Custom Retriever

1"""
2Custom Retriever
3=============================
4
5Use knowledge_retriever to provide a custom retrieval function.
6
7Instead of using a Knowledge instance, you can supply your own callable
8that returns documents. The agent will use it as its search_knowledge_base tool.
9"""
10
11from typing import List, Optional
12
13from kern.agent import Agent
14from kern.models.openai import OpenAIResponses
15
16# ---------------------------------------------------------------------------
17# Custom Retriever Function
18# ---------------------------------------------------------------------------
19# A simple in-memory retriever for demonstration.
20# In production, this could call an external API, database, or search engine.
21DOCUMENTS = [
22    {
23        "title": "Python Basics",
24        "content": "Python is a high-level programming language known for its readability.",
25    },
26    {
27        "title": "TypeScript Intro",
28        "content": "TypeScript adds static typing to JavaScript.",
29    },
30    {
31        "title": "Rust Overview",
32        "content": "Rust is a systems language focused on safety and performance.",
33    },
34]
35
36
37def my_retriever(
38    query: str, num_documents: Optional[int] = None, **kwargs
39) -> Optional[List[dict]]:
40    """Search documents by simple keyword matching."""
41    query_lower = query.lower()
42    results = [
43        doc
44        for doc in DOCUMENTS
45        if query_lower in doc["content"].lower() or query_lower in doc["title"].lower()
46    ]
47    if num_documents:
48        results = results[:num_documents]
49    return results if results else None
50
51
52# ---------------------------------------------------------------------------
53# Create Agent
54# ---------------------------------------------------------------------------
55agent = Agent(
56    model=OpenAIResponses(id="gpt-5.2"),
57    # Use a custom retriever instead of a Knowledge instance
58    knowledge_retriever=my_retriever,
59    # search_knowledge is True by default when knowledge_retriever is set
60    markdown=True,
61)
62
63# ---------------------------------------------------------------------------
64# Run Agent
65# ---------------------------------------------------------------------------
66if __name__ == "__main__":
67    agent.print_response(
68        "Tell me about Python.",
69        stream=True,
70    )

1# Clone and setup repo
2git clone https://github.com/kern-ai/kern.git
3cd kern/cookbook/02_agents/07_knowledge
4
5# Create and activate virtual environment
6./scripts/demo_setup.sh
7source .venvs/demo/bin/activate
8
9python custom_retriever.py