Merge pull request #2371 from code-yeongyu/fix/issue-2323

fix: respect multimodal provider vision capabilities
This commit is contained in:
YeonGyu-Kim
2026-03-11 20:22:35 +09:00
committed by GitHub
8 changed files with 430 additions and 13 deletions
@@ -0,0 +1,84 @@
/// <reference types="bun-types" />
import { describe, expect, test } from "bun:test"
import { applyProviderConfig } from "./provider-config-handler"
import { createModelCacheState } from "../plugin-state"
import { clearVisionCapableModelsCache, readVisionCapableModelsCache } from "../shared/vision-capable-models-cache"
describe("applyProviderConfig", () => {
test("caches vision-capable models from modalities and capabilities", () => {
// given
const modelCacheState = createModelCacheState()
const visionCapableModelsCache = modelCacheState.visionCapableModelsCache
if (!visionCapableModelsCache) {
throw new Error("visionCapableModelsCache should be initialized")
}
const config = {
provider: {
rundao: {
models: {
"public/qwen3.5-397b": {
modalities: {
input: ["text", "image"],
},
},
"public/text-only": {
modalities: {
input: ["text"],
},
},
},
},
google: {
models: {
"gemini-3-flash": {
capabilities: {
input: {
image: true,
},
},
},
},
},
},
} satisfies Record<string, unknown>
// when
applyProviderConfig({ config, modelCacheState })
// then
expect(Array.from(visionCapableModelsCache.keys())).toEqual([
"rundao/public/qwen3.5-397b",
"google/gemini-3-flash",
])
expect(readVisionCapableModelsCache()).toEqual([
{ providerID: "rundao", modelID: "public/qwen3.5-397b" },
{ providerID: "google", modelID: "gemini-3-flash" },
])
})
test("clears stale vision-capable models when provider config changes", () => {
// given
const modelCacheState = createModelCacheState()
const visionCapableModelsCache = modelCacheState.visionCapableModelsCache
if (!visionCapableModelsCache) {
throw new Error("visionCapableModelsCache should be initialized")
}
visionCapableModelsCache.set("stale/old-model", {
providerID: "stale",
modelID: "old-model",
})
// when
applyProviderConfig({
config: { provider: {} },
modelCacheState,
})
// then
expect(visionCapableModelsCache.size).toBe(0)
expect(readVisionCapableModelsCache()).toEqual([])
})
})
clearVisionCapableModelsCache()
+36 -2
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@@ -1,10 +1,31 @@
import type { ModelCacheState } from "../plugin-state";
import type { ModelCacheState, VisionCapableModel } from "../plugin-state";
import { setVisionCapableModelsCache } from "../shared/vision-capable-models-cache"
type ProviderConfig = {
options?: { headers?: Record<string, string> };
models?: Record<string, { limit?: { context?: number } }>;
models?: Record<string, ProviderModelConfig>;
};
type ProviderModelConfig = {
limit?: { context?: number };
modalities?: {
input?: string[];
};
capabilities?: {
input?: {
image?: boolean;
};
};
}
function supportsImageInput(modelConfig: ProviderModelConfig | undefined): boolean {
if (modelConfig?.modalities?.input?.includes("image")) {
return true
}
return modelConfig?.capabilities?.input?.image === true
}
export function applyProviderConfig(params: {
config: Record<string, unknown>;
modelCacheState: ModelCacheState;
@@ -17,6 +38,12 @@ export function applyProviderConfig(params: {
params.modelCacheState.anthropicContext1MEnabled =
anthropicBeta?.includes("context-1m") ?? false;
const visionCapableModelsCache = params.modelCacheState.visionCapableModelsCache
?? new Map<string, VisionCapableModel>()
params.modelCacheState.visionCapableModelsCache = visionCapableModelsCache
visionCapableModelsCache.clear()
setVisionCapableModelsCache(visionCapableModelsCache)
if (!providers) return;
for (const [providerID, providerConfig] of Object.entries(providers)) {
@@ -24,6 +51,13 @@ export function applyProviderConfig(params: {
if (!models) continue;
for (const [modelID, modelConfig] of Object.entries(models)) {
if (supportsImageInput(modelConfig)) {
visionCapableModelsCache.set(
`${providerID}/${modelID}`,
{ providerID, modelID },
)
}
const contextLimit = modelConfig?.limit?.context;
if (!contextLimit) continue;
+7
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@@ -1,11 +1,18 @@
export type VisionCapableModel = {
providerID: string
modelID: string
}
export interface ModelCacheState {
modelContextLimitsCache: Map<string, number>;
visionCapableModelsCache?: Map<string, VisionCapableModel>;
anthropicContext1MEnabled: boolean;
}
export function createModelCacheState(): ModelCacheState {
return {
modelContextLimitsCache: new Map<string, number>(),
visionCapableModelsCache: new Map<string, VisionCapableModel>(),
anthropicContext1MEnabled: false,
};
}
+17
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@@ -0,0 +1,17 @@
import type { VisionCapableModel } from "../plugin-state"
let visionCapableModelsCache = new Map<string, VisionCapableModel>()
export function setVisionCapableModelsCache(
cache: Map<string, VisionCapableModel>,
): void {
visionCapableModelsCache = cache
}
export function readVisionCapableModelsCache(): VisionCapableModel[] {
return Array.from(visionCapableModelsCache.values())
}
export function clearVisionCapableModelsCache(): void {
visionCapableModelsCache = new Map<string, VisionCapableModel>()
}
@@ -0,0 +1,115 @@
/// <reference types="bun-types" />
import { afterEach, beforeEach, describe, expect, mock, spyOn, test } from "bun:test"
import type { PluginInput } from "@opencode-ai/plugin"
import { resolveMultimodalLookerAgentMetadata } from "./multimodal-agent-metadata"
import { setVisionCapableModelsCache, clearVisionCapableModelsCache } from "../../shared/vision-capable-models-cache"
import * as connectedProvidersCache from "../../shared/connected-providers-cache"
import * as modelAvailability from "../../shared/model-availability"
function createPluginInput(agentData: Array<Record<string, unknown>>): PluginInput {
const client = {} as PluginInput["client"]
Object.assign(client, {
app: {
agents: mock(async () => ({ data: agentData })),
},
})
return {
client,
project: {} as PluginInput["project"],
directory: "/project",
worktree: "/project",
serverUrl: new URL("http://localhost"),
$: {} as PluginInput["$"],
}
}
describe("resolveMultimodalLookerAgentMetadata", () => {
beforeEach(() => {
clearVisionCapableModelsCache()
})
afterEach(() => {
clearVisionCapableModelsCache()
;(modelAvailability.fetchAvailableModels as unknown as { mockRestore?: () => void }).mockRestore?.()
;(connectedProvidersCache.readConnectedProvidersCache as unknown as { mockRestore?: () => void }).mockRestore?.()
})
test("returns configured multimodal-looker model when it already matches a vision-capable override", async () => {
// given
setVisionCapableModelsCache(new Map([
[
"rundao/public/qwen3.5-397b",
{ providerID: "rundao", modelID: "public/qwen3.5-397b" },
],
]))
spyOn(modelAvailability, "fetchAvailableModels").mockResolvedValue(
new Set(["rundao/public/qwen3.5-397b"]),
)
spyOn(connectedProvidersCache, "readConnectedProvidersCache").mockReturnValue(["rundao"])
const ctx = createPluginInput([
{
name: "multimodal-looker",
model: { providerID: "rundao", modelID: "public/qwen3.5-397b" },
},
])
// when
const result = await resolveMultimodalLookerAgentMetadata(ctx)
// then
expect(result).toEqual({
agentModel: { providerID: "rundao", modelID: "public/qwen3.5-397b" },
agentVariant: undefined,
})
})
test("prefers connected vision-capable provider models before the hardcoded fallback chain", async () => {
// given
setVisionCapableModelsCache(new Map([
[
"rundao/public/qwen3.5-397b",
{ providerID: "rundao", modelID: "public/qwen3.5-397b" },
],
]))
spyOn(modelAvailability, "fetchAvailableModels").mockResolvedValue(
new Set(["openai/gpt-5.4", "rundao/public/qwen3.5-397b"]),
)
spyOn(connectedProvidersCache, "readConnectedProvidersCache").mockReturnValue(["openai", "rundao"])
const ctx = createPluginInput([
{
name: "multimodal-looker",
model: { providerID: "openai", modelID: "gpt-5.4" },
variant: "medium",
},
])
// when
const result = await resolveMultimodalLookerAgentMetadata(ctx)
// then
expect(result).toEqual({
agentModel: { providerID: "rundao", modelID: "public/qwen3.5-397b" },
agentVariant: undefined,
})
})
test("falls back to the hardcoded multimodal chain when no dynamic vision model exists", async () => {
// given
spyOn(modelAvailability, "fetchAvailableModels").mockResolvedValue(
new Set(["google/gemini-3-flash"]),
)
spyOn(connectedProvidersCache, "readConnectedProvidersCache").mockReturnValue(["google"])
const ctx = createPluginInput([])
// when
const result = await resolveMultimodalLookerAgentMetadata(ctx)
// then
expect(result).toEqual({
agentModel: { providerID: "google", modelID: "gemini-3-flash" },
agentVariant: undefined,
})
})
})
+91 -11
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@@ -1,6 +1,11 @@
import type { PluginInput } from "@opencode-ai/plugin"
import { MULTIMODAL_LOOKER_AGENT } from "./constants"
import { log } from "../../shared"
import { fetchAvailableModels } from "../../shared/model-availability"
import { log } from "../../shared/logger"
import { readConnectedProvidersCache } from "../../shared/connected-providers-cache"
import { resolveModelPipeline } from "../../shared/model-resolution-pipeline"
import { readVisionCapableModelsCache } from "../../shared/vision-capable-models-cache"
import { buildMultimodalLookerFallbackChain } from "./multimodal-fallback-chain"
type AgentModel = { providerID: string; modelID: string }
@@ -19,6 +24,20 @@ function isObject(value: unknown): value is Record<string, unknown> {
return typeof value === "object" && value !== null
}
function getFullModelKey(model: AgentModel): string {
return `${model.providerID}/${model.modelID}`
}
function parseAgentModel(model: string): AgentModel | undefined {
const [providerID, ...modelIDParts] = model.split("/")
const modelID = modelIDParts.join("/")
if (!providerID || modelID.length === 0) {
return undefined
}
return { providerID, modelID }
}
function toAgentInfo(value: unknown): AgentInfo | null {
if (!isObject(value)) return null
const name = typeof value["name"] === "string" ? value["name"] : undefined
@@ -33,22 +52,83 @@ function toAgentInfo(value: unknown): AgentInfo | null {
return { name, model, variant }
}
async function resolveRegisteredAgentMetadata(
ctx: PluginInput,
): Promise<ResolvedAgentMetadata> {
const agentsResult = await ctx.client.app?.agents?.()
const agentsRaw = isObject(agentsResult) ? agentsResult["data"] : undefined
const agents = Array.isArray(agentsRaw) ? agentsRaw.map(toAgentInfo).filter(Boolean) : []
const matched = agents.find(
(agent) => agent?.name?.toLowerCase() === MULTIMODAL_LOOKER_AGENT.toLowerCase()
)
return {
agentModel: matched?.model,
agentVariant: matched?.variant,
}
}
async function resolveDynamicAgentMetadata(
ctx: PluginInput,
visionCapableModels = readVisionCapableModelsCache(),
): Promise<ResolvedAgentMetadata> {
const fallbackChain = buildMultimodalLookerFallbackChain(visionCapableModels)
const connectedProviders = readConnectedProvidersCache()
const availableModels = await fetchAvailableModels(ctx.client, {
connectedProviders,
})
const resolution = resolveModelPipeline({
constraints: {
availableModels,
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(
ctx: PluginInput
): Promise<ResolvedAgentMetadata> {
try {
const agentsResult = await ctx.client.app?.agents?.()
const agentsRaw = isObject(agentsResult) ? agentsResult["data"] : undefined
const agents = Array.isArray(agentsRaw) ? agentsRaw.map(toAgentInfo).filter(Boolean) : []
const registeredMetadata = await resolveRegisteredAgentMetadata(ctx)
const visionCapableModels = readVisionCapableModelsCache()
const matched = agents.find(
(agent) => agent?.name?.toLowerCase() === MULTIMODAL_LOOKER_AGENT.toLowerCase()
)
return {
agentModel: matched?.model,
agentVariant: matched?.variant,
if (registeredMetadata.agentModel && visionCapableModels.length === 0) {
return registeredMetadata
}
const dynamicMetadata = await resolveDynamicAgentMetadata(ctx, visionCapableModels)
if (isConfiguredVisionModel(registeredMetadata.agentModel, dynamicMetadata.agentModel)) {
return registeredMetadata
}
if (dynamicMetadata.agentModel) {
return dynamicMetadata
}
return registeredMetadata
} catch (error) {
log("[look_at] Failed to resolve multimodal-looker model info", error)
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
}