Compress tool outputs, logs, files, and RAG chunks before they reach the LLM. 20% fewer tokens for coding agents, 60-95% fewer tokens for JSON, same answers. Library, proxy, MCP server.
Repository Index
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Structured Outputs
- generative-ai
- llms
- prompt-engineering
- symbolic-ai
structured outputs for llms
- openai
- python
- pydantic-v2
- openai-functions
The Ruby AI framework.
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
Integrate ChatGPT-style LLMs into Neovim: ask questions, keep multi-file context, pull diagnostics / command output, and chat without leaving your editor. Highly configurable, async, lua-only plugin.
PDF extraction that audits its own output — and certifies any other extractor's, catching pages they silently dropped. Verify signed manifests offline: free, MIT, no account. 0.903 on opendataloader-bench, #2 of 8 engines. 7-tool MCP server.
A Go toolkit for building AI agents and applications across multiple providers. Unified LLM client, agent framework with handoffs, tool calling, streaming, structured output, MCP integration, and cost tracking.
- ai
- golang
- llm
- structured-output
The production agent framework for Go — type-safe agents, structured output, multi-provider streaming, guardrails, and multi-agent orchestration with zero core dependencies.
Prompt-injection firewall for LLM applications — 33 input detectors, 9 output scanners, federated ed25519-signed threat-intel feed. Apache 2.0, 1040 tests, F1 96.0% with 0% false positives. Docker, GitHub Action, LangChain/LlamaIndex/CrewAI integrations.
- agentic-ai
- ai-safety
- fastapi
- langchain