mirror of
https://github.com/RooVetGit/Roo-Code.git
synced 2026-08-28 05:27:24 +00:00
feat: add OpenRouter embedding provider support (#8973)
* feat: add OpenRouter embedding provider support Implement comprehensive OpenRouter embedding provider support for codebase indexing with the following features: - New OpenRouterEmbedder class with full API compatibility - Support for OpenRouter's OpenAI-compatible embedding endpoint - Rate limiting and retry logic with exponential backoff - Base64 embedding handling to bypass OpenAI package limitations - Global rate limit state management across embedder instances - Configuration updates for API key storage and provider selection - UI integration for OpenRouter provider settings - Comprehensive test suite with mocking - Model dimension support for OpenRouter's embedding models This adds OpenRouter as the 7th supported embedding provider alongside OpenAI, Ollama, OpenAI-compatible, Gemini, Mistral, and Vercel AI Gateway. * Add translation key * Fix mutex double release bug * Add translations * Add more translations * Fix failing tests * code-index(openrouter): fix HTTP-Referer header to RooCodeInc/Roo-Code; i18n: add and wire OpenRouter Code Index strings; test: assert default headers in embedder --------- Co-authored-by: daniel-lxs <ricciodaniel98@gmail.com>
This commit is contained in:
David Markey
GitHub
parent
d0e519de3f
commit
34f45f1b28
49 changed files with 965 additions and 22 deletions
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@ -22,7 +22,7 @@ export const codebaseIndexConfigSchema = z.object({
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codebaseIndexEnabled: z.boolean().optional(),
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codebaseIndexQdrantUrl: z.string().optional(),
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codebaseIndexEmbedderProvider: z
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.enum(["openai", "ollama", "openai-compatible", "gemini", "mistral", "vercel-ai-gateway"])
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.enum(["openai", "ollama", "openai-compatible", "gemini", "mistral", "vercel-ai-gateway", "openrouter"])
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.optional(),
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codebaseIndexEmbedderBaseUrl: z.string().optional(),
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codebaseIndexEmbedderModelId: z.string().optional(),
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@ -51,6 +51,7 @@ export const codebaseIndexModelsSchema = z.object({
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gemini: z.record(z.string(), z.object({ dimension: z.number() })).optional(),
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mistral: z.record(z.string(), z.object({ dimension: z.number() })).optional(),
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"vercel-ai-gateway": z.record(z.string(), z.object({ dimension: z.number() })).optional(),
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openrouter: z.record(z.string(), z.object({ dimension: z.number() })).optional(),
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})
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export type CodebaseIndexModels = z.infer<typeof codebaseIndexModelsSchema>
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@ -68,6 +69,7 @@ export const codebaseIndexProviderSchema = z.object({
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codebaseIndexGeminiApiKey: z.string().optional(),
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codebaseIndexMistralApiKey: z.string().optional(),
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codebaseIndexVercelAiGatewayApiKey: z.string().optional(),
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codebaseIndexOpenRouterApiKey: z.string().optional(),
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})
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export type CodebaseIndexProvider = z.infer<typeof codebaseIndexProviderSchema>
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@ -232,6 +232,7 @@ export const SECRET_STATE_KEYS = [
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"codebaseIndexGeminiApiKey",
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"codebaseIndexMistralApiKey",
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"codebaseIndexVercelAiGatewayApiKey",
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"codebaseIndexOpenRouterApiKey",
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"huggingFaceApiKey",
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"sambaNovaApiKey",
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"zaiApiKey",
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@ -2556,6 +2556,12 @@ export const webviewMessageHandler = async (
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settings.codebaseIndexVercelAiGatewayApiKey,
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)
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}
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if (settings.codebaseIndexOpenRouterApiKey !== undefined) {
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await provider.contextProxy.storeSecret(
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"codebaseIndexOpenRouterApiKey",
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settings.codebaseIndexOpenRouterApiKey,
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)
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}
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// Send success response first - settings are saved regardless of validation
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await provider.postMessageToWebview({
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@ -2693,6 +2699,7 @@ export const webviewMessageHandler = async (
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const hasVercelAiGatewayApiKey = !!(await provider.context.secrets.get(
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"codebaseIndexVercelAiGatewayApiKey",
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))
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const hasOpenRouterApiKey = !!(await provider.context.secrets.get("codebaseIndexOpenRouterApiKey"))
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provider.postMessageToWebview({
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type: "codeIndexSecretStatus",
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@ -2703,6 +2710,7 @@ export const webviewMessageHandler = async (
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hasGeminiApiKey,
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hasMistralApiKey,
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hasVercelAiGatewayApiKey,
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hasOpenRouterApiKey,
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},
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})
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break
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1
src/i18n/locales/ca/embeddings.json
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src/i18n/locales/ca/embeddings.json
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@ -47,6 +47,7 @@
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"openAiCompatibleConfigMissing": "Falta la configuració compatible amb OpenAI per crear l'embedder",
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"geminiConfigMissing": "Falta la configuració de Gemini per crear l'embedder",
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"mistralConfigMissing": "Falta la configuració de Mistral per crear l'embedder",
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"openRouterConfigMissing": "Falta la configuració d'OpenRouter per crear l'embedder",
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"vercelAiGatewayConfigMissing": "Falta la configuració de Vercel AI Gateway per crear l'embedder",
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"invalidEmbedderType": "Tipus d'embedder configurat no vàlid: {{embedderProvider}}",
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"vectorDimensionNotDeterminedOpenAiCompatible": "No s'ha pogut determinar la dimensió del vector per al model '{{modelId}}' amb el proveïdor '{{provider}}'. Assegura't que la 'Dimensió d'incrustació' estigui configurada correctament als paràmetres del proveïdor compatible amb OpenAI.",
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src/i18n/locales/de/embeddings.json
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src/i18n/locales/de/embeddings.json
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@ -47,6 +47,7 @@
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"openAiCompatibleConfigMissing": "OpenAI-kompatible Konfiguration fehlt für die Erstellung des Embedders",
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"geminiConfigMissing": "Gemini-Konfiguration fehlt für die Erstellung des Embedders",
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"mistralConfigMissing": "Mistral-Konfiguration fehlt für die Erstellung des Embedders",
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"openRouterConfigMissing": "OpenRouter-Konfiguration fehlt für die Erstellung des Embedders",
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"vercelAiGatewayConfigMissing": "Vercel AI Gateway-Konfiguration fehlt für die Erstellung des Embedders",
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"invalidEmbedderType": "Ungültiger Embedder-Typ konfiguriert: {{embedderProvider}}",
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"vectorDimensionNotDeterminedOpenAiCompatible": "Konnte die Vektordimension für Modell '{{modelId}}' mit Anbieter '{{provider}}' nicht bestimmen. Stelle sicher, dass die 'Embedding-Dimension' in den OpenAI-kompatiblen Anbietereinstellungen korrekt eingestellt ist.",
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@ -47,6 +47,7 @@
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"openAiCompatibleConfigMissing": "OpenAI Compatible configuration missing for embedder creation",
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"geminiConfigMissing": "Gemini configuration missing for embedder creation",
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"mistralConfigMissing": "Mistral configuration missing for embedder creation",
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"openRouterConfigMissing": "OpenRouter configuration missing for embedder creation",
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"vercelAiGatewayConfigMissing": "Vercel AI Gateway configuration missing for embedder creation",
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"invalidEmbedderType": "Invalid embedder type configured: {{embedderProvider}}",
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"vectorDimensionNotDeterminedOpenAiCompatible": "Could not determine vector dimension for model '{{modelId}}' with provider '{{provider}}'. Please ensure the 'Embedding Dimension' is correctly set in the OpenAI-Compatible provider settings.",
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1
src/i18n/locales/es/embeddings.json
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src/i18n/locales/es/embeddings.json
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@ -47,6 +47,7 @@
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"openAiCompatibleConfigMissing": "Falta la configuración compatible con OpenAI para crear el incrustador",
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"geminiConfigMissing": "Falta la configuración de Gemini para crear el incrustador",
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"mistralConfigMissing": "Falta la configuración de Mistral para la creación del incrustador",
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"openRouterConfigMissing": "Falta la configuración de OpenRouter para la creación del incrustador",
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"vercelAiGatewayConfigMissing": "Falta la configuración de Vercel AI Gateway para la creación del incrustador",
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"invalidEmbedderType": "Tipo de incrustador configurado inválido: {{embedderProvider}}",
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"vectorDimensionNotDeterminedOpenAiCompatible": "No se pudo determinar la dimensión del vector para el modelo '{{modelId}}' con el proveedor '{{provider}}'. Asegúrate de que la 'Dimensión de incrustación' esté configurada correctamente en los ajustes del proveedor compatible con OpenAI.",
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1
src/i18n/locales/fr/embeddings.json
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src/i18n/locales/fr/embeddings.json
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@ -47,6 +47,7 @@
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"openAiCompatibleConfigMissing": "Configuration compatible OpenAI manquante pour la création de l'embedder",
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"geminiConfigMissing": "Configuration Gemini manquante pour la création de l'embedder",
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"mistralConfigMissing": "Configuration Mistral manquante pour la création de l'embedder",
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"openRouterConfigMissing": "Configuration OpenRouter manquante pour la création de l'embedder",
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"vercelAiGatewayConfigMissing": "Configuration Vercel AI Gateway manquante pour la création de l'embedder",
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"invalidEmbedderType": "Type d'embedder configuré invalide : {{embedderProvider}}",
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"vectorDimensionNotDeterminedOpenAiCompatible": "Impossible de déterminer la dimension du vecteur pour le modèle '{{modelId}}' avec le fournisseur '{{provider}}'. Assure-toi que la 'Dimension d'embedding' est correctement définie dans les paramètres du fournisseur compatible OpenAI.",
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src/i18n/locales/hi/embeddings.json
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@ -47,6 +47,7 @@
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"openAiCompatibleConfigMissing": "एम्बेडर बनाने के लिए OpenAI संगत कॉन्फ़िगरेशन गायब है",
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"geminiConfigMissing": "एम्बेडर बनाने के लिए Gemini कॉन्फ़िगरेशन गायब है",
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"mistralConfigMissing": "एम्बेडर निर्माण के लिए मिस्ट्रल कॉन्फ़िगरेशन गायब है",
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"openRouterConfigMissing": "एम्बेडर निर्माण के लिए OpenRouter कॉन्फ़िगरेशन गायब है",
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"vercelAiGatewayConfigMissing": "एम्बेडर निर्माण के लिए Vercel AI Gateway कॉन्फ़िगरेशन गायब है",
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"invalidEmbedderType": "अमान्य एम्बेडर प्रकार कॉन्फ़िगर किया गया: {{embedderProvider}}",
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"vectorDimensionNotDeterminedOpenAiCompatible": "प्रदाता '{{provider}}' के साथ मॉडल '{{modelId}}' के लिए वेक्टर आयाम निर्धारित नहीं कर सका। कृपया सुनिश्चित करें कि OpenAI-संगत प्रदाता सेटिंग्स में 'एम्बेडिंग आयाम' सही तरीके से सेट है।",
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src/i18n/locales/id/embeddings.json
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1
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@ -47,6 +47,7 @@
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"openAiCompatibleConfigMissing": "Konfigurasi yang kompatibel dengan OpenAI tidak ada untuk membuat embedder",
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"geminiConfigMissing": "Konfigurasi Gemini tidak ada untuk membuat embedder",
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"mistralConfigMissing": "Konfigurasi Mistral hilang untuk pembuatan embedder",
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"openRouterConfigMissing": "Konfigurasi OpenRouter hilang untuk pembuatan embedder",
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"vercelAiGatewayConfigMissing": "Konfigurasi Vercel AI Gateway hilang untuk pembuatan embedder",
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"invalidEmbedderType": "Tipe embedder yang dikonfigurasi tidak valid: {{embedderProvider}}",
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"vectorDimensionNotDeterminedOpenAiCompatible": "Tidak dapat menentukan dimensi vektor untuk model '{{modelId}}' dengan penyedia '{{provider}}'. Pastikan 'Dimensi Embedding' diatur dengan benar di pengaturan penyedia yang kompatibel dengan OpenAI.",
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src/i18n/locales/it/embeddings.json
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src/i18n/locales/it/embeddings.json
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@ -47,6 +47,7 @@
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"openAiCompatibleConfigMissing": "Configurazione compatibile con OpenAI mancante per la creazione dell'embedder",
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"geminiConfigMissing": "Configurazione Gemini mancante per la creazione dell'embedder",
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"mistralConfigMissing": "Configurazione di Mistral mancante per la creazione dell'embedder",
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"openRouterConfigMissing": "Configurazione di OpenRouter mancante per la creazione dell'embedder",
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"vercelAiGatewayConfigMissing": "Configurazione di Vercel AI Gateway mancante per la creazione dell'embedder",
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"invalidEmbedderType": "Tipo di embedder configurato non valido: {{embedderProvider}}",
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"vectorDimensionNotDeterminedOpenAiCompatible": "Impossibile determinare la dimensione del vettore per il modello '{{modelId}}' con il provider '{{provider}}'. Assicurati che la 'Dimensione di embedding' sia impostata correttamente nelle impostazioni del provider compatibile con OpenAI.",
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src/i18n/locales/ja/embeddings.json
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@ -47,6 +47,7 @@
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"openAiCompatibleConfigMissing": "エンベッダー作成のためのOpenAI互換設定がありません",
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"geminiConfigMissing": "エンベッダー作成のためのGemini設定がありません",
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"mistralConfigMissing": "エンベッダー作成のためのMistral設定がありません",
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"openRouterConfigMissing": "エンベッダー作成のためのOpenRouter設定がありません",
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"vercelAiGatewayConfigMissing": "エンベッダー作成のためのVercel AI Gateway設定がありません",
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"invalidEmbedderType": "無効なエンベッダータイプが設定されています: {{embedderProvider}}",
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"vectorDimensionNotDeterminedOpenAiCompatible": "プロバイダー '{{provider}}' のモデル '{{modelId}}' の埋め込み次元を決定できませんでした。OpenAI互換プロバイダー設定で「埋め込み次元」が正しく設定されていることを確認してください。",
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src/i18n/locales/ko/embeddings.json
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@ -47,6 +47,7 @@
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"openAiCompatibleConfigMissing": "임베더 생성을 위한 OpenAI 호환 구성이 누락되었습니다",
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"geminiConfigMissing": "임베더 생성을 위한 Gemini 구성이 누락되었습니다",
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"mistralConfigMissing": "임베더 생성을 위한 Mistral 구성이 없습니다",
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"openRouterConfigMissing": "임베더 생성을 위한 OpenRouter 구성이 없습니다",
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"vercelAiGatewayConfigMissing": "임베더 생성을 위한 Vercel AI Gateway 구성이 없습니다",
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"invalidEmbedderType": "잘못된 임베더 유형이 구성되었습니다: {{embedderProvider}}",
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"vectorDimensionNotDeterminedOpenAiCompatible": "프로바이더 '{{provider}}'의 모델 '{{modelId}}'에 대한 벡터 차원을 결정할 수 없습니다. OpenAI 호환 프로바이더 설정에서 '임베딩 차원'이 올바르게 설정되어 있는지 확인하세요.",
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src/i18n/locales/nl/embeddings.json
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@ -47,6 +47,7 @@
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"openAiCompatibleConfigMissing": "OpenAI-compatibele configuratie ontbreekt voor het maken van embedder",
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"geminiConfigMissing": "Gemini-configuratie ontbreekt voor het maken van embedder",
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"mistralConfigMissing": "Mistral-configuratie ontbreekt voor het maken van de embedder",
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"openRouterConfigMissing": "OpenRouter-configuratie ontbreekt voor het maken van de embedder",
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"vercelAiGatewayConfigMissing": "Vercel AI Gateway-configuratie ontbreekt voor het maken van de embedder",
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"invalidEmbedderType": "Ongeldig embedder-type geconfigureerd: {{embedderProvider}}",
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"vectorDimensionNotDeterminedOpenAiCompatible": "Kan de vectordimensie voor model '{{modelId}}' met provider '{{provider}}' niet bepalen. Zorg ervoor dat de 'Embedding Dimensie' correct is ingesteld in de OpenAI-compatibele provider-instellingen.",
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src/i18n/locales/pl/embeddings.json
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"openAiCompatibleConfigMissing": "Brak konfiguracji kompatybilnej z OpenAI do utworzenia embeddera",
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"geminiConfigMissing": "Brak konfiguracji Gemini do utworzenia embeddera",
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"mistralConfigMissing": "Brak konfiguracji Mistral do utworzenia embeddera",
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"openRouterConfigMissing": "Brak konfiguracji OpenRouter do utworzenia embeddera",
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"vercelAiGatewayConfigMissing": "Brak konfiguracji Vercel AI Gateway do utworzenia embeddera",
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"invalidEmbedderType": "Skonfigurowano nieprawidłowy typ embeddera: {{embedderProvider}}",
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"vectorDimensionNotDeterminedOpenAiCompatible": "Nie można określić wymiaru wektora dla modelu '{{modelId}}' z dostawcą '{{provider}}'. Upewnij się, że 'Wymiar osadzania' jest poprawnie ustawiony w ustawieniach dostawcy kompatybilnego z OpenAI.",
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src/i18n/locales/pt-BR/embeddings.json
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1
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"openAiCompatibleConfigMissing": "Configuração compatível com OpenAI ausente para criação do embedder",
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"geminiConfigMissing": "Configuração do Gemini ausente para criação do embedder",
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"mistralConfigMissing": "Configuração do Mistral ausente para a criação do embedder",
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"openRouterConfigMissing": "Configuração do OpenRouter ausente para a criação do embedder",
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"vercelAiGatewayConfigMissing": "Configuração do Vercel AI Gateway ausente para a criação do embedder",
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"invalidEmbedderType": "Tipo de embedder configurado inválido: {{embedderProvider}}",
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"vectorDimensionNotDeterminedOpenAiCompatible": "Não foi possível determinar a dimensão do vetor para o modelo '{{modelId}}' com o provedor '{{provider}}'. Certifique-se de que a 'Dimensão de Embedding' esteja configurada corretamente nas configurações do provedor compatível com OpenAI.",
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src/i18n/locales/ru/embeddings.json
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1
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"openAiCompatibleConfigMissing": "Отсутствует конфигурация, совместимая с OpenAI, для создания эмбеддера",
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"geminiConfigMissing": "Отсутствует конфигурация Gemini для создания эмбеддера",
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"mistralConfigMissing": "Конфигурация Mistral отсутствует для создания эмбеддера",
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"openRouterConfigMissing": "Конфигурация OpenRouter отсутствует для создания эмбеддера",
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"vercelAiGatewayConfigMissing": "Конфигурация Vercel AI Gateway отсутствует для создания эмбеддера",
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"invalidEmbedderType": "Настроен недопустимый тип эмбеддера: {{embedderProvider}}",
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"vectorDimensionNotDeterminedOpenAiCompatible": "Не удалось определить размерность вектора для модели '{{modelId}}' с провайдером '{{provider}}'. Убедитесь, что 'Размерность эмбеддинга' правильно установлена в настройках провайдера, совместимого с OpenAI.",
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src/i18n/locales/tr/embeddings.json
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@ -47,6 +47,7 @@
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"openAiCompatibleConfigMissing": "Gömücü oluşturmak için OpenAI uyumlu yapılandırması eksik",
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"geminiConfigMissing": "Gömücü oluşturmak için Gemini yapılandırması eksik",
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"mistralConfigMissing": "Gömücü oluşturmak için Mistral yapılandırması eksik",
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"openRouterConfigMissing": "Gömücü oluşturmak için OpenRouter yapılandırması eksik",
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"vercelAiGatewayConfigMissing": "Gömücü oluşturmak için Vercel AI Gateway yapılandırması eksik",
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"invalidEmbedderType": "Geçersiz gömücü türü yapılandırıldı: {{embedderProvider}}",
|
||||
"vectorDimensionNotDeterminedOpenAiCompatible": "'{{provider}}' sağlayıcısı ile '{{modelId}}' modeli için vektör boyutu belirlenemedi. OpenAI uyumlu sağlayıcı ayarlarında 'Gömme Boyutu'nun doğru ayarlandığından emin ol.",
|
||||
|
|
|
|||
1
src/i18n/locales/vi/embeddings.json
generated
1
src/i18n/locales/vi/embeddings.json
generated
|
|
@ -47,6 +47,7 @@
|
|||
"openAiCompatibleConfigMissing": "Thiếu cấu hình tương thích OpenAI để tạo embedder",
|
||||
"geminiConfigMissing": "Thiếu cấu hình Gemini để tạo embedder",
|
||||
"mistralConfigMissing": "Thiếu cấu hình Mistral để tạo trình nhúng",
|
||||
"openRouterConfigMissing": "Thiếu cấu hình OpenRouter để tạo trình nhúng",
|
||||
"vercelAiGatewayConfigMissing": "Thiếu cấu hình Vercel AI Gateway để tạo trình nhúng",
|
||||
"invalidEmbedderType": "Loại embedder được cấu hình không hợp lệ: {{embedderProvider}}",
|
||||
"vectorDimensionNotDeterminedOpenAiCompatible": "Không thể xác định kích thước vector cho mô hình '{{modelId}}' với nhà cung cấp '{{provider}}'. Hãy đảm bảo 'Kích thước Embedding' được cài đặt đúng trong cài đặt nhà cung cấp tương thích OpenAI.",
|
||||
|
|
|
|||
1
src/i18n/locales/zh-CN/embeddings.json
generated
1
src/i18n/locales/zh-CN/embeddings.json
generated
|
|
@ -47,6 +47,7 @@
|
|||
"openAiCompatibleConfigMissing": "创建嵌入器缺少 OpenAI 兼容配置",
|
||||
"geminiConfigMissing": "创建嵌入器缺少 Gemini 配置",
|
||||
"mistralConfigMissing": "创建嵌入器时缺少 Mistral 配置",
|
||||
"openRouterConfigMissing": "创建嵌入器时缺少 OpenRouter 配置",
|
||||
"vercelAiGatewayConfigMissing": "创建嵌入器时缺少 Vercel AI Gateway 配置",
|
||||
"invalidEmbedderType": "配置的嵌入器类型无效：{{embedderProvider}}",
|
||||
"vectorDimensionNotDeterminedOpenAiCompatible": "无法确定提供商 '{{provider}}' 的模型 '{{modelId}}' 的向量维度。请确保在 OpenAI 兼容提供商设置中正确设置了「嵌入维度」。",
|
||||
|
|
|
|||
1
src/i18n/locales/zh-TW/embeddings.json
generated
1
src/i18n/locales/zh-TW/embeddings.json
generated
|
|
@ -47,6 +47,7 @@
|
|||
"openAiCompatibleConfigMissing": "建立嵌入器缺少 OpenAI 相容設定",
|
||||
"geminiConfigMissing": "建立嵌入器缺少 Gemini 設定",
|
||||
"mistralConfigMissing": "建立嵌入器時缺少 Mistral 設定",
|
||||
"openRouterConfigMissing": "建立嵌入器時缺少 OpenRouter 設定",
|
||||
"vercelAiGatewayConfigMissing": "建立嵌入器時缺少 Vercel AI Gateway 設定",
|
||||
"invalidEmbedderType": "設定的嵌入器類型無效：{{embedderProvider}}",
|
||||
"vectorDimensionNotDeterminedOpenAiCompatible": "無法確定提供商 '{{provider}}' 的模型 '{{modelId}}' 的向量維度。請確保在 OpenAI 相容提供商設定中正確設定了「嵌入維度」。",
|
||||
|
|
|
|||
|
|
@ -20,6 +20,7 @@ export class CodeIndexConfigManager {
|
|||
private geminiOptions?: { apiKey: string }
|
||||
private mistralOptions?: { apiKey: string }
|
||||
private vercelAiGatewayOptions?: { apiKey: string }
|
||||
private openRouterOptions?: { apiKey: string }
|
||||
private qdrantUrl?: string = "http://localhost:6333"
|
||||
private qdrantApiKey?: string
|
||||
private searchMinScore?: number
|
||||
|
|
@ -71,6 +72,7 @@ export class CodeIndexConfigManager {
|
|||
const geminiApiKey = this.contextProxy?.getSecret("codebaseIndexGeminiApiKey") ?? ""
|
||||
const mistralApiKey = this.contextProxy?.getSecret("codebaseIndexMistralApiKey") ?? ""
|
||||
const vercelAiGatewayApiKey = this.contextProxy?.getSecret("codebaseIndexVercelAiGatewayApiKey") ?? ""
|
||||
const openRouterApiKey = this.contextProxy?.getSecret("codebaseIndexOpenRouterApiKey") ?? ""
|
||||
|
||||
// Update instance variables with configuration
|
||||
this.codebaseIndexEnabled = codebaseIndexEnabled ?? true
|
||||
|
|
@ -108,6 +110,8 @@ export class CodeIndexConfigManager {
|
|||
this.embedderProvider = "mistral"
|
||||
} else if (codebaseIndexEmbedderProvider === "vercel-ai-gateway") {
|
||||
this.embedderProvider = "vercel-ai-gateway"
|
||||
} else if (codebaseIndexEmbedderProvider === "openrouter") {
|
||||
this.embedderProvider = "openrouter"
|
||||
} else {
|
||||
this.embedderProvider = "openai"
|
||||
}
|
||||
|
|
@ -129,6 +133,7 @@ export class CodeIndexConfigManager {
|
|||
this.geminiOptions = geminiApiKey ? { apiKey: geminiApiKey } : undefined
|
||||
this.mistralOptions = mistralApiKey ? { apiKey: mistralApiKey } : undefined
|
||||
this.vercelAiGatewayOptions = vercelAiGatewayApiKey ? { apiKey: vercelAiGatewayApiKey } : undefined
|
||||
this.openRouterOptions = openRouterApiKey ? { apiKey: openRouterApiKey } : undefined
|
||||
}
|
||||
|
||||
/**
|
||||
|
|
@ -147,6 +152,7 @@ export class CodeIndexConfigManager {
|
|||
geminiOptions?: { apiKey: string }
|
||||
mistralOptions?: { apiKey: string }
|
||||
vercelAiGatewayOptions?: { apiKey: string }
|
||||
openRouterOptions?: { apiKey: string }
|
||||
qdrantUrl?: string
|
||||
qdrantApiKey?: string
|
||||
searchMinScore?: number
|
||||
|
|
@ -167,6 +173,7 @@ export class CodeIndexConfigManager {
|
|||
geminiApiKey: this.geminiOptions?.apiKey ?? "",
|
||||
mistralApiKey: this.mistralOptions?.apiKey ?? "",
|
||||
vercelAiGatewayApiKey: this.vercelAiGatewayOptions?.apiKey ?? "",
|
||||
openRouterApiKey: this.openRouterOptions?.apiKey ?? "",
|
||||
qdrantUrl: this.qdrantUrl ?? "",
|
||||
qdrantApiKey: this.qdrantApiKey ?? "",
|
||||
}
|
||||
|
|
@ -192,6 +199,7 @@ export class CodeIndexConfigManager {
|
|||
geminiOptions: this.geminiOptions,
|
||||
mistralOptions: this.mistralOptions,
|
||||
vercelAiGatewayOptions: this.vercelAiGatewayOptions,
|
||||
openRouterOptions: this.openRouterOptions,
|
||||
qdrantUrl: this.qdrantUrl,
|
||||
qdrantApiKey: this.qdrantApiKey,
|
||||
searchMinScore: this.currentSearchMinScore,
|
||||
|
|
@ -234,6 +242,11 @@ export class CodeIndexConfigManager {
|
|||
const qdrantUrl = this.qdrantUrl
|
||||
const isConfigured = !!(apiKey && qdrantUrl)
|
||||
return isConfigured
|
||||
} else if (this.embedderProvider === "openrouter") {
|
||||
const apiKey = this.openRouterOptions?.apiKey
|
||||
const qdrantUrl = this.qdrantUrl
|
||||
const isConfigured = !!(apiKey && qdrantUrl)
|
||||
return isConfigured
|
||||
}
|
||||
return false // Should not happen if embedderProvider is always set correctly
|
||||
}
|
||||
|
|
@ -269,6 +282,7 @@ export class CodeIndexConfigManager {
|
|||
const prevGeminiApiKey = prev?.geminiApiKey ?? ""
|
||||
const prevMistralApiKey = prev?.mistralApiKey ?? ""
|
||||
const prevVercelAiGatewayApiKey = prev?.vercelAiGatewayApiKey ?? ""
|
||||
const prevOpenRouterApiKey = prev?.openRouterApiKey ?? ""
|
||||
const prevQdrantUrl = prev?.qdrantUrl ?? ""
|
||||
const prevQdrantApiKey = prev?.qdrantApiKey ?? ""
|
||||
|
||||
|
|
@ -307,6 +321,7 @@ export class CodeIndexConfigManager {
|
|||
const currentGeminiApiKey = this.geminiOptions?.apiKey ?? ""
|
||||
const currentMistralApiKey = this.mistralOptions?.apiKey ?? ""
|
||||
const currentVercelAiGatewayApiKey = this.vercelAiGatewayOptions?.apiKey ?? ""
|
||||
const currentOpenRouterApiKey = this.openRouterOptions?.apiKey ?? ""
|
||||
const currentQdrantUrl = this.qdrantUrl ?? ""
|
||||
const currentQdrantApiKey = this.qdrantApiKey ?? ""
|
||||
|
||||
|
|
@ -337,6 +352,10 @@ export class CodeIndexConfigManager {
|
|||
return true
|
||||
}
|
||||
|
||||
if (prevOpenRouterApiKey !== currentOpenRouterApiKey) {
|
||||
return true
|
||||
}
|
||||
|
||||
// Check for model dimension changes (generic for all providers)
|
||||
if (prevModelDimension !== currentModelDimension) {
|
||||
return true
|
||||
|
|
@ -395,6 +414,7 @@ export class CodeIndexConfigManager {
|
|||
geminiOptions: this.geminiOptions,
|
||||
mistralOptions: this.mistralOptions,
|
||||
vercelAiGatewayOptions: this.vercelAiGatewayOptions,
|
||||
openRouterOptions: this.openRouterOptions,
|
||||
qdrantUrl: this.qdrantUrl,
|
||||
qdrantApiKey: this.qdrantApiKey,
|
||||
searchMinScore: this.currentSearchMinScore,
|
||||
|
|
|
|||
289
src/services/code-index/embedders/__tests__/openrouter.spec.ts
Normal file
289
src/services/code-index/embedders/__tests__/openrouter.spec.ts
Normal file
|
|
@ -0,0 +1,289 @@
|
|||
import type { MockedClass, MockedFunction } from "vitest"
|
||||
import { describe, it, expect, beforeEach, vi } from "vitest"
|
||||
import { OpenAI } from "openai"
|
||||
import { OpenRouterEmbedder } from "../openrouter"
|
||||
import { getModelDimension, getDefaultModelId } from "../../../../shared/embeddingModels"
|
||||
|
||||
// Mock the OpenAI SDK
|
||||
vi.mock("openai")
|
||||
|
||||
// Mock TelemetryService
|
||||
vi.mock("@roo-code/telemetry", () => ({
|
||||
TelemetryService: {
|
||||
instance: {
|
||||
captureEvent: vi.fn(),
|
||||
},
|
||||
},
|
||||
TelemetryEventName: {},
|
||||
}))
|
||||
|
||||
// Mock i18n
|
||||
vi.mock("../../../../i18n", () => ({
|
||||
t: (key: string, params?: Record<string, any>) => {
|
||||
const translations: Record<string, string> = {
|
||||
"embeddings:validation.apiKeyRequired": "validation.apiKeyRequired",
|
||||
"embeddings:authenticationFailed":
|
||||
"Failed to create embeddings: Authentication failed. Please check your OpenRouter API key.",
|
||||
"embeddings:failedWithStatus": `Failed to create embeddings after ${params?.attempts} attempts: HTTP ${params?.statusCode} - ${params?.errorMessage}`,
|
||||
"embeddings:failedWithError": `Failed to create embeddings after ${params?.attempts} attempts: ${params?.errorMessage}`,
|
||||
"embeddings:failedMaxAttempts": `Failed to create embeddings after ${params?.attempts} attempts`,
|
||||
"embeddings:textExceedsTokenLimit": `Text at index ${params?.index} exceeds maximum token limit (${params?.itemTokens} > ${params?.maxTokens}). Skipping.`,
|
||||
"embeddings:rateLimitRetry": `Rate limit hit, retrying in ${params?.delayMs}ms (attempt ${params?.attempt}/${params?.maxRetries})`,
|
||||
}
|
||||
return translations[key] || key
|
||||
},
|
||||
}))
|
||||
|
||||
const MockedOpenAI = OpenAI as MockedClass<typeof OpenAI>
|
||||
|
||||
describe("OpenRouterEmbedder", () => {
|
||||
const mockApiKey = "test-api-key"
|
||||
let mockEmbeddingsCreate: MockedFunction<any>
|
||||
let mockOpenAIInstance: any
|
||||
|
||||
beforeEach(() => {
|
||||
vi.clearAllMocks()
|
||||
vi.spyOn(console, "warn").mockImplementation(() => {})
|
||||
vi.spyOn(console, "error").mockImplementation(() => {})
|
||||
|
||||
// Setup mock OpenAI instance
|
||||
mockEmbeddingsCreate = vi.fn()
|
||||
mockOpenAIInstance = {
|
||||
embeddings: {
|
||||
create: mockEmbeddingsCreate,
|
||||
},
|
||||
}
|
||||
|
||||
MockedOpenAI.mockImplementation(() => mockOpenAIInstance)
|
||||
})
|
||||
|
||||
afterEach(() => {
|
||||
vi.restoreAllMocks()
|
||||
})
|
||||
|
||||
describe("constructor", () => {
|
||||
it("should create an instance with valid API key", () => {
|
||||
const embedder = new OpenRouterEmbedder(mockApiKey)
|
||||
expect(embedder).toBeInstanceOf(OpenRouterEmbedder)
|
||||
})
|
||||
|
||||
it("should throw error with empty API key", () => {
|
||||
expect(() => new OpenRouterEmbedder("")).toThrow("validation.apiKeyRequired")
|
||||
})
|
||||
|
||||
it("should use default model when none specified", () => {
|
||||
const embedder = new OpenRouterEmbedder(mockApiKey)
|
||||
const expectedDefault = getDefaultModelId("openrouter")
|
||||
expect(embedder.embedderInfo.name).toBe("openrouter")
|
||||
})
|
||||
|
||||
it("should use custom model when specified", () => {
|
||||
const customModel = "openai/text-embedding-3-small"
|
||||
const embedder = new OpenRouterEmbedder(mockApiKey, customModel)
|
||||
expect(embedder.embedderInfo.name).toBe("openrouter")
|
||||
})
|
||||
|
||||
it("should initialize OpenAI client with correct headers", () => {
|
||||
new OpenRouterEmbedder(mockApiKey)
|
||||
|
||||
expect(MockedOpenAI).toHaveBeenCalledWith({
|
||||
baseURL: "https://openrouter.ai/api/v1",
|
||||
apiKey: mockApiKey,
|
||||
defaultHeaders: {
|
||||
"HTTP-Referer": "https://github.com/RooCodeInc/Roo-Code",
|
||||
"X-Title": "Roo Code",
|
||||
},
|
||||
})
|
||||
})
|
||||
})
|
||||
|
||||
describe("embedderInfo", () => {
|
||||
it("should return correct embedder info", () => {
|
||||
const embedder = new OpenRouterEmbedder(mockApiKey)
|
||||
expect(embedder.embedderInfo).toEqual({
|
||||
name: "openrouter",
|
||||
})
|
||||
})
|
||||
})
|
||||
|
||||
describe("createEmbeddings", () => {
|
||||
let embedder: OpenRouterEmbedder
|
||||
|
||||
beforeEach(() => {
|
||||
embedder = new OpenRouterEmbedder(mockApiKey)
|
||||
})
|
||||
|
||||
it("should create embeddings successfully", async () => {
|
||||
// Create base64 encoded embedding with values that can be exactly represented in Float32
|
||||
const testEmbedding = new Float32Array([0.25, 0.5, 0.75])
|
||||
const base64String = Buffer.from(testEmbedding.buffer).toString("base64")
|
||||
|
||||
const mockResponse = {
|
||||
data: [
|
||||
{
|
||||
embedding: base64String,
|
||||
},
|
||||
],
|
||||
usage: {
|
||||
prompt_tokens: 5,
|
||||
total_tokens: 5,
|
||||
},
|
||||
}
|
||||
|
||||
mockEmbeddingsCreate.mockResolvedValue(mockResponse)
|
||||
|
||||
const result = await embedder.createEmbeddings(["test text"])
|
||||
|
||||
expect(mockEmbeddingsCreate).toHaveBeenCalledWith({
|
||||
input: ["test text"],
|
||||
model: "openai/text-embedding-3-large",
|
||||
encoding_format: "base64",
|
||||
})
|
||||
expect(result.embeddings).toHaveLength(1)
|
||||
expect(result.embeddings[0]).toEqual([0.25, 0.5, 0.75])
|
||||
expect(result.usage?.promptTokens).toBe(5)
|
||||
expect(result.usage?.totalTokens).toBe(5)
|
||||
})
|
||||
|
||||
it("should handle multiple texts", async () => {
|
||||
const embedding1 = new Float32Array([0.25, 0.5])
|
||||
const embedding2 = new Float32Array([0.75, 1.0])
|
||||
const base64String1 = Buffer.from(embedding1.buffer).toString("base64")
|
||||
const base64String2 = Buffer.from(embedding2.buffer).toString("base64")
|
||||
|
||||
const mockResponse = {
|
||||
data: [
|
||||
{
|
||||
embedding: base64String1,
|
||||
},
|
||||
{
|
||||
embedding: base64String2,
|
||||
},
|
||||
],
|
||||
usage: {
|
||||
prompt_tokens: 10,
|
||||
total_tokens: 10,
|
||||
},
|
||||
}
|
||||
|
||||
mockEmbeddingsCreate.mockResolvedValue(mockResponse)
|
||||
|
||||
const result = await embedder.createEmbeddings(["text1", "text2"])
|
||||
|
||||
expect(result.embeddings).toHaveLength(2)
|
||||
expect(result.embeddings[0]).toEqual([0.25, 0.5])
|
||||
expect(result.embeddings[1]).toEqual([0.75, 1.0])
|
||||
})
|
||||
|
||||
it("should use custom model when provided", async () => {
|
||||
const customModel = "mistralai/mistral-embed-2312"
|
||||
const embedderWithCustomModel = new OpenRouterEmbedder(mockApiKey, customModel)
|
||||
|
||||
const testEmbedding = new Float32Array([0.25, 0.5])
|
||||
const base64String = Buffer.from(testEmbedding.buffer).toString("base64")
|
||||
|
||||
const mockResponse = {
|
||||
data: [
|
||||
{
|
||||
embedding: base64String,
|
||||
},
|
||||
],
|
||||
usage: {
|
||||
prompt_tokens: 5,
|
||||
total_tokens: 5,
|
||||
},
|
||||
}
|
||||
|
||||
mockEmbeddingsCreate.mockResolvedValue(mockResponse)
|
||||
|
||||
await embedderWithCustomModel.createEmbeddings(["test"])
|
||||
|
||||
// Verify the embeddings.create was called with the custom model
|
||||
expect(mockEmbeddingsCreate).toHaveBeenCalledWith({
|
||||
input: ["test"],
|
||||
model: customModel,
|
||||
encoding_format: "base64",
|
||||
})
|
||||
})
|
||||
})
|
||||
|
||||
describe("validateConfiguration", () => {
|
||||
let embedder: OpenRouterEmbedder
|
||||
|
||||
beforeEach(() => {
|
||||
embedder = new OpenRouterEmbedder(mockApiKey)
|
||||
})
|
||||
|
||||
it("should validate configuration successfully", async () => {
|
||||
const testEmbedding = new Float32Array([0.25, 0.5])
|
||||
const base64String = Buffer.from(testEmbedding.buffer).toString("base64")
|
||||
|
||||
const mockResponse = {
|
||||
data: [
|
||||
{
|
||||
embedding: base64String,
|
||||
},
|
||||
],
|
||||
usage: {
|
||||
prompt_tokens: 1,
|
||||
total_tokens: 1,
|
||||
},
|
||||
}
|
||||
|
||||
mockEmbeddingsCreate.mockResolvedValue(mockResponse)
|
||||
|
||||
const result = await embedder.validateConfiguration()
|
||||
|
||||
expect(result.valid).toBe(true)
|
||||
expect(result.error).toBeUndefined()
|
||||
expect(mockEmbeddingsCreate).toHaveBeenCalledWith({
|
||||
input: ["test"],
|
||||
model: "openai/text-embedding-3-large",
|
||||
encoding_format: "base64",
|
||||
})
|
||||
})
|
||||
|
||||
it("should handle validation failure", async () => {
|
||||
const authError = new Error("Invalid API key")
|
||||
;(authError as any).status = 401
|
||||
|
||||
mockEmbeddingsCreate.mockRejectedValue(authError)
|
||||
|
||||
const result = await embedder.validateConfiguration()
|
||||
|
||||
expect(result.valid).toBe(false)
|
||||
expect(result.error).toBe("embeddings:validation.authenticationFailed")
|
||||
})
|
||||
})
|
||||
|
||||
describe("integration with shared models", () => {
|
||||
it("should work with defined OpenRouter models", () => {
|
||||
const openRouterModels = [
|
||||
"openai/text-embedding-3-small",
|
||||
"openai/text-embedding-3-large",
|
||||
"openai/text-embedding-ada-002",
|
||||
"google/gemini-embedding-001",
|
||||
"mistralai/mistral-embed-2312",
|
||||
"mistralai/codestral-embed-2505",
|
||||
"qwen/qwen3-embedding-8b",
|
||||
]
|
||||
|
||||
openRouterModels.forEach((model) => {
|
||||
const dimension = getModelDimension("openrouter", model)
|
||||
expect(dimension).toBeDefined()
|
||||
expect(dimension).toBeGreaterThan(0)
|
||||
|
||||
const embedder = new OpenRouterEmbedder(mockApiKey, model)
|
||||
expect(embedder.embedderInfo.name).toBe("openrouter")
|
||||
})
|
||||
})
|
||||
|
||||
it("should use correct default model", () => {
|
||||
const defaultModel = getDefaultModelId("openrouter")
|
||||
expect(defaultModel).toBe("openai/text-embedding-3-large")
|
||||
|
||||
const dimension = getModelDimension("openrouter", defaultModel)
|
||||
expect(dimension).toBe(3072)
|
||||
})
|
||||
})
|
||||
})
|
||||
396
src/services/code-index/embedders/openrouter.ts
Normal file
396
src/services/code-index/embedders/openrouter.ts
Normal file
|
|
@ -0,0 +1,396 @@
|
|||
import { OpenAI } from "openai"
|
||||
import { IEmbedder, EmbeddingResponse, EmbedderInfo } from "../interfaces/embedder"
|
||||
import {
|
||||
MAX_BATCH_TOKENS,
|
||||
MAX_ITEM_TOKENS,
|
||||
MAX_BATCH_RETRIES as MAX_RETRIES,
|
||||
INITIAL_RETRY_DELAY_MS as INITIAL_DELAY_MS,
|
||||
} from "../constants"
|
||||
import { getDefaultModelId, getModelQueryPrefix } from "../../../shared/embeddingModels"
|
||||
import { t } from "../../../i18n"
|
||||
import { withValidationErrorHandling, HttpError, formatEmbeddingError } from "../shared/validation-helpers"
|
||||
import { TelemetryEventName } from "@roo-code/types"
|
||||
import { TelemetryService } from "@roo-code/telemetry"
|
||||
import { Mutex } from "async-mutex"
|
||||
import { handleOpenAIError } from "../../../api/providers/utils/openai-error-handler"
|
||||
|
||||
interface EmbeddingItem {
|
||||
embedding: string | number[]
|
||||
[key: string]: any
|
||||
}
|
||||
|
||||
interface OpenRouterEmbeddingResponse {
|
||||
data: EmbeddingItem[]
|
||||
usage?: {
|
||||
prompt_tokens?: number
|
||||
total_tokens?: number
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* OpenRouter implementation of the embedder interface with batching and rate limiting.
|
||||
* OpenRouter provides an OpenAI-compatible API that gives access to hundreds of models
|
||||
* through a single endpoint, automatically handling fallbacks and cost optimization.
|
||||
*/
|
||||
export class OpenRouterEmbedder implements IEmbedder {
|
||||
private embeddingsClient: OpenAI
|
||||
private readonly defaultModelId: string
|
||||
private readonly apiKey: string
|
||||
private readonly maxItemTokens: number
|
||||
private readonly baseUrl: string = "https://openrouter.ai/api/v1"
|
||||
|
||||
// Global rate limiting state shared across all instances
|
||||
private static globalRateLimitState = {
|
||||
isRateLimited: false,
|
||||
rateLimitResetTime: 0,
|
||||
consecutiveRateLimitErrors: 0,
|
||||
lastRateLimitError: 0,
|
||||
// Mutex to ensure thread-safe access to rate limit state
|
||||
mutex: new Mutex(),
|
||||
}
|
||||
|
||||
/**
|
||||
* Creates a new OpenRouter embedder
|
||||
* @param apiKey The API key for authentication
|
||||
* @param modelId Optional model identifier (defaults to "openai/text-embedding-3-large")
|
||||
* @param maxItemTokens Optional maximum tokens per item (defaults to MAX_ITEM_TOKENS)
|
||||
*/
|
||||
constructor(apiKey: string, modelId?: string, maxItemTokens?: number) {
|
||||
if (!apiKey) {
|
||||
throw new Error(t("embeddings:validation.apiKeyRequired"))
|
||||
}
|
||||
|
||||
this.apiKey = apiKey
|
||||
|
||||
// Wrap OpenAI client creation to handle invalid API key characters
|
||||
try {
|
||||
this.embeddingsClient = new OpenAI({
|
||||
baseURL: this.baseUrl,
|
||||
apiKey: apiKey,
|
||||
defaultHeaders: {
|
||||
"HTTP-Referer": "https://github.com/RooCodeInc/Roo-Code",
|
||||
"X-Title": "Roo Code",
|
||||
},
|
||||
})
|
||||
} catch (error) {
|
||||
// Use the error handler to transform ByteString conversion errors
|
||||
throw handleOpenAIError(error, "OpenRouter")
|
||||
}
|
||||
|
||||
this.defaultModelId = modelId || getDefaultModelId("openrouter")
|
||||
this.maxItemTokens = maxItemTokens || MAX_ITEM_TOKENS
|
||||
}
|
||||
|
||||
/**
|
||||
* Creates embeddings for the given texts with batching and rate limiting
|
||||
* @param texts Array of text strings to embed
|
||||
* @param model Optional model identifier
|
||||
* @returns Promise resolving to embedding response
|
||||
*/
|
||||
async createEmbeddings(texts: string[], model?: string): Promise<EmbeddingResponse> {
|
||||
const modelToUse = model || this.defaultModelId
|
||||
|
||||
// Apply model-specific query prefix if required
|
||||
const queryPrefix = getModelQueryPrefix("openrouter", modelToUse)
|
||||
const processedTexts = queryPrefix
|
||||
? texts.map((text, index) => {
|
||||
// Prevent double-prefixing
|
||||
if (text.startsWith(queryPrefix)) {
|
||||
return text
|
||||
}
|
||||
const prefixedText = `${queryPrefix}${text}`
|
||||
const estimatedTokens = Math.ceil(prefixedText.length / 4)
|
||||
if (estimatedTokens > MAX_ITEM_TOKENS) {
|
||||
console.warn(
|
||||
t("embeddings:textWithPrefixExceedsTokenLimit", {
|
||||
index,
|
||||
estimatedTokens,
|
||||
maxTokens: MAX_ITEM_TOKENS,
|
||||
}),
|
||||
)
|
||||
// Return original text if adding prefix would exceed limit
|
||||
return text
|
||||
}
|
||||
return prefixedText
|
||||
})
|
||||
: texts
|
||||
|
||||
const allEmbeddings: number[][] = []
|
||||
const usage = { promptTokens: 0, totalTokens: 0 }
|
||||
const remainingTexts = [...processedTexts]
|
||||
|
||||
while (remainingTexts.length > 0) {
|
||||
const currentBatch: string[] = []
|
||||
let currentBatchTokens = 0
|
||||
const processedIndices: number[] = []
|
||||
|
||||
for (let i = 0; i < remainingTexts.length; i++) {
|
||||
const text = remainingTexts[i]
|
||||
const itemTokens = Math.ceil(text.length / 4)
|
||||
|
||||
if (itemTokens > this.maxItemTokens) {
|
||||
console.warn(
|
||||
t("embeddings:textExceedsTokenLimit", {
|
||||
index: i,
|
||||
itemTokens,
|
||||
maxTokens: this.maxItemTokens,
|
||||
}),
|
||||
)
|
||||
processedIndices.push(i)
|
||||
continue
|
||||
}
|
||||
|
||||
if (currentBatchTokens + itemTokens <= MAX_BATCH_TOKENS) {
|
||||
currentBatch.push(text)
|
||||
currentBatchTokens += itemTokens
|
||||
processedIndices.push(i)
|
||||
} else {
|
||||
break
|
||||
}
|
||||
}
|
||||
|
||||
// Remove processed items from remainingTexts (in reverse order to maintain correct indices)
|
||||
for (let i = processedIndices.length - 1; i >= 0; i--) {
|
||||
remainingTexts.splice(processedIndices[i], 1)
|
||||
}
|
||||
|
||||
if (currentBatch.length > 0) {
|
||||
const batchResult = await this._embedBatchWithRetries(currentBatch, modelToUse)
|
||||
allEmbeddings.push(...batchResult.embeddings)
|
||||
usage.promptTokens += batchResult.usage.promptTokens
|
||||
usage.totalTokens += batchResult.usage.totalTokens
|
||||
}
|
||||
}
|
||||
|
||||
return { embeddings: allEmbeddings, usage }
|
||||
}
|
||||
|
||||
/**
|
||||
* Helper method to handle batch embedding with retries and exponential backoff
|
||||
* @param batchTexts Array of texts to embed in this batch
|
||||
* @param model Model identifier to use
|
||||
* @returns Promise resolving to embeddings and usage statistics
|
||||
*/
|
||||
private async _embedBatchWithRetries(
|
||||
batchTexts: string[],
|
||||
model: string,
|
||||
): Promise<{ embeddings: number[][]; usage: { promptTokens: number; totalTokens: number } }> {
|
||||
for (let attempts = 0; attempts < MAX_RETRIES; attempts++) {
|
||||
// Check global rate limit before attempting request
|
||||
await this.waitForGlobalRateLimit()
|
||||
|
||||
try {
|
||||
const response = (await this.embeddingsClient.embeddings.create({
|
||||
input: batchTexts,
|
||||
model: model,
|
||||
// OpenAI package (as of v4.78.1) has a parsing issue that truncates embedding dimensions to 256
|
||||
// when processing numeric arrays, which breaks compatibility with models using larger dimensions.
|
||||
// By requesting base64 encoding, we bypass the package's parser and handle decoding ourselves.
|
||||
encoding_format: "base64",
|
||||
})) as OpenRouterEmbeddingResponse
|
||||
|
||||
// Convert base64 embeddings to float32 arrays
|
||||
const processedEmbeddings = response.data.map((item: EmbeddingItem) => {
|
||||
if (typeof item.embedding === "string") {
|
||||
const buffer = Buffer.from(item.embedding, "base64")
|
||||
|
||||
// Create Float32Array view over the buffer
|
||||
const float32Array = new Float32Array(buffer.buffer, buffer.byteOffset, buffer.byteLength / 4)
|
||||
|
||||
return {
|
||||
...item,
|
||||
embedding: Array.from(float32Array),
|
||||
}
|
||||
}
|
||||
return item
|
||||
})
|
||||
|
||||
// Replace the original data with processed embeddings
|
||||
response.data = processedEmbeddings
|
||||
|
||||
const embeddings = response.data.map((item) => item.embedding as number[])
|
||||
|
||||
return {
|
||||
embeddings: embeddings,
|
||||
usage: {
|
||||
promptTokens: response.usage?.prompt_tokens || 0,
|
||||
totalTokens: response.usage?.total_tokens || 0,
|
||||
},
|
||||
}
|
||||
} catch (error) {
|
||||
// Capture telemetry before error is reformatted
|
||||
TelemetryService.instance.captureEvent(TelemetryEventName.CODE_INDEX_ERROR, {
|
||||
error: error instanceof Error ? error.message : String(error),
|
||||
stack: error instanceof Error ? error.stack : undefined,
|
||||
location: "OpenRouterEmbedder:_embedBatchWithRetries",
|
||||
attempt: attempts + 1,
|
||||
})
|
||||
|
||||
const hasMoreAttempts = attempts < MAX_RETRIES - 1
|
||||
|
||||
// Check if it's a rate limit error
|
||||
const httpError = error as HttpError
|
||||
if (httpError?.status === 429) {
|
||||
// Update global rate limit state
|
||||
await this.updateGlobalRateLimitState(httpError)
|
||||
|
||||
if (hasMoreAttempts) {
|
||||
// Calculate delay based on global rate limit state
|
||||
const baseDelay = INITIAL_DELAY_MS * Math.pow(2, attempts)
|
||||
const globalDelay = await this.getGlobalRateLimitDelay()
|
||||
const delayMs = Math.max(baseDelay, globalDelay)
|
||||
|
||||
console.warn(
|
||||
t("embeddings:rateLimitRetry", {
|
||||
delayMs,
|
||||
attempt: attempts + 1,
|
||||
maxRetries: MAX_RETRIES,
|
||||
}),
|
||||
)
|
||||
await new Promise((resolve) => setTimeout(resolve, delayMs))
|
||||
continue
|
||||
}
|
||||
}
|
||||
|
||||
// Log the error for debugging
|
||||
console.error(`OpenRouter embedder error (attempt ${attempts + 1}/${MAX_RETRIES}):`, error)
|
||||
|
||||
// Format and throw the error
|
||||
throw formatEmbeddingError(error, MAX_RETRIES)
|
||||
}
|
||||
}
|
||||
|
||||
throw new Error(t("embeddings:failedMaxAttempts", { attempts: MAX_RETRIES }))
|
||||
}
|
||||
|
||||
/**
|
||||
* Validates the OpenRouter embedder configuration by testing API connectivity
|
||||
* @returns Promise resolving to validation result with success status and optional error message
|
||||
*/
|
||||
async validateConfiguration(): Promise<{ valid: boolean; error?: string }> {
|
||||
return withValidationErrorHandling(async () => {
|
||||
try {
|
||||
// Test with a minimal embedding request
|
||||
const testTexts = ["test"]
|
||||
const modelToUse = this.defaultModelId
|
||||
|
||||
const response = (await this.embeddingsClient.embeddings.create({
|
||||
input: testTexts,
|
||||
model: modelToUse,
|
||||
encoding_format: "base64",
|
||||
})) as OpenRouterEmbeddingResponse
|
||||
|
||||
// Check if we got a valid response
|
||||
if (!response?.data || response.data.length === 0) {
|
||||
return {
|
||||
valid: false,
|
||||
error: "embeddings:validation.invalidResponse",
|
||||
}
|
||||
}
|
||||
|
||||
return { valid: true }
|
||||
} catch (error) {
|
||||
// Capture telemetry for validation errors
|
||||
TelemetryService.instance.captureEvent(TelemetryEventName.CODE_INDEX_ERROR, {
|
||||
error: error instanceof Error ? error.message : String(error),
|
||||
stack: error instanceof Error ? error.stack : undefined,
|
||||
location: "OpenRouterEmbedder:validateConfiguration",
|
||||
})
|
||||
throw error
|
||||
}
|
||||
}, "openrouter")
|
||||
}
|
||||
|
||||
/**
|
||||
* Returns information about this embedder
|
||||
*/
|
||||
get embedderInfo(): EmbedderInfo {
|
||||
return {
|
||||
name: "openrouter",
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Waits if there's an active global rate limit
|
||||
*/
|
||||
private async waitForGlobalRateLimit(): Promise<void> {
|
||||
const release = await OpenRouterEmbedder.globalRateLimitState.mutex.acquire()
|
||||
let mutexReleased = false
|
||||
|
||||
try {
|
||||
const state = OpenRouterEmbedder.globalRateLimitState
|
||||
|
||||
if (state.isRateLimited && state.rateLimitResetTime > Date.now()) {
|
||||
const waitTime = state.rateLimitResetTime - Date.now()
|
||||
// Silent wait - no logging to prevent flooding
|
||||
release()
|
||||
mutexReleased = true
|
||||
await new Promise((resolve) => setTimeout(resolve, waitTime))
|
||||
return
|
||||
}
|
||||
|
||||
// Reset rate limit if time has passed
|
||||
if (state.isRateLimited && state.rateLimitResetTime <= Date.now()) {
|
||||
state.isRateLimited = false
|
||||
state.consecutiveRateLimitErrors = 0
|
||||
}
|
||||
} finally {
|
||||
// Only release if we haven't already
|
||||
if (!mutexReleased) {
|
||||
release()
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Updates global rate limit state when a 429 error occurs
|
||||
*/
|
||||
private async updateGlobalRateLimitState(error: HttpError): Promise<void> {
|
||||
const release = await OpenRouterEmbedder.globalRateLimitState.mutex.acquire()
|
||||
try {
|
||||
const state = OpenRouterEmbedder.globalRateLimitState
|
||||
const now = Date.now()
|
||||
|
||||
// Increment consecutive rate limit errors
|
||||
if (now - state.lastRateLimitError < 60000) {
|
||||
// Within 1 minute
|
||||
state.consecutiveRateLimitErrors++
|
||||
} else {
|
||||
state.consecutiveRateLimitErrors = 1
|
||||
}
|
||||
|
||||
state.lastRateLimitError = now
|
||||
|
||||
// Calculate exponential backoff based on consecutive errors
|
||||
const baseDelay = 5000 // 5 seconds base
|
||||
const maxDelay = 300000 // 5 minutes max
|
||||
const exponentialDelay = Math.min(baseDelay * Math.pow(2, state.consecutiveRateLimitErrors - 1), maxDelay)
|
||||
|
||||
// Set global rate limit
|
||||
state.isRateLimited = true
|
||||
state.rateLimitResetTime = now + exponentialDelay
|
||||
|
||||
// Silent rate limit activation - no logging to prevent flooding
|
||||
} finally {
|
||||
release()
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Gets the current global rate limit delay
|
||||
*/
|
||||
private async getGlobalRateLimitDelay(): Promise<number> {
|
||||
const release = await OpenRouterEmbedder.globalRateLimitState.mutex.acquire()
|
||||
try {
|
||||
const state = OpenRouterEmbedder.globalRateLimitState
|
||||
|
||||
if (state.isRateLimited && state.rateLimitResetTime > Date.now()) {
|
||||
return state.rateLimitResetTime - Date.now()
|
||||
}
|
||||
|
||||
return 0
|
||||
} finally {
|
||||
release()
|
||||
}
|
||||
}
|
||||
}
|
||||
|
|
@ -15,6 +15,7 @@ export interface CodeIndexConfig {
|
|||
geminiOptions?: { apiKey: string }
|
||||
mistralOptions?: { apiKey: string }
|
||||
vercelAiGatewayOptions?: { apiKey: string }
|
||||
openRouterOptions?: { apiKey: string }
|
||||
qdrantUrl?: string
|
||||
qdrantApiKey?: string
|
||||
searchMinScore?: number
|
||||
|
|
@ -37,6 +38,7 @@ export type PreviousConfigSnapshot = {
|
|||
geminiApiKey?: string
|
||||
mistralApiKey?: string
|
||||
vercelAiGatewayApiKey?: string
|
||||
openRouterApiKey?: string
|
||||
qdrantUrl?: string
|
||||
qdrantApiKey?: string
|
||||
}
|
||||
|
|
|
|||
|
|
@ -28,7 +28,14 @@ export interface EmbeddingResponse {
|
|||
}
|
||||
}
|
||||
|
||||
export type AvailableEmbedders = "openai" | "ollama" | "openai-compatible" | "gemini" | "mistral" | "vercel-ai-gateway"
|
||||
export type AvailableEmbedders =
|
||||
| "openai"
|
||||
| "ollama"
|
||||
| "openai-compatible"
|
||||
| "gemini"
|
||||
| "mistral"
|
||||
| "vercel-ai-gateway"
|
||||
| "openrouter"
|
||||
|
||||
export interface EmbedderInfo {
|
||||
name: AvailableEmbedders
|
||||
|
|
|
|||
|
|
@ -70,7 +70,14 @@ export interface ICodeIndexManager {
|
|||
}
|
||||
|
||||
export type IndexingState = "Standby" | "Indexing" | "Indexed" | "Error"
|
||||
export type EmbedderProvider = "openai" | "ollama" | "openai-compatible" | "gemini" | "mistral" | "vercel-ai-gateway"
|
||||
export type EmbedderProvider =
|
||||
| "openai"
|
||||
| "ollama"
|
||||
| "openai-compatible"
|
||||
| "gemini"
|
||||
| "mistral"
|
||||
| "vercel-ai-gateway"
|
||||
| "openrouter"
|
||||
|
||||
export interface IndexProgressUpdate {
|
||||
systemStatus: IndexingState
|
||||
|
|
|
|||
|
|
@ -5,6 +5,7 @@ import { OpenAICompatibleEmbedder } from "./embedders/openai-compatible"
|
|||
import { GeminiEmbedder } from "./embedders/gemini"
|
||||
import { MistralEmbedder } from "./embedders/mistral"
|
||||
import { VercelAiGatewayEmbedder } from "./embedders/vercel-ai-gateway"
|
||||
import { OpenRouterEmbedder } from "./embedders/openrouter"
|
||||
import { EmbedderProvider, getDefaultModelId, getModelDimension } from "../../shared/embeddingModels"
|
||||
import { QdrantVectorStore } from "./vector-store/qdrant-client"
|
||||
import { codeParser, DirectoryScanner, FileWatcher } from "./processors"
|
||||
|
|
@ -79,6 +80,11 @@ export class CodeIndexServiceFactory {
|
|||
throw new Error(t("embeddings:serviceFactory.vercelAiGatewayConfigMissing"))
|
||||
}
|
||||
return new VercelAiGatewayEmbedder(config.vercelAiGatewayOptions.apiKey, config.modelId)
|
||||
} else if (provider === "openrouter") {
|
||||
if (!config.openRouterOptions?.apiKey) {
|
||||
throw new Error(t("embeddings:serviceFactory.openRouterConfigMissing"))
|
||||
}
|
||||
return new OpenRouterEmbedder(config.openRouterOptions.apiKey, config.modelId)
|
||||
}
|
||||
|
||||
throw new Error(
|
||||
|
|
|
|||
|
|
@ -292,6 +292,7 @@ export interface WebviewMessage {
|
|||
| "gemini"
|
||||
| "mistral"
|
||||
| "vercel-ai-gateway"
|
||||
| "openrouter"
|
||||
codebaseIndexEmbedderBaseUrl?: string
|
||||
codebaseIndexEmbedderModelId: string
|
||||
codebaseIndexEmbedderModelDimension?: number // Generic dimension for all providers
|
||||
|
|
@ -306,6 +307,7 @@ export interface WebviewMessage {
|
|||
codebaseIndexGeminiApiKey?: string
|
||||
codebaseIndexMistralApiKey?: string
|
||||
codebaseIndexVercelAiGatewayApiKey?: string
|
||||
codebaseIndexOpenRouterApiKey?: string
|
||||
}
|
||||
}
|
||||
|
||||
|
|
|
|||
|
|
@ -2,7 +2,14 @@
|
|||
* Defines profiles for different embedding models, including their dimensions.
|
||||
*/
|
||||
|
||||
export type EmbedderProvider = "openai" | "ollama" | "openai-compatible" | "gemini" | "mistral" | "vercel-ai-gateway" // Add other providers as needed
|
||||
export type EmbedderProvider =
|
||||
| "openai"
|
||||
| "ollama"
|
||||
| "openai-compatible"
|
||||
| "gemini"
|
||||
| "mistral"
|
||||
| "vercel-ai-gateway"
|
||||
| "openrouter" // Add other providers as needed
|
||||
|
||||
export interface EmbeddingModelProfile {
|
||||
dimension: number
|
||||
|
|
@ -70,6 +77,19 @@ export const EMBEDDING_MODEL_PROFILES: EmbeddingModelProfiles = {
|
|||
"mistral/codestral-embed": { dimension: 1536, scoreThreshold: 0.4 },
|
||||
"mistral/mistral-embed": { dimension: 1024, scoreThreshold: 0.4 },
|
||||
},
|
||||
openrouter: {
|
||||
// OpenAI models via OpenRouter
|
||||
"openai/text-embedding-3-small": { dimension: 1536, scoreThreshold: 0.4 },
|
||||
"openai/text-embedding-3-large": { dimension: 3072, scoreThreshold: 0.4 },
|
||||
"openai/text-embedding-ada-002": { dimension: 1536, scoreThreshold: 0.4 },
|
||||
// Google models via OpenRouter
|
||||
"google/gemini-embedding-001": { dimension: 3072, scoreThreshold: 0.4 },
|
||||
// Mistral models via OpenRouter
|
||||
"mistralai/mistral-embed-2312": { dimension: 1024, scoreThreshold: 0.4 },
|
||||
"mistralai/codestral-embed-2505": { dimension: 3072, scoreThreshold: 0.4 },
|
||||
// Qwen models via OpenRouter
|
||||
"qwen/qwen3-embedding-8b": { dimension: 4096, scoreThreshold: 0.4 },
|
||||
},
|
||||
}
|
||||
|
||||
/**
|
||||
|
|
@ -163,6 +183,9 @@ export function getDefaultModelId(provider: EmbedderProvider): string {
|
|||
case "vercel-ai-gateway":
|
||||
return "openai/text-embedding-3-large"
|
||||
|
||||
case "openrouter":
|
||||
return "openai/text-embedding-3-large"
|
||||
|
||||
default:
|
||||
// Fallback for unknown providers
|
||||
console.warn(`Unknown provider for default model ID: ${provider}. Falling back to OpenAI default.`)
|
||||
|
|
|
|||
|
|
@ -73,6 +73,7 @@ interface LocalCodeIndexSettings {
|
|||
codebaseIndexGeminiApiKey?: string
|
||||
codebaseIndexMistralApiKey?: string
|
||||
codebaseIndexVercelAiGatewayApiKey?: string
|
||||
codebaseIndexOpenRouterApiKey?: string
|
||||
}
|
||||
|
||||
// Validation schema for codebase index settings
|
||||
|
|
@ -149,6 +150,16 @@ const createValidationSchema = (provider: EmbedderProvider, t: any) => {
|
|||
.min(1, t("settings:codeIndex.validation.modelSelectionRequired")),
|
||||
})
|
||||
|
||||
case "openrouter":
|
||||
return baseSchema.extend({
|
||||
codebaseIndexOpenRouterApiKey: z
|
||||
.string()
|
||||
.min(1, t("settings:codeIndex.validation.openRouterApiKeyRequired")),
|
||||
codebaseIndexEmbedderModelId: z
|
||||
.string()
|
||||
.min(1, t("settings:codeIndex.validation.modelSelectionRequired")),
|
||||
})
|
||||
|
||||
default:
|
||||
return baseSchema
|
||||
}
|
||||
|
|
@ -194,6 +205,7 @@ export const CodeIndexPopover: React.FC<CodeIndexPopoverProps> = ({
|
|||
codebaseIndexGeminiApiKey: "",
|
||||
codebaseIndexMistralApiKey: "",
|
||||
codebaseIndexVercelAiGatewayApiKey: "",
|
||||
codebaseIndexOpenRouterApiKey: "",
|
||||
})
|
||||
|
||||
// Initial settings state - stores the settings when popover opens
|
||||
|
|
@ -229,6 +241,7 @@ export const CodeIndexPopover: React.FC<CodeIndexPopoverProps> = ({
|
|||
codebaseIndexGeminiApiKey: "",
|
||||
codebaseIndexMistralApiKey: "",
|
||||
codebaseIndexVercelAiGatewayApiKey: "",
|
||||
codebaseIndexOpenRouterApiKey: "",
|
||||
}
|
||||
setInitialSettings(settings)
|
||||
setCurrentSettings(settings)
|
||||
|
|
@ -345,6 +358,14 @@ export const CodeIndexPopover: React.FC<CodeIndexPopoverProps> = ({
|
|||
? SECRET_PLACEHOLDER
|
||||
: ""
|
||||
}
|
||||
if (
|
||||
!prev.codebaseIndexOpenRouterApiKey ||
|
||||
prev.codebaseIndexOpenRouterApiKey === SECRET_PLACEHOLDER
|
||||
) {
|
||||
updated.codebaseIndexOpenRouterApiKey = secretStatus.hasOpenRouterApiKey
|
||||
? SECRET_PLACEHOLDER
|
||||
: ""
|
||||
}
|
||||
|
||||
return updated
|
||||
}
|
||||
|
|
@ -418,7 +439,8 @@ export const CodeIndexPopover: React.FC<CodeIndexPopoverProps> = ({
|
|||
key === "codebaseIndexOpenAiCompatibleApiKey" ||
|
||||
key === "codebaseIndexGeminiApiKey" ||
|
||||
key === "codebaseIndexMistralApiKey" ||
|
||||
key === "codebaseIndexVercelAiGatewayApiKey"
|
||||
key === "codebaseIndexVercelAiGatewayApiKey" ||
|
||||
key === "codebaseIndexOpenRouterApiKey"
|
||||
) {
|
||||
dataToValidate[key] = "placeholder-valid"
|
||||
}
|
||||
|
|
@ -669,6 +691,9 @@ export const CodeIndexPopover: React.FC<CodeIndexPopoverProps> = ({
|
|||
<SelectItem value="vercel-ai-gateway">
|
||||
{t("settings:codeIndex.vercelAiGatewayProvider")}
|
||||
</SelectItem>
|
||||
<SelectItem value="openrouter">
|
||||
{t("settings:codeIndex.openRouterProvider")}
|
||||
</SelectItem>
|
||||
</SelectContent>
|
||||
</Select>
|
||||
</div>
|
||||
|
|
@ -1131,6 +1156,71 @@ export const CodeIndexPopover: React.FC<CodeIndexPopoverProps> = ({
|
|||
</>
|
||||
)}
|
||||
|
||||
{currentSettings.codebaseIndexEmbedderProvider === "openrouter" && (
|
||||
<>
|
||||
<div className="space-y-2">
|
||||
<label className="text-sm font-medium">
|
||||
{t("settings:codeIndex.openRouterApiKeyLabel")}
|
||||
</label>
|
||||
<VSCodeTextField
|
||||
type="password"
|
||||
value={currentSettings.codebaseIndexOpenRouterApiKey || ""}
|
||||
onInput={(e: any) =>
|
||||
updateSetting("codebaseIndexOpenRouterApiKey", e.target.value)
|
||||
}
|
||||
placeholder={t("settings:codeIndex.openRouterApiKeyPlaceholder")}
|
||||
className={cn("w-full", {
|
||||
"border-red-500": formErrors.codebaseIndexOpenRouterApiKey,
|
||||
})}
|
||||
/>
|
||||
{formErrors.codebaseIndexOpenRouterApiKey && (
|
||||
<p className="text-xs text-vscode-errorForeground mt-1 mb-0">
|
||||
{formErrors.codebaseIndexOpenRouterApiKey}
|
||||
</p>
|
||||
)}
|
||||
</div>
|
||||
|
||||
<div className="space-y-2">
|
||||
<label className="text-sm font-medium">
|
||||
{t("settings:codeIndex.modelLabel")}
|
||||
</label>
|
||||
<VSCodeDropdown
|
||||
value={currentSettings.codebaseIndexEmbedderModelId}
|
||||
onChange={(e: any) =>
|
||||
updateSetting("codebaseIndexEmbedderModelId", e.target.value)
|
||||
}
|
||||
className={cn("w-full", {
|
||||
"border-red-500": formErrors.codebaseIndexEmbedderModelId,
|
||||
})}>
|
||||
<VSCodeOption value="" className="p-2">
|
||||
{t("settings:codeIndex.selectModel")}
|
||||
</VSCodeOption>
|
||||
{getAvailableModels().map((modelId) => {
|
||||
const model =
|
||||
codebaseIndexModels?.[
|
||||
currentSettings.codebaseIndexEmbedderProvider
|
||||
]?.[modelId]
|
||||
return (
|
||||
<VSCodeOption key={modelId} value={modelId} className="p-2">
|
||||
{modelId}{" "}
|
||||
{model
|
||||
? t("settings:codeIndex.modelDimensions", {
|
||||
dimension: model.dimension,
|
||||
})
|
||||
: ""}
|
||||
</VSCodeOption>
|
||||
)
|
||||
})}
|
||||
</VSCodeDropdown>
|
||||
{formErrors.codebaseIndexEmbedderModelId && (
|
||||
<p className="text-xs text-vscode-errorForeground mt-1 mb-0">
|
||||
{formErrors.codebaseIndexEmbedderModelId}
|
||||
</p>
|
||||
)}
|
||||
</div>
|
||||
</>
|
||||
)}
|
||||
|
||||
{/* Qdrant Settings */}
|
||||
<div className="space-y-2">
|
||||
<label className="text-sm font-medium">
|
||||
|
|
|
|||
6
webview-ui/src/i18n/locales/ca/settings.json
generated
6
webview-ui/src/i18n/locales/ca/settings.json
generated
|
|
@ -58,6 +58,9 @@
|
|||
"vercelAiGatewayProvider": "Vercel AI Gateway",
|
||||
"vercelAiGatewayApiKeyLabel": "Clau API",
|
||||
"vercelAiGatewayApiKeyPlaceholder": "Introduïu la vostra clau API de Vercel AI Gateway",
|
||||
"openRouterProvider": "OpenRouter",
|
||||
"openRouterApiKeyLabel": "Clau de l'API d'OpenRouter",
|
||||
"openRouterApiKeyPlaceholder": "Introduïu la vostra clau de l'API d'OpenRouter",
|
||||
"openaiCompatibleProvider": "Compatible amb OpenAI",
|
||||
"openAiKeyLabel": "Clau API OpenAI",
|
||||
"openAiKeyPlaceholder": "Introduïu la vostra clau API OpenAI",
|
||||
|
|
@ -124,7 +127,8 @@
|
|||
"vercelAiGatewayApiKeyRequired": "Es requereix la clau API de Vercel AI Gateway",
|
||||
"ollamaBaseUrlRequired": "Cal una URL base d'Ollama",
|
||||
"baseUrlRequired": "Cal una URL base",
|
||||
"modelDimensionMinValue": "La dimensió del model ha de ser superior a 0"
|
||||
"modelDimensionMinValue": "La dimensió del model ha de ser superior a 0",
|
||||
"openRouterApiKeyRequired": "Clau API d'OpenRouter és requerida"
|
||||
},
|
||||
"advancedConfigLabel": "Configuració avançada",
|
||||
"searchMinScoreLabel": "Llindar de puntuació de cerca",
|
||||
|
|
|
|||
6
webview-ui/src/i18n/locales/de/settings.json
generated
6
webview-ui/src/i18n/locales/de/settings.json
generated
|
|
@ -60,6 +60,9 @@
|
|||
"vercelAiGatewayProvider": "Vercel AI Gateway",
|
||||
"vercelAiGatewayApiKeyLabel": "API-Schlüssel",
|
||||
"vercelAiGatewayApiKeyPlaceholder": "Gib deinen Vercel AI Gateway API-Schlüssel ein",
|
||||
"openRouterProvider": "OpenRouter",
|
||||
"openRouterApiKeyLabel": "OpenRouter API-Schlüssel",
|
||||
"openRouterApiKeyPlaceholder": "Gib deinen OpenRouter API-Schlüssel ein",
|
||||
"mistralProvider": "Mistral",
|
||||
"mistralApiKeyLabel": "API-Schlüssel:",
|
||||
"mistralApiKeyPlaceholder": "Gib deinen Mistral-API-Schlüssel ein",
|
||||
|
|
@ -124,7 +127,8 @@
|
|||
"vercelAiGatewayApiKeyRequired": "Vercel AI Gateway API-Schlüssel ist erforderlich",
|
||||
"ollamaBaseUrlRequired": "Ollama-Basis-URL ist erforderlich",
|
||||
"baseUrlRequired": "Basis-URL ist erforderlich",
|
||||
"modelDimensionMinValue": "Modellabmessung muss größer als 0 sein"
|
||||
"modelDimensionMinValue": "Modellabmessung muss größer als 0 sein",
|
||||
"openRouterApiKeyRequired": "OpenRouter API-Schlüssel ist erforderlich"
|
||||
},
|
||||
"advancedConfigLabel": "Erweiterte Konfiguration",
|
||||
"searchMinScoreLabel": "Suchergebnis-Schwellenwert",
|
||||
|
|
|
|||
|
|
@ -69,6 +69,9 @@
|
|||
"vercelAiGatewayProvider": "Vercel AI Gateway",
|
||||
"vercelAiGatewayApiKeyLabel": "API Key",
|
||||
"vercelAiGatewayApiKeyPlaceholder": "Enter your Vercel AI Gateway API key",
|
||||
"openRouterProvider": "OpenRouter",
|
||||
"openRouterApiKeyLabel": "OpenRouter API Key",
|
||||
"openRouterApiKeyPlaceholder": "Enter your OpenRouter API key",
|
||||
"openaiCompatibleProvider": "OpenAI Compatible",
|
||||
"openAiKeyLabel": "OpenAI API Key",
|
||||
"openAiKeyPlaceholder": "Enter your OpenAI API key",
|
||||
|
|
@ -135,6 +138,7 @@
|
|||
"geminiApiKeyRequired": "Gemini API key is required",
|
||||
"mistralApiKeyRequired": "Mistral API key is required",
|
||||
"vercelAiGatewayApiKeyRequired": "Vercel AI Gateway API key is required",
|
||||
"openRouterApiKeyRequired": "OpenRouter API key is required",
|
||||
"ollamaBaseUrlRequired": "Ollama base URL is required",
|
||||
"baseUrlRequired": "Base URL is required",
|
||||
"modelDimensionMinValue": "Model dimension must be greater than 0"
|
||||
|
|
|
|||
6
webview-ui/src/i18n/locales/es/settings.json
generated
6
webview-ui/src/i18n/locales/es/settings.json
generated
|
|
@ -60,6 +60,9 @@
|
|||
"vercelAiGatewayProvider": "Vercel AI Gateway",
|
||||
"vercelAiGatewayApiKeyLabel": "Clave API",
|
||||
"vercelAiGatewayApiKeyPlaceholder": "Introduce tu clave API de Vercel AI Gateway",
|
||||
"openRouterProvider": "OpenRouter",
|
||||
"openRouterApiKeyLabel": "Clave de API de OpenRouter",
|
||||
"openRouterApiKeyPlaceholder": "Introduce tu clave de API de OpenRouter",
|
||||
"mistralProvider": "Mistral",
|
||||
"mistralApiKeyLabel": "Clave API:",
|
||||
"mistralApiKeyPlaceholder": "Introduce tu clave de API de Mistral",
|
||||
|
|
@ -124,7 +127,8 @@
|
|||
"vercelAiGatewayApiKeyRequired": "Se requiere la clave API de Vercel AI Gateway",
|
||||
"ollamaBaseUrlRequired": "Se requiere la URL base de Ollama",
|
||||
"baseUrlRequired": "Se requiere la URL base",
|
||||
"modelDimensionMinValue": "La dimensión del modelo debe ser mayor que 0"
|
||||
"modelDimensionMinValue": "La dimensión del modelo debe ser mayor que 0",
|
||||
"openRouterApiKeyRequired": "Se requiere la clave API de OpenRouter"
|
||||
},
|
||||
"advancedConfigLabel": "Configuración avanzada",
|
||||
"searchMinScoreLabel": "Umbral de puntuación de búsqueda",
|
||||
|
|
|
|||
6
webview-ui/src/i18n/locales/fr/settings.json
generated
6
webview-ui/src/i18n/locales/fr/settings.json
generated
|
|
@ -60,6 +60,9 @@
|
|||
"vercelAiGatewayProvider": "Vercel AI Gateway",
|
||||
"vercelAiGatewayApiKeyLabel": "Clé API",
|
||||
"vercelAiGatewayApiKeyPlaceholder": "Entrez votre clé API Vercel AI Gateway",
|
||||
"openRouterProvider": "OpenRouter",
|
||||
"openRouterApiKeyLabel": "Clé d'API OpenRouter",
|
||||
"openRouterApiKeyPlaceholder": "Entrez votre clé d'API OpenRouter",
|
||||
"mistralProvider": "Mistral",
|
||||
"mistralApiKeyLabel": "Clé d'API:",
|
||||
"mistralApiKeyPlaceholder": "Entrez votre clé d'API Mistral",
|
||||
|
|
@ -124,7 +127,8 @@
|
|||
"vercelAiGatewayApiKeyRequired": "La clé API Vercel AI Gateway est requise",
|
||||
"ollamaBaseUrlRequired": "L'URL de base Ollama est requise",
|
||||
"baseUrlRequired": "L'URL de base est requise",
|
||||
"modelDimensionMinValue": "La dimension du modèle doit être supérieure à 0"
|
||||
"modelDimensionMinValue": "La dimension du modèle doit être supérieure à 0",
|
||||
"openRouterApiKeyRequired": "Clé API OpenRouter est requise"
|
||||
},
|
||||
"advancedConfigLabel": "Configuration avancée",
|
||||
"searchMinScoreLabel": "Seuil de score de recherche",
|
||||
|
|
|
|||
6
webview-ui/src/i18n/locales/hi/settings.json
generated
6
webview-ui/src/i18n/locales/hi/settings.json
generated
|
|
@ -55,6 +55,9 @@
|
|||
"vercelAiGatewayProvider": "Vercel AI Gateway",
|
||||
"vercelAiGatewayApiKeyLabel": "API कुंजी",
|
||||
"vercelAiGatewayApiKeyPlaceholder": "अपनी Vercel AI Gateway API कुंजी दर्ज करें",
|
||||
"openRouterProvider": "ओपनराउटर",
|
||||
"openRouterApiKeyLabel": "ओपनराउटर एपीआई कुंजी",
|
||||
"openRouterApiKeyPlaceholder": "अपनी ओपनराउटर एपीआई कुंजी दर्ज करें",
|
||||
"mistralProvider": "Mistral",
|
||||
"mistralApiKeyLabel": "API कुंजी:",
|
||||
"mistralApiKeyPlaceholder": "अपनी मिस्ट्रल एपीआई कुंजी दर्ज करें",
|
||||
|
|
@ -124,7 +127,8 @@
|
|||
"vercelAiGatewayApiKeyRequired": "Vercel AI Gateway API कुंजी आवश्यक है",
|
||||
"ollamaBaseUrlRequired": "Ollama आधार URL आवश्यक है",
|
||||
"baseUrlRequired": "आधार URL आवश्यक है",
|
||||
"modelDimensionMinValue": "मॉडल आयाम 0 से बड़ा होना चाहिए"
|
||||
"modelDimensionMinValue": "मॉडल आयाम 0 से बड़ा होना चाहिए",
|
||||
"openRouterApiKeyRequired": "OpenRouter API कुंजी आवश्यक है"
|
||||
},
|
||||
"advancedConfigLabel": "उन्नत कॉन्फ़िगरेशन",
|
||||
"searchMinScoreLabel": "खोज स्कोर थ्रेसहोल्ड",
|
||||
|
|
|
|||
6
webview-ui/src/i18n/locales/id/settings.json
generated
6
webview-ui/src/i18n/locales/id/settings.json
generated
|
|
@ -55,6 +55,9 @@
|
|||
"vercelAiGatewayProvider": "Vercel AI Gateway",
|
||||
"vercelAiGatewayApiKeyLabel": "API Key",
|
||||
"vercelAiGatewayApiKeyPlaceholder": "Masukkan kunci API Vercel AI Gateway Anda",
|
||||
"openRouterProvider": "OpenRouter",
|
||||
"openRouterApiKeyLabel": "Kunci API OpenRouter",
|
||||
"openRouterApiKeyPlaceholder": "Masukkan kunci API OpenRouter Anda",
|
||||
"mistralProvider": "Mistral",
|
||||
"mistralApiKeyLabel": "Kunci API:",
|
||||
"mistralApiKeyPlaceholder": "Masukkan kunci API Mistral Anda",
|
||||
|
|
@ -124,7 +127,8 @@
|
|||
"vercelAiGatewayApiKeyRequired": "Kunci API Vercel AI Gateway diperlukan",
|
||||
"ollamaBaseUrlRequired": "URL dasar Ollama diperlukan",
|
||||
"baseUrlRequired": "URL dasar diperlukan",
|
||||
"modelDimensionMinValue": "Dimensi model harus lebih besar dari 0"
|
||||
"modelDimensionMinValue": "Dimensi model harus lebih besar dari 0",
|
||||
"openRouterApiKeyRequired": "Kunci API OpenRouter diperlukan"
|
||||
},
|
||||
"advancedConfigLabel": "Konfigurasi Lanjutan",
|
||||
"searchMinScoreLabel": "Ambang Batas Skor Pencarian",
|
||||
|
|
|
|||
6
webview-ui/src/i18n/locales/it/settings.json
generated
6
webview-ui/src/i18n/locales/it/settings.json
generated
|
|
@ -55,6 +55,9 @@
|
|||
"vercelAiGatewayProvider": "Vercel AI Gateway",
|
||||
"vercelAiGatewayApiKeyLabel": "Chiave API",
|
||||
"vercelAiGatewayApiKeyPlaceholder": "Inserisci la tua chiave API Vercel AI Gateway",
|
||||
"openRouterProvider": "OpenRouter",
|
||||
"openRouterApiKeyLabel": "Chiave API OpenRouter",
|
||||
"openRouterApiKeyPlaceholder": "Inserisci la tua chiave API OpenRouter",
|
||||
"mistralProvider": "Mistral",
|
||||
"mistralApiKeyLabel": "Chiave API:",
|
||||
"mistralApiKeyPlaceholder": "Inserisci la tua chiave API Mistral",
|
||||
|
|
@ -124,7 +127,8 @@
|
|||
"vercelAiGatewayApiKeyRequired": "È richiesta la chiave API Vercel AI Gateway",
|
||||
"ollamaBaseUrlRequired": "È richiesto l'URL di base di Ollama",
|
||||
"baseUrlRequired": "È richiesto l'URL di base",
|
||||
"modelDimensionMinValue": "La dimensione del modello deve essere maggiore di 0"
|
||||
"modelDimensionMinValue": "La dimensione del modello deve essere maggiore di 0",
|
||||
"openRouterApiKeyRequired": "Chiave API OpenRouter è richiesta"
|
||||
},
|
||||
"advancedConfigLabel": "Configurazione avanzata",
|
||||
"searchMinScoreLabel": "Soglia punteggio di ricerca",
|
||||
|
|
|
|||
6
webview-ui/src/i18n/locales/ja/settings.json
generated
6
webview-ui/src/i18n/locales/ja/settings.json
generated
|
|
@ -55,6 +55,9 @@
|
|||
"vercelAiGatewayProvider": "Vercel AI Gateway",
|
||||
"vercelAiGatewayApiKeyLabel": "APIキー",
|
||||
"vercelAiGatewayApiKeyPlaceholder": "Vercel AI GatewayのAPIキーを入力してください",
|
||||
"openRouterProvider": "OpenRouter",
|
||||
"openRouterApiKeyLabel": "OpenRouter APIキー",
|
||||
"openRouterApiKeyPlaceholder": "OpenRouter APIキーを入力してください",
|
||||
"mistralProvider": "Mistral",
|
||||
"mistralApiKeyLabel": "APIキー:",
|
||||
"mistralApiKeyPlaceholder": "Mistral APIキーを入力してください",
|
||||
|
|
@ -124,7 +127,8 @@
|
|||
"vercelAiGatewayApiKeyRequired": "Vercel AI Gateway APIキーが必要です",
|
||||
"ollamaBaseUrlRequired": "OllamaのベースURLが必要です",
|
||||
"baseUrlRequired": "ベースURLが必要です",
|
||||
"modelDimensionMinValue": "モデルの次元は0より大きくなければなりません"
|
||||
"modelDimensionMinValue": "モデルの次元は0より大きくなければなりません",
|
||||
"openRouterApiKeyRequired": "OpenRouter APIキーが必要です"
|
||||
},
|
||||
"advancedConfigLabel": "詳細設定",
|
||||
"searchMinScoreLabel": "検索スコアのしきい値",
|
||||
|
|
|
|||
6
webview-ui/src/i18n/locales/ko/settings.json
generated
6
webview-ui/src/i18n/locales/ko/settings.json
generated
|
|
@ -58,6 +58,9 @@
|
|||
"vercelAiGatewayProvider": "Vercel AI Gateway",
|
||||
"vercelAiGatewayApiKeyLabel": "API 키",
|
||||
"vercelAiGatewayApiKeyPlaceholder": "Vercel AI Gateway API 키를 입력하세요",
|
||||
"openRouterProvider": "OpenRouter",
|
||||
"openRouterApiKeyLabel": "OpenRouter API 키",
|
||||
"openRouterApiKeyPlaceholder": "OpenRouter API 키를 입력하세요",
|
||||
"openaiCompatibleProvider": "OpenAI 호환",
|
||||
"openAiKeyLabel": "OpenAI API 키",
|
||||
"openAiKeyPlaceholder": "OpenAI API 키를 입력하세요",
|
||||
|
|
@ -124,7 +127,8 @@
|
|||
"vercelAiGatewayApiKeyRequired": "Vercel AI Gateway API 키가 필요합니다",
|
||||
"ollamaBaseUrlRequired": "Ollama 기본 URL이 필요합니다",
|
||||
"baseUrlRequired": "기본 URL이 필요합니다",
|
||||
"modelDimensionMinValue": "모델 차원은 0보다 커야 합니다"
|
||||
"modelDimensionMinValue": "모델 차원은 0보다 커야 합니다",
|
||||
"openRouterApiKeyRequired": "OpenRouter API 키가 필요합니다"
|
||||
},
|
||||
"advancedConfigLabel": "고급 구성",
|
||||
"searchMinScoreLabel": "검색 점수 임계값",
|
||||
|
|
|
|||
6
webview-ui/src/i18n/locales/nl/settings.json
generated
6
webview-ui/src/i18n/locales/nl/settings.json
generated
|
|
@ -55,6 +55,9 @@
|
|||
"vercelAiGatewayProvider": "Vercel AI Gateway",
|
||||
"vercelAiGatewayApiKeyLabel": "API-sleutel",
|
||||
"vercelAiGatewayApiKeyPlaceholder": "Voer uw Vercel AI Gateway API-sleutel in",
|
||||
"openRouterProvider": "OpenRouter",
|
||||
"openRouterApiKeyLabel": "OpenRouter API-sleutel",
|
||||
"openRouterApiKeyPlaceholder": "Voer uw OpenRouter API-sleutel in",
|
||||
"mistralProvider": "Mistral",
|
||||
"mistralApiKeyLabel": "API-sleutel:",
|
||||
"mistralApiKeyPlaceholder": "Voer uw Mistral API-sleutel in",
|
||||
|
|
@ -124,7 +127,8 @@
|
|||
"vercelAiGatewayApiKeyRequired": "Vercel AI Gateway API-sleutel is vereist",
|
||||
"ollamaBaseUrlRequired": "Ollama basis-URL is vereist",
|
||||
"baseUrlRequired": "Basis-URL is vereist",
|
||||
"modelDimensionMinValue": "Modelafmeting moet groter zijn dan 0"
|
||||
"modelDimensionMinValue": "Modelafmeting moet groter zijn dan 0",
|
||||
"openRouterApiKeyRequired": "OpenRouter API-sleutel is vereist"
|
||||
},
|
||||
"advancedConfigLabel": "Geavanceerde configuratie",
|
||||
"searchMinScoreLabel": "Zoekscore drempel",
|
||||
|
|
|
|||
6
webview-ui/src/i18n/locales/pl/settings.json
generated
6
webview-ui/src/i18n/locales/pl/settings.json
generated
|
|
@ -58,6 +58,9 @@
|
|||
"vercelAiGatewayProvider": "Vercel AI Gateway",
|
||||
"vercelAiGatewayApiKeyLabel": "Klucz API",
|
||||
"vercelAiGatewayApiKeyPlaceholder": "Wprowadź swój klucz API Vercel AI Gateway",
|
||||
"openRouterProvider": "OpenRouter",
|
||||
"openRouterApiKeyLabel": "Klucz API OpenRouter",
|
||||
"openRouterApiKeyPlaceholder": "Wprowadź swój klucz API OpenRouter",
|
||||
"openaiCompatibleProvider": "Kompatybilny z OpenAI",
|
||||
"openAiKeyLabel": "Klucz API OpenAI",
|
||||
"openAiKeyPlaceholder": "Wprowadź swój klucz API OpenAI",
|
||||
|
|
@ -124,7 +127,8 @@
|
|||
"vercelAiGatewayApiKeyRequired": "Klucz API Vercel AI Gateway jest wymagany",
|
||||
"ollamaBaseUrlRequired": "Wymagany jest bazowy adres URL Ollama",
|
||||
"baseUrlRequired": "Wymagany jest bazowy adres URL",
|
||||
"modelDimensionMinValue": "Wymiar modelu musi być większy niż 0"
|
||||
"modelDimensionMinValue": "Wymiar modelu musi być większy niż 0",
|
||||
"openRouterApiKeyRequired": "Wymagany jest klucz API OpenRouter"
|
||||
},
|
||||
"advancedConfigLabel": "Konfiguracja zaawansowana",
|
||||
"searchMinScoreLabel": "Próg wyniku wyszukiwania",
|
||||
|
|
|
|||
6
webview-ui/src/i18n/locales/pt-BR/settings.json
generated
6
webview-ui/src/i18n/locales/pt-BR/settings.json
generated
|
|
@ -55,6 +55,9 @@
|
|||
"vercelAiGatewayProvider": "Vercel AI Gateway",
|
||||
"vercelAiGatewayApiKeyLabel": "Chave de API",
|
||||
"vercelAiGatewayApiKeyPlaceholder": "Digite sua chave de API do Vercel AI Gateway",
|
||||
"openRouterProvider": "OpenRouter",
|
||||
"openRouterApiKeyLabel": "Chave de API do OpenRouter",
|
||||
"openRouterApiKeyPlaceholder": "Digite sua chave de API do OpenRouter",
|
||||
"mistralProvider": "Mistral",
|
||||
"mistralApiKeyLabel": "Chave de API:",
|
||||
"mistralApiKeyPlaceholder": "Digite sua chave de API da Mistral",
|
||||
|
|
@ -124,7 +127,8 @@
|
|||
"vercelAiGatewayApiKeyRequired": "A chave de API do Vercel AI Gateway é obrigatória",
|
||||
"ollamaBaseUrlRequired": "A URL base do Ollama é obrigatória",
|
||||
"baseUrlRequired": "A URL base é obrigatória",
|
||||
"modelDimensionMinValue": "A dimensão do modelo deve ser maior que 0"
|
||||
"modelDimensionMinValue": "A dimensão do modelo deve ser maior que 0",
|
||||
"openRouterApiKeyRequired": "Chave API do OpenRouter é obrigatória"
|
||||
},
|
||||
"advancedConfigLabel": "Configuração Avançada",
|
||||
"searchMinScoreLabel": "Limite de pontuação de busca",
|
||||
|
|
|
|||
6
webview-ui/src/i18n/locales/ru/settings.json
generated
6
webview-ui/src/i18n/locales/ru/settings.json
generated
|
|
@ -55,6 +55,9 @@
|
|||
"vercelAiGatewayProvider": "Vercel AI Gateway",
|
||||
"vercelAiGatewayApiKeyLabel": "Ключ API",
|
||||
"vercelAiGatewayApiKeyPlaceholder": "Введите свой API-ключ Vercel AI Gateway",
|
||||
"openRouterProvider": "OpenRouter",
|
||||
"openRouterApiKeyLabel": "Ключ API OpenRouter",
|
||||
"openRouterApiKeyPlaceholder": "Введите свой ключ API OpenRouter",
|
||||
"mistralProvider": "Mistral",
|
||||
"mistralApiKeyLabel": "Ключ API:",
|
||||
"mistralApiKeyPlaceholder": "Введите свой API-ключ Mistral",
|
||||
|
|
@ -124,7 +127,8 @@
|
|||
"vercelAiGatewayApiKeyRequired": "Требуется API-ключ Vercel AI Gateway",
|
||||
"ollamaBaseUrlRequired": "Требуется базовый URL Ollama",
|
||||
"baseUrlRequired": "Требуется базовый URL",
|
||||
"modelDimensionMinValue": "Размерность модели должна быть больше 0"
|
||||
"modelDimensionMinValue": "Размерность модели должна быть больше 0",
|
||||
"openRouterApiKeyRequired": "Требуется ключ API OpenRouter"
|
||||
},
|
||||
"advancedConfigLabel": "Расширенная конфигурация",
|
||||
"searchMinScoreLabel": "Порог оценки поиска",
|
||||
|
|
|
|||
6
webview-ui/src/i18n/locales/tr/settings.json
generated
6
webview-ui/src/i18n/locales/tr/settings.json
generated
|
|
@ -58,6 +58,9 @@
|
|||
"vercelAiGatewayProvider": "Vercel AI Gateway",
|
||||
"vercelAiGatewayApiKeyLabel": "API Anahtarı",
|
||||
"vercelAiGatewayApiKeyPlaceholder": "Vercel AI Gateway API anahtarınızı girin",
|
||||
"openRouterProvider": "OpenRouter",
|
||||
"openRouterApiKeyLabel": "OpenRouter API Anahtarı",
|
||||
"openRouterApiKeyPlaceholder": "OpenRouter API anahtarınızı girin",
|
||||
"openaiCompatibleProvider": "OpenAI Uyumlu",
|
||||
"openAiKeyLabel": "OpenAI API Anahtarı",
|
||||
"openAiKeyPlaceholder": "OpenAI API anahtarınızı girin",
|
||||
|
|
@ -124,7 +127,8 @@
|
|||
"vercelAiGatewayApiKeyRequired": "Vercel AI Gateway API anahtarı gereklidir",
|
||||
"ollamaBaseUrlRequired": "Ollama temel URL'si gereklidir",
|
||||
"baseUrlRequired": "Temel URL'si gereklidir",
|
||||
"modelDimensionMinValue": "Model boyutu 0'dan büyük olmalıdır"
|
||||
"modelDimensionMinValue": "Model boyutu 0'dan büyük olmalıdır",
|
||||
"openRouterApiKeyRequired": "OpenRouter API anahtarı gereklidir"
|
||||
},
|
||||
"advancedConfigLabel": "Gelişmiş Yapılandırma",
|
||||
"searchMinScoreLabel": "Arama Skoru Eşiği",
|
||||
|
|
|
|||
6
webview-ui/src/i18n/locales/vi/settings.json
generated
6
webview-ui/src/i18n/locales/vi/settings.json
generated
|
|
@ -58,6 +58,9 @@
|
|||
"vercelAiGatewayProvider": "Vercel AI Gateway",
|
||||
"vercelAiGatewayApiKeyLabel": "Khóa API",
|
||||
"vercelAiGatewayApiKeyPlaceholder": "Nhập khóa API Vercel AI Gateway của bạn",
|
||||
"openRouterProvider": "OpenRouter",
|
||||
"openRouterApiKeyLabel": "Khóa API OpenRouter",
|
||||
"openRouterApiKeyPlaceholder": "Nhập khóa API OpenRouter của bạn",
|
||||
"openaiCompatibleProvider": "Tương thích OpenAI",
|
||||
"openAiKeyLabel": "Khóa API OpenAI",
|
||||
"openAiKeyPlaceholder": "Nhập khóa API OpenAI của bạn",
|
||||
|
|
@ -124,7 +127,8 @@
|
|||
"vercelAiGatewayApiKeyRequired": "Cần có khóa API Vercel AI Gateway",
|
||||
"ollamaBaseUrlRequired": "Yêu cầu URL cơ sở Ollama",
|
||||
"baseUrlRequired": "Yêu cầu URL cơ sở",
|
||||
"modelDimensionMinValue": "Kích thước mô hình phải lớn hơn 0"
|
||||
"modelDimensionMinValue": "Kích thước mô hình phải lớn hơn 0",
|
||||
"openRouterApiKeyRequired": "Yêu cầu khóa API OpenRouter"
|
||||
},
|
||||
"advancedConfigLabel": "Cấu hình nâng cao",
|
||||
"searchMinScoreLabel": "Ngưỡng điểm tìm kiếm",
|
||||
|
|
|
|||
6
webview-ui/src/i18n/locales/zh-CN/settings.json
generated
6
webview-ui/src/i18n/locales/zh-CN/settings.json
generated
|
|
@ -60,6 +60,9 @@
|
|||
"vercelAiGatewayProvider": "Vercel AI Gateway",
|
||||
"vercelAiGatewayApiKeyLabel": "API 密钥",
|
||||
"vercelAiGatewayApiKeyPlaceholder": "输入您的 Vercel AI Gateway API 密钥",
|
||||
"openRouterProvider": "OpenRouter",
|
||||
"openRouterApiKeyLabel": "OpenRouter API 密钥",
|
||||
"openRouterApiKeyPlaceholder": "输入您的 OpenRouter API 密钥",
|
||||
"mistralProvider": "Mistral",
|
||||
"mistralApiKeyLabel": "API 密钥:",
|
||||
"mistralApiKeyPlaceholder": "输入您的 Mistral API 密钥",
|
||||
|
|
@ -124,7 +127,8 @@
|
|||
"vercelAiGatewayApiKeyRequired": "需要 Vercel AI Gateway API 密钥",
|
||||
"ollamaBaseUrlRequired": "需要 Ollama 基础 URL",
|
||||
"baseUrlRequired": "需要基础 URL",
|
||||
"modelDimensionMinValue": "模型维度必须大于 0"
|
||||
"modelDimensionMinValue": "模型维度必须大于 0",
|
||||
"openRouterApiKeyRequired": "OpenRouter API 密钥是必需的"
|
||||
},
|
||||
"advancedConfigLabel": "高级配置",
|
||||
"searchMinScoreLabel": "搜索分数阈值",
|
||||
|
|
|
|||
6
webview-ui/src/i18n/locales/zh-TW/settings.json
generated
6
webview-ui/src/i18n/locales/zh-TW/settings.json
generated
|
|
@ -55,6 +55,9 @@
|
|||
"vercelAiGatewayProvider": "Vercel AI Gateway",
|
||||
"vercelAiGatewayApiKeyLabel": "API 金鑰",
|
||||
"vercelAiGatewayApiKeyPlaceholder": "輸入您的 Vercel AI Gateway API 金鑰",
|
||||
"openRouterProvider": "OpenRouter",
|
||||
"openRouterApiKeyLabel": "OpenRouter API 金鑰",
|
||||
"openRouterApiKeyPlaceholder": "輸入您的 OpenRouter API 金鑰",
|
||||
"mistralProvider": "Mistral",
|
||||
"mistralApiKeyLabel": "API 金鑰：",
|
||||
"mistralApiKeyPlaceholder": "輸入您的 Mistral API 金鑰",
|
||||
|
|
@ -124,7 +127,8 @@
|
|||
"vercelAiGatewayApiKeyRequired": "需要 Vercel AI Gateway API 金鑰",
|
||||
"ollamaBaseUrlRequired": "需要 Ollama 基礎 URL",
|
||||
"baseUrlRequired": "需要基礎 URL",
|
||||
"modelDimensionMinValue": "模型維度必須大於 0"
|
||||
"modelDimensionMinValue": "模型維度必須大於 0",
|
||||
"openRouterApiKeyRequired": "OpenRouter API 密鑰是必需的"
|
||||
},
|
||||
"advancedConfigLabel": "進階設定",
|
||||
"searchMinScoreLabel": "搜尋分數閾值",
|
||||
|
|
|
|||
Loading…
Add table
Reference in a new issue