anthropic-vertex-ai/dist/index.js

[nalaso/anthropic-vertex-ai](https://github.com/nalaso/anthropic-vertex-ai) is a community provider that uses Anthropic models through Vertex AI to provide language model support 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);

// src/index.ts
var src_exports = {};
__export(src_exports, {
  anthropicVertex: () => anthropicVertex,
  createAnthropicVertex: () => createAnthropicVertex
});
module.exports = __toCommonJS(src_exports);

// src/anthropic-vertex-provider.ts
var import_provider_utils4 = require("@ai-sdk/provider-utils");
var import_google_auth_library = require("google-auth-library");

// src/anthropic-messages-language-model.ts
var import_provider2 = require("@ai-sdk/provider");
var import_provider_utils3 = require("@ai-sdk/provider-utils");
var import_zod2 = require("zod");

// src/anthropic-error.ts
var import_provider_utils = require("@ai-sdk/provider-utils");
var import_zod = require("zod");
var anthropicErrorDataSchema = import_zod.z.object({
  type: import_zod.z.literal("error"),
  error: import_zod.z.object({
    type: import_zod.z.string(),
    message: import_zod.z.string()
  })
});
var anthropicFailedResponseHandler = (0, import_provider_utils.createJsonErrorResponseHandler)({
  errorSchema: anthropicErrorDataSchema,
  errorToMessage: (data) => data.error.message
});

// src/convert-to-anthropic-messages-prompt.ts
var import_provider = require("@ai-sdk/provider");
var import_provider_utils2 = require("@ai-sdk/provider-utils");
function convertToAnthropicMessagesPrompt(prompt) {
  var _a;
  const blocks = groupIntoBlocks(prompt);
  let system = void 0;
  const messages = [];
  for (let i = 0; i < blocks.length; i++) {
    const block = blocks[i];
    const type = block.type;
    switch (type) {
      case "system": {
        if (system != null) {
          throw new import_provider.UnsupportedFunctionalityError({
            functionality: "Multiple system messages that are separated by user/assistant messages"
          });
        }
        system = block.messages.map(({ content }) => content).join("\n");
        break;
      }
      case "user": {
        const anthropicContent = [];
        for (const { role, content } of block.messages) {
          switch (role) {
            case "user": {
              for (const part of content) {
                switch (part.type) {
                  case "text": {
                    anthropicContent.push({ type: "text", text: part.text });
                    break;
                  }
                  case "image": {
                    if (part.image instanceof URL) {
                      throw new import_provider.UnsupportedFunctionalityError({
                        functionality: "Image URLs in user messages"
                      });
                    }
                    anthropicContent.push({
                      type: "image",
                      source: {
                        type: "base64",
                        media_type: (_a = part.mimeType) != null ? _a : "image/jpeg",
                        data: (0, import_provider_utils2.convertUint8ArrayToBase64)(part.image)
                      }
                    });
                    break;
                  }
                }
              }
              break;
            }
            case "tool": {
              for (const part of content) {
                anthropicContent.push({
                  type: "tool_result",
                  tool_use_id: part.toolCallId,
                  content: JSON.stringify(part.result),
                  is_error: part.isError
                });
              }
              break;
            }
            default: {
              const _exhaustiveCheck = role;
              throw new Error(`Unsupported role: ${_exhaustiveCheck}`);
            }
          }
        }
        messages.push({ role: "user", content: anthropicContent });
        break;
      }
      case "assistant": {
        if (block.messages.length > 1) {
          throw new import_provider.UnsupportedFunctionalityError({
            functionality: "Multiple assistant messages in block"
          });
        }
        const { content } = block.messages[0];
        messages.push({
          role: "assistant",
          content: content.map((part, j) => {
            switch (part.type) {
              case "text": {
                if (i === blocks.length - 1 && j === block.messages.length - 1) {
                  return { type: "text", text: part.text.trim() };
                }
                return { type: "text", text: part.text };
              }
              case "tool-call": {
                return {
                  type: "tool_use",
                  id: part.toolCallId,
                  name: part.toolName,
                  input: part.args
                };
              }
            }
          })
        });
        break;
      }
      default: {
        const _exhaustiveCheck = type;
        throw new Error(`Unsupported type: ${_exhaustiveCheck}`);
      }
    }
  }
  return {
    system,
    messages
  };
}
function groupIntoBlocks(prompt) {
  const blocks = [];
  let currentBlock = void 0;
  for (const { role, content } of prompt) {
    switch (role) {
      case "system": {
        if ((currentBlock == null ? void 0 : currentBlock.type) !== "system") {
          currentBlock = { type: "system", messages: [] };
          blocks.push(currentBlock);
        }
        currentBlock.messages.push({ role, content });
        break;
      }
      case "assistant": {
        if ((currentBlock == null ? void 0 : currentBlock.type) !== "assistant") {
          currentBlock = { type: "assistant", messages: [] };
          blocks.push(currentBlock);
        }
        currentBlock.messages.push({ role, content });
        break;
      }
      case "user": {
        if ((currentBlock == null ? void 0 : currentBlock.type) !== "user") {
          currentBlock = { type: "user", messages: [] };
          blocks.push(currentBlock);
        }
        currentBlock.messages.push({ role, content });
        break;
      }
      case "tool": {
        if ((currentBlock == null ? void 0 : currentBlock.type) !== "user") {
          currentBlock = { type: "user", messages: [] };
          blocks.push(currentBlock);
        }
        currentBlock.messages.push({ role, content });
        break;
      }
      default: {
        const _exhaustiveCheck = role;
        throw new Error(`Unsupported role: ${_exhaustiveCheck}`);
      }
    }
  }
  return blocks;
}

// src/map-anthropic-stop-reason.ts
function mapAnthropicStopReason(finishReason) {
  switch (finishReason) {
    case "end_turn":
    case "stop_sequence":
      return "stop";
    case "tool_use":
      return "tool-calls";
    case "max_tokens":
      return "length";
    default:
      return "other";
  }
}

// src/anthropic-messages-language-model.ts
var AnthropicMessagesLanguageModel = class {
  constructor(modelId, settings, config) {
    this.specificationVersion = "v1";
    this.defaultObjectGenerationMode = "tool";
    this.supportsImageUrls = false;
    this.defaultVersion = "vertex-2023-10-16";
    this.modelId = modelId;
    this.settings = settings;
    this.config = config;
    this.path = `/projects/${config.projectId}/locations/${config.region}/publishers/anthropic/models/${modelId}`;
  }
  get provider() {
    return this.config.provider;
  }
  async getArgs({
    mode,
    prompt,
    maxTokens,
    temperature,
    topP,
    topK,
    frequencyPenalty,
    presencePenalty,
    stopSequences,
    responseFormat,
    seed
  }) {
    const type = mode.type;
    const warnings = [];
    if (frequencyPenalty != null) {
      warnings.push({
        type: "unsupported-setting",
        setting: "frequencyPenalty"
      });
    }
    if (presencePenalty != null) {
      warnings.push({
        type: "unsupported-setting",
        setting: "presencePenalty"
      });
    }
    if (seed != null) {
      warnings.push({
        type: "unsupported-setting",
        setting: "seed"
      });
    }
    if (responseFormat != null && responseFormat.type !== "text") {
      warnings.push({
        type: "unsupported-setting",
        setting: "responseFormat",
        details: "JSON response format is not supported."
      });
    }
    const messagesPrompt = convertToAnthropicMessagesPrompt(prompt);
    const baseArgs = {
      anthropic_version: this.defaultVersion,
      // model specific settings:
      top_k: topK != null ? topK : this.settings.topK,
      // standardized settings:
      max_tokens: maxTokens != null ? maxTokens : 4096,
      // 4096: max model output tokens
      temperature,
      top_p: topP,
      stop_sequences: stopSequences,
      // prompt:
      system: messagesPrompt.system,
      messages: messagesPrompt.messages
    };
    switch (type) {
      case "regular": {
        return {
          args: { ...baseArgs, ...prepareToolsAndToolChoice(mode) },
          warnings
        };
      }
      case "object-json": {
        throw new import_provider2.UnsupportedFunctionalityError({
          functionality: "json-mode object generation"
        });
      }
      case "object-tool": {
        const { name, description, parameters } = mode.tool;
        return {
          args: {
            ...baseArgs,
            tools: [{ name, description, input_schema: parameters }],
            tool_choice: { type: "tool", name }
          },
          warnings
        };
      }
      default: {
        const _exhaustiveCheck = type;
        throw new Error(`Unsupported type: ${_exhaustiveCheck}`);
      }
    }
  }
  async doGenerate(options) {
    var _a;
    const { args, warnings } = await this.getArgs(options);
    const authClient = await ((_a = this.config.googleAuth) == null ? void 0 : _a.getClient());
    const authHeaders = await (authClient == null ? void 0 : authClient.getRequestHeaders());
    options.headers = { ...authHeaders, ...options.headers };
    const specifier = "rawPredict";
    const { responseHeaders, value: response } = await (0, import_provider_utils3.postJsonToApi)({
      url: `${this.config.baseURL}${this.path}:${specifier}`,
      headers: (0, import_provider_utils3.combineHeaders)(this.config.headers(), options.headers),
      body: args,
      failedResponseHandler: anthropicFailedResponseHandler,
      successfulResponseHandler: (0, import_provider_utils3.createJsonResponseHandler)(
        anthropicMessagesResponseSchema
      ),
      abortSignal: options.abortSignal,
      fetch: this.config.fetch
    });
    const { messages: rawPrompt, ...rawSettings } = args;
    let text = "";
    for (const content of response.content) {
      if (content.type === "text") {
        text += content.text;
      }
    }
    let toolCalls = void 0;
    if (response.content.some((content) => content.type === "tool_use")) {
      toolCalls = [];
      for (const content of response.content) {
        if (content.type === "tool_use") {
          toolCalls.push({
            toolCallType: "function",
            toolCallId: content.id,
            toolName: content.name,
            args: JSON.stringify(content.input)
          });
        }
      }
    }
    return {
      text,
      toolCalls,
      finishReason: mapAnthropicStopReason(response.stop_reason),
      usage: {
        promptTokens: response.usage.input_tokens,
        completionTokens: response.usage.output_tokens
      },
      rawCall: { rawPrompt, rawSettings },
      rawResponse: { headers: responseHeaders },
      warnings
    };
  }
  async doStream(options) {
    var _a;
    const { args, warnings } = await this.getArgs(options);
    const authClient = await ((_a = this.config.googleAuth) == null ? void 0 : _a.getClient());
    const authHeaders = await (authClient == null ? void 0 : authClient.getRequestHeaders());
    options.headers = { ...authHeaders, ...options.headers };
    const specifier = "streamRawPredict";
    const { responseHeaders, value: response } = await (0, import_provider_utils3.postJsonToApi)({
      url: `${this.config.baseURL}${this.path}:${specifier}`,
      headers: (0, import_provider_utils3.combineHeaders)(this.config.headers(), options.headers),
      body: {
        ...args,
        stream: true
      },
      failedResponseHandler: anthropicFailedResponseHandler,
      successfulResponseHandler: (0, import_provider_utils3.createEventSourceResponseHandler)(
        anthropicMessagesChunkSchema
      ),
      abortSignal: options.abortSignal,
      fetch: this.config.fetch
    });
    const { messages: rawPrompt, ...rawSettings } = args;
    let finishReason = "other";
    const usage = {
      promptTokens: Number.NaN,
      completionTokens: Number.NaN
    };
    const toolCallContentBlocks = {};
    return {
      stream: response.pipeThrough(
        new TransformStream({
          transform(chunk, controller) {
            if (!chunk.success) {
              controller.enqueue({ type: "error", error: chunk.error });
              return;
            }
            const value = chunk.value;
            switch (value.type) {
              case "ping": {
                return;
              }
              case "content_block_start": {
                const contentBlockType = value.content_block.type;
                switch (contentBlockType) {
                  case "text": {
                    return;
                  }
                  case "tool_use": {
                    toolCallContentBlocks[value.index] = {
                      toolCallId: value.content_block.id,
                      toolName: value.content_block.name,
                      jsonText: ""
                    };
                    return;
                  }
                  default: {
                    const _exhaustiveCheck = contentBlockType;
                    throw new Error(
                      `Unsupported content block type: ${_exhaustiveCheck}`
                    );
                  }
                }
              }
              case "content_block_stop": {
                if (toolCallContentBlocks[value.index] != null) {
                  const contentBlock = toolCallContentBlocks[value.index];
                  controller.enqueue({
                    type: "tool-call",
                    toolCallType: "function",
                    toolCallId: contentBlock.toolCallId,
                    toolName: contentBlock.toolName,
                    args: contentBlock.jsonText
                  });
                  delete toolCallContentBlocks[value.index];
                }
                return;
              }
              case "content_block_delta": {
                const deltaType = value.delta.type;
                switch (deltaType) {
                  case "text_delta": {
                    controller.enqueue({
                      type: "text-delta",
                      textDelta: value.delta.text
                    });
                    return;
                  }
                  case "input_json_delta": {
                    const contentBlock = toolCallContentBlocks[value.index];
                    controller.enqueue({
                      type: "tool-call-delta",
                      toolCallType: "function",
                      toolCallId: contentBlock.toolCallId,
                      toolName: contentBlock.toolName,
                      argsTextDelta: value.delta.partial_json
                    });
                    contentBlock.jsonText += value.delta.partial_json;
                    return;
                  }
                  default: {
                    const _exhaustiveCheck = deltaType;
                    throw new Error(
                      `Unsupported delta type: ${_exhaustiveCheck}`
                    );
                  }
                }
              }
              case "message_start": {
                usage.promptTokens = value.message.usage.input_tokens;
                usage.completionTokens = value.message.usage.output_tokens;
                return;
              }
              case "message_delta": {
                usage.completionTokens = value.usage.output_tokens;
                finishReason = mapAnthropicStopReason(value.delta.stop_reason);
                return;
              }
              case "message_stop": {
                controller.enqueue({ type: "finish", finishReason, usage });
                return;
              }
              default: {
                const _exhaustiveCheck = value;
                throw new Error(`Unsupported chunk type: ${_exhaustiveCheck}`);
              }
            }
          }
        })
      ),
      rawCall: { rawPrompt, rawSettings },
      rawResponse: { headers: responseHeaders },
      warnings
    };
  }
};
var anthropicMessagesResponseSchema = import_zod2.z.object({
  type: import_zod2.z.literal("message"),
  content: import_zod2.z.array(
    import_zod2.z.discriminatedUnion("type", [
      import_zod2.z.object({
        type: import_zod2.z.literal("text"),
        text: import_zod2.z.string()
      }),
      import_zod2.z.object({
        type: import_zod2.z.literal("tool_use"),
        id: import_zod2.z.string(),
        name: import_zod2.z.string(),
        input: import_zod2.z.unknown()
      })
    ])
  ),
  stop_reason: import_zod2.z.string().optional().nullable(),
  usage: import_zod2.z.object({
    input_tokens: import_zod2.z.number(),
    output_tokens: import_zod2.z.number()
  })
});
var anthropicMessagesChunkSchema = import_zod2.z.discriminatedUnion("type", [
  import_zod2.z.object({
    type: import_zod2.z.literal("message_start"),
    message: import_zod2.z.object({
      usage: import_zod2.z.object({
        input_tokens: import_zod2.z.number(),
        output_tokens: import_zod2.z.number()
      })
    })
  }),
  import_zod2.z.object({
    type: import_zod2.z.literal("content_block_start"),
    index: import_zod2.z.number(),
    content_block: import_zod2.z.discriminatedUnion("type", [
      import_zod2.z.object({
        type: import_zod2.z.literal("text"),
        text: import_zod2.z.string()
      }),
      import_zod2.z.object({
        type: import_zod2.z.literal("tool_use"),
        id: import_zod2.z.string(),
        name: import_zod2.z.string()
      })
    ])
  }),
  import_zod2.z.object({
    type: import_zod2.z.literal("content_block_delta"),
    index: import_zod2.z.number(),
    delta: import_zod2.z.discriminatedUnion("type", [
      import_zod2.z.object({
        type: import_zod2.z.literal("input_json_delta"),
        partial_json: import_zod2.z.string()
      }),
      import_zod2.z.object({
        type: import_zod2.z.literal("text_delta"),
        text: import_zod2.z.string()
      })
    ])
  }),
  import_zod2.z.object({
    type: import_zod2.z.literal("content_block_stop"),
    index: import_zod2.z.number()
  }),
  import_zod2.z.object({
    type: import_zod2.z.literal("message_delta"),
    delta: import_zod2.z.object({ stop_reason: import_zod2.z.string().optional().nullable() }),
    usage: import_zod2.z.object({ output_tokens: import_zod2.z.number() })
  }),
  import_zod2.z.object({
    type: import_zod2.z.literal("message_stop")
  }),
  import_zod2.z.object({
    type: import_zod2.z.literal("ping")
  })
]);
function prepareToolsAndToolChoice(mode) {
  var _a;
  const tools = ((_a = mode.tools) == null ? void 0 : _a.length) ? mode.tools : void 0;
  if (tools == null) {
    return { tools: void 0, tool_choice: void 0 };
  }
  const mappedTools = tools.map((tool) => ({
    name: tool.name,
    description: tool.description,
    input_schema: tool.parameters
  }));
  const toolChoice = mode.toolChoice;
  if (toolChoice == null) {
    return { tools: mappedTools, tool_choice: void 0 };
  }
  const type = toolChoice.type;
  switch (type) {
    case "auto":
      return { tools: mappedTools, tool_choice: { type: "auto" } };
    case "required":
      return { tools: mappedTools, tool_choice: { type: "any" } };
    case "none":
      return { tools: void 0, tool_choice: void 0 };
    case "tool":
      return {
        tools: mappedTools,
        tool_choice: { type: "tool", name: toolChoice.toolName }
      };
    default: {
      const _exhaustiveCheck = type;
      throw new Error(`Unsupported tool choice type: ${_exhaustiveCheck}`);
    }
  }
}

// src/anthropic-vertex-provider.ts
function createAnthropicVertex(options = {}) {
  const getConfig = () => {
    const config = {
      projectId: (0, import_provider_utils4.loadSetting)({
        settingValue: options.projectId,
        settingName: "projectId",
        environmentVariableName: "GOOGLE_VERTEX_PROJECT_ID",
        description: "Google Vertex project id"
      }),
      region: (0, import_provider_utils4.loadSetting)({
        settingValue: options.region,
        settingName: "region",
        environmentVariableName: "GOOGLE_VERTEX_REGION",
        description: "Google Vertex region"
      }),
      googleAuth: options.googleAuth
    };
    if (!config.region) {
      throw new Error(
        "No region was given. The client should be instantiated with the `region` option or the `GOOGLE_VERTEX_REGION` environment variable should be set."
      );
    }
    if (!config.projectId) {
      throw new Error(
        "No project was given. The client should be instantiated with the `projectID` option or the `GOOGLE_VERTEX_PROJECT_ID` environment variable should be set."
      );
    }
    return config;
  };
  const createChatModel = (modelId, settings = {}) => {
    var _a, _b;
    const config = getConfig();
    const baseURL = (_a = (0, import_provider_utils4.withoutTrailingSlash)(options.baseURL)) != null ? _a : `https://${config.region}-aiplatform.googleapis.com/v1`;
    const auth = (_b = options.googleAuth) != null ? _b : new import_google_auth_library.GoogleAuth({ scopes: "https://www.googleapis.com/auth/cloud-platform" });
    return new AnthropicMessagesLanguageModel(modelId, settings, {
      provider: "anthropic.messages",
      baseURL,
      headers: () => ({
        ...options.headers
      }),
      fetch: options.fetch,
      projectId: config.projectId,
      region: config.region,
      googleAuth: auth
    });
  };
  const provider = function(modelId, settings) {
    if (new.target) {
      throw new Error(
        "The Anthropic model function cannot be called with the new keyword."
      );
    }
    return createChatModel(modelId, settings);
  };
  provider.languageModel = createChatModel;
  provider.chat = createChatModel;
  return provider;
}
var anthropicVertex = createAnthropicVertex();
// Annotate the CommonJS export names for ESM import in node:
0 && (module.exports = {
  anthropicVertex,
  createAnthropicVertex
});
//# sourceMappingURL=index.js.map