{"version":3,"file":"faux.d.ts","sourceRoot":"","sources":["../../src/providers/faux.ts"],"names":[],"mappings":"AACA,OAAO,KAAK,EACX,gBAAgB,EAEhB,OAAO,EAGP,KAAK,EAGL,aAAa,EACb,WAAW,EACX,eAAe,EACf,QAAQ,EAGR,MAAM,aAAa,CAAC;AAoBrB,MAAM,WAAW,mBAAmB;IACnC,EAAE,EAAE,MAAM,CAAC;IACX,IAAI,CAAC,EAAE,MAAM,CAAC;IACd,SAAS,CAAC,EAAE,OAAO,CAAC;IACpB,KAAK,CAAC,EAAE,CAAC,MAAM,GAAG,OAAO,CAAC,EAAE,CAAC;IAC7B,IAAI,CAAC,EAAE;QAAE,KAAK,EAAE,MAAM,CAAC;QAAC,MAAM,EAAE,MAAM,CAAC;QAAC,SAAS,EAAE,MAAM,CAAC;QAAC,UAAU,EAAE,MAAM,CAAA;KAAE,CAAC;IAChF,aAAa,CAAC,EAAE,MAAM,CAAC;IACvB,SAAS,CAAC,EAAE,MAAM,CAAC;CACnB;AAED,MAAM,MAAM,gBAAgB,GAAG,WAAW,GAAG,eAAe,GAAG,QAAQ,CAAC;AAExE,wBAAgB,QAAQ,CAAC,IAAI,EAAE,MAAM,GAAG,WAAW,CAElD;AAED,wBAAgB,YAAY,CAAC,QAAQ,EAAE,MAAM,GAAG,eAAe,CAE9D;AAED,wBAAgB,YAAY,CAAC,IAAI,EAAE,MAAM,EAAE,UAAU,EAAE,QAAQ,CAAC,WAAW,CAAC,EAAE,OAAO,GAAE;IAAE,EAAE,CAAC,EAAE,MAAM,CAAA;CAAO,GAAG,QAAQ,CAOrH;AASD,wBAAgB,oBAAoB,CACnC,OAAO,EAAE,MAAM,GAAG,gBAAgB,GAAG,gBAAgB,EAAE,EACvD,OAAO,GAAE;IACR,UAAU,CAAC,EAAE,gBAAgB,CAAC,YAAY,CAAC,CAAC;IAC5C,YAAY,CAAC,EAAE,MAAM,CAAC;IACtB,UAAU,CAAC,EAAE,MAAM,CAAC;IACpB,SAAS,CAAC,EAAE,MAAM,CAAC;CACd,GACJ,gBAAgB,CAalB;AAED,MAAM,MAAM,mBAAmB,GAAG,CACjC,OAAO,EAAE,OAAO,EAChB,OAAO,EAAE,aAAa,GAAG,SAAS,EAClC,KAAK,EAAE;IAAE,SAAS,EAAE,MAAM,CAAA;CAAE,EAC5B,KAAK,EAAE,KAAK,CAAC,MAAM,CAAC,KAChB,gBAAgB,GAAG,OAAO,CAAC,gBAAgB,CAAC,CAAC;AAElD,MAAM,MAAM,gBAAgB,GAAG,gBAAgB,GAAG,mBAAmB,CAAC;AAEtE,MAAM,WAAW,2BAA2B;IAC3C,GAAG,CAAC,EAAE,MAAM,CAAC;IACb,QAAQ,CAAC,EAAE,MAAM,CAAC;IAClB,MAAM,CAAC,EAAE,mBAAmB,EAAE,CAAC;IAC/B,eAAe,CAAC,EAAE,MAAM,CAAC;IACzB,SAAS,CAAC,EAAE;QACX,GAAG,CAAC,EAAE,MAAM,CAAC;QACb,GAAG,CAAC,EAAE,MAAM,CAAC;KACb,CAAC;CACF;AAED,MAAM,WAAW,wBAAwB;IACxC,GAAG,EAAE,MAAM,CAAC;IACZ,MAAM,EAAE,CAAC,KAAK,CAAC,MAAM,CAAC,EAAE,GAAG,KAAK,CAAC,MAAM,CAAC,EAAE,CAAC,CAAC;IAC5C,QAAQ,IAAI,KAAK,CAAC,MAAM,CAAC,CAAC;IAC1B,QAAQ,CAAC,OAAO,EAAE,MAAM,GAAG,KAAK,CAAC,MAAM,CAAC,GAAG,SAAS,CAAC;IACrD,KAAK,EAAE;QAAE,SAAS,EAAE,MAAM,CAAA;KAAE,CAAC;IAC7B,YAAY,EAAE,CAAC,SAAS,EAAE,gBAAgB,EAAE,KAAK,IAAI,CAAC;IACtD,eAAe,EAAE,CAAC,SAAS,EAAE,gBAAgB,EAAE,KAAK,IAAI,CAAC;IACzD,uBAAuB,EAAE,MAAM,MAAM,CAAC;IACtC,UAAU,EAAE,MAAM,IAAI,CAAC;CACvB;AAyQD,wBAAgB,oBAAoB,CAAC,OAAO,GAAE,2BAAgC,GAAG,wBAAwB,CA4GxG","sourcesContent":["import { registerApiProvider, unregisterApiProviders } from \"../api-registry.ts\";\nimport type {\n\tAssistantMessage,\n\tAssistantMessageEventStream,\n\tContext,\n\tImageContent,\n\tMessage,\n\tModel,\n\tSimpleStreamOptions,\n\tStreamFunction,\n\tStreamOptions,\n\tTextContent,\n\tThinkingContent,\n\tToolCall,\n\tToolResultMessage,\n\tUsage,\n} from \"../types.ts\";\nimport { createAssistantMessageEventStream } from \"../utils/event-stream.ts\";\n\nconst DEFAULT_API = \"faux\";\nconst DEFAULT_PROVIDER = \"faux\";\nconst DEFAULT_MODEL_ID = \"faux-1\";\nconst DEFAULT_MODEL_NAME = \"Faux Model\";\nconst DEFAULT_BASE_URL = \"http://localhost:0\";\nconst DEFAULT_MIN_TOKEN_SIZE = 3;\nconst DEFAULT_MAX_TOKEN_SIZE = 5;\n\nconst DEFAULT_USAGE: Usage = {\n\tinput: 0,\n\toutput: 0,\n\tcacheRead: 0,\n\tcacheWrite: 0,\n\ttotalTokens: 0,\n\tcost: { input: 0, output: 0, cacheRead: 0, cacheWrite: 0, total: 0 },\n};\n\nexport interface FauxModelDefinition {\n\tid: string;\n\tname?: string;\n\treasoning?: boolean;\n\tinput?: (\"text\" | \"image\")[];\n\tcost?: { input: number; output: number; cacheRead: number; cacheWrite: number };\n\tcontextWindow?: number;\n\tmaxTokens?: number;\n}\n\nexport type FauxContentBlock = TextContent | ThinkingContent | ToolCall;\n\nexport function fauxText(text: string): TextContent {\n\treturn { type: \"text\", text };\n}\n\nexport function fauxThinking(thinking: string): ThinkingContent {\n\treturn { type: \"thinking\", thinking };\n}\n\nexport function fauxToolCall(name: string, arguments_: ToolCall[\"arguments\"], options: { id?: string } = {}): ToolCall {\n\treturn {\n\t\ttype: \"toolCall\",\n\t\tid: options.id ?? randomId(\"tool\"),\n\t\tname,\n\t\targuments: arguments_,\n\t};\n}\n\nfunction normalizeFauxAssistantContent(content: string | FauxContentBlock | FauxContentBlock[]): FauxContentBlock[] {\n\tif (typeof content === \"string\") {\n\t\treturn [fauxText(content)];\n\t}\n\treturn Array.isArray(content) ? content : [content];\n}\n\nexport function fauxAssistantMessage(\n\tcontent: string | FauxContentBlock | FauxContentBlock[],\n\toptions: {\n\t\tstopReason?: AssistantMessage[\"stopReason\"];\n\t\terrorMessage?: string;\n\t\tresponseId?: string;\n\t\ttimestamp?: number;\n\t} = {},\n): AssistantMessage {\n\treturn {\n\t\trole: \"assistant\",\n\t\tcontent: normalizeFauxAssistantContent(content),\n\t\tapi: DEFAULT_API,\n\t\tprovider: DEFAULT_PROVIDER,\n\t\tmodel: DEFAULT_MODEL_ID,\n\t\tusage: DEFAULT_USAGE,\n\t\tstopReason: options.stopReason ?? \"stop\",\n\t\terrorMessage: options.errorMessage,\n\t\tresponseId: options.responseId,\n\t\ttimestamp: options.timestamp ?? Date.now(),\n\t};\n}\n\nexport type FauxResponseFactory = (\n\tcontext: Context,\n\toptions: StreamOptions | undefined,\n\tstate: { callCount: number },\n\tmodel: Model<string>,\n) => AssistantMessage | Promise<AssistantMessage>;\n\nexport type FauxResponseStep = AssistantMessage | FauxResponseFactory;\n\nexport interface RegisterFauxProviderOptions {\n\tapi?: string;\n\tprovider?: string;\n\tmodels?: FauxModelDefinition[];\n\ttokensPerSecond?: number;\n\ttokenSize?: {\n\t\tmin?: number;\n\t\tmax?: number;\n\t};\n}\n\nexport interface FauxProviderRegistration {\n\tapi: string;\n\tmodels: [Model<string>, ...Model<string>[]];\n\tgetModel(): Model<string>;\n\tgetModel(modelId: string): Model<string> | undefined;\n\tstate: { callCount: number };\n\tsetResponses: (responses: FauxResponseStep[]) => void;\n\tappendResponses: (responses: FauxResponseStep[]) => void;\n\tgetPendingResponseCount: () => number;\n\tunregister: () => void;\n}\n\nfunction estimateTokens(text: string): number {\n\treturn Math.ceil(text.length / 4);\n}\n\nfunction randomId(prefix: string): string {\n\treturn `${prefix}:${Date.now()}:${Math.random().toString(36).slice(2)}`;\n}\n\nfunction contentToText(content: string | Array<TextContent | ImageContent>): string {\n\tif (typeof content === \"string\") {\n\t\treturn content;\n\t}\n\treturn content\n\t\t.map((block) => {\n\t\t\tif (block.type === \"text\") {\n\t\t\t\treturn block.text;\n\t\t\t}\n\t\t\treturn `[image:${block.mimeType}:${block.data.length}]`;\n\t\t})\n\t\t.join(\"\\n\");\n}\n\nfunction assistantContentToText(content: Array<TextContent | ThinkingContent | ToolCall>): string {\n\treturn content\n\t\t.map((block) => {\n\t\t\tif (block.type === \"text\") {\n\t\t\t\treturn block.text;\n\t\t\t}\n\t\t\tif (block.type === \"thinking\") {\n\t\t\t\treturn block.thinking;\n\t\t\t}\n\t\t\treturn `${block.name}:${JSON.stringify(block.arguments)}`;\n\t\t})\n\t\t.join(\"\\n\");\n}\n\nfunction toolResultToText(message: ToolResultMessage): string {\n\treturn [message.toolName, ...message.content.map((block) => contentToText([block]))].join(\"\\n\");\n}\n\nfunction messageToText(message: Message): string {\n\tif (message.role === \"user\") {\n\t\treturn contentToText(message.content);\n\t}\n\tif (message.role === \"assistant\") {\n\t\treturn assistantContentToText(message.content);\n\t}\n\treturn toolResultToText(message);\n}\n\nfunction serializeContext(context: Context): string {\n\tconst parts: string[] = [];\n\tif (context.systemPrompt) {\n\t\tparts.push(`system:${context.systemPrompt}`);\n\t}\n\tfor (const message of context.messages) {\n\t\tparts.push(`${message.role}:${messageToText(message)}`);\n\t}\n\tif (context.tools?.length) {\n\t\tparts.push(`tools:${JSON.stringify(context.tools)}`);\n\t}\n\treturn parts.join(\"\\n\\n\");\n}\n\nfunction commonPrefixLength(a: string, b: string): number {\n\tconst length = Math.min(a.length, b.length);\n\tlet index = 0;\n\twhile (index < length && a[index] === b[index]) {\n\t\tindex++;\n\t}\n\treturn index;\n}\n\nfunction withUsageEstimate(\n\tmessage: AssistantMessage,\n\tcontext: Context,\n\toptions: StreamOptions | undefined,\n\tpromptCache: Map<string, string>,\n): AssistantMessage {\n\tconst promptText = serializeContext(context);\n\tconst promptTokens = estimateTokens(promptText);\n\tconst outputTokens = estimateTokens(assistantContentToText(message.content));\n\tlet input = promptTokens;\n\tlet cacheRead = 0;\n\tlet cacheWrite = 0;\n\tconst sessionId = options?.sessionId;\n\n\tif (sessionId && options?.cacheRetention !== \"none\") {\n\t\tconst previousPrompt = promptCache.get(sessionId);\n\t\tif (previousPrompt) {\n\t\t\tconst cachedChars = commonPrefixLength(previousPrompt, promptText);\n\t\t\tcacheRead = estimateTokens(previousPrompt.slice(0, cachedChars));\n\t\t\tcacheWrite = estimateTokens(promptText.slice(cachedChars));\n\t\t\tinput = Math.max(0, promptTokens - cacheRead);\n\t\t} else {\n\t\t\tcacheWrite = promptTokens;\n\t\t}\n\t\tpromptCache.set(sessionId, promptText);\n\t}\n\n\treturn {\n\t\t...message,\n\t\tusage: {\n\t\t\tinput,\n\t\t\toutput: outputTokens,\n\t\t\tcacheRead,\n\t\t\tcacheWrite,\n\t\t\ttotalTokens: input + outputTokens + cacheRead + cacheWrite,\n\t\t\tcost: { input: 0, output: 0, cacheRead: 0, cacheWrite: 0, total: 0 },\n\t\t},\n\t};\n}\n\nfunction splitStringByTokenSize(text: string, minTokenSize: number, maxTokenSize: number): string[] {\n\tconst chunks: string[] = [];\n\tlet index = 0;\n\twhile (index < text.length) {\n\t\tconst tokenSize = minTokenSize + Math.floor(Math.random() * (maxTokenSize - minTokenSize + 1));\n\t\tconst charSize = Math.max(1, tokenSize * 4);\n\t\tchunks.push(text.slice(index, index + charSize));\n\t\tindex += charSize;\n\t}\n\treturn chunks.length > 0 ? chunks : [\"\"];\n}\n\nfunction cloneMessage(message: AssistantMessage, api: string, provider: string, modelId: string): AssistantMessage {\n\tconst cloned = structuredClone(message);\n\treturn {\n\t\t...cloned,\n\t\tapi,\n\t\tprovider,\n\t\tmodel: modelId,\n\t\ttimestamp: cloned.timestamp ?? Date.now(),\n\t\tusage: cloned.usage ?? DEFAULT_USAGE,\n\t};\n}\n\nfunction createErrorMessage(error: unknown, api: string, provider: string, modelId: string): AssistantMessage {\n\treturn {\n\t\trole: \"assistant\",\n\t\tcontent: [],\n\t\tapi,\n\t\tprovider,\n\t\tmodel: modelId,\n\t\tusage: DEFAULT_USAGE,\n\t\tstopReason: \"error\",\n\t\terrorMessage: error instanceof Error ? error.message : String(error),\n\t\ttimestamp: Date.now(),\n\t};\n}\n\nfunction createAbortedMessage(partial: AssistantMessage): AssistantMessage {\n\treturn {\n\t\t...partial,\n\t\tstopReason: \"aborted\",\n\t\terrorMessage: \"Request was aborted\",\n\t\ttimestamp: Date.now(),\n\t};\n}\n\nfunction scheduleChunk(chunk: string, tokensPerSecond: number | undefined): Promise<void> {\n\tif (!tokensPerSecond || tokensPerSecond <= 0) {\n\t\treturn new Promise((resolve) => queueMicrotask(resolve));\n\t}\n\tconst delayMs = (estimateTokens(chunk) / tokensPerSecond) * 1000;\n\treturn new Promise((resolve) => setTimeout(resolve, delayMs));\n}\n\nasync function streamWithDeltas(\n\tstream: AssistantMessageEventStream,\n\tmessage: AssistantMessage,\n\tminTokenSize: number,\n\tmaxTokenSize: number,\n\ttokensPerSecond: number | undefined,\n\tsignal: AbortSignal | undefined,\n): Promise<void> {\n\tconst partial: AssistantMessage = { ...message, content: [] };\n\tif (signal?.aborted) {\n\t\tconst aborted = createAbortedMessage(partial);\n\t\tstream.push({ type: \"error\", reason: \"aborted\", error: aborted });\n\t\tstream.end(aborted);\n\t\treturn;\n\t}\n\n\tstream.push({ type: \"start\", partial: { ...partial } });\n\n\tfor (let index = 0; index < message.content.length; index++) {\n\t\tif (signal?.aborted) {\n\t\t\tconst aborted = createAbortedMessage(partial);\n\t\t\tstream.push({ type: \"error\", reason: \"aborted\", error: aborted });\n\t\t\tstream.end(aborted);\n\t\t\treturn;\n\t\t}\n\n\t\tconst block = message.content[index];\n\n\t\tif (block.type === \"thinking\") {\n\t\t\tpartial.content = [...partial.content, { type: \"thinking\", thinking: \"\" }];\n\t\t\tstream.push({ type: \"thinking_start\", contentIndex: index, partial: { ...partial } });\n\t\t\tfor (const chunk of splitStringByTokenSize(block.thinking, minTokenSize, maxTokenSize)) {\n\t\t\t\tawait scheduleChunk(chunk, tokensPerSecond);\n\t\t\t\tif (signal?.aborted) {\n\t\t\t\t\tconst aborted = createAbortedMessage(partial);\n\t\t\t\t\tstream.push({ type: \"error\", reason: \"aborted\", error: aborted });\n\t\t\t\t\tstream.end(aborted);\n\t\t\t\t\treturn;\n\t\t\t\t}\n\t\t\t\t(partial.content[index] as ThinkingContent).thinking += chunk;\n\t\t\t\tstream.push({ type: \"thinking_delta\", contentIndex: index, delta: chunk, partial: { ...partial } });\n\t\t\t}\n\t\t\tstream.push({\n\t\t\t\ttype: \"thinking_end\",\n\t\t\t\tcontentIndex: index,\n\t\t\t\tcontent: block.thinking,\n\t\t\t\tpartial: { ...partial },\n\t\t\t});\n\t\t\tcontinue;\n\t\t}\n\n\t\tif (block.type === \"text\") {\n\t\t\tpartial.content = [...partial.content, { type: \"text\", text: \"\" }];\n\t\t\tstream.push({ type: \"text_start\", contentIndex: index, partial: { ...partial } });\n\t\t\tfor (const chunk of splitStringByTokenSize(block.text, minTokenSize, maxTokenSize)) {\n\t\t\t\tawait scheduleChunk(chunk, tokensPerSecond);\n\t\t\t\tif (signal?.aborted) {\n\t\t\t\t\tconst aborted = createAbortedMessage(partial);\n\t\t\t\t\tstream.push({ type: \"error\", reason: \"aborted\", error: aborted });\n\t\t\t\t\tstream.end(aborted);\n\t\t\t\t\treturn;\n\t\t\t\t}\n\t\t\t\t(partial.content[index] as TextContent).text += chunk;\n\t\t\t\tstream.push({ type: \"text_delta\", contentIndex: index, delta: chunk, partial: { ...partial } });\n\t\t\t}\n\t\t\tstream.push({ type: \"text_end\", contentIndex: index, content: block.text, partial: { ...partial } });\n\t\t\tcontinue;\n\t\t}\n\n\t\tpartial.content = [...partial.content, { type: \"toolCall\", id: block.id, name: block.name, arguments: {} }];\n\t\tstream.push({ type: \"toolcall_start\", contentIndex: index, partial: { ...partial } });\n\t\tfor (const chunk of splitStringByTokenSize(JSON.stringify(block.arguments), minTokenSize, maxTokenSize)) {\n\t\t\tawait scheduleChunk(chunk, tokensPerSecond);\n\t\t\tif (signal?.aborted) {\n\t\t\t\tconst aborted = createAbortedMessage(partial);\n\t\t\t\tstream.push({ type: \"error\", reason: \"aborted\", error: aborted });\n\t\t\t\tstream.end(aborted);\n\t\t\t\treturn;\n\t\t\t}\n\t\t\tstream.push({ type: \"toolcall_delta\", contentIndex: index, delta: chunk, partial: { ...partial } });\n\t\t}\n\t\t(partial.content[index] as ToolCall).arguments = block.arguments;\n\t\tstream.push({ type: \"toolcall_end\", contentIndex: index, toolCall: block, partial: { ...partial } });\n\t}\n\n\tif (message.stopReason === \"error\" || message.stopReason === \"aborted\") {\n\t\tstream.push({ type: \"error\", reason: message.stopReason, error: message });\n\t\tstream.end(message);\n\t\treturn;\n\t}\n\n\tstream.push({ type: \"done\", reason: message.stopReason, message });\n\tstream.end(message);\n}\n\nexport function registerFauxProvider(options: RegisterFauxProviderOptions = {}): FauxProviderRegistration {\n\tconst api = options.api ?? randomId(DEFAULT_API);\n\tconst provider = options.provider ?? DEFAULT_PROVIDER;\n\tconst sourceId = randomId(\"faux-provider\");\n\tconst minTokenSize = Math.max(\n\t\t1,\n\t\tMath.min(options.tokenSize?.min ?? DEFAULT_MIN_TOKEN_SIZE, options.tokenSize?.max ?? DEFAULT_MAX_TOKEN_SIZE),\n\t);\n\tconst maxTokenSize = Math.max(minTokenSize, options.tokenSize?.max ?? DEFAULT_MAX_TOKEN_SIZE);\n\tlet pendingResponses: FauxResponseStep[] = [];\n\tconst tokensPerSecond = options.tokensPerSecond;\n\tconst state = { callCount: 0 };\n\tconst promptCache = new Map<string, string>();\n\n\tconst modelDefinitions = options.models?.length\n\t\t? options.models\n\t\t: [\n\t\t\t\t{\n\t\t\t\t\tid: DEFAULT_MODEL_ID,\n\t\t\t\t\tname: DEFAULT_MODEL_NAME,\n\t\t\t\t\treasoning: false,\n\t\t\t\t\tinput: [\"text\", \"image\"] as (\"text\" | \"image\")[],\n\t\t\t\t\tcost: { input: 0, output: 0, cacheRead: 0, cacheWrite: 0 },\n\t\t\t\t\tcontextWindow: 128000,\n\t\t\t\t\tmaxTokens: 16384,\n\t\t\t\t},\n\t\t\t];\n\tconst models = modelDefinitions.map((definition) => ({\n\t\tid: definition.id,\n\t\tname: definition.name ?? definition.id,\n\t\tapi,\n\t\tprovider,\n\t\tbaseUrl: DEFAULT_BASE_URL,\n\t\treasoning: definition.reasoning ?? false,\n\t\tinput: definition.input ?? [\"text\", \"image\"],\n\t\tcost: definition.cost ?? { input: 0, output: 0, cacheRead: 0, cacheWrite: 0 },\n\t\tcontextWindow: definition.contextWindow ?? 128000,\n\t\tmaxTokens: definition.maxTokens ?? 16384,\n\t})) as [Model<string>, ...Model<string>[]];\n\n\tconst stream: StreamFunction<string, StreamOptions> = (requestModel, context, streamOptions) => {\n\t\tconst outer = createAssistantMessageEventStream();\n\t\tconst step = pendingResponses.shift();\n\t\tstate.callCount++;\n\n\t\tqueueMicrotask(async () => {\n\t\t\ttry {\n\t\t\t\tawait streamOptions?.onResponse?.({ status: 200, headers: {} }, requestModel);\n\t\t\t\tif (!step) {\n\t\t\t\t\tlet message = createErrorMessage(\n\t\t\t\t\t\tnew Error(\"No more faux responses queued\"),\n\t\t\t\t\t\tapi,\n\t\t\t\t\t\tprovider,\n\t\t\t\t\t\trequestModel.id,\n\t\t\t\t\t);\n\t\t\t\t\tmessage = withUsageEstimate(message, context, streamOptions, promptCache);\n\t\t\t\t\touter.push({ type: \"error\", reason: \"error\", error: message });\n\t\t\t\t\touter.end(message);\n\t\t\t\t\treturn;\n\t\t\t\t}\n\n\t\t\t\tconst resolved =\n\t\t\t\t\ttypeof step === \"function\" ? await step(context, streamOptions, state, requestModel) : step;\n\t\t\t\tlet message = cloneMessage(resolved, api, provider, requestModel.id);\n\t\t\t\tmessage = withUsageEstimate(message, context, streamOptions, promptCache);\n\t\t\t\tawait streamWithDeltas(outer, message, minTokenSize, maxTokenSize, tokensPerSecond, streamOptions?.signal);\n\t\t\t} catch (error) {\n\t\t\t\tconst message = createErrorMessage(error, api, provider, requestModel.id);\n\t\t\t\touter.push({ type: \"error\", reason: \"error\", error: message });\n\t\t\t\touter.end(message);\n\t\t\t}\n\t\t});\n\n\t\treturn outer;\n\t};\n\n\tconst streamSimple: StreamFunction<string, SimpleStreamOptions> = (streamModel, context, streamOptions) =>\n\t\tstream(streamModel, context, streamOptions);\n\n\tregisterApiProvider({ api, stream, streamSimple }, sourceId);\n\n\tfunction getModel(): Model<string>;\n\tfunction getModel(requestedModelId: string): Model<string> | undefined;\n\tfunction getModel(requestedModelId?: string): Model<string> | undefined {\n\t\tif (!requestedModelId) {\n\t\t\treturn models[0];\n\t\t}\n\t\treturn models.find((candidate) => candidate.id === requestedModelId);\n\t}\n\n\treturn {\n\t\tapi,\n\t\tmodels,\n\t\tgetModel,\n\t\tstate,\n\t\tsetResponses(responses) {\n\t\t\tpendingResponses = [...responses];\n\t\t},\n\t\tappendResponses(responses) {\n\t\t\tpendingResponses.push(...responses);\n\t\t},\n\t\tgetPendingResponseCount() {\n\t\t\treturn pendingResponses.length;\n\t\t},\n\t\tunregister() {\n\t\t\tunregisterApiProviders(sourceId);\n\t\t},\n\t};\n}\n"]}