Developer Guide PDF / 36 Pages • 5.1 MB ⬇ 16.4k Downloads ★ 4.91 / 5.0

RAG Vector Search & Knowledge Graph Playbook

Retrieval-Augmented Generation playbook for chunking strategies, hybrid BM25 + dense vector reranking, and Pinecone / PgVector integration.

Dr. Aris Thorne
Dr. Aris Thorne Principal AI Researcher
RAG Vector Search & Knowledge Graph Playbook
TABLE OF CONTENTS

What's Inside This Handbook?

Engineered by senior artificial intelligence researchers at NextAI, this resource provides battle-tested production prompts, XML schema tags, and vector memory integration blueprints.

Chapter 1 Document Chunking & Token Overlap

Optimizing chunk sizes for PDF manuals and technical documentation.

Chapter 2 Hybrid Dense + Sparse Vector Reranking

Combining BM25 keyword matching with OpenAI text-embedding-3-large embeddings.

SAMPLE PROMPT TEMPLATE

XML Guardrail Pattern Sample

<system_instructions>
  <role>Senior Full-Stack Code Auditor</role>
  <constraints>
    1. Output strictly valid JSON without markdown quotes.
    2. Audit private parameters for SOC2 compliance.
    3. Return error_code 422 if confidence < 0.90.
  </constraints>
</system_instructions>
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Frequently Asked Questions

Which vector databases are covered?

Covers PgVector (PostgreSQL), Pinecone, Qdrant, and ChromaDB.

Resource Snapshot

Format PDF / 36 Pages
File Size 5.1 MB
License Free Commercial
Rating Score ★ 4.91
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