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Ana Sayfaya Dön

Introducing Auto Documentation powered by Codebase Knowledge Graphs With CodeGPT, we traverse your entire repo to build a Knowledge Graph that understands how your software works. Capturing relationships between classes, modules, and dependencies. This allows us to generate robust, accurate documentation that misses no detail. We’re helping top companies... show more

Daniel San

12,421 subscribers

53,329 görüntüleme • 1 yıl önce •via X (Twitter)

Oyun Bilim & Teknoloji Eğitim

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Defi.Central profil fotoğrafı

Defi.Central1 yıl önce

You must make it public. Because their is no bigger company then opensource code lib. That uses by developers around world.

Rainmaker profil fotoğrafı

Rainmaker2 yıl önce

Here I share an XGBoost model that delivers a 25% CAGR with minimal drawdown on Visa stock. In this free Substack post I share code and commentary for a powerful Machine Learning strategy that delivers powerful returns.

benferrum - e/jounce profil fotoğrafı

benferrum - e/jounce1 yıl önce

awesome, now go 3D and AR

ANIRUDDHA ADAK profil fotoğrafı

ANIRUDDHA ADAK1 yıl önce

That is just a wow

Parag profil fotoğrafı

Parag1 yıl önce

How does CodeGPT handle dynamically typed or metaprogrammed code when constructing the Knowledge Graph, especially in languages like Python or JavaScript?

Jacek (Jomsborg.eth) profil fotoğrafı

Jacek (Jomsborg.eth)1 yıl önce

what is addeded value vs RAG

Ben Woodward profil fotoğrafı

Ben Woodward1 yıl önce

@kevinvangundy really cool

UmbraAtrox profil fotoğrafı

UmbraAtrox1 yıl önce

I've been waiting for this

options enjoyer profil fotoğrafı

options enjoyer1 yıl önce

Is this similar to lightRAG ?

David Olivencia profil fotoğrafı

David Olivencia1 yıl önce

Great feature. Go @codegptAI

Benzer Videolar

Our new short course, Knowledge Graphs for RAG, is now available! Knowledge graphs are a data structure that is great at capturing complex relationships between data of multiple types. By enabling more sophisticated retrieval of text than similarity search alone, knowledge graphs can improve the context you pass to the LLM and the performance of your RAG applications. In this course, taught by Andreas Kollegger of Neo4j, you’ll - Explore how knowledge graphs work by building a graph of public financial documents from scratch - Learn to write queries that retrieve text and data from the graph and use it to enhance the context you pass to an LLM chatbot - Combine a knowledge graph with a question-answer chain to build better RAG-powered chat systems Sign up here!

Our new short course, Knowledge Graphs for RAG, is now available! Knowledge graphs are a data structure that is great at capturing complex relationships between data of multiple types. By enabling more sophisticated retrieval of text than similarity search alone, knowledge graphs can improve the context you pass to the LLM and the performance of your RAG applications. In this course, taught by Andreas Kollegger of Neo4j, you’ll - Explore how knowledge graphs work by building a graph of public financial documents from scratch - Learn to write queries that retrieve text and data from the graph and use it to enhance the context you pass to an LLM chatbot - Combine a knowledge graph with a question-answer chain to build better RAG-powered chat systems Sign up here!

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Claude Code auto-documentation agent with Docusaurus and GitHub Actions 👏 Finally finished the step-by-step tutorial for building an agent that automatically documents all new features I push to my repository. Claude code agent reviews changes and creates a PR with identified documentation updates in the same project where Docusaurus is installed. Saving documentation time is sacred in development workflow... imagine how much time this flow will save in companies.

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You can now use Knowledge Graphs with Claude 3.5 Sonnet in Cursor! 🤩 CodeGPT’s Knowledge Graphs (KG) let you explore your entire codebase. In this case, we're navigating through Anthropic Python SDK. We asked how to send messages in batches and the tool identified the nodes and relationships in all relevant functions and classes. If you're curious about how LLMs will start handling large code repositories, you'll want to start programming CodeGPT’s KGs... I bet Andrej Karpathy will find this fascinating! I hope you get to try them out, because for me, reading documentation feels so 2024... now I just turn repos into KGs and get to work! 🧑🏽‍💻

You can now use Knowledge Graphs with Claude 3.5 Sonnet in Cursor! 🤩 CodeGPT’s Knowledge Graphs (KG) let you explore your entire codebase. In this case, we're navigating through Anthropic Python SDK. We asked how to send messages in batches and the tool identified the nodes and relationships in all relevant functions and classes. If you're curious about how LLMs will start handling large code repositories, you'll want to start programming CodeGPT’s KGs... I bet Andrej Karpathy will find this fascinating! I hope you get to try them out, because for me, reading documentation feels so 2024... now I just turn repos into KGs and get to work! 🧑🏽‍💻

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Introducing Default Context — Context7 now auto-generates library documentation using Claude models, even if its repo has zero docs. Try it: refresh your library and open: 👉 CONTEXT7_PROJECT_URL/llms.txt

Context7

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Introducing Codebase Knowledge Graphs in Cursor 🤩 In this video, I’ll walk you through how we went from using a knowledge graph of a repository on the CodeGPT platform to leveraging it directly within the Cursor editor This tool is specifically designed to navigate massive codebases, identify nodes and relationships, and deliver richer context to models specialized in code development, such as Anthropic Claude 3.5 Sonnet Stay tuned for an upcoming tutorial where I'll show you step-by-step how to create knowledge graphs and integrate them seamlessly into your entire software development workflow, from Commits and Pull Requests to even Trello tickets!

Introducing Codebase Knowledge Graphs in Cursor 🤩 In this video, I’ll walk you through how we went from using a knowledge graph of a repository on the CodeGPT platform to leveraging it directly within the Cursor editor This tool is specifically designed to navigate massive codebases, identify nodes and relationships, and deliver richer context to models specialized in code development, such as Anthropic Claude 3.5 Sonnet Stay tuned for an upcoming tutorial where I'll show you step-by-step how to create knowledge graphs and integrate them seamlessly into your entire software development workflow, from Commits and Pull Requests to even Trello tickets!

Daniel San

230,185 görüntüleme • 1 yıl önce

Build better RAG by letting a team of agents extract and connect your reference materials into a knowledge graph. Our new short course, “Agentic Knowledge Graph Construction,” taught by Neo4j Innovation Lead Andreas Kollegger, shows you how. Knowledge graphs are an important way to store information accurately but they are a lot of work to build manually. In this course you’ll learn how to build a team of agents that turn data– in this case product reviews and invoices from suppliers–into structured graphs of entities and relationships for RAG. Learn how agents can automatically handle the time-consuming work of building graphs — extracting entities and relationships (e.g., Product "contains" Assembly, Part "supplied_by" Supplier, Customer review "mentions" Product), deduplicating them, fact-checking them, and committing them to a graph database — so your retrieval system can find right information to generate accurate output. For example, you can use agents to help trace customer complaints directly to specific suppliers, manufacturing processes, and product hierarchies, thus turning fragmented information into queryable business intelligence. Skills you’ll gain: - Build, store, and access knowledge graphs using the Neo4j graph database - Build multi-agent systems using Google’s Agent Development Kit (ADK) - Set up a loop of agentic workflows to propose and refine a graph schema through fact-checking - Connect agent-generated graphs of unstructured and structured data into a unified knowledge graph This course gets into the practicum of why knowledge graphs give more accurate information retrieval than vector search alone, especially for high-stakes applications where precision matters more than fuzzy similarity matching. Sign up here:

Build better RAG by letting a team of agents extract and connect your reference materials into a knowledge graph. Our new short course, “Agentic Knowledge Graph Construction,” taught by Neo4j Innovation Lead Andreas Kollegger, shows you how. Knowledge graphs are an important way to store information accurately but they are a lot of work to build manually. In this course you’ll learn how to build a team of agents that turn data– in this case product reviews and invoices from suppliers–into structured graphs of entities and relationships for RAG. Learn how agents can automatically handle the time-consuming work of building graphs — extracting entities and relationships (e.g., Product "contains" Assembly, Part "supplied_by" Supplier, Customer review "mentions" Product), deduplicating them, fact-checking them, and committing them to a graph database — so your retrieval system can find right information to generate accurate output. For example, you can use agents to help trace customer complaints directly to specific suppliers, manufacturing processes, and product hierarchies, thus turning fragmented information into queryable business intelligence. Skills you’ll gain: - Build, store, and access knowledge graphs using the Neo4j graph database - Build multi-agent systems using Google’s Agent Development Kit (ADK) - Set up a loop of agentic workflows to propose and refine a graph schema through fact-checking - Connect agent-generated graphs of unstructured and structured data into a unified knowledge graph This course gets into the practicum of why knowledge graphs give more accurate information retrieval than vector search alone, especially for high-stakes applications where precision matters more than fuzzy similarity matching. Sign up here:

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audit and fix your entire developer docs site in under a minute We built an AI agent with Browserbase and Cerebras that audits your entire docs site > point it at any documentation site > agent goes down the link tree > agent crawls and verifies every page, checks every link, reads every code snippet > agent also compares content to your GitHub repo > returns a full report with suggested fixes and source references The full code and tutorial for how to build this yourself is live now.

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Most documentation rots because it’s expensive to maintain and easy to ignore. Software Factory is documentation-first so teams can describe systems in English and let agents compile that intent into code. It detects drift on every code push and keeps documentation synchronized with reality. Context stays alive. Agents keep building. Try it here:

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8090

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Introducing DeepGraph - now live for any public GitHub repo... for FREE! Navigate codebases with complete understanding of dependencies, nodes, and relationships. Turn any repository into an interactive knowledge graph you can chat with.

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Daniel San

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Cursor ultra tip turn a repository into documentation add documentation to composer and ask about it this will save you from hours of tutorial videos

Cursor ultra tip turn a repository into documentation add documentation to composer and ask about it this will save you from hours of tutorial videos

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Access To Documentation:: Should fathers not acquire documentation for their children in the absence of the child’s mother?

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Claude Code documentation agent keeps project docs up to date with Docusaurus. Created a Docusaurus site: npx create-docusaurus@latest my-docs classic Added the agent: npx claude-code-templates@latest --agent=documentation/docusaurus-expert --yes Then prompt: "Use docusaurus-expert to review that the documentation is correct and up-to-date" Now the docs stay synced with code changes. That’s how I set up as shown in the video.

Claude Code documentation agent keeps project docs up to date with Docusaurus. Created a Docusaurus site: npx create-docusaurus@latest my-docs classic Added the agent: npx claude-code-templates@latest --agent=documentation/docusaurus-expert --yes Then prompt: "Use docusaurus-expert to review that the documentation is correct and up-to-date" Now the docs stay synced with code changes. That’s how I set up as shown in the video.

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Cross-context Personal Knowledge Base with Social Graph🧠 Introducing Cross-context Personal Knowledge Base with Social Graph. Your Memory, Across Every Conversation Most AI forgets you the moment a chat ends. Teamily's Personal Knowledge Base remembers — across every group, every agent, and every context. Powered by your social graph, it connects the dots between your work, relationships, and ideas, so your AI always knows who you are, what you care about, and what happened before. No setup. No tagging. Just intelligence that grows with you. 🙌Try the prompt today: “visualize my knowledge base with social graph” #teamily #AI #Agent #KnowledgeBase #Social #SocialGraph

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🚀 Today, I'm launching the beta for Buildprint - the FREE, AI-powered documentation tool for every Bubble app. Automatically generate docs for your Bubble apps in seconds. Draw diagrams and charts for complex flows. Check out the quick demo video below 👇 Reply if you want early access, and I'll DM you the link.

🚀 Today, I'm launching the beta for Buildprint - the FREE, AI-powered documentation tool for every Bubble app. Automatically generate docs for your Bubble apps in seconds. Draw diagrams and charts for complex flows. Check out the quick demo video below 👇 Reply if you want early access, and I'll DM you the link.

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34,368 görüntüleme • 1 yıl önce

We’re kicking off 2025 with everything we've got! 🤩 Introducing CodeGPT's Knowledge Graphs, navigating through the entire Anthropic SDK repository. In this example, we loaded Anthropic Python SDK repository and successfully provided the LLM with all the knowledge it needs to fully understand the codebase. You can leverage these knowledge graphs using the CodeGPT extension in VSCode by simply calling the Codebase command 👏 Stay tuned for more tutorials on how to use this powerful tool! Happy 2025! 🎉

We’re kicking off 2025 with everything we've got! 🤩 Introducing CodeGPT's Knowledge Graphs, navigating through the entire Anthropic SDK repository. In this example, we loaded Anthropic Python SDK repository and successfully provided the LLM with all the knowledge it needs to fully understand the codebase. You can leverage these knowledge graphs using the CodeGPT extension in VSCode by simply calling the Codebase command 👏 Stay tuned for more tutorials on how to use this powerful tool! Happy 2025! 🎉

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