ToolAI.io · Kanal GitHub
Jelajahi direktori lengkap ToolAI yang berisi proyek AI sumber terbuka di GitHub, yang diatur berdasarkan topik, bahasa, dan lisensi.
Data repositori publik
anthropics/claude-cookbooks
Anthropic’s collection of Claude development examples covers classification, summarization, retrieval augmentation, tool use, image understanding, and evaluation. It is suitable for learning from specific tasks and adapting the code.
DietrichGebert/ponytail
Reusable guidance that encourages coding agents to simplify implementations and avoid unnecessary code.
pathwaycom/llm-app
Application templates for RAG, search and AI pipelines using live data sources.
microsoft/graphrag
A graph-based text indexing and question-answering research project, now largely in maintenance mode.
onyx-dot-app/onyx
A self-hostable team AI platform combining knowledge connectors, retrieval, agents, and research workflows.
labring/FastGPT
A visual knowledge-workflow platform with document ingestion, hybrid retrieval, reranking, and application publishing.
stackitcloud/rag-template
A template for building AI chatbots and document management systems using Retrieval-Augmented Generation (RAG), vector search, and FastAPI, designed for deployment on Kubernetes.
infino-ai/infino
Infino is a fast retrieval engine that executes SQL, full-text search, and vector search over a single copy of data stored natively as Parquet on object storage.
xerj-org/xerj
XERJ is a search engine for AI agents that automatically indexes code, documents, logs, and PDFs, enabling agents to query data rather than reading entire files into their context windows. It is Elasticsearch-compatible, allowing existing clients and tooling to work unchanged.
facebookresearch/faiss
A library for efficient similarity search and clustering of dense vectors
QwenLM/Qwen-Agent
Agent framework and applications built upon Qwen>=3.0, featuring Function Calling, MCP, Code Interpreter, RAG, Chrome extension, etc
mtrnix/metronix-memory
Self-hosted memory infrastructure for AI agents featuring MCP-native integration, hybrid RAG, a temporal knowledge graph, and an ontology layer, designed for local-model friendliness and durable, agent-scoped context.
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