Milvus

Overview

Milvus is an open-source vector database built for scalable similarity search and AI applications. It supports embedded (Lite), local, and cloud deployments with advanced indexing options and consistency levels. Provider Class: MilvusProvider
Config Class: MilvusConfig

Dependencies

pip install "upsonic[rag]"

Examples

from upsonic import Agent, Task, KnowledgeBase
from upsonic.embeddings.openai_provider import OpenAIEmbeddingProvider
from upsonic.vectordb import MilvusProvider, MilvusConfig, ConnectionConfig, Mode, HNSWIndexConfig

# Setup embedding provider
embedding = OpenAIEmbeddingProvider(api_key="your-api-key")

# Embedded mode (Milvus Lite)
config = MilvusConfig(
    collection_name="my_collection",
    vector_size=1536,
    connection=ConnectionConfig(mode=Mode.EMBEDDED, db_path="./milvus_db"),
    index=HNSWIndexConfig(m=16, ef_construction=200),
    consistency_level="Bounded"
)
vectordb = MilvusProvider(config)

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

# Use with Agent
agent = Agent("openai/gpt-4o")
task = Task(
    description="Search the knowledge base",
    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
`auto_generate_content_id`	`bool`	Auto-generate content IDs	`True`	No
`indexed_fields`	`Optional[List[Union[str, Dict[str, Any]]]]`	Fields to index for filtering	`None`	No

Milvus-Specific Parameters

Parameter	Type	Description	Default	Required
`connection`	`ConnectionConfig`	Connection configuration (mode, db_path, etc.)	-	Yes
`index`	`IndexConfig`	Index type configuration (`HNSWIndexConfig`, `IVFIndexConfig`, `FlatIndexConfig`)	`HNSWIndexConfig()`	No
`consistency_level`	`Literal['Strong', 'Bounded', 'Session', 'Eventually']`	Consistency level	`'Bounded'`	No
`index_params`	`Optional[Dict[str, Any]]`	Additional index parameters (overrides automatic params)	`None`	No
`use_sparse_vectors`	`bool`	Enable sparse vector support (auto-enables `hybrid_search_enabled`)	`False`	No
`dense_vector_field`	`str`	Dense vector field name	`"dense_vector"`	No
`sparse_vector_field`	`str`	Sparse vector field name	`"sparse_vector"`	No
`search_params`	`Optional[Dict[str, Any]]`	Default search parameters	`None`	No
`rrf_k`	`int`	RRF ranker k parameter for hybrid search	`60`	No
`batch_size`	`int`	Batch size for upsert operations	`100`	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

GET STARTED

CONCEPTS

STARTING AN AGENT PROJECT

DEPLOYMENT

FURTHER READINGS

Overview

Dependencies

Examples

Parameters

Base Parameters (from BaseVectorDBConfig)

Milvus-Specific Parameters

ConnectionConfig Parameters

GET STARTED

CONCEPTS

STARTING AN AGENT PROJECT

DEPLOYMENT

FURTHER READINGS

​Overview

​Dependencies

​Examples

​Parameters

​Base Parameters (from BaseVectorDBConfig)

​Milvus-Specific Parameters

​ConnectionConfig Parameters

Overview

Dependencies

Examples

Parameters

Base Parameters (from BaseVectorDBConfig)

Milvus-Specific Parameters

ConnectionConfig Parameters