> ## Documentation Index
> Fetch the complete documentation index at: https://agno-v2-service-account.mintlify.site/llms.txt
> Use this file to discover all available pages before exploring further.

# Claude Model Test

> Tests learning with Claude instead of OpenAI.

```python claude_model.py theme={null}
"""
Claude Model Test
=================
Tests learning with Claude instead of OpenAI.

All other cookbooks use OpenAI (gpt-5.5). This test verifies that
learning works with Claude models, ensuring the implementation is
model-agnostic.

Key things to verify:
1. Profile extraction works with Claude
2. Tool calls work correctly (Claude uses different tool format)
3. Background extraction completes successfully
"""

from agno.agent import Agent
from agno.db.postgres import PostgresDb
from agno.learn import LearningMachine, LearningMode, UserProfileConfig
from agno.models.anthropic import Claude

# ---------------------------------------------------------------------------
# Create Agent - Using Claude instead of OpenAI
# ---------------------------------------------------------------------------

db = PostgresDb(db_url="postgresql+psycopg://ai:ai@localhost:5532/ai")

agent = Agent(
    model=Claude(id="claude-sonnet-4-6"),  # Using Claude
    db=db,
    learning=LearningMachine(
        user_profile=UserProfileConfig(
            mode=LearningMode.ALWAYS,
        ),
    ),
    markdown=True,
)

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

if __name__ == "__main__":
    user_id = "claude_test@example.com"

    print("\n" + "=" * 60)
    print("TEST: Learning with Claude model")
    print("=" * 60 + "\n")

    print(f"Model type: {type(agent.model).__name__}")

    # Session 1: Share information
    print("\n" + "=" * 60)
    print("SESSION 1: Share information (Claude extraction)")
    print("=" * 60 + "\n")

    agent.print_response(
        "Hi! I'm Bruce Wayne, but my friends call me Batman.",
        user_id=user_id,
        session_id="claude_session_1",
        stream=True,
    )

    # Check if LearningMachine was initialized
    lm = agent.learning_machine
    print(f"\nLearningMachine exists: {lm is not None}")

    if lm and lm.user_profile_store:
        lm.user_profile_store.print(user_id=user_id)
    else:
        print("\n[WARNING] UserProfileStore not available - extraction may have failed")
        print(
            "Note: Some Claude models may not support structured outputs required for extraction"
        )

    # Session 2: Verify profile persisted
    print("\n" + "=" * 60)
    print("SESSION 2: Profile recall (Claude)")
    print("=" * 60 + "\n")

    agent.print_response(
        "What's my secret identity?",
        user_id=user_id,
        session_id="claude_session_2",
        stream=True,
    )

    if lm and lm.user_profile_store:
        lm.user_profile_store.print(user_id=user_id)

    print("\n" + "=" * 60)
    print("CLAUDE MODEL TEST COMPLETE")
    print("=" * 60)
```

## Run the Example

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

  <Step title="Install dependencies">
    ```bash theme={null}
    uv pip install -U agno anthropic psycopg-binary sqlalchemy
    ```
  </Step>

  <Step title="Export your Anthropic API key">
    <CodeGroup>
      ```bash Mac/Linux theme={null}
      export ANTHROPIC_API_KEY="your_anthropic_api_key_here"
      ```

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

  <Snippet file="run-pgvector-step.mdx" />

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

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

Full source: [cookbook/08\_learning/06\_quick\_tests/04\_claude\_model.py](https://github.com/agno-agi/agno/blob/main/cookbook/08_learning/06_quick_tests/04_claude_model.py)