​
Setup

pip install chromadb

​
Example

agent_with_knowledge.py
import asyncio

from agno.agent import Agent
from agno.knowledge.knowledge import Knowledge
from agno.vectordb.chroma import ChromaDb

# Create Knowledge Instance with ChromaDB
knowledge = Knowledge(
    name="Basic SDK Knowledge Base",
    description="Agno 2.0 Knowledge Implementation with ChromaDB",
    vector_db=ChromaDb(
        collection="vectors", path="tmp/chromadb", persistent_client=True
    ),
)

asyncio.run(
    knowledge.add_content_async(
        name="Recipes",
        url="https://agno-public.s3.amazonaws.com/recipes/ThaiRecipes.pdf",
        metadata={"doc_type": "recipe_book"},
    )
)

# Create and use the agent
agent = Agent(knowledge=knowledge)
agent.print_response("List down the ingredients to make Massaman Gai", markdown=True)

# Delete operations examples
vector_db = knowledge.vector_db
vector_db.delete_by_name("Recipes")
# or
vector_db.delete_by_metadata({"user_tag": "Recipes from website"})

Async Support ⚡

ChromaDB also supports asynchronous operations, enabling concurrency and leading to better performance.

async_chroma_db.py
# install chromadb - `pip install chromadb`

import asyncio

from agno.agent import Agent
from agno.knowledge.knowledge import Knowledge
from agno.vectordb.chroma import ChromaDb

# Initialize ChromaDB
vector_db = ChromaDb(collection="recipes", path="tmp/chromadb", persistent_client=True)

# Create knowledge base
knowledge = Knowledge(
    vector_db=vector_db,
)

# Create and use the agent
agent = Agent(knowledge=knowledge)

if __name__ == "__main__":
    # Comment out after first run
    asyncio.run(
        knowledge.add_content_async(url="https://docs.agno.com/introduction/agents.md")
    )

    # Create and use the agent
    asyncio.run(
        agent.aprint_response("What is the purpose of an Agno Agent?", markdown=True)
    )
Use add_content_async() and aprint_response() methods with asyncio.run() for non-blocking operations in high-throughput applications.

​
ChromaDb Params

ParameterTypeDefaultDescription
collectionstr-The name of the collection to use.
embedderEmbedderOpenAIEmbedder()The embedder to use for embedding document contents.
distanceDistancecosineThe distance metric to use.
pathstr"tmp/chromadb"The path where ChromaDB data will be stored.
persistent_clientboolFalseWhether to use a persistent ChromaDB client.

​
Developer Resources