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Expert Selection with pick() and pick_multiple()

This example demonstrates LLMling-agent's type-safe selection methods:

  • Using pick() for single expert selection
  • Using pick_multiple() for team selection
  • Type-safe results with reasoning
  • Team-based agent selection

How It Works

  1. Single Selection (pick):
  2. Takes a team of agents and a task description
  3. Returns a single expert with reasoning

  4. Result is type-safe: Pick[Agent]

  5. Multiple Selection (pick_multiple):

  6. Takes same inputs plus min/max picks
  7. Returns multiple experts with reasoning
  8. Result is type-safe: MultiPick[Agent]

Example Output: 

Selected: database_expert
Reason: The task specifically involves SQL query optimization, which is the database expert's primary specialty.

Selected: frontend_dev, security_expert
Reason: Creating a secure login page requires both frontend expertise for the user interface and security expertise for proper authentication implementation.

This demonstrates:

  • Type-safe agent selection
  • Reasoned decision-making
  • Team-based operations
  • Flexible expert allocation

Open in Pydantic Playground