Files
9router/src/app/api/v1/models/route.js
2026-05-04 11:29:02 +07:00

399 lines
13 KiB
JavaScript

import { PROVIDER_MODELS, PROVIDER_ID_TO_ALIAS } from "@/shared/constants/models";
import {
AI_PROVIDERS,
getProviderAlias,
isAnthropicCompatibleProvider,
isOpenAICompatibleProvider,
} from "@/shared/constants/providers";
import { getProviderConnections, getCombos, getCustomModels, getModelAliases } from "@/lib/localDb";
const parseOpenAIStyleModels = (data) => {
if (Array.isArray(data)) return data;
return data?.data || data?.models || data?.results || [];
};
// Matches provider IDs that are upstream/cross-instance connections (contain a UUID suffix)
const UPSTREAM_CONNECTION_RE = /[-_][0-9a-f]{8,}$/i;
// LLM kind sentinel — combos/models with no explicit kind default to LLM
const LLM_KIND = "llm";
// Map per-model `type` field (in PROVIDER_MODELS) to service kind.
// Models without `type` are treated as LLM.
const MODEL_TYPE_TO_KIND = {
image: "image",
tts: "tts",
embedding: "embedding",
stt: "stt",
imageToText: "imageToText",
};
function modelKind(model) {
if (!model?.type) return LLM_KIND;
return MODEL_TYPE_TO_KIND[model.type] || LLM_KIND;
}
// For dynamic/unknown model IDs (compatible providers, alias map, custom models)
// fall back to provider-level kind matching when per-model type is unavailable.
function inferKindFromUnknownModelId(modelId) {
const lower = String(modelId).toLowerCase();
if (/embed/.test(lower)) return "embedding";
if (/tts|speech|audio|voice/.test(lower)) return "tts";
if (/image|imagen|dall-?e|flux|sdxl|sd-|stable-diffusion/.test(lower)) return "image";
return LLM_KIND;
}
async function fetchCompatibleModelIds(connection) {
if (!connection?.apiKey) return [];
const baseUrl = typeof connection?.providerSpecificData?.baseUrl === "string"
? connection.providerSpecificData.baseUrl.trim().replace(/\/$/, "")
: "";
if (!baseUrl) return [];
let url = `${baseUrl}/models`;
const headers = {
"Content-Type": "application/json",
};
if (isOpenAICompatibleProvider(connection.provider)) {
headers.Authorization = `Bearer ${connection.apiKey}`;
} else if (isAnthropicCompatibleProvider(connection.provider)) {
if (url.endsWith("/messages/models")) {
url = url.slice(0, -9);
} else if (url.endsWith("/messages")) {
url = `${url.slice(0, -9)}/models`;
}
headers["x-api-key"] = connection.apiKey;
headers["anthropic-version"] = "2023-06-01";
headers.Authorization = `Bearer ${connection.apiKey}`;
} else {
return [];
}
try {
const controller = new AbortController();
const timeoutId = setTimeout(() => controller.abort(), 5000);
const response = await fetch(url, {
method: "GET",
headers,
cache: "no-store",
signal: controller.signal,
});
clearTimeout(timeoutId);
if (!response.ok) return [];
const data = await response.json();
const rawModels = parseOpenAIStyleModels(data);
return Array.from(
new Set(
rawModels
.map((model) => model?.id || model?.name || model?.model)
.filter((modelId) => typeof modelId === "string" && modelId.trim() !== "")
)
);
} catch {
return [];
}
}
// Provider matches kindFilter when its serviceKinds intersect the requested kinds.
// LLM is the default kind for providers missing serviceKinds.
function providerMatchesKinds(providerId, kindFilter) {
const provider = AI_PROVIDERS[providerId];
const kinds = Array.isArray(provider?.serviceKinds) && provider.serviceKinds.length > 0
? provider.serviceKinds
: [LLM_KIND];
return kindFilter.some((k) => kinds.includes(k));
}
// Combo matches kindFilter when its `kind` field is in the list.
// Combos with no kind are treated as LLM.
function comboMatchesKinds(combo, kindFilter) {
const kind = combo?.kind || LLM_KIND;
return kindFilter.includes(kind);
}
/**
* Build OpenAI-format models list filtered by service kinds.
* @param {string[]} kindFilter - List of service kinds to include (e.g. ["llm"], ["webSearch","webFetch"]).
*/
export async function buildModelsList(kindFilter) {
let connections = [];
try {
connections = await getProviderConnections();
connections = connections.filter(c => c.isActive !== false);
} catch (e) {
console.log("Could not fetch providers, returning all models");
}
let combos = [];
try {
combos = await getCombos();
} catch (e) {
console.log("Could not fetch combos");
}
let customModels = [];
try {
customModels = await getCustomModels();
} catch (e) {
console.log("Could not fetch custom models");
}
let modelAliases = {};
try {
modelAliases = await getModelAliases();
} catch (e) {
console.log("Could not fetch model aliases");
}
const activeConnectionByProvider = new Map();
for (const conn of connections) {
if (!activeConnectionByProvider.has(conn.provider)) {
activeConnectionByProvider.set(conn.provider, conn);
}
}
const models = [];
const timestamp = Math.floor(Date.now() / 1000);
// Combos first (filtered by kind). Web combos expose `kind` so AI knows search vs fetch.
for (const combo of combos) {
if (!comboMatchesKinds(combo, kindFilter)) continue;
const entry = {
id: combo.name,
object: "model",
created: timestamp,
owned_by: "combo",
};
if (combo.kind === "webSearch" || combo.kind === "webFetch") {
entry.kind = combo.kind;
}
models.push(entry);
}
if (connections.length === 0) {
// DB unavailable -> return static models, filtered by per-model kind
const aliasToProviderId = Object.fromEntries(
Object.entries(PROVIDER_ID_TO_ALIAS).map(([id, alias]) => [alias, id])
);
for (const [alias, providerModels] of Object.entries(PROVIDER_MODELS)) {
const providerId = aliasToProviderId[alias] || alias;
if (!providerMatchesKinds(providerId, kindFilter)) continue;
for (const model of providerModels) {
if (!kindFilter.includes(modelKind(model))) continue;
models.push({
id: `${alias}/${model.id}`,
object: "model",
created: timestamp,
owned_by: alias,
});
}
}
for (const customModel of customModels) {
if (!customModel?.id || (customModel.type && customModel.type !== "llm")) continue;
// Custom models without active connection are LLM-only by current schema
if (!kindFilter.includes(LLM_KIND)) continue;
const providerAlias = customModel.providerAlias;
if (!providerAlias) continue;
const modelId = String(customModel.id).trim();
if (!modelId) continue;
models.push({
id: `${providerAlias}/${modelId}`,
object: "model",
created: timestamp,
owned_by: providerAlias,
});
}
} else {
for (const [providerId, conn] of activeConnectionByProvider.entries()) {
if (!providerMatchesKinds(providerId, kindFilter)) continue;
const staticAlias = PROVIDER_ID_TO_ALIAS[providerId] || providerId;
const outputAlias = (
conn?.providerSpecificData?.prefix
|| getProviderAlias(providerId)
|| staticAlias
).trim();
const providerModels = PROVIDER_MODELS[staticAlias] || [];
const enabledModels = conn?.providerSpecificData?.enabledModels;
const hasExplicitEnabledModels =
Array.isArray(enabledModels) && enabledModels.length > 0;
const isCompatibleProvider =
isOpenAICompatibleProvider(providerId) || isAnthropicCompatibleProvider(providerId);
// Build kind lookup for static models so we can filter even when only IDs are exposed
const staticModelKindById = new Map(
providerModels.map((m) => [m.id, modelKind(m)])
);
let rawModelIds = hasExplicitEnabledModels
? Array.from(
new Set(
enabledModels.filter(
(modelId) => typeof modelId === "string" && modelId.trim() !== "",
),
),
)
: providerModels.map((model) => model.id);
if (isCompatibleProvider && rawModelIds.length === 0 && !UPSTREAM_CONNECTION_RE.test(providerId)) {
rawModelIds = await fetchCompatibleModelIds(conn);
}
const modelIds = rawModelIds
.map((modelId) => {
if (modelId.startsWith(`${outputAlias}/`)) {
return modelId.slice(outputAlias.length + 1);
}
if (modelId.startsWith(`${staticAlias}/`)) {
return modelId.slice(staticAlias.length + 1);
}
if (modelId.startsWith(`${providerId}/`)) {
return modelId.slice(providerId.length + 1);
}
return modelId;
})
.filter((modelId) => typeof modelId === "string" && modelId.trim() !== "");
const customModelIds = customModels
.filter((m) => {
if (!m?.id || (m.type && m.type !== "llm")) return false;
const alias = m.providerAlias;
return alias === staticAlias || alias === outputAlias || alias === providerId;
})
.map((m) => String(m.id).trim())
.filter((modelId) => modelId !== "");
const aliasModelIds = Object.values(modelAliases || {})
.filter((fullModel) => {
if (typeof fullModel !== "string" || !fullModel.includes("/")) return false;
return (
fullModel.startsWith(`${outputAlias}/`) ||
fullModel.startsWith(`${staticAlias}/`) ||
fullModel.startsWith(`${providerId}/`)
);
})
.map((fullModel) => {
if (fullModel.startsWith(`${outputAlias}/`)) {
return fullModel.slice(outputAlias.length + 1);
}
if (fullModel.startsWith(`${staticAlias}/`)) {
return fullModel.slice(staticAlias.length + 1);
}
if (fullModel.startsWith(`${providerId}/`)) {
return fullModel.slice(providerId.length + 1);
}
return fullModel;
})
.filter((modelId) => typeof modelId === "string" && modelId.trim() !== "");
const mergedModelIds = Array.from(new Set([...modelIds, ...customModelIds, ...aliasModelIds]));
for (const modelId of mergedModelIds) {
// Resolve kind: prefer static metadata, otherwise infer from ID heuristics
const kind = staticModelKindById.get(modelId) || inferKindFromUnknownModelId(modelId);
if (!kindFilter.includes(kind)) continue;
models.push({
id: `${outputAlias}/${modelId}`,
object: "model",
created: timestamp,
owned_by: outputAlias,
});
}
// Merge sub-config models (TTS / embedding) that live on AI_PROVIDERS, not PROVIDER_MODELS
const providerInfo = AI_PROVIDERS[providerId];
const subConfigModels = [];
if (kindFilter.includes("tts") && Array.isArray(providerInfo?.ttsConfig?.models)) {
for (const m of providerInfo.ttsConfig.models) {
if (m?.id) subConfigModels.push(m.id);
}
}
if (kindFilter.includes("embedding") && Array.isArray(providerInfo?.embeddingConfig?.models)) {
for (const m of providerInfo.embeddingConfig.models) {
if (m?.id) subConfigModels.push(m.id);
}
}
for (const subId of subConfigModels) {
models.push({
id: `${outputAlias}/${subId}`,
object: "model",
created: timestamp,
owned_by: outputAlias,
});
}
// Web search/fetch — provider IS the model, expose as {alias}/search and/or {alias}/fetch with explicit kind
if (kindFilter.includes("webSearch") && providerInfo?.searchConfig) {
models.push({
id: `${outputAlias}/search`,
object: "model",
kind: "webSearch",
created: timestamp,
owned_by: outputAlias,
});
}
if (kindFilter.includes("webFetch") && providerInfo?.fetchConfig) {
models.push({
id: `${outputAlias}/fetch`,
object: "model",
kind: "webFetch",
created: timestamp,
owned_by: outputAlias,
});
}
}
}
const dedupedModels = [];
const seenModelIds = new Set();
for (const model of models) {
if (!model?.id || seenModelIds.has(model.id)) continue;
seenModelIds.add(model.id);
dedupedModels.push(model);
}
return dedupedModels;
}
/**
* Handle CORS preflight
*/
export async function OPTIONS() {
return new Response(null, {
headers: {
"Access-Control-Allow-Origin": "*",
"Access-Control-Allow-Methods": "GET, OPTIONS",
"Access-Control-Allow-Headers": "*",
},
});
}
/**
* GET /v1/models - OpenAI compatible models list (LLM/chat models only by default).
* For other capabilities use /v1/models/{kind} (image, tts, stt, embedding, image-to-text, web).
*/
export async function GET() {
try {
const data = await buildModelsList([LLM_KIND]);
return Response.json({ object: "list", data }, {
headers: { "Access-Control-Allow-Origin": "*" },
});
} catch (error) {
console.log("Error fetching models:", error);
return Response.json(
{ error: { message: error.message, type: "server_error" } },
{ status: 500 }
);
}
}