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feat(ai): add Vertex Chat entrypoint (#37281)
This commit is contained in:
Shoubhit Dash
@@ -128,11 +128,12 @@ OpenAI Chat and OpenAI Responses are separate semantic entrypoints:
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- `@opencode-ai/ai/providers/openai-compatible/responses`
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- `@opencode-ai/ai/providers/anthropic-compatible`
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- `@opencode-ai/ai/providers/google-vertex/gemini`
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- `@opencode-ai/ai/providers/google-vertex/chat`
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- `@opencode-ai/ai/providers/google-vertex/messages`
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Responses HTTP versus WebSocket is a scoped `transport` setting on the OpenAI Responses entrypoint, not another entrypoint. Azure follows the same Chat/Responses split at `providers/azure/chat` and `providers/azure/responses`. Generic OpenAI-compatible Chat remains at `providers/openai-compatible`; compatible Responses is separate at `providers/openai-compatible/responses`. Generic Anthropic Messages-compatible providers use `providers/anthropic-compatible`, which the named Anthropic provider composes. Google Gemini and Amazon Bedrock expose their single native API through their existing provider paths.
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Vertex Gemini and Vertex Messages are separate API entrypoints. Both accept `project`, `location`, and an optional `accessToken`; when no explicit token or auth override is supplied they lazily use Google Application Default Credentials. Vertex Gemini instead selects express mode when `apiKey` or `GOOGLE_VERTEX_API_KEY` is present. `providers/google-vertex` remains the default alias for `providers/google-vertex/gemini`.
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Vertex Gemini, Vertex Chat, and Vertex Messages are separate API entrypoints. All accept `project`, `location`, and an optional `accessToken`; when no explicit token or auth override is supplied they lazily use Google Application Default Credentials. Vertex Gemini instead selects express mode when `apiKey` or `GOOGLE_VERTEX_API_KEY` is present. Vertex Chat targets MaaS models through the OpenAI-compatible Chat Completions endpoint. `providers/google-vertex` remains the default alias for `providers/google-vertex/gemini`.
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Tuned Vertex Gemini deployments use model ids shaped like `endpoints/1234567890` and require OAuth or ADC; Vertex express-mode API keys support publisher models only.
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@@ -142,6 +143,12 @@ import { model } from "@opencode-ai/ai/providers/google-vertex/gemini"
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model("gemini-3.5-flash", { project: "my-project", location: "global" })
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```
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```ts
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import { model } from "@opencode-ai/ai/providers/google-vertex/chat"
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model("deepseek-ai/deepseek-v3.2-maas", { project: "my-project", location: "global" })
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```
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```ts
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import { model } from "@opencode-ai/ai/providers/google-vertex/messages"
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@@ -24,6 +24,7 @@ This file tracks the gap between the native `@opencode-ai/ai` package and the AI
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| Anthropic Messages | `src/protocols/anthropic-messages.ts`, `src/providers/anthropic.ts` | Usable. Supports tools, thinking, cache control, images, server-hosted tool events, and usage. | Provider option surface is small. Beta/header handling, metadata, and newer Messages fields need a typed parity pass. |
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| Gemini Developer API | `src/protocols/gemini.ts`, `src/providers/google.ts` | Usable for Google API key flow. Supports text, images, tools, thinking signatures, and cache usage. | This is not Vertex. Typed provider options are narrow; many Gemini request fields currently require raw `http.body` overlays. |
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| Vertex Gemini | `src/protocols/gemini.ts`, `src/providers/google-vertex.ts` | Usable through API-key express mode, explicit OAuth tokens, or ADC with project/location endpoint derivation, including tuned `endpoints/...` deployments. | Core runner/catalog mapping and recorded provider coverage are missing. |
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| Vertex Chat | `src/protocols/openai-chat.ts`, `src/providers/google-vertex-chat.ts` | Usable for MaaS models through OpenAI-compatible Chat Completions with explicit OAuth tokens or ADC and project/location endpoint derivation. | Core runner/catalog mapping and recorded provider coverage are missing; MaaS family-specific request parity needs review. |
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| Vertex Messages | `src/protocols/anthropic-messages.ts`, `src/providers/google-vertex-messages.ts` | Usable through explicit OAuth tokens or ADC, including global, regional, and `eu`/`us` multi-region endpoints. | Core runner/catalog mapping and recorded provider coverage are missing; Vertex-specific hosted-tool parity needs review. |
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| Bedrock Converse | `src/protocols/bedrock-converse.ts`, `src/providers/amazon-bedrock.ts` | Partial but real. Supports AWS event-stream framing, SigV4 with supplied credentials, bearer auth, tools, reasoning signatures, media, cache points, and recorded tests. | Native facade does not mirror the AI SDK plugin's default AWS credential chain/profile behavior. Runner/catalog mapping is missing. Guardrails, inference profiles, region-specific model ID fixes, and model-specific request fields need a parity pass. |
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| Azure OpenAI | `src/providers/azure.ts` using OpenAI Chat/Responses protocols | Partial. Supports resource/base URL setup, API key auth, API version query, Chat, and Responses selectors. | Core runner does not map `@ai-sdk/azure` to this native facade. AAD/token auth and Azure-specific endpoint variants need review. |
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@@ -54,7 +55,7 @@ Other `aisdk:` packages, including Google Vertex, Azure, and Bedrock, currently
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| `@ai-sdk/google` | Gemini Developer API | Partial / usable | Add typed options for safety, response schema/modalities, cached content, grounding/search/code execution, and non-text output modes where supported. |
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| `@ai-sdk/google-vertex` | Vertex Gemini namespace/facade | Partial / usable | Add runner/catalog mapping, recorded coverage, and broader provider-option parity. |
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| `@ai-sdk/google-vertex/anthropic` | Anthropic Messages over Vertex namespace/facade | Partial / usable | Add runner/catalog mapping, recorded coverage, and Vertex-specific hosted-tool parity. |
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| `@ai-sdk/google-vertex/maas` | Vertex MaaS OpenAI-compatible namespace/facade | Missing | Decide native Chat/Responses selection, endpoint derivation, auth, and catalog mapping. |
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| `@ai-sdk/google-vertex/maas` | Vertex Chat | Partial / usable | Add runner/catalog mapping, recorded coverage, and MaaS family-specific request parity. |
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| `@ai-sdk/google-vertex/xai` | Vertex xAI OpenAI-compatible namespace/facade | Missing | Decide whether this composes the generic compatible bases or the xAI facade, then add endpoint/auth mapping and tests. |
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| `@ai-sdk/azure` | Azure OpenAI Chat/Responses facade | Partial | Map runner/catalog metadata to native Azure, handle resourceName/baseURL/apiVersion variants, add AAD/token auth story, and verify Chat vs Responses deployment selection. |
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| `@ai-sdk/amazon-bedrock` | Bedrock Converse | Partial | Add default AWS credential chain/profile support, region/inference-profile model ID handling, provider option parity via `additionalModelRequestFields`, guardrails/performance config, and runner/catalog mapping. |
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@@ -65,11 +66,11 @@ Other `aisdk:` packages, including Google Vertex, Azure, and Bedrock, currently
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1. Runner support is narrower than the LLM package. The package has native provider facades for Google, Azure, and Bedrock, but the V2 Session runner only maps OpenAI, Anthropic, and explicit OpenAI-compatible Chat from `aisdk` catalog metadata.
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2. OpenAI-compatible Responses is available as a separate package entrypoint, but the V2 runner still maps `@ai-sdk/openai-compatible` to Chat only. Catalog selection must become API-aware before Responses deployments can use it.
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3. Bedrock native auth is not AI SDK parity. The AI SDK plugin uses the default AWS provider chain, profile, container credentials, and Bedrock bearer token env behavior. Native Bedrock currently expects explicit credentials or bearer auth on the facade.
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4. Vertex Gemini and Vertex Messages now have native package entrypoints, but the core runner does not map catalog metadata to them yet and recorded provider coverage is still missing.
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4. Vertex Gemini, Vertex Chat, and Vertex Messages now have native package entrypoints, but the core runner does not map catalog metadata to them yet and recorded provider coverage is still missing.
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5. Azure is only a provider facade, not a full runtime replacement. Native Azure exists, but the catalog runner does not select it, and token auth/resource variants need review.
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6. Provider option typing is uneven. OpenAI, Anthropic, Gemini, Bedrock, and OpenRouter each expose a small typed subset plus raw HTTP overlays; this is useful but not equivalent to AI SDK provider option coverage.
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7. Structured output is not provider-native yet. `LLM.generateObject` still uses a synthetic tool strategy, while the future design expects native structured output where reliable and tool fallback where needed.
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8. Package/namespace boundaries for the current native loading set are explicit in docs and exports. Other exported provider facades are not catalog package entrypoints until they implement the contract. Missing native boundaries remain for Vertex MaaS, Vertex xAI, and Bedrock Mantle.
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8. Package/namespace boundaries for the current native loading set are explicit in docs and exports. Other exported provider facades are not catalog package entrypoints until they implement the contract. Missing native boundaries remain for Vertex xAI and Bedrock Mantle.
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9. Recorded coverage is uneven. OpenAI, Anthropic, Gemini, Bedrock Converse, Cloudflare, OpenRouter, and several OpenAI-compatible Chat providers have cassettes. Azure, Vertex, and Mantle need first-class recorded scenarios before switching defaults.
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## Native Namespace Shape
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@@ -86,8 +87,8 @@ These are implementation/API slices, not separate npm packages.
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| Anthropic Messages | `@opencode-ai/ai/providers/anthropic` | Anthropic Messages API. |
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| Gemini Developer API | `@opencode-ai/ai/providers/google` | Google AI Studio Gemini API. |
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| Vertex Gemini | `@opencode-ai/ai/providers/google-vertex/gemini` | Vertex Gemini API; `providers/google-vertex` is the default alias. |
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| Vertex Chat | `@opencode-ai/ai/providers/google-vertex/chat` | Vertex OpenAI-compatible Chat Completions for MaaS models. |
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| Vertex Messages | `@opencode-ai/ai/providers/google-vertex/messages` | Vertex-hosted Anthropic Messages API. |
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| Vertex MaaS | Missing | Vertex OpenAI-compatible MaaS APIs. |
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| Vertex xAI | Missing | Vertex-hosted xAI APIs. |
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| Bedrock Converse | `@opencode-ai/ai/providers/amazon-bedrock` | AWS Bedrock Converse API. |
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| Bedrock Mantle | Missing | AWS Bedrock Mantle OpenAI-compatible APIs. |
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@@ -99,8 +100,8 @@ These are implementation/API slices, not separate npm packages.
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1. Add native runner/catalog mappings for `@ai-sdk/azure`, `@ai-sdk/google`, and `@ai-sdk/amazon-bedrock` where the existing native facades are already close.
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2. Add API-aware runner/catalog selection between OpenAI-compatible Chat and Responses.
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3. Bring Bedrock native auth/config to AI SDK parity: region, profile, default AWS credential chain, bearer token env, endpoint override, and cross-region inference profile handling.
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4. Add runner/catalog mappings and recorded scenarios for the native Vertex Gemini and Vertex Messages entrypoints.
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5. Add native Vertex MaaS and Vertex xAI entrypoints by composing the compatible bases and shared Vertex auth/endpoint setup.
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4. Add runner/catalog mappings and recorded scenarios for the native Vertex Gemini, Chat, and Messages entrypoints.
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5. Add native Vertex Responses and decide Chat/Responses selection for Vertex xAI.
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6. Add Bedrock Mantle as a separate OpenAI-compatible Bedrock namespace after deciding whether it uses Chat, Responses, or both by model.
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7. Expand typed provider options from the existing V1 lowerer knowledge in `packages/core/src/v1/config/provider-options.ts` before adding more raw overlay examples.
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8. Add recorded provider tests for Azure, Vertex Gemini, Vertex Messages, Bedrock credential-chain behavior, and Mantle before making native runtime the default for those packages.
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8. Add recorded provider tests for Azure, Vertex Gemini, Vertex Chat, Vertex Messages, Bedrock credential-chain behavior, and Mantle before making native runtime the default for those packages.
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@@ -360,7 +360,7 @@ import { model } from "@opencode-ai/ai/providers/openai/responses"
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model("gpt-4o", { apiKey, transport: "websocket" })
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```
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Vertex keeps Gemini and Messages as separate package-like entrypoints,
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Vertex keeps Gemini, Chat, and Messages as separate package-like entrypoints,
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while sharing project/location resolution and ADC authentication internally:
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```ts
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@@ -369,6 +369,12 @@ import { model } from "@opencode-ai/ai/providers/google-vertex/gemini"
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model("gemini-3.5-flash", { project, location: "global" })
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```
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```ts
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import { model } from "@opencode-ai/ai/providers/google-vertex/chat"
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model("deepseek-ai/deepseek-v3.2-maas", { project, location: "global" })
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```
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```ts
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import { model } from "@opencode-ai/ai/providers/google-vertex/messages"
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@@ -0,0 +1,81 @@
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import type { ProviderPackage } from "../provider-package"
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import { OpenAICompatibleChat } from "../protocols/openai-compatible-chat"
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import type { RouteDefaultsInput } from "../route/client"
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import { ProviderID, type ModelID, type ProviderOptions } from "../schema"
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import { GoogleVertexShared } from "./google-vertex-shared"
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export const id = ProviderID.make("google-vertex")
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export type Config = RouteDefaultsInput &
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GoogleVertexShared.OAuthOptions & {
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readonly baseURL?: string
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readonly location?: string
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readonly project?: string
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}
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export interface Settings extends ProviderPackage.Settings {
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readonly accessToken?: string
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readonly apiKey?: never
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readonly baseURL?: string
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readonly location?: string
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readonly project?: string
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readonly providerOptions?: ProviderOptions
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}
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const route = OpenAICompatibleChat.route.with({
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id: "google-vertex-chat",
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provider: id,
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})
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export const routes = [route]
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const configuredRoute = (input: Config) => {
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if ("apiKey" in input && input.apiKey !== undefined) throw new Error("Google Vertex Chat does not support API keys")
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const {
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accessToken: _accessToken,
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auth: _auth,
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baseURL,
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location: inputLocation,
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project: inputProject,
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...rest
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} = input
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const location = GoogleVertexShared.location(inputLocation, "global")
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const project = GoogleVertexShared.project(inputProject)
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return route.with({
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...rest,
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endpoint: {
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baseURL:
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baseURL ??
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`https://aiplatform.googleapis.com/v1/projects/${GoogleVertexShared.requireProject(project)}/locations/${location}/endpoints/openapi`,
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},
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auth: GoogleVertexShared.oauth(input, project),
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})
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}
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export const configure = (input: Config = {}) => {
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const route = configuredRoute(input)
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return {
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id,
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model: (modelID: string | ModelID) => route.model({ id: modelID }),
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configure,
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}
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}
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export const provider = {
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id,
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configure,
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}
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export const model: ProviderPackage.Definition<Settings>["model"] = (modelID, settings) => {
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if (settings.apiKey !== undefined) throw new Error("Google Vertex Chat does not support API keys")
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return configure({
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accessToken: settings.accessToken,
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baseURL: settings.baseURL,
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headers: settings.headers === undefined ? undefined : { ...settings.headers },
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http: settings.body === undefined ? undefined : { body: { ...settings.body } },
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limits: settings.limits,
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location: settings.location,
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project: settings.project,
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providerOptions: settings.providerOptions,
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}).model(modelID)
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}
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@@ -0,0 +1,2 @@
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export { model } from "../google-vertex-chat"
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export type { Settings } from "../google-vertex-chat"
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@@ -7,6 +7,7 @@ export { CloudflareAIGateway, CloudflareWorkersAI } from "./cloudflare"
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export * as GitHubCopilot from "./github-copilot"
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export * as Google from "./google"
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export * as GoogleVertex from "./google-vertex"
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export * as GoogleVertexChat from "./google-vertex-chat"
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export * as GoogleVertexMessages from "./google-vertex-messages"
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export * as OpenAI from "./openai"
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export * as OpenAICompatible from "./openai-compatible"
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@@ -11,6 +11,7 @@ import * as Cloudflare from "../src/providers/cloudflare"
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import * as GitHubCopilot from "../src/providers/github-copilot"
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import * as Google from "../src/providers/google"
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import * as GoogleVertex from "../src/providers/google-vertex"
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import * as GoogleVertexChat from "../src/providers/google-vertex-chat"
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import * as GoogleVertexMessages from "../src/providers/google-vertex-messages"
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import * as OpenAI from "../src/providers/openai"
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import * as OpenAICompatible from "../src/providers/openai-compatible"
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@@ -171,6 +172,24 @@ GoogleVertex.configure({ accessToken: "vertex-token", apiKey: "vertex-key", proj
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// @ts-expect-error Vertex Gemini package settings accept only one auth source.
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GoogleVertex.model("gemini-3.5-flash", { accessToken: "vertex-token", apiKey: "vertex-key", project: "project" })
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GoogleVertexChat.configure({ accessToken: "vertex-token", project: "project" }).model("deepseek-ai/deepseek-v3.2-maas")
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GoogleVertexChat.configure({ auth: RuntimeAuth.bearer("vertex-token"), project: "project" }).model(
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"deepseek-ai/deepseek-v3.2-maas",
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)
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// @ts-expect-error Vertex Chat package settings do not accept API keys.
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GoogleVertexChat.model("deepseek-ai/deepseek-v3.2-maas", { apiKey: "vertex-key", project: "project" })
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GoogleVertexChat.configure({ accessToken: "vertex-token", project: "project" }).model(
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"deepseek-ai/deepseek-v3.2-maas",
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// @ts-expect-error Vertex Chat model selectors only accept model ids.
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{},
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)
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GoogleVertexChat.configure({
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accessToken: "vertex-token",
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// @ts-expect-error Vertex Chat config accepts only one auth source.
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auth: RuntimeAuth.bearer("vertex-token"),
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project: "project",
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})
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GoogleVertexMessages.configure({ accessToken: "vertex-token", project: "project" }).model("claude-sonnet-4-6")
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// @ts-expect-error Vertex Messages package settings do not accept API keys.
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GoogleVertexMessages.model("claude-sonnet-4-6", { apiKey: "vertex-key", project: "project" })
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@@ -18,6 +18,7 @@ describe("provider package entrypoints", () => {
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import("@opencode-ai/ai/providers/google"),
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import("@opencode-ai/ai/providers/google-vertex"),
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import("@opencode-ai/ai/providers/google-vertex/gemini"),
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import("@opencode-ai/ai/providers/google-vertex/chat"),
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import("@opencode-ai/ai/providers/google-vertex/messages"),
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])
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@@ -182,6 +183,7 @@ describe("provider package entrypoints", () => {
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test("selects Vertex entrypoints with the same model contract", async () => {
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const GoogleVertex = await import("@opencode-ai/ai/providers/google-vertex")
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const GoogleVertexGemini = await import("@opencode-ai/ai/providers/google-vertex/gemini")
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const GoogleVertexChat = await import("@opencode-ai/ai/providers/google-vertex/chat")
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const GoogleVertexMessages = await import("@opencode-ai/ai/providers/google-vertex/messages")
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const gemini = GoogleVertex.model("gemini-3.5-flash", {
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apiKey: "fixture",
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@@ -194,6 +196,11 @@ describe("provider package entrypoints", () => {
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location: "global",
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project: "vertex-project",
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})
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const chat = GoogleVertexChat.model("deepseek-ai/deepseek-v3.2-maas", {
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accessToken: "fixture",
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location: "global",
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project: "vertex-project",
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})
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expect(GoogleVertexGemini.model).toBe(GoogleVertex.model)
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expect(gemini.route.id).toBe("google-vertex-gemini")
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@@ -214,10 +221,17 @@ describe("provider package entrypoints", () => {
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expect(messages.route.endpoint.baseURL).toBe(
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"https://aiplatform.googleapis.com/v1/projects/vertex-project/locations/global/publishers/anthropic/models",
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)
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expect(chat.route.id).toBe("google-vertex-chat")
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expect(chat.route.protocol).toBe("openai-chat")
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expect(chat.route.endpoint).toMatchObject({
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baseURL: "https://aiplatform.googleapis.com/v1/projects/vertex-project/locations/global/endpoints/openapi",
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path: "/chat/completions",
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})
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})
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test("rejects conflicting Vertex auth settings at runtime", async () => {
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const GoogleVertex = await import("@opencode-ai/ai/providers/google-vertex")
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const GoogleVertexChat = await import("@opencode-ai/ai/providers/google-vertex/chat")
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const GoogleVertexMessages = await import("@opencode-ai/ai/providers/google-vertex/messages")
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const Providers = await import("@opencode-ai/ai/providers")
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expect(() =>
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@@ -241,5 +255,16 @@ describe("provider package entrypoints", () => {
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{ apiKey: "fixture", project: "vertex-project" },
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]),
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).toThrow("Google Vertex Messages does not support API keys")
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expect(() =>
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Reflect.apply(GoogleVertexChat.model, undefined, [
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"deepseek-ai/deepseek-v3.2-maas",
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{ apiKey: "fixture", project: "vertex-project" },
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]),
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).toThrow("Google Vertex Chat does not support API keys")
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expect(() =>
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Reflect.apply(Providers.GoogleVertexChat.configure, undefined, [
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{ apiKey: "fixture", project: "vertex-project" },
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]),
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).toThrow("Google Vertex Chat does not support API keys")
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})
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})
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@@ -2,10 +2,11 @@ import { describe, expect } from "bun:test"
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import { Effect } from "effect"
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import { HttpClientRequest } from "effect/unstable/http"
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import { LLM } from "../../src"
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import { GoogleVertex, GoogleVertexMessages } from "../../src/providers"
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import { GoogleVertex, GoogleVertexChat, GoogleVertexMessages } from "../../src/providers"
|
||||
import { LLMClient } from "../../src/route"
|
||||
import { it } from "../lib/effect"
|
||||
import { dynamicResponse } from "../lib/http"
|
||||
import { deltaChunk, finishChunk } from "../lib/openai-chunks"
|
||||
import { sseEvents } from "../lib/sse"
|
||||
|
||||
describe("Google Vertex providers", () => {
|
||||
@@ -99,6 +100,44 @@ describe("Google Vertex providers", () => {
|
||||
}),
|
||||
)
|
||||
|
||||
it.effect("sends MaaS requests through Vertex Chat Completions", () =>
|
||||
Effect.gen(function* () {
|
||||
const response = yield* LLMClient.generate(
|
||||
LLM.request({
|
||||
model: GoogleVertexChat.configure({
|
||||
accessToken: "vertex-token",
|
||||
location: "global",
|
||||
project: "vertex-project",
|
||||
}).model("deepseek-ai/deepseek-v3.2-maas"),
|
||||
prompt: "Say hello.",
|
||||
}),
|
||||
).pipe(
|
||||
Effect.provide(
|
||||
dynamicResponse((input) =>
|
||||
Effect.gen(function* () {
|
||||
const request = yield* HttpClientRequest.toWeb(input.request).pipe(Effect.orDie)
|
||||
expect(request.url).toBe(
|
||||
"https://aiplatform.googleapis.com/v1/projects/vertex-project/locations/global/endpoints/openapi/chat/completions",
|
||||
)
|
||||
expect(request.headers.get("authorization")).toBe("Bearer vertex-token")
|
||||
expect(yield* Effect.promise(() => request.json())).toMatchObject({
|
||||
model: "deepseek-ai/deepseek-v3.2-maas",
|
||||
messages: [{ role: "user", content: "Say hello." }],
|
||||
stream: true,
|
||||
stream_options: { include_usage: true },
|
||||
})
|
||||
return input.respond(sseEvents(deltaChunk({ content: "Hello." }), finishChunk("stop")), {
|
||||
headers: { "content-type": "text/event-stream" },
|
||||
})
|
||||
}),
|
||||
),
|
||||
),
|
||||
)
|
||||
|
||||
expect(response.text).toBe("Hello.")
|
||||
}),
|
||||
)
|
||||
|
||||
it.effect("protects the Vertex Messages API version from body overlays", () =>
|
||||
Effect.gen(function* () {
|
||||
const error = yield* LLMClient.prepare(
|
||||
|
||||
@@ -557,6 +557,7 @@ describe("SessionRunnerModel", () => {
|
||||
const packages = [
|
||||
["@opencode-ai/ai/providers/google-vertex", "accessToken"],
|
||||
["@opencode-ai/ai/providers/google-vertex/gemini", "accessToken"],
|
||||
["@opencode-ai/ai/providers/google-vertex/chat", "accessToken"],
|
||||
["@opencode-ai/ai/providers/google-vertex/messages", "accessToken"],
|
||||
["@opencode-ai/ai/providers/anthropic", "authToken"],
|
||||
["@opencode-ai/ai/providers/anthropic-compatible", "authToken"],
|
||||
|
||||
Reference in New Issue
Block a user