{"version":3,"file":"openrouter.d.ts","sourceRoot":"","sources":["../../../src/providers/images/openrouter.ts"],"names":[],"mappings":"AAQA,OAAO,KAAK,EAIX,cAAc,EAEd,aAAa,EAEb,MAAM,gBAAgB,CAAC;AAoBxB,eAAO,MAAM,wBAAwB,EAAE,cAAc,CAAC,mBAAmB,EAAE,aAAa,CAmEvF,CAAC","sourcesContent":["import OpenAI from \"openai\";\nimport type {\n\tChatCompletion,\n\tChatCompletionContentPart,\n\tChatCompletionContentPartImage,\n\tChatCompletionContentPartText,\n\tChatCompletionCreateParamsNonStreaming,\n} from \"openai/resources/chat/completions.js\";\nimport type {\n\tAssistantImages,\n\tImageContent,\n\tImagesContext,\n\tImagesFunction,\n\tImagesModel,\n\tImagesOptions,\n\tTextContent,\n} from \"../../types.ts\";\nimport { headersToRecord } from \"../../utils/headers.ts\";\nimport { sanitizeSurrogates } from \"../../utils/sanitize-unicode.ts\";\n\ninterface OpenRouterGeneratedImage {\n\timage_url?: string | { url?: string };\n}\n\ntype OpenRouterImageGenerationMessage = ChatCompletion[\"choices\"][number][\"message\"] & {\n\timages?: OpenRouterGeneratedImage[];\n};\n\ntype OpenRouterImageGenerationChoice = ChatCompletion[\"choices\"][number] & {\n\tmessage: OpenRouterImageGenerationMessage;\n};\n\ntype OpenRouterImageGenerationResponse = ChatCompletion & {\n\tchoices: OpenRouterImageGenerationChoice[];\n};\n\nexport const generateImagesOpenRouter: ImagesFunction<\"openrouter-images\", ImagesOptions> = async (\n\tmodel: ImagesModel<\"openrouter-images\">,\n\tcontext: ImagesContext,\n\toptions?: ImagesOptions,\n) => {\n\tconst output: AssistantImages = {\n\t\tapi: model.api,\n\t\tprovider: model.provider,\n\t\tmodel: model.id,\n\t\toutput: [],\n\t\tstopReason: \"stop\",\n\t\ttimestamp: Date.now(),\n\t};\n\n\ttry {\n\t\tconst apiKey = options?.apiKey;\n\t\tif (!apiKey) {\n\t\t\tthrow new Error(`No API key for provider: ${model.provider}`);\n\t\t}\n\t\tconst client = createClient(model, apiKey, options?.headers);\n\t\tlet params = buildParams(model, context);\n\t\tconst nextParams = await options?.onPayload?.(params, model);\n\t\tif (nextParams !== undefined) {\n\t\t\tparams = nextParams as typeof params;\n\t\t}\n\t\tconst requestOptions = {\n\t\t\t...(options?.signal ? { signal: options.signal } : {}),\n\t\t\t...(options?.timeoutMs !== undefined ? { timeout: options.timeoutMs } : {}),\n\t\t\tmaxRetries: options?.maxRetries ?? 0,\n\t\t};\n\t\tconst { data: response, response: rawResponse } = await client.chat.completions\n\t\t\t.create(params as unknown as ChatCompletionCreateParamsNonStreaming, requestOptions)\n\t\t\t.withResponse();\n\t\tawait options?.onResponse?.({ status: rawResponse.status, headers: headersToRecord(rawResponse.headers) }, model);\n\n\t\tconst imageResponse = response as OpenRouterImageGenerationResponse;\n\t\toutput.responseId = imageResponse.id;\n\t\tif (imageResponse.usage) {\n\t\t\toutput.usage = parseUsage(imageResponse.usage, model);\n\t\t}\n\n\t\tconst choice = imageResponse.choices[0];\n\t\tif (choice) {\n\t\t\tconst content = choice.message.content;\n\t\t\tif (typeof content === \"string\" && content.length > 0) {\n\t\t\t\toutput.output.push({ type: \"text\", text: content } satisfies TextContent);\n\t\t\t}\n\n\t\t\tfor (const image of choice.message.images ?? []) {\n\t\t\t\tconst imageUrl = typeof image.image_url === \"string\" ? image.image_url : image.image_url?.url;\n\t\t\t\tif (!imageUrl?.startsWith(\"data:\")) continue;\n\t\t\t\tconst matches = imageUrl.match(/^data:([^;]+);base64,(.+)$/);\n\t\t\t\tif (!matches) continue;\n\t\t\t\toutput.output.push({\n\t\t\t\t\ttype: \"image\",\n\t\t\t\t\tmimeType: matches[1],\n\t\t\t\t\tdata: matches[2],\n\t\t\t\t} satisfies ImageContent);\n\t\t\t}\n\t\t}\n\n\t\treturn output;\n\t} catch (error) {\n\t\toutput.stopReason = options?.signal?.aborted ? \"aborted\" : \"error\";\n\t\toutput.errorMessage = error instanceof Error ? error.message : JSON.stringify(error);\n\t\treturn output;\n\t}\n};\n\nfunction createClient(\n\tmodel: ImagesModel<\"openrouter-images\">,\n\tapiKey: string,\n\toptionsHeaders?: Record<string, string>,\n): OpenAI {\n\treturn new OpenAI({\n\t\tapiKey,\n\t\tbaseURL: model.baseUrl,\n\t\tdangerouslyAllowBrowser: true,\n\t\tdefaultHeaders: {\n\t\t\t...model.headers,\n\t\t\t...optionsHeaders,\n\t\t},\n\t});\n}\n\ntype OpenRouterImagesCreateParams = Omit<ChatCompletionCreateParamsNonStreaming, \"modalities\"> & {\n\tmodalities: Array<\"image\" | \"text\">;\n};\n\nfunction buildParams(model: ImagesModel<\"openrouter-images\">, context: ImagesContext): OpenRouterImagesCreateParams {\n\tconst content: ChatCompletionContentPart[] = context.input.map((item): ChatCompletionContentPart => {\n\t\tif (item.type === \"text\") {\n\t\t\treturn {\n\t\t\t\ttype: \"text\",\n\t\t\t\ttext: sanitizeSurrogates(item.text),\n\t\t\t} satisfies ChatCompletionContentPartText;\n\t\t}\n\t\treturn {\n\t\t\ttype: \"image_url\",\n\t\t\timage_url: {\n\t\t\t\turl: `data:${item.mimeType};base64,${item.data}`,\n\t\t\t},\n\t\t} satisfies ChatCompletionContentPartImage;\n\t});\n\n\treturn {\n\t\tmodel: model.id,\n\t\tmessages: [\n\t\t\t{\n\t\t\t\trole: \"user\" as const,\n\t\t\t\tcontent,\n\t\t\t},\n\t\t],\n\t\tstream: false,\n\t\tmodalities: model.output.includes(\"text\") ? [\"image\", \"text\"] : [\"image\"],\n\t};\n}\n\nfunction parseUsage(\n\trawUsage: {\n\t\tprompt_tokens?: number;\n\t\tcompletion_tokens?: number;\n\t\tprompt_tokens_details?: { cached_tokens?: number; cache_write_tokens?: number };\n\t},\n\tmodel: ImagesModel<\"openrouter-images\">,\n) {\n\tconst promptTokens = rawUsage.prompt_tokens || 0;\n\tconst reportedCachedTokens = rawUsage.prompt_tokens_details?.cached_tokens || 0;\n\tconst cacheWriteTokens = rawUsage.prompt_tokens_details?.cache_write_tokens || 0;\n\tconst cacheReadTokens =\n\t\tcacheWriteTokens > 0 ? Math.max(0, reportedCachedTokens - cacheWriteTokens) : reportedCachedTokens;\n\tconst input = Math.max(0, promptTokens - cacheReadTokens - cacheWriteTokens);\n\tconst output = rawUsage.completion_tokens || 0;\n\tconst usage = {\n\t\tinput,\n\t\toutput,\n\t\tcacheRead: cacheReadTokens,\n\t\tcacheWrite: cacheWriteTokens,\n\t\ttotalTokens: input + output + cacheReadTokens + cacheWriteTokens,\n\t\tcost: {\n\t\t\tinput: (model.cost.input / 1000000) * input,\n\t\t\toutput: (model.cost.output / 1000000) * output,\n\t\t\tcacheRead: (model.cost.cacheRead / 1000000) * cacheReadTokens,\n\t\t\tcacheWrite: (model.cost.cacheWrite / 1000000) * cacheWriteTokens,\n\t\t\ttotal: 0,\n\t\t},\n\t};\n\tusage.cost.total = usage.cost.input + usage.cost.output + usage.cost.cacheRead + usage.cost.cacheWrite;\n\treturn usage;\n}\n"]}