Qdrant’s Post

⚡ Build the fastest answering customer service AI-powered Discord bot! Learn how 🐫 CAMEL-AI.org, 🔥 Firecrawl & 👨🚀 Qdrant work together to create the ultimate customer service Discord bot powered by Qwen's Qwen 2.5 70b and Qwen 2.5 Coder 32b models severed by ⚡ SambaNova Systems. SambaNova Systems is the clear leader in output speed for using the Qwen 2.5 models; check here for a full breakdown: https://lnkd.in/etmwDpds 👇 Full architecture breakdown in the figure below. 🔗 Run the code via our cookbook: https://lnkd.in/eisNUxj5

🖌️Local RAG with Llama3 Loads webpage data using WebBaseLoader Splits it using RecursiveCharacterTextSplitter Uses Ollama embeddings and Chroma Uses Llama3 to answer Uses streamlit for a nice UI s/o Shubham Saboo for a great video https://lnkd.in/ge8PNDhE

pub.towardsai.net: The content discusses how to streamline the machine learning workflow using MLflow, focusing on Experiment Tracking, Model Registry, and Model Serving. It covers the features of Model Registry, such as organizing and managing trained machine-learning models, and explains how to register and serve models using the MLflow UI and API. The article also includes practical examples, code snippets, and a GitHub repository for further exploration. The author encourages engagement and feedback from the audience.

ThoughtSpot to the moon! Check out our new updates. Myself and others will be at Snowflake Summit demoing these live from the booth! Feel free to dm to schedule a meet up! Patrick Evans, Tri Tu, Brian Reynolds 👉 Drill, filter, customize charts, and verify formulas and SQL queries for AI answers without leaving the ThoughtSpot Sage experience 👉 Iteratively drill and auto-examine each attribute with SpotIQ Change Analysis for deeper insights 👉 Track your content's version history effortlessly using Git right within the ThoughtSpot UI

AI tools have acquiring human like interface smoothly.

The Power of One-Click Observability with LlamaIndex and MLflow! Hej LlamaIndex, "As we advance in the world of AI, observability is not just a feature; it's a foundational pillar that supports the innovation we bring to our applications." Today, as I reflect on my experiences with MLflow and LlamaIndex, I can confidently say that this powerful combination has been the key to my success in developing robust LLM applications. In today’s rapidly evolving landscape of LLM applications, ensuring robust observability is not just a luxury—it's a necessity. LlamaIndex is another important tool to empower you with one-click observability, enabling you to build principled LLM applications that thrive in production environments. Why Observability Matters in LLM Development? When developing applications like Retrieval-Augmented Generation (RAG) systems and dynamic agents, the ability to observe, debug, and evaluate your system is crucial. With LlamaIndex, you can track the interaction of your components seamlessly, gain insights into every detail, and ensure your models perform as expected. Therefore, Key Features of LlamaIndex's Observability, and Instrumentation module has taken observability to new heights. Here's what you can do: 🔍 View LLM Inputs/Outputs: Gain insights into the prompts that drive your LLMs and the responses generated, ensuring you understand every step of the interaction. ✅ Performance Tracking: Monitor outputs from all components, including LLMs and embeddings, making sure they’re delivering the performance you need. 🧩 Call Traces for Indexing and Querying: Follow the pathways of your requests, allowing you to debug and optimize your system efficiently. 🎮 Integrate Easily with MLflow for Enhanced Control: Pairing LlamaIndex with MLflow means you can effortlessly manage and optimize your workflows! 🌟 🔍 Track Your Indices: Keep an eye on every index within MLflow effortlessly! Say goodbye to the chaos of scattered data. 📊 📦 Package Your LlamaIndex Engine: Ensure consistent environments across all stages of the ML lifecycle by packaging dependencies and metadata directly with your engine. 🌐 📈 Evaluate Performance: Use MLflow’s native evaluation capabilities to effectively analyze your LlamaIndex applications. Gain insights that drive improvement! 🔧 📝 Automatic Logging: Just one command to instrument your LlamaIndex application means full visibility without the hassle of extra coding! 💡 How to Get Started? 🤔 Dive into the powerful combinations of LlamaIndex and MLflow, and create your first index and enable tracing for comprehensive insights. Embrace the future of LLM applications with LlamaIndex—where observability meets simplicity and effectiveness. Building, debugging, and deploying your models has never been easier! 🌍✨ 👉 Explore the full integration guides and elevate your LLM applications! #LlamaIndex #LLM #Observability #MLflow #AI #MachineLearning #DataIntegration #TechInnovation

Really useful pipeline outline graph.

🚀 Here is a comprehensive video guide on building a RAG chatbot using Langflow, DataStax Astra DB, and Streamlit! Dive into Langflow's intuitive drag-and-drop interface, explore the key components of RAG architecture, and learn how to create an application in just 5 minutes. 🔗 RESOURCES: 📖 Discover how DataStax + Langflow simplifies RAG by 100x: Learn More ⭐️ Explore Langflow on GitHub: Check it Out 💻 Start coding with our Langflow Quickstart Guide: Get Started 🔍 ABOUT LANGFLOW: ➡️ Langflow is an open-source visual framework for building GenAI and RAG applications using LangChain and prebuilt components. ➡️ Easily drag and drop components, visualize data flow, and iterate quickly with fine-grained control over AI applications. ➡️ Langflow generates the workflow code and LangChain objects needed for rapid production deployment. ➡️ DataStax + Langflow empowers developers to focus on building apps efficiently and effectively. #Innovation #Technology #RAG #AI #Chatbots #Langflow #DataStax #Streamlit #AstraDB https://lnkd.in/gw6b5qWT

🚀 Introducing FileCon: A Simple File Concatenator CLI Tool! Just launched my latest project - FileCon, a command-line tool that helps you easily merge specific file types into a single document. Whether you’re working on AI projects or just want to concatenate files quickly, FileCon has you covered! ⚡ Key Features: - Interactive wizard or command-line options - Filter by file extensions (e.g., .go, .js, .py) - Option to remove tabs & extra spaces Details: https://lnkd.in/g-5nxvWi GitHub: https://lnkd.in/gSTdv-dx #Go #CLI #Automation #FileProcessing #AItools #Cobra

Transform your unstructured data into #RAG-ready structured data in a few easy steps! 🚀 Join this live, virtual workshop to learn how to turn PDFs, HTML, PPT, and even handwritten notes into structured data suitable to interact with #LLMs or #Chatbots. 🔗Register for Free Now: https://hubs.li/Q02WXPVl0