Principle:Cohere ai Cohere python Chat Response Processing
| Metadata | |
|---|---|
| Source Repo | Cohere Python SDK |
| Source Doc | Cohere API Reference |
| Domains | NLP, Response_Parsing, Chat_API |
| Last Updated | 2026-02-15 14:00 GMT |
Overview
A structured data extraction pattern for parsing language model responses into typed fields for downstream consumption.
Description
Chat Response Processing is the practice of extracting and interpreting the structured fields from a chat API response. A chat response contains the generated text (in message.content), a finish reason indicating why generation stopped (COMPLETE, MAX_TOKENS, TOOL_CALL, etc.), optional tool calls when the model invokes functions, optional citations linking text spans to source documents, and usage statistics for billing and monitoring. Understanding the finish reason is critical for control flow — TOOL_CALL indicates the model needs external function results before continuing.
Usage
Use this principle after every chat API call. Always check the finish_reason to determine next steps: COMPLETE means the response is final, MAX_TOKENS means the response was truncated, TOOL_CALL means tool execution is needed before continuing the conversation.
Theoretical Basis
Response processing follows the structured output paradigm where API responses are parsed into strongly-typed data models. The finish_reason field implements a state machine for multi-turn interactions: COMPLETE is a terminal state, while TOOL_CALL triggers a continuation loop requiring tool execution and re-submission.