{"version":3,"file":"ibm.cjs","names":["model: string","tool_call_id: string","_convertToolCallIdToMistralCompatible","tools: ChatWatsonxToolType[]","MESSAGE_TYPE_TO_ROLE_MAP: Record<MessageType, string>","role: MessageType","message: BaseMessage","model?: string","convertLangChainToolCallToOpenAI","messages: BaseMessage[]","choice: TextChatResultChoice | ChatsChoice","rawDataId: string","usage?: TextChatUsage","e: unknown","additional_kwargs: Record<string, unknown>","AIMessage","ChatMessage","helperIndex: { [\"value\"]: number }","delta: WatsonxDeltaStream","rawData: TextChatResponse | ChatsResponse","defaultRole?: TextChatMessagesTextChatMessageAssistant.Constants.Role","HumanMessageChunk","toolCallChunks: ToolCallChunk[]","AIMessageChunk","ToolMessageChunk","FunctionMessageChunk","ChatMessageChunk","toolChoice: TextChatParameterTools | string | \"auto\" | \"any\"","BaseChatModel","options: this[\"ParsedCallOptions\"]","fields: this[\"ParsedCallOptions\"] | ChatWatsonxConstructorInput","validProps: string[]","checkValidProps","fields: ChatWatsonxConstructorInput","expectOneOf","authenticateAndSetGatewayInstance","authenticateAndSetInstance","toolParams: Record<string, WatsonXAI.TextChatParameterTools[]>","toolChoiceParams: Record<\n      string,\n      TextChatParameterTools | string | undefined\n    >","gatewayParams: Record<string, any>","kwargs?: Partial<CallOptions>","options?: this[\"ParsedCallOptions\"]","callback: () => T","AsyncCaller","scopeId: ReturnType<ChatWatsonx[\"scopeId\"]>","params: ReturnType<ChatWatsonx[\"invocationParams\"]>","messages: ChatsMessage[]","signal?: AbortSignal","stream: S","runManager?: CallbackManagerForLLMRun","finalChunks: Record<number, ChatGenerationChunk>","tokenUsage: UsageMetadata","tokenUsages: UsageMetadata[]","generations: ChatGeneration[]","generation: ChatGeneration","_runManager?: CallbackManagerForLLMRun","usage: TextChatUsage | undefined","generationChunk","ChatGenerationChunk","outputSchema:\n      | InteropZodType<RunOutput>\n      // eslint-disable-next-line @typescript-eslint/no-explicit-any\n      | Record<string, any>","config?: StructuredOutputMethodOptions<boolean>","schema: InteropZodType<RunOutput> | Record<string, any>","outputParser: BaseLLMOutputParser<RunOutput>","llm: Runnable<BaseLanguageModelInput>","outputFormatSchema: JsonSchema7Type | undefined","StructuredOutputParser","JsonOutputParser","WatsonxToolsOutputParser","openAIFunctionDefinition: FunctionDefinition","RunnablePassthrough","input: any","config","RunnableSequence"],"sources":["../../src/chat_models/ibm.ts"],"sourcesContent":["import {\n  AIMessage,\n  AIMessageChunk,\n  ChatMessage,\n  ChatMessageChunk,\n  FunctionMessageChunk,\n  HumanMessageChunk,\n  isAIMessage,\n  MessageType,\n  ToolMessageChunk,\n  UsageMetadata,\n  type BaseMessage,\n} from \"@langchain/core/messages\";\nimport {\n  BaseLanguageModelInput,\n  FunctionDefinition,\n  StructuredOutputMethodOptions,\n} from \"@langchain/core/language_models/base\";\nimport { CallbackManagerForLLMRun } from \"@langchain/core/callbacks/manager\";\nimport {\n  BaseChatModel,\n  BindToolsInput,\n  LangSmithParams,\n  type BaseChatModelParams,\n} from \"@langchain/core/language_models/chat_models\";\nimport {\n  ChatGeneration,\n  ChatGenerationChunk,\n  ChatResult,\n} from \"@langchain/core/outputs\";\nimport { AsyncCaller } from \"@langchain/core/utils/async_caller\";\nimport {\n  DeploymentsTextChatParams,\n  RequestCallbacks,\n  TextChatMessagesTextChatMessageAssistant,\n  TextChatParameterTools,\n  TextChatParams,\n  TextChatResponse,\n  TextChatResponseFormat,\n  TextChatResultChoice,\n  TextChatResultMessage,\n  TextChatToolCall,\n  TextChatUsage,\n} from \"@ibm-cloud/watsonx-ai/dist/watsonx-ai-ml/vml_v1.js\";\nimport { WatsonXAI, Stream } from \"@ibm-cloud/watsonx-ai\";\nimport { Response } from \"@ibm-cloud/watsonx-ai/base\";\nimport {\n  convertLangChainToolCallToOpenAI,\n  makeInvalidToolCall,\n  parseToolCall,\n} from \"@langchain/core/output_parsers/openai_tools\";\nimport { ToolCallChunk } from \"@langchain/core/messages/tool\";\nimport {\n  Runnable,\n  RunnablePassthrough,\n  RunnableSequence,\n} from \"@langchain/core/runnables\";\nimport {\n  BaseLLMOutputParser,\n  JsonOutputParser,\n  StructuredOutputParser,\n} from \"@langchain/core/output_parsers\";\nimport {\n  InteropZodType,\n  isInteropZodSchema,\n} from \"@langchain/core/utils/types\";\nimport {\n  JsonSchema7Type,\n  toJsonSchema,\n} from \"@langchain/core/utils/json_schema\";\nimport { NewTokenIndices } from \"@langchain/core/callbacks/base\";\nimport {\n  ChatObjectStream,\n  ChatsChoice,\n  ChatsMessage,\n  ChatsRequestTool,\n  ChatsResponse,\n  CreateChatCompletionsParams,\n  Gateway,\n} from \"@ibm-cloud/watsonx-ai/gateway\";\nimport { WatsonxAuth, XOR, WatsonxBaseChatParams } from \"../types/ibm.js\";\nimport {\n  _convertToolCallIdToMistralCompatible,\n  authenticateAndSetGatewayInstance,\n  authenticateAndSetInstance,\n  checkValidProps,\n  expectOneOf,\n  WatsonxToolsOutputParser,\n} from \"../utils/ibm.js\";\n\n// Ensuring back compatibility\nexport interface WatsonxCallParams extends WatsonxCallOptionsChat {}\nexport interface WatsonxCallDeployedParams extends DeploymentsTextChatParams {}\n\nexport interface WatsonxDeltaStream {\n  role?: string;\n  content?: string;\n  tool_calls?: TextChatToolCall[];\n  refusal?: string;\n}\n\n/** Project/space params */\n\nexport interface WatsonxCallOptionsChat\n  extends Partial<Omit<TextChatParams, \"modelId\" | \"toolChoice\" | \"messages\">>,\n    WatsonxBaseChatParams {\n  model?: string;\n}\n\nexport interface WatsonxProjectSpaceParams extends WatsonxCallOptionsChat {\n  model: string;\n  serviceUrl: string;\n  version: string;\n}\n/** Deployed params */\nexport interface WatsonxCallOptionsDeployedChat\n  extends Partial<Omit<DeploymentsTextChatParams, \"messages\">>,\n    WatsonxBaseChatParams {}\n\nexport interface WatsonxDeployedParams extends WatsonxCallOptionsDeployedChat {\n  serviceUrl: string;\n  version: string;\n}\n/** Gateway params */\nexport interface WatsonxGatewayChatKwargs\n  extends Omit<\n    CreateChatCompletionsParams,\n    keyof TextChatParams | \"model\" | \"stream\" | \"messages\"\n  > {}\nexport interface WatsonxCallOptionsGatewayChat\n  extends Omit<\n      CreateChatCompletionsParams,\n      | \"stream\"\n      | \"toolChoice\"\n      | \"messages\"\n      | \"prompt\"\n      | keyof WatsonxGatewayChatKwargs\n    >,\n    WatsonxBaseChatParams {\n  /** Additional parameters usable only in model gateway */\n  modelGatewayKwargs?: WatsonxGatewayChatKwargs;\n}\n\nexport interface WatsonxGatewayChatParams\n  extends WatsonxCallOptionsGatewayChat {\n  serviceUrl: string;\n  version: string;\n}\n\n// Chat input for different chat modes\nexport interface ChatWatsonxInput\n  extends BaseChatModelParams,\n    WatsonxProjectSpaceParams {}\n\nexport interface ChatWatsonxDeployedInput\n  extends BaseChatModelParams,\n    WatsonxDeployedParams {}\n\nexport interface ChatWatsonxGatewayInput\n  extends BaseChatModelParams,\n    WatsonxGatewayChatParams {\n  /** Flag indicating weather to use Model Gateway or no */\n  modelGateway: boolean;\n}\n\n// Chat type to be extended by chat class\nexport type ChatWatsonxConstructor = BaseChatModelParams &\n  Partial<WatsonxBaseChatParams> &\n  WatsonxDeployedParams &\n  WatsonxCallParams &\n  WatsonxDeployedParams;\n\nfunction _convertToValidToolId(model: string, tool_call_id: string): string {\n  if (model.startsWith(\"mistralai\") && tool_call_id)\n    return _convertToolCallIdToMistralCompatible(tool_call_id);\n  return tool_call_id;\n}\n\ntype ChatWatsonxToolType =\n  | BindToolsInput\n  | TextChatParameterTools\n  | ChatsRequestTool;\n\nfunction _convertToolToWatsonxTool(\n  tools: ChatWatsonxToolType[]\n): WatsonXAI.TextChatParameterTools[] {\n  return tools.map((tool) => {\n    if (\"type\" in tool) {\n      return tool as WatsonXAI.TextChatParameterTools;\n    }\n    // Check if schema is a Zod schema or already a JSON schema\n    const parameters = isInteropZodSchema(tool.schema)\n      ? toJsonSchema(tool.schema)\n      : tool.schema;\n\n    return {\n      type: \"function\",\n      function: {\n        name: tool.name,\n        description: tool.description ?? `Tool: ${tool.name}`,\n        parameters,\n      },\n    };\n  });\n}\nconst MESSAGE_TYPE_TO_ROLE_MAP: Record<MessageType, string> = {\n  human: \"user\",\n  ai: \"assistant\",\n  system: \"system\",\n  tool: \"tool\",\n  function: \"function\",\n  generic: \"assistant\",\n  developer: \"developer\",\n  remove: \"function\",\n};\n\nconst getRole = (role: MessageType): string => {\n  const watsonRole = MESSAGE_TYPE_TO_ROLE_MAP[role];\n  if (!watsonRole) {\n    throw new Error(`Unknown message type: ${role}`);\n  }\n  return watsonRole;\n};\n\nconst getToolCalls = (message: BaseMessage, model?: string) => {\n  if (isAIMessage(message) && message.tool_calls?.length) {\n    return message.tool_calls\n      .map((toolCall) => ({\n        ...toolCall,\n        id: _convertToValidToolId(model ?? \"\", toolCall.id ?? \"\"),\n      }))\n      .map(convertLangChainToolCallToOpenAI);\n  }\n  return undefined;\n};\n\nfunction _convertMessagesToWatsonxMessages(\n  messages: BaseMessage[],\n  model?: string\n): TextChatResultMessage[] | ChatsMessage[] {\n  return messages.map((message) => {\n    const toolCalls = getToolCalls(message, model);\n    const content = toolCalls === undefined ? message.content : \"\";\n    if (\"tool_call_id\" in message && typeof message.tool_call_id === \"string\") {\n      return {\n        role: getRole(message.getType()),\n        content,\n        name: message.name,\n        tool_call_id: _convertToValidToolId(model ?? \"\", message.tool_call_id),\n      };\n    }\n\n    return {\n      role: getRole(message.getType()),\n      content,\n      tool_calls: toolCalls,\n    };\n  });\n}\n\nfunction _watsonxResponseToChatMessage(\n  choice: TextChatResultChoice | ChatsChoice,\n  rawDataId: string,\n  usage?: TextChatUsage\n): BaseMessage {\n  const { message } = choice;\n  if (!message) throw new Error(\"No message presented\");\n  const rawToolCalls = message.tool_calls ?? [];\n\n  switch (message.role) {\n    case \"assistant\": {\n      const toolCalls = [];\n      const invalidToolCalls = [];\n      for (const rawToolCall of rawToolCalls) {\n        try {\n          const parsed = parseToolCall(rawToolCall, { returnId: true });\n          toolCalls.push(parsed);\n        } catch (e: unknown) {\n          invalidToolCalls.push(\n            makeInvalidToolCall(rawToolCall, (e as Error).message)\n          );\n        }\n      }\n      const additional_kwargs: Record<string, unknown> = {\n        tool_calls: rawToolCalls.map((toolCall) => ({\n          ...toolCall,\n          type: \"function\",\n        })),\n      };\n\n      return new AIMessage({\n        id: rawDataId,\n        content: message.content ?? \"\",\n        tool_calls: toolCalls,\n        invalid_tool_calls: invalidToolCalls,\n        additional_kwargs,\n        usage_metadata: usage\n          ? {\n              input_tokens: usage.prompt_tokens ?? 0,\n              output_tokens: usage.completion_tokens ?? 0,\n              total_tokens: usage.total_tokens ?? 0,\n            }\n          : undefined,\n      });\n    }\n    default:\n      return new ChatMessage(message.content ?? \"\", message.role ?? \"unknown\");\n  }\n}\n\nfunction _convertDeltaToMessageChunk(\n  helperIndex: { [\"value\"]: number },\n  delta: WatsonxDeltaStream,\n  rawData: TextChatResponse | ChatsResponse,\n  model?: string,\n  usage?: TextChatUsage,\n  defaultRole?: TextChatMessagesTextChatMessageAssistant.Constants.Role\n) {\n  if (delta.refusal) throw new Error(delta.refusal);\n\n  const rawToolCalls = delta.tool_calls?.length\n    ? delta.tool_calls?.map(\n        (\n          toolCall,\n          index\n        ): TextChatToolCall & { index: number; type: \"function\" } => {\n          const validId =\n            toolCall.id && toolCall.id !== \"\"\n              ? _convertToValidToolId(model ?? \"\", toolCall.id)\n              : undefined;\n          if (toolCall.id) helperIndex.value += 1;\n          return {\n            index:\n              delta?.tool_calls && delta?.tool_calls?.length > 1\n                ? index\n                : helperIndex.value,\n            ...toolCall,\n            ...(validId !== null && { id: validId }),\n            type: \"function\",\n          };\n        }\n      )\n    : undefined;\n\n  const role = delta.role || defaultRole || \"assistant\";\n  const content = delta.content ?? \"\";\n  const additional_kwargs = rawToolCalls ? { tool_calls: rawToolCalls } : {};\n\n  const usageMetadata = {\n    input_tokens: usage?.prompt_tokens ?? 0,\n    output_tokens: usage?.completion_tokens ?? 0,\n    total_tokens: usage?.total_tokens ?? 0,\n  };\n  switch (role) {\n    case \"user\":\n      return new HumanMessageChunk({ content });\n\n    case \"assistant\": {\n      // Extract tool call chunks creation\n      const toolCallChunks: ToolCallChunk[] = [];\n      if (rawToolCalls && rawToolCalls?.length > 0) {\n        for (const rawToolCallChunk of rawToolCalls) {\n          const toolCallName = rawToolCallChunk.function.name;\n          toolCallChunks.push({\n            name: toolCallName.length > 0 ? toolCallName : undefined,\n            args: rawToolCallChunk.function?.arguments,\n            id: rawToolCallChunk.id,\n            index: rawToolCallChunk.index,\n            type: \"tool_call_chunk\",\n          });\n        }\n      }\n\n      return new AIMessageChunk({\n        content,\n        tool_call_chunks: toolCallChunks,\n        additional_kwargs,\n        usage_metadata: usageMetadata,\n        id: rawData.id,\n      });\n    }\n\n    case \"tool\":\n      if (rawToolCalls) {\n        return new ToolMessageChunk({\n          content,\n          additional_kwargs,\n          tool_call_id: _convertToValidToolId(model ?? \"\", rawToolCalls[0].id),\n        });\n      }\n      return null;\n\n    case \"function\":\n      return new FunctionMessageChunk({\n        content,\n        additional_kwargs,\n      });\n\n    default:\n      return new ChatMessageChunk({ content, role });\n  }\n}\n\nfunction _convertToolChoiceToWatsonxToolChoice(\n  toolChoice: TextChatParameterTools | string | \"auto\" | \"any\"\n) {\n  if (typeof toolChoice === \"string\") {\n    if (toolChoice === \"any\" || toolChoice === \"required\") {\n      return { toolChoiceOption: \"required\" };\n    } else if (toolChoice === \"auto\" || toolChoice === \"none\") {\n      return { toolChoiceOption: toolChoice };\n    } else {\n      return {\n        toolChoice: {\n          type: \"function\",\n          function: { name: toolChoice },\n        },\n      };\n    }\n  } else if (\"type\" in toolChoice) return { toolChoice };\n  else\n    throw new Error(\n      `Unrecognized tool_choice type. Expected string or TextChatParameterTools. Recieved ${toolChoice}`\n    );\n}\n\n// Combined input for chat excluding each mode to not be present at the same time\nexport type ChatWatsonxConstructorInput = XOR<\n  XOR<ChatWatsonxInput, ChatWatsonxDeployedInput>,\n  ChatWatsonxGatewayInput\n> &\n  WatsonxAuth;\n\n// Helper to force type expansion\nexport type ChatWatsonxCallOptions = XOR<\n  XOR<WatsonxCallOptionsChat, WatsonxCallOptionsDeployedChat>,\n  WatsonxCallOptionsGatewayChat\n>;\n\nexport class ChatWatsonx<\n    CallOptions extends ChatWatsonxCallOptions = ChatWatsonxCallOptions,\n  >\n  extends BaseChatModel<CallOptions>\n  implements ChatWatsonxConstructor\n{\n  static lc_name() {\n    return \"ChatWatsonx\";\n  }\n\n  lc_serializable = true;\n\n  get lc_secrets(): { [key: string]: string } {\n    return {\n      authenticator: \"AUTHENTICATOR\",\n      apiKey: \"WATSONX_AI_APIKEY\",\n      apikey: \"WATSONX_AI_APIKEY\",\n      watsonxAIAuthType: \"WATSONX_AI_AUTH_TYPE\",\n      watsonxAIApikey: \"WATSONX_AI_APIKEY\",\n      watsonxAIBearerToken: \"WATSONX_AI_BEARER_TOKEN\",\n      watsonxAIUsername: \"WATSONX_AI_USERNAME\",\n      watsonxAIPassword: \"WATSONX_AI_PASSWORD\",\n      watsonxAIUrl: \"WATSONX_AI_URL\",\n    };\n  }\n\n  get lc_aliases(): { [key: string]: string } {\n    return {\n      authenticator: \"authenticator\",\n      apikey: \"watsonx_ai_apikey\",\n      apiKey: \"watsonx_ai_apikey\",\n      watsonxAIAuthType: \"watsonx_ai_auth_type\",\n      watsonxAIApikey: \"watsonx_ai_apikey\",\n      watsonxAIBearerToken: \"watsonx_ai_bearer_token\",\n      watsonxAIUsername: \"watsonx_ai_username\",\n      watsonxAIPassword: \"watsonx_ai_password\",\n      watsonxAIUrl: \"watsonx_ai_url\",\n    };\n  }\n\n  getLsParams(options: this[\"ParsedCallOptions\"]): LangSmithParams {\n    const params = this.invocationParams(options);\n    return {\n      ls_provider: \"watsonx\",\n      ls_model_name: this.model,\n      ls_model_type: \"chat\",\n      ls_temperature: params.temperature ?? undefined,\n      ls_max_tokens: params.maxTokens ?? undefined,\n    };\n  }\n\n  private checkValidProperties(\n    fields: this[\"ParsedCallOptions\"] | ChatWatsonxConstructorInput,\n    includeCommonProps = true\n  ) {\n    const PROPERTY_GROUPS = {\n      ALWAYS_ALLOWED: [\n        \"headers\",\n        \"signal\",\n        \"tool_choice\",\n        \"promptIndex\",\n        \"ls_structured_output_format\",\n        \"watsonxCallbacks\",\n        \"writer\",\n        \"interrupt\",\n      ],\n\n      AUTH: [\n        \"serviceUrl\",\n        \"watsonxAIApikey\",\n        \"watsonxAIBearerToken\",\n        \"watsonxAIUsername\",\n        \"watsonxAIPassword\",\n        \"watsonxAIUrl\",\n        \"watsonxAIAuthType\",\n        \"disableSSL\",\n      ],\n\n      SHARED: [\n        \"maxRetries\",\n        \"authenticator\",\n        \"serviceUrl\",\n        \"version\",\n        \"streaming\",\n        \"callbackManager\",\n        \"callbacks\",\n        \"maxConcurrency\",\n        \"cache\",\n        \"metadata\",\n        \"concurrency\",\n        \"onFailedAttempt\",\n        \"verbose\",\n        \"tags\",\n        \"headers\",\n        \"disableStreaming\",\n        \"timeout\",\n        \"stopSequences\",\n      ],\n\n      GATEWAY: [\n        \"tools\",\n        \"frequencyPenalty\",\n        \"logitBias\",\n        \"logprobs\",\n        \"topLogprobs\",\n        \"maxTokens\",\n        \"n\",\n        \"presencePenalty\",\n        \"responseFormat\",\n        \"seed\",\n        \"stop\",\n        \"temperature\",\n        \"topP\",\n        \"model\",\n        \"modelGatewayKwargs\",\n        \"modelGateway\",\n      ],\n\n      DEPLOYMENT: [\"idOrName\"],\n\n      PROJECT_OR_SPACE: [\n        \"spaceId\",\n        \"projectId\",\n        \"tools\",\n        \"toolChoiceOption\",\n        \"frequencyPenalty\",\n        \"logitBias\",\n        \"logprobs\",\n        \"topLogprobs\",\n        \"maxTokens\",\n        \"maxCompletionTokens\",\n        \"n\",\n        \"presencePenalty\",\n        \"responseFormat\",\n        \"seed\",\n        \"stop\",\n        \"temperature\",\n        \"topP\",\n        \"timeLimit\",\n        \"model\",\n      ],\n    };\n\n    const validProps: string[] = [...PROPERTY_GROUPS.ALWAYS_ALLOWED];\n\n    if (includeCommonProps) {\n      validProps.push(...PROPERTY_GROUPS.AUTH, ...PROPERTY_GROUPS.SHARED);\n    }\n\n    if (this.modelGateway) {\n      validProps.push(...PROPERTY_GROUPS.GATEWAY);\n    } else if (this.idOrName) {\n      validProps.push(...PROPERTY_GROUPS.DEPLOYMENT);\n    } else if (this.spaceId || this.projectId) {\n      validProps.push(...PROPERTY_GROUPS.PROJECT_OR_SPACE);\n    }\n\n    checkValidProps(fields, validProps);\n  }\n\n  protected service?: WatsonXAI;\n\n  protected gateway?: Gateway;\n\n  model?: string;\n\n  version = \"2024-05-31\";\n\n  modelGateway = false;\n\n  maxTokens?: number;\n\n  maxCompletionTokens?: number;\n\n  maxRetries = 0;\n\n  serviceUrl: string;\n\n  spaceId?: string;\n\n  projectId?: string;\n\n  idOrName?: string;\n\n  frequencyPenalty?: number;\n\n  logprobs?: boolean;\n\n  topLogprobs?: number;\n\n  n?: number;\n\n  presencePenalty?: number;\n\n  temperature?: number;\n\n  topP?: number;\n\n  timeLimit?: number;\n\n  maxConcurrency?: number;\n\n  responseFormat?: TextChatResponseFormat;\n\n  streaming = false;\n\n  modelGatewayKwargs?: WatsonxGatewayChatKwargs;\n\n  watsonxCallbacks?: RequestCallbacks;\n\n  constructor(fields: ChatWatsonxConstructorInput) {\n    super(fields);\n    const uniqueProps = [\"spaceId\", \"projectId\", \"idOrName\", \"modelGateway\"];\n    expectOneOf(fields, uniqueProps, true);\n\n    this.idOrName = fields?.idOrName;\n    this.projectId = fields?.projectId;\n    this.modelGateway = fields.modelGateway || this.modelGateway;\n    this.spaceId = fields?.spaceId;\n\n    this.checkValidProperties(fields);\n\n    this.model = fields?.model ?? this.model;\n    this.projectId = fields?.projectId;\n    this.spaceId = fields?.spaceId;\n    this.watsonxCallbacks = fields?.watsonxCallbacks;\n    this.serviceUrl = fields?.serviceUrl;\n    this.version = fields?.version ?? this.version;\n\n    this.temperature = fields?.temperature;\n    this.maxRetries = fields?.maxRetries || this.maxRetries;\n    this.maxConcurrency = fields?.maxConcurrency;\n    this.frequencyPenalty = fields?.frequencyPenalty;\n    this.maxTokens = fields?.maxTokens ?? this.maxTokens;\n    this.maxCompletionTokens = fields?.maxCompletionTokens;\n    this.presencePenalty = fields?.presencePenalty;\n    this.topP = fields?.topP;\n    this.responseFormat = fields?.responseFormat ?? this.responseFormat;\n    this.streaming = fields?.streaming ?? this.streaming;\n    this.n = fields?.n ?? this.n;\n    this.timeLimit = fields?.timeLimit;\n\n    this.modelGateway = fields?.modelGateway ?? this.modelGateway;\n    this.modelGatewayKwargs = fields?.modelGatewayKwargs;\n\n    const {\n      watsonxAIApikey,\n      watsonxAIAuthType,\n      watsonxAIBearerToken,\n      watsonxAIUsername,\n      watsonxAIPassword,\n      watsonxAIUrl,\n      disableSSL,\n      version,\n      serviceUrl,\n    } = fields;\n\n    const authData = {\n      watsonxAIApikey,\n      watsonxAIAuthType,\n      watsonxAIBearerToken,\n      watsonxAIUsername,\n      watsonxAIPassword,\n      watsonxAIUrl,\n      disableSSL,\n      version,\n      serviceUrl,\n    };\n\n    if (this.modelGateway) {\n      const chatGateway = authenticateAndSetGatewayInstance(authData);\n      if (chatGateway) this.gateway = chatGateway;\n      else throw new Error(\"You have not provided any type of authentication\");\n    } else {\n      const service = authenticateAndSetInstance(authData);\n\n      if (service) this.service = service;\n      else throw new Error(\"You have not provided any type of authentication\");\n    }\n  }\n\n  _llmType() {\n    return \"watsonx\";\n  }\n\n  invocationParams(options: this[\"ParsedCallOptions\"]) {\n    const { tools, responseFormat, timeLimit, tool_choice } = options;\n\n    expectOneOf(options, [\"spaceId\", \"projectId\", \"idOrName\", \"modelGateway\"]);\n    this.checkValidProperties(options, false);\n\n    const paramDefaults = {\n      maxTokens: options.maxTokens ?? this.maxTokens,\n      maxCompletionTokens:\n        options.maxCompletionTokens ?? this.maxCompletionTokens,\n      temperature: options.temperature ?? this.temperature,\n      topP: options.topP ?? this.topP,\n      presencePenalty: options.presencePenalty ?? this.presencePenalty,\n      n: options.n ?? this.n,\n      topLogprobs: options.topLogprobs ?? this.topLogprobs,\n      logprobs: options.logprobs ?? this.logprobs,\n      frequencyPenalty: options.frequencyPenalty ?? this.frequencyPenalty,\n    };\n\n    const toolParams: Record<string, WatsonXAI.TextChatParameterTools[]> = tools\n      ? { tools: _convertToolToWatsonxTool(tools) }\n      : {};\n\n    const toolChoiceParams: Record<\n      string,\n      TextChatParameterTools | string | undefined\n    > = tool_choice ? _convertToolChoiceToWatsonxToolChoice(tool_choice) : {};\n\n    // eslint-disable-next-line @typescript-eslint/no-explicit-any\n    const gatewayParams: Record<string, any> = this.modelGateway\n      ? { ...this.modelGatewayKwargs }\n      : {\n          timeLimit: timeLimit ?? this.timeLimit,\n          projectId: options.projectId ?? this.projectId,\n        };\n\n    return {\n      ...paramDefaults,\n      ...toolParams,\n      responseFormat,\n      ...toolChoiceParams,\n      ...gatewayParams,\n    };\n  }\n\n  invocationCallbacks(options: this[\"ParsedCallOptions\"]) {\n    return options.watsonxCallbacks ?? this.watsonxCallbacks;\n  }\n\n  override bindTools(\n    tools: ChatWatsonxToolType[],\n    kwargs?: Partial<CallOptions>\n  ): Runnable<BaseLanguageModelInput, AIMessageChunk, CallOptions> {\n    return this.withConfig({\n      tools: _convertToolToWatsonxTool(tools),\n      ...kwargs,\n    } as CallOptions);\n  }\n\n  scopeId(\n    options?: this[\"ParsedCallOptions\"]\n  ):\n    | { idOrName: string }\n    | { projectId: string; modelId: string }\n    | { spaceId: string; modelId: string }\n    | { modelId: string }\n    | { model: string } {\n    const model = options?.model ?? this.model;\n    const projectId = options?.projectId ?? this.projectId;\n    const spaceId = options?.spaceId ?? this.spaceId;\n    const idOrName = options?.idOrName ?? this.idOrName;\n\n    if (this.modelGateway) {\n      if (!model) {\n        throw new Error(\n          \"No model provided! Model gateway expects model to be provided\"\n        );\n      }\n      return { model };\n    }\n\n    if (projectId && model) return { projectId, modelId: model };\n    if (spaceId && model) return { spaceId, modelId: model };\n    if (idOrName) return { idOrName };\n    if (model) return { modelId: model };\n\n    throw new Error(\"No id or model provided!\");\n  }\n\n  async completionWithRetry<T>(\n    callback: () => T,\n    options?: this[\"ParsedCallOptions\"]\n  ) {\n    const caller = new AsyncCaller({\n      maxConcurrency: options?.maxConcurrency ?? this.maxConcurrency,\n      maxRetries: this.maxRetries,\n    });\n    const result = options\n      ? caller.callWithOptions(\n          {\n            signal: options.signal,\n          },\n          async () => callback()\n        )\n      : caller.call(async () => callback());\n\n    return result;\n  }\n\n  private async _chatModelGateway<S extends boolean = false>(\n    scopeId: ReturnType<ChatWatsonx[\"scopeId\"]>,\n    params: ReturnType<ChatWatsonx[\"invocationParams\"]>,\n    messages: ChatsMessage[],\n    signal?: AbortSignal,\n    stream: S = false as S\n  ): Promise<\n    S extends true ? Stream<ChatObjectStream> : Response<ChatsResponse>\n  > {\n    if (this.gateway) {\n      if (\"model\" in scopeId) {\n        return this.gateway.chat.completion.create({\n          ...params,\n          ...scopeId,\n          signal,\n          stream,\n          ...(stream ? { returnObject: true } : {}),\n          messages,\n        });\n      }\n      throw new Error(\n        \"No 'model' specified. Model needs to be spcified for model gateway\"\n      );\n    }\n    throw new Error(\n      \"'gateway' instance is not set. Please check your implementation\"\n    );\n  }\n\n  async _generate(\n    messages: BaseMessage[],\n    options: this[\"ParsedCallOptions\"],\n    runManager?: CallbackManagerForLLMRun\n  ): Promise<ChatResult> {\n    if (this.streaming) {\n      const stream = this._streamResponseChunks(messages, options, runManager);\n      const finalChunks: Record<number, ChatGenerationChunk> = {};\n      let tokenUsage: UsageMetadata = {\n        input_tokens: 0,\n        output_tokens: 0,\n        total_tokens: 0,\n      };\n      const tokenUsages: UsageMetadata[] = [];\n      for await (const chunk of stream) {\n        const message = chunk.message as AIMessageChunk;\n        const usageMetadata = message?.usage_metadata as UsageMetadata;\n        if (usageMetadata) {\n          const completion = chunk.generationInfo?.completion;\n          if (tokenUsages[completion])\n            tokenUsages[completion].output_tokens =\n              usageMetadata?.output_tokens;\n          else tokenUsages[completion] = usageMetadata;\n        }\n        chunk.message.response_metadata = {\n          model: this.model,\n          ...chunk.generationInfo,\n          ...chunk.message.response_metadata,\n        };\n\n        const index =\n          (chunk.generationInfo as NewTokenIndices)?.completion ?? 0;\n        if (finalChunks[index] === undefined) {\n          finalChunks[index] = chunk;\n        } else {\n          finalChunks[index] = finalChunks[index].concat(chunk);\n        }\n      }\n      tokenUsage = tokenUsages.reduce((acc, curr) => {\n        return {\n          input_tokens: acc.input_tokens + curr.input_tokens,\n          output_tokens: acc.output_tokens + curr.output_tokens,\n          total_tokens: acc.total_tokens + curr.total_tokens,\n        };\n      });\n      const generations = Object.entries(finalChunks)\n        .sort(([aKey], [bKey]) => parseInt(aKey, 10) - parseInt(bKey, 10))\n        .map(([_, value]) => value);\n      return { generations, llmOutput: { tokenUsage } };\n    } else {\n      const params = this.invocationParams(options);\n      const scopeId = this.scopeId(options);\n      const watsonxCallbacks = this.invocationCallbacks(options);\n      const watsonxMessages = _convertMessagesToWatsonxMessages(\n        messages,\n        this.model\n      );\n      const callback = () => {\n        if (this.modelGateway) {\n          return this._chatModelGateway(\n            scopeId,\n            params,\n            watsonxMessages,\n            options.signal,\n            false\n          );\n        }\n\n        if (this.service) {\n          if (\"idOrName\" in scopeId) {\n            return this.service.deploymentsTextChat(\n              {\n                ...scopeId,\n                messages: watsonxMessages,\n                signal: options?.signal,\n              },\n              watsonxCallbacks\n            );\n          }\n\n          if (\"modelId\" in scopeId)\n            return this.service.textChat(\n              {\n                ...params,\n                ...scopeId,\n                messages: watsonxMessages,\n                signal: options?.signal,\n              },\n              watsonxCallbacks\n            );\n        }\n\n        throw new Error(\n          \"No service or gateway set. Please check your intsance init\"\n        );\n      };\n\n      const { result } = await this.completionWithRetry(callback, options);\n      const generations: ChatGeneration[] = [];\n      for (const part of result.choices) {\n        const generation: ChatGeneration = {\n          text: part.message?.content ?? \"\",\n          message: _watsonxResponseToChatMessage(\n            part,\n            result.id,\n            result?.usage\n          ),\n        };\n        if (part.finish_reason) {\n          generation.generationInfo = { finish_reason: part.finish_reason };\n        }\n        generations.push(generation);\n      }\n\n      return {\n        generations,\n        llmOutput: {\n          tokenUsage: result?.usage,\n          model_name: this.model,\n          model: this.model,\n        },\n      };\n    }\n  }\n\n  async *_streamResponseChunks(\n    messages: BaseMessage[],\n    options: this[\"ParsedCallOptions\"],\n    _runManager?: CallbackManagerForLLMRun\n  ): AsyncGenerator<ChatGenerationChunk> {\n    const params = this.invocationParams(options);\n    const scopeId = this.scopeId(options);\n    const watsonxMessages = _convertMessagesToWatsonxMessages(\n      messages,\n      this.model\n    );\n    const watsonxCallbacks = this.invocationCallbacks(options);\n    const { signal } = options;\n    const callback = () => {\n      if (this.modelGateway) {\n        return this._chatModelGateway(\n          scopeId,\n          params,\n          watsonxMessages,\n          signal,\n          true\n        );\n      }\n      if (this.service) {\n        if (\"idOrName\" in scopeId)\n          return this.service.deploymentsTextChatStream(\n            {\n              ...scopeId,\n              messages: watsonxMessages,\n              returnObject: true,\n              signal,\n            },\n            watsonxCallbacks\n          );\n        if (\"modelId\" in scopeId)\n          return this.service.textChatStream(\n            {\n              ...params,\n              ...scopeId,\n              messages: watsonxMessages,\n              returnObject: true,\n              signal,\n            },\n            watsonxCallbacks\n          );\n\n        throw new Error(\n          \"No idOrName or modelId specified. At least one of these needs to be specified in basic mode\"\n        );\n      }\n      throw new Error(\n        \"No service or gateway set. Please check your intsance init\"\n      );\n    };\n    const stream = await this.completionWithRetry(callback, options);\n    let defaultRole;\n    let usage: TextChatUsage | undefined;\n    let currentCompletion = 0;\n    const counter = { value: -1 };\n    for await (const chunk of stream) {\n      if (chunk?.data?.usage) usage = chunk.data.usage;\n      const { data } = chunk;\n      const choice = data.choices[0] as TextChatResultChoice &\n        Record<\"delta\", TextChatResultMessage>;\n\n      if (choice && !(\"delta\" in choice)) {\n        continue;\n      }\n      const delta = choice?.delta;\n      if (!delta) {\n        continue;\n      }\n\n      currentCompletion = choice.index ?? 0;\n      const newTokenIndices = {\n        prompt: options.promptIndex ?? 0,\n        completion: choice.index ?? 0,\n      };\n\n      const generationInfo = {\n        ...newTokenIndices,\n        finish_reason: choice.finish_reason,\n      };\n\n      const message = _convertDeltaToMessageChunk(\n        counter,\n        delta,\n        data,\n        this.model,\n        chunk.data.usage,\n        defaultRole\n      );\n      defaultRole = (delta.role ||\n        defaultRole) as TextChatMessagesTextChatMessageAssistant.Constants.Role;\n\n      if (\n        message === null ||\n        (!delta.content && !delta.tool_calls && delta.role === \"assistant\")\n      ) {\n        continue;\n      }\n      const generationChunk = new ChatGenerationChunk({\n        message,\n        text: delta.content ?? \"\",\n        generationInfo,\n      });\n\n      yield generationChunk;\n      // eslint-disable-next-line no-void\n      void _runManager?.handleLLMNewToken(\n        generationChunk.text,\n        newTokenIndices,\n        undefined,\n        undefined,\n        undefined,\n        { chunk: generationChunk }\n      );\n    }\n\n    const generationChunk = new ChatGenerationChunk({\n      message: new AIMessageChunk({\n        content: \"\",\n        response_metadata: {\n          model: this.model,\n          usage,\n        },\n        usage_metadata: {\n          input_tokens: usage?.prompt_tokens ?? 0,\n          output_tokens: usage?.completion_tokens ?? 0,\n          total_tokens: usage?.total_tokens ?? 0,\n        },\n      }),\n      text: \"\",\n      generationInfo: {\n        prompt: options.promptIndex ?? 0,\n        completion: currentCompletion ?? 0,\n      },\n    });\n    yield generationChunk;\n  }\n\n  /** @ignore */\n  _combineLLMOutput() {\n    return [];\n  }\n\n  withStructuredOutput<\n    // eslint-disable-next-line @typescript-eslint/no-explicit-any\n    RunOutput extends Record<string, any> = Record<string, any>,\n  >(\n    outputSchema:\n      | InteropZodType<RunOutput>\n      // eslint-disable-next-line @typescript-eslint/no-explicit-any\n      | Record<string, any>,\n    config?: StructuredOutputMethodOptions<false>\n  ): Runnable<BaseLanguageModelInput, RunOutput>;\n\n  withStructuredOutput<\n    // eslint-disable-next-line @typescript-eslint/no-explicit-any\n    RunOutput extends Record<string, any> = Record<string, any>,\n  >(\n    outputSchema:\n      | InteropZodType<RunOutput>\n      // eslint-disable-next-line @typescript-eslint/no-explicit-any\n      | Record<string, any>,\n    config?: StructuredOutputMethodOptions<true>\n  ): Runnable<BaseLanguageModelInput, { raw: BaseMessage; parsed: RunOutput }>;\n\n  withStructuredOutput<\n    // eslint-disable-next-line @typescript-eslint/no-explicit-any\n    RunOutput extends Record<string, any> = Record<string, any>,\n  >(\n    outputSchema:\n      | InteropZodType<RunOutput>\n      // eslint-disable-next-line @typescript-eslint/no-explicit-any\n      | Record<string, any>,\n    config?: StructuredOutputMethodOptions<boolean>\n  ):\n    | Runnable<BaseLanguageModelInput, RunOutput>\n    | Runnable<\n        BaseLanguageModelInput,\n        { raw: BaseMessage; parsed: RunOutput }\n      > {\n    // eslint-disable-next-line @typescript-eslint/no-explicit-any\n    const schema: InteropZodType<RunOutput> | Record<string, any> =\n      outputSchema;\n    const name = config?.name;\n    const method = config?.method;\n    const includeRaw = config?.includeRaw;\n    let functionName = name ?? \"extract\";\n    let outputParser: BaseLLMOutputParser<RunOutput>;\n    let llm: Runnable<BaseLanguageModelInput>;\n    if (method === \"jsonMode\") {\n      let outputFormatSchema: JsonSchema7Type | undefined;\n      if (isInteropZodSchema(schema)) {\n        outputParser = StructuredOutputParser.fromZodSchema(schema);\n        outputFormatSchema = toJsonSchema(schema);\n      } else {\n        outputParser = new JsonOutputParser<RunOutput>();\n      }\n      const options = {\n        responseFormat: { type: \"json_object\" },\n        ls_structured_output_format: {\n          kwargs: { method: \"jsonMode\" },\n          schema: outputFormatSchema,\n        },\n      } as Partial<CallOptions>;\n      llm = this.withConfig(options);\n    } else {\n      if (isInteropZodSchema(schema)) {\n        const asJsonSchema = toJsonSchema(schema);\n        llm = this.withConfig({\n          tools: [\n            {\n              type: \"function\" as const,\n              function: {\n                name: functionName,\n                description:\n                  asJsonSchema.description ?? `Tool: ${functionName}`,\n                parameters: asJsonSchema,\n              },\n            },\n          ],\n          // Ideally that would be set to required but this is not supported yet\n          tool_choice: {\n            type: \"function\",\n            function: {\n              name: functionName,\n            },\n          },\n          ls_structured_output_format: {\n            kwargs: { method: \"functionCalling\" },\n            schema: asJsonSchema,\n          },\n        } as Partial<CallOptions>);\n        outputParser = new WatsonxToolsOutputParser({\n          returnSingle: true,\n          keyName: functionName,\n          zodSchema: schema,\n        });\n      } else {\n        let openAIFunctionDefinition: FunctionDefinition;\n        if (\n          typeof schema.name === \"string\" &&\n          typeof schema.parameters === \"object\" &&\n          schema.parameters != null\n        ) {\n          openAIFunctionDefinition = schema as FunctionDefinition;\n          functionName = schema.name;\n        } else {\n          openAIFunctionDefinition = {\n            name: functionName,\n            description: schema.description ?? \"\",\n            parameters: schema,\n          };\n        }\n        llm = this.withConfig({\n          tools: [\n            {\n              type: \"function\" as const,\n              function: openAIFunctionDefinition,\n            },\n          ],\n          tool_choice: {\n            type: \"function\" as const,\n            function: {\n              name: functionName,\n            },\n          },\n          ls_structured_output_format: {\n            kwargs: { method: \"functionCalling\" },\n            schema: toJsonSchema(schema),\n          },\n        } as Partial<CallOptions>);\n        outputParser = new WatsonxToolsOutputParser<RunOutput>({\n          returnSingle: true,\n          keyName: functionName,\n        });\n      }\n    }\n\n    if (!includeRaw) {\n      return llm.pipe(outputParser) as Runnable<\n        BaseLanguageModelInput,\n        RunOutput\n      >;\n    }\n\n    const parserAssign = RunnablePassthrough.assign({\n      // eslint-disable-next-line @typescript-eslint/no-explicit-any\n      parsed: (input: any, config) => outputParser.invoke(input.raw, config),\n    });\n    const parserNone = RunnablePassthrough.assign({\n      parsed: () => null,\n    });\n    const parsedWithFallback = parserAssign.withFallbacks({\n      fallbacks: [parserNone],\n    });\n    return RunnableSequence.from<\n      BaseLanguageModelInput,\n      { raw: BaseMessage; parsed: RunOutput 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