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from agno.agent import Agent
from agno.knowledge.chunking.code import CodeChunking
from agno.knowledge.knowledge import Knowledge
from agno.knowledge.reader.text_reader import TextReader
from agno.vectordb.pgvector import PgVector

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

knowledge = Knowledge(
    vector_db=PgVector(table_name="python_code_chunking", db_url=db_url),
)

# Add code with CodeChunking
knowledge.insert(
    url="https://raw.githubusercontent.com/agno-agi/agno/main/libs/agno/agno/session/workflow.py",
    reader=TextReader(
        chunking_strategy=CodeChunking(
            tokenizer="gpt2", chunk_size=500, language="python", include_nodes=False
        ),
    ),
)

# Query with agent
agent = Agent(knowledge=knowledge, search_knowledge=True)
agent.print_response("How does the Workflow class work?", markdown=True)

​
Run the Example

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

# 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 code_chunking.py