Multiple Knowledge Bases

Serve a PgVector-backed knowledge agent and manage documents through AgentOS knowledge endpoints.

multiple_knowledge_bases.py

"""
Multiple Knowledge Bases
========================

Demonstrates multiple knowledge bases.
"""

from agno.agent import Agent
from agno.db.json import JsonDb
from agno.knowledge.knowledge import Knowledge
from agno.models.openai import OpenAIChat
from agno.os import AgentOS
from agno.vectordb.pgvector import PgVector

# ---------------------------------------------------------------------------
# Create Example
# ---------------------------------------------------------------------------

db_url = "postgresql+psycopg://ai:ai@localhost:5532/ai"


vector_db = PgVector(table_name="vectors", db_url=db_url)
secondary_vector_db = PgVector(table_name="more_vectors", db_url=db_url)
contents_db = JsonDb(db_path="./agno_json_data", knowledge_table="main_knowledge")
secondary_contents_db = JsonDb(
    db_path="./agno_json_data_2", knowledge_table="secondary_knowledge"
)

# Create knowledge bases
knowledge_base = Knowledge(
    name="Main Knowledge Base",
    description="A simple knowledge base",
    contents_db=contents_db,
    vector_db=vector_db,
)

main_agent = Agent(
    name="Main Agent",
    model=OpenAIChat(id="gpt-4o"),
    knowledge=knowledge_base,
    add_datetime_to_context=True,
    markdown=True,
    db=contents_db,
)

agent_os = AgentOS(
    description="Example app for basic agent with knowledge capabilities",
    id="knowledge-demo",
    agents=[main_agent],
)
app = agent_os.get_app()

# ---------------------------------------------------------------------------
# Run Example
# ---------------------------------------------------------------------------

if __name__ == "__main__":
    """ Run your AgentOS:
    Now you can interact with your knowledge base using the API. Examples:
    - http://localhost:8001/knowledge/{id}/documents
    - http://localhost:8001/knowledge/{id}/documents/123
    - http://localhost:8001/knowledge/{id}/documents?agent_id=123
    - http://localhost:8001/knowledge/{id}/documents?limit=10&page=0&sort_by=created_at&sort_order=desc
    """
    agent_os.serve(app="multiple_knowledge_bases:app", reload=True)

Run the Example

1. Set up your virtual environment

   Mac

   uv venv --python 3.12
   source .venv/bin/activate
   

   uv venv --python 3.12
   .venv\Scripts\activate
   
2. Install dependencies

   uv pip install -U "agno[os]" "psycopg[binary]" openai pgvector
   
3. Export your OpenAI API key

   Mac/Linux

   export OPENAI_API_KEY="your_openai_api_key_here"
   

   $Env:OPENAI_API_KEY="your_openai_api_key_here"
   
4. Run PgVector

   macOS / Linux

   docker run -d \
     -e POSTGRES_DB=ai \
     -e POSTGRES_USER=ai \
     -e POSTGRES_PASSWORD=ai \
     -e PGDATA=/var/lib/postgresql \
     -v pgvolume:/var/lib/postgresql \
     -p 5532:5432 \
     --name pgvector \
     agnohq/pgvector:18
   

   docker run -d `
     -e POSTGRES_DB=ai `
     -e POSTGRES_USER=ai `
     -e POSTGRES_PASSWORD=ai `
     -e PGDATA=/var/lib/postgresql `
     -v pgvolume:/var/lib/postgresql `
     -p 5532:5432 `
     --name pgvector `
     agnohq/pgvector:18
   
5. Run the example

   Save the code above as multiple_knowledge_bases.py, then run:

   python multiple_knowledge_bases.py
   

Full source: cookbook/05_agent_os/advanced_demo/multiple_knowledge_bases.py