# Chroma

## Docs

- [CLI Commands](https://mintlify.wiki/chroma-core/chroma/api/cli/commands.md): Complete reference for the Chroma CLI commands and options
- [CLI Configuration](https://mintlify.wiki/chroma-core/chroma/api/cli/configuration.md): Configure the Chroma CLI with profiles, environment variables, and configuration files
- [Go Client Overview](https://mintlify.wiki/chroma-core/chroma/api/go/overview.md): Official Go client for Chroma - the AI-native open-source embedding database
- [Client](https://mintlify.wiki/chroma-core/chroma/api/javascript/client.md): JavaScript client API reference for ChromaClient, CloudClient, and AdminClient
- [Collection](https://mintlify.wiki/chroma-core/chroma/api/javascript/collection.md): JavaScript Collection API reference for managing and querying embeddings
- [Types](https://mintlify.wiki/chroma-core/chroma/api/javascript/types.md): TypeScript type definitions for the Chroma JavaScript client
- [Client API](https://mintlify.wiki/chroma-core/chroma/api/python/client.md): Python client for connecting to Chroma and managing collections
- [Collection API](https://mintlify.wiki/chroma-core/chroma/api/python/collection.md): Collection methods for adding, querying, and managing documents
- [Search API](https://mintlify.wiki/chroma-core/chroma/api/python/search.md): Advanced hybrid search with filtering, ranking, and aggregation
- [Type Definitions](https://mintlify.wiki/chroma-core/chroma/api/python/types.md): Type definitions and data structures for the Chroma Python API
- [Collections](https://mintlify.wiki/chroma-core/chroma/concepts/collections.md): Understanding Chroma collections - the containers for your embeddings
- [Embeddings](https://mintlify.wiki/chroma-core/chroma/concepts/embeddings.md): Understanding embeddings and how Chroma handles vector representations
- [Metadata](https://mintlify.wiki/chroma-core/chroma/concepts/metadata.md): Understanding metadata in Chroma and how to filter on it
- [Querying](https://mintlify.wiki/chroma-core/chroma/concepts/querying.md): Understand how to query your Chroma collections with similarity search and filtering
- [Cloud Provider Deployments](https://mintlify.wiki/chroma-core/chroma/deployment/cloud-providers.md): Deploy Chroma on AWS, GCP, and Azure using infrastructure as code
- [Docker Deployment](https://mintlify.wiki/chroma-core/chroma/deployment/docker.md): Deploy Chroma using Docker and Docker Compose
- [Kubernetes Deployment](https://mintlify.wiki/chroma-core/chroma/deployment/kubernetes.md): Deploy Chroma on Kubernetes using Helm charts and manifests
- [Deployment Overview](https://mintlify.wiki/chroma-core/chroma/deployment/overview.md): Understanding Chroma's deployment modes and choosing the right option for your use case
- [Authentication](https://mintlify.wiki/chroma-core/chroma/guides/authentication.md): Secure your Chroma deployment with authentication
- [Client-Server Deployment](https://mintlify.wiki/chroma-core/chroma/guides/client-server-mode.md): Deploy Chroma in client-server mode for production applications
- [Embedding Functions](https://mintlify.wiki/chroma-core/chroma/guides/embedding-functions.md): Use built-in and custom embedding functions in Chroma
- [Filtering and Where Clauses](https://mintlify.wiki/chroma-core/chroma/guides/filtering.md): Filter query results using metadata and document content
- [Hybrid Search](https://mintlify.wiki/chroma-core/chroma/guides/hybrid-search.md): Combine vector similarity and full-text search for better results
- [Multimodal Data](https://mintlify.wiki/chroma-core/chroma/guides/multimodal.md): Work with images, text, and other data types in Chroma
- [Installation](https://mintlify.wiki/chroma-core/chroma/installation.md): Install Chroma for Python, JavaScript, Go, or Docker
- [Cohere embeddings](https://mintlify.wiki/chroma-core/chroma/integrations/cohere.md): Use Cohere's multilingual embedding models with Chroma for global semantic search
- [Hugging Face embeddings](https://mintlify.wiki/chroma-core/chroma/integrations/huggingface.md): Use Hugging Face models with Chroma for flexible, open-source embeddings
- [LangChain integration](https://mintlify.wiki/chroma-core/chroma/integrations/langchain.md): Use Chroma as a vector store with LangChain for building LLM applications
- [LlamaIndex integration](https://mintlify.wiki/chroma-core/chroma/integrations/llamaindex.md): Use Chroma as a vector store with LlamaIndex for building data-driven LLM applications
- [OpenAI embeddings](https://mintlify.wiki/chroma-core/chroma/integrations/openai.md): Use OpenAI's embedding models with Chroma for semantic search and retrieval
- [Sentence Transformers](https://mintlify.wiki/chroma-core/chroma/integrations/sentence-transformers.md): Chroma's default embedding function powered by Sentence Transformers
- [Introduction](https://mintlify.wiki/chroma-core/chroma/introduction.md): Chroma - the open-source search engine for AI
- [Configuration](https://mintlify.wiki/chroma-core/chroma/operations/configuration.md): Configure Chroma server and client settings
- [Schema Migrations](https://mintlify.wiki/chroma-core/chroma/operations/migrations.md): Manage database schema migrations and version upgrades
- [Observability](https://mintlify.wiki/chroma-core/chroma/operations/observability.md): Monitor Chroma with OpenTelemetry, metrics, and logging
- [Performance Tuning](https://mintlify.wiki/chroma-core/chroma/operations/performance.md): Optimize Chroma for speed, throughput, and resource efficiency
- [Quickstart](https://mintlify.wiki/chroma-core/chroma/quickstart.md): Get started with Chroma in under 5 minutes