Examples
- Examples
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Models
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Vector Databases
MongoDB Integration
Code
cookbook/agent_concepts/vector_dbs/mongodb.py
from agno.agent import Agent
from agno.knowledge.pdf_url import PDFUrlKnowledgeBase
from agno.vectordb.mongodb import MongoDb
mdb_connection_string = "mongodb://ai:ai@localhost:27017/ai?authSource=admin"
knowledge_base = PDFUrlKnowledgeBase(
urls=["https://agno-public.s3.amazonaws.com/recipes/ThaiRecipes.pdf"],
vector_db=MongoDb(
collection_name="recipes",
db_url=mdb_connection_string,
wait_until_index_ready=60,
wait_after_insert=300,
),
)
knowledge_base.load(recreate=True)
agent = Agent(knowledge=knowledge_base, show_tool_calls=True)
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 Agent
python cookbook/agent_concepts/vector_dbs/mongodb.py
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