Agent Description

Chroma is an open-source vector database that streamlines AI application development by managing embeddings, vector searches, and multi-modal data with integrated full-text search and metadata filtering. It supports Python and JavaScript SDKs, offering flexible deployment for local or cloud-based environments.

Key Features

• Stores and queries vector embeddings with default Sentence Transformers (all-MiniLM-L6-v2) or custom models like OpenAI and Cohere.
• Enables fast vector search with HNSW indexing for efficient nearest-neighbor retrieval.
• Supports full-text search for exact or partial text matches alongside semantic search.
• Facilitates metadata filtering to refine queries based on attributes like source or category.
• Handles multi-modal data, including text and images, with OpenCLIP embedding support.
• Deploys easily with pip for in-memory prototyping or Docker for persistent storage.
• Ensures SOC 2 compliance and scalability with backends like DuckDB or ClickHouse.

Use Cases

• Semantic Search: Enhances e-commerce search with 30% better relevance by combining vector and full-text search, per weaviate.io comparisons.
• RAG for LLMs: Powers chatbots with accurate context retrieval, as seen in LangChain integrations, reducing response times by 20%.
• Multi-Modal Retrieval: Enables media platforms to search text-image datasets, boosting engagement, per analyticsvidhya.com.
• Recommendation Systems: Supports personalized content delivery, improving user retention for streaming services, per projectpro.io.

Differentiation Factors

• Fully open-source with no vendor lock-in, unlike Pinecone’s proprietary model.
• Multi-modal support with OpenCLIP outperforms Qdrant’s text-focused approach.
• Lightweight pip installation and in-memory prototyping surpass Milvus’s complex setup.

Pricing Plans

• Starter: $0/month + usage Get up and running quickly. Free credits then usage-based pricing.
• Team: $250/month + usage Scale your production use cases. $100 credits then usage-based pricing.
• Enterprise: Custom For organizations prioritizing security, scale, support, and confidence

Frequently Aked Questions (FAQs)

• What is Chroma?
  Chroma is an open-source vector database for AI applications, managing embeddings, vector search, and multi-modal data with full-text search capabilities.
• Can Chroma handle non-text data?
  Yes, it supports multi-modal data like images using OpenCLIP embeddings, with audio and video support planned.
• How does Chroma integrate with LLMs?
  It integrates with LangChain, LlamaIndex, and embedding providers like OpenAI for RAG and semantic search.
• Is Chroma suitable for local development?
  Absolutely, it runs in-memory with pip install or via Docker for persistent local setups.