Skip to content

feat: add support for new cohere command r models #118

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
merged 5 commits into from
Nov 22, 2024
Merged

feat: add support for new cohere command r models #118

Show file tree
Hide file tree
Changes from 2 commits
Commits
Show all changes
5 commits
Select commit Hold shift + click to select a range
a3355ea
feat: add support for new cohere command r models
yiyuan-he Nov 6, 2024
c25d7de
fix: mistral ai model conditional
yiyuan-he Nov 8, 2024
3487804
remove logging statement
yiyuan-he Nov 21, 2024
bb23cf1
Merge branch 'main' into add-command-r-model
yiyuan-he Nov 21, 2024
3e1017c
Merge branch 'main' into add-command-r-model
mxiamxia Nov 21, 2024
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
34 changes: 29 additions & 5 deletions aws-distro-opentelemetry-node-autoinstrumentation/src/patches/aws/services/bedrock.ts
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -245,6 +245,22 @@ export class BedrockRuntimeServiceExtension implements ServiceExtension {
if (requestBody.top_p !== undefined) {
spanAttributes[AwsSpanProcessingUtil.GEN_AI_REQUEST_TOP_P] = requestBody.top_p;
}
} else if (modelId.includes('cohere.command-r')) {
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;
}
if (requestBody.message !== 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.message.length / 6);
}
} else if (modelId.includes('cohere.command')) {
if (requestBody.max_tokens !== undefined) {
spanAttributes[AwsSpanProcessingUtil.GEN_AI_REQUEST_MAX_TOKENS] = requestBody.max_tokens;
Expand All @@ -255,6 +271,9 @@ export class BedrockRuntimeServiceExtension implements ServiceExtension {
if (requestBody.p !== undefined) {
spanAttributes[AwsSpanProcessingUtil.GEN_AI_REQUEST_TOP_P] = requestBody.p;
}
if (requestBody.prompt !== undefined) {
spanAttributes[AwsSpanProcessingUtil.GEN_AI_USAGE_INPUT_TOKENS] = Math.ceil(requestBody.prompt.length / 6);
}
} else if (modelId.includes('ai21.jamba')) {
if (requestBody.max_tokens !== undefined) {
spanAttributes[AwsSpanProcessingUtil.GEN_AI_REQUEST_MAX_TOKENS] = requestBody.max_tokens;
Expand All @@ -265,7 +284,7 @@ export class BedrockRuntimeServiceExtension implements ServiceExtension {
if (requestBody.top_p !== undefined) {
spanAttributes[AwsSpanProcessingUtil.GEN_AI_REQUEST_TOP_P] = requestBody.top_p;
}
} else if (modelId.includes('mistral.mistral')) {
} else if (modelId.includes('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.
Expand Down Expand Up @@ -329,13 +348,18 @@ export class BedrockRuntimeServiceExtension implements ServiceExtension {
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) {
} else if (currentModelId.includes('cohere.command-r')) {
console.log('Response Body:', responseBody);
if (responseBody.text !== 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));
span.setAttribute(AwsSpanProcessingUtil.GEN_AI_USAGE_OUTPUT_TOKENS, Math.ceil(responseBody.text.length / 6));
}
if (responseBody.finish_reason !== undefined) {
span.setAttribute(AwsSpanProcessingUtil.GEN_AI_RESPONSE_FINISH_REASONS, [responseBody.finish_reason]);
}
} else if (currentModelId.includes('cohere.command')) {
if (responseBody.generations?.[0]?.text !== undefined) {
span.setAttribute(
AwsSpanProcessingUtil.GEN_AI_USAGE_OUTPUT_TOKENS,
Expand All @@ -362,7 +386,7 @@ export class BedrockRuntimeServiceExtension implements ServiceExtension {
responseBody.choices[0].finish_reason,
]);
}
} else if (currentModelId.includes('mistral.mistral')) {
} else if (currentModelId.includes('mistral')) {
if (responseBody.outputs?.[0]?.text !== undefined) {
span.setAttribute(
AwsSpanProcessingUtil.GEN_AI_USAGE_OUTPUT_TOKENS,
Expand Down
54 changes: 54 additions & 0 deletions aws-distro-opentelemetry-node-autoinstrumentation/test/patches/aws/services/bedrock.test.ts
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -517,6 +517,60 @@ describe('BedrockRuntime', () => {
expect(invokeModelSpan.kind).toBe(SpanKind.CLIENT);
});

it('Add Cohere Command R model attributes to span', async () => {
const modelId: string = 'cohere.command-r-v1:0"';
const prompt: string = "Describe the purpose of a 'hello world' program in one line";
const nativeRequest: any = {
message: prompt,
max_tokens: 512,
temperature: 0.5,
p: 0.65,
};
const mockRequestBody: string = JSON.stringify(nativeRequest);
const mockResponseBody: any = {
finish_reason: 'COMPLETE',
text: 'test-generation-text',
prompt: prompt,
request: {
commandInput: {
modelId: modelId,
},
},
};

nock(`https://bedrock-runtime.${region}.amazonaws.com`)
.post(`/model/${encodeURIComponent(modelId)}/invoke`)
.reply(200, mockResponseBody);

await bedrock
.invokeModel({
modelId: modelId,
body: mockRequestBody,
})
.catch((err: any) => {
console.log('error', err);
});

const testSpans: ReadableSpan[] = getTestSpans();
const invokeModelSpans: ReadableSpan[] = testSpans.filter((s: ReadableSpan) => {
return s.name === 'BedrockRuntime.InvokeModel';
});
expect(invokeModelSpans.length).toBe(1);
const invokeModelSpan = invokeModelSpans[0];
expect(invokeModelSpan.attributes[AWS_ATTRIBUTE_KEYS.AWS_BEDROCK_AGENT_ID]).toBeUndefined();
expect(invokeModelSpan.attributes[AWS_ATTRIBUTE_KEYS.AWS_BEDROCK_KNOWLEDGE_BASE_ID]).toBeUndefined();
expect(invokeModelSpan.attributes[AWS_ATTRIBUTE_KEYS.AWS_BEDROCK_DATA_SOURCE_ID]).toBeUndefined();
expect(invokeModelSpan.attributes[AwsSpanProcessingUtil.GEN_AI_SYSTEM]).toBe('aws_bedrock');
expect(invokeModelSpan.attributes[AwsSpanProcessingUtil.GEN_AI_REQUEST_MODEL]).toBe(modelId);
expect(invokeModelSpan.attributes[AwsSpanProcessingUtil.GEN_AI_REQUEST_MAX_TOKENS]).toBe(512);
expect(invokeModelSpan.attributes[AwsSpanProcessingUtil.GEN_AI_REQUEST_TEMPERATURE]).toBe(0.5);
expect(invokeModelSpan.attributes[AwsSpanProcessingUtil.GEN_AI_REQUEST_TOP_P]).toBe(0.65);
expect(invokeModelSpan.attributes[AwsSpanProcessingUtil.GEN_AI_USAGE_INPUT_TOKENS]).toBe(10);
expect(invokeModelSpan.attributes[AwsSpanProcessingUtil.GEN_AI_USAGE_OUTPUT_TOKENS]).toBe(4);
expect(invokeModelSpan.attributes[AwsSpanProcessingUtil.GEN_AI_RESPONSE_FINISH_REASONS]).toEqual(['COMPLETE']);
expect(invokeModelSpan.kind).toBe(SpanKind.CLIENT);
});

it('Add Meta Llama model attributes to span', async () => {
const modelId: string = 'meta.llama2-13b-chat-v1';
const prompt: string = 'Describe the purpose of an interpreter program in one line.';
Expand Down
Loading