Skip to main content

​
Code

cookbook/knowledge/vector_db/mongo_db/mongo_db.py

from agno.agent import Agent
from agno.knowledge.knowledge import Knowledge
from agno.vectordb.mongodb import MongoVectorDb

mdb_connection_string = "mongodb://localhost:27017"
knowledge = Knowledge(
    vector_db=MongoVectorDb(
        collection_name="recipes",
        db_url=mdb_connection_string,
        search_index_name="recipes",
    ),
)

knowledge.add_content(
    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("How to make Thai curry?", markdown=True)

​
Usage

1

Create a virtual environment

Open the Terminal and create a python virtual environment.
python3 -m venv .venv
source .venv/bin/activate
2

Install libraries

pip install -U pymongo pypdf openai agno
3

Run MongoDB

docker run -d \
--name local-mongo \
-p 27017:27017 \
-e MONGO_INITDB_ROOT_USERNAME=mongoadmin \
-e MONGO_INITDB_ROOT_PASSWORD=secret \
mongo
4

Run Agent

python cookbook/knowledge/vector_db/mongo_db/mongo_db.py