Code Chunking

CodeChunking wraps Chonkie's AST-based code chunker. Configure its tokenizer, token limit, and source language.

Code chunking supports several built-in tokenizers or a custom Tokenizer instance.

Create a Python file

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),
)

knowledge.insert(
    url="https://raw.githubusercontent.com/agno-agi/agno/v2.7.2/libs/agno/agno/workflow/workflow.py",
    reader=TextReader(
        chunking_strategy=CodeChunking(
            tokenizer="character",
            chunk_size=500,
            language="python",
        ),
    ),
)

agent = Agent(knowledge=knowledge, search_knowledge=True)
agent.print_response("How does Workflow run its steps?", markdown=True)

Set up your virtual environment

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

Install dependencies

uv pip install -U agno sqlalchemy psycopg pgvector "chonkie[code]" openai

Export your OpenAI API key

Set OpenAI Key

Set your OPENAI_API_KEY as an environment variable. You can get one from OpenAI.

export OPENAI_API_KEY=sk-***

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

Run the script

python code_chunking.py

Code Chunking Params

Parameter	Type	Default	Description
`tokenizer`	`Union[str, TokenizerProtocol]`	`"character"`	The tokenizer for measuring chunk sizes. Supports several built-in tokenizers or a custom `Tokenizer` instance.
`chunk_size`	`int`	`2048`	Maximum size of each chunk in tokens (based on the selected tokenizer).
`language`	`Union[Literal["auto"], Any]`	`"auto"`	The programming language to parse. Use `"auto"` for automatic detection or specify a tree-sitter language name (e.g., `"python"`, `"javascript"`, `"go"`, `"rust"`).
`include_nodes`	`bool`	`False`	Whether to include AST nodes. Note: Chonkie's base Chunk type does not store node information.
`chunker_params`	`Optional[Dict[str, Any]]`	`None`	Additional parameters to pass directly to Chonkie's CodeChunker.