, vectorization and tool calling for your Ash application
The production agent framework for Go — type-safe agents, structured output, multi-provider streaming, guardrails, and multi-agent orchestration with zero core dependencies.