Agentic Chunking
Split documents with AgenticChunking, which uses a model to find natural breakpoints.
AgenticChunking asks a model to choose each split position within max_chunk_size characters. It uses the size limit when the model call fails or the response cannot be parsed as an integer. Positions above the limit are clamped.
Create a Python file
from agno.agent import Agent
from agno.knowledge.chunking.agentic import AgenticChunking
from agno.knowledge.knowledge import Knowledge
from agno.knowledge.reader.pdf_reader import PDFReader
from agno.vectordb.pgvector import PgVector
db_url = "postgresql+psycopg://ai:ai@localhost:5532/ai"
knowledge = Knowledge(
vector_db=PgVector(table_name="recipes_agentic_chunking", db_url=db_url),
)
knowledge.insert(
url="https://agno-public.s3.amazonaws.com/recipes/ThaiRecipes.pdf",
reader=PDFReader(
name="Agentic Chunking Reader",
chunking_strategy=AgenticChunking(),
),
)
agent = Agent(
knowledge=knowledge,
search_knowledge=True,
)
agent.print_response("How do I make Thai curry?", markdown=True)Set up your virtual environment
uv venv --python 3.12
source .venv/bin/activateInstall dependencies
uv pip install -U agno openai pypdf sqlalchemy psycopg pgvectorExport 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:18Run the script
python agentic_chunking.pyCustom Prompts
from agno.knowledge.chunking.agentic import AgenticChunking
AgenticChunking(
custom_prompt="Split at major section boundaries. Keep complete clauses together.",
max_chunk_size=3000,
)custom_prompt is inserted into Agno's chunking instructions. For the chunker to make progress, the model must return a positive integer.
Set max_chunk_size explicitly when using a custom prompt so the model receives the intended limit.
Agentic Chunking Params
| Parameter | Type | Default | Description |
|---|---|---|---|
model | Optional[Union[Model, str]] | None | The model to use for chunking. Accepts a Model instance or a model ID string. Defaults to OpenAIChat with gpt-5.4-mini when not set. |
max_chunk_size | Optional[int] | None | The maximum size of each chunk. Defaults to 5000 characters when not set. |
custom_prompt | Optional[str] | None | Personalized instructions for determining chunk breakpoints. |