Neon’s Post

There's a long list of tech that goes into building RAG systems. ✅Vector databases ✅Retrieval and search ✅Frameworks & libraries ✅Document chunking ✅More... Here are some of the best tools we've used (and read about) for RAG. 📙Read list here: https://lnkd.in/gS_iMVxy #ai #rag #ragtools #llms #vectordb

“This article aims to help you build AI agents powered by memory, knowledgebase, tools, and reasoning and chat with them using the command line and beautiful agent UIs.“ Read “Best 5 Frameworks To Build Multi-Agent AI Applications“ by Amos Gyamfi on Medium: https://lnkd.in/gppTjsug

Imagine your PowerShell scripts infused with AI intelligence - GitHub AI intelligence. With PSGitHubChat, you can integrate diverse AI models directly into your workflow, enhancing creativity and efficiency. Ready to transform your coding experience? Install PSGitHubChat: 🛠️Install-Module PSGitHubChat Discover more: https://lnkd.in/eAEeqVxQ Make your scripts stand out with the power of AI. #PowerShell #AI #GitHubMarketplace #GenAI #MSFT

Structure-Aware Multi-objective Metaprompt Optimization (SAMMO) framework is a new open-source tool that streamlines the optimization of prompts, particularly those that combine different types of structural information like RAG. It can make structural changes, such as removing entire components or replacing them with different ones. These features enable AI practitioners and researchers to efficiently refine their prompts with little manual effort.

the code generation is one of the function of the ai models. the claude sonnet tops the list I reviewed deepseek coder few weeks ago. it's available through api call, and I think is the best based upon price performance ratio, even though it shows up 2nd https://lnkd.in/gKiWHE54

From this entire article one thing which rings the bell "MLE bench, a benchmark designed to assess how effectively AI agents can perform machine learning engineering tasks" https://lnkd.in/gxaN56ii

🚀 Dive into the future of AI with LLM agents! Discover the challenges and best practices for deploying production architectures. Whether you're a data engineer or AI enthusiast, this guide from ZenML is a must-read. "The vision of plug-and-play agent augmentation is alluring. But practical challenges remain in scaling these architectures to production. Agent-tool interactions are notoriously difficult to test and debug—a single "hallucinated" API call can derail an entire workflow." Get ahead in the AI game and explore today! 👉 [Read More] https://lnkd.in/gNDiFMEf #AI #LLMAgents #MachineLearning #TechInnovation

🚀 **Unlock the Power of LangChain: Your Ultimate Guide to AI-Driven Workflows!** Are you ready to dive into the world of Generative AI and build sophisticated conversational agents? The LangChain book is your comprehensive guide to mastering this powerful framework! ### Why LangChain? LangChain is revolutionizing AI development by offering a robust suite of features for creating efficient, scalable, and versatile AI applications. Whether you're a developer, a business professional, or simply curious about AI, LangChain provides the tools you need to integrate powerful AI capabilities into your projects. ### What You'll Learn: 1. **Basics of LangChain**: Understand the core components like chat models, prompt templates, document loaders, retrievers, memory, tool building, and chains. 2. **Working with Chat Models**: Learn to interact with various large language models including OpenAI's GPT and Anthropic's Claude. 3. **Adding Memory**: Enhance your applications with memory to maintain context across interactions. 4. **Vector Databases**: Implement vector databases like Chroma DB for efficient data retrieval. 5. **Automating Tasks with Chains**: Automate complex workflows by linking multiple tasks. 6. **Building a Conversational Agent**: Step-by-step guide to creating "Max," a Generative AI Agent capable of autonomous decision-making and complex task execution. ### Advanced Features: - **Retrieval Augmented Generation (RAG)**: Combine retrieval and generation capabilities for more accurate and contextually relevant responses. - **Agentic RAG**: Enable your agents to perform autonomous decision-making and task execution using tools like OpenAI and custom retrievers. ### Ready to Transform Your AI Projects? Get your copy now and start building intelligent, context-aware applications that can revolutionize your workflow and productivity. 👉 [Get the LangChain Book on Amazon](https://lnkd.in/gCTV6hB2) Embark on your journey to mastering LangChain and unleash the full potential of Generative AI! 🌟 #LangChain #AI #GenerativeAI #Chatbots #AIDevelopment #MachineLearning #Python #AIWorkflow #ConversationalAgents #RAG #VectorDatabases #Automation #AItools

Comprehensive Guide to Build AI Agents from Scratch