AI Summary

Overview

WeKnora is a powerful, open-source LLM-powered knowledge framework designed to transform raw documents into dynamic, queryable knowledge assets. It seamlessly integrates Retrieval Augmented Generation (RAG), autonomous reasoning agents, and a self-maintaining Wiki, enabling enterprises to unlock the full potential of their data. Go beyond simple Q&A with intelligent agents that can orchestrate complex tasks, access a catalog of skills, and even generate and manage a structured Wiki with version control and knowledge graphs.

Key Features

  • Intelligent RAG & Reasoning: Turn any document collection into a queryable knowledge base for instant answers, or empower autonomous agents to tackle multi-step tasks by orchestrating RAG, tools, and web search.
  • Autonomous Agents with Skill Sandboxes: Deploy agents within persistent Docker, E2B, or Cube sandboxes. Install and manage skills from a catalog, execute shell commands, manage files, and leverage per-tenant network policies for secure, on-demand capabilities.
  • Self-Maintaining Wiki Mode: Automatically distill raw documents into a structured, interlinked Markdown wiki with an interactive knowledge graph. Enjoy features like manual editing, comprehensive revision history with line-level diffs, and one-click rollbacks.
  • Long-Term Memory & Personalization: Agents remember user preferences, past tasks, and learned facts across sessions, providing a highly personalized and context-aware experience.
  • Comprehensive Knowledge Management:
    • Folder Tree Preservation: Uploaded document structures are maintained, allowing for familiar file-system-like navigation.
    • Chunk Editing & Revision History: Directly edit retrieval chunks, review diffs, and rollback changes with full version control.
    • Multi-Source Ingestion: Seamlessly import data from Feishu, GitLab, Notion, Yuque, DingTalk, RSS, and more, supporting over 10 document formats including Office files.
  • Enterprise-Ready Integrations: Extensive LLM provider support (OpenAI, LiteLLM, Ollama, etc.), Langfuse observability, RBAC for multi-workspace management, scoped API keys, and flexible multi-instance storage backends.
  • Self-Hostable & Extensible: A modular architecture ensures complete data sovereignty and allows for easy customization and integration with your existing infrastructure.

Typical Use Cases

  • Enterprise Knowledge Management: Create a central, queryable repository for all internal documentation, policies, and technical manuals, accessible via natural language.
  • Automated Content Curation: Automatically transform long reports, research papers, or articles into structured, searchable Wiki pages with rich interlinking and version history.
  • Intelligent Customer Support: Deploy agents that can access and synthesize information from diverse knowledge sources to provide accurate and context-aware answers to customer queries.
  • Developer Productivity: Enable agents to access code repositories, documentation, and even execute scripts within secure sandboxes to assist with development tasks.
  • Research & Analysis: Quickly extract insights from large datasets and documents, with agents capable of performing multi-step analysis and synthesizing findings.
  • Internal Documentation Wiki: Effortlessly maintain up-to-date internal wikis with automatic generation, version control, and collaborative editing features.

Repository Trajectory

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Contributors

Languages

Vue

16%

Python

2%

JavaScript

1%

Shell

1%

PLpgSQL

1%

Go

65%

TypeScript

13%