{"repo":"akashicode/kash","free":true,"listed":false,"github":"https://github.com/akashicode/kash","clone":"git clone https://github.com/akashicode/kash.git","description":"Kash is a Go CLI that turns your raw documents (PDFs, Markdown, text files) into a self-contained AI agent packaged in a lightweight Docker container.","language":"Go","stars":13,"topics":["agent-as-a-service","agentic-ai","agents","knowledge-as-a-service","knowledge-base","ai","ai-agents","graphrag","local-rag","rag"],"license":null,"category":"ai-agents","readme_excerpt":"⚡ Kash Cache your knowledge. Channel the Akashic. Compile your documents into an embedded GraphRAG brain — ship AI agents as Docker images. --- 💡 Why Kash? RAG usually means Python servers, external vector databases, and infrastructure glue. Kash is a compiler instead : it ingests your documents at build time and produces a single self-contained agent that just serves queries at runtime. Typical RAG Stack ⚡ Kash --- --- --- Runtime Python + dependencies Single Go binary Vector DB Hosted service (Pinecone, etc.) Embedded ( chromem-go ) Graph DB Neo4j server Embedded ( cayley ) Deploy Multi-service setup One 50MB container Share an agent \"Clone the repo, install...\" docker run Works with any OpenAI-compatible API — OpenAI, Ollama, LiteLLM, OneAPI. Bring your own model. 🔑 --- ⚡ Quick Start 🎉 Your agent is live at http://localhost:8000 [!IMPORTANT] kash init auto-generates /.kash/config.yaml on first run. Edit it with your API keys (OpenAI, Voyage, etc.) before running kash build . See Configuration. --- 🏗️ How It Works Build time — documents are chunked, embedded into a vector store, and mined for graph triples via LLM. Builds are incremental and resumable. Runtime — the query is rewritten to stand alone, hybrid search finds context, graph traversal follows connected facts one hop, and the whole thing is fed to your LLM with source citations. --- 🔁 Incremental, Versioned Builds kash build tracks every document in data/build.manifest.json — content hash, chunk and triple cou","default_branch":null,"files":null,"tree":[],"storefront":"/r/akashicode","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/akashicode/kash/request-supported","requests":0},"note":"indexed from public GitHub; nothing is for sale on this page. Clone it from GitHub. Paid listings live at /search."}