Paper
Vector Search Explained | Weaviate
Learn about vector search, a technique that uses mathematical representations of data to find similar items in large data sets.
HNSW
Concept
SmolAgents— Grocery Finder
A complete walkthrough for building a code-generating AI agent that recommends grocery items by querying SurrealDB's HNSW vector index.
ExampleNirDiamant/agents-towards-production: This repository delivers end-to-end, code-first tutorials covering every layer of production-grade GenAI agents, guiding you from spark to scale with proven patterns and reusable blueprints for real-world launches.
This repository delivers end-to-end, code-first tutorials covering every layer of production-grade GenAI agents, guiding you from spark to scale with proven patterns and reusable blueprints for re...
Tutorial
Computer Use
Agentic GraphRAG for Commercial Contracts | Towards Data Science
Structuring legal information as a knowledge graph to increase the answer accuracy using a LangGraph agent
Design Pattern
Mastering RAG: How to Select A Reranking Model
Choosing the best reranking model for your RAG-based QA system can be tricky. This blog post simplifies RAG reranking model selection, helping you pick the right one to optimize your system's performance.
Design Pattern
Concept
How we built our multi-agent research system \ Anthropic
On the the engineering challenges and lessons learned from building Claude's Research system
Design Pattern
Jason Zhou (@jasonzhou1993) on X
After 1 hr research,
Here are the best open source 'General agent' projects:
- Suna: https://t.co/BRsQToXL9P
- Deer-flow from Bytedance: https://t.co/4zwuRKaNFZ
- Google-gemini-search: https://t.co/iFIMgBxfeg
- Langchanin open deep search:
Concept
Cognition | Don’t Build Multi-Agents
Frameworks for LLM Agents have been surprisingly disappointing. I want to offer some principles for building agents based on our own trial & error, and explain why some tempting ideas are actually quite bad in practice.
Concept
Contradiction Detection in RAG Systems: Evaluating LLMs as Context Validators for Improved Information Consistency
Comprehensive Guide on Reranker for RAG
Explore how reranker for RAG systems by refining results, reducing hallucinations, and improving relevance and accuracy.
Fine-Tuning Cohere's Reranker | Weaviate
Learn how to fine-tune Cohere's reranker and generate synthetic data using DSPy!
RankZephyr
TutorialPassionNet: An Innovative Framework for Duplicate and Conflicting Requirements Identification
Alternative Approaches
Escape Prompt Hell With These 8 Must-have Open-source Tools | HackerNoon
Discover 8 powerful tools transforming prompt engineering from trial-and-error into scalable systems—featuring visual workflows, auto-tuned prompts, and memory-
Prompt Engineering
Paper
RAG is dead, long live agentic retrieval — LlamaIndex - Build Knowledge Assistants over your Enterprise Data
LlamaIndex is a simple, flexible framework for building knowledge assistants using LLMs connected to your enterprise data.
Concept
Semantic Chunking for RAG: Better Context, Better Results
Explore how semantic chunking enhances RAG systems by improving context, precision, and performance through optimized chunking strategies and advanced tools.
Design Pattern
NirDiamant/RAG_Techniques: This repository showcases various advanced techniques for Retrieval-Augmented Generation (RAG) systems. RAG systems combine information retrieval with generative models to provide accurate and contextually rich responses.
This repository showcases various advanced techniques for Retrieval-Augmented Generation (RAG) systems. RAG systems combine information retrieval with generative models to provide accurate and cont...
Example
Ebook
Create custom model serving endpoints | Databricks Documentation
Learn how to create and configure model serving endpoints that serve custom models.
Databricks Certified Generative AI Engineer Associate
Evaluation Driven Development for Agentic Systems.
My step-by-step approach for building and evolving Agentic Systems that work.
Design Pattern12 Factor Agents: What are the principles we can use to build LLM-powered software that is actually good enough to put in the hands of production customers?
What are the principles we can use to build LLM-powered software that is actually good enough to put in the hands of production customers? - humanlayer/12-factor-agents
Aura Graph Analytics: A Technical Deep Dive - Graph Database & Analytics
Take a deep dive into Neo4j Aura Graph Analytics, and learn how to run PageRank, community detection, and other algorithms directly in your workflow.
Deep Dive
Dual Approaches to Building Knowledge Graphs: Traditional Techniques or LLMs
Knowledge graphs are powerful tools for representing relationships between entities in a structured format. They are widely used in various…
Concept
Creating Knowledge Graphs from Unstructured Data - Developer Guides
Tutorial
From Zero to GenAI Hero: Building Your GenAI App with HuggingFace and Databricks | Databricks Blog
A comprehensive guide to building a GenAI app using a HuggingFace model, MLflow, Unity Catalog and Databricks Apps, covering setup, development, and deployment.
Memory