knowledge.py
"""Run `uv pip install ddgs sqlalchemy pgvector pypdf anthropic openai` to install dependencies."""
from agno.agent import Agent
from agno.knowledge.embedder.openai import OpenAIEmbedder
from agno.knowledge.knowledge import Knowledge
from agno.models.vertexai.claude import Claude
from agno.vectordb.pgvector import PgVector
# ---------------------------------------------------------------------------
# Create Agent
# ---------------------------------------------------------------------------
db_url = "postgresql+psycopg://ai:ai@localhost:5532/ai"
knowledge = Knowledge(
vector_db=PgVector(
table_name="recipes",
db_url=db_url,
embedder=OpenAIEmbedder(),
),
)
# Add content to the knowledge
knowledge.insert(url="https://agno-public.s3.amazonaws.com/recipes/ThaiRecipes.pdf")
agent = Agent(
model=Claude(id="claude-sonnet-4@20250514"),
knowledge=knowledge,
)
agent.print_response("How to make Thai curry?", markdown=True)
# ---------------------------------------------------------------------------
# Run Agent
# ---------------------------------------------------------------------------
if __name__ == "__main__":
pass
Run the Example
1
Set up your virtual environment
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 "anthropic[vertex]" "psycopg[binary]" beautifulsoup4 openai pgvector pypdf sqlalchemy
3
Export environment variables
export ANTHROPIC_VERTEX_PROJECT_ID="your_anthropic_vertex_project_id_here"
export CLOUD_ML_REGION="your_cloud_ml_region_here"
export OPENAI_API_KEY="your_openai_api_key_here"
$Env:ANTHROPIC_VERTEX_PROJECT_ID="your_anthropic_vertex_project_id_here"
$Env:CLOUD_ML_REGION="your_cloud_ml_region_here"
$Env:OPENAI_API_KEY="your_openai_api_key_here"
4
Authenticate with Google Cloud
Sign in with Application Default Credentials:
gcloud auth application-default login
5
Run PgVector
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
6
Run the example
Save the code above as
knowledge.py, then run:python knowledge.py