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GitHub
AI Agent·2025
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VibeTunnel

amantus-ai, Mario Zechner +4·Amantus Machina

Forwards local terminal sessions to any web browser, so you can watch and steer long-running CLI processes — including AI coding agents like Claude Code — from a phone or another machine. A macOS menu-bar app proxies PTY output over WebSocket.

#vibe-coding#ai-agent#cli#typescript#gitHub+2
GitHub
AI Infra·2025
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Project N.O.M.A.D.

Crosstalk-Solutions

Offline-first knowledge server that bundles local AI chat (Ollama + vector RAG), offline Wikipedia/education/maps, and utility tools behind a Dockerized management UI — designed to keep searchable knowledge available without cloud access.

#docker#RAG#embeddings#ai-tools#llm+3
GitHub
AI Client·2025
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MonkeyCode

chaitin

Browser-based AI development platform that runs tasks inside isolated cloud development environments: natural-language agents read code, run commands, modify files, and integrate results back into Git. Key features include per-task sandboxes, multi-model selection, and an enterprise private-deploy option.

#ai-client#ai-agent#ai-coding#github#LLM+3
GitHub
AI Infra·2025
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LEANN

Yichuan Wang, Zhifei Li +1·Sky Computing Lab, UC Berkeley

Stores a pruned proximity graph instead of all embeddings, recomputing vectors on demand at query time. A 60M-doc index takes 6GB, not 201GB (97% less), at comparable recall. Powers private local RAG over files, mail, chat, and browser history.

#RAG#github#ai-library#ai-tools#ai-development+5
GitHub
AI Infra·2025
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AngelSlim

Tencent Hunyuan AI Infra Team

Model-compression toolkit for large LLMs/VLMs that integrates quantization (FP8/INT4/etc.), speculative decoding, token pruning and deployment hooks—designed for end-to-end performance on single/multi-GPU inference workflows and research-to-prod model optimization.

#huggingface#vllm#transformers#ai-inference#ai-deploy+6
GitHub
AI Infra·2025
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OpenRAG

langflow-ai·Langflow

Bundles Langflow, Docling, and OpenSearch into one installable package so you can ingest messy documents, run agentic retrieval with re-ranking, and chat over your own knowledge base. Ships Python/TS SDKs and a built-in MCP server at /mcp.

#RAG#ai-workflow#mcp-server#python#typescript+5
GitHub
AI Infra·2025
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WeKnora

Tencent

Turns enterprise documents into RAG Q&A, autonomous reasoning agents, and self-maintaining wiki pages, with multi-source ingestion, RBAC, observability, and self-hosted deployment.

#chatbot#llm#RAG#ai-tools#ai-development+3
GitHub
AI Infra·2025
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Memori

Memori Labs·MemoriLabs

An open-source memory layer that turns agent runs and conversations into structured, persistent state recallable across sessions. Captures facts, events, preferences, and relationships automatically; LLM-agnostic with SDK and MCP integration.

#RAG#embeddings#ai-agent#python#typescript+4
GitHub
AI Agent·2025
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memU

NevaMind-AI·NevaMind AI

Compiles an agent's raw chat logs, documents, and tool traces into three persistent layers — index, learned skills, and user memory — so context survives sessions. Claims 92% Locomo-benchmark accuracy and up to 95% lower token cost than replaying history.

#ai-agent#agent-skills#embeddings#RAG#python+2
GitHub
AI Infra·2025
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InsForge

InsForge

Lets AI coding agents provision and operate a full backend themselves — Postgres with pgvector, OAuth2 auth, S3-style storage, Deno edge functions, and hosting — through one interface, plus an OpenAI-compatible model gateway.

#mcp-server#ai-coding#ai-development#postgres#ai-api-management+3
GitHub
MCP Server·2025
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FFF

dmtrKovalenko

Provides a long‑lived, in‑process file and content search library for editors and AI agents, with typo‑resistant fuzzy matching, frecency‑ranked results, background watchers, and a lightweight in‑memory content index — optimized for repeated searches in long‑running processes.

#mcp#mcp-server#nodejs#rust#plugin+5
GitHub
AI Deploy·2025
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Mini-SGLang

sgl-project·LMSYS Org

A ~5,000-line Python LLM inference engine that re-implements SGLang's serving optimizations — radix KV-cache reuse, chunked prefill, overlap scheduling, tensor parallelism — as a fully type-annotated reference instead of a black box.

#ai-inference#ai-serving#llm#python#docker+5
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