#go #agent #agentic #ai #chatbot #chatbots #embeddings #evaluation #generative_ai #golang #knowledge_base #llm #multi_tenant #multimodel #ollama #openai #question_answering #rag #reranking #semantic_search #vector_search

WeKnora is a powerful tool that helps you understand and find answers in complex documents like PDFs and Word files. It uses advanced AI to read documents, understand what they mean, and answer your questions in a simple way. This tool is useful for businesses and researchers because it can quickly find information from many documents, making it easier to manage knowledge and make decisions. It also supports multiple languages and can be used privately, ensuring your data stays safe.

https://github.com/Tencent/WeKnora

#python #blocknotejs #collaborative #django #documentation #g2g #government #knowledge #knowledge_base #mit #mit_license #opensource #reactjs #realtime_collaboration #self_hosted #wiki #yjs

Docs is a collaborative online text editor that helps you and your team write, edit, and organize documents together in real time, even offline. It offers easy formatting, AI tools like summarizing and rephrasing, and secure sharing with controlled access. You can export documents in various formats and create structured knowledge with subpages. Docs is open source, easy to self-host, and used by public organizations, ensuring your data stays secure and private. This tool saves time, improves teamwork, and turns your notes into organized knowledge you can access anytime. It’s great for teams wanting efficient, secure, and collaborative document editing.

https://github.com/suitenumerique/docs

#rust #ai #change_data_capture #context_engineering #data #data_engineering #data_indexing #data_infrastructure #data_processing #etl #hacktoberfest #help_wanted #indexing #knowledge_graph #llm #pipeline #python #rag #real_time #rust #semantic_search

**CocoIndex** is a fast, open-source Python tool (Rust core) for transforming data into AI formats like vector indexes or knowledge graphs. Define simple data flows in ~100 lines of code using plug-and-play blocks for sources, embeddings, and targets—install via `pip install cocoindex`, add Postgres, and run. It auto-syncs fresh data with minimal recompute on changes, tracking lineage. **You save time building scalable RAG/semantic search pipelines effortlessly, avoiding complex ETL and stale data issues for production-ready AI apps.**

https://github.com/cocoindex-io/cocoindex

#python #agent_memory #financial_forecasting #future_prediction #knowledge_graph #llms #multi_agent_simulation #public_opinion_analysis #python3 #social_prediction #swarm_intelligence

MiroFish is a simple AI tool that predicts anything by creating a digital world from your data like news, policies, or stories. Upload seed info and describe what you want to predict; it builds thousands of smart agents with personalities and memories to interact, simulate futures, and give you a detailed report plus chat access. You benefit by testing decisions risk-free—like policy impacts or story endings—making smart choices or fun ideas win through safe, accurate previews.

https://github.com/666ghj/MiroFish

#typescript #antigravity_skills #business_knowledge #claude_code #claude_skills #codebase_analysis #codex #codex_skills #developer_tools_ai_agent #gemini_cli_skills #karpathy_llm_wiki #knowledge_base #knowledge_graph #memory #opencode_skills #pi_agent #understandcode #vibe_coding

Understand Anything turns a codebase or docs into an interactive knowledge graph you can search, explore, and ask questions about. It works with tools like Claude Code, Codex, Cursor, Copilot, and Gemini CLI. You can see files, functions, classes, and dependencies in one place, get plain-English explanations, and find what changes affect before you commit. This helps you learn large projects faster, understand how pieces fit together, and save time when onboarding or reviewing code.

https://github.com/Lum1104/Understand-Anything

#c_lang #aider #ast #claude_code #code_analysis #code_intelligence #codex #cursor #cypher #developer_tools #gemini_cli #graph_visualization #kilocode #knowledge_graph #mcp #mcp_server #model_context_protocol #opencode #sqlite #tree_sitter #windsurf

This is a fast, local code tool that builds a smart map of a codebase, so you can find functions, calls, routes, and dependencies in seconds instead of reading files one by one. It works on macOS, Linux, and Windows, supports many languages, and helps you understand changes, reduce wasted tokens, and save time while coding.

https://github.com/DeusData/codebase-memory-mcp

#python #ai #ai_agents #cli #hypergraph #information_extraction #knowledge #knowledge_graph #llm #python #rag

Hyper-Extract is a tool that uses AI to turn messy documents into clean, structured knowledge like lists, graphs, and linked data with one command. It gives you fast search, easy visual reports, and ready-made templates, so you can save time, understand information faster, and keep adding new documents without rebuilding everything.

https://github.com/yifanfeng97/Hyper-Extract

#python #antigravity #claude_code #codex #gemini #graphrag #knowledge_graph #leiden #openclaw #rag #skills #tree_sitter

Graphify is an AI tool that maps your entire project—code, docs, PDFs, images, and videos—into a searchable knowledge graph instead of forcing you to grep through files. You simply type `/graphify .` in your AI coding assistant (like Cursor, Claude, or Copilot) to get three outputs: an interactive HTML map, a report with key concepts and surprising connections, and a JSON file for instant queries. The main benefit to you is that you can instantly ask complex questions like "what connects auth to the database?" and get precise answers from the graph, saving hours of manual file searching and helping you understand your project's architecture faster.

https://github.com/safishamsi/graphify

#python #ai_coding #claude #claude_code #code_review #graphrag #incremental #knowledge_graph #llm #mcp #python #static_analysis #tree_sitter

code-review-graph is a free, local-first tool that builds a structural map of your code to stop AI assistants from re-reading your entire codebase, saving you significant money and time. By using Tree-sitter to parse your code into a graph and tracking changes incrementally, it identifies the exact "blast radius" of a change so your AI only reads the few files that actually matter. This reduces token usage by an average of 82x (up to 528x in best cases), cutting costs and making AI reviews feasible for massive projects like monorepos.

https://github.com/tirth8205/code-review-graph

#python #agent_memory #ai #ai_governance #ai_infrastructure #artificial_intelligence #context_engineering #context_graphs #data_engineering #decision_intelligence #developer_tools #explainable_ai #generative_ai #graph_rag #knowledge_graph #llm #ontology #provenance #python #reasoning #semantic_search

Semantica is an open-source tool that turns messy data into clear, connected knowledge graphs for AI. It helps you track where facts came from, explain AI decisions, find conflicts, and keep systems auditable and trustworthy. This benefits you by making AI easier to trust, easier to check, and safer to use in important work like finance, healthcare, legal, and government.

https://github.com/semantica-agi/semantica

#python #ai #ast #claude_code #code_analysis #code_understanding #codebase_search #developer_tools #graph_database #knowledge_graph #llm #mcp #mcp_server #memgraph #monorepo #multi_language #python #rag #retrieval_augmented_generation #semantic_search #tree_sitter

Code-Graph-RAG is an open-source tool that reads a codebase, builds a graph of functions, classes, modules, and links, and lets you ask questions, find code, edit safely, and improve code in plain English. It supports many languages and can run as an MCP server for direct use with AI tools. Benefit: you can understand and change large mixed-language projects faster, with less manual searching and fewer mistakes.

https://github.com/vitali87/code-graph-rag