buildEvaluationInstructions method

  1. @override
List<ChatMessage>? buildEvaluationInstructions(
  1. List<ChatMessage> messages,
  2. ChatResponse modelResponse,
  3. List<EvaluationContext> additionalContext
)
override

Builds the evaluation instructions (system + user messages).

Return null to signal that a required context was missing.

Implementation

@override
List<ChatMessage>? buildEvaluationInstructions(
  List<ChatMessage> messages,
  ChatResponse modelResponse,
  List<EvaluationContext> additionalContext,
) {
  final ctx = additionalContext.whereType<IntentResolutionEvaluatorContext>().firstOrNull;
  final userRequest = messages.lastUserMessage?.text ?? '';
  final response = modelResponse.text;

  final toolsSection = ctx != null && ctx.toolDefinitions.isNotEmpty
      ? '\nAVAILABLE TOOLS:\n${ctx.contents.map((c) => c.toString()).join("\n")}'
      : '';

  final prompt = '''
# Definition
**Intent Resolution** measures how accurately the AI identified the user's intent and produced a response that fulfills it.$toolsSection

# Ratings
## [IntentResolution: 1] The user's intent was completely misidentified.
## [IntentResolution: 2] The intent was partially identified but the response does not fulfill it.
## [IntentResolution: 3] The intent was identified but the response only partially fulfills it.
## [IntentResolution: 4] The intent was correctly identified and mostly fulfilled.
## [IntentResolution: 5] The intent was perfectly identified and completely fulfilled.

# Data
QUERY: $userRequest
RESPONSE: $response

# Tasks
## Score how well the RESPONSE resolves the user's intent.
- **ThoughtChain**: Think step by step. Start with "Let's think step by step:".
- **Explanation**: A very short explanation of why you think the input Data should get that Score.
- **Score**: An integer score (1–5) based on the definitions.

## Please provide your answers between the tags: <S0>your chain of thoughts</S0>, <S1>your explanation</S1>, <S2>your Score</S2>.
# Output
''';
  return [
    ChatMessage.fromText(ChatRole.system, _systemPrompt),
    ChatMessage.fromText(ChatRole.user, prompt),
  ];
}