Chroma - Upsonic AI

Overview

ChromaDB is an open-source vector database designed for embedding search and similarity matching. It supports embedded, local, and cloud deployments with HNSW and FLAT index types. Provider Class: ChromaProvider
Config Class: ChromaConfig

Install

Install the Chroma optional dependency group:

  uv pip install "upsonic[chroma]"

Examples

from upsonic import Agent, Task, KnowledgeBase
from upsonic.embeddings import OpenAIEmbedding, OpenAIEmbeddingConfig
from upsonic.vectordb import ChromaProvider, ChromaConfig, ConnectionConfig, Mode, HNSWIndexConfig

# Setup embedding provider
embedding = OpenAIEmbedding(OpenAIEmbeddingConfig())

# Embedded mode (local file storage)
config = ChromaConfig(
    collection_name="my_collection",
    vector_size=1536,
    connection=ConnectionConfig(mode=Mode.EMBEDDED, db_path="./chroma_db"),
    index=HNSWIndexConfig(m=16, ef_construction=200)
)
vectordb = ChromaProvider(config)

# Create knowledge base
kb = KnowledgeBase(
    sources="document.pdf",
    embedding_provider=embedding,
    vectordb=vectordb
)

# Use with Agent
agent = Agent("anthropic/claude-sonnet-4-5")
task = Task(
    description="What is this document about?",
    context=[kb]
)
result = agent.do(task)

Parameters

Base Parameters (from BaseVectorDBConfig)

Parameter	Type	Description	Default	Required
`collection_name`	`str`	Name of the collection	`"default_collection"`	No
`vector_size`	`int`	Dimension of vectors	-	Yes
`distance_metric`	`DistanceMetric`	Similarity metric (`COSINE`, `EUCLIDEAN`, `DOT_PRODUCT`)	`COSINE`	No
`recreate_if_exists`	`bool`	Recreate collection if it exists	`False`	No
`default_top_k`	`int`	Default number of results	`10`	No
`default_similarity_threshold`	`Optional[float]`	Minimum similarity score (0.0-1.0)	`None`	No
`dense_search_enabled`	`bool`	Enable dense vector search	`True`	No
`full_text_search_enabled`	`bool`	Enable full-text search	`True`	No
`hybrid_search_enabled`	`bool`	Enable hybrid search	`True`	No
`default_hybrid_alpha`	`float`	Default alpha for hybrid search (0.0-1.0)	`0.5`	No
`default_fusion_method`	`Literal['rrf', 'weighted']`	Default fusion method for hybrid search	`'weighted'`	No
`provider_name`	`Optional[str]`	Provider name	`None`	No
`provider_description`	`Optional[str]`	Provider description	`None`	No
`provider_id`	`Optional[str]`	Provider ID	`None`	No
`default_metadata`	`Optional[Dict[str, Any]]`	Default metadata for all records	`None`	No
`indexed_fields`	`Optional[List[Union[str, Dict[str, Any]]]]`	Fields to index for filtering	`None`	No

Chroma-Specific Parameters

Parameter	Type	Description	Default	Required
`connection`	`ConnectionConfig`	Connection configuration (mode, db_path, etc.)	-	Yes
`index`	`Union[HNSWIndexConfig, FlatIndexConfig]`	Index type configuration	`HNSWIndexConfig()`	No
`tenant`	`Optional[str]`	Tenant name for multi-tenancy	`None`	No
`database`	`Optional[str]`	Database name	`None`	No

ConnectionConfig Parameters

Parameter	Type	Description	Default	Required
`mode`	`Mode`	Connection mode (`EMBEDDED`, `LOCAL`, `CLOUD`, `IN_MEMORY`)	-	Yes
`db_path`	`Optional[str]`	Path for embedded/local storage	`None`	Required for `EMBEDDED`
`host`	`Optional[str]`	Host address	`None`	Required for `LOCAL`
`port`	`Optional[int]`	Port number	`None`	Required for `LOCAL`
`api_key`	`Optional[SecretStr]`	API key for cloud/local	`None`	Required for `CLOUD`
`url`	`Optional[str]`	Full connection URL	`None`	No
`use_tls`	`bool`	Use TLS encryption	`True`	No
`grpc_port`	`Optional[int]`	gRPC port	`None`	No
`prefer_grpc`	`bool`	Prefer gRPC over HTTP	`False`	No
`https`	`Optional[bool]`	Use HTTPS	`None`	No
`prefix`	`Optional[str]`	URL path prefix	`None`	No
`timeout`	`Optional[float]`	Request timeout in seconds	`None`	No
`location`	`Optional[str]`	Special location string	`None`	No

​Overview

​Install

​Examples

​Parameters

​Base Parameters (from BaseVectorDBConfig)

​Chroma-Specific Parameters

​ConnectionConfig Parameters

Overview

Install

Examples

Parameters

Base Parameters (from BaseVectorDBConfig)

Chroma-Specific Parameters

ConnectionConfig Parameters