Stars
MCP server to provide Figma layout information to AI coding agents like Cursor
The Web Data API for AI - Turn entire websites into LLM-ready markdown or structured data 🔥
SWE-bench: Can Language Models Resolve Real-world Github Issues?
AI powered one-click comprehensive docs from transcripts and text.
A lightweight, low-dependency, unified API to use all common reranking and cross-encoder models.
Superfast AI decision making and intelligent processing of multi-modal data.
Supercharge Your LLM Application Evaluations 🚀
Convert PDF to markdown + JSON quickly with high accuracy
SGLang is a fast serving framework for large language models and vision language models.
Easily use and train state of the art late-interaction retrieval methods (ColBERT) in any RAG pipeline. Designed for modularity and ease-of-use, backed by research.
Structured data extraction and instruction calling with ML, LLM and Vision LLM
A blazing fast AI Gateway with integrated guardrails. Route to 200+ LLMs, 50+ AI Guardrails with 1 fast & friendly API.
An open-source framework for detecting, redacting, masking, and anonymizing sensitive data (PII) across text, images, and structured data. Supports NLP, pattern matching, and customizable pipelines.
Superduper: End-to-end framework for building custom AI applications and agents.
Natural language search for complex JSON arrays, with AI Quickstart.
Run any open-source LLMs, such as DeepSeek and Llama, as OpenAI compatible API endpoint in the cloud.
Enforce the output format (JSON Schema, Regex etc) of a language model
DSPy: The framework for programming—not prompting—language models
Customizable implementation of the self-instruct paper.
Browser extension that generates API specs for any app or website
A language for constraint-guided and efficient LLM programming.
A guidance language for controlling large language models.
Python SDK, Proxy Server (LLM Gateway) to call 100+ LLM APIs in OpenAI format - [Bedrock, Azure, OpenAI, VertexAI, Cohere, Anthropic, Sagemaker, HuggingFace, Replicate, Groq]
Sparsity-aware deep learning inference runtime for CPUs