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Third-party integrations for LangChain.js
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{"version":3,"file":"alibaba_tongyi.cjs","names":["message: ChatMessage","message: BaseMessage","ChatMessage","BaseChatModel","fields: Partial<AlibabaTongyiChatInput> & BaseChatModelParams","parameters: ChatCompletionRequest[\"parameters\"]","messages: BaseMessage[]","options?: this[\"ParsedCallOptions\"]","runManager?: CallbackManagerForLLMRun","messagesMapped: TongyiMessage[]","response: ChatCompletionResponse","data: ChatCompletionResponse","data","text","AIMessage","request: ChatCompletionRequest","stream: boolean","signal?: AbortSignal","onmessage?: (event: MessageEvent) => void","ChatGenerationChunk","AIMessageChunk","IterableReadableStream"],"sources":["../../src/chat_models/alibaba_tongyi.ts"],"sourcesContent":["import { type CallbackManagerForLLMRun } from \"@langchain/core/callbacks/manager\";\nimport {\n BaseChatModel,\n type BaseChatModelParams,\n} from \"@langchain/core/language_models/chat_models\";\nimport {\n AIMessage,\n type BaseMessage,\n ChatMessage,\n AIMessageChunk,\n} from \"@langchain/core/messages\";\nimport { type ChatResult } from \"@langchain/core/outputs\";\nimport { ChatGenerationChunk } from \"@langchain/core/outputs\";\nimport { getEnvironmentVariable } from \"@langchain/core/utils/env\";\nimport { IterableReadableStream } from \"@langchain/core/utils/stream\";\n\n/**\n * Type representing the role of a message in the Tongyi chat model.\n */\nexport type TongyiMessageRole = \"system\" | \"assistant\" | \"user\";\n\n/**\n * Interface representing a message in the Tongyi chat model.\n */\ninterface TongyiMessage {\n role: TongyiMessageRole;\n content: string;\n}\n\n/**\n * Interface representing a request for a chat completion.\n *\n * See https://help.aliyun.com/zh/dashscope/developer-reference/model-square/\n */\ninterface ChatCompletionRequest {\n model:\n | (string & NonNullable<unknown>)\n | \"qwen-turbo\"\n | \"qwen-plus\"\n | \"qwen-max\"\n | \"qwen-max-1201\"\n | \"qwen-max-longcontext\"\n // 通义千问开源系列\n | \"qwen-7b-chat\"\n | \"qwen-14b-chat\"\n | \"qwen-72b-chat\"\n // LLAMA2\n | \"llama2-7b-chat-v2\"\n | \"llama2-13b-chat-v2\"\n // 百川\n | \"baichuan-7b-v1\"\n | \"baichuan2-13b-chat-v1\"\n | \"baichuan2-7b-chat-v1\"\n // ChatGLM\n | \"chatglm3-6b\"\n | \"chatglm-6b-v2\";\n input: {\n messages: TongyiMessage[];\n };\n parameters: {\n stream?: boolean;\n result_format?: \"text\" | \"message\";\n seed?: number | null;\n max_tokens?: number | null;\n top_p?: number | null;\n top_k?: number | null;\n repetition_penalty?: number | null;\n temperature?: number | null;\n enable_search?: boolean | null;\n incremental_output?: boolean | null;\n };\n}\n\n/**\n * Interface representing a response from a chat completion.\n */\ninterface ChatCompletionResponse {\n code?: string;\n message?: string;\n request_id: string;\n usage: {\n output_tokens: number;\n input_tokens: number;\n total_tokens: number;\n };\n output: {\n text: string;\n finish_reason: \"stop\" | \"length\" | \"null\" | null;\n };\n}\n\n/**\n * Interface defining the input to the ChatAlibabaTongyi class.\n */\ninterface AlibabaTongyiChatInput {\n /**\n * Model name to use. Available options are: qwen-turbo, qwen-plus, qwen-max, or Other compatible models.\n * Alias for `model`\n * @default \"qwen-turbo\"\n */\n modelName: string;\n\n /** Model name to use. Available options are: qwen-turbo, qwen-plus, qwen-max, or Other compatible models.\n * @default \"qwen-turbo\"\n */\n model: string;\n\n /** Whether to stream the results or not. Defaults to false. */\n streaming?: boolean;\n\n /** Messages to pass as a prefix to the prompt */\n prefixMessages?: TongyiMessage[];\n\n /**\n * API key to use when making requests. Defaults to the value of\n * `ALIBABA_API_KEY` environment variable.\n */\n alibabaApiKey?: string;\n\n /** Amount of randomness injected into the response. Ranges\n * from 0 to 1 (0 is not included). Use temp closer to 0 for analytical /\n * multiple choice, and temp closer to 1 for creative\n * and generative tasks. Defaults to 0.95.\n */\n temperature?: number;\n\n /** Total probability mass of tokens to consider at each step. Range\n * from 0 to 1.0. Defaults to 0.8.\n */\n topP?: number;\n\n topK?: number;\n\n enableSearch?: boolean;\n\n maxTokens?: number;\n\n seed?: number;\n\n /** Penalizes repeated tokens according to frequency. Range\n * from 1.0 to 2.0. Defaults to 1.0.\n */\n repetitionPenalty?: number;\n}\n\n/**\n * Function that extracts the custom role of a generic chat message.\n * @param message Chat message from which to extract the custom role.\n * @returns The custom role of the chat message.\n */\nfunction extractGenericMessageCustomRole(message: ChatMessage) {\n if ([\"system\", \"assistant\", \"user\"].includes(message.role) === false) {\n console.warn(`Unknown message role: ${message.role}`);\n }\n\n return message.role as TongyiMessageRole;\n}\n\n/**\n * Function that converts a base message to a Tongyi message role.\n * @param message Base message to convert.\n * @returns The Tongyi message role.\n */\nfunction messageToTongyiRole(message: BaseMessage): TongyiMessageRole {\n const type = message._getType();\n switch (type) {\n case \"ai\":\n return \"assistant\";\n case \"human\":\n return \"user\";\n case \"system\":\n return \"system\";\n case \"function\":\n throw new Error(\"Function messages not supported\");\n case \"generic\": {\n if (!ChatMessage.isInstance(message))\n throw new Error(\"Invalid generic chat message\");\n return extractGenericMessageCustomRole(message);\n }\n default:\n throw new Error(`Unknown message type: ${type}`);\n }\n}\n\n/**\n * Wrapper around Ali Tongyi large language models that use the Chat endpoint.\n *\n * To use you should have the `ALIBABA_API_KEY`\n * environment variable set.\n *\n * @augments BaseLLM\n * @augments AlibabaTongyiInput\n * @example\n * ```typescript\n * const qwen = new ChatAlibabaTongyi({\n * alibabaApiKey: \"YOUR-API-KEY\",\n * });\n *\n * const qwen = new ChatAlibabaTongyi({\n * model: \"qwen-turbo\",\n * temperature: 1,\n * alibabaApiKey: \"YOUR-API-KEY\",\n * });\n *\n * const messages = [new HumanMessage(\"Hello\")];\n *\n * await qwen.call(messages);\n * ```\n */\nexport class ChatAlibabaTongyi\n extends BaseChatModel\n implements AlibabaTongyiChatInput\n{\n static lc_name() {\n return \"ChatAlibabaTongyi\";\n }\n\n get callKeys() {\n return [\"stop\", \"signal\", \"options\"];\n }\n\n get lc_secrets() {\n return {\n alibabaApiKey: \"ALIBABA_API_KEY\",\n };\n }\n\n get lc_aliases() {\n return undefined;\n }\n\n lc_serializable: boolean;\n\n alibabaApiKey?: string;\n\n streaming: boolean;\n\n prefixMessages?: TongyiMessage[];\n\n modelName: ChatCompletionRequest[\"model\"];\n\n model: ChatCompletionRequest[\"model\"];\n\n apiUrl: string;\n\n maxTokens?: number | undefined;\n\n temperature?: number | undefined;\n\n topP?: number | undefined;\n\n topK?: number | undefined;\n\n repetitionPenalty?: number | undefined;\n\n seed?: number | undefined;\n\n enableSearch?: boolean | undefined;\n\n constructor(\n fields: Partial<AlibabaTongyiChatInput> & BaseChatModelParams = {}\n ) {\n super(fields);\n\n this.alibabaApiKey =\n fields?.alibabaApiKey ?? getEnvironmentVariable(\"ALIBABA_API_KEY\");\n if (!this.alibabaApiKey) {\n throw new Error(\"Ali API key not found\");\n }\n\n this.apiUrl =\n \"https://dashscope.aliyuncs.com/api/v1/services/aigc/text-generation/generation\";\n this.lc_serializable = true;\n this.streaming = fields.streaming ?? false;\n this.prefixMessages = fields.prefixMessages ?? [];\n this.temperature = fields.temperature;\n this.topP = fields.topP;\n this.topK = fields.topK;\n this.seed = fields.seed;\n this.maxTokens = fields.maxTokens;\n this.repetitionPenalty = fields.repetitionPenalty;\n this.enableSearch = fields.enableSearch;\n this.modelName = fields?.model ?? fields.modelName ?? \"qwen-turbo\";\n this.model = this.modelName;\n }\n\n /**\n * Get the parameters used to invoke the model\n */\n invocationParams(): ChatCompletionRequest[\"parameters\"] {\n const parameters: ChatCompletionRequest[\"parameters\"] = {\n stream: this.streaming,\n temperature: this.temperature,\n top_p: this.topP,\n top_k: this.topK,\n seed: this.seed,\n max_tokens: this.maxTokens,\n result_format: \"text\",\n enable_search: this.enableSearch,\n };\n\n if (this.streaming) {\n parameters.incremental_output = true;\n } else {\n parameters.repetition_penalty = this.repetitionPenalty;\n }\n\n return parameters;\n }\n\n /**\n * Get the identifying parameters for the model\n */\n identifyingParams(): ChatCompletionRequest[\"parameters\"] &\n Pick<ChatCompletionRequest, \"model\"> {\n return {\n model: this.model,\n ...this.invocationParams(),\n };\n }\n\n /** @ignore */\n async _generate(\n messages: BaseMessage[],\n options?: this[\"ParsedCallOptions\"],\n runManager?: CallbackManagerForLLMRun\n ): Promise<ChatResult> {\n const parameters = this.invocationParams();\n\n const messagesMapped: TongyiMessage[] = messages.map((message) => ({\n role: messageToTongyiRole(message),\n content: message.content as string,\n }));\n\n const data = parameters.stream\n ? await new Promise<ChatCompletionResponse>((resolve, reject) => {\n let response: ChatCompletionResponse;\n let rejected = false;\n let resolved = false;\n this.completionWithRetry(\n {\n model: this.model,\n parameters,\n input: {\n messages: messagesMapped,\n },\n },\n true,\n options?.signal,\n (event) => {\n const data: ChatCompletionResponse = JSON.parse(event.data);\n if (data?.code) {\n if (rejected) {\n return;\n }\n rejected = true;\n reject(new Error(data?.message));\n return;\n }\n\n const { text, finish_reason } = data.output;\n\n if (!response) {\n response = data;\n } else {\n response.output.text += text;\n response.output.finish_reason = finish_reason;\n response.usage = data.usage;\n }\n\n // eslint-disable-next-line no-void\n void runManager?.handleLLMNewToken(text ?? \"\");\n if (finish_reason && finish_reason !== \"null\") {\n if (resolved || rejected) {\n return;\n }\n resolved = true;\n resolve(response);\n }\n }\n ).catch((error) => {\n if (!rejected) {\n rejected = true;\n reject(error);\n }\n });\n })\n : await this.completionWithRetry(\n {\n model: this.model,\n parameters,\n input: {\n messages: messagesMapped,\n },\n },\n false,\n options?.signal\n ).then<ChatCompletionResponse>((data) => {\n if (data?.code) {\n throw new Error(data?.message);\n }\n\n return data;\n });\n\n const {\n input_tokens = 0,\n output_tokens = 0,\n total_tokens = 0,\n } = data.usage;\n\n const { text } = data.output;\n\n return {\n generations: [\n {\n text,\n message: new AIMessage(text),\n },\n ],\n llmOutput: {\n tokenUsage: {\n promptTokens: input_tokens,\n completionTokens: output_tokens,\n totalTokens: total_tokens,\n },\n },\n };\n }\n\n /** @ignore */\n async completionWithRetry(\n request: ChatCompletionRequest,\n stream: boolean,\n signal?: AbortSignal,\n onmessage?: (event: MessageEvent) => void\n ) {\n const makeCompletionRequest = async () => {\n const response = await fetch(this.apiUrl, {\n method: \"POST\",\n headers: {\n ...(stream ? { Accept: \"text/event-stream\" } : {}),\n Authorization: `Bearer ${this.alibabaApiKey}`,\n \"Content-Type\": \"application/json\",\n },\n body: JSON.stringify(request),\n signal,\n });\n\n if (!stream) {\n return response.json();\n }\n\n if (response.body) {\n // response will not be a stream if an error occurred\n if (\n !response.headers.get(\"content-type\")?.startsWith(\"text/event-stream\")\n ) {\n onmessage?.(\n new MessageEvent(\"message\", {\n data: await response.text(),\n })\n );\n return;\n }\n const reader = response.body.getReader();\n const decoder = new TextDecoder(\"utf-8\");\n let data = \"\";\n let continueReading = true;\n while (continueReading) {\n const { done, value } = await reader.read();\n if (done) {\n continueReading = false;\n break;\n }\n data += decoder.decode(value);\n let continueProcessing = true;\n while (continueProcessing) {\n const newlineIndex = data.indexOf(\"\\n\");\n if (newlineIndex === -1) {\n continueProcessing = false;\n break;\n }\n const line = data.slice(0, newlineIndex);\n data = data.slice(newlineIndex + 1);\n if (line.startsWith(\"data:\")) {\n const event = new MessageEvent(\"message\", {\n data: line.slice(\"data:\".length).trim(),\n });\n onmessage?.(event);\n }\n }\n }\n }\n };\n\n return this.caller.call(makeCompletionRequest);\n }\n\n async *_streamResponseChunks(\n messages: BaseMessage[],\n options?: this[\"ParsedCallOptions\"],\n runManager?: CallbackManagerForLLMRun\n ): AsyncGenerator<ChatGenerationChunk> {\n const parameters = {\n ...this.invocationParams(),\n stream: true,\n incremental_output: true,\n };\n\n const messagesMapped: TongyiMessage[] = messages.map((message) => ({\n role: messageToTongyiRole(message),\n content: message.content as string,\n }));\n\n const stream = await this.caller.call(async () =>\n this.createTongyiStream(\n {\n model: this.model,\n parameters,\n input: {\n messages: messagesMapped,\n },\n },\n options?.signal\n )\n );\n\n for await (const chunk of stream) {\n /* if some error occurs:\n {\n \"code\": \"DataInspectionFailed\",\n \"message\": \"Output data may contain inappropriate content.\",\n \"request_id\": \"43d18007-5aa5-9d18-b3b3-a55aba9ce8cb\"\n }\n */\n if (!chunk.output && chunk.code) {\n throw new Error(JSON.stringify(chunk));\n }\n const { text, finish_reason } = chunk.output;\n yield new ChatGenerationChunk({\n text,\n message: new AIMessageChunk({ content: text }),\n generationInfo:\n finish_reason === \"stop\"\n ? {\n finish_reason,\n request_id: chunk.request_id,\n usage: chunk.usage,\n }\n : undefined,\n });\n await runManager?.handleLLMNewToken(text);\n }\n }\n\n private async *createTongyiStream(\n request: ChatCompletionRequest,\n signal?: AbortSignal\n ) {\n const response = await fetch(this.apiUrl, {\n method: \"POST\",\n headers: {\n Authorization: `Bearer ${this.alibabaApiKey}`,\n Accept: \"text/event-stream\",\n \"Content-Type\": \"application/json\",\n },\n body: JSON.stringify(request),\n signal,\n });\n\n if (!response.ok) {\n let error;\n const responseText = await response.text();\n try {\n const json = JSON.parse(responseText);\n error = new Error(\n `Tongyi call failed with status code ${response.status}: ${json.error}`\n );\n } catch {\n error = new Error(\n `Tongyi call failed with status code ${response.status}: ${responseText}`\n );\n }\n // eslint-disable-next-line @typescript-eslint/no-explicit-any\n (error as any).response = response;\n throw error;\n }\n if (!response.body) {\n throw new Error(\n \"Could not begin Tongyi stream. Please check the given URL and try again.\"\n );\n }\n const stream = IterableReadableStream.fromReadableStream(response.body);\n const decoder = new TextDecoder();\n let extra = \"\";\n for await (const chunk of stream) {\n const decoded = extra + decoder.decode(chunk);\n const lines = decoded.split(\"\\n\");\n extra = lines.pop() || \"\";\n for (const line of lines) {\n if (!line.startsWith(\"data:\")) {\n continue;\n }\n try {\n yield JSON.parse(line.slice(\"data:\".length).trim());\n } catch {\n console.warn(`Received a non-JSON parseable chunk: ${line}`);\n }\n }\n }\n }\n\n _llmType(): string {\n return \"alibaba_tongyi\";\n }\n\n /** @ignore */\n _combineLLMOutput() {\n return [];\n 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