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fix(ai): harden Gemini tool call id handling on Vertex and duplicate streams (#44454)

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This commit is contained in:
Aiden Cline
2026-08-23 12:31:30 -05:00
committed by GitHub
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parent 697e3e13cc
commit e012a57d1d
14 changed files with 620 additions and 40 deletions
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packages/ai/src/protocols/gemini.ts
+25 -19
View File
@@ -41,6 +41,13 @@ const requiresThoughtSignatureFallback = (modelID: string) => {
// so their tool-result attachments lower as a separate user turn instead.
const routesLegacyToolMedia = (modelID: string) => /gemini-2[.-]5(?:[.-]|$)/i.test(modelID)
// Blacklist: Gemini 1.x/2.x ignore or reject explicit function call ids.
// Every other model id (Gemini 3+, gemma, anything unrecognized) gets them.
const omitsFunctionCallIds = (modelID: string) => {
const match = /^gemini(?:-live)?-(\d+)/i.exec(modelID)
return match !== null && Number(match[1]) < 3
}
export interface OptionsInput {
readonly [key: string]: unknown
readonly cachedContent?: string
@@ -217,6 +224,7 @@ interface ParserState {
readonly lifecycle: Lifecycle.State
readonly reasoningSignature?: string
readonly textSignature?: string
readonly seenCallIds?: ReadonlySet<string>
}
// =============================================================================
@@ -274,20 +282,14 @@ const thoughtSignature = (providerMetadata: ProviderMetadata | undefined) => {
: undefined
}
const functionCallId = (providerMetadata: ProviderMetadata | undefined) => {
const google = providerMetadata?.google
return ProviderShared.isRecord(google) && typeof google.functionCallId === "string"
? google.functionCallId
: undefined
}
const lowerToolCall = (part: ToolCallPart) => ({
functionCall: { id: functionCallId(part.providerMetadata), name: part.name, args: part.input },
const lowerToolCall = (part: ToolCallPart, omitIds: boolean) => ({
functionCall: { ...(omitIds ? {} : { id: part.id }), name: part.name, args: part.input },
thoughtSignature: thoughtSignature(part.providerMetadata),
})
const lowerMessages = Effect.fn("Gemini.lowerMessages")(function* (request: LLMRequest) {
const contents: GeminiContent[] = []
const omitCallIds = omitsFunctionCallIds(request.model.id)
const legacyToolMedia = routesLegacyToolMedia(request.model.id)
let pendingMedia: GeminiInlineDataPart[] | undefined
const flushMedia = () => {
@@ -336,7 +338,7 @@ const lowerMessages = Effect.fn("Gemini.lowerMessages")(function* (request: LLMR
continue
}
if (part.type === "tool-call") {
const lowered = lowerToolCall(part)
const lowered = lowerToolCall(part, omitCallIds)
const signature = lowered.thoughtSignature
parts.push({
...lowered,
@@ -361,7 +363,7 @@ const lowerMessages = Effect.fn("Gemini.lowerMessages")(function* (request: LLMR
if (part.result.type !== "content") {
parts.push({
functionResponse: {
id: functionCallId(part.providerMetadata),
...(omitCallIds ? {} : { id: part.id }),
name: part.name,
response: {
name: part.name,
@@ -382,7 +384,7 @@ const lowerMessages = Effect.fn("Gemini.lowerMessages")(function* (request: LLMR
if (legacyToolMedia && media.length > 0) (pendingMedia ??= []).push(...media)
parts.push({
functionResponse: {
id: functionCallId(part.providerMetadata),
...(omitCallIds ? {} : { id: part.id }),
name: part.name,
response: {
name: part.name,
@@ -581,6 +583,8 @@ const step = (state: ParserState, event: GeminiEvent) => {
let lifecycle = nextState.lifecycle
let reasoningSignature = nextState.reasoningSignature
let textSignature = nextState.textSignature
// Supplier ids must be tracked across chunks of the same response, not just within one event's parts.
const seenCallIds = new Set(nextState.seenCallIds)
for (const part of candidate.content.parts) {
const signature = "thoughtSignature" in part && part.thoughtSignature ? part.thoughtSignature : undefined
@@ -618,13 +622,13 @@ const step = (state: ParserState, event: GeminiEvent) => {
if ("functionCall" in part) {
const input = part.functionCall.args === undefined ? {} : part.functionCall.args
// Gemini 2.0+ and Vertex supply a unique function call ID on the part; when omitted (e.g. Gemini 1.5),
// Gemini 2.0+ supplies a unique function call ID on the part; when omitted (e.g. Gemini 1.5),
// generate a globally unique ID rather than a per-request counter to prevent cross-request collisions in downstream registries.
const id = part.functionCall.id ?? `tool_${crypto.randomUUID().replaceAll("-", "")}`
const metadata = {
...(part.functionCall.id === undefined ? {} : { functionCallId: part.functionCall.id }),
...(part.thoughtSignature === undefined ? {} : { thoughtSignature: part.thoughtSignature }),
}
// A repeated supplier id would replay as two identical calls, so only the first occurrence keeps it.
const supplied = part.functionCall.id
const duplicate = supplied !== undefined && seenCallIds.has(supplied)
if (supplied !== undefined) seenCallIds.add(supplied)
const id = supplied !== undefined && !duplicate ? supplied : `tool_${crypto.randomUUID().replaceAll("-", "")}`
lifecycle = Lifecycle.reasoningEnd(
lifecycle,
events,
@@ -637,7 +641,8 @@ const step = (state: ParserState, event: GeminiEvent) => {
id,
name: part.functionCall.name,
input,
providerMetadata: Object.keys(metadata).length > 0 ? googleMetadata(metadata) : undefined,
providerMetadata:
part.thoughtSignature === undefined ? undefined : googleMetadata({ thoughtSignature: part.thoughtSignature }),
}),
)
hasToolCalls = true
@@ -651,6 +656,7 @@ const step = (state: ParserState, event: GeminiEvent) => {
lifecycle,
reasoningSignature,
textSignature,
seenCallIds,
finishReason: candidate.finishReason ?? nextState.finishReason,
},
events,
packages/ai/src/providers/google-vertex.ts
+11 -1
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@@ -38,13 +38,23 @@ export type Settings = ProviderPackage.Settings &
const fromRequest = Effect.fn("GoogleVertex.fromRequest")(function* (request: LLMRequest) {
const body = yield* Gemini.protocol.body.from(request)
// Vertex's native REST schema rejects `id` on FunctionCall/FunctionResponse parts with HTTP 400,
// unlike AI Studio, so history minted there cannot be lowered verbatim.
const contents = body.contents.map((content) => ({
...content,
parts: content.parts.map((part) => {
if ("functionCall" in part) return { ...part, functionCall: { ...part.functionCall, id: undefined } }
if ("functionResponse" in part) return { ...part, functionResponse: { ...part.functionResponse, id: undefined } }
return part
}),
}))
const value = request.providerOptions?.labels
const labels = ProviderShared.isRecord(value)
? Object.fromEntries(
Object.entries(value).filter((entry): entry is [string, string] => typeof entry[1] === "string"),
)
: undefined
return { ...body, labels }
return { ...body, contents, labels }
})
const protocol = {
packages/ai/test/fixtures/recordings/azure/chat-streams-text.json
Vendored
+31
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@@ -0,0 +1,31 @@
{
"version": 1,
"metadata": {
"tags": [
"prefix:azure",
"provider:azure"
],
"name": "azure/chat-streams-text",
"recordedAt": "2026-08-23T17:21:53.198Z"
},
"interactions": [
{
"transport": "http",
"request": {
"method": "POST",
"url": "https://aiden-azury-group.openai.azure.com/openai/v1/chat/completions?api-version=v1",
"headers": {
"content-type": "application/json"
},
"body": "{\"model\":\"gpt-5.6-luna\",\"messages\":[{\"role\":\"user\",\"content\":\"Reply with exactly one word: hello\"}],\"stream\":true,\"stream_options\":{\"include_usage\":true},\"store\":false,\"reasoning_effort\":\"medium\"}"
},
"response": {
"status": 200,
"headers": {
"content-type": "text/event-stream; charset=utf-8"
},
"body": "data: {\"choices\":[],\"created\":0,\"id\":\"\",\"model\":\"\",\"object\":\"\",\"prompt_filter_results\":[{\"prompt_index\":0,\"content_filter_results\":{}}]}\n\ndata: {\"choices\":[{\"content_filter_results\":{},\"delta\":{\"content\":\"\",\"refusal\":null,\"role\":\"assistant\"},\"finish_reason\":null,\"index\":0,\"logprobs\":null}],\"created\":1787505712,\"id\":\"chatcmpl-EG6BEiYSfrcTSI2WX8PqNzERZDcPc\",\"model\":\"gpt-5.6-luna-2026-07-09\",\"obfuscation\":\"Mxr\",\"object\":\"chat.completion.chunk\",\"service_tier\":\"default\",\"system_fingerprint\":null,\"usage\":null}\n\ndata: {\"choices\":[{\"content_filter_results\":{},\"delta\":{\"content\":\"hello\"},\"finish_reason\":null,\"index\":0,\"logprobs\":null}],\"created\":1787505712,\"id\":\"chatcmpl-EG6BEiYSfrcTSI2WX8PqNzERZDcPc\",\"model\":\"gpt-5.6-luna-2026-07-09\",\"obfuscation\":\"\",\"object\":\"chat.completion.chunk\",\"service_tier\":\"default\",\"system_fingerprint\":null,\"usage\":null}\n\ndata: {\"choices\":[{\"content_filter_results\":{},\"delta\":{},\"finish_reason\":\"stop\",\"index\":0,\"logprobs\":null}],\"created\":1787505712,\"id\":\"chatcmpl-EG6BEiYSfrcTSI2WX8PqNzERZDcPc\",\"model\":\"gpt-5.6-luna-2026-07-09\",\"obfuscation\":\"WyZa5AY1CaCeFdS\",\"object\":\"chat.completion.chunk\",\"service_tier\":\"default\",\"system_fingerprint\":null,\"usage\":null}\n\ndata: {\"choices\":[],\"created\":1787505712,\"id\":\"chatcmpl-EG6BEiYSfrcTSI2WX8PqNzERZDcPc\",\"latency_checkpoint\":{\"engine_tbt_ms\":20,\"engine_ttft_ms\":106,\"engine_ttlt_ms\":206,\"pre_inference_ms\":89,\"service_tbt_ms\":20,\"service_ttft_ms\":480,\"service_ttlt_ms\":576,\"total_duration_ms\":491,\"user_visible_ttft_ms\":391},\"model\":\"gpt-5.6-luna-2026-07-09\",\"obfuscation\":\"6\",\"object\":\"chat.completion.chunk\",\"service_tier\":\"default\",\"system_fingerprint\":null,\"usage\":{\"completion_tokens\":5,\"completion_tokens_details\":{\"accepted_prediction_tokens\":0,\"audio_tokens\":0,\"reasoning_tokens\":0,\"rejected_prediction_tokens\":0},\"prompt_tokens\":13,\"prompt_tokens_details\":{\"audio_tokens\":0,\"cache_write_tokens\":0,\"cached_tokens\":0},\"total_tokens\":18}}\n\ndata: [DONE]\n\n"
}
}
]
}
packages/ai/test/fixtures/recordings/azure/responses-calls-a-tool.json
Vendored
+31
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packages/ai/test/fixtures/recordings/azure/responses-continues-after-a-tool-result.json
Vendored
+31
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packages/ai/test/fixtures/recordings/azure/responses-streams-text.json
Vendored
+31
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packages/ai/test/fixtures/recordings/google-vertex/calls-a-tool.json
Vendored
+32
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@@ -0,0 +1,32 @@
{
"version": 1,
"metadata": {
"tags": [
"prefix:google-vertex",
"provider:google-vertex",
"protocol:gemini"
],
"name": "google-vertex/calls-a-tool",
"recordedAt": "2026-08-23T17:21:51.036Z"
},
"interactions": [
{
"transport": "http",
"request": {
"method": "POST",
"url": "https://aiplatform.googleapis.com/v1/publishers/google/models/gemini-3.5-flash:streamGenerateContent?alt=sse",
"headers": {
"content-type": "application/json"
},
"body": "{\"contents\":[{\"role\":\"user\",\"parts\":[{\"text\":\"What is the weather in Paris? Use the lookup_weather tool.\"}]}],\"tools\":[{\"functionDeclarations\":[{\"name\":\"lookup_weather\",\"description\":\"Look up the current weather for a city\",\"parameters\":{\"required\":[\"city\"],\"type\":\"object\",\"properties\":{\"city\":{\"type\":\"string\"}}}}]}]}"
},
"response": {
"status": 200,
"headers": {
"content-type": "text/event-stream"
},
"body": "data: {\"candidates\": [{\"content\": {\"role\": \"model\",\"parts\": [{\"functionCall\": {\"name\": \"lookup_weather\",\"args\": {\"city\": \"Paris\"},\"id\": \"call_425130\"},\"thoughtSignature\": \"AY89a1+1fXnLgYhHMuN3Ak6LBhT6PcrYOW7iPav4LfsacvG/Z6l1yJ+AsU7vWhFj/JyPIbsJJQ+GjohM9sCIZ6nqUOIg3reo/7osmrCvFrVHedTHQcwiPzoz2Kp3gb+uWjFAXxk1EX4IRAKcu0ox1W/Z9PpuZvHkTerGO2a82e02N6MAF1YhhtbXFvSdqLRih2Os68rdOk5/Bcld7ol8qUgeyIZ3CtI3OJ5jwRcD8LjvK33A7ZFzH5Bxp/peUmXvqnu5iNhnGBxZaJy/vupCtxRZxjaS+ojG0/UhyrnRiKIpbzQ0FBkxePPn8GCX/LOe2y3GUc98co8lN8OOuCd9ZmEdx5AjHmQkPO9fAV9SxG6Bda6SDWVL8o/Uz3WSQYoUEfAdoajEWIBvcisoeCJjb7zgmRRZ9VQSPl3RXj5LFRvX8jn0YKV1CahYbc24jA==\"}]}}],\"usageMetadata\": {\"trafficType\": \"ON_DEMAND\"},\"modelVersion\": \"gemini-3.5-flash\",\"createTime\": \"2026-08-23T17:21:50.308576Z\",\"responseId\": \"LiyLauDqErCErb8Pj8aWkAs\"}\r\n\r\ndata: {\"candidates\": [{\"content\": {\"role\": \"model\",\"parts\": [{\"text\": \"\"}]},\"finishReason\": \"STOP\"}],\"usageMetadata\": {\"promptTokenCount\": 39,\"candidatesTokenCount\": 16,\"totalTokenCount\": 102,\"trafficType\": \"ON_DEMAND\",\"promptTokensDetails\": [{\"modality\": \"TEXT\",\"tokenCount\": 39}],\"candidatesTokensDetails\": [{\"modality\": \"TEXT\",\"tokenCount\": 16}],\"thoughtsTokenCount\": 47},\"modelVersion\": \"gemini-3.5-flash\",\"createTime\": \"2026-08-23T17:21:50.308576Z\",\"responseId\": \"LiyLauDqErCErb8Pj8aWkAs\"}\r\n\r\n"
}
}
]
}
packages/ai/test/fixtures/recordings/google-vertex/continues-after-a-tool-result.json
Vendored
+32
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@@ -0,0 +1,32 @@
{
"version": 1,
"metadata": {
"tags": [
"prefix:google-vertex",
"provider:google-vertex",
"protocol:gemini"
],
"name": "google-vertex/continues-after-a-tool-result",
"recordedAt": "2026-08-23T17:21:51.853Z"
},
"interactions": [
{
"transport": "http",
"request": {
"method": "POST",
"url": "https://aiplatform.googleapis.com/v1/publishers/google/models/gemini-3.5-flash:streamGenerateContent?alt=sse",
"headers": {
"content-type": "application/json"
},
"body": "{\"contents\":[{\"role\":\"user\",\"parts\":[{\"text\":\"What is the weather in Paris?\"}]},{\"role\":\"model\",\"parts\":[{\"functionCall\":{\"name\":\"lookup_weather\",\"args\":{\"city\":\"Paris\"}},\"thoughtSignature\":\"skip_thought_signature_validator\"}]},{\"role\":\"user\",\"parts\":[{\"functionResponse\":{\"name\":\"lookup_weather\",\"response\":{\"name\":\"lookup_weather\",\"content\":\"18C, light rain\"}}}]}],\"tools\":[{\"functionDeclarations\":[{\"name\":\"lookup_weather\",\"description\":\"Look up the current weather for a city\",\"parameters\":{\"required\":[\"city\"],\"type\":\"object\",\"properties\":{\"city\":{\"type\":\"string\"}}}}]}]}"
},
"response": {
"status": 200,
"headers": {
"content-type": "text/event-stream"
},
"body": "data: {\"candidates\": [{\"content\": {\"role\": \"model\",\"parts\": [{\"text\": \"The weather in Paris is currently 18°C with light rain.\"}]}}],\"usageMetadata\": {\"trafficType\": \"ON_DEMAND\"},\"modelVersion\": \"gemini-3.5-flash\",\"createTime\": \"2026-08-23T17:21:51.220919Z\",\"responseId\": \"LyyLave9DbWnrb8P1IjLmQQ\"}\r\n\r\ndata: {\"candidates\": [{\"content\": {\"role\": \"model\",\"parts\": [{\"text\": \"\",\"thoughtSignature\": \"AY89a197c+fpHJftPtcufnqMAyoRQKVEQK+KeG+RVHVx2wKil3L4jP4YWvfVbcuOFr2jio4Kre/hCrDANAoMFSvaZrdaPeo1b5bXQSmJKMH03yM5M6q6ME6JiBvXym143U4exIde4UbOh2tMeyXMvB3aWxcavIHd78g5G5QPLreo6A3LO5871cYYVeRwteY+/zbEdqfaAq1hlk6WYpWkNljYpjMyKwr15YC8rFLh3HYayS9tTN++GGrk/reZn6C3OEPlzPou/pXRATzcEAGVl/TW\"}]},\"finishReason\": \"STOP\"}],\"usageMetadata\": {\"promptTokenCount\": 59,\"candidatesTokenCount\": 15,\"totalTokenCount\": 98,\"trafficType\": \"ON_DEMAND\",\"promptTokensDetails\": [{\"modality\": \"TEXT\",\"tokenCount\": 59}],\"candidatesTokensDetails\": [{\"modality\": \"TEXT\",\"tokenCount\": 15}],\"thoughtsTokenCount\": 24},\"modelVersion\": \"gemini-3.5-flash\",\"createTime\": \"2026-08-23T17:21:51.220919Z\",\"responseId\": \"LyyLave9DbWnrb8P1IjLmQQ\"}\r\n\r\n"
}
}
]
}
packages/ai/test/fixtures/recordings/google-vertex/streams-text.json
Vendored
+32
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@@ -0,0 +1,32 @@
{
"version": 1,
"metadata": {
"tags": [
"prefix:google-vertex",
"provider:google-vertex",
"protocol:gemini"
],
"name": "google-vertex/streams-text",
"recordedAt": "2026-08-23T17:21:50.112Z"
},
"interactions": [
{
"transport": "http",
"request": {
"method": "POST",
"url": "https://aiplatform.googleapis.com/v1/publishers/google/models/gemini-3.5-flash:streamGenerateContent?alt=sse",
"headers": {
"content-type": "application/json"
},
"body": "{\"contents\":[{\"role\":\"user\",\"parts\":[{\"text\":\"Reply with exactly one word: hello\"}]}]}"
},
"response": {
"status": 200,
"headers": {
"content-type": "text/event-stream"
},
"body": "data: {\"candidates\": [{\"content\": {\"role\": \"model\",\"parts\": [{\"text\": \"Hello\"}]}}],\"usageMetadata\": {\"trafficType\": \"ON_DEMAND\"},\"modelVersion\": \"gemini-3.5-flash\",\"createTime\": \"2026-08-23T17:21:48.528714Z\",\"responseId\": \"LCyLasqiIO6crb8P1sDboQc\"}\r\n\r\ndata: {\"candidates\": [{\"content\": {\"role\": \"model\",\"parts\": [{\"text\": \"\",\"thoughtSignature\": \"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\"}]},\"finishReason\": \"STOP\"}],\"usageMetadata\": {\"promptTokenCount\": 7,\"candidatesTokenCount\": 1,\"totalTokenCount\": 150,\"trafficType\": \"ON_DEMAND\",\"promptTokensDetails\": [{\"modality\": \"TEXT\",\"tokenCount\": 7}],\"candidatesTokensDetails\": [{\"modality\": \"TEXT\",\"tokenCount\": 1}],\"thoughtsTokenCount\": 142},\"modelVersion\": \"gemini-3.5-flash\",\"createTime\": \"2026-08-23T17:21:48.528714Z\",\"responseId\": \"LCyLasqiIO6crb8P1sDboQc\"}\r\n\r\n"
}
}
]
}
packages/ai/test/provider/azure.recorded.test.ts
+93
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@@ -0,0 +1,93 @@
import { describe, expect } from "bun:test"
import { Effect } from "effect"
import { LLM, Message, ToolDefinition, ToolCallPart } from "../../src/index.js"
import { Azure } from "../../src/providers.js"
import { LLMClient } from "../../src/route.js"
import { recordedTests } from "../recorded-test.js"
const resourceName = process.env.AZURE_OPENAI_RESOURCE_NAME ?? "aiden-azury-group"
const chatModel = Azure.configure({
resourceName,
apiKey: process.env.AZURE_OPENAI_API_KEY ?? "fixture",
}).chat("gpt-5.6-luna")
const responsesModel = Azure.configure({
resourceName,
apiKey: process.env.AZURE_OPENAI_API_KEY ?? "fixture",
}).responses("gpt-5.6-luna")
const lookupWeather = ToolDefinition.make({
name: "lookup_weather",
description: "Look up the current weather for a city",
inputSchema: { type: "object", properties: { city: { type: "string" } }, required: ["city"] },
})
const recorded = recordedTests({
prefix: "azure",
provider: "azure",
requires: ["AZURE_OPENAI_API_KEY"],
})
describe("Azure OpenAI recorded", () => {
recorded.effect("chat streams text", () =>
Effect.gen(function* () {
const response = yield* LLMClient.generate(
LLM.request({ model: chatModel, prompt: "Reply with exactly one word: hello" }),
)
expect(response.text.toLowerCase()).toContain("hello")
}),
)
recorded.effect("responses streams text", () =>
Effect.gen(function* () {
const response = yield* LLMClient.generate(
LLM.request({ model: responsesModel, prompt: "Reply with exactly one word: bonjour" }),
)
expect(response.text.toLowerCase()).toContain("bonjour")
}),
)
recorded.effect("responses calls a tool", () =>
Effect.gen(function* () {
const response = yield* LLMClient.generate(
LLM.request({
model: responsesModel,
prompt: "What is the weather in Paris? Use the lookup_weather tool.",
tools: [lookupWeather],
}),
)
const call = response.toolCalls.find((part) => part.name === "lookup_weather")
expect(call).toBeDefined()
expect(call?.input).toMatchObject({ city: "Paris" })
}),
)
recorded.effect("responses continues after a tool result", () =>
Effect.gen(function* () {
const response = yield* LLMClient.generate(
LLM.request({
model: responsesModel,
messages: [
Message.user("What is the weather in Paris?"),
Message.assistant([
ToolCallPart.make({ id: "call_paris_1", name: "lookup_weather", input: { city: "Paris" } }),
]),
Message.tool({
id: "call_paris_1",
name: "lookup_weather",
result: "18C, light rain",
resultType: "text",
}),
],
tools: [lookupWeather],
}),
)
expect(response.text.length).toBeGreaterThan(0)
}),
)
})
packages/ai/test/provider/gemini.test.ts
+145 -18
View File
@@ -156,14 +156,13 @@ describe("Gemini route", () => {
expect(prepared.body.contents).toEqual([
{
role: "model",
parts: [{ functionCall: { id: undefined, name: "lookup", args: { query: "weather" } } }],
parts: [{ functionCall: { name: "lookup", args: { query: "weather" } } }],
},
{
role: "user",
parts: [
{
functionResponse: {
id: undefined,
name: "lookup",
response: { name: "lookup", content: "done" },
},
@@ -201,8 +200,8 @@ describe("Gemini route", () => {
{
role: "model",
parts: [
{ functionCall: { id: undefined, name: "lookup", args: { query: "weather" } } },
{ functionCall: { id: undefined, name: "lookup", args: { query: "time" } } },
{ functionCall: { name: "lookup", args: { query: "weather" } } },
{ functionCall: { name: "lookup", args: { query: "time" } } },
],
},
{
@@ -210,14 +209,12 @@ describe("Gemini route", () => {
parts: [
{
functionResponse: {
id: undefined,
name: "lookup",
response: { name: "lookup", content: "sunny" },
},
},
{
functionResponse: {
id: undefined,
name: "lookup",
response: { name: "lookup", content: "noon" },
},
@@ -228,6 +225,104 @@ describe("Gemini route", () => {
}),
)
it.effect("lowers function call ids for gemini 3 models", () =>
Effect.gen(function* () {
const prepared = yield* compileRequest(
LLM.request({
model: gemini3,
messages: [
Message.assistant([ToolCallPart.make({ id: "call_1", name: "lookup", input: { query: "weather" } })]),
Message.tool({ id: "call_1", name: "lookup", result: "done", resultType: "text" }),
],
}),
)
expect(prepared.body.contents).toEqual([
{
role: "model",
parts: [
{
functionCall: { id: "call_1", name: "lookup", args: { query: "weather" } },
thoughtSignature: "skip_thought_signature_validator",
},
],
},
{
role: "user",
parts: [
{
functionResponse: {
id: "call_1",
name: "lookup",
response: { name: "lookup", content: "done" },
},
},
],
},
])
}),
)
it.effect("omits function call ids entirely for pre-gemini-3 models", () =>
Effect.gen(function* () {
const messages = [
Message.assistant([ToolCallPart.make({ id: "call_1", name: "lookup", input: { query: "weather" } })]),
Message.tool({ id: "call_1", name: "lookup", result: "done", resultType: "text" }),
]
const legacy = yield* compileRequest(LLM.request({ model, messages }))
const older = yield* compileRequest(
LLM.request({
model: Gemini.route
.with({
endpoint: { baseURL: "https://generativelanguage.test/v1beta/" },
auth: Auth.header("x-goog-api-key", "test"),
})
.model({ id: "gemini-1.5-flash" }),
messages,
}),
)
expect(legacy.body.contents).toEqual([
{ role: "model", parts: [{ functionCall: { name: "lookup", args: { query: "weather" } } }] },
{
role: "user",
parts: [{ functionResponse: { name: "lookup", response: { name: "lookup", content: "done" } } }],
},
])
expect(JSON.stringify(legacy.body.contents)).not.toContain('"id"')
expect(JSON.stringify(older.body.contents)).not.toContain('"id"')
}),
)
it.effect("includes function call ids for non-gemini model ids", () =>
Effect.gen(function* () {
const prepared = yield* compileRequest(
LLM.request({
model: Gemini.route
.with({
endpoint: { baseURL: "https://generativelanguage.test/v1beta/" },
auth: Auth.header("x-goog-api-key", "test"),
})
.model({ id: "gemma-3-27b-it" }),
messages: [
Message.assistant([ToolCallPart.make({ id: "call_1", name: "lookup", input: { query: "weather" } })]),
Message.tool({ id: "call_1", name: "lookup", result: "done", resultType: "text" }),
],
}),
)
expect(prepared.body.contents).toEqual([
{ role: "model", parts: [{ functionCall: { id: "call_1", name: "lookup", args: { query: "weather" } } }] },
{
role: "user",
parts: [
{ functionResponse: { id: "call_1", name: "lookup", response: { name: "lookup", content: "done" } } },
],
},
])
}),
)
it.effect("prepares multimodal user input and tool history", () =>
Effect.gen(function* () {
const prepared = yield* compileRequest(
@@ -419,13 +514,16 @@ describe("Gemini route", () => {
expect(prepared.body.contents).toEqual([
{
role: "model",
parts: [{ functionCall: { name: "read", args: { path: "pixel.png" } }, thoughtSignature: "sig_1" }],
parts: [
{ functionCall: { id: "call_image", name: "read", args: { path: "pixel.png" } }, thoughtSignature: "sig_1" },
],
},
{
role: "user",
parts: [
{
functionResponse: {
id: "call_image",
name: "read",
response: { name: "read", content: "Image read successfully" },
parts: [{ inlineData: { mimeType: "image/png", data: "AAECAw==" } }],
@@ -849,7 +947,7 @@ describe("Gemini route", () => {
})
expect(toolCall).toMatchObject({
id: "provider_call",
providerMetadata: { google: { functionCallId: "provider_call", thoughtSignature: "tool_sig" } },
providerMetadata: { google: { thoughtSignature: "tool_sig" } },
})
expect(response.events.findIndex((event) => event.type === "reasoning-end")).toBeLessThan(
response.events.findIndex((event) => event.type === "tool-call"),
@@ -857,7 +955,7 @@ describe("Gemini route", () => {
const prepared = yield* compileRequest(
LLM.request({
model,
model: gemini3,
messages: [
Message.assistant([
{ type: "reasoning", text: "thinking", providerMetadata: reasoningEnd?.providerMetadata },
@@ -873,7 +971,6 @@ describe("Gemini route", () => {
name: "lookup",
result: "done",
resultType: "text",
providerMetadata: toolCall?.providerMetadata,
}),
],
}),
@@ -977,7 +1074,7 @@ describe("Gemini route", () => {
role: "model",
parts: [
{
functionCall: { id: undefined, name: "lookup", args: { query: "weather" } },
functionCall: { id: "tool_0", name: "lookup", args: { query: "weather" } },
thoughtSignature: "skip_thought_signature_validator",
},
],
@@ -987,7 +1084,7 @@ describe("Gemini route", () => {
parts: [
{
functionResponse: {
id: undefined,
id: "tool_0",
name: "lookup",
response: { name: "lookup", content: "done" },
},
@@ -1023,15 +1120,15 @@ describe("Gemini route", () => {
role: "model",
parts: [
{
functionCall: { id: undefined, name: "lookup", args: { query: "weather" } },
functionCall: { id: "tool_0", name: "lookup", args: { query: "weather" } },
thoughtSignature: "parallel_signature",
},
{
functionCall: { id: undefined, name: "lookup", args: { query: "news" } },
functionCall: { id: "tool_1", name: "lookup", args: { query: "news" } },
thoughtSignature: undefined,
},
{
functionCall: { id: undefined, name: "lookup", args: { query: "sports" } },
functionCall: { id: "tool_2", name: "lookup", args: { query: "sports" } },
thoughtSignature: undefined,
},
],
@@ -1059,11 +1156,11 @@ describe("Gemini route", () => {
role: "model",
parts: [
{
functionCall: { id: undefined, name: "lookup", args: { query: "weather" } },
functionCall: { id: "tool_0", name: "lookup", args: { query: "weather" } },
thoughtSignature: "skip_thought_signature_validator",
},
{
functionCall: { id: undefined, name: "lookup", args: { query: "news" } },
functionCall: { id: "tool_1", name: "lookup", args: { query: "news" } },
thoughtSignature: "skip_thought_signature_validator",
},
],
@@ -1214,7 +1311,6 @@ describe("Gemini route", () => {
id: "call_0",
name: "lookup",
input: { query: "weather" },
providerMetadata: { google: { functionCallId: "call_0" } },
})
expect(response.toolCalls[1]).toMatchObject({
type: "tool-call",
@@ -1230,6 +1326,37 @@ describe("Gemini route", () => {
}),
)
it.effect("replaces repeated supplier ids with fresh fallback ids", () =>
Effect.gen(function* () {
const body = sseEvents({
candidates: [
{
content: {
role: "model",
parts: [
{ functionCall: { id: "dup_call", name: "lookup", args: { query: "weather" } } },
{ functionCall: { id: "dup_call", name: "lookup", args: { query: "news" } } },
],
},
finishReason: "STOP",
},
],
})
const response = yield* LLMClient.generate(
LLMRequest.update(request, {
tools: [ToolDefinition.make({ name: "lookup", description: "Lookup data", inputSchema: { type: "object" } })],
}),
).pipe(Effect.provide(fixedResponse(body)))
expect(response.toolCalls[0]).toMatchObject({
id: "dup_call",
providerMetadata: undefined,
})
expect(response.toolCalls[1].id).toMatch(/^tool_[0-9a-zA-Z]+$/)
expect(response.toolCalls[1].id).not.toBe(response.toolCalls[0].id)
}),
)
it.effect("assigns distinct unique fallback ids across separate requests", () =>
Effect.gen(function* () {
const body = sseEvents({
packages/ai/test/provider/google-vertex.recorded.test.ts
+77
View File
@@ -0,0 +1,77 @@
import { describe, expect } from "bun:test"
import { Effect } from "effect"
import { LLM, Message, ToolDefinition, ToolCallPart } from "../../src/index.js"
import { GoogleVertex } from "../../src/providers.js"
import { LLMClient } from "../../src/route.js"
import { recordedTests } from "../recorded-test.js"
const model = GoogleVertex.configure({
apiKey: process.env.GOOGLE_VERTEX_API_KEY ?? "fixture",
}).model("gemini-3.5-flash")
const lookupWeather = ToolDefinition.make({
name: "lookup_weather",
description: "Look up the current weather for a city",
inputSchema: { type: "object", properties: { city: { type: "string" } }, required: ["city"] },
})
const recorded = recordedTests({
prefix: "google-vertex",
provider: "google-vertex",
protocol: "gemini",
requires: ["GOOGLE_VERTEX_API_KEY"],
})
describe("Google Vertex Gemini recorded", () => {
recorded.effect("streams text", () =>
Effect.gen(function* () {
const response = yield* LLMClient.generate(
LLM.request({ model, prompt: "Reply with exactly one word: hello" }),
)
expect(response.text.toLowerCase()).toContain("hello")
}),
)
recorded.effect("calls a tool", () =>
Effect.gen(function* () {
const response = yield* LLMClient.generate(
LLM.request({
model,
prompt: "What is the weather in Paris? Use the lookup_weather tool.",
tools: [lookupWeather],
}),
)
const call = response.toolCalls.find((part) => part.name === "lookup_weather")
expect(call).toBeDefined()
expect(call?.input).toMatchObject({ city: "Paris" })
}),
)
recorded.effect("continues after a tool result", () =>
Effect.gen(function* () {
const response = yield* LLMClient.generate(
LLM.request({
model,
messages: [
Message.user("What is the weather in Paris?"),
Message.assistant([
ToolCallPart.make({ id: "call_paris_1", name: "lookup_weather", input: { city: "Paris" } }),
]),
Message.tool({
id: "call_paris_1",
name: "lookup_weather",
result: "18C, light rain",
resultType: "text",
}),
],
tools: [lookupWeather],
}),
)
expect(response.text.length).toBeGreaterThan(0)
}),
)
})
packages/ai/test/provider/google-vertex.test.ts
+48 -1
View File
@@ -1,7 +1,7 @@
import { describe, expect } from "bun:test"
import { Effect } from "effect"
import { HttpClientRequest } from "effect/unstable/http"
import { LLM } from "../../src/index.js"
import { LLM, Message, ToolCallPart } from "../../src/index.js"
import { GoogleVertex, GoogleVertexChat, GoogleVertexMessages, GoogleVertexResponses } from "../../src/providers.js"
import { LLMClient } from "../../src/route.js"
import { compileRequest } from "../../src/route/client.js"
@@ -75,6 +75,53 @@ describe("Google Vertex providers", () => {
}),
)
it.effect("strips function call ids Vertex does not accept from lowered bodies", () =>
Effect.gen(function* () {
const prepared = yield* compileRequest(
LLM.request({
model: GoogleVertex.configure({
accessToken: "vertex-token",
project: "vertex-project",
}).model("gemini-3.5-flash"),
messages: [
Message.assistant([
ToolCallPart.make({
id: "call_1",
name: "lookup",
input: { query: "weather" },
providerMetadata: { google: { functionCallId: "provider_call_1" } },
}),
]),
Message.tool({
id: "call_1",
name: "lookup",
result: "sunny",
resultType: "text",
providerMetadata: { google: { functionCallId: "provider_call_1" } },
}),
],
}),
)
expect(JSON.stringify(prepared.body.contents)).not.toContain('"id"')
expect(prepared.body.contents).toMatchObject([
{ role: "model", parts: [{ functionCall: { id: undefined, name: "lookup", args: { query: "weather" } } }] },
{
role: "user",
parts: [
{
functionResponse: {
id: undefined,
name: "lookup",
response: { name: "lookup", content: "sunny" },
},
},
],
},
])
}),
)
it.effect("projects Anthropic Messages onto the Vertex raw-predict API", () =>
Effect.gen(function* () {
const model = GoogleVertexMessages.configure({
packages/ai/test/tool-runtime.test.ts
+1 -1
View File
@@ -191,7 +191,7 @@ describe("LLMClient tools", () => {
success: Schema.String,
execute: () => Effect.succeed("hello"),
})
const providerMetadata = { google: { functionCallId: "provider_call" } }
const providerMetadata = { google: { thoughtSignature: "provider_sig" } }
const dispatched = yield* ToolRuntime.dispatch(
{ tool },
LLMEvent.toolCall({ id: "call_1", name: "tool", input: {}, providerMetadata }),