Vertex AI Claude Adaptive Thinking

Use adaptive thinking with effort levels to control reasoning depth on Claude VertexAI.

Cookbook example demonstrating adaptive thinking with output_config on VertexAI.

The pinned v2.7.4 source imports Claude from the empty agno.models.vertexai package root. Use the released module path before running.

adaptive_thinking.py

"""
VertexAI Claude Adaptive Thinking
=================================

Cookbook example demonstrating adaptive thinking with output_config on VertexAI.

For Claude 4.6 VertexAI models, use adaptive thinking with the effort parameter
to control thinking depth. Valid effort values:
- "low": Most efficient, significant token savings
- "medium": Balanced approach with moderate savings
- "high": Default, high capability for complex reasoning
- "max": Absolute maximum capability (Opus 4.6 only)

Prerequisites:
- Set GOOGLE_CLOUD_PROJECT and CLOUD_ML_REGION environment variables
- Authenticate with: gcloud auth application-default login
"""

from agno.agent import Agent
from agno.models.vertexai import Claude

# ---------------------------------------------------------------------------
# Create Agent with Adaptive Thinking
# ---------------------------------------------------------------------------

agent = Agent(
    model=Claude(
        id="claude-sonnet-4-6@20250514",
        max_tokens=4096,
        thinking={"type": "adaptive"},
        output_config={"effort": "high"},
    ),
    markdown=True,
)

# ---------------------------------------------------------------------------
# Run Agent
# ---------------------------------------------------------------------------
if __name__ == "__main__":
    # Complex reasoning task that benefits from extended thinking
    agent.print_response(
        "Explain the key differences between recursion and iteration, "
        "and when you would choose one over the other in software development."
    )

    # With streaming
    agent.print_response(
        "What are the trade-offs between microservices and monolithic architectures?",
        stream=True,
    )

Run the Example

1. Set up your virtual environment

   Mac

   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 "anthropic[vertex]"
   
3. Export environment variables

   Mac/Linux

   export ANTHROPIC_VERTEX_PROJECT_ID="your_anthropic_vertex_project_id_here"
   export CLOUD_ML_REGION="your_cloud_ml_region_here"
   

   $Env:ANTHROPIC_VERTEX_PROJECT_ID="your_anthropic_vertex_project_id_here"
   $Env:CLOUD_ML_REGION="your_cloud_ml_region_here"
   
4. Authenticate with Google Cloud

   Sign in with Application Default Credentials:

   gcloud auth application-default login
   
5. Fix the Claude import

   Replace from agno.models.vertexai import Claude with from agno.models.vertexai.claude import Claude in the saved file.

6. Run the example

   Save the code above as adaptive_thinking.py, then run:

   python adaptive_thinking.py
   

Full source: cookbook/90_models/vertexai/claude/adaptive_thinking.py