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from agno.knowledge.knowledge import Knowledge
from agno.vectordb.pgvector import PgVector, SearchType

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

# Load knowledge base using vector search
vector_db = PgVector(table_name="recipes", db_url=db_url, search_type=SearchType.vector)
knowledge = Knowledge(
    name="Vector Search Knowledge Base",
    vector_db=vector_db,
)

knowledge.insert(
    url="https://agno-public.s3.amazonaws.com/recipes/ThaiRecipes.pdf",
)

# Run a vector-based query
results = vector_db.search("chicken coconut soup", limit=5)
print("Vector Search Results:", results)

​
Run the Example

# Clone and setup repo
git clone https://github.com/agno-agi/agno.git
cd agno/cookbook/07_knowledge/search_type

# Create and activate virtual environment
./scripts/demo_setup.sh
source .venvs/demo/bin/activate

# Optiona: Run PgVector (needs docker)
./cookbook/scripts/run_pgvector.sh

python vector_search.py