<p align="center"> <picture> <img src="./docs/images/logo.png" alt="WeKnora Logo" height="120"/> </picture> </p> <p align="center"> <picture> <a href="https://trendshift.io/repositories/15289" target="_blank"> <img src="https://trendshift.io/api/badge/repositories/15289" alt="Tencent%2FWeKnora | Trendshift" style="width: 250px; height: 55px;" width="250" height="55"/> </a> </picture> </p> <p align="center"> <a href="https://weknora.weixin.qq.com" target="_blank"> <img alt="Official Website" src="https://img.shields.io/badge/Official Website-WeKnora-4e6b99"> </a> <a href="https://chatbot.weixin.qq.com" target="_blank"> <img alt="WeChat Dialog Open Platform" src="https://img.shields.io/badge/WeChat Dialog Open Platform-5ac725"> </a> <a href="https://chromewebstore.google.com/detail/jpemjbopikggjlmikmclgbmkhhopjdgd" target="_blank"> <img alt="Chrome Extension" src="https://img.shields.io/badge/Chrome Extension-WeKnora-4285F4"> </a> <a href="https://clawhub.ai/lyingbug/weknora" target="_blank"> <img alt="ClawHub Skill" src="https://img.shields.io/badge/ClawHub Skill-WeKnora-ff6b35"> </a> <a href="https://github.com/Tencent/WeKnora/blob/main/LICENSE"> <img src="https://img.shields.io/badge/License-MIT-ffffff?labelColor=d4eaf7&color=2e6cc4" alt="License"> </a> <a href="./CHANGELOG.md"> <img alt="Version" src="https://img.shields.io/badge/version-0.7.2-2e6cc4?labelColor=d4eaf7"> </a> </p> <p align="center"> | <b>English</b> | <a href="./README_CN.md"><b>简体中文</b></a> | <a href="./README_JA.md"><b>日本語</b></a> | <a href="./README_KO.md"><b>한국어</b></a> | </p> <p align="center"> <h4 align="center">

Overview • Architecture • Key Features • Getting Started • API Reference • Developer Guide

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💡 WeKnora — Turn Documents into Living Knowledge with RAG, Agents and Auto-Wiki

📌 Overview

WeKnora is an open-source, LLM-powered knowledge framework built for enterprise-grade document understanding, semantic retrieval, and autonomous reasoning.

It is organized around three core capabilities: RAG-based Quick Q&A for everyday lookups, a ReAct Agent that autonomously orchestrates retrieval, MCP tools and web search to handle complex multi-step tasks, and a brand-new Wiki Mode in which agents distill raw documents into a self-maintaining, interlinked markdown knowledge base with an interactive knowledge graph, complete with manual editing, revision history and one-click rollback. Knowledge curation is equally hands-on: a tree-structured folder view preserves the directory layout of uploads, and chunk editing with revision history lets retrieval chunks be edited, diffed and reverted like documents. Combined with multi-source ingestion (Feishu wiki / Feishu Drive / Notion / Yuque / RSS, and growing), website embed widgets for publishing agents to external sites, scoped API keys with a principal model for programmatic integrations, multi-instance storage backends per workspace for flexible data placement, 20+ LLM provider integrations, full Langfuse observability plus a runtime task-queue dashboard with worker-pool governance, enterprise-ready multi-workspace RBAC (4-tier role matrix + per-resource ownership + per-workspace audit log), and a fully self-hostable modular architecture, WeKnora turns scattered documents into a queryable, reasoning-capable, continuously evolving knowledge asset.

The framework supports auto-syncing knowledge from Feishu, Notion, and Yuque (more data sources coming soon), handles 10+ document formats including PDF, Word, images, and Excel, and can serve Q&A directly through IM channels like WeCom, Feishu, Slack, and Telegram. It is compatible with major LLM providers including OpenAI, DeepSeek, Qwen (Alibaba Cloud), Zhipu, Hunyuan, Gemini, MiniMax, NVIDIA, and Ollama. Its fully modular design allows swapping LLMs, vector databases, and storage backends, with support for local and private cloud deployment ensuring complete data sovereignty. WeKnora also integrates with Langfuse for comprehensive observability into agent reasoning, token usage, and pipeline tracing.

✨ Latest Updates

• v0.7.2 — Launched the official product documentation site (VitePress; six sections, ~50 pages covering ~360 API endpoints and ~150 environment variables, with standalone Docker/Nginx deployment, quickstart sample data and a local MCP demo); knowledge base folder tree (upload paths stored as first-class data, browse/rename/re-file documents like a file manager); chunk editing with revision history (edit retrieval chunks in the UI, per-version diff and rollback, automatic reindexing, plus custom document metadata); Wiki page revision history (snapshots + line-level diff + one-click rollback + in-browser manual editing); directly loadable file URLs via resource_urls=public / RESOURCE_URL_MODE (third-party apps render images and files without a second authenticated proxy call); Feishu Drive data source and docx sync through the blocks API; batch document tagging; MCP Server 1.1.x (migrated to the mcp 2.x high-level API, official PyPI package tencent-weknora-mcp, new create_knowledge_from_text and list_shared_knowledge_bases for 29 tools total); AWS S3 default credential chain (IAM Role / IRSA); local HTML upload parsing; QQBot markdown replies; new PR CI checks for app / frontend / docreader / mcp-server. Plus large-scale router and modelcontext refactors, rerank and chunking quality work, and broad stability fixes. See CHANGELOG.md.
• v0.7.1 — New Yunzhijia (云之家) IM integration (WebSocket + image messages + markdown replies); Volcengine rerank provider (with request batching) and Zhipu AI web search provider; platform-scoped API keys for control-plane automation (tenant management, system settings, runtime queues, audit logs); per-KB activity audit trail; FAQ management enhancements (filtering, tagging, export, import tracking); Langfuse OTLP/OTel tracing migration with W3C traceparent propagation; chat header actions with one-click Markdown export and wiki tool results in the references drawer; prompt-cache observability; session channel governance (admin-scoped IM/embed/API sessions); resilient Feishu large-wiki sync; and removal of the legacy Neo4j conversation-memory dependency. Plus broad slug-integrity, SSRF-transport, and state-sync hardening. See CHANGELOG.md.
• v0.7.0 — Fine-grained scoped API keys & principal model (capability-level grants + per-KB restriction + API integration playground); runtime task-queue observability dashboard & worker-pool governance (per-stage pools + per-model concurrency governors + failed-task inspection/retry); multi-instance storage backends (multiple storage instances per workspace, per-KB binding, default instance); session-scoped temporary attachments (async image/doc parsing + combined limits); question & follow-up suggestions; stable resource registry with LLM-context alias compaction; @Skill / @MCP mentions with scoped agent runtime; mid-conversation MCP OAuth; QQBot & Lark (Feishu International) IM integration; Redis TLS; Requesty model provider + Keenable web search; tenantless provisioning & gated self-service workspaces; admin password reset; knowledge base duplicate flow; weknora CLI v0.10. Plus broad security hardening (SSRF, secret redaction, SQL validation, IDOR). See CHANGELOG.md.
• v0.6.3 — Website embed widget & Integrations Center (secure-mode token exchange + rate limits); chat experience overhaul (citation popovers, RAG pipeline progress, streaming markdown); document multi-tag & batch reparse; Wiki folders & hierarchy navigation; RSS data source; MCP OAuth2; EPUB / MHTML parsing; agent model-readiness checks; model test debugger; session source filter; workspace deletion UI. See CHANGELOG.md.
• v0.6.2 — Per-upload process configuration with upload-confirm dialog; document reparse with process_config; weknora CLI v0.9 (bundled Agent Skills, session stop, auth/profile harmonization); KB marquee multi-select; HNSW index for 1024-dim pgvector embeddings; chat resources store refactor; Langfuse-only tracing (Jaeger removed). See CHANGELOG.md.
• v0.6.1 — Document parsing trace timeline (Langfuse-style span tree with stage-by-stage progress + stop-parse); OpenSearch vector store driver; declarative built-in models via YAML; system admin & consolidated platform settings + audit log; new-user onboarding guide; settings UI redesign; weknora CLI v0.7 / v0.8 (agent-first wire contract, NDJSON, --dry-run); OpenDataLoader + PaddleOCR-VL parsers; MCP server multi-transport (stdio / SSE / HTTP); per-model thinking-mode config; Tencent LKEAP rerank + native Gemini embeddings + MiniMax-M3. See CHANGELOG.md.
• v0.6.0 — Workspace RBAC (4-tier role matrix Owner / Admin / Contributor / Viewer + per-KB ownership + per-workspace audit log), workspace member management & multi-workspace UX, self-service workspaces; weknora CLI v0.4 GA with mcp serve; KB retrieval fan-out across vector stores; AES-256-GCM credential encryption + docreader gRPC TLS + Token; Zhipu embedder + Huawei OBS; server-side user preferences; Go 1.26.0. See docs/RBAC说明.md and CHANGELOG.md.
• v0.5.2 — Wiki ingest scales to 40k-document KBs (task queue + DLQ); MCP human-in-the-loop tool approval; Anthropic / Apache Doris / Tencent VectorDB / KS3 / SearXNG backends; adaptive 3-tier chunking with live preview; global ⌘K command palette; Yuque connector + WeChat Mini Program; weknora CLI pr