Merge pull request #2371 from code-yeongyu/fix/issue-2323
fix: respect multimodal provider vision capabilities
This commit is contained in:
@@ -0,0 +1,84 @@
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/// <reference types="bun-types" />
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import { describe, expect, test } from "bun:test"
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import { applyProviderConfig } from "./provider-config-handler"
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import { createModelCacheState } from "../plugin-state"
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import { clearVisionCapableModelsCache, readVisionCapableModelsCache } from "../shared/vision-capable-models-cache"
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describe("applyProviderConfig", () => {
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test("caches vision-capable models from modalities and capabilities", () => {
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// given
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const modelCacheState = createModelCacheState()
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const visionCapableModelsCache = modelCacheState.visionCapableModelsCache
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if (!visionCapableModelsCache) {
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throw new Error("visionCapableModelsCache should be initialized")
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}
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const config = {
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provider: {
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rundao: {
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models: {
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"public/qwen3.5-397b": {
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modalities: {
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input: ["text", "image"],
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},
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},
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"public/text-only": {
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modalities: {
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input: ["text"],
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},
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},
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},
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},
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google: {
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models: {
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"gemini-3-flash": {
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capabilities: {
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input: {
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image: true,
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},
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},
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},
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},
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},
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},
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} satisfies Record<string, unknown>
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// when
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applyProviderConfig({ config, modelCacheState })
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// then
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expect(Array.from(visionCapableModelsCache.keys())).toEqual([
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"rundao/public/qwen3.5-397b",
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"google/gemini-3-flash",
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])
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expect(readVisionCapableModelsCache()).toEqual([
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{ providerID: "rundao", modelID: "public/qwen3.5-397b" },
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{ providerID: "google", modelID: "gemini-3-flash" },
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])
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})
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test("clears stale vision-capable models when provider config changes", () => {
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// given
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const modelCacheState = createModelCacheState()
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const visionCapableModelsCache = modelCacheState.visionCapableModelsCache
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if (!visionCapableModelsCache) {
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throw new Error("visionCapableModelsCache should be initialized")
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}
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visionCapableModelsCache.set("stale/old-model", {
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providerID: "stale",
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modelID: "old-model",
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})
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// when
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applyProviderConfig({
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config: { provider: {} },
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modelCacheState,
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})
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// then
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expect(visionCapableModelsCache.size).toBe(0)
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expect(readVisionCapableModelsCache()).toEqual([])
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})
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})
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clearVisionCapableModelsCache()
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@@ -1,10 +1,31 @@
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import type { ModelCacheState } from "../plugin-state";
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import type { ModelCacheState, VisionCapableModel } from "../plugin-state";
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import { setVisionCapableModelsCache } from "../shared/vision-capable-models-cache"
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type ProviderConfig = {
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type ProviderConfig = {
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options?: { headers?: Record<string, string> };
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options?: { headers?: Record<string, string> };
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models?: Record<string, { limit?: { context?: number } }>;
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models?: Record<string, ProviderModelConfig>;
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};
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};
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type ProviderModelConfig = {
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limit?: { context?: number };
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modalities?: {
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input?: string[];
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};
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capabilities?: {
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input?: {
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image?: boolean;
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};
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};
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}
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function supportsImageInput(modelConfig: ProviderModelConfig | undefined): boolean {
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if (modelConfig?.modalities?.input?.includes("image")) {
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return true
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}
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return modelConfig?.capabilities?.input?.image === true
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}
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export function applyProviderConfig(params: {
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export function applyProviderConfig(params: {
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config: Record<string, unknown>;
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config: Record<string, unknown>;
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modelCacheState: ModelCacheState;
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modelCacheState: ModelCacheState;
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@@ -17,6 +38,12 @@ export function applyProviderConfig(params: {
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params.modelCacheState.anthropicContext1MEnabled =
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params.modelCacheState.anthropicContext1MEnabled =
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anthropicBeta?.includes("context-1m") ?? false;
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anthropicBeta?.includes("context-1m") ?? false;
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const visionCapableModelsCache = params.modelCacheState.visionCapableModelsCache
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?? new Map<string, VisionCapableModel>()
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params.modelCacheState.visionCapableModelsCache = visionCapableModelsCache
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visionCapableModelsCache.clear()
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setVisionCapableModelsCache(visionCapableModelsCache)
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if (!providers) return;
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if (!providers) return;
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for (const [providerID, providerConfig] of Object.entries(providers)) {
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for (const [providerID, providerConfig] of Object.entries(providers)) {
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@@ -24,6 +51,13 @@ export function applyProviderConfig(params: {
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if (!models) continue;
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if (!models) continue;
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for (const [modelID, modelConfig] of Object.entries(models)) {
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for (const [modelID, modelConfig] of Object.entries(models)) {
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if (supportsImageInput(modelConfig)) {
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visionCapableModelsCache.set(
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`${providerID}/${modelID}`,
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{ providerID, modelID },
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)
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}
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const contextLimit = modelConfig?.limit?.context;
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const contextLimit = modelConfig?.limit?.context;
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if (!contextLimit) continue;
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if (!contextLimit) continue;
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@@ -1,11 +1,18 @@
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export type VisionCapableModel = {
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providerID: string
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modelID: string
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}
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export interface ModelCacheState {
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export interface ModelCacheState {
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modelContextLimitsCache: Map<string, number>;
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modelContextLimitsCache: Map<string, number>;
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visionCapableModelsCache?: Map<string, VisionCapableModel>;
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anthropicContext1MEnabled: boolean;
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anthropicContext1MEnabled: boolean;
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}
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}
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export function createModelCacheState(): ModelCacheState {
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export function createModelCacheState(): ModelCacheState {
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return {
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return {
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modelContextLimitsCache: new Map<string, number>(),
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modelContextLimitsCache: new Map<string, number>(),
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visionCapableModelsCache: new Map<string, VisionCapableModel>(),
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anthropicContext1MEnabled: false,
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anthropicContext1MEnabled: false,
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};
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};
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}
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}
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@@ -0,0 +1,17 @@
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import type { VisionCapableModel } from "../plugin-state"
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let visionCapableModelsCache = new Map<string, VisionCapableModel>()
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export function setVisionCapableModelsCache(
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cache: Map<string, VisionCapableModel>,
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): void {
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visionCapableModelsCache = cache
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}
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export function readVisionCapableModelsCache(): VisionCapableModel[] {
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return Array.from(visionCapableModelsCache.values())
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}
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export function clearVisionCapableModelsCache(): void {
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visionCapableModelsCache = new Map<string, VisionCapableModel>()
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}
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@@ -0,0 +1,115 @@
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/// <reference types="bun-types" />
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import { afterEach, beforeEach, describe, expect, mock, spyOn, test } from "bun:test"
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import type { PluginInput } from "@opencode-ai/plugin"
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import { resolveMultimodalLookerAgentMetadata } from "./multimodal-agent-metadata"
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import { setVisionCapableModelsCache, clearVisionCapableModelsCache } from "../../shared/vision-capable-models-cache"
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import * as connectedProvidersCache from "../../shared/connected-providers-cache"
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import * as modelAvailability from "../../shared/model-availability"
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function createPluginInput(agentData: Array<Record<string, unknown>>): PluginInput {
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const client = {} as PluginInput["client"]
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Object.assign(client, {
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app: {
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agents: mock(async () => ({ data: agentData })),
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},
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})
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return {
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client,
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project: {} as PluginInput["project"],
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directory: "/project",
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worktree: "/project",
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serverUrl: new URL("http://localhost"),
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$: {} as PluginInput["$"],
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}
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}
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describe("resolveMultimodalLookerAgentMetadata", () => {
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beforeEach(() => {
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clearVisionCapableModelsCache()
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})
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afterEach(() => {
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clearVisionCapableModelsCache()
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;(modelAvailability.fetchAvailableModels as unknown as { mockRestore?: () => void }).mockRestore?.()
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;(connectedProvidersCache.readConnectedProvidersCache as unknown as { mockRestore?: () => void }).mockRestore?.()
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})
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test("returns configured multimodal-looker model when it already matches a vision-capable override", async () => {
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// given
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setVisionCapableModelsCache(new Map([
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[
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"rundao/public/qwen3.5-397b",
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{ providerID: "rundao", modelID: "public/qwen3.5-397b" },
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],
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]))
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spyOn(modelAvailability, "fetchAvailableModels").mockResolvedValue(
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new Set(["rundao/public/qwen3.5-397b"]),
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)
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spyOn(connectedProvidersCache, "readConnectedProvidersCache").mockReturnValue(["rundao"])
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const ctx = createPluginInput([
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{
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name: "multimodal-looker",
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model: { providerID: "rundao", modelID: "public/qwen3.5-397b" },
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},
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])
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// when
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const result = await resolveMultimodalLookerAgentMetadata(ctx)
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// then
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expect(result).toEqual({
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agentModel: { providerID: "rundao", modelID: "public/qwen3.5-397b" },
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agentVariant: undefined,
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})
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})
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test("prefers connected vision-capable provider models before the hardcoded fallback chain", async () => {
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// given
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setVisionCapableModelsCache(new Map([
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[
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"rundao/public/qwen3.5-397b",
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{ providerID: "rundao", modelID: "public/qwen3.5-397b" },
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],
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]))
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spyOn(modelAvailability, "fetchAvailableModels").mockResolvedValue(
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new Set(["openai/gpt-5.4", "rundao/public/qwen3.5-397b"]),
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)
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spyOn(connectedProvidersCache, "readConnectedProvidersCache").mockReturnValue(["openai", "rundao"])
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const ctx = createPluginInput([
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{
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name: "multimodal-looker",
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model: { providerID: "openai", modelID: "gpt-5.4" },
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variant: "medium",
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},
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])
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// when
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const result = await resolveMultimodalLookerAgentMetadata(ctx)
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// then
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expect(result).toEqual({
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agentModel: { providerID: "rundao", modelID: "public/qwen3.5-397b" },
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agentVariant: undefined,
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})
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})
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test("falls back to the hardcoded multimodal chain when no dynamic vision model exists", async () => {
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// given
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spyOn(modelAvailability, "fetchAvailableModels").mockResolvedValue(
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new Set(["google/gemini-3-flash"]),
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)
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spyOn(connectedProvidersCache, "readConnectedProvidersCache").mockReturnValue(["google"])
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const ctx = createPluginInput([])
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// when
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const result = await resolveMultimodalLookerAgentMetadata(ctx)
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// then
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expect(result).toEqual({
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agentModel: { providerID: "google", modelID: "gemini-3-flash" },
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agentVariant: undefined,
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})
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})
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})
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@@ -1,6 +1,11 @@
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import type { PluginInput } from "@opencode-ai/plugin"
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import type { PluginInput } from "@opencode-ai/plugin"
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import { MULTIMODAL_LOOKER_AGENT } from "./constants"
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import { MULTIMODAL_LOOKER_AGENT } from "./constants"
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import { log } from "../../shared"
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import { fetchAvailableModels } from "../../shared/model-availability"
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import { log } from "../../shared/logger"
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import { readConnectedProvidersCache } from "../../shared/connected-providers-cache"
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import { resolveModelPipeline } from "../../shared/model-resolution-pipeline"
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import { readVisionCapableModelsCache } from "../../shared/vision-capable-models-cache"
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import { buildMultimodalLookerFallbackChain } from "./multimodal-fallback-chain"
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type AgentModel = { providerID: string; modelID: string }
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type AgentModel = { providerID: string; modelID: string }
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|
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@@ -19,6 +24,20 @@ function isObject(value: unknown): value is Record<string, unknown> {
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return typeof value === "object" && value !== null
|
return typeof value === "object" && value !== null
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}
|
}
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|
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function getFullModelKey(model: AgentModel): string {
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return `${model.providerID}/${model.modelID}`
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}
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|
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function parseAgentModel(model: string): AgentModel | undefined {
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|
const [providerID, ...modelIDParts] = model.split("/")
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|
const modelID = modelIDParts.join("/")
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|
if (!providerID || modelID.length === 0) {
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|
return undefined
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|
}
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|
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|
return { providerID, modelID }
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|
}
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|
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function toAgentInfo(value: unknown): AgentInfo | null {
|
function toAgentInfo(value: unknown): AgentInfo | null {
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if (!isObject(value)) return null
|
if (!isObject(value)) return null
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const name = typeof value["name"] === "string" ? value["name"] : undefined
|
const name = typeof value["name"] === "string" ? value["name"] : undefined
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@@ -33,22 +52,83 @@ function toAgentInfo(value: unknown): AgentInfo | null {
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return { name, model, variant }
|
return { name, model, variant }
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}
|
}
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|
|
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|
async function resolveRegisteredAgentMetadata(
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|
ctx: PluginInput,
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|
): Promise<ResolvedAgentMetadata> {
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|
const agentsResult = await ctx.client.app?.agents?.()
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|
const agentsRaw = isObject(agentsResult) ? agentsResult["data"] : undefined
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const agents = Array.isArray(agentsRaw) ? agentsRaw.map(toAgentInfo).filter(Boolean) : []
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|
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|
const matched = agents.find(
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|
(agent) => agent?.name?.toLowerCase() === MULTIMODAL_LOOKER_AGENT.toLowerCase()
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|
)
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|
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|
return {
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|
agentModel: matched?.model,
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|
agentVariant: matched?.variant,
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|
}
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|
}
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|
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|
async function resolveDynamicAgentMetadata(
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||||||
|
ctx: PluginInput,
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|
visionCapableModels = readVisionCapableModelsCache(),
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|
): Promise<ResolvedAgentMetadata> {
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|
const fallbackChain = buildMultimodalLookerFallbackChain(visionCapableModels)
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|
const connectedProviders = readConnectedProvidersCache()
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|
const availableModels = await fetchAvailableModels(ctx.client, {
|
||||||
|
connectedProviders,
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||||||
|
})
|
||||||
|
|
||||||
|
const resolution = resolveModelPipeline({
|
||||||
|
constraints: {
|
||||||
|
availableModels,
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||||||
|
connectedProviders,
|
||||||
|
},
|
||||||
|
policy: {
|
||||||
|
fallbackChain,
|
||||||
|
},
|
||||||
|
})
|
||||||
|
|
||||||
|
const agentModel = resolution ? parseAgentModel(resolution.model) : undefined
|
||||||
|
return {
|
||||||
|
agentModel,
|
||||||
|
agentVariant: resolution?.variant,
|
||||||
|
}
|
||||||
|
}
|
||||||
|
|
||||||
|
function isConfiguredVisionModel(
|
||||||
|
configuredModel: AgentModel | undefined,
|
||||||
|
dynamicModel: AgentModel | undefined,
|
||||||
|
): boolean {
|
||||||
|
if (!configuredModel || !dynamicModel) {
|
||||||
|
return false
|
||||||
|
}
|
||||||
|
|
||||||
|
return getFullModelKey(configuredModel) === getFullModelKey(dynamicModel)
|
||||||
|
}
|
||||||
|
|
||||||
export async function resolveMultimodalLookerAgentMetadata(
|
export async function resolveMultimodalLookerAgentMetadata(
|
||||||
ctx: PluginInput
|
ctx: PluginInput
|
||||||
): Promise<ResolvedAgentMetadata> {
|
): Promise<ResolvedAgentMetadata> {
|
||||||
try {
|
try {
|
||||||
const agentsResult = await ctx.client.app?.agents?.()
|
const registeredMetadata = await resolveRegisteredAgentMetadata(ctx)
|
||||||
const agentsRaw = isObject(agentsResult) ? agentsResult["data"] : undefined
|
const visionCapableModels = readVisionCapableModelsCache()
|
||||||
const agents = Array.isArray(agentsRaw) ? agentsRaw.map(toAgentInfo).filter(Boolean) : []
|
|
||||||
|
|
||||||
const matched = agents.find(
|
if (registeredMetadata.agentModel && visionCapableModels.length === 0) {
|
||||||
(agent) => agent?.name?.toLowerCase() === MULTIMODAL_LOOKER_AGENT.toLowerCase()
|
return registeredMetadata
|
||||||
)
|
|
||||||
|
|
||||||
return {
|
|
||||||
agentModel: matched?.model,
|
|
||||||
agentVariant: matched?.variant,
|
|
||||||
}
|
}
|
||||||
|
|
||||||
|
const dynamicMetadata = await resolveDynamicAgentMetadata(ctx, visionCapableModels)
|
||||||
|
|
||||||
|
if (isConfiguredVisionModel(registeredMetadata.agentModel, dynamicMetadata.agentModel)) {
|
||||||
|
return registeredMetadata
|
||||||
|
}
|
||||||
|
|
||||||
|
if (dynamicMetadata.agentModel) {
|
||||||
|
return dynamicMetadata
|
||||||
|
}
|
||||||
|
|
||||||
|
return registeredMetadata
|
||||||
} catch (error) {
|
} catch (error) {
|
||||||
log("[look_at] Failed to resolve multimodal-looker model info", error)
|
log("[look_at] Failed to resolve multimodal-looker model info", error)
|
||||||
return {}
|
return {}
|
||||||
|
|||||||
@@ -0,0 +1,31 @@
|
|||||||
|
describe("buildMultimodalLookerFallbackChain", () => {
|
||||||
|
it("builds fallback chain from vision-capable models", async () => {
|
||||||
|
// given
|
||||||
|
const { buildMultimodalLookerFallbackChain } = await import("./multimodal-fallback-chain")
|
||||||
|
const visionCapableModels = [
|
||||||
|
{ providerID: "openai", modelID: "gpt-5.4" },
|
||||||
|
{ providerID: "opencode", modelID: "gpt-5.4" },
|
||||||
|
]
|
||||||
|
|
||||||
|
// when
|
||||||
|
const result = buildMultimodalLookerFallbackChain(visionCapableModels)
|
||||||
|
|
||||||
|
// then
|
||||||
|
const gpt54Entries = result.filter((entry) => entry.model === "gpt-5.4")
|
||||||
|
expect(gpt54Entries.length).toBeGreaterThan(0)
|
||||||
|
})
|
||||||
|
|
||||||
|
it("avoids duplicates when adding hardcoded entries", async () => {
|
||||||
|
// given
|
||||||
|
const { buildMultimodalLookerFallbackChain } = await import("./multimodal-fallback-chain")
|
||||||
|
const visionCapableModels = [{ providerID: "openai", modelID: "gpt-5.4" }]
|
||||||
|
|
||||||
|
// when
|
||||||
|
const result = buildMultimodalLookerFallbackChain(visionCapableModels)
|
||||||
|
|
||||||
|
// then
|
||||||
|
expect(result.length).toBeGreaterThan(0)
|
||||||
|
expect(result[0].model).toBe("gpt-5.4")
|
||||||
|
expect(result[0].providers).toContain("openai")
|
||||||
|
})
|
||||||
|
})
|
||||||
@@ -0,0 +1,49 @@
|
|||||||
|
import type { FallbackEntry } from "../../shared/model-requirements"
|
||||||
|
import { AGENT_MODEL_REQUIREMENTS } from "../../shared/model-requirements"
|
||||||
|
import type { VisionCapableModel } from "../../plugin-state"
|
||||||
|
|
||||||
|
const MULTIMODAL_LOOKER_REQUIREMENT = AGENT_MODEL_REQUIREMENTS["multimodal-looker"]
|
||||||
|
|
||||||
|
function getFullModelKey(providerID: string, modelID: string): string {
|
||||||
|
return `${providerID}/${modelID}`
|
||||||
|
}
|
||||||
|
|
||||||
|
export function isHardcodedMultimodalFallbackModel(model: VisionCapableModel): boolean {
|
||||||
|
return MULTIMODAL_LOOKER_REQUIREMENT.fallbackChain.some((entry) =>
|
||||||
|
entry.providers.some((providerID) =>
|
||||||
|
getFullModelKey(providerID, entry.model) === getFullModelKey(model.providerID, model.modelID),
|
||||||
|
),
|
||||||
|
)
|
||||||
|
}
|
||||||
|
|
||||||
|
export function buildMultimodalLookerFallbackChain(
|
||||||
|
visionCapableModels: VisionCapableModel[],
|
||||||
|
): FallbackEntry[] {
|
||||||
|
const seen = new Set<string>()
|
||||||
|
const fallbackChain: FallbackEntry[] = []
|
||||||
|
|
||||||
|
for (const visionCapableModel of visionCapableModels) {
|
||||||
|
const key = getFullModelKey(visionCapableModel.providerID, visionCapableModel.modelID)
|
||||||
|
if (seen.has(key)) continue
|
||||||
|
|
||||||
|
seen.add(key)
|
||||||
|
fallbackChain.push({
|
||||||
|
providers: [visionCapableModel.providerID],
|
||||||
|
model: visionCapableModel.modelID,
|
||||||
|
})
|
||||||
|
}
|
||||||
|
|
||||||
|
for (const entry of MULTIMODAL_LOOKER_REQUIREMENT.fallbackChain) {
|
||||||
|
const providerModelKeys = entry.providers.map((providerID) =>
|
||||||
|
getFullModelKey(providerID, entry.model),
|
||||||
|
)
|
||||||
|
if (providerModelKeys.every((key) => seen.has(key))) {
|
||||||
|
continue
|
||||||
|
}
|
||||||
|
|
||||||
|
providerModelKeys.forEach((key) => seen.add(key))
|
||||||
|
fallbackChain.push(entry)
|
||||||
|
}
|
||||||
|
|
||||||
|
return fallbackChain
|
||||||
|
}
|
||||||
Reference in New Issue
Block a user