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vantedge-ai-sdk

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VantEdge AI SDK provider for AI SDK

github.com/8vdx1/vantedge-ai-sdk

8vdx1/vantedge-ai-sdk

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You can use it as a middleware to intercept requests,\nor to provide a custom fetch implementation for e.g. testing.\n*/\n fetch?: FetchFunction;\n}\n\nexport interface VantEdgeAIProvider {\n /**\nCreates a model for text generation.\n*/\n (\n modelId: VantEdgeAIChatModelId,\n settings?: VantEdgeAIChatSettings,\n ): LanguageModelV1;\n\n /**\nCreates a chat model for text generation.\n*/\n chatModel(\n modelId: VantEdgeAIChatModelId,\n settings?: VantEdgeAIChatSettings,\n ): LanguageModelV1;\n\n /**\nCreates a completion model for text generation.\n*/\n completionModel(\n modelId: VantEdgeAICompletionModelId,\n settings?: VantEdgeAICompletionSettings,\n ): LanguageModelV1;\n\n /**\nCreates a text embedding model for text generation.\n*/\n textEmbeddingModel(\n modelId: VantEdgeAIEmbeddingModelId,\n settings?: VantEdgeAIEmbeddingSettings,\n ): EmbeddingModelV1<string>;\n\n /**\nCreates an image model for image generation.\n*/\n imageModel(\n modelId: VantEdgeAIImageModelId,\n settings?: VantEdgeAIImageSettings,\n ): ImageModelV1;\n}\n\n// Global threadId context\nlet globalThreadId: string | null = null;\n\nexport function setGlobalThreadId(threadId: string) {\n globalThreadId = threadId;\n}\n\nexport function createVantEdgeAI(\n options: VantEdgeAIProviderSettings = {},\n): VantEdgeAIProvider {\n const baseURL = withoutTrailingSlash(\n options.baseURL ?? `${process.env.NEXT_PUBLIC_API_URL}`,\n );\n const getHeaders = () => ({\n Authorization: `Bearer ${loadApiKey({\n apiKey: options.apiKey ?? '1234567890',\n environmentVariableName: 'VANTEDGEAI_API_KEY',\n description: 'VantEdgeAI API key',\n })}`,\n ...options.headers,\n });\n\n interface CommonModelConfig {\n provider: string;\n url: ({ path }: { path: string }) => string;\n headers: () => Record<string, string>;\n fetch?: FetchFunction;\n }\n\n const getCommonModelConfig = (modelType: string): CommonModelConfig => ({\n provider: `vantedgeai.${modelType}`,\n url: ({ path }) => {\n const url = new URL(`${baseURL}${path}`);\n if (options.queryParams) {\n url.search = new URLSearchParams(options.queryParams).toString();\n }\n return url.toString();\n },\n headers: getHeaders,\n fetch: options.fetch,\n });\n\n const createChatModel = (\n modelId: VantEdgeAIChatModelId,\n settings: VantEdgeAIChatSettings = {},\n ) => {\n // Create a custom fetch function that adds threadId to the request body\n const customFetch: FetchFunction = async (url, options) => {\n if (options?.body && (settings.threadId || globalThreadId)) {\n try {\n const body = JSON.parse(options.body as string);\n body.threadId = settings.threadId || globalThreadId;\n options.body = JSON.stringify(body);\n } catch (error) {\n console.warn(\n 'Failed to parse request body for threadId injection:',\n error,\n );\n }\n }\n\n // Use the original fetch function\n return globalThis.fetch(url, options);\n };\n\n return new OpenAICompatibleChatLanguageModel(modelId, settings, {\n ...getCommonModelConfig('chat'),\n defaultObjectGenerationMode: 'tool',\n fetch: customFetch,\n });\n };\n\n const createCompletionModel = (\n modelId: VantEdgeAICompletionModelId,\n settings: VantEdgeAICompletionSettings = {},\n ) =>\n new OpenAICompatibleCompletionLanguageModel(\n modelId,\n settings,\n getCommonModelConfig('completion'),\n );\n\n const createTextEmbeddingModel = (\n modelId: VantEdgeAIEmbeddingModelId,\n settings: VantEdgeAIEmbeddingSettings = {},\n ) =>\n new OpenAICompatibleEmbeddingModel(\n modelId,\n settings,\n getCommonModelConfig('embedding'),\n );\n\n const createImageModel = (\n modelId: VantEdgeAIImageModelId,\n settings: VantEdgeAIImageSettings = {},\n ) =>\n new OpenAICompatibleImageModel(\n modelId,\n settings,\n getCommonModelConfig('image'),\n );\n\n const provider = (\n modelId: VantEdgeAIChatModelId,\n settings?: VantEdgeAIChatSettings,\n ) => createChatModel(modelId, settings);\n\n provider.completionModel = createCompletionModel;\n provider.chatModel = createChatModel;\n provider.textEmbeddingModel = createTextEmbeddingModel;\n provider.imageModel = createImageModel;\n\n return provider;\n}\n\n// Export default instance\nexport const vantedgeai = createVantEdgeAI();\n"]}