custom_retriever.py
"""
Custom Retriever
=============================
Use knowledge_retriever to provide a custom retrieval function.
Instead of using a Knowledge instance, you can supply your own callable
that returns documents. The agent will use it as its search_knowledge_base tool.
"""
from typing import List, Optional
from agno.agent import Agent
from agno.models.openai import OpenAIResponses
# ---------------------------------------------------------------------------
# Custom Retriever Function
# ---------------------------------------------------------------------------
# A simple in-memory retriever for demonstration.
# In production, this could call an external API, database, or search engine.
DOCUMENTS = [
{
"title": "Python Basics",
"content": "Python is a high-level programming language known for its readability.",
},
{
"title": "TypeScript Intro",
"content": "TypeScript adds static typing to JavaScript.",
},
{
"title": "Rust Overview",
"content": "Rust is a systems language focused on safety and performance.",
},
]
def my_retriever(
query: str, num_documents: Optional[int] = None, **kwargs
) -> Optional[List[dict]]:
"""Search documents by simple keyword matching."""
query_lower = query.lower()
results = [
doc
for doc in DOCUMENTS
if query_lower in doc["content"].lower() or query_lower in doc["title"].lower()
]
if num_documents:
results = results[:num_documents]
return results if results else None
# ---------------------------------------------------------------------------
# Create Agent
# ---------------------------------------------------------------------------
agent = Agent(
model=OpenAIResponses(id="gpt-5.2"),
# Use a custom retriever instead of a Knowledge instance
knowledge_retriever=my_retriever,
# search_knowledge is True by default when knowledge_retriever is set
markdown=True,
)
# ---------------------------------------------------------------------------
# Run Agent
# ---------------------------------------------------------------------------
if __name__ == "__main__":
agent.print_response(
"Tell me about Python.",
stream=True,
)
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 openai
3
Export your OpenAI API key
export OPENAI_API_KEY="your_openai_api_key_here"
$Env:OPENAI_API_KEY="your_openai_api_key_here"
4
Run the example
Save the code above as
custom_retriever.py, then run:python custom_retriever.py