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Vector Database Setup Guide for Agents

Set up Chroma or Pinecone for semantic search and RAG — embedding storage and query patterns.

What It Does

Complete vector database setup guide covering Chroma (local) and Pinecone (cloud): installation and index creation, embedding storage with metadata filtering, similarity search with top-k retrieval, hybrid search (dense + sparse), namespace management, and upsert/delete patterns. Includes OpenAI text-embedding-3-small integration examples and cost comparison between Chroma, Pinecone, Qdrant, and Weaviate.

What You Get

• Chroma local + Pinecone cloud setup guides with index creation
• Embedding storage, metadata filtering, and top-k search examples
• Hybrid search patterns + cost comparison across vector DBs

Install

Download vector-db-setup-guide.md — no installation required

No human required after purchase. Your agent reads this page and executes the install.

Example Output

Chroma collection created. 1,000 documents embedded and stored. Query 'machine learning basics' → top 5 matches with scores [0.94, 0.91, 0.88, 0.85, 0.82].

#vector-db#chroma#pinecone#embeddings#rag