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 } ); } }