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fix(core): Fix truncation to only keep last message in vercel #19080
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a0fabf0
fix(core): Fix truncation to only keep last message in vercel
nicohrubec a14a741
no longer set gen_ai.prompt in vercel
nicohrubec 0a8a976
clean
nicohrubec c1d8eea
handle messages array input
nicohrubec 85f963b
truncate ai.prompt as well
nicohrubec d746121
fix tests
nicohrubec ed69ebd
let's try again
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51 changes: 51 additions & 0 deletions
51
dev-packages/node-integration-tests/suites/tracing/vercelai/scenario-message-truncation.mjs
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,51 @@ | ||
| import * as Sentry from '@sentry/node'; | ||
| import { generateText } from 'ai'; | ||
| import { MockLanguageModelV1 } from 'ai/test'; | ||
|
|
||
| async function run() { | ||
| await Sentry.startSpan({ op: 'function', name: 'main' }, async () => { | ||
| const largeContent1 = 'A'.repeat(15000); // ~15KB | ||
| const largeContent2 = 'B'.repeat(15000); // ~15KB | ||
| const largeContent3 = 'C'.repeat(25000) + 'D'.repeat(25000); // ~50KB (will be truncated) | ||
|
|
||
| // Test 1: Messages array with large last message that gets truncated | ||
| // Only the last message should be kept, and it should be truncated to only Cs | ||
| await generateText({ | ||
| experimental_telemetry: { isEnabled: true }, | ||
| model: new MockLanguageModelV1({ | ||
| doGenerate: async () => ({ | ||
| rawCall: { rawPrompt: null, rawSettings: {} }, | ||
| finishReason: 'stop', | ||
| usage: { promptTokens: 10, completionTokens: 5 }, | ||
| text: 'Response to truncated messages', | ||
| }), | ||
| }), | ||
| messages: [ | ||
| { role: 'user', content: largeContent1 }, | ||
| { role: 'assistant', content: largeContent2 }, | ||
| { role: 'user', content: largeContent3 }, | ||
| ], | ||
| }); | ||
|
|
||
| // Test 2: Messages array where last message is small and kept intact | ||
| const smallContent = 'This is a small message that fits within the limit'; | ||
| await generateText({ | ||
| experimental_telemetry: { isEnabled: true }, | ||
| model: new MockLanguageModelV1({ | ||
| doGenerate: async () => ({ | ||
| rawCall: { rawPrompt: null, rawSettings: {} }, | ||
| finishReason: 'stop', | ||
| usage: { promptTokens: 10, completionTokens: 5 }, | ||
| text: 'Response to small message', | ||
| }), | ||
| }), | ||
| messages: [ | ||
| { role: 'user', content: largeContent1 }, | ||
| { role: 'assistant', content: largeContent2 }, | ||
| { role: 'user', content: smallContent }, | ||
| ], | ||
| }); | ||
| }); | ||
| } | ||
|
|
||
| run(); |
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