Interleaved Thinking Example

This example demonstrates Claude 3.7+'s interleaved thinking capability, which allows the model to use thinking tokens between tool calls for better multi-step reasoning.

What is Interleaved Thinking?

Interleaved thinking enables Claude to:

• Think between tool calls: Use reasoning tokens to plan which tool to use next
• Interpret results: Process tool outputs before deciding on next steps
• Synthesize information: Combine results from multiple tools coherently

Features Demonstrated

1. Multi-step problem solving with quarterly sales analysis
2. Tool orchestration with calculate, search, and analyze functions
3. Thinking tokens used for planning and interpretation
4. Token metrics showing thinking vs visible output

Running the Example

# Set your API key
export ANTHROPIC_API_KEY=your-api-key

# Run the example
go run .

Key Implementation

// Enable interleaved thinking for tool use
opts := []llms.CallOption{
    // Thinking mode for reasoning
    llms.WithThinkingMode(llms.ThinkingModeMedium),
    
    // Enable interleaved thinking beta feature
    anthropic.WithInterleavedThinking(),
    
    // Provide tools for the model to use
    llms.WithTools(tools),
}

Example Flow

The demo presents a multi-step analysis task:

1. Calculate year-over-year growth rates
2. Analyze data trends
3. Search for explanatory factors
4. Make predictions based on findings

Between each tool call, Claude uses thinking tokens to:

• Decide which tool to use next
• Interpret the results from the previous tool
• Plan the next step in the analysis

Token Metrics

The example displays detailed token usage:

• Thinking Tokens: Used for internal reasoning between tools
• Visible Output: The actual response content
• Thinking Ratio: Percentage of tokens used for thinking

Requirements

• Claude 3.7 Sonnet model (claude-3-7-sonnet-20250219)
• Valid Anthropic API key
• Interleaved thinking feature access