sarvam-ai-sdk/dist/index.mjs

Sarvam AI Provider support for AI-SDK

// src/sarvam-provider.ts
import {
  loadApiKey,
  withoutTrailingSlash
} from "@ai-sdk/provider-utils";

// src/sarvam-chat-language-model.ts
import {
  InvalidResponseDataError
} from "@ai-sdk/provider";
import {
  combineHeaders,
  createEventSourceResponseHandler,
  createJsonResponseHandler,
  generateId as generateId2,
  isParsableJson,
  parseProviderOptions,
  postJsonToApi
} from "@ai-sdk/provider-utils";
import { z as z2 } from "zod";

// src/convert-to-sarvam-chat-messages.ts
import {
  UnsupportedFunctionalityError
} from "@ai-sdk/provider";
import { convertUint8ArrayToBase64 } from "@ai-sdk/provider-utils";
function convertToSarvamChatMessages(prompt, fakeToolSystemPrompt) {
  const messages = [];
  for (const { role, content } of prompt) {
    switch (role) {
      case "system": {
        const contentData = fakeToolSystemPrompt ? `${content}

${fakeToolSystemPrompt}` : content;
        messages.push({ role: "system", content: contentData });
        break;
      }
      case "user": {
        if (content.length === 1 && content[0].type === "text") {
          messages.push({ role: "user", content: content[0].text });
          break;
        }
        messages.push({
          role: "user",
          content: content.map((part) => {
            var _a;
            switch (part.type) {
              case "text": {
                return { type: "text", text: part.text };
              }
              case "image": {
                return {
                  type: "image_url",
                  image_url: {
                    url: part.image instanceof URL ? part.image.toString() : `data:${(_a = part.mimeType) != null ? _a : "image/jpeg"};base64,${convertUint8ArrayToBase64(part.image)}`
                  }
                };
              }
              case "file": {
                throw new UnsupportedFunctionalityError({
                  functionality: "File content parts in user messages"
                });
              }
            }
          })
        });
        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: JSON.stringify(part.args)
                }
              });
              break;
            }
          }
        }
        messages.push({
          role: "assistant",
          content: text,
          tool_calls: toolCalls.length > 0 ? toolCalls : void 0
        });
        break;
      }
      case "tool": {
        for (const toolResponse of content) {
          messages.push({
            role: "tool",
            tool_call_id: toolResponse.toolCallId,
            content: JSON.stringify(toolResponse.result)
          });
        }
        break;
      }
      default: {
        const _exhaustiveCheck = role;
        throw new Error(`Unsupported role: ${_exhaustiveCheck}`);
      }
    }
  }
  return messages;
}

// src/get-response-metadata.ts
function getResponseMetadata({
  id,
  model,
  created
}) {
  return {
    id: id != null ? id : void 0,
    modelId: model != null ? model : void 0,
    timestamp: created != null ? new Date(created * 1e3) : void 0
  };
}

// src/map-sarvam-finish-reason.ts
function mapSarvamFinishReason(finishReason) {
  switch (finishReason) {
    case "stop":
      return "stop";
    case "length":
      return "length";
    case "content_filter":
      return "content-filter";
    case "function_call":
    case "tool_calls":
      return "tool-calls";
    default:
      return "unknown";
  }
}

// src/sarvam-error.ts
import { z } from "zod";
import { createJsonErrorResponseHandler } from "@ai-sdk/provider-utils";
var sarvamErrorDataSchema = z.object({
  error: z.object({
    message: z.string(),
    type: z.string()
  })
});
var sarvamFailedResponseHandler = createJsonErrorResponseHandler({
  errorSchema: sarvamErrorDataSchema,
  errorToMessage: (data) => data.error.message
});

// src/sarvam-prepare-tools.ts
import {
  UnsupportedFunctionalityError as UnsupportedFunctionalityError2
} from "@ai-sdk/provider";
import { generateId } from "@ai-sdk/provider-utils";
import { compile } from "json-schema-to-typescript";
function prepareTools({
  mode
}) {
  var _a;
  const tools = ((_a = mode.tools) == null ? void 0 : _a.length) ? mode.tools : void 0;
  const toolWarnings = [];
  if (tools == null) {
    return { tools: void 0, tool_choice: void 0, toolWarnings };
  }
  const toolChoice = mode.toolChoice;
  const sarvamTools = [];
  for (const tool of tools) {
    if (tool.type === "provider-defined") {
      toolWarnings.push({ type: "unsupported-tool", tool });
    } else {
      sarvamTools.push({
        type: "function",
        function: {
          name: tool.name,
          description: tool.description,
          parameters: tool.parameters
        }
      });
    }
  }
  if (toolChoice == null) {
    return { tools: sarvamTools, tool_choice: void 0, toolWarnings };
  }
  const type = toolChoice.type;
  switch (type) {
    case "auto":
    case "none":
    case "required":
      return { tools: sarvamTools, tool_choice: type, toolWarnings };
    case "tool":
      return {
        tools: sarvamTools,
        tool_choice: {
          type: "function",
          function: {
            name: toolChoice.toolName
          }
        },
        toolWarnings
      };
    default: {
      const _exhaustiveCheck = type;
      throw new UnsupportedFunctionalityError2({
        functionality: `Unsupported tool choice type: ${_exhaustiveCheck}`
      });
    }
  }
}
var simulateToolCalling = async (tools) => {
  const context = [];
  const names = [];
  for (const tool of tools) {
    names.push(tool.function.name);
    const tsType = await compile(
      tool.function.parameters,
      tool.function.name,
      {
        bannerComment: "",
        format: false,
        declareExternallyReferenced: true,
        enableConstEnums: true,
        unreachableDefinitions: false,
        strictIndexSignatures: false
      }
    );
    const toolContext = tsType.replace(
      /export interface (\w+) \{/,
      (_, name) => `type ${tool.function.name} = {`
    ).replace(/\/\*\*\s*\n\s*\*\s*(.*?)\s*\n\s*\*\//, "// $1");
    context.push(`// ${tool.function.description}
${toolContext}`);
  }
  const text = `These are the available tool you can execute.

${context.join("\n")}

type YourToolChoices = {
 'toolName': '${names.join("' | '")}',
 'toolData': ${names.join(" | ")}
}

Respond normally.
If user request to execute any tool, respond with pure JSON format
Make sure to translate toolData to English.

eg:
const myChoice: YourToolChoices = {
    "toolName": <name>,
    "toolData": <data>
}`;
  return text;
};
var extractToolCallData = (jsonObject) => {
  const toolFunction = jsonObject;
  if (!("toolName" in toolFunction)) return;
  if (!("toolData" in toolFunction)) return;
  return {
    args: JSON.stringify(toolFunction.toolData),
    toolCallId: generateId(),
    toolCallType: "function",
    toolName: toolFunction.toolName
  };
};
var parseJSON = (text) => {
  const jsonRegex = /\{(?:[^{}]*|\{[^{}]*\})*\}/g;
  const jsonMatches = text.match(jsonRegex);
  if (jsonMatches && jsonMatches[0]) {
    try {
      const jsonObject = JSON.parse(jsonMatches[0]);
      return jsonObject;
    } catch (error) {
    }
  }
};
var simulateJsonSchema = () => "If user doen't specify, make sure to translate json data content into pure English.";

// src/sarvam-chat-language-model.ts
var SarvamChatLanguageModel = class {
  constructor(modelId, settings, config) {
    this.specificationVersion = "v1";
    this.supportsStructuredOutputs = false;
    this.defaultObjectGenerationMode = "json";
    this.modelId = modelId;
    this.settings = settings;
    this.config = config;
  }
  get provider() {
    return this.config.provider;
  }
  get supportsImageUrls() {
    return !this.settings.downloadImages;
  }
  async getArgs({
    mode,
    prompt,
    maxTokens,
    temperature,
    topP,
    topK,
    frequencyPenalty,
    presencePenalty,
    stopSequences,
    responseFormat,
    seed,
    stream,
    providerMetadata
  }) {
    const type = mode.type;
    const simulate = this.settings.simulate;
    if (type === "object-json" && simulate === "tool-calling")
      throw new Error('Use { simulate: "json-object" } with generateObject()');
    if (type === "regular" && simulate === "json-object")
      throw new Error('Use { simulate: "tool-calling" } with generateText()');
    const warnings = [];
    if (stream) {
      warnings.push({
        type: "other",
        message: "Streaming is still experimental for Sarvam"
      });
    }
    if (topK != null) {
      warnings.push({
        type: "unsupported-setting",
        setting: "topK"
      });
    }
    if (responseFormat != null && responseFormat.type === "json" && responseFormat.schema != null) {
      warnings.push({
        type: "unsupported-setting",
        setting: "responseFormat",
        details: "JSON response format schema is not supported"
      });
    }
    const sarvamOptions = parseProviderOptions({
      provider: "sarvam",
      providerOptions: providerMetadata,
      schema: z2.object({
        reasoningFormat: z2.enum(["parsed", "raw", "hidden"]).nullish()
      })
    });
    const baseArgs = (prompt2, extraSystemPrompt) => ({
      // model id:
      model: this.modelId,
      // model specific settings:
      user: this.settings.user,
      parallel_tool_calls: this.settings.parallelToolCalls,
      // standardized settings:
      max_tokens: maxTokens,
      temperature,
      top_p: topP,
      frequency_penalty: frequencyPenalty,
      presence_penalty: presencePenalty,
      stop: stopSequences,
      seed,
      // response format:
      response_format: (
        // json object response format is not supported for streaming:
        stream === false && (responseFormat == null ? void 0 : responseFormat.type) === "json" ? { type: "json_object" } : void 0
      ),
      // provider options:
      reasoning_format: sarvamOptions == null ? void 0 : sarvamOptions.reasoningFormat,
      // messages:
      messages: convertToSarvamChatMessages(prompt2, extraSystemPrompt)
    });
    switch (type) {
      case "regular": {
        const { tools, tool_choice, toolWarnings } = prepareTools({
          mode
        });
        const extraSystemPrompt = tools && simulate === "tool-calling" ? await simulateToolCalling(tools) : void 0;
        return {
          args: {
            ...baseArgs(prompt, extraSystemPrompt),
            tools,
            tool_choice
          },
          warnings: [...warnings, ...toolWarnings]
        };
      }
      case "object-json": {
        const extraSystemPrompt = simulate === "json-object" ? simulateJsonSchema() : void 0;
        return {
          args: {
            ...baseArgs(prompt, extraSystemPrompt),
            response_format: (
              // json object response format is not supported for streaming:
              stream === false ? { type: "json_object" } : void 0
            )
          },
          warnings
        };
      }
      case "object-tool": {
        return {
          args: {
            ...baseArgs(prompt),
            tool_choice: {
              type: "function",
              function: { name: mode.tool.name }
            },
            tools: [
              {
                type: "function",
                function: {
                  name: mode.tool.name,
                  description: mode.tool.description,
                  parameters: mode.tool.parameters
                }
              }
            ]
          },
          warnings
        };
      }
      default: {
        const _exhaustiveCheck = type;
        throw new Error(`Unsupported type: ${_exhaustiveCheck}`);
      }
    }
  }
  async doGenerate(options) {
    var _a, _b, _c, _d, _e, _f, _g;
    const { args, warnings } = await this.getArgs({
      ...options,
      stream: false
    });
    const body = JSON.stringify(args);
    const {
      responseHeaders,
      value: response,
      rawValue: rawResponse
    } = await postJsonToApi({
      url: this.config.url({
        path: "/chat/completions",
        modelId: this.modelId
      }),
      headers: combineHeaders(this.config.headers(), options.headers),
      body: args,
      failedResponseHandler: sarvamFailedResponseHandler,
      successfulResponseHandler: createJsonResponseHandler(
        sarvamChatResponseSchema
      ),
      abortSignal: options.abortSignal,
      fetch: this.config.fetch
    });
    const { messages: rawPrompt, ...rawSettings } = args;
    const choice = response.choices[0];
    let text = (_a = choice.message.content) != null ? _a : void 0;
    let toolCalls = (_b = choice.message.tool_calls) == null ? void 0 : _b.map((toolCall) => {
      var _a2;
      return {
        toolCallType: "function",
        toolCallId: (_a2 = toolCall.id) != null ? _a2 : generateId2(),
        toolName: toolCall.function.name,
        args: toolCall.function.arguments
      };
    });
    if (this.settings.simulate === "tool-calling") {
      if (text && text.length !== 0) {
        const jsonObject = parseJSON(text);
        if (jsonObject) {
          const newTools = extractToolCallData(jsonObject);
          if (newTools) {
            toolCalls = [newTools];
            text = void 0;
          }
        }
      }
    }
    if (this.settings.simulate === "json-object") {
      if (text && text.length !== 0) {
        const jsonObject = parseJSON(text);
        if (jsonObject) {
          const newTools = extractToolCallData(jsonObject);
          text = JSON.stringify(jsonObject);
        }
      }
    }
    return {
      text,
      toolCalls,
      reasoning: (_c = choice.message.reasoning) != null ? _c : void 0,
      finishReason: mapSarvamFinishReason(choice.finish_reason),
      usage: {
        promptTokens: (_e = (_d = response.usage) == null ? void 0 : _d.prompt_tokens) != null ? _e : NaN,
        completionTokens: (_g = (_f = response.usage) == null ? void 0 : _f.completion_tokens) != null ? _g : NaN
      },
      rawCall: { rawPrompt, rawSettings },
      rawResponse: { headers: responseHeaders, body: rawResponse },
      response: getResponseMetadata(response),
      warnings,
      request: { body }
    };
  }
  async doStream(options) {
    const { args, warnings } = await this.getArgs({ ...options, stream: true });
    const body = JSON.stringify({ ...args, stream: true });
    const { responseHeaders, value: response } = await postJsonToApi({
      url: this.config.url({
        path: "/chat/completions",
        modelId: this.modelId
      }),
      headers: combineHeaders(this.config.headers(), options.headers),
      body: {
        ...args,
        stream: true
      },
      failedResponseHandler: sarvamFailedResponseHandler,
      successfulResponseHandler: createEventSourceResponseHandler(
        sarvamChatChunkSchema
      ),
      abortSignal: options.abortSignal,
      fetch: this.config.fetch
    });
    const { messages: rawPrompt, ...rawSettings } = args;
    const toolCalls = [];
    let finishReason = "unknown";
    let usage = {
      promptTokens: void 0,
      completionTokens: void 0
    };
    let isFirstChunk = true;
    let providerMetadata;
    return {
      stream: response.pipeThrough(
        new TransformStream({
          transform(chunk, controller) {
            var _a, _b, _c, _d, _e, _f, _g, _h, _i, _j, _k, _l, _m, _n, _o;
            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",
                ...getResponseMetadata(value)
              });
            }
            if (((_a = value.x_sarvam) == null ? void 0 : _a.usage) != null) {
              usage = {
                promptTokens: (_b = value.x_sarvam.usage.prompt_tokens) != null ? _b : void 0,
                completionTokens: (_c = value.x_sarvam.usage.completion_tokens) != null ? _c : void 0
              };
            }
            const choice = value.choices[0];
            if ((choice == null ? void 0 : choice.finish_reason) != null) {
              finishReason = mapSarvamFinishReason(choice.finish_reason);
            }
            if ((choice == null ? void 0 : choice.delta) == null) {
              return;
            }
            const delta = choice.delta;
            if (delta.reasoning != null && delta.reasoning.length > 0) {
              controller.enqueue({
                type: "reasoning",
                textDelta: delta.reasoning
              });
            }
            if (delta.content != null && delta.content.length > 0) {
              controller.enqueue({
                type: "text-delta",
                textDelta: delta.content
              });
            }
            if (delta.tool_calls != null) {
              for (const toolCallDelta of delta.tool_calls) {
                const index = toolCallDelta.index;
                if (toolCalls[index] == null) {
                  if (toolCallDelta.type !== "function") {
                    throw new InvalidResponseDataError({
                      data: toolCallDelta,
                      message: `Expected 'function' type.`
                    });
                  }
                  if (toolCallDelta.id == null) {
                    throw new InvalidResponseDataError({
                      data: toolCallDelta,
                      message: `Expected 'id' to be a string.`
                    });
                  }
                  if (((_d = toolCallDelta.function) == null ? void 0 : _d.name) == null) {
                    throw new InvalidResponseDataError({
                      data: toolCallDelta,
                      message: `Expected 'function.name' to be a string.`
                    });
                  }
                  toolCalls[index] = {
                    id: toolCallDelta.id,
                    type: "function",
                    function: {
                      name: toolCallDelta.function.name,
                      arguments: (_e = toolCallDelta.function.arguments) != null ? _e : ""
                    },
                    hasFinished: false
                  };
                  const toolCall2 = toolCalls[index];
                  if (((_f = toolCall2.function) == null ? void 0 : _f.name) != null && ((_g = toolCall2.function) == null ? void 0 : _g.arguments) != null) {
                    if (toolCall2.function.arguments.length > 0) {
                      controller.enqueue({
                        type: "tool-call-delta",
                        toolCallType: "function",
                        toolCallId: toolCall2.id,
                        toolName: toolCall2.function.name,
                        argsTextDelta: toolCall2.function.arguments
                      });
                    }
                    if (isParsableJson(toolCall2.function.arguments)) {
                      controller.enqueue({
                        type: "tool-call",
                        toolCallType: "function",
                        toolCallId: (_h = toolCall2.id) != null ? _h : generateId2(),
                        toolName: toolCall2.function.name,
                        args: toolCall2.function.arguments
                      });
                      toolCall2.hasFinished = true;
                    }
                  }
                  continue;
                }
                const toolCall = toolCalls[index];
                if (toolCall.hasFinished) {
                  continue;
                }
                if (((_i = toolCallDelta.function) == null ? void 0 : _i.arguments) != null) {
                  toolCall.function.arguments += (_k = (_j = toolCallDelta.function) == null ? void 0 : _j.arguments) != null ? _k : "";
                }
                controller.enqueue({
                  type: "tool-call-delta",
                  toolCallType: "function",
                  toolCallId: toolCall.id,
                  toolName: toolCall.function.name,
                  argsTextDelta: (_l = toolCallDelta.function.arguments) != null ? _l : ""
                });
                if (((_m = toolCall.function) == null ? void 0 : _m.name) != null && ((_n = toolCall.function) == null ? void 0 : _n.arguments) != null && isParsableJson(toolCall.function.arguments)) {
                  controller.enqueue({
                    type: "tool-call",
                    toolCallType: "function",
                    toolCallId: (_o = toolCall.id) != null ? _o : generateId2(),
                    toolName: toolCall.function.name,
                    args: toolCall.function.arguments
                  });
                  toolCall.hasFinished = true;
                }
              }
            }
          },
          flush(controller) {
            var _a, _b;
            controller.enqueue({
              type: "finish",
              finishReason,
              usage: {
                promptTokens: (_a = usage.promptTokens) != null ? _a : NaN,
                completionTokens: (_b = usage.completionTokens) != null ? _b : NaN
              },
              ...providerMetadata != null ? { providerMetadata } : {}
            });
          }
        })
      ),
      rawCall: { rawPrompt, rawSettings },
      rawResponse: { headers: responseHeaders },
      warnings,
      request: { body }
    };
  }
};
var sarvamChatResponseSchema = z2.object({
  id: z2.string().nullish(),
  created: z2.number().nullish(),
  model: z2.string().nullish(),
  choices: z2.array(
    z2.object({
      message: z2.object({
        content: z2.string().nullish(),
        reasoning: z2.string().nullish(),
        tool_calls: z2.array(
          z2.object({
            id: z2.string().nullish(),
            type: z2.literal("function"),
            function: z2.object({
              name: z2.string(),
              arguments: z2.string()
            })
          })
        ).nullish()
      }),
      index: z2.number(),
      finish_reason: z2.string().nullish()
    })
  ),
  usage: z2.object({
    prompt_tokens: z2.number().nullish(),
    completion_tokens: z2.number().nullish()
  }).nullish()
});
var sarvamChatChunkSchema = z2.union([
  z2.object({
    id: z2.string().nullish(),
    created: z2.number().nullish(),
    model: z2.string().nullish(),
    choices: z2.array(
      z2.object({
        delta: z2.object({
          content: z2.string().nullish(),
          reasoning: z2.string().nullish(),
          tool_calls: z2.array(
            z2.object({
              index: z2.number(),
              id: z2.string().nullish(),
              type: z2.literal("function").optional(),
              function: z2.object({
                name: z2.string().nullish(),
                arguments: z2.string().nullish()
              })
            })
          ).nullish()
        }).nullish(),
        finish_reason: z2.string().nullable().optional(),
        index: z2.number()
      })
    ),
    x_sarvam: z2.object({
      usage: z2.object({
        prompt_tokens: z2.number().nullish(),
        completion_tokens: z2.number().nullish()
      }).nullish()
    }).nullish()
  }),
  sarvamErrorDataSchema
]);

// src/sarvam-speech-model.ts
import {
  combineHeaders as combineHeaders2,
  createJsonResponseHandler as createJsonResponseHandler2,
  parseProviderOptions as parseProviderOptions2,
  postJsonToApi as postJsonToApi2
} from "@ai-sdk/provider-utils";

// src/sarvam-speech-settings.ts
import { z as z3 } from "zod";
var SpeakerSchema = z3.enum([
  "meera",
  "pavithra",
  "maitreyi",
  "arvind",
  "amol",
  "amartya",
  "diya",
  "neel",
  "misha",
  "vian",
  "arjun",
  "maya",
  "anushka",
  "abhilash",
  "manisha",
  "vidya",
  "arya",
  "karun",
  "hitesh"
]).default("meera");
var SarvamProviderOptionsSchema = z3.object({
  speaker: SpeakerSchema,
  pitch: z3.number().min(-0.75).max(0.75).default(0),
  pace: z3.number().min(0.5).max(2).default(1),
  loudness: z3.number().min(0.3).max(3).default(1),
  speech_sample_rate: z3.union([
    z3.literal(8e3),
    z3.literal(16e3),
    z3.literal(22050),
    z3.literal(24e3)
  ]).default(22050),
  enable_preprocessing: z3.boolean().default(false)
}).partial();

// src/sarvam-speech-model.ts
import { z as z4 } from "zod";
var SarvamSpeechModel = class {
  constructor(modelId, languageCode, config) {
    this.modelId = modelId;
    this.languageCode = languageCode;
    this.config = config;
    this.specificationVersion = "v1";
  }
  get provider() {
    return this.config.provider;
  }
  getArgs({
    text,
    voice,
    outputFormat = "wav",
    // speed,
    // instructions,
    providerOptions
  }) {
    const warnings = [];
    const sarvamOptions = parseProviderOptions2({
      provider: "sarvam",
      providerOptions: {
        sarvam: {
          ...providerOptions == null ? void 0 : providerOptions.sarvam,
          ...this.config.speech
        }
      },
      schema: SarvamProviderOptionsSchema
    });
    const getSpeaker = () => {
      if (sarvamOptions == null ? void 0 : sarvamOptions.speaker) return sarvamOptions.speaker;
      if (voice) {
        return SpeakerSchema.parse(voice);
      }
      switch (this.modelId) {
        case "bulbul:v1":
          return "meera";
        case "bulbul:v2":
          return "manisha";
      }
      return "meera";
    };
    const requestBody = {
      model: this.modelId,
      text,
      target_language_code: this.languageCode,
      speaker: getSpeaker()
      // response_format: "wav",
      // speed,
      // instructions,
    };
    if (outputFormat) {
      if (["mp3", "opus", "aac", "flac", "wav", "pcm"].includes(
        outputFormat
      )) {
        requestBody.response_format = outputFormat;
      } else {
        warnings.push({
          type: "unsupported-setting",
          setting: "outputFormat",
          details: `Unsupported output format: ${outputFormat}. Using mp3 instead.`
        });
      }
    }
    if (sarvamOptions) {
      const speechModelOptions = {};
      for (const key in speechModelOptions) {
        const value = speechModelOptions[key];
        if (value !== void 0) {
          requestBody[key] = value;
        }
      }
    }
    return {
      requestBody,
      warnings
    };
  }
  async doGenerate(options) {
    var _a, _b, _c;
    const currentDate = (_c = (_b = (_a = this.config._internal) == null ? void 0 : _a.currentDate) == null ? void 0 : _b.call(_a)) != null ? _c : /* @__PURE__ */ new Date();
    const { requestBody, warnings } = this.getArgs(options);
    const {
      value,
      responseHeaders,
      rawValue: rawResponse
    } = await postJsonToApi2({
      url: this.config.url({
        path: "/text-to-speech",
        modelId: this.modelId
      }),
      headers: combineHeaders2(this.config.headers(), options.headers),
      body: requestBody,
      failedResponseHandler: sarvamFailedResponseHandler,
      successfulResponseHandler: createJsonResponseHandler2(
        z4.object({
          request_id: z4.string(),
          audios: z4.array(z4.string())
        })
      ),
      abortSignal: options.abortSignal,
      fetch: this.config.fetch
    });
    const audio = value.audios[0];
    return {
      audio,
      warnings,
      request: {
        body: JSON.stringify(requestBody)
      },
      response: {
        timestamp: currentDate,
        modelId: this.modelId,
        headers: responseHeaders,
        body: rawResponse
      }
    };
  }
};

// src/sarvam-transcription-model.ts
import {
  combineHeaders as combineHeaders3,
  createJsonResponseHandler as createJsonResponseHandler3,
  parseProviderOptions as parseProviderOptions3,
  postFormDataToApi
} from "@ai-sdk/provider-utils";
import { z as z6 } from "zod";

// src/sarvam-transcription-settings.ts
import { z as z5 } from "zod";
var SarvamProviderOptionsSchema2 = z5.object({
  with_timestamps: z5.boolean().nullish().default(false),
  with_diarization: z5.boolean().nullish().default(false),
  num_speakers: z5.number().int().nullish()
});

// src/sarvam-transcription-model.ts
var SarvamTranscriptionModel = class {
  constructor(modelId, languageCode, config) {
    this.modelId = modelId;
    this.languageCode = languageCode;
    this.config = config;
    this.specificationVersion = "v1";
  }
  get provider() {
    return this.config.provider;
  }
  getArgs({
    audio,
    mediaType,
    providerOptions
  }) {
    const warnings = [];
    if (this.modelId === "saarika:v1" && this.languageCode === "unknown")
      throw new Error(
        "Language code unknown is not supported for model saarika:v1"
      );
    const sarvamOptions = parseProviderOptions3({
      provider: "sarvam",
      providerOptions: {
        sarvam: {
          ...providerOptions == null ? void 0 : providerOptions.sarvam,
          ...this.config.transcription
        }
      },
      schema: SarvamProviderOptionsSchema2
    });
    const formData = new FormData();
    const blob = audio instanceof Blob ? audio : new Blob([audio], { type: mediaType });
    formData.append("file", blob);
    formData.append("model", this.modelId);
    if (sarvamOptions) {
      formData.append("language_code", this.languageCode);
      formData.append(
        "with_timestamps",
        sarvamOptions.with_timestamps ? "true" : "false"
      );
      formData.append(
        "with_diarization",
        sarvamOptions.with_diarization ? "true" : "false"
      );
      if (sarvamOptions.num_speakers !== null && sarvamOptions.num_speakers !== void 0) {
        formData.append(
          "num_speakers",
          sarvamOptions.num_speakers.toString()
        );
      }
    }
    return {
      formData,
      warnings
    };
  }
  async doGenerate(options) {
    var _a, _b, _c, _d, _e;
    const currentDate = (_c = (_b = (_a = this.config._internal) == null ? void 0 : _a.currentDate) == null ? void 0 : _b.call(_a)) != null ? _c : /* @__PURE__ */ new Date();
    const { formData, warnings } = this.getArgs(options);
    const {
      value: response,
      responseHeaders,
      rawValue: rawResponse
    } = await postFormDataToApi({
      url: this.config.url({
        path: "/speech-to-text",
        modelId: this.modelId
      }),
      headers: combineHeaders3(this.config.headers(), options.headers),
      formData,
      failedResponseHandler: sarvamFailedResponseHandler,
      successfulResponseHandler: createJsonResponseHandler3(
        sarvamTranscriptionResponseSchema
      ),
      abortSignal: options.abortSignal,
      fetch: this.config.fetch
    });
    return {
      text: response.transcript,
      segments: response.timestamps ? response.timestamps.words.map((word, index) => ({
        text: word,
        startSecond: response.timestamps.start_time_seconds[index],
        endSecond: response.timestamps.end_time_seconds[index]
      })) : [],
      language: response.language_code ? response.language_code : void 0,
      durationInSeconds: (_e = (_d = response.timestamps) == null ? void 0 : _d.end_time_seconds[response.timestamps.end_time_seconds.length - 1]) != null ? _e : void 0,
      warnings,
      response: {
        timestamp: currentDate,
        modelId: this.modelId,
        headers: responseHeaders,
        body: rawResponse
      }
    };
  }
};
var sarvamTranscriptionResponseSchema = z6.object({
  request_id: z6.string().nullable(),
  transcript: z6.string(),
  language_code: z6.string().nullable(),
  timestamps: z6.object({
    end_time_seconds: z6.array(z6.number()),
    start_time_seconds: z6.array(z6.number()),
    words: z6.array(z6.string())
  }).optional(),
  diarized_transcript: z6.object({
    entries: z6.array(
      z6.object({
        end_time_seconds: z6.array(z6.number()),
        start_time_seconds: z6.array(z6.number()),
        transcript: z6.string(),
        speaker_id: z6.string()
      })
    )
  }).optional()
});

// src/sarvam-translation-model.ts
import {
  combineHeaders as combineHeaders4,
  createJsonResponseHandler as createJsonResponseHandler4,
  postJsonToApi as postJsonToApi3
} from "@ai-sdk/provider-utils";
import { z as z8 } from "zod";

// src/sarvam-config.ts
import { z as z7 } from "zod";
var SarvamLanguageCodeSchema = z7.enum([
  "hi-IN",
  "bn-IN",
  "kn-IN",
  "ml-IN",
  "mr-IN",
  "od-IN",
  "pa-IN",
  "ta-IN",
  "te-IN",
  "en-IN",
  "gu-IN"
]);
var SarvamScriptCodeSchema = z7.enum([
  "Latn",
  "Deva",
  "Beng",
  "Gujr",
  "Knda",
  "Mlym",
  "Orya",
  "Guru",
  "Taml",
  "Telu"
]);

// src/sarvam-translation-model.ts
var SarvamTranslationModel = class {
  constructor(settings, config) {
    this.specificationVersion = "v1";
    this.supportsStructuredOutputs = false;
    this.defaultObjectGenerationMode = "json";
    var _a;
    this.modelId = (_a = settings.model) != null ? _a : "mayura:v1";
    this.settings = settings;
    this.config = config;
  }
  get provider() {
    return this.config.provider;
  }
  get supportsImageUrls() {
    return false;
  }
  getArgs({
    mode,
    prompt
  }) {
    var _a, _b, _c, _d, _e, _f, _g, _h;
    const type = mode.type;
    const warnings = [];
    if (this.settings.from === this.settings.to) {
      throw new Error(
        "Source and target languages code must be different."
      );
    }
    if (this.modelId === "sarvam-translate:v1") {
      if (((_a = this.settings.mode) != null ? _a : "formal") !== "formal")
        throw new Error(
          "Sarvam 'sarvam-translate:v1' only support mode formal."
        );
      if (((_b = this.settings.from) != null ? _b : "auto") === "auto")
        throw new Error(
          "Sarvam 'sarvam-translate:v1' requires source language code."
        );
    }
    if (type !== "regular") {
      const _exhaustiveCheck = type;
      throw new Error(`Unsupported type: ${_exhaustiveCheck}`);
    }
    const messages = convertToSarvamChatMessages(prompt);
    return {
      messages,
      args: {
        input: messages.filter((m) => m.role === "user").map((m) => m.content).join("\n"),
        source_language_code: (_c = this.settings.from) != null ? _c : "auto",
        target_language_code: this.settings.to,
        numerals_format: (_d = this.settings.numerals_format) != null ? _d : "international",
        enable_preprocessing: (_e = this.settings.enable_preprocessing) != null ? _e : false,
        output_script: (_f = this.settings.output_script) != null ? _f : null,
        speaker_gender: (_g = this.settings.speaker_gender) != null ? _g : "Male",
        mode: (_h = this.settings.mode) != null ? _h : "formal",
        model: this.modelId
      },
      warnings
    };
  }
  async doGenerate(options) {
    var _a;
    const { args, warnings, messages } = this.getArgs({
      ...options,
      stream: false
    });
    const body = JSON.stringify(args);
    const {
      responseHeaders,
      value: response,
      rawValue: rawResponse
    } = await postJsonToApi3({
      url: this.config.url({
        path: "/translate"
      }),
      headers: combineHeaders4(this.config.headers(), options.headers),
      body: args,
      failedResponseHandler: sarvamFailedResponseHandler,
      successfulResponseHandler: createJsonResponseHandler4(
        sarvamTranslationResponseSchema
      ),
      abortSignal: options.abortSignal,
      fetch: this.config.fetch
    });
    const { input: rawPrompt, ...rawSettings } = args;
    const text = (_a = response.translated_text) != null ? _a : void 0;
    return {
      text,
      toolCalls: void 0,
      reasoning: void 0,
      finishReason: "unknown",
      usage: {
        promptTokens: NaN,
        completionTokens: NaN
      },
      rawCall: { rawPrompt, rawSettings },
      rawResponse: { headers: responseHeaders, body: rawResponse },
      response: void 0,
      warnings,
      request: { body }
    };
  }
  async doStream(options) {
    throw new Error("Translation feature doesn't support streaming yet");
  }
};
var sarvamTranslationResponseSchema = z8.object({
  translated_text: z8.string().nullish(),
  source_language_code: SarvamLanguageCodeSchema.nullable(),
  request_id: z8.string().nullish()
});

// src/sarvam-transliterate-model.ts
import {
  combineHeaders as combineHeaders5,
  createJsonResponseHandler as createJsonResponseHandler5,
  postJsonToApi as postJsonToApi4
} from "@ai-sdk/provider-utils";
import { z as z9 } from "zod";
var SarvamTransliterateModel = class {
  constructor(settings, config) {
    this.specificationVersion = "v1";
    this.supportsStructuredOutputs = false;
    this.defaultObjectGenerationMode = "json";
    this.modelId = "unknown";
    this.settings = settings;
    this.config = config;
  }
  get provider() {
    return this.config.provider;
  }
  get supportsImageUrls() {
    return false;
  }
  getArgs({
    mode,
    prompt
  }) {
    var _a, _b, _c;
    const type = mode.type;
    const warnings = [];
    if (this.settings.from !== "auto") {
      if (this.settings.to !== "en-IN" && this.settings.from !== "en-IN")
        throw new Error(
          "Sarvam doesn't support Indic-Indic Transliteration yet"
        );
    }
    if (type !== "regular") {
      const _exhaustiveCheck = type;
      throw new Error(`Unsupported type: ${_exhaustiveCheck}`);
    }
    const messages = convertToSarvamChatMessages(prompt);
    return {
      messages,
      args: {
        input: messages.filter((m) => m.role === "user").map((m) => m.content).join("\n"),
        source_language_code: (_a = this.settings.from) != null ? _a : "auto",
        target_language_code: this.settings.to,
        numerals_format: (_b = this.settings.numerals_format) != null ? _b : "international",
        ...this.settings.spoken_form ? {
          spoken_form: this.settings.spoken_form,
          spoken_form_numerals_language: (_c = this.settings.spoken_form_numerals_language) != null ? _c : "english"
        } : {}
      },
      warnings
    };
  }
  async doGenerate(options) {
    var _a;
    const { args, warnings, messages } = this.getArgs({
      ...options,
      stream: false
    });
    const body = JSON.stringify(args);
    const {
      responseHeaders,
      value: response,
      rawValue: rawResponse
    } = await postJsonToApi4({
      url: this.config.url({
        path: "/transliterate"
      }),
      headers: combineHeaders5(this.config.headers(), options.headers),
      body: args,
      failedResponseHandler: sarvamFailedResponseHandler,
      successfulResponseHandler: createJsonResponseHandler5(
        sarvamTransliterateResponseSchema
      ),
      abortSignal: options.abortSignal,
      fetch: this.config.fetch
    });
    const { input: rawPrompt, ...rawSettings } = args;
    let text = (_a = response.transliterated_text) != null ? _a : void 0;
    return {
      text,
      toolCalls: void 0,
      reasoning: void 0,
      finishReason: "unknown",
      usage: {
        promptTokens: NaN,
        completionTokens: NaN
      },
      rawCall: { rawPrompt, rawSettings },
      rawResponse: { headers: responseHeaders, body: rawResponse },
      response: void 0,
      warnings,
      request: { body }
    };
  }
  async doStream(options) {
    throw new Error("Transliterate feature doesn't streaming yet");
  }
};
var sarvamTransliterateResponseSchema = z9.object({
  transliterated_text: z9.string().nullish(),
  source_language_code: SarvamLanguageCodeSchema.nullable(),
  request_id: z9.string().nullish()
});

// src/sarvam-lid-model.ts
import {
  combineHeaders as combineHeaders6,
  createJsonResponseHandler as createJsonResponseHandler6,
  postJsonToApi as postJsonToApi5
} from "@ai-sdk/provider-utils";
import { z as z10 } from "zod";
var SarvamLidModel = class {
  constructor(config) {
    this.specificationVersion = "v1";
    this.supportsStructuredOutputs = false;
    this.defaultObjectGenerationMode = "json";
    this.modelId = "unknown";
    this.config = config;
  }
  get provider() {
    return this.config.provider;
  }
  get supportsImageUrls() {
    return false;
  }
  getArgs({
    mode,
    prompt
  }) {
    const type = mode.type;
    const warnings = [];
    if (type !== "regular") {
      const _exhaustiveCheck = type;
      throw new Error(`Unsupported type: ${_exhaustiveCheck}`);
    }
    const messages = convertToSarvamChatMessages(prompt);
    return {
      messages,
      args: {
        input: messages.filter((m) => m.role === "user").map((m) => m.content).join("\n")
      },
      warnings
    };
  }
  async doGenerate(options) {
    var _a;
    const { args, warnings, messages } = this.getArgs({
      ...options,
      stream: false
    });
    const body = JSON.stringify(args);
    const {
      responseHeaders,
      value: response,
      rawValue: rawResponse
    } = await postJsonToApi5({
      url: this.config.url({
        path: "/text-lid"
      }),
      headers: combineHeaders6(this.config.headers(), options.headers),
      body: args,
      failedResponseHandler: sarvamFailedResponseHandler,
      successfulResponseHandler: createJsonResponseHandler6(
        sarvamLidResponseSchema
      ),
      abortSignal: options.abortSignal,
      fetch: this.config.fetch
    });
    const { input: rawPrompt, ...rawSettings } = args;
    const text = (_a = response.language_code) != null ? _a : void 0;
    return {
      text,
      toolCalls: void 0,
      reasoning: void 0,
      finishReason: "unknown",
      usage: {
        promptTokens: NaN,
        completionTokens: NaN
      },
      rawCall: { rawPrompt, rawSettings },
      rawResponse: { headers: responseHeaders, body: rawResponse },
      response: void 0,
      warnings,
      request: { body }
    };
  }
  async doStream(options) {
    throw new Error("Language Identification feature doesn't streaming yet");
  }
};
var sarvamLidResponseSchema = z10.object({
  script_code: SarvamScriptCodeSchema.nullish(),
  language_code: SarvamLanguageCodeSchema.nullable(),
  request_id: z10.string().nullish()
});

// src/sarvam-speech-translation-model.ts
import {
  combineHeaders as combineHeaders7,
  createJsonResponseHandler as createJsonResponseHandler7,
  postFormDataToApi as postFormDataToApi2
} from "@ai-sdk/provider-utils";
import { z as z11 } from "zod";
var SarvamSpeechTranslationModel = class {
  constructor(modelId, config) {
    this.modelId = modelId;
    this.config = config;
    this.specificationVersion = "v1";
  }
  get provider() {
    return this.config.provider;
  }
  getArgs({
    audio,
    mediaType,
    providerOptions
  }) {
    const warnings = [];
    const formData = new FormData();
    const blob = audio instanceof Blob ? audio : new Blob([audio], { type: mediaType });
    formData.append("file", blob);
    formData.append("model", this.modelId);
    return {
      formData,
      warnings
    };
  }
  async doGenerate(options) {
    var _a, _b, _c;
    const currentDate = (_c = (_b = (_a = this.config._internal) == null ? void 0 : _a.currentDate) == null ? void 0 : _b.call(_a)) != null ? _c : /* @__PURE__ */ new Date();
    const { formData, warnings } = this.getArgs(options);
    const {
      value: response,
      responseHeaders,
      rawValue: rawResponse
    } = await postFormDataToApi2({
      url: this.config.url({
        path: "/speech-to-text-translate",
        modelId: this.modelId
      }),
      headers: combineHeaders7(this.config.headers(), options.headers),
      formData,
      failedResponseHandler: sarvamFailedResponseHandler,
      successfulResponseHandler: createJsonResponseHandler7(
        sarvamTranscriptionResponseSchema2
      ),
      abortSignal: options.abortSignal,
      fetch: this.config.fetch
    });
    return {
      text: response.transcript,
      segments: [],
      language: response.language_code ? response.language_code : void 0,
      durationInSeconds: void 0,
      warnings,
      response: {
        timestamp: currentDate,
        modelId: this.modelId,
        headers: responseHeaders,
        body: rawResponse
      }
    };
  }
};
var sarvamTranscriptionResponseSchema2 = z11.object({
  request_id: z11.string().nullable(),
  transcript: z11.string(),
  language_code: z11.string().nullable(),
  // timestamps: z
  //   .object({
  //     end_time_seconds: z.array(z.number()),
  //     start_time_seconds: z.array(z.number()),
  //     words: z.array(z.string()),
  //   })
  //   .optional(),
  diarized_transcript: z11.object({
    entries: z11.array(
      z11.object({
        end_time_seconds: z11.array(z11.number()),
        start_time_seconds: z11.array(z11.number()),
        transcript: z11.string(),
        speaker_id: z11.string()
      })
    )
  }).nullable().optional()
});

// src/sarvam-provider.ts
function createSarvam(options = {}) {
  var _a;
  const baseURL = (_a = withoutTrailingSlash(options.baseURL)) != null ? _a : "https://api.sarvam.ai";
  const getApiKey = () => loadApiKey({
    apiKey: options.apiKey,
    environmentVariableName: "SARVAM_API_KEY",
    description: "Sarvam"
  });
  const getHeaders = () => ({
    Authorization: `Bearer ${getApiKey()}`,
    "api-subscription-key": getApiKey(),
    ...options.headers
  });
  const createChatModel = (modelId, settings = {}) => new SarvamChatLanguageModel(modelId, settings, {
    provider: "sarvam.chat",
    url: ({ path }) => `${baseURL}/v1${path}`,
    headers: getHeaders,
    fetch: options.fetch
  });
  const createLanguageModel = (modelId, settings) => {
    if (new.target) {
      throw new Error(
        "The Sarvam model function cannot be called with the new keyword."
      );
    }
    return createChatModel(modelId, settings);
  };
  const createTranscriptionModel = (modelId, languageCode = "unknown", settings) => new SarvamTranscriptionModel(modelId, languageCode, {
    provider: "sarvam.transcription",
    url: ({ path }) => `${baseURL}${path}`,
    headers: getHeaders,
    fetch: options.fetch,
    transcription: settings
  });
  const createSpeechTranslation = (modelId) => new SarvamSpeechTranslationModel(modelId, {
    provider: "sarvam.transcription",
    url: ({ path }) => `${baseURL}${path}`,
    headers: getHeaders,
    fetch: options.fetch
  });
  const createSpeechModel = (modelId, languageCode, settings) => new SarvamSpeechModel(modelId, languageCode, {
    provider: "sarvam.speech",
    url: ({ path }) => `${baseURL}${path}`,
    headers: getHeaders,
    fetch: options.fetch,
    speech: settings
  });
  const createTransliterateModel = (settings) => new SarvamTransliterateModel(
    settings,
    {
      provider: "sarvam.transliterate",
      url: ({ path }) => `${baseURL}${path}`,
      headers: getHeaders,
      fetch: options.fetch
    }
  );
  const createTranslationModel = (settings) => new SarvamTranslationModel(
    settings,
    {
      provider: "sarvam.translation",
      url: ({ path }) => `${baseURL}${path}`,
      headers: getHeaders,
      fetch: options.fetch
    }
  );
  const createLidModel = () => new SarvamLidModel(
    {
      provider: "sarvam.lid",
      url: ({ path }) => `${baseURL}${path}`,
      headers: getHeaders,
      fetch: options.fetch
    }
  );
  const provider = (modelId, settings) => createLanguageModel(modelId, settings);
  provider.languageModel = createLanguageModel;
  provider.chat = createChatModel;
  provider.transcription = createTranscriptionModel;
  provider.speechTranslation = createSpeechTranslation;
  provider.speech = createSpeechModel;
  provider.transliterate = createTransliterateModel;
  provider.translation = createTranslationModel;
  provider.languageIdentification = createLidModel;
  return provider;
}
var sarvam = createSarvam();
export {
  createSarvam,
  sarvam
};
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