Principle:Cohere ai Cohere python Tool Function Execution
| Metadata | Value |
|---|---|
| Source | Cohere Tool Use |
| Domains | Agentic_AI, Function_Calling, Tool_Use |
| Last Updated | 2026-02-15 14:00 GMT |
| Implemented By | Implementation:Cohere_ai_Cohere_python_Tool_Execution_Pattern |
Overview
A client-side execution pattern for running external functions requested by language model tool calls.
Description
Tool Function Execution is the client-side process of taking a model's tool call request (function name + JSON arguments), dispatching it to the appropriate function, executing it, and collecting the results. This is entirely user-defined — the Cohere SDK provides the tool call data structure, but the actual function execution happens in user code. Users must: parse the function.arguments JSON string, route to the correct function by name, execute with the parsed arguments, handle errors, and format results as strings for the tool result message.
Usage
Implement after detecting tool calls in a chat response (finish_reason == "TOOL_CALL"). Create a dispatch mechanism that maps function names to actual implementations. Handle errors gracefully — return error messages as tool results rather than crashing.
Theoretical Basis
Tool execution implements the Acting phase of ReAct (Reason + Act). The dispatch pattern (name to function mapping) follows the Command design pattern. Error handling in tool execution is critical because the model depends on receiving results to continue the conversation.
Practical Guide
- Create a dictionary mapping function names to callables
- Parse JSON arguments with error handling
- Execute functions with timeouts for external API calls
- Return results as JSON strings
- Handle errors by returning error descriptions as tool results