> ## Documentation Index
> Fetch the complete documentation index at: https://docs-v1.agno.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Reasoning Agent with Knowledge Tools

## Code

```python cookbook/reasoning/tools/knowledge_tools.py theme={null}

from agno.agent import Agent
from agno.embedder.openai import OpenAIEmbedder
from agno.knowledge.url import UrlKnowledge
from agno.models.openai import OpenAIChat
from agno.tools.knowledge import KnowledgeTools
from agno.vectordb.lancedb import LanceDb, SearchType

# Create a knowledge base containing information from a URL
agno_docs = UrlKnowledge(
    urls=["https://docs-v1.agno.com/llms-full.txt"],
    # Use LanceDB as the vector database and store embeddings in the `agno_docs` table
    vector_db=LanceDb(
        uri="tmp/lancedb",
        table_name="agno_docs",
        search_type=SearchType.hybrid,
        embedder=OpenAIEmbedder(id="text-embedding-3-small"),
    ),
)

knowledge_tools = KnowledgeTools(
    knowledge=agno_docs,
    think=True,
    search=True,
    analyze=True,
    add_few_shot=True,
)

agent = Agent(
    model=OpenAIChat(id="gpt-4o"),
    tools=[knowledge_tools],
    show_tool_calls=True,
    markdown=True,
)

if __name__ == "__main__":
    # Load the knowledge base, comment after first run
    agno_docs.load(recreate=True)
    agent.print_response("How do I build multi-agent teams with Agno?", stream=True)


```

## Usage

<Steps>
  <Snippet file="create-venv-step.mdx" />

  <Step title="Set your API key">
    ```bash theme={null}
    export OPENAI_API_KEY=xxx
    ```
  </Step>

  <Step title="Install libraries">
    ```bash theme={null}
    pip install -U openai lancedb tantivy sqlalchemy agno
    ```
  </Step>

  <Step title="Run Example">
    <CodeGroup>
      ```bash Mac theme={null}
      python cookbook/reasoning/tools/knowledge_tools.py
      ```

      ```bash Windows theme={null}
      python cookbook/reasoning/tools/knowledge_tools.py
      ```
    </CodeGroup>
  </Step>
</Steps>