/chroma-integration

name: chroma-integration
description: Chroma local vector database setup and operations for development and production
allowed-tools:
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graph:
  domains: [domain:software-engineering]
  specializations: [specialization:ai-agents-conversational]
  skillAreas: [skill-area:retrieval-augmented-generation, skill-area:search-indexing]
  roles: [role:ml-engineer, role:backend-engineer]
  workflows: [workflow:ml-model-lifecycle, workflow:feature-development]

Chroma Integration Skill

Capabilities

• Set up Chroma (ephemeral, persistent, client-server)
• Create and manage collections
• Implement document ingestion with embeddings
• Configure metadata filtering
• Set up multi-tenant collections
• Implement where and where_document filters

Target Processes

• vector-database-setup
• rag-pipeline-implementation

Implementation Details

Deployment Modes

1. **Ephemeral**: In-memory for testing 2. **Persistent**: Local file-based storage 3. **Client-Server**: Chroma server deployment

Core Operations

• Collection creation with embedding functions
• Add/update/delete documents
• Query with filters
• Metadata management

Configuration Options

• Embedding function selection
• Persistence directory
• Distance metric (l2, ip, cosine)
• Collection metadata
• Server configuration

Best Practices

• Use persistent mode for development
• Deploy server mode for production
• Design metadata schema upfront
• Implement proper ID strategies

Dependencies

• chromadb
• langchain-chroma