Self-managed Context Management

Claude’s context management feature for automatic tool result clearing.

Claude’s context management feature for automatic tool result clearing. This reduces token usage in long-running conversations with extensive tool use.

context_management.py

"""
Self-managed Context Management

This cookbook demonstrates Claude's context management feature for automatic tool result clearing.
This reduces token usage in long-running conversations with extensive tool use.

You can read more in Anthropic docs: https://docs.claude.com/en/docs/build-with-claude/context-editing

1. Install dependencies: `uv pip install -U agno anthropic ddgs sqlalchemy`
2. Set your `ANTHROPIC_API_KEY` in your environment variables.
3. Run the cookbook
"""

from agno.agent import Agent
from agno.models.anthropic import Claude
from agno.tools.websearch import WebSearchTools

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

agent = Agent(
    model=Claude(
        id="claude-sonnet-4-5",
        # Activate and configure the context management feature
        betas=["context-management-2025-06-27"],
        context_management={
            "edits": [
                {
                    "type": "clear_tool_uses_20250919",
                    "trigger": {"type": "tool_uses", "value": 2},
                    "keep": {"type": "tool_uses", "value": 1},
                }
            ]
        },
    ),
    instructions="You are a helpful assistant with access to the web.",
    tools=[WebSearchTools()],
    session_id="context-editing",
    add_history_to_context=True,
    markdown=True,
)

agent.print_response(
    "Search for AI regulation in US. Make multiple searches to find the latest information."
)

# Display context management metrics
print("\n" + "=" * 60)
print("CONTEXT MANAGEMENT SUMMARY")
print("=" * 60)
response = agent.get_last_run_output()
if response and response.metrics:
    print(f"\nInput tokens: {response.metrics.input_tokens:,}")

# Print context management stats from the last message
if response and response.messages:
    for message in reversed(response.messages):
        if message.provider_data and "context_management" in message.provider_data:
            edits = message.provider_data["context_management"].get("applied_edits", [])
            if edits:
                print(
                    f"\n✅ Saved: {edits[-1].get('cleared_input_tokens', 0):,} tokens"
                )
                print(f"   Cleared: {edits[-1].get('cleared_tool_uses', 0)} tool uses")
                break

print("\n" + "=" * 60)

# ---------------------------------------------------------------------------
# Run Agent
# ---------------------------------------------------------------------------

if __name__ == "__main__":
    pass

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 ddgs
   
3. Export your Anthropic API key

   Mac/Linux

   export ANTHROPIC_API_KEY="your_anthropic_api_key_here"
   

   $Env:ANTHROPIC_API_KEY="your_anthropic_api_key_here"
   
4. Run the example

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

   python context_management.py
   

Full source: cookbook/90_models/anthropic/context_management.py