🤩Integrate Qdrant and #Neo4j to enhance your RAG Pipeline🤩 Follow Will Tai's instructions and quickly set up a local environment to test the QdrantNeo4jRetriever by Integrating Neo4j for managing graph-based data and Qdrant for performing vector similarity searches. https://bit.ly/4h9Hbps Have fun! #graphdatabase #GraphRAG Will Tai 戴肇恩
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Beyond Event Viewer: WMI queries with wmic process get caption, commandline can reveal hidden processes & command-line arguments. Not all secrets hide in logs! #WindowsForensics #L33tKnowledge
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You can now use helix to calculate your equations! :D Added expression execution using Operator precedence parsing.
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[Swarms Memory][FAISS Example] 🔥 Deploy FAISS into production now with swarms-memory! ✅ Add, Get, Update, ✅ Custom preprocess, tokenize functions ✅ Extensive logging and monitoring! Get started now: https://buff.ly/4cvi1zr
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In Gtk 2.0 the cell toggled event, for example, passes the cell rendered and the path to the callba Check it out: https://lnkd.in/dKA_mCNJ Join the conversation! #gtk #gtktreeview
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Day44/160 #dsa #gfg #160days #Geeksforgeeks🚀 Optimizing Algorithm for Zero-Sum Triplets! 🚀 Just completed optimizing a solution for finding unique triplets in an array that sum up to zero. By utilizing the two-pointer technique and sorting, I was able to improve the efficiency of the algorithm and handle larger test cases effortlessly. 🔍 Key Takeaways: Sorting the array for efficient triplet discovery Using two-pointer technique for faster pair matching Handling uniqueness using a HashSet Time Complexity: O(n^2) for optimal performance
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[Swarms Memory][FAISS Example] 🔥 Deploy FAISS into production now with swarms-memory! ✅ Add, Get, Update, ✅ Custom preprocess, tokenize functions ✅ Extensive logging and monitoring! Get started now: https://buff.ly/4cvi1zr
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RunReveal Supercharges Monitoring with Stream Processing Discover how RunReveal can enhance your monitoring with stream processing. Get a sneak peek at their upcoming detection framework for efficient query running and real-time event stream analysis. Stay ahead of the game! https://lnkd.in/gRzKyyRK #StreamProcessing #Monitoring #DetectionFramework #EfficiencyBoost #RealTimeAnalysis #EventStream #QueryRunning #StayAhead #DataAnalysis #RunReveal
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Let's talk about collection info counts in Qdrant! 📊 Did you know the following numbers are approximate? Here's what they mean: - `𝘱𝘰𝘪𝘯𝘵𝘴_𝘤𝘰𝘶𝘯𝘵`: total objects (vectors + payloads) in collection - `𝘷𝘦𝘤𝘵𝘰𝘳𝘴_𝘤𝘰𝘶𝘯𝘵`: total vectors (useful when you have multiple vectors per point) - `𝘪𝘯𝘥𝘦𝘹𝘦𝘥_𝘷𝘦𝘤𝘵𝘰𝘳𝘴_𝘤𝘰𝘶𝘯𝘵`: vectors stored in HNSW/sparse index 🔍 ⚡️ Pro tip: These numbers may temporarily differ from what you expect due to internal optimizations. For exact counts, use the count API instead! Learn more: https://buff.ly/4fYoOTf
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Thanks for sharing Erika Cardenas, Weaviate 🙌 Automated prompt engineering is evolving and reducing time for AI engineers, with it comes the need for observability solutions. Check-out how we can help with that via the link in the post below. Want to get support on your use-case? Schedule a call with us via this link: https://lnkd.in/ePsEVZRZ? and add "Auto-prompt-engineering" in the notes to get the right Expert on the call. 🧑💻
New LangWatch Recipe thanks to Rogério Chaves 🍽 Automated prompt engineering requires new observability tools. LangWatch tracks the performance of each prompt paraphrasing + few-shot examples with optimizers like MIPRO. It also supports DSPy program tracing. Check out the notebook where Rogerio builds a DSPy program using Weaviate! Notebook: https://lnkd.in/edYPGfHh LangWatch recipe: https://lnkd.in/etWBHcQ5
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David Sudia, Senior Product Engineer at Teleport, explores promising tools from the CNCF Sandbox. He highlights Cartography for its ability to visualize complex system relationships, Eraser which enhances security maintenance by automatically removing vulnerable container images, and K3s which simplifies local Kubernetes development. These tools represent different approaches to solving key challenges in cluster management, from system visualization to security automation. Watch the full interview: https://ku.bz/KGLswKTsh
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AI/Data Scientist | AI Agent Architect | eDiscovery Expert
1moOh wow. KAG is key.