Function Calling with Registry

[chris-cozy]

Summary
Introduce a structured function-calling mechanism where the agent can dynamically invoke predefined functions during its thinking process. A registry of available functions, their purposes, and usage constraints should be maintained and accessible to the agent.

Details

• Function Registry

  • Centralized list of all available functions.
  • Each function includes metadata: name, description, parameters, return type, and usage context.
  • Supports dynamic registration and updates.

• Function Calling

  • During its reasoning/thinking process, the agent can determine when to call a registered function.
  • Functions should be invoked with the correct parameters based on the registry schema.
  • The system should handle results (success/failure) and feed outputs back into the agent’s process.

• Execution Flow

  1. Agent reasoning identifies the need for an action.
  2. Agent selects the appropriate function from the registry.
  3. Function executes with provided parameters.
  4. Output is returned to the agent for further reasoning or communication.

Example Use Case

• Function: search_knowledge_base(query: string) → results[]
• Agent decides a user’s request requires a knowledge base lookup.
• Agent calls the function with query="local expression design".
• Results are returned, and the agent incorporates them into its response.

Acceptance Criteria

• A function registry exists with metadata for all available functions.
• Agent can discover and select functions at runtime.
• Agent can execute registered functions with parameters.
• Function outputs are integrated into the agent’s reasoning.
• Clear error handling for invalid calls or failed executions.

Why This Matters
Function calling enables the agent to take meaningful actions beyond pure conversation. By leveraging a well-defined registry, the system ensures safe, predictable, and extensible integrations while allowing the agent to dynamically adapt its behavior.