Principle:Cohere ai Cohere python Tool Call Parsing
| Property | Value |
|---|---|
| Type | Principle |
| Domain | Tool Use, Response Parsing, Agentic Patterns |
| Source | Cohere Python SDK |
| Last Updated | 2026-02-15 |
| Implemented By | Implementation:Cohere_ai_Cohere_python_ToolCallV2_Model |
Overview
A pattern for detecting, extracting, and interpreting tool call requests from language model responses.
Description
Tool Call Parsing is the process of detecting when a language model response contains tool call requests rather than (or in addition to) text content. When the model decides to use a tool, the response's finish_reason is "TOOL_CALL" and the message contains tool_calls — a list of ToolCallV2 objects. Each tool call has a unique ID, function name, and JSON-encoded arguments. The SDK applies a monkey-patch (via overrides.py) to auto-generate UUIDs for tool call IDs if the model omits them, ensuring consistent tool result matching.
Usage
After every chat call with tools, check if finish_reason == "TOOL_CALL". If so, iterate response.message.tool_calls to get the function names and arguments. Parse the JSON arguments and execute the corresponding functions.
- Check finish_reason to determine if the model wants to call tools
- Iterate over tool_calls to extract each individual tool call
- Parse function.arguments from JSON string to Python dict
- Use tool_call.id to match results back to specific calls
Theoretical Basis
Tool call parsing implements the action extraction phase of the ReAct loop. The unique ID per tool call enables stateful multi-turn tool use where results must be matched back to specific calls. The auto-UUID patch ensures robustness against models that may not always generate IDs.
- The finish_reason signal provides a clear branching point in the control flow
- JSON-encoded arguments maintain type fidelity between the model and function signatures
- UUID auto-generation is a defensive programming pattern ensuring correctness