llm

⚡ Unit tests for AI. Test prompts, compare models, save money.

Deepmark AI enables a unique testing environment for language models (LLM) assessment on task-specific metrics and on your own data so your GenAI-powered solution has predictable and reliable performance.

AI tools curated by autonomous agents for makers and SMBs

🧠 Active memory management system enabling functional infinite context for LLMs through cognitive workspace architecture

Self improving agents through iterations

InsightSolver: Colab notebooks for exploring and solving operational issues using deep learning, machine learning, and related models.

[EMNLP'21] Visual News: Benchmark and Challenges in News Image Captioning

The fastest way to put Volcengine Ark in your terminal and your AI agent — go from prompt to generated media, multimodal answer, or deployed endpoint in a single command, no API glue code.

Real-time hardware and LLM inference monitoring — GPU, CPU, memory, and vLLM metrics streamed to a dashboard.

Local Apple Notes + LLM Chat

This repo accelerates development of RAG applications with rich data sources including SQL Warehouses and documents analysed with Azure Document Intelligence

Deepstory turns a text/generated text into a video where the character is animated to speak your story using his/her voice.

AI-powered universal search for all your personal data, tailored just for you. Goal:The world's first product with "edge-side LLMs + consumer data localization" as its core development direction.

Durable, file-based long-term memory for AI agents. Five-package plugin family: SDK, CLI, MCP server, Hermes adapter, and a LangGraph BaseStore. No vector database, no embeddings.

一个基于 Docker 的 ComfyUI 弹性 Serverless 应用，提供完整的前后端分离架构和用户友好的界面。

📚 Local PDF-Integrated Chat Bot: Secure Conversations and Document Assistance with LLM-Powered Privacy

OpenAI/Anthropic-compatible AI router that keeps apps online with provider failover, key rotation, caching, analytics, and local-model fallback.

Fine-Tuning Dataset Auto-Generation for Graph Query Languages.

🐙 A curated set of Codex and OpenClaw skills for workflow automation, technical debugging, and agent-assisted development patterns.

lm-scratch-pytorch - The code is designed to be beginner-friendly, with a focus on understanding the fundamentals of PyTorch and implementing LLMs from scratch,step by step.