MastodonTech.de

michabbbWorks with <a href="https://social.vivaldi.net/tags/Python" class="mention hashtag" rel="nofollow noopener" target="_blank">#Python</a> <a href="https://social.vivaldi.net/tags/JavaScript" class="mention hashtag" rel="nofollow noopener" target="_blank">#JavaScript</a> <a href="https://social.vivaldi.net/tags/TypeScript" class="mention hashtag" rel="nofollow noopener" target="_blank">#TypeScript</a> <a href="https://social.vivaldi.net/tags/Go" class="mention hashtag" rel="nofollow noopener" target="_blank">#Go</a> supporting frameworks like <a href="https://social.vivaldi.net/tags/LangChain" class="mention hashtag" rel="nofollow noopener" target="_blank">#LangChain</a> <a href="https://social.vivaldi.net/tags/LlamaIndex" class="mention hashtag" rel="nofollow noopener" target="_blank">#LlamaIndex</a> <a href="https://social.vivaldi.net/tags/Genkit" class="mention hashtag" rel="nofollow noopener" target="_blank">#Genkit</a> & more Github: <a href="https://github.com/googleapis/genai-toolbox" rel="nofollow noopener" translate="no" target="_blank">https://github.com/googleapis/genai-toolbox</a> MCP Manual: <a href="https://cloud.google.com/sql/docs/mysql/pre-built-tools-with-mcp-toolbox" rel="nofollow noopener" translate="no" target="_blank">https://cloud.google.com/sql/docs/mysql/pre-built-tools-with-mcp-toolbox</a>

OpenSearch ProjectOpenSearch’s new MCP standard lets LLMs like Claude securely access + act on your data — no brittle glue code.🧠 Dynamic tool discovery 🔐 Built-in auth + security ⚙️ Unified JSON interfaceBuild smarter AI assistants + RAG apps → 🔗 <a href="https://opensearch.org/blog/introducing-mcp-in-opensearch/" rel="nofollow noopener" translate="no" target="_blank">https://opensearch.org/blog/introducing-mcp-in-opensearch/</a><a href="https://fosstodon.org/tags/Claude" class="mention hashtag" rel="nofollow noopener" target="_blank">#Claude</a> <a href="https://fosstodon.org/tags/OpenSearch" class="mention hashtag" rel="nofollow noopener" target="_blank">#OpenSearch</a> <a href="https://fosstodon.org/tags/MCP" class="mention hashtag" rel="nofollow noopener" target="_blank">#MCP</a> <a href="https://fosstodon.org/tags/AIInfra" class="mention hashtag" rel="nofollow noopener" target="_blank">#AIInfra</a> <a href="https://fosstodon.org/tags/RAG" class="mention hashtag" rel="nofollow noopener" target="_blank">#RAG</a> <a href="https://fosstodon.org/tags/LangChain" class="mention hashtag" rel="nofollow noopener" target="_blank">#LangChain</a> <a href="https://fosstodon.org/tags/OpenSource" class="mention hashtag" rel="nofollow noopener" target="_blank">#OpenSource</a>

Dr. Thompson🧠 Want to build AI that acts, not just chats?Discover why OpenAI’s new Agents SDK is outperforming LangChain and AutoGen in 2025. From agent chaining to built-in guardrails, this SDK changes the game for devs.👇 Here’s your edge in the Agentic AI era:🔗 <a href="https://medium.com/@rogt.x1997/7-reasons-why-openais-agents-sdk-beats-langchain-and-autogen-in-2025-690b58007e54" rel="nofollow noopener" translate="no" target="_blank">https://medium.com/@rogt.x1997/7-reasons-why-openais-agents-sdk-beats-langchain-and-autogen-in-2025-690b58007e54</a><a href="https://mastodon.social/tags/AgenticAI" class="mention hashtag" rel="nofollow noopener" target="_blank">#AgenticAI</a> <a href="https://mastodon.social/tags/OpenAI" class="mention hashtag" rel="nofollow noopener" target="_blank">#OpenAI</a> <a href="https://mastodon.social/tags/LangChain" class="mention hashtag" rel="nofollow noopener" target="_blank">#LangChain</a> <a href="https://mastodon.social/tags/PythonDev" class="mention hashtag" rel="nofollow noopener" target="_blank">#PythonDev</a> <a href="https://medium.com/@rogt.x1997/7-reasons-why-openais-agents-sdk-beats-langchain-and-autogen-in-2025-690b58007e54" rel="nofollow noopener" translate="no" target="_blank">https://medium.com/@rogt.x1997/7-reasons-why-openais-agents-sdk-beats-langchain-and-autogen-in-2025-690b58007e54</a>

Sarah LeaLangWHAT? You've seen names like LangChain, LangGraph, LangFlow or LangSmith – but what’s really behind them?:blobcoffee: LangChain helps us build LLM apps via modular code.:blobcoffee: LangGraph adds branching logic and multi-agent workflows.:blobcoffee: LangFlow lets us create flows with drag & drop.:blobcoffee: LangSmith monitors and evaluates our LLM stack.LangChain, LangGraph and LangSmith come from the same ecosystem. LangFlow is a visual builder developed independently by DataStax.Tried both LangChain and Langflow to build the same chatbot — Medium article coming shortly.<a href="https://techhub.social/tags/LangChain" class="mention hashtag" rel="nofollow noopener" target="_blank">#LangChain</a> <a href="https://techhub.social/tags/LangFlow" class="mention hashtag" rel="nofollow noopener" target="_blank">#LangFlow</a> <a href="https://techhub.social/tags/LLM" class="mention hashtag" rel="nofollow noopener" target="_blank">#LLM</a> <a href="https://techhub.social/tags/AI" class="mention hashtag" rel="nofollow noopener" target="_blank">#AI</a> <a href="https://techhub.social/tags/KI" class="mention hashtag" rel="nofollow noopener" target="_blank">#KI</a> <a href="https://techhub.social/tags/python" class="mention hashtag" rel="nofollow noopener" target="_blank">#python</a> <a href="https://techhub.social/tags/OpenSource" class="mention hashtag" rel="nofollow noopener" target="_blank">#OpenSource</a> <a href="https://techhub.social/tags/LangGraph" class="mention hashtag" rel="nofollow noopener" target="_blank">#LangGraph</a> <a href="https://techhub.social/tags/LangSmith" class="mention hashtag" rel="nofollow noopener" target="_blank">#LangSmith</a> <a href="https://techhub.social/tags/technology" class="mention hashtag" rel="nofollow noopener" target="_blank">#technology</a> <a href="https://techhub.social/tags/chatbot" class="mention hashtag" rel="nofollow noopener" target="_blank">#chatbot</a> <a href="https://techhub.social/tags/ollama" class="mention hashtag" rel="nofollow noopener" target="_blank">#ollama</a>

Alvin Ashcraft 🐿️Microsoft and LangChain: Leading the Way in AI Security for Open Source on Azure.<a href="https://devblogs.microsoft.com/blog/microsoft-and-langchain-leading-the-way-in-ai-security-for-open-source-on-azure" rel="nofollow noopener" translate="no" target="_blank">https://devblogs.microsoft.com/blog/microsoft-and-langchain-leading-the-way-in-ai-security-for-open-source-on-azure</a> <a href="https://hachyderm.io/tags/ai" class="mention hashtag" rel="nofollow noopener" target="_blank">#ai</a> <a href="https://hachyderm.io/tags/langchain" class="mention hashtag" rel="nofollow noopener" target="_blank">#langchain</a> <a href="https://hachyderm.io/tags/security" class="mention hashtag" rel="nofollow noopener" target="_blank">#security</a> <a href="https://hachyderm.io/tags/oss" class="mention hashtag" rel="nofollow noopener" target="_blank">#oss</a> <a href="https://hachyderm.io/tags/azure" class="mention hashtag" rel="nofollow noopener" target="_blank">#azure</a> <a href="https://hachyderm.io/tags/cloud" class="mention hashtag" rel="nofollow noopener" target="_blank">#cloud</a>

Towards Data ScienceWant to build a generative AI web app without the headache? Ed Izaguirre explores the full spectrum, from complex MERN stacks with <a href="https://hachyderm.io/tags/LangChain" class="mention hashtag" rel="nofollow noopener" target="_blank">#LangChain</a> and Pinecone, to surprisingly capable single-file SQLite monoliths.<a href="https://towardsdatascience.com/the-simplest-possible-ai-web-app/" rel="nofollow noopener" translate="no" target="_blank">https://towardsdatascience.com/the-simplest-possible-ai-web-app/</a>

Dr. Thompson🚀 Think you know how GenAI works? It's not just prompts. It’s orchestration with 25 next-gen Python libraries powering the world’s smartest LLMs: agents, memory, RAG, grammar control & more 🧠💻 Dive into the tools under the hood of AI in 2025 👇 🔗 <a href="https://medium.com/@rogt.x1997/25-groundbreaking-python-libraries-powering-genai-workflows-in-2025-982add3d9301" rel="nofollow noopener" translate="no" target="_blank">https://medium.com/@rogt.x1997/25-groundbreaking-python-libraries-powering-genai-workflows-in-2025-982add3d9301</a> <a href="https://mastodon.social/tags/GenAI" class="mention hashtag" rel="nofollow noopener" target="_blank">#GenAI</a> <a href="https://mastodon.social/tags/PythonLibraries" class="mention hashtag" rel="nofollow noopener" target="_blank">#PythonLibraries</a> <a href="https://mastodon.social/tags/LLM" class="mention hashtag" rel="nofollow noopener" target="_blank">#LLM</a> <a href="https://mastodon.social/tags/AIstack" class="mention hashtag" rel="nofollow noopener" target="_blank">#AIstack</a> <a href="https://mastodon.social/tags/LangChain" class="mention hashtag" rel="nofollow noopener" target="_blank">#LangChain</a> <a href="https://mastodon.social/tags/AutoGen" class="mention hashtag" rel="nofollow noopener" target="_blank">#AutoGen</a> <a href="https://mastodon.social/tags/AItools" class="mention hashtag" rel="nofollow noopener" target="_blank">#AItools</a> <a href="https://mastodon.social/tags/ArtificialIntelligence" class="mention hashtag" rel="nofollow noopener" target="_blank">#ArtificialIntelligence</a> <a href="https://medium.com/@rogt.x1997/25-groundbreaking-python-libraries-powering-genai-workflows-in-2025-982add3d9301" rel="nofollow noopener" translate="no" target="_blank">https://medium.com/@rogt.x1997/25-groundbreaking-python-libraries-powering-genai-workflows-in-2025-982add3d9301</a>

KrisStarted building LLM apps with Rust + rig.rs, now diving into LangGraph and Python too. Been a super fun ride so far 🤓🛠️<a href="https://mastodon.social/tags/Rust" class="mention hashtag" rel="nofollow noopener" target="_blank">#Rust</a> <a href="https://mastodon.social/tags/Python" class="mention hashtag" rel="nofollow noopener" target="_blank">#Python</a> <a href="https://mastodon.social/tags/LLM" class="mention hashtag" rel="nofollow noopener" target="_blank">#LLM</a> <a href="https://mastodon.social/tags/AI" class="mention hashtag" rel="nofollow noopener" target="_blank">#AI</a> <a href="https://mastodon.social/tags/LangChain" class="mention hashtag" rel="nofollow noopener" target="_blank">#LangChain</a>

HAPPY HAGGEN🚀 Built a RAG system with LangChain, OpenSearch, Google’s Gemini & OpenAI embeddings! Transform data into smart apps—optimize, deploy, and innovate. Your AI toolkit is ready. 🔍💡 <a href="https://techhub.social/tags/AI" class="mention hashtag" rel="nofollow noopener" target="_blank">#AI</a> <a href="https://techhub.social/tags/RAG" class="mention hashtag" rel="nofollow noopener" target="_blank">#RAG</a> <a href="https://techhub.social/tags/LangChain" class="mention hashtag" rel="nofollow noopener" target="_blank">#LangChain</a> <a href="https://techhub.social/tags/GenerativeAI" class="mention hashtag" rel="nofollow noopener" target="_blank">#GenerativeAI</a> <a href="https://zilliz.com/tutorials/rag/langchain-and-opensearch-and-google-vertex-ai-gemini-2.0-pro-and-openai-text-embedding-ada-002" rel="nofollow noopener" translate="no" target="_blank">https://zilliz.com/tutorials/rag/langchain-and-opensearch-and-google-vertex-ai-gemini-2.0-pro-and-openai-text-embedding-ada-002</a>

Mark Free"Built a RAG system with LangChain, OpenSearch, Fireworks AI's Llama 3.1, and Azure embeddings! 🚀 Optimize, calculate costs, and innovate. <a href="https://techhub.social/tags/GenerativeAI" class="mention hashtag" rel="nofollow noopener" target="_blank">#GenerativeAI</a> <a href="https://techhub.social/tags/RAG" class="mention hashtag" rel="nofollow noopener" target="_blank">#RAG</a> <a href="https://techhub.social/tags/LangChain" class="mention hashtag" rel="nofollow noopener" target="_blank">#LangChain</a> <a href="https://techhub.social/tags/Llama3" class="mention hashtag" rel="nofollow noopener" target="_blank">#Llama3</a>" <a href="https://zilliz.com/tutorials/rag/langchain-and-opensearch-and-fireworks-ai-llama-3.1-8b-instruct-and-azure-text-embedding-3-large" rel="nofollow noopener" translate="no" target="_blank">https://zilliz.com/tutorials/rag/langchain-and-opensearch-and-fireworks-ai-llama-3.1-8b-instruct-and-azure-text-embedding-3-large</a>

Microsoft DevBlogsONNX Runtime GenAI is the optimal choice! <a href="https://dotnet.social/tags/AI" class="mention hashtag" rel="nofollow noopener" target="_blank">#AI</a> <a href="https://dotnet.social/tags/OnPrem" class="mention hashtag" rel="nofollow noopener" target="_blank">#OnPrem</a> <a href="https://dotnet.social/tags/MachineLearning" class="mention hashtag" rel="nofollow noopener" target="_blank">#MachineLearning</a> <a href="https://dotnet.social/tags/LangChain" class="mention hashtag" rel="nofollow noopener" target="_blank">#LangChain</a>For more information check: <a href="https://devblogs.microsoft.com/ise/running-rag-onnxruntime-genai/" rel="nofollow noopener" translate="no" target="_blank">https://devblogs.microsoft.com/ise/running-rag-onnxruntime-genai/</a>.

Harald KlinkeNeo4j treibt mit GraphRAG, Vektor-Indizes & Agentic RAG die <a href="https://det.social/tags/KI" class="mention hashtag" rel="nofollow noopener" target="_blank">#KI</a>-Entwicklung voran. Ob <a href="https://det.social/tags/LangChain" class="mention hashtag" rel="nofollow noopener" target="_blank">#LangChain</a>, <a href="https://det.social/tags/LlamaIndex" class="mention hashtag" rel="nofollow noopener" target="_blank">#LlamaIndex</a>, <a href="https://det.social/tags/SpringAI" class="mention hashtag" rel="nofollow noopener" target="_blank">#SpringAI</a> oder <a href="https://det.social/tags/VertexAI" class="mention hashtag" rel="nofollow noopener" target="_blank">#VertexAI</a> – das neue Python-Paket und das Model Context Protocol (MCP) verknüpfen Graphdaten nahtlos mit <a href="https://det.social/tags/LLM" class="mention hashtag" rel="nofollow noopener" target="_blank">#LLM</a>-Anwendungen. <a href="https://det.social/tags/Neo4j" class="mention hashtag" rel="nofollow noopener" target="_blank">#Neo4j</a> <a href="https://det.social/tags/GenAI" class="mention hashtag" rel="nofollow noopener" target="_blank">#GenAI</a> <a href="https://det.social/tags/RAG" class="mention hashtag" rel="nofollow noopener" target="_blank">#RAG</a> <a href="https://det.social/tags/GraphQL" class="mention hashtag" rel="nofollow noopener" target="_blank">#GraphQL</a> <a href="https://det.social/tags/Cypher" class="mention hashtag" rel="nofollow noopener" target="_blank">#Cypher</a> <a href="https://det.social/tags/VectorSearch" class="mention hashtag" rel="nofollow noopener" target="_blank">#VectorSearch</a> <a href="https://det.social/tags/AgenticAI" class="mention hashtag" rel="nofollow noopener" target="_blank">#AgenticAI</a> <a href="https://www.bigdata-insider.de/leistungssprung-bei-graph-datenbanken-mit-ki-integration-cloud-skalierung-und-terabyte-graphen-a-2307ed20cfaf562a1a0094b712b5be95/" rel="nofollow noopener" translate="no" target="_blank">https://www.bigdata-insider.de/leistungssprung-bei-graph-datenbanken-mit-ki-integration-cloud-skalierung-und-terabyte-graphen-a-2307ed20cfaf562a1a0094b712b5be95/</a>

Sarah LeaUnderstand RAG at Easter? 🐣 Why not use the time to learn something new — and build your own local PDF chatbot?Learn how chunking, embeddings and vector search work in practice - with LangChain, FAISS, Ollama and Mistral running entirely on your machine (no API key required).Perfect for beginners - here's the full guide & GitHub repo 👇:blobcoffee: step-by-step guide: <a href="https://bit.ly/3EfOHB9" rel="nofollow noopener" translate="no" target="_blank">https://bit.ly/3EfOHB9</a> :blobcoffee: GitHub Repo: <a href="https://bit.ly/3EtqYgK" rel="nofollow noopener" translate="no" target="_blank">https://bit.ly/3EtqYgK</a><a href="https://techhub.social/tags/RAG" class="mention hashtag" rel="nofollow noopener" target="_blank">#RAG</a> <a href="https://techhub.social/tags/Langchain" class="mention hashtag" rel="nofollow noopener" target="_blank">#Langchain</a> <a href="https://techhub.social/tags/Mistral" class="mention hashtag" rel="nofollow noopener" target="_blank">#Mistral</a> <a href="https://techhub.social/tags/LLM" class="mention hashtag" rel="nofollow noopener" target="_blank">#LLM</a> <a href="https://techhub.social/tags/AI" class="mention hashtag" rel="nofollow noopener" target="_blank">#AI</a> <a href="https://techhub.social/tags/Chatbot" class="mention hashtag" rel="nofollow noopener" target="_blank">#Chatbot</a> <a href="https://techhub.social/tags/KI" class="mention hashtag" rel="nofollow noopener" target="_blank">#KI</a> <a href="https://techhub.social/tags/Python" class="mention hashtag" rel="nofollow noopener" target="_blank">#Python</a> <a href="https://techhub.social/tags/Technology" class="mention hashtag" rel="nofollow noopener" target="_blank">#Technology</a> <a href="https://techhub.social/tags/DataScience" class="mention hashtag" rel="nofollow noopener" target="_blank">#DataScience</a> <a href="https://techhub.social/tags/Easter" class="mention hashtag" rel="nofollow noopener" target="_blank">#Easter</a>

:rss: Qiita - 人気の記事`langchain-mcp-adapters` を使用した LangChain と MCP サーバーの連携 <a href="https://qiita.com/nanami_bitwise/items/d04dedb0c276bb624d8a?utm_campaign=popular_items&utm_medium=feed&utm_source=popular_items" rel="nofollow noopener" translate="no" target="_blank">https://qiita.com/nanami_bitwise/items/d04dedb0c276bb624d8a?utm_campaign=popular_items&utm_medium=feed&utm_source=popular_items</a><a href="https://rss-mstdn.studiofreesia.com/tags/qiita" class="mention hashtag" rel="nofollow noopener" target="_blank">#qiita</a> <a href="https://rss-mstdn.studiofreesia.com/tags/Python" class="mention hashtag" rel="nofollow noopener" target="_blank">#Python</a> <a href="https://rss-mstdn.studiofreesia.com/tags/AI" class="mention hashtag" rel="nofollow noopener" target="_blank">#AI</a> <a href="https://rss-mstdn.studiofreesia.com/tags/MCP" class="mention hashtag" rel="nofollow noopener" target="_blank">#MCP</a> <a href="https://rss-mstdn.studiofreesia.com/tags/LangChain" class="mention hashtag" rel="nofollow noopener" target="_blank">#LangChain</a> <a href="https://rss-mstdn.studiofreesia.com/tags/MCP%E3%82%B5%E3%83%BC%E3%83%90%E3%83%BC" class="mention hashtag" rel="nofollow noopener" target="_blank">#MCPサーバー</a>

Hacker NewsQuick Primer on MCP Using Ollama and LangChain<a href="https://www.polarsparc.com/xhtml/MCP.html" rel="nofollow noopener" translate="no" target="_blank">https://www.polarsparc.com/xhtml/MCP.html</a><a href="https://mastodon.social/tags/HackerNews" class="mention hashtag" rel="nofollow noopener" target="_blank">#HackerNews</a> <a href="https://mastodon.social/tags/MCP" class="mention hashtag" rel="nofollow noopener" target="_blank">#MCP</a> <a href="https://mastodon.social/tags/Ollama" class="mention hashtag" rel="nofollow noopener" target="_blank">#Ollama</a> <a href="https://mastodon.social/tags/LangChain" class="mention hashtag" rel="nofollow noopener" target="_blank">#LangChain</a> <a href="https://mastodon.social/tags/TechTutorial" class="mention hashtag" rel="nofollow noopener" target="_blank">#TechTutorial</a> <a href="https://mastodon.social/tags/Programming" class="mention hashtag" rel="nofollow noopener" target="_blank">#Programming</a>

Sarfraaz Ahmed🛫 Getting started with LangChain ✨ Rerun your failed tests in PyTest ✨ Usefulness of Context Managers in Python ✨ Testing your Flask AppLatest Edition of My Voyage of Discovery: <a href="http://eepurl.com/jbSOOQ" rel="nofollow noopener" translate="no" target="_blank">http://eepurl.com/jbSOOQ</a> Subscribe for more at: <a href="http://eepurl.com/iu6PFU" rel="nofollow noopener" translate="no" target="_blank">http://eepurl.com/iu6PFU</a><a href="https://mastodon.social/tags/LangChain" class="mention hashtag" rel="nofollow noopener" target="_blank">#LangChain</a> <a href="https://mastodon.social/tags/PyTest" class="mention hashtag" rel="nofollow noopener" target="_blank">#PyTest</a> <a href="https://mastodon.social/tags/python" class="mention hashtag" rel="nofollow noopener" target="_blank">#python</a> <a href="https://mastodon.social/tags/Advanced" class="mention hashtag" rel="nofollow noopener" target="_blank">#Advanced</a> <a href="https://mastodon.social/tags/Flask" class="mention hashtag" rel="nofollow noopener" target="_blank">#Flask</a> <a href="https://mastodon.social/tags/MyVoD" class="mention hashtag" rel="nofollow noopener" target="_blank">#MyVoD</a>

Alessio Pomaro🧠 In questo test, in una SERP di <a href="https://mastodon.uno/tags/Google" class="mention hashtag" rel="nofollow noopener" target="_blank">#Google</a> in cui compare <a href="https://mastodon.uno/tags/AI" class="mention hashtag" rel="nofollow noopener" target="_blank">#AI</a> Overviews, ho preso i contenuti nelle prime 12 posizioni e ho creato un piccolo <a href="https://mastodon.uno/tags/RAG" class="mention hashtag" rel="nofollow noopener" target="_blank">#RAG</a> usando <a href="https://mastodon.uno/tags/LangChain" class="mention hashtag" rel="nofollow noopener" target="_blank">#LangChain</a>, <a href="https://mastodon.uno/tags/Chroma" class="mention hashtag" rel="nofollow noopener" target="_blank">#Chroma</a> DB e <a href="https://mastodon.uno/tags/GPT4o" class="mention hashtag" rel="nofollow noopener" target="_blank">#GPT4o</a>. ✨ Inviandolo la query al RAG, ottengo una risposta simile a quella proposta da AI Overviews. 💡 Chiaramente Google usa anche query correlate ("fan-out") e il Knowledge Graph per espandere i risultati.<a href="https://mastodon.uno/tags/AI" class="mention hashtag" rel="nofollow noopener" target="_blank">#AI</a> <a href="https://mastodon.uno/tags/GenAI" class="mention hashtag" rel="nofollow noopener" target="_blank">#GenAI</a> <a href="https://mastodon.uno/tags/GenerativeAI" class="mention hashtag" rel="nofollow noopener" target="_blank">#GenerativeAI</a> <a href="https://mastodon.uno/tags/IntelligenzaArtificiale" class="mention hashtag" rel="nofollow noopener" target="_blank">#IntelligenzaArtificiale</a> <a href="https://mastodon.uno/tags/LLM" class="mention hashtag" rel="nofollow noopener" target="_blank">#LLM</a>

Sarah LeaWhat is an agent? That’s what Day 3 of Kaggle’s Gen AI Challenge is all about.:blobcoffee: An agent is a system that observes its environment, plans actions, uses tools like APIs, functions, or data stores, and acts autonomously to achieve a goal – often over multiple steps (see whitepaper from Google below).The cognitive architecture of an agent consists of three essential components: 🧠 a model (like a language model), 🔧 tools (like APIs or functions), and 🎯 an orchestration layer that coordinates reasoning and action.You can build such agents using tools like LangChain and LangGraph.The full whitepaper from course day 3: <a href="https://www.kaggle.com/whitepaper-agents" rel="nofollow noopener" translate="no" target="_blank">https://www.kaggle.com/whitepaper-agents</a><a href="https://techhub.social/tags/agenticAI" class="mention hashtag" rel="nofollow noopener" target="_blank">#agenticAI</a> <a href="https://techhub.social/tags/genai" class="mention hashtag" rel="nofollow noopener" target="_blank">#genai</a> <a href="https://techhub.social/tags/GenerativeAI" class="mention hashtag" rel="nofollow noopener" target="_blank">#GenerativeAI</a> <a href="https://techhub.social/tags/ai" class="mention hashtag" rel="nofollow noopener" target="_blank">#ai</a> <a href="https://techhub.social/tags/ki" class="mention hashtag" rel="nofollow noopener" target="_blank">#ki</a> <a href="https://techhub.social/tags/google" class="mention hashtag" rel="nofollow noopener" target="_blank">#google</a> <a href="https://techhub.social/tags/kaggle" class="mention hashtag" rel="nofollow noopener" target="_blank">#kaggle</a> <a href="https://techhub.social/tags/llm" class="mention hashtag" rel="nofollow noopener" target="_blank">#llm</a> <a href="https://techhub.social/tags/langchain" class="mention hashtag" rel="nofollow noopener" target="_blank">#langchain</a>

Nicolas Fränkel 🇺🇦🇬🇪La Grosse Conf 2025 - <a href="https://mastodon.top/tags/LangChain" class="mention hashtag" rel="nofollow noopener" target="_blank">#LangChain</a> : <a href="https://mastodon.top/tags/OpenSource" class="mention hashtag" rel="nofollow noopener" target="_blank">#OpenSource</a>, compléxité et adaptation permanente<a href="https://blog.octo.com/la-grosse-conf-2025-langchain--opensource-complexite-et-adaptation-permanente" rel="nofollow noopener" translate="no" target="_blank">https://blog.octo.com/la-grosse-conf-2025-langchain--opensource-complexite-et-adaptation-permanente</a>

Philipp Krennsneak peek: we'll have an <a href="https://mastodon.social/tags/elastic" class="mention hashtag" rel="nofollow noopener" target="_blank">#elastic</a> developer event in mountain view in may — single track and just engineering. and I'll make sure to keep it *very* technical: besides developers from <a href="https://mastodon.social/tags/LangChain" class="mention hashtag" rel="nofollow noopener" target="_blank">#LangChain</a> and <a href="https://mastodon.social/tags/github" class="mention hashtag" rel="nofollow noopener" target="_blank">#github</a> with more to come, we'll have shay (elasticsearch creator), costin (who most recently worked on JOINs for ES|QL), and dinesh (currently researching on agentic search) from elastic 1/2

Frühere Suchanfragen

Suchoptionen

Verwaltet von:

Serverstatistik:

#langchain