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feat: set up gen ai inference attributes for foundational text models #111

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merged 10 commits into from
Nov 1, 2024
Merged

feat: set up gen ai inference attributes for foundational text models #111

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3aa360d
feat: set up gen ai inference attributes for foundational text models
yiyuan-he Oct 28, 2024
2061da2
Merge branch 'aws-observability:main' into gen-ai-support
yiyuan-he Oct 29, 2024
6cd9bcc
chore: apply lint
yiyuan-he Oct 29, 2024
842f9c9
feat: add unit tests for gen ai inference attributes
yiyuan-he Oct 29, 2024
c730602
Merge branch 'main' into gen-ai-support
yiyuan-he Oct 30, 2024
3a57302
fix: add strict undefined checks
yiyuan-he Oct 31, 2024
fae5c83
doc: add inline comments for token count approximation
yiyuan-he Oct 31, 2024
650eb93
chore: apply lint
yiyuan-he Oct 31, 2024
ad29de3
Merge branch 'main' into gen-ai-support
yiyuan-he Oct 31, 2024
63d6800
Merge branch 'main' into gen-ai-support
yiyuan-he Nov 1, 2024
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6 changes: 6 additions & 0 deletions aws-distro-opentelemetry-node-autoinstrumentation/src/aws-span-processing-util.ts
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Original file line number Diff line number Diff line change
Expand Up @@ -47,6 +47,12 @@ export class AwsSpanProcessingUtil {
// TODO: Use Semantic Conventions once upgraded
static GEN_AI_REQUEST_MODEL: string = 'gen_ai.request.model';
static GEN_AI_SYSTEM: string = 'gen_ai.system';
static GEN_AI_REQUEST_MAX_TOKENS: string = 'gen_ai.request.max_tokens';
static GEN_AI_REQUEST_TEMPERATURE: string = 'gen_ai.request.temperature';
static GEN_AI_REQUEST_TOP_P: string = 'gen_ai.request.top_p';
static GEN_AI_RESPONSE_FINISH_REASONS: string = 'gen_ai.response.finish_reasons';
static GEN_AI_USAGE_INPUT_TOKENS: string = 'gen_ai.usage.input_tokens';
static GEN_AI_USAGE_OUTPUT_TOKENS: string = 'gen_ai.usage.output_tokens';

static getDialectKeywords(): string[] {
return SQL_DIALECT_KEYWORDS_JSON.keywords;
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162 changes: 162 additions & 0 deletions aws-distro-opentelemetry-node-autoinstrumentation/src/patches/aws/services/bedrock.ts
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Expand Up @@ -211,11 +211,173 @@ export class BedrockRuntimeServiceExtension implements ServiceExtension {
spanAttributes[AwsSpanProcessingUtil.GEN_AI_REQUEST_MODEL] = modelId;
}

if (request.commandInput?.body) {
const requestBody = JSON.parse(request.commandInput.body);
if (modelId.includes('amazon.titan')) {
if (requestBody.textGenerationConfig?.temperature !== undefined) {
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spanAttributes[AwsSpanProcessingUtil.GEN_AI_REQUEST_TEMPERATURE] =
requestBody.textGenerationConfig.temperature;
}
if (requestBody.textGenerationConfig?.topP !== undefined) {
spanAttributes[AwsSpanProcessingUtil.GEN_AI_REQUEST_TOP_P] = requestBody.textGenerationConfig.topP;
}
if (requestBody.textGenerationConfig?.maxTokenCount !== undefined) {
spanAttributes[AwsSpanProcessingUtil.GEN_AI_REQUEST_MAX_TOKENS] =
requestBody.textGenerationConfig.maxTokenCount;
}
} else if (modelId.includes('anthropic.claude')) {
if (requestBody.max_tokens !== undefined) {
spanAttributes[AwsSpanProcessingUtil.GEN_AI_REQUEST_MAX_TOKENS] = requestBody.max_tokens;
}
if (requestBody.temperature !== undefined) {
spanAttributes[AwsSpanProcessingUtil.GEN_AI_REQUEST_TEMPERATURE] = requestBody.temperature;
}
if (requestBody.top_p !== undefined) {
spanAttributes[AwsSpanProcessingUtil.GEN_AI_REQUEST_TOP_P] = requestBody.top_p;
}
} else if (modelId.includes('meta.llama')) {
if (requestBody.max_gen_len !== undefined) {
spanAttributes[AwsSpanProcessingUtil.GEN_AI_REQUEST_MAX_TOKENS] = requestBody.max_gen_len;
}
if (requestBody.temperature !== undefined) {
spanAttributes[AwsSpanProcessingUtil.GEN_AI_REQUEST_TEMPERATURE] = requestBody.temperature;
}
if (requestBody.top_p !== undefined) {
spanAttributes[AwsSpanProcessingUtil.GEN_AI_REQUEST_TOP_P] = requestBody.top_p;
}
} else if (modelId.includes('cohere.command')) {
if (requestBody.max_tokens !== undefined) {
spanAttributes[AwsSpanProcessingUtil.GEN_AI_REQUEST_MAX_TOKENS] = requestBody.max_tokens;
}
if (requestBody.temperature !== undefined) {
spanAttributes[AwsSpanProcessingUtil.GEN_AI_REQUEST_TEMPERATURE] = requestBody.temperature;
}
if (requestBody.p !== undefined) {
spanAttributes[AwsSpanProcessingUtil.GEN_AI_REQUEST_TOP_P] = requestBody.p;
}
} else if (modelId.includes('ai21.jamba')) {
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if (requestBody.max_tokens !== undefined) {
spanAttributes[AwsSpanProcessingUtil.GEN_AI_REQUEST_MAX_TOKENS] = requestBody.max_tokens;
}
if (requestBody.temperature !== undefined) {
spanAttributes[AwsSpanProcessingUtil.GEN_AI_REQUEST_TEMPERATURE] = requestBody.temperature;
}
if (requestBody.top_p !== undefined) {
spanAttributes[AwsSpanProcessingUtil.GEN_AI_REQUEST_TOP_P] = requestBody.top_p;
}
} else if (modelId.includes('mistral.mistral')) {
if (requestBody.prompt !== undefined) {
// NOTE: We approximate the token count since this value is not directly available in the body
// According to Bedrock docs they use (total_chars / 6) to approximate token count for pricing.
// https://docs.aws.amazon.com/bedrock/latest/userguide/model-customization-prepare.html
spanAttributes[AwsSpanProcessingUtil.GEN_AI_USAGE_INPUT_TOKENS] = Math.ceil(requestBody.prompt.length / 6);
}
if (requestBody.max_tokens !== undefined) {
spanAttributes[AwsSpanProcessingUtil.GEN_AI_REQUEST_MAX_TOKENS] = requestBody.max_tokens;
}
if (requestBody.temperature !== undefined) {
spanAttributes[AwsSpanProcessingUtil.GEN_AI_REQUEST_TEMPERATURE] = requestBody.temperature;
}
if (requestBody.top_p !== undefined) {
spanAttributes[AwsSpanProcessingUtil.GEN_AI_REQUEST_TOP_P] = requestBody.top_p;
}
}
}

return {
isIncoming,
spanAttributes,
spanKind,
spanName,
};
}

responseHook(response: NormalizedResponse, span: Span, tracer: Tracer, config: AwsSdkInstrumentationConfig): void {
const currentModelId = response.request.commandInput?.modelId;
if (response.data?.body) {
const decodedResponseBody = new TextDecoder().decode(response.data.body);
const responseBody = JSON.parse(decodedResponseBody);
if (currentModelId.includes('amazon.titan')) {
if (responseBody.inputTextTokenCount !== undefined) {
span.setAttribute(AwsSpanProcessingUtil.GEN_AI_USAGE_INPUT_TOKENS, responseBody.inputTextTokenCount);
}
if (responseBody.results?.[0]?.tokenCount !== undefined) {
span.setAttribute(AwsSpanProcessingUtil.GEN_AI_USAGE_OUTPUT_TOKENS, responseBody.results[0].tokenCount);
}
if (responseBody.results?.[0]?.completionReason !== undefined) {
span.setAttribute(AwsSpanProcessingUtil.GEN_AI_RESPONSE_FINISH_REASONS, [
responseBody.results[0].completionReason,
]);
}
} else if (currentModelId.includes('anthropic.claude')) {
if (responseBody.usage?.input_tokens !== undefined) {
span.setAttribute(AwsSpanProcessingUtil.GEN_AI_USAGE_INPUT_TOKENS, responseBody.usage.input_tokens);
}
if (responseBody.usage?.output_tokens !== undefined) {
span.setAttribute(AwsSpanProcessingUtil.GEN_AI_USAGE_OUTPUT_TOKENS, responseBody.usage.output_tokens);
}
if (responseBody.stop_reason !== undefined) {
span.setAttribute(AwsSpanProcessingUtil.GEN_AI_RESPONSE_FINISH_REASONS, [responseBody.stop_reason]);
}
} else if (currentModelId.includes('meta.llama')) {
if (responseBody.prompt_token_count !== undefined) {
span.setAttribute(AwsSpanProcessingUtil.GEN_AI_USAGE_INPUT_TOKENS, responseBody.prompt_token_count);
}
if (responseBody.generation_token_count !== undefined) {
span.setAttribute(AwsSpanProcessingUtil.GEN_AI_USAGE_OUTPUT_TOKENS, responseBody.generation_token_count);
}
if (responseBody.stop_reason !== undefined) {
span.setAttribute(AwsSpanProcessingUtil.GEN_AI_RESPONSE_FINISH_REASONS, [responseBody.stop_reason]);
}
} else if (currentModelId.includes('cohere.command')) {
if (responseBody.prompt !== undefined) {
// NOTE: We approximate the token count since this value is not directly available in the body
// According to Bedrock docs they use (total_chars / 6) to approximate token count for pricing.
// https://docs.aws.amazon.com/bedrock/latest/userguide/model-customization-prepare.html
span.setAttribute(AwsSpanProcessingUtil.GEN_AI_USAGE_INPUT_TOKENS, Math.ceil(responseBody.prompt.length / 6));
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}
if (responseBody.generations?.[0]?.text !== undefined) {
span.setAttribute(
AwsSpanProcessingUtil.GEN_AI_USAGE_OUTPUT_TOKENS,
// NOTE: We approximate the token count since this value is not directly available in the body
// According to Bedrock docs they use (total_chars / 6) to approximate token count for pricing.
// https://docs.aws.amazon.com/bedrock/latest/userguide/model-customization-prepare.html
Math.ceil(responseBody.generations[0].text.length / 6)
);
}
if (responseBody.generations?.[0]?.finish_reason !== undefined) {
span.setAttribute(AwsSpanProcessingUtil.GEN_AI_RESPONSE_FINISH_REASONS, [
responseBody.generations[0].finish_reason,
]);
}
} else if (currentModelId.includes('ai21.jamba')) {
if (responseBody.usage?.prompt_tokens !== undefined) {
span.setAttribute(AwsSpanProcessingUtil.GEN_AI_USAGE_INPUT_TOKENS, responseBody.usage.prompt_tokens);
}
if (responseBody.usage?.completion_tokens !== undefined) {
span.setAttribute(AwsSpanProcessingUtil.GEN_AI_USAGE_OUTPUT_TOKENS, responseBody.usage.completion_tokens);
}
if (responseBody.choices?.[0]?.finish_reason !== undefined) {
span.setAttribute(AwsSpanProcessingUtil.GEN_AI_RESPONSE_FINISH_REASONS, [
responseBody.choices[0].finish_reason,
]);
}
} else if (currentModelId.includes('mistral.mistral')) {
if (responseBody.outputs?.[0]?.text !== undefined) {
span.setAttribute(
AwsSpanProcessingUtil.GEN_AI_USAGE_OUTPUT_TOKENS,
// NOTE: We approximate the token count since this value is not directly available in the body
// According to Bedrock docs they use (total_chars / 6) to approximate token count for pricing.
// https://docs.aws.amazon.com/bedrock/latest/userguide/model-customization-prepare.html
Math.ceil(responseBody.outputs[0].text.length / 6)
);
}
if (responseBody.outputs?.[0]?.stop_reason !== undefined) {
span.setAttribute(AwsSpanProcessingUtil.GEN_AI_RESPONSE_FINISH_REASONS, [
responseBody.outputs[0].stop_reason,
]);
}
}
}
}
}
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