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

# Knowledge Tools: Think, Search, Analyze

> This gives agents more sophisticated reasoning over knowledge.

```python knowledge_tools.py theme={null}
"""
Knowledge Tools: Think, Search, Analyze
=========================================
KnowledgeTools provides a richer set of tools for knowledge interaction
beyond basic search:

- think: Agent reasons about the query before searching
- search: Standard knowledge base search
- analyze: Deep analysis of search results

This gives agents more sophisticated reasoning over knowledge.
"""

import asyncio

from agno.agent import Agent
from agno.knowledge.embedder.openai import OpenAIEmbedder
from agno.knowledge.knowledge import Knowledge
from agno.models.openai import OpenAIChat
from agno.tools.knowledge import KnowledgeTools
from agno.vectordb.qdrant import Qdrant
from agno.vectordb.search import SearchType

# ---------------------------------------------------------------------------
# Setup
# ---------------------------------------------------------------------------

qdrant_url = "http://localhost:6333"

knowledge = Knowledge(
    vector_db=Qdrant(
        collection="knowledge_tools_demo",
        url=qdrant_url,
        search_type=SearchType.hybrid,
        embedder=OpenAIEmbedder(id="text-embedding-3-small"),
    ),
)

knowledge_tools = KnowledgeTools(
    knowledge=knowledge,
    enable_think=True,
    enable_search=True,
    enable_analyze=True,
    add_few_shot=True,
)

# ---------------------------------------------------------------------------
# Create Agent
# ---------------------------------------------------------------------------

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

# ---------------------------------------------------------------------------
# Run Demo
# ---------------------------------------------------------------------------

if __name__ == "__main__":

    async def main():
        await knowledge.ainsert(url="https://docs.agno.com/llms-full.txt")

        print("\n" + "=" * 60)
        print("KnowledgeTools: think + search + analyze")
        print("=" * 60 + "\n")

        agent.print_response(
            "How do I build a team of agents in Agno?",
            stream=True,
        )

    asyncio.run(main())
```

## Run the Example

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

  <Step title="Install dependencies">
    ```bash theme={null}
    uv pip install -U agno fastembed openai qdrant-client
    ```
  </Step>

  <Step title="Export your OpenAI API key">
    <CodeGroup>
      ```bash Mac/Linux theme={null}
      export OPENAI_API_KEY="your_openai_api_key_here"
      ```

      ```bash Windows theme={null}
      $Env:OPENAI_API_KEY="your_openai_api_key_here"
      ```
    </CodeGroup>
  </Step>

  <Step title="Run Qdrant">
    ```bash theme={null}
    docker run -d --name qdrant -p 6333:6333 qdrant/qdrant:latest
    ```
  </Step>

  <Step title="Run the example">
    Save the code above as `knowledge_tools.py`, then run:

    ```bash theme={null}
    python knowledge_tools.py
    ```
  </Step>
</Steps>

Full source: [cookbook/07\_knowledge/04\_advanced/04\_knowledge\_tools.py](https://github.com/agno-agi/agno/blob/main/cookbook/07_knowledge/04_advanced/04_knowledge_tools.py)