Claude-Mem is a persistent memory compression system built for Claude Code. It automatically captures tool usage observations during coding sessions, generates semantic summaries using Claude's agent-sdk, and injects relevant context into future sessions to maintain continuity of project knowledge.
Generates interactive codebase wikis from GitHub, GitLab, or Bitbucket repositories by analyzing structure, writing documentation, and creating diagrams for navigation.
Organizes reusable AI prompts as Markdown 'Patterns' you run from the CLI — summarize a video, extract claims, rate content. Switch among 20+ providers (OpenAI, Claude, Gemini, Ollama) and reach them via CLI, web UI, or REST API.
AI Hedge Fund is a proof-of-concept for an AI-powered hedge fund. It employs multiple AI agents modeled after renowned investors to analyze stocks, perform valuations, sentiment analysis, and generate trading signals. Designed for educational purposes only, it supports CLI and web interfaces, requiring API keys for LLMs and financial data.
Lets AI agents place and answer business phone calls, holding spoken conversations to collect structured data, answer questions, and escalate to humans. Built on Azure Communication Services and Azure OpenAI, with RAG over your own documents.
Python framework for building and serving LLM agents in production: a unified event bus for real-time frontends and human-in-the-loop, fine-grained tool permissions, multi-tenant serving, and tool/code execution sandboxed via Docker or E2B.
Clones a voice from a 5-second sample for zero-shot TTS, or fine-tunes on ~1 minute of audio for few-shot synthesis. Covers Chinese, English, Japanese, Korean, and Cantonese, with a WebUI bundling vocal separation, ASR, and dataset labeling.
Reworks AUTOMATIC1111's Stable Diffusion WebUI onto a custom backend that auto-manages GPU memory to speed inference and cut VRAM use. Adds native FLUX support with NF4/GGUF quantization and a UNetPatcher framework for model-agnostic extensions.
Curates 300+ agentic AI projects, tools, and resources into a categorized, regularly updated list — includes top projects, rising projects, and curated links for building or researching autonomous LLM agents.
Curated developer resources that demonstrate building RAG systems, multi-agent workflows, and memory-augmented AI using Oracle AI Database and OCI — includes end-to-end reference apps, notebooks, guides, and workshops for hands-on prototyping.
Gives developers low-level primitives for building stateful single-agent, multi-agent, and graph-based control flows, with built-in human-in-the-loop checkpoints, persistent cross-session memory, and token-level streaming.
A family of GUI agents that operate phones, desktops, and browsers by perceiving the screen visually rather than reading app code. Ships open GUI-Owl vision-language models (7B/32B) plus a multi-agent framework for planning, reflection, and tool use.