@rama-adi/watsonx-unofficial-ai-provider/dist/index.js

Unofficial Watsonx provider for the Vercel AI SDK

"use strict";
var __defProp = Object.defineProperty;
var __getOwnPropDesc = Object.getOwnPropertyDescriptor;
var __getOwnPropNames = Object.getOwnPropertyNames;
var __hasOwnProp = Object.prototype.hasOwnProperty;
var __export = (target, all) => {
  for (var name in all)
    __defProp(target, name, { get: all[name], enumerable: true });
};
var __copyProps = (to, from, except, desc) => {
  if (from && typeof from === "object" || typeof from === "function") {
    for (let key of __getOwnPropNames(from))
      if (!__hasOwnProp.call(to, key) && key !== except)
        __defProp(to, key, { get: () => from[key], enumerable: !(desc = __getOwnPropDesc(from, key)) || desc.enumerable });
  }
  return to;
};
var __toCommonJS = (mod) => __copyProps(__defProp({}, "__esModule", { value: true }), mod);

// index.ts
var index_exports = {};
__export(index_exports, {
  ChatModelLists: () => ChatModelLists,
  CompletionModelLists: () => CompletionModelLists,
  EmbedingModelLists: () => EmbedingModelLists,
  FunctionCallingModelLists: () => FunctionCallingModelLists,
  VisionModelLists: () => VisionModelLists,
  WatsonxClusters: () => WatsonxClusters,
  createWatsonx: () => createWatsonx,
  watsonx: () => watsonx
});
module.exports = __toCommonJS(index_exports);

// src/provider.ts
var import_provider_utils6 = require("@ai-sdk/provider-utils");

// src/models/chat-models/watsonx-chat-model.ts
var import_provider2 = require("@ai-sdk/provider");
var import_provider_utils3 = require("@ai-sdk/provider-utils");
var import_v44 = require("zod/v4");

// src/models/chat-models/watsonx-chat-finish-reason.ts
function mapWatsonxChatFinishReason(reason) {
  switch (reason) {
    case "stop":
      return "stop";
    case "length":
      return "length";
    case "tool_calls":
      return "tool-calls";
    case "time_limit":
      return "other";
    case "cancelled":
      return "other";
    case "error":
      return "error";
    case null:
    case void 0:
      return "unknown";
    default:
      return "unknown";
  }
}

// src/models/chat-models/convert-to-watsonx-chat-messages.ts
var import_provider = require("@ai-sdk/provider");
var import_provider_utils = require("@ai-sdk/provider-utils");
function convertToWatsonxChatMessages(prompt) {
  const messages = [];
  for (let i = 0; i < prompt.length; i++) {
    const { role, content } = prompt[i];
    const isLastMessage = i === prompt.length - 1;
    switch (role) {
      case "system": {
        messages.push({ role: "system", content });
        break;
      }
      case "user": {
        messages.push({
          role: "user",
          content: content.map((part) => {
            switch (part.type) {
              case "text": {
                return { type: "text", text: part.text };
              }
              case "file": {
                throw new import_provider.UnsupportedFunctionalityError({
                  functionality: "File content in user messages is not supported by watsonx text chat"
                });
              }
            }
          })
        });
        break;
      }
      case "assistant": {
        let text = "";
        const toolCalls = [];
        for (const part of content) {
          switch (part.type) {
            case "text": {
              text += part.text;
              break;
            }
            case "tool-call": {
              toolCalls.push({
                id: part.toolCallId,
                type: "function",
                function: {
                  name: part.toolName,
                  arguments: typeof part.input === "string" ? part.input : JSON.stringify(part.input)
                }
              });
              break;
            }
          }
        }
        messages.push({
          role: "assistant",
          content: text,
          tool_calls: toolCalls.length > 0 ? toolCalls : void 0
        });
        break;
      }
      case "tool": {
        for (const toolResponse of content) {
          let resultContent = "";
          switch (toolResponse.output.type) {
            case "text":
            case "error-text":
              resultContent = toolResponse.output.value;
              break;
            case "json":
            case "error-json":
              resultContent = JSON.stringify(toolResponse.output.value);
              break;
            case "content":
              resultContent = JSON.stringify(toolResponse.output.value);
              break;
          }
          messages.push({
            role: "tool",
            content: resultContent,
            tool_call_id: toolResponse.toolCallId
          });
        }
        break;
      }
      default: {
        throw new Error(`Unsupported role: ${role}`);
      }
    }
  }
  return messages;
}

// src/types/watsonx-response-schema.ts
var import_provider_utils2 = require("@ai-sdk/provider-utils");
var import_v4 = require("zod/v4");
var watsonxErrorResponseSchema = import_v4.z.object({
  errors: import_v4.z.array(
    import_v4.z.object({
      code: import_v4.z.string(),
      message: import_v4.z.string(),
      more_info: import_v4.z.string()
    })
  ),
  trace: import_v4.z.string(),
  status_code: import_v4.z.number()
});
var watsonxFailedResponseHandler = (0, import_provider_utils2.createJsonErrorResponseHandler)({
  errorSchema: watsonxErrorResponseSchema,
  errorToMessage: (data) => [
    "watsonx API encountered error(s):",
    data.errors.map((e) => "- " + e.message),
    "Trace ID: " + data.trace
  ].join("\n")
});

// src/models/chat-models/watsonx-chat-model-settings.ts
var ChatModelLists = {
  "ca-tor": [
    "ibm/granite-3-8b-instruct",
    "meta-llama/llama-3-2-11b-vision-instruct",
    "meta-llama/llama-3-3-70b-instruct"
  ],
  "jp-tok": [
    "ibm/granite-3-8b-instruct",
    "meta-llama/llama-3-2-11b-vision-instruct",
    "meta-llama/llama-3-3-70b-instruct",
    "meta-llama/llama-4-maverick-17b-128e-instruct-fp8",
    "meta-llama/llama-guard-3-11b-vision",
    "mistralai/mistral-medium-2505",
    "mistralai/mistral-small-3-1-24b-instruct-2503"
  ],
  "eu-gb": [
    "ibm/granite-3-8b-instruct",
    "meta-llama/llama-3-2-11b-vision-instruct",
    "meta-llama/llama-3-3-70b-instruct",
    "meta-llama/llama-4-maverick-17b-128e-instruct-fp8"
  ],
  "eu-de": [
    "ibm/granite-3-3-8b-instruct",
    "ibm/granite-3-8b-instruct",
    "meta-llama/llama-3-2-11b-vision-instruct",
    "meta-llama/llama-3-2-90b-vision-instruct",
    "meta-llama/llama-3-3-70b-instruct",
    "meta-llama/llama-4-maverick-17b-128e-instruct-fp8",
    "mistralai/mistral-medium-2505",
    "mistralai/mistral-small-3-1-24b-instruct-2503"
  ],
  "us-south": [
    "ibm/granite-3-2-8b-instruct",
    "ibm/granite-3-3-8b-instruct",
    "ibm/granite-3-8b-instruct",
    "meta-llama/llama-3-2-11b-vision-instruct",
    "meta-llama/llama-3-2-90b-vision-instruct",
    "meta-llama/llama-3-3-70b-instruct",
    "meta-llama/llama-3-405b-instruct",
    "meta-llama/llama-4-maverick-17b-128e-instruct-fp8",
    "meta-llama/llama-guard-3-11b-vision",
    "mistralai/mistral-medium-2505",
    "mistralai/mistral-small-3-1-24b-instruct-2503",
    "openai/gpt-oss-120b"
  ],
  "au-syd": [
    "ibm/granite-3-8b-instruct",
    "meta-llama/llama-3-2-11b-vision-instruct",
    "meta-llama/llama-3-2-90b-vision-instruct",
    "meta-llama/llama-guard-3-11b-vision"
  ]
};
var VisionModelLists = {
  "ca-tor": ["meta-llama/llama-3-2-11b-vision-instruct"],
  "jp-tok": [
    "meta-llama/llama-3-2-11b-vision-instruct",
    "meta-llama/llama-4-maverick-17b-128e-instruct-fp8",
    "meta-llama/llama-guard-3-11b-vision",
    "mistralai/mistral-medium-2505",
    "mistralai/mistral-small-3-1-24b-instruct-2503"
  ],
  "eu-gb": [
    "meta-llama/llama-3-2-11b-vision-instruct",
    "meta-llama/llama-4-maverick-17b-128e-instruct-fp8"
  ],
  "eu-de": [
    "meta-llama/llama-3-2-11b-vision-instruct",
    "meta-llama/llama-3-2-90b-vision-instruct",
    "meta-llama/llama-4-maverick-17b-128e-instruct-fp8",
    "mistralai/mistral-medium-2505",
    "mistralai/mistral-small-3-1-24b-instruct-2503"
  ],
  "us-south": [
    "meta-llama/llama-3-2-11b-vision-instruct",
    "meta-llama/llama-3-2-90b-vision-instruct",
    "meta-llama/llama-4-maverick-17b-128e-instruct-fp8",
    "meta-llama/llama-guard-3-11b-vision",
    "mistralai/mistral-medium-2505",
    "mistralai/mistral-small-3-1-24b-instruct-2503"
  ],
  "au-syd": [
    "meta-llama/llama-3-2-11b-vision-instruct",
    "meta-llama/llama-3-2-90b-vision-instruct",
    "meta-llama/llama-guard-3-11b-vision"
  ]
};
var FunctionCallingModelLists = {
  "ca-tor": [
    "ibm/granite-3-8b-instruct",
    "meta-llama/llama-3-2-11b-vision-instruct",
    "meta-llama/llama-3-3-70b-instruct"
  ],
  "jp-tok": [
    "ibm/granite-3-8b-instruct",
    "meta-llama/llama-3-2-11b-vision-instruct",
    "meta-llama/llama-3-3-70b-instruct",
    "meta-llama/llama-4-maverick-17b-128e-instruct-fp8",
    "mistralai/mistral-medium-2505",
    "mistralai/mistral-small-3-1-24b-instruct-2503"
  ],
  "eu-gb": [
    "ibm/granite-3-8b-instruct",
    "meta-llama/llama-3-2-11b-vision-instruct",
    "meta-llama/llama-3-3-70b-instruct",
    "meta-llama/llama-4-maverick-17b-128e-instruct-fp8"
  ],
  "eu-de": [
    "ibm/granite-3-3-8b-instruct",
    "ibm/granite-3-8b-instruct",
    "meta-llama/llama-3-2-11b-vision-instruct",
    "meta-llama/llama-3-2-90b-vision-instruct",
    "meta-llama/llama-3-3-70b-instruct",
    "meta-llama/llama-4-maverick-17b-128e-instruct-fp8",
    "mistralai/mistral-medium-2505",
    "mistralai/mistral-small-3-1-24b-instruct-2503"
  ],
  "us-south": [
    "ibm/granite-3-2-8b-instruct",
    "ibm/granite-3-3-8b-instruct",
    "ibm/granite-3-8b-instruct",
    "meta-llama/llama-3-2-11b-vision-instruct",
    "meta-llama/llama-3-2-90b-vision-instruct",
    "meta-llama/llama-3-3-70b-instruct",
    "meta-llama/llama-3-405b-instruct",
    "meta-llama/llama-4-maverick-17b-128e-instruct-fp8",
    "mistralai/mistral-medium-2505",
    "mistralai/mistral-small-3-1-24b-instruct-2503",
    "openai/gpt-oss-120b"
  ],
  "au-syd": [
    "ibm/granite-3-8b-instruct",
    "meta-llama/llama-3-2-11b-vision-instruct",
    "meta-llama/llama-3-2-90b-vision-instruct"
  ]
};

// src/models/chat-models/watsonx-chat-schema.ts
var import_v43 = require("zod/v4");

// src/types/watsonx-common-schema.ts
var import_v42 = require("zod/v4");
var WatsonxClusters = [
  "ca-tor",
  "jp-tok",
  "eu-gb",
  "eu-de",
  "us-south",
  "au-syd"
];
var systemDetailsSchema = import_v42.z.object({
  warnings: import_v42.z.array(
    import_v42.z.object({
      message: import_v42.z.string().optional(),
      id: import_v42.z.string().optional(),
      more_info: import_v42.z.string().optional(),
      additional_properties: import_v42.z.record(import_v42.z.string(), import_v42.z.unknown()).optional()
    })
  ).optional()
}).optional();
var watsonxModerationsSchema = import_v42.z.object({
  hap: import_v42.z.object({
    input: import_v42.z.object({
      enabled: import_v42.z.boolean(),
      threshold: import_v42.z.number().min(0).max(1)
    }),
    output: import_v42.z.object({
      enabled: import_v42.z.boolean(),
      threshold: import_v42.z.number().min(0).max(1)
    }),
    mask: import_v42.z.object({
      remove_entity_value: import_v42.z.boolean()
    })
  }),
  pii: import_v42.z.object({
    input: import_v42.z.object({
      enabled: import_v42.z.boolean()
    }),
    output: import_v42.z.object({
      enabled: import_v42.z.boolean()
    }),
    mask: import_v42.z.object({
      remove_entity_value: import_v42.z.boolean()
    })
  })
}).optional();

// src/models/chat-models/watsonx-chat-schema.ts
var watsonxChatChunkSchema = import_v43.z.object({
  id: import_v43.z.string().nullish(),
  model_id: import_v43.z.string().nullish(),
  created: import_v43.z.number().nullish(),
  choices: import_v43.z.array(
    import_v43.z.object({
      delta: import_v43.z.object({
        role: import_v43.z.enum(["assistant"]).optional(),
        content: import_v43.z.string().nullish(),
        tool_calls: import_v43.z.array(
          import_v43.z.object({
            index: import_v43.z.number(),
            id: import_v43.z.string().optional(),
            type: import_v43.z.literal("function").nullish(),
            function: import_v43.z.object({
              name: import_v43.z.string(),
              arguments: import_v43.z.string()
            })
          })
        ).nullish()
      }),
      finish_reason: import_v43.z.enum([
        "stop",
        "length",
        "tool_calls",
        "time_limit",
        "cancelled",
        "error"
      ]).nullish(),
      index: import_v43.z.number()
    })
  ),
  model_version: import_v43.z.string().nullish(),
  created_at: import_v43.z.string().nullish(),
  usage: import_v43.z.object({
    prompt_tokens: import_v43.z.number(),
    completion_tokens: import_v43.z.number(),
    total_tokens: import_v43.z.number()
  }).nullish(),
  system: systemDetailsSchema
});
var watsonxChatResponseSchema = import_v43.z.object({
  id: import_v43.z.string(),
  model_id: import_v43.z.string(),
  created: import_v43.z.number(),
  choices: import_v43.z.array(
    import_v43.z.object({
      message: import_v43.z.object({
        role: import_v43.z.literal("assistant"),
        content: import_v43.z.string().nullish(),
        refusal: import_v43.z.string().nullish(),
        tool_calls: import_v43.z.array(
          import_v43.z.object({
            id: import_v43.z.string(),
            type: import_v43.z.literal("function"),
            function: import_v43.z.object({
              name: import_v43.z.string(),
              arguments: import_v43.z.string()
            })
          })
        ).nullish()
      }),
      index: import_v43.z.number(),
      finish_reason: import_v43.z.enum([
        "stop",
        "length",
        "tool_calls",
        "time_limit",
        "cancelled",
        "error"
      ])
    })
  ),
  model_version: import_v43.z.string().nullish(),
  created_at: import_v43.z.string(),
  usage: import_v43.z.object({
    prompt_tokens: import_v43.z.number(),
    completion_tokens: import_v43.z.number(),
    total_tokens: import_v43.z.number()
  }),
  system: systemDetailsSchema
});

// src/models/chat-models/watsonx-chat-model.ts
var WatsonxChatModel = class {
  specificationVersion = "v2";
  provider;
  defaultObjectGenerationMode = "tool";
  supportsImageUrls = false;
  supportedUrls = {};
  modelId;
  settings;
  config;
  constructor(modelId, settings, config) {
    this.modelId = modelId;
    this.settings = settings;
    this.config = config;
    this.provider = config.provider;
  }
  sanityCheck(options) {
    if (options.tools?.length && !Object.values(FunctionCallingModelLists).some(
      (models) => models.includes(this.modelId)
    )) {
      throw new import_provider2.UnsupportedFunctionalityError({
        functionality: "Tool calling",
        message: `The model ${this.modelId} does not support tool calling`
      });
    }
  }
  getArgs({
    prompt,
    maxOutputTokens,
    temperature,
    topP,
    topK,
    frequencyPenalty,
    presencePenalty,
    stopSequences,
    responseFormat,
    seed,
    tools,
    toolChoice,
    providerOptions
  }) {
    const warnings = [];
    if (topK != null) {
      warnings.push({
        type: "unsupported-setting",
        setting: "topK"
      });
    }
    const requestedN = providerOptions?.watsonx?.n;
    let nArg = void 0;
    if (typeof requestedN === "number") {
      if (requestedN !== 1) {
        warnings.push({ type: "unsupported-setting", setting: "n" });
      }
      nArg = 1;
    }
    const topLogprobs = providerOptions?.watsonx?.topLogprobs;
    const topLogprobsNum = typeof topLogprobs === "number" ? topLogprobs : void 0;
    const requestedLogprobs = providerOptions?.watsonx?.logprobs;
    const requestedLogprobsBool = typeof requestedLogprobs === "boolean" ? requestedLogprobs : void 0;
    const requestedContext = providerOptions?.watsonx?.context;
    const requestedContextStr = typeof requestedContext === "string" ? requestedContext : void 0;
    const baseArgs = {
      temperature,
      model_id: this.modelId,
      project_id: this.config.projectID,
      frequency_penalty: frequencyPenalty,
      // IBM watsonx prefers max_completion_tokens; max_tokens is deprecated
      ...maxOutputTokens != null ? { max_completion_tokens: maxOutputTokens } : {},
      presence_penalty: presencePenalty,
      top_p: topP,
      seed,
      messages: convertToWatsonxChatMessages(prompt),
      time_limit: providerOptions?.watsonx?.timeLimit,
      // OpenAPI optional parameters supported via providerOptions.watsonx
      ...typeof providerOptions?.watsonx?.maxCompletionTokens === "number" ? { max_completion_tokens: providerOptions.watsonx.maxCompletionTokens } : {},
      ...requestedLogprobsBool != null ? { logprobs: requestedLogprobsBool } : topLogprobsNum != null ? { logprobs: true } : {},
      ...topLogprobsNum != null ? { top_logprobs: topLogprobsNum } : {},
      ...providerOptions?.watsonx?.logitBias != null ? { logit_bias: providerOptions.watsonx.logitBias } : {},
      ...nArg != null ? { n: nArg } : {},
      ...providerOptions?.watsonx?.spaceId != null ? { space_id: providerOptions.watsonx.spaceId } : {},
      ...requestedContextStr != null ? { context: requestedContextStr } : {},
      ...stopSequences != null ? { stop: stopSequences } : {}
    };
    if (responseFormat?.type === "json") {
      return {
        args: {
          ...baseArgs,
          response_format: { type: "json_object" }
        },
        warnings
      };
    }
    if (tools && tools.length > 0) {
      const mappedTools = tools.filter((tool) => tool.type === "function").map((tool) => ({
        type: "function",
        function: {
          name: tool.name,
          description: tool.description,
          parameters: tool.inputSchema
        }
      }));
      let tool_choice_option = void 0;
      let tool_choice = void 0;
      if (toolChoice?.type === "tool") {
        tool_choice = {
          type: "function",
          function: {
            name: toolChoice.toolName
          }
        };
      } else if (toolChoice?.type === "auto") {
        tool_choice_option = "auto";
      } else if (toolChoice?.type === "required") {
        if (mappedTools.length === 1) {
          tool_choice = {
            type: "function",
            function: { name: mappedTools[0].function.name }
          };
        } else {
          warnings.push({
            type: "unsupported-setting",
            setting: "toolChoice.required"
          });
          tool_choice_option = "auto";
        }
      }
      return {
        args: {
          ...baseArgs,
          tools: mappedTools,
          tool_choice_option,
          tool_choice
        },
        warnings
      };
    }
    return {
      args: baseArgs,
      warnings
    };
  }
  async doGenerate(options) {
    this.sanityCheck(options);
    const { args, warnings } = this.getArgs(options);
    const { value: response, responseHeaders } = await (0, import_provider_utils3.postJsonToApi)({
      url: `${this.config.clusterURL}/text/chat?version=${this.config.version}`,
      headers: (0, import_provider_utils3.combineHeaders)(this.config.headers(), options.headers),
      body: args,
      failedResponseHandler: watsonxFailedResponseHandler,
      successfulResponseHandler: (0, import_provider_utils3.createJsonResponseHandler)(
        watsonxChatResponseSchema
      ),
      abortSignal: options.abortSignal,
      fetch: this.config.fetch
    });
    const choice = response.choices[0];
    if (!choice) {
      throw new Error("No choice in response");
    }
    const content = [];
    if (choice.message.content) {
      content.push({
        type: "text",
        text: choice.message.content
      });
    }
    if (choice.message.tool_calls) {
      for (const toolCall of choice.message.tool_calls) {
        content.push({
          type: "tool-call",
          toolCallId: toolCall.id,
          toolName: toolCall.function.name,
          input: toolCall.function.arguments
        });
      }
    }
    return {
      content,
      finishReason: mapWatsonxChatFinishReason(choice.finish_reason),
      usage: {
        inputTokens: response.usage.prompt_tokens,
        outputTokens: response.usage.completion_tokens,
        totalTokens: response.usage.total_tokens
      },
      warnings,
      request: { body: args },
      response: {
        id: response.id,
        modelId: response.model_id,
        headers: responseHeaders
      }
    };
  }
  async doStream(options) {
    this.sanityCheck(options);
    const { args, warnings } = this.getArgs(options);
    const url = `${this.config.clusterURL}/text/chat_stream?version=${this.config.version}`;
    const body = { ...args };
    const { value: response, responseHeaders } = await (0, import_provider_utils3.postJsonToApi)({
      url,
      headers: (0, import_provider_utils3.combineHeaders)(this.config.headers(), options.headers),
      body,
      failedResponseHandler: watsonxFailedResponseHandler,
      successfulResponseHandler: (0, import_provider_utils3.createEventSourceResponseHandler)(
        watsonxChatChunkSchema
      ),
      abortSignal: options.abortSignal,
      fetch: this.config.fetch
    });
    const toolCalls = [];
    let finishReason = "other";
    const usage = {
      inputTokens: Number.NaN,
      outputTokens: Number.NaN,
      totalTokens: Number.NaN
    };
    let chunkNumber = 0;
    let textStarted = false;
    let textId;
    let watsonxResponseId;
    let trimLeadingSpace = false;
    return {
      stream: response.pipeThrough(
        new TransformStream({
          transform(chunk, controller) {
            if (!chunk.success) {
              finishReason = "error";
              controller.enqueue({ type: "error", error: chunk.error });
              return;
            }
            chunkNumber++;
            const value = chunk.value;
            if (value.id) {
              watsonxResponseId = value.id;
              controller.enqueue({
                type: "response-metadata",
                id: value.id
              });
            }
            if (value.model_id) {
              controller.enqueue({
                type: "response-metadata",
                modelId: value.model_id
              });
            }
            if (value.usage != null) {
              usage.inputTokens = value.usage.prompt_tokens;
              usage.outputTokens = value.usage.completion_tokens;
              usage.totalTokens = value.usage.total_tokens;
            }
            const choice = value.choices[0];
            if (!choice) {
              return;
            }
            if (choice?.finish_reason != null) {
              finishReason = mapWatsonxChatFinishReason(choice.finish_reason);
            }
            if (choice?.delta == null) {
              return;
            }
            const delta = choice.delta;
            const textContent = delta.content ?? "";
            if (chunkNumber <= 2) {
              const messages = convertToWatsonxChatMessages(options.prompt);
              const lastMessage = messages[messages.length - 1];
              if (lastMessage?.role === "assistant" && lastMessage.content && textContent === lastMessage.content.trimEnd()) {
                if (textContent.length < lastMessage.content.length) {
                  trimLeadingSpace = true;
                }
                return;
              }
            }
            if (textContent != null && textContent !== "") {
              if (!textStarted) {
                textId = watsonxResponseId || (0, import_provider_utils3.generateId)();
                controller.enqueue({
                  type: "text-start",
                  id: textId
                });
                textStarted = true;
              }
              controller.enqueue({
                type: "text-delta",
                delta: trimLeadingSpace ? textContent.trimStart() : textContent,
                id: textId || (0, import_provider_utils3.generateId)()
              });
              trimLeadingSpace = false;
            }
            if (delta.tool_calls != null) {
              for (const toolCallDelta of delta.tool_calls) {
                const index = toolCallDelta.index ?? toolCalls.length - 1;
                if (toolCalls[index] == null) {
                  if (toolCallDelta.type !== "function") {
                    throw new import_provider2.InvalidResponseDataError({
                      data: toolCallDelta,
                      message: `Expected 'function' type.`
                    });
                  }
                  const toolCallId = toolCallDelta.id ?? (0, import_provider_utils3.generateId)();
                  if (toolCallDelta.function?.name == null) {
                    throw new import_provider2.InvalidResponseDataError({
                      data: toolCallDelta,
                      message: `Expected 'function.name' to be a string.`
                    });
                  }
                  toolCalls[index] = {
                    id: toolCallId,
                    type: "function",
                    function: {
                      name: toolCallDelta.function.name,
                      arguments: toolCallDelta.function.arguments ?? ""
                    },
                    inputStarted: false,
                    sent: false
                  };
                  const toolCall2 = toolCalls[index];
                  if (toolCall2 == null) {
                    throw new Error("Tool call is missing");
                  }
                  if (toolCall2.function?.name != null && toolCall2.function?.arguments != null && (0, import_provider_utils3.isParsableJson)(toolCall2.function.arguments)) {
                    toolCall2.inputStarted = true;
                    controller.enqueue({
                      type: "tool-input-start",
                      id: toolCall2.id,
                      toolName: toolCall2.function.name
                    });
                    controller.enqueue({
                      type: "tool-input-delta",
                      id: toolCall2.id,
                      delta: toolCall2.function.arguments
                    });
                    controller.enqueue({
                      type: "tool-input-end",
                      id: toolCall2.id
                    });
                    controller.enqueue({
                      type: "tool-call",
                      toolCallId: toolCall2.id,
                      toolName: toolCall2.function.name,
                      input: toolCall2.function.arguments
                    });
                    toolCall2.sent = true;
                  }
                  continue;
                }
                const toolCall = toolCalls[index];
                if (toolCall == null) {
                  throw new Error("Tool call is missing");
                }
                if (!toolCall.inputStarted) {
                  toolCall.inputStarted = true;
                  controller.enqueue({
                    type: "tool-input-start",
                    id: toolCall.id,
                    toolName: toolCall.function.name
                  });
                }
                if (toolCallDelta.function?.arguments != null) {
                  toolCall.function.arguments += toolCallDelta.function?.arguments ?? "";
                }
                controller.enqueue({
                  type: "tool-input-delta",
                  id: toolCall.id,
                  delta: toolCallDelta.function.arguments ?? ""
                });
                if (toolCall.function?.name != null && toolCall.function?.arguments != null && (0, import_provider_utils3.isParsableJson)(toolCall.function.arguments)) {
                  controller.enqueue({
                    type: "tool-call",
                    toolCallId: toolCall.id ?? (0, import_provider_utils3.generateId)(),
                    toolName: toolCall.function.name,
                    input: toolCall.function.arguments
                  });
                  toolCall.sent = true;
                }
              }
            }
          },
          flush(controller) {
            if (finishReason === "tool-calls") {
              for (const toolCall of toolCalls) {
                if (toolCall && !toolCall.sent) {
                  controller.enqueue({
                    type: "tool-call",
                    toolCallId: toolCall.id ?? (0, import_provider_utils3.generateId)(),
                    toolName: toolCall.function.name,
                    // Coerce invalid arguments to an empty JSON object
                    input: (0, import_provider_utils3.isParsableJson)(toolCall.function.arguments) ? toolCall.function.arguments : "{}"
                  });
                  toolCall.sent = true;
                }
              }
            }
            if (textStarted) {
              controller.enqueue({
                type: "text-end",
                id: textId || (0, import_provider_utils3.generateId)()
              });
            }
            controller.enqueue({
              type: "finish",
              finishReason,
              usage
            });
          }
        })
      ),
      warnings,
      request: { body },
      response: { headers: responseHeaders }
    };
  }
};

// src/models/embedding-models/watsonx-embedding-model.ts
var import_provider3 = require("@ai-sdk/provider");
var import_provider_utils4 = require("@ai-sdk/provider-utils");
var import_v45 = require("zod/v4");
var WatsonxEmbeddingModel = class {
  config;
  specificationVersion = "v2";
  modelId;
  settings;
  get provider() {
    return this.config.provider;
  }
  get maxEmbeddingsPerCall() {
    return this.settings.maxEmbeddingsPerCall ?? 32;
  }
  get supportsParallelCalls() {
    return this.settings.supportsParallelCalls ?? false;
  }
  constructor(modelId, settings, config) {
    this.modelId = modelId;
    this.settings = settings;
    this.config = config;
  }
  #WatsonxTextEmbeddingResponseSchema = import_v45.z.object({
    model_id: import_v45.z.string(),
    results: import_v45.z.array(
      import_v45.z.object({
        embedding: import_v45.z.array(import_v45.z.number()),
        input: import_v45.z.object({
          text: import_v45.z.string()
        }).nullish()
      })
    ),
    created_at: import_v45.z.string(),
    input_token_count: import_v45.z.number(),
    system: systemDetailsSchema
  });
  async doEmbed({
    values,
    abortSignal,
    headers
  }) {
    if (values.length > this.maxEmbeddingsPerCall) {
      throw new import_provider3.TooManyEmbeddingValuesForCallError({
        provider: this.provider,
        modelId: this.modelId,
        maxEmbeddingsPerCall: this.maxEmbeddingsPerCall,
        values
      });
    }
    const { responseHeaders, value: response } = await (0, import_provider_utils4.postJsonToApi)({
      url: `${this.config.clusterURL}/text/embeddings?version=${this.config.version}`,
      headers: (0, import_provider_utils4.combineHeaders)(this.config.headers(), headers),
      body: {
        model_id: this.modelId,
        project_id: this.config.projectID,
        inputs: values,
        encoding_format: "float",
        ...this.settings.truncate_input_tokens != null || this.settings.return_options != null ? {
          parameters: {
            ...this.settings.truncate_input_tokens != null ? {
              truncate_input_tokens: this.settings.truncate_input_tokens
            } : {},
            ...this.settings.return_options != null ? { return_options: this.settings.return_options } : {}
          }
        } : {}
      },
      failedResponseHandler: watsonxFailedResponseHandler,
      successfulResponseHandler: (0, import_provider_utils4.createJsonResponseHandler)(
        this.#WatsonxTextEmbeddingResponseSchema
      ),
      abortSignal,
      fetch: this.config.fetch
    });
    return {
      embeddings: response.results.map((r) => r.embedding),
      usage: {
        tokens: response.input_token_count
      },
      response: { headers: responseHeaders }
    };
  }
};

// src/models/completion-models/watsonx-completion-model.ts
var import_provider5 = require("@ai-sdk/provider");
var import_provider_utils5 = require("@ai-sdk/provider-utils");
var import_v47 = require("zod/v4");

// src/models/completion-models/convert-to-watsonx-completion.ts
var import_provider4 = require("@ai-sdk/provider");
function convertToWatsonxCompletion({
  prompt,
  inputFormat,
  user = "user",
  assistant = "assistant"
}) {
  if (inputFormat === "prompt" && prompt.length === 1 && prompt[0].role === "user" && prompt[0].content.length === 1 && prompt[0].content[0].type === "text") {
    return { prompt: prompt[0].content[0].text };
  }
  let text = "";
  if (prompt[0].role === "system") {
    text += `${prompt[0].content}

`;
    prompt = prompt.slice(1);
  }
  for (const { role, content } of prompt) {
    switch (role) {
      case "system": {
        throw new import_provider4.InvalidPromptError({
          message: "Unexpected system message in prompt: ${content}",
          prompt
        });
      }
      case "user": {
        const userMessage = content.map((part) => {
          switch (part.type) {
            case "text": {
              return part.text;
            }
            case "file": {
              throw new import_provider4.UnsupportedFunctionalityError({
                functionality: "file"
              });
            }
          }
        }).join("");
        text += `${user}:
${userMessage}

`;
        break;
      }
      case "assistant": {
        const assistantMessage = content.map((part) => {
          switch (part.type) {
            case "text": {
              return part.text;
            }
            case "tool-call": {
              throw new import_provider4.UnsupportedFunctionalityError({
                functionality: "tool-call messages"
              });
            }
          }
        }).join("");
        text += `${assistant}:
${assistantMessage}

`;
        break;
      }
      case "tool": {
        throw new import_provider4.UnsupportedFunctionalityError({
          functionality: "tool messages"
        });
      }
      default: {
        throw new Error(`Unsupported role: ${role}`);
      }
    }
  }
  text += `${assistant}:
`;
  return {
    prompt: text,
    stopSequences: [`
${user}:`]
  };
}

// src/models/completion-models/watsonx-completion-schema.ts
var import_v46 = require("zod/v4");
var textgenTokenInfo = import_v46.z.array(
  import_v46.z.object({
    text: import_v46.z.string(),
    logprob: import_v46.z.number(),
    rank: import_v46.z.number(),
    top_tokens: import_v46.z.array(
      import_v46.z.object({
        text: import_v46.z.string(),
        logprob: import_v46.z.number()
      })
    )
  })
);
var watsonxCompletionChunkSchema = import_v46.z.object({
  id: import_v46.z.string().nullish(),
  model_id: import_v46.z.string().nullish(),
  created: import_v46.z.number().nullish(),
  results: import_v46.z.array(
    import_v46.z.object({
      generated_text: import_v46.z.string(),
      stop_reason: import_v46.z.string(),
      generated_token_count: import_v46.z.number().nullish(),
      input_token_count: import_v46.z.number().nullish(),
      seed: import_v46.z.number().nullish(),
      generated_tokens: textgenTokenInfo.optional(),
      input_tokens: textgenTokenInfo.optional(),
      moderations: watsonxModerationsSchema
    })
  ),
  model_version: import_v46.z.string().nullish(),
  created_at: import_v46.z.string().nullish(),
  usage: import_v46.z.object({
    prompt_tokens: import_v46.z.number(),
    completion_tokens: import_v46.z.number(),
    total_tokens: import_v46.z.number()
  }).nullish(),
  system: systemDetailsSchema
});
var watsonxCompletionResponseSchema = import_v46.z.object({
  id: import_v46.z.string().nullish(),
  model_id: import_v46.z.string(),
  model_version: import_v46.z.string().nullish(),
  created_at: import_v46.z.string(),
  results: import_v46.z.array(
    import_v46.z.object({
      generated_text: import_v46.z.string(),
      stop_reason: import_v46.z.string(),
      generated_token_count: import_v46.z.number(),
      input_token_count: import_v46.z.number(),
      seed: import_v46.z.number().nullish(),
      generated_tokens: textgenTokenInfo.optional(),
      input_tokens: textgenTokenInfo.optional(),
      moderations: watsonxModerationsSchema
    })
  ),
  usage: import_v46.z.object({
    prompt_tokens: import_v46.z.number(),
    completion_tokens: import_v46.z.number(),
    total_tokens: import_v46.z.number()
  }).nullish(),
  system: systemDetailsSchema
});

// src/models/completion-models/watsonx-completion-finish-reason.ts
function mapWatsonxCompletionFinishReason(reason) {
  switch (reason) {
    case "not_finished":
      return "other";
    case "max_tokens":
    case "token_limit":
      return "length";
    case "eos_token":
    case "stop_sequence":
      return "stop";
    case "cancelled":
      return "stop";
    case "time_limit":
      return "unknown";
    case "error":
      return "error";
    case null:
    case void 0:
      return "unknown";
    default:
      return "unknown";
  }
}

// src/models/completion-models/watsonx-completion-model.ts
var WatsonxCompletionModel = class {
  specificationVersion = "v2";
  provider;
  defaultObjectGenerationMode = void 0;
  supportsImageUrls = false;
  supportedUrls = {};
  modelId;
  settings;
  config;
  constructor(modelId, settings, config) {
    this.modelId = modelId;
    this.settings = settings;
    this.config = config;
    this.provider = config.provider;
  }
  getArgs(options) {
    const {
      prompt,
      maxOutputTokens,
      temperature,
      topP,
      topK,
      frequencyPenalty,
      presencePenalty,
      stopSequences: userStopSequences,
      responseFormat,
      seed,
      providerOptions
    } = options;
    const warnings = [];
    if (responseFormat != null && responseFormat.type !== "text") {
      warnings.push({
        type: "unsupported-setting",
        setting: "responseFormat"
      });
    }
    const { prompt: completionPrompt, stopSequences } = convertToWatsonxCompletion({
      prompt,
      inputFormat: "prompt"
    });
    const stop = [...stopSequences ?? [], ...userStopSequences ?? []];
    const baseArgs = {
      model_id: this.modelId,
      project_id: this.config.projectID,
      input: completionPrompt,
      parameters: {
        // sampling & decoding
        decoding_method: this.settings.decodingMethod ?? "greedy",
        temperature,
        top_p: topP,
        top_k: topK,
        // penalties and limits
        frequency_penalty: frequencyPenalty,
        presence_penalty: presencePenalty,
        max_new_tokens: maxOutputTokens ?? this.settings.maxNewTokens,
        min_new_tokens: this.settings.minNewTokens,
        // control & misc
        stop_sequences: stop,
        random_seed: seed,
        time_limit: providerOptions?.watsonx?.timeLimit,
        ...this.settings.textgenLengthPenalty !== void 0 ? {
          length_penalty: {
            decay_factor: this.settings.textgenLengthPenalty.decayFactor,
            start_index: this.settings.textgenLengthPenalty.startIndex
          }
        } : {}
      },
      return_options: {
        input_text: this.settings.returnOptions?.inputText ?? false,
        generated_tokens: this.settings.returnOptions?.generatedTokens ?? false
      }
    };
    return { args: baseArgs, warnings };
  }
  async doGenerate(options) {
    const { args, warnings } = this.getArgs(options);
    const {
      responseHeaders,
      value: response,
      rawValue: rawResponse
    } = await (0, import_provider_utils5.postJsonToApi)({
      url: `${this.config.clusterURL}/text/generation?version=${this.config.version}`,
      headers: (0, import_provider_utils5.combineHeaders)(this.config.headers(), options.headers),
      body: args,
      failedResponseHandler: watsonxFailedResponseHandler,
      successfulResponseHandler: (0, import_provider_utils5.createJsonResponseHandler)(
        watsonxCompletionResponseSchema
      ),
      abortSignal: options.abortSignal,
      fetch: this.config.fetch
    });
    const { messages: rawPrompt, ...rawSettings } = args;
    const choice = response.results[0];
    if (!choice) {
      throw new Error("No choice in response");
    }
    return {
      content: [
        {
          type: "text",
          text: choice.generated_text
        }
      ],
      finishReason: mapWatsonxCompletionFinishReason(choice.stop_reason),
      usage: {
        inputTokens: response.usage?.prompt_tokens ?? NaN,
        outputTokens: response.usage?.completion_tokens ?? NaN,
        totalTokens: (response.usage?.prompt_tokens ?? 0) + (response.usage?.completion_tokens ?? 0)
      },
      warnings,
      request: { body: args },
      response: {
        id: (0, import_provider_utils5.generateId)(),
        modelId: response.model_id,
        headers: responseHeaders,
        body: rawResponse
      }
    };
  }
  async doStream(options) {
    const url = `${this.config.clusterURL}/text/generation_stream?version=${this.config.version}`;
    const { args, warnings } = this.getArgs(options);
    const body = {
      ...args,
      stream: true
    };
    const { value: response, responseHeaders } = await (0, import_provider_utils5.postJsonToApi)({
      url,
      headers: (0, import_provider_utils5.combineHeaders)(this.config.headers(), options.headers),
      body,
      failedResponseHandler: watsonxFailedResponseHandler,
      successfulResponseHandler: (0, import_provider_utils5.createEventSourceResponseHandler)(
        watsonxCompletionChunkSchema
      ),
      abortSignal: options.abortSignal,
      fetch: this.config.fetch
    });
    let finishReason = "other";
    let usage = {
      inputTokens: Number.NaN,
      outputTokens: Number.NaN,
      totalTokens: Number.NaN
    };
    let isFirstChunk = true;
    return {
      stream: response.pipeThrough(
        new TransformStream({
          transform(chunk, controller) {
            if (!chunk.success) {
              finishReason = "error";
              controller.enqueue({ type: "error", error: chunk.error });
              return;
            }
            const value = chunk.value;
            if ("error" in value) {
              finishReason = "error";
              controller.enqueue({ type: "error", error: value.error });
              return;
            }
            if (isFirstChunk) {
              isFirstChunk = false;
              controller.enqueue({
                type: "response-metadata",
                id: value.id ?? (0, import_provider_utils5.generateId)(),
                modelId: value.model_id ?? void 0,
                timestamp: value.created != null ? new Date(value.created * 1e3) : void 0
              });
            }
            if (value.usage != null) {
              usage = {
                inputTokens: value.usage.prompt_tokens,
                outputTokens: value.usage.completion_tokens,
                totalTokens: value.usage.prompt_tokens + value.usage.completion_tokens
              };
            }
            const choice = value.results[0];
            if (choice?.stop_reason != null) {
              finishReason = mapWatsonxCompletionFinishReason(
                choice.stop_reason
              );
            }
            if (choice?.generated_text != null) {
              controller.enqueue({
                type: "text-delta",
                id: (0, import_provider_utils5.generateId)(),
                delta: choice.generated_text
              });
            }
          },
          flush(controller) {
            controller.enqueue({
              type: "finish",
              finishReason,
              usage
            });
          }
        })
      ),
      warnings,
      request: { body },
      response: { headers: responseHeaders }
    };
  }
};

// src/provider.ts
function createWatsonx(options = {}) {
  const clusterURL = (0, import_provider_utils6.loadOptionalSetting)({
    settingValue: options.clusterURL,
    environmentVariableName: "WATSONX_CLUSTER_URL"
  }) ?? (() => {
    const cluster = (0, import_provider_utils6.loadSetting)({
      settingValue: options.cluster,
      settingName: "cluster",
      environmentVariableName: "WATSONX_CLUSTER",
      description: "The IBM watsonx Cluster"
    });
    return `${(0, import_provider_utils6.withoutTrailingSlash)(`https://${cluster}.ml.cloud.ibm.com`)}/ml/v1`;
  })();
  const projectID = (0, import_provider_utils6.loadSetting)({
    settingValue: options.projectID,
    settingName: "projectID",
    environmentVariableName: "WATSONX_PROJECT_ID",
    description: "The IBM watsonx Project ID"
  });
  const getHeaders = () => ({
    Authorization: `Bearer ${(0, import_provider_utils6.loadApiKey)({
      apiKey: options.bearerToken,
      environmentVariableName: "WATSONX_BEARER_TOKEN",
      description: "Watsonx"
    })}`,
    ...options.headers
  });
  const createChatModel = (modelId, settings = {}) => new WatsonxChatModel(modelId, settings, {
    provider: "watsonx.chat",
    clusterURL,
    projectID,
    headers: getHeaders,
    fetch: options.fetch,
    version: "2024-02-13"
  });
  const createEmbeddingModel = (modelId, settings = {}) => new WatsonxEmbeddingModel(modelId, settings, {
    provider: "watsonx.embedding",
    clusterURL,
    projectID,
    headers: getHeaders,
    fetch: options.fetch,
    version: "2024-02-13"
  });
  const createCompletionModel = (modelId, settings = {}) => new WatsonxCompletionModel(modelId, settings, {
    provider: "watsonx.completion",
    clusterURL,
    projectID,
    headers: getHeaders,
    fetch: options.fetch,
    version: "2024-02-13"
  });
  const provider = function(modelId, settings) {
    if (new.target) {
      throw new Error(
        "The watsonx model function cannot be called with the new keyword."
      );
    }
    return createChatModel(modelId, settings);
  };
  provider.languageModel = (modelId, settings) => createChatModel(modelId, settings);
  provider.embedding = (modelId, settings) => createEmbeddingModel(modelId, settings);
  provider.textEmbeddingModel = (modelId, settings) => createEmbeddingModel(modelId, settings);
  provider.textEmbedding = (modelId, settings) => createEmbeddingModel(modelId, settings);
  provider.completion = (modelId, settings) => createCompletionModel(modelId, settings);
  provider.imageModel = () => {
    throw new Error("Image models are not supported by watsonx provider");
  };
  return provider;
}
var watsonx = createWatsonx();

// src/models/embedding-models/watsonx-embedding-model-settings.ts
var EmbedingModelLists = {
  "ca-tor": [
    "ibm/granite-embedding-278m-multilingual",
    "ibm/slate-125m-english-rtrvr-v2",
    "ibm/slate-30m-english-rtrvr-v2",
    "intfloat/multilingual-e5-large"
  ],
  "jp-tok": [
    "ibm/granite-embedding-278m-multilingual",
    "ibm/slate-125m-english-rtrvr-v2",
    "ibm/slate-30m-english-rtrvr-v2",
    "intfloat/multilingual-e5-large",
    "sentence-transformers/all-minilm-l6-v2"
  ],
  "eu-gb": [
    "ibm/granite-embedding-278m-multilingual",
    "ibm/slate-125m-english-rtrvr-v2",
    "ibm/slate-30m-english-rtrvr-v2",
    "intfloat/multilingual-e5-large",
    "sentence-transformers/all-minilm-l6-v2"
  ],
  "eu-de": [
    "ibm/granite-embedding-278m-multilingual",
    "ibm/slate-125m-english-rtrvr-v2",
    "ibm/slate-30m-english-rtrvr-v2",
    "intfloat/multilingual-e5-large",
    "sentence-transformers/all-minilm-l6-v2"
  ],
  "us-south": [
    "ibm/granite-embedding-278m-multilingual",
    "ibm/slate-125m-english-rtrvr-v2",
    "ibm/slate-30m-english-rtrvr-v2",
    "intfloat/multilingual-e5-large",
    "sentence-transformers/all-minilm-l6-v2"
  ],
  "au-syd": [
    "ibm/slate-125m-english-rtrvr-v2",
    "ibm/slate-30m-english-rtrvr-v2",
    "intfloat/multilingual-e5-large"
  ]
};

// src/models/completion-models/watsonx-completion-model-settings.ts
var CompletionModelLists = {
  "ca-tor": [],
  "jp-tok": [],
  "eu-gb": [],
  "eu-de": ["sdaia/allam-1-13b-instruct"],
  "us-south": ["ibm/granite-8b-code-instruct"],
  "au-syd": ["ibm/granite-8b-code-instruct"]
};
// Annotate the CommonJS export names for ESM import in node:
0 && (module.exports = {
  ChatModelLists,
  CompletionModelLists,
  EmbedingModelLists,
  FunctionCallingModelLists,
  VisionModelLists,
  WatsonxClusters,
  createWatsonx,
  watsonx
});
//# sourceMappingURL=index.js.map