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Fix LangChain JS token total metrics #2181
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,5 @@ | ||
| --- | ||
| "braintrust": patch | ||
| --- | ||
|
|
||
| fix: Emit canonical LangChain JS total token metrics |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
|
|
@@ -116,6 +116,7 @@ | |
| "completion_tokens", | ||
| "prompt_cached_tokens", | ||
| "prompt_tokens", | ||
| "tokens", | ||
| "total_tokens" | ||
| ] | ||
| } | ||
|
|
||
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,132 @@ | ||
| import { describe, expect, it, vi } from "vitest"; | ||
| import { BraintrustLangChainCallbackHandler } from "./callback-handler"; | ||
|
|
||
| function createHarness() { | ||
| const logs: unknown[] = []; | ||
| const span = { | ||
| log: vi.fn((event: unknown) => { | ||
| logs.push(event); | ||
| }), | ||
| end: vi.fn(), | ||
| }; | ||
| const parent = { | ||
| startSpan: vi.fn(() => span), | ||
| }; | ||
| const handler = new BraintrustLangChainCallbackHandler({ | ||
| parent: parent as never, | ||
| }); | ||
|
|
||
| return { handler, logs, parent, span }; | ||
| } | ||
|
|
||
| async function finishChatModelRun(output: unknown) { | ||
| const harness = createHarness(); | ||
|
|
||
| await harness.handler.handleChatModelStart( | ||
| { name: "ChatOpenAI" }, | ||
| [[{ role: "user", content: "hello" }]], | ||
| "run-1", | ||
| ); | ||
| await harness.handler.handleLLMEnd(output as never, "run-1"); | ||
|
|
||
| const endLog = harness.logs.at(-1) as { | ||
| metrics?: Record<string, number>; | ||
| }; | ||
| return { ...harness, endLog }; | ||
| } | ||
|
|
||
| describe("BraintrustLangChainCallbackHandler metrics", () => { | ||
| it("synthesizes tokens from message usage metadata prompt and completion counts", async () => { | ||
| const { endLog } = await finishChatModelRun({ | ||
| generations: [ | ||
| [ | ||
| { | ||
| message: { | ||
| usage_metadata: { | ||
| input_tokens: 10, | ||
| output_tokens: 2, | ||
| }, | ||
| }, | ||
| }, | ||
| ], | ||
| ], | ||
| }); | ||
|
|
||
| expect(endLog.metrics).toEqual({ | ||
| prompt_tokens: 10, | ||
| completion_tokens: 2, | ||
| tokens: 12, | ||
| }); | ||
| }); | ||
|
|
||
| it("prefers explicit total tokens from message usage metadata", async () => { | ||
| const { endLog } = await finishChatModelRun({ | ||
| generations: [ | ||
| [ | ||
| { | ||
| message: { | ||
| usage_metadata: { | ||
| input_tokens: 10, | ||
| output_tokens: 2, | ||
| total_tokens: 99, | ||
| }, | ||
| }, | ||
| }, | ||
| ], | ||
| ], | ||
| }); | ||
|
|
||
| expect(endLog.metrics).toEqual({ | ||
| total_tokens: 99, | ||
| prompt_tokens: 10, | ||
| completion_tokens: 2, | ||
| tokens: 99, | ||
| }); | ||
| }); | ||
|
|
||
| it("synthesizes tokens from llmOutput token usage prompt and completion counts", async () => { | ||
| const { endLog } = await finishChatModelRun({ | ||
| llmOutput: { | ||
| tokenUsage: { | ||
| promptTokens: 10, | ||
| completionTokens: 2, | ||
| }, | ||
| }, | ||
| }); | ||
|
|
||
| expect(endLog.metrics).toEqual({ | ||
| prompt_tokens: 10, | ||
| completion_tokens: 2, | ||
| tokens: 12, | ||
| }); | ||
| }); | ||
|
|
||
| it("preserves cache metrics from message usage metadata", async () => { | ||
| const { endLog } = await finishChatModelRun({ | ||
| generations: [ | ||
| [ | ||
| { | ||
| message: { | ||
| usage_metadata: { | ||
| input_tokens: 10, | ||
| output_tokens: 2, | ||
| input_token_details: { | ||
| cache_creation: 4, | ||
| cache_read: 3, | ||
| }, | ||
| }, | ||
| }, | ||
| }, | ||
| ], | ||
| ], | ||
| }); | ||
|
|
||
| expect(endLog.metrics).toEqual({ | ||
| prompt_tokens: 10, | ||
| completion_tokens: 2, | ||
| prompt_cache_creation_tokens: 4, | ||
| prompt_cached_tokens: 3, | ||
| tokens: 12, | ||
| }); | ||
| }); | ||
| }); |
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What's the actual diff between tokens and total_tokens?