ToolAI.io · GitHub চ্যানেল
GitHub-এ সম্প্রতি যোগ করা ওপেন-সোর্স AI প্রকল্প আবিষ্কার করুন—রিপোজিটরির তথ্য, সেটআপ নোট, লাইসেন্স ও সংশ্লিষ্ট রিসোর্সসহ।
পাবলিক রিপোজিটরির তথ্য
genkit-ai/genkit
Genkit is an open-source framework built and used in production by Google's Firebase for developing full-stack, AI-powered applications. It provides cross-language SDKs and unified APIs for integrating various AI models to build chatbots, automations, and recommendation systems.
lancedb/lancedb
An open-source, developer-friendly embedded retrieval library and multimodal AI lakehouse designed for fast, scalable, and production-ready vector search, built on the Lance columnar format.
dataelement/bisheng
BISHENG is an open-source LLM application DevOps platform designed for next-generation enterprise AI applications, offering comprehensive features like GenAI workflow orchestration, RAG, Agent management, and enterprise-grade system controls.
langchain4j/langchain4j
An idiomatic, open-source Java library for building LLM-powered applications on the JVM, offering a unified API over popular LLM providers and vector stores with support for tool calling, MCP, agents, and RAG.
promptfoo/promptfoo
An open-source CLI and library for evaluating, testing, and red-teaming LLM applications, RAGs, and agents. It enables side-by-side model comparison and vulnerability scanning with declarative configs and CI/CD integration.
volcengine/openviking
OpenViking is an open-source context database that unifies agent memory, knowledge RAG, and skills into a single virtual filesystem, enabling AI agents to browse and retrieve context deterministically using a file-system-like protocol.
getzep/graphiti
Graphiti is an open-source Python framework by Zep for building and querying temporal context graphs. It autonomously transforms structured and unstructured data into a dynamic knowledge graph that tracks fact validity over time, preserving provenance and enabling hybrid retrieval for AI agents.
hkuds/lightrag
A lightweight, graph-based retrieval-augmented generation (RAG) framework that uses a dual-layer architecture combining knowledge graphs and vector embeddings to deliver efficient indexing, low-cost incremental updates, and high-quality contextual retrieval.
run-llama/llama_index
LlamaIndex is an open-source Python data framework for building LLM applications with private data, offering data connectors, indexing structures, and advanced retrieval interfaces. It is complemented by LlamaParse, an enterprise platform for agentic OCR, parsing, extraction, and indexing.
headroomlabs-ai/headroom
Headroom is a local-first context compression layer that reduces token usage for AI agents by compressing tool outputs, logs, files, and RAG chunks before they reach the LLM. It offers library, proxy, and MCP server modes and claims to preserve answer accuracy while cutting tokens by 15-95% depending on workload.
graphify-labs/graphify
Graphify is a local-first CLI tool and AI assistant skill that parses codebases, docs, SQL schemas, and PDFs into a queryable knowledge graph using deterministic AST parsing, eliminating the need for vector stores or embeddings.
vectifyai/pageindex
PageIndex is a Python project for creating hierarchical document indexes and performing reasoning-based retrieval without a vector database or artificial chunking. It supports self-hosted processing of PDF and Markdown documents, with optional agentic RAG examples and hosted MCP/API services.
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