Self-managed Context Management

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

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.

"""
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

# Clone and setup repo
git clone https://github.com/agno-agi/agno.git
cd agno/cookbook/90_models/anthropic

# Create and activate virtual environment
./scripts/demo_setup.sh
source .venvs/demo/bin/activate

# Export relevant API keys
export ANTHROPIC_API_KEY="***"

python context_management.py