'use strict';

var chunkDBTKQ3U2_cjs = require('./chunk-DBTKQ3U2.cjs');
var chunkZMNN3DOV_cjs = require('./chunk-ZMNN3DOV.cjs');
var chunkOCS2GTEN_cjs = require('./chunk-OCS2GTEN.cjs');
var chunk6QR4RQID_cjs = require('./chunk-6QR4RQID.cjs');
var chunkXSOONORA_cjs = require('./chunk-XSOONORA.cjs');
var fs = require('fs');
var module$1 = require('module');
var os = require('os');
var path = require('path');
var v4 = require('zod/v4');
var WebSocket = require('ws');

var _documentCurrentScript = typeof document !== 'undefined' ? document.currentScript : null;
function _interopDefault (e) { return e && e.__esModule ? e : { default: e }; }

var fs__default = /*#__PURE__*/_interopDefault(fs);
var os__default = /*#__PURE__*/_interopDefault(os);
var path__default = /*#__PURE__*/_interopDefault(path);
var WebSocket__default = /*#__PURE__*/_interopDefault(WebSocket);

var openaiErrorDataSchema = v4.z.object({
  error: v4.z.object({
    message: v4.z.string(),
    // The additional information below is handled loosely to support
    // OpenAI-compatible providers that have slightly different error
    // responses:
    type: v4.z.string().nullish(),
    param: v4.z.any().nullish(),
    code: v4.z.union([v4.z.string(), v4.z.number()]).nullish()
  })
});
var openaiFailedResponseHandler = chunkOCS2GTEN_cjs.createJsonErrorResponseHandler({
  errorSchema: openaiErrorDataSchema,
  errorToMessage: (data) => data.error.message
});
function getOpenAILanguageModelCapabilities(modelId) {
  const supportsFlexProcessing = modelId.startsWith("o3") || modelId.startsWith("o4-mini") || modelId.startsWith("gpt-5") && !modelId.startsWith("gpt-5-chat");
  const supportsPriorityProcessing = modelId.startsWith("gpt-4") || modelId.startsWith("gpt-5") && !modelId.startsWith("gpt-5-nano") && !modelId.startsWith("gpt-5-chat") && !modelId.startsWith("gpt-5.4-nano") || modelId.startsWith("o3") || modelId.startsWith("o4-mini");
  const isReasoningModel = !(modelId.startsWith("gpt-3") || modelId.startsWith("gpt-4") || modelId.startsWith("chatgpt-4o") || modelId.startsWith("gpt-5-chat"));
  const supportsNonReasoningParameters = modelId.startsWith("gpt-5.1") || modelId.startsWith("gpt-5.2") || modelId.startsWith("gpt-5.3") || modelId.startsWith("gpt-5.4");
  const systemMessageMode = isReasoningModel ? "developer" : "system";
  return {
    supportsFlexProcessing,
    supportsPriorityProcessing,
    isReasoningModel,
    systemMessageMode,
    supportsNonReasoningParameters
  };
}
function convertToOpenAIChatMessages({
  prompt,
  systemMessageMode = "system"
}) {
  const messages = [];
  const warnings = [];
  for (const { role, content } of prompt) {
    switch (role) {
      case "system": {
        switch (systemMessageMode) {
          case "system": {
            messages.push({ role: "system", content });
            break;
          }
          case "developer": {
            messages.push({ role: "developer", content });
            break;
          }
          case "remove": {
            warnings.push({
              type: "other",
              message: "system messages are removed for this model"
            });
            break;
          }
          default: {
            const _exhaustiveCheck = systemMessageMode;
            throw new Error(
              `Unsupported system message mode: ${_exhaustiveCheck}`
            );
          }
        }
        break;
      }
      case "user": {
        if (content.length === 1 && content[0].type === "text") {
          messages.push({ role: "user", content: content[0].text });
          break;
        }
        messages.push({
          role: "user",
          content: content.map((part, index) => {
            var _a, _b, _c;
            switch (part.type) {
              case "text": {
                return { type: "text", text: part.text };
              }
              case "file": {
                if (part.mediaType.startsWith("image/")) {
                  const mediaType = part.mediaType === "image/*" ? "image/jpeg" : part.mediaType;
                  return {
                    type: "image_url",
                    image_url: {
                      url: part.data instanceof URL ? part.data.toString() : `data:${mediaType};base64,${chunkOCS2GTEN_cjs.convertToBase64(part.data)}`,
                      // OpenAI specific extension: image detail
                      detail: (_b = (_a = part.providerOptions) == null ? void 0 : _a.openai) == null ? void 0 : _b.imageDetail
                    }
                  };
                } else if (part.mediaType.startsWith("audio/")) {
                  if (part.data instanceof URL) {
                    throw new chunkOCS2GTEN_cjs.UnsupportedFunctionalityError({
                      functionality: "audio file parts with URLs"
                    });
                  }
                  switch (part.mediaType) {
                    case "audio/wav": {
                      return {
                        type: "input_audio",
                        input_audio: {
                          data: chunkOCS2GTEN_cjs.convertToBase64(part.data),
                          format: "wav"
                        }
                      };
                    }
                    case "audio/mp3":
                    case "audio/mpeg": {
                      return {
                        type: "input_audio",
                        input_audio: {
                          data: chunkOCS2GTEN_cjs.convertToBase64(part.data),
                          format: "mp3"
                        }
                      };
                    }
                    default: {
                      throw new chunkOCS2GTEN_cjs.UnsupportedFunctionalityError({
                        functionality: `audio content parts with media type ${part.mediaType}`
                      });
                    }
                  }
                } else if (part.mediaType === "application/pdf") {
                  if (part.data instanceof URL) {
                    throw new chunkOCS2GTEN_cjs.UnsupportedFunctionalityError({
                      functionality: "PDF file parts with URLs"
                    });
                  }
                  return {
                    type: "file",
                    file: typeof part.data === "string" && part.data.startsWith("file-") ? { file_id: part.data } : {
                      filename: (_c = part.filename) != null ? _c : `part-${index}.pdf`,
                      file_data: `data:application/pdf;base64,${chunkOCS2GTEN_cjs.convertToBase64(part.data)}`
                    }
                  };
                } else {
                  throw new chunkOCS2GTEN_cjs.UnsupportedFunctionalityError({
                    functionality: `file part media type ${part.mediaType}`
                  });
                }
              }
            }
          })
        });
        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.input)
                }
              });
              break;
            }
          }
        }
        messages.push({
          role: "assistant",
          content: text,
          tool_calls: toolCalls.length > 0 ? toolCalls : void 0
        });
        break;
      }
      case "tool": {
        for (const toolResponse of content) {
          const output = toolResponse.output;
          let contentValue;
          switch (output.type) {
            case "text":
            case "error-text":
              contentValue = output.value;
              break;
            case "content":
            case "json":
            case "error-json":
              contentValue = JSON.stringify(output.value);
              break;
          }
          messages.push({
            role: "tool",
            tool_call_id: toolResponse.toolCallId,
            content: contentValue
          });
        }
        break;
      }
      default: {
        const _exhaustiveCheck = role;
        throw new Error(`Unsupported role: ${_exhaustiveCheck}`);
      }
    }
  }
  return { messages, warnings };
}
function getResponseMetadata({
  id,
  model,
  created
}) {
  return {
    id: id != null ? id : void 0,
    modelId: model != null ? model : void 0,
    timestamp: created ? new Date(created * 1e3) : void 0
  };
}
function mapOpenAIFinishReason(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";
  }
}
var openaiChatResponseSchema = chunkOCS2GTEN_cjs.lazyValidator(
  () => chunkOCS2GTEN_cjs.zodSchema(
    v4.z.object({
      id: v4.z.string().nullish(),
      created: v4.z.number().nullish(),
      model: v4.z.string().nullish(),
      choices: v4.z.array(
        v4.z.object({
          message: v4.z.object({
            role: v4.z.literal("assistant").nullish(),
            content: v4.z.string().nullish(),
            tool_calls: v4.z.array(
              v4.z.object({
                id: v4.z.string().nullish(),
                type: v4.z.literal("function"),
                function: v4.z.object({
                  name: v4.z.string(),
                  arguments: v4.z.string()
                })
              })
            ).nullish(),
            annotations: v4.z.array(
              v4.z.object({
                type: v4.z.literal("url_citation"),
                url_citation: v4.z.object({
                  start_index: v4.z.number(),
                  end_index: v4.z.number(),
                  url: v4.z.string(),
                  title: v4.z.string()
                })
              })
            ).nullish()
          }),
          index: v4.z.number(),
          logprobs: v4.z.object({
            content: v4.z.array(
              v4.z.object({
                token: v4.z.string(),
                logprob: v4.z.number(),
                top_logprobs: v4.z.array(
                  v4.z.object({
                    token: v4.z.string(),
                    logprob: v4.z.number()
                  })
                )
              })
            ).nullish()
          }).nullish(),
          finish_reason: v4.z.string().nullish()
        })
      ),
      usage: v4.z.object({
        prompt_tokens: v4.z.number().nullish(),
        completion_tokens: v4.z.number().nullish(),
        total_tokens: v4.z.number().nullish(),
        prompt_tokens_details: v4.z.object({
          cached_tokens: v4.z.number().nullish()
        }).nullish(),
        completion_tokens_details: v4.z.object({
          reasoning_tokens: v4.z.number().nullish(),
          accepted_prediction_tokens: v4.z.number().nullish(),
          rejected_prediction_tokens: v4.z.number().nullish()
        }).nullish()
      }).nullish()
    })
  )
);
var openaiChatChunkSchema = chunkOCS2GTEN_cjs.lazyValidator(
  () => chunkOCS2GTEN_cjs.zodSchema(
    v4.z.union([
      v4.z.object({
        id: v4.z.string().nullish(),
        created: v4.z.number().nullish(),
        model: v4.z.string().nullish(),
        choices: v4.z.array(
          v4.z.object({
            delta: v4.z.object({
              role: v4.z.enum(["assistant"]).nullish(),
              content: v4.z.string().nullish(),
              tool_calls: v4.z.array(
                v4.z.object({
                  index: v4.z.number(),
                  id: v4.z.string().nullish(),
                  type: v4.z.literal("function").nullish(),
                  function: v4.z.object({
                    name: v4.z.string().nullish(),
                    arguments: v4.z.string().nullish()
                  })
                })
              ).nullish(),
              annotations: v4.z.array(
                v4.z.object({
                  type: v4.z.literal("url_citation"),
                  url_citation: v4.z.object({
                    start_index: v4.z.number(),
                    end_index: v4.z.number(),
                    url: v4.z.string(),
                    title: v4.z.string()
                  })
                })
              ).nullish()
            }).nullish(),
            logprobs: v4.z.object({
              content: v4.z.array(
                v4.z.object({
                  token: v4.z.string(),
                  logprob: v4.z.number(),
                  top_logprobs: v4.z.array(
                    v4.z.object({
                      token: v4.z.string(),
                      logprob: v4.z.number()
                    })
                  )
                })
              ).nullish()
            }).nullish(),
            finish_reason: v4.z.string().nullish(),
            index: v4.z.number()
          })
        ),
        usage: v4.z.object({
          prompt_tokens: v4.z.number().nullish(),
          completion_tokens: v4.z.number().nullish(),
          total_tokens: v4.z.number().nullish(),
          prompt_tokens_details: v4.z.object({
            cached_tokens: v4.z.number().nullish()
          }).nullish(),
          completion_tokens_details: v4.z.object({
            reasoning_tokens: v4.z.number().nullish(),
            accepted_prediction_tokens: v4.z.number().nullish(),
            rejected_prediction_tokens: v4.z.number().nullish()
          }).nullish()
        }).nullish()
      }),
      openaiErrorDataSchema
    ])
  )
);
var openaiChatLanguageModelOptions = chunkOCS2GTEN_cjs.lazyValidator(
  () => chunkOCS2GTEN_cjs.zodSchema(
    v4.z.object({
      /**
       * Modify the likelihood of specified tokens appearing in the completion.
       *
       * Accepts a JSON object that maps tokens (specified by their token ID in
       * the GPT tokenizer) to an associated bias value from -100 to 100.
       */
      logitBias: v4.z.record(v4.z.coerce.number(), v4.z.number()).optional(),
      /**
       * Return the log probabilities of the tokens.
       *
       * Setting to true will return the log probabilities of the tokens that
       * were generated.
       *
       * Setting to a number will return the log probabilities of the top n
       * tokens that were generated.
       */
      logprobs: v4.z.union([v4.z.boolean(), v4.z.number()]).optional(),
      /**
       * Whether to enable parallel function calling during tool use. Default to true.
       */
      parallelToolCalls: v4.z.boolean().optional(),
      /**
       * A unique identifier representing your end-user, which can help OpenAI to
       * monitor and detect abuse.
       */
      user: v4.z.string().optional(),
      /**
       * Reasoning effort for reasoning models. Defaults to `medium`.
       */
      reasoningEffort: v4.z.enum(["none", "minimal", "low", "medium", "high", "xhigh"]).optional(),
      /**
       * Maximum number of completion tokens to generate. Useful for reasoning models.
       */
      maxCompletionTokens: v4.z.number().optional(),
      /**
       * Whether to enable persistence in responses API.
       */
      store: v4.z.boolean().optional(),
      /**
       * Metadata to associate with the request.
       */
      metadata: v4.z.record(v4.z.string().max(64), v4.z.string().max(512)).optional(),
      /**
       * Parameters for prediction mode.
       */
      prediction: v4.z.record(v4.z.string(), v4.z.any()).optional(),
      /**
       * Whether to use structured outputs.
       *
       * @default true
       */
      structuredOutputs: v4.z.boolean().optional(),
      /**
       * Service tier for the request.
       * - 'auto': Default service tier. The request will be processed with the service tier configured in the
       *           Project settings. Unless otherwise configured, the Project will use 'default'.
       * - 'flex': 50% cheaper processing at the cost of increased latency. Only available for o3 and o4-mini models.
       * - 'priority': Higher-speed processing with predictably low latency at premium cost. Available for Enterprise customers.
       * - 'default': The request will be processed with the standard pricing and performance for the selected model.
       *
       * @default 'auto'
       */
      serviceTier: v4.z.enum(["auto", "flex", "priority", "default"]).optional(),
      /**
       * Whether to use strict JSON schema validation.
       *
       * @default false
       */
      strictJsonSchema: v4.z.boolean().optional(),
      /**
       * Controls the verbosity of the model's responses.
       * Lower values will result in more concise responses, while higher values will result in more verbose responses.
       */
      textVerbosity: v4.z.enum(["low", "medium", "high"]).optional(),
      /**
       * A cache key for prompt caching. Allows manual control over prompt caching behavior.
       * Useful for improving cache hit rates and working around automatic caching issues.
       */
      promptCacheKey: v4.z.string().optional(),
      /**
       * The retention policy for the prompt cache.
       * - 'in_memory': Default. Standard prompt caching behavior.
       * - '24h': Extended prompt caching that keeps cached prefixes active for up to 24 hours.
       *          Currently only available for 5.1 series models.
       *
       * @default 'in_memory'
       */
      promptCacheRetention: v4.z.enum(["in_memory", "24h"]).optional(),
      /**
       * A stable identifier used to help detect users of your application
       * that may be violating OpenAI's usage policies. The IDs should be a
       * string that uniquely identifies each user. We recommend hashing their
       * username or email address, in order to avoid sending us any identifying
       * information.
       */
      safetyIdentifier: v4.z.string().optional()
    })
  )
);
function prepareChatTools({
  tools,
  toolChoice,
  structuredOutputs,
  strictJsonSchema
}) {
  tools = (tools == null ? void 0 : tools.length) ? tools : void 0;
  const toolWarnings = [];
  if (tools == null) {
    return { tools: void 0, toolChoice: void 0, toolWarnings };
  }
  const openaiTools = [];
  for (const tool of tools) {
    switch (tool.type) {
      case "function":
        openaiTools.push({
          type: "function",
          function: {
            name: tool.name,
            description: tool.description,
            parameters: tool.inputSchema,
            strict: structuredOutputs ? strictJsonSchema : void 0
          }
        });
        break;
      default:
        toolWarnings.push({ type: "unsupported-tool", tool });
        break;
    }
  }
  if (toolChoice == null) {
    return { tools: openaiTools, toolChoice: void 0, toolWarnings };
  }
  const type = toolChoice.type;
  switch (type) {
    case "auto":
    case "none":
    case "required":
      return { tools: openaiTools, toolChoice: type, toolWarnings };
    case "tool":
      return {
        tools: openaiTools,
        toolChoice: {
          type: "function",
          function: {
            name: toolChoice.toolName
          }
        },
        toolWarnings
      };
    default: {
      const _exhaustiveCheck = type;
      throw new chunkOCS2GTEN_cjs.UnsupportedFunctionalityError({
        functionality: `tool choice type: ${_exhaustiveCheck}`
      });
    }
  }
}
var OpenAIChatLanguageModel = class {
  constructor(modelId, config) {
    this.specificationVersion = "v2";
    this.supportedUrls = {
      "image/*": [/^https?:\/\/.*$/]
    };
    this.modelId = modelId;
    this.config = config;
  }
  get provider() {
    return this.config.provider;
  }
  async getArgs({
    prompt,
    maxOutputTokens,
    temperature,
    topP,
    topK,
    frequencyPenalty,
    presencePenalty,
    stopSequences,
    responseFormat,
    seed,
    tools,
    toolChoice,
    providerOptions
  }) {
    var _a, _b, _c, _d;
    const warnings = [];
    const openaiOptions = (_a = await chunkOCS2GTEN_cjs.parseProviderOptions({
      provider: "openai",
      providerOptions,
      schema: openaiChatLanguageModelOptions
    })) != null ? _a : {};
    const structuredOutputs = (_b = openaiOptions.structuredOutputs) != null ? _b : true;
    const modelCapabilities = getOpenAILanguageModelCapabilities(this.modelId);
    if (topK != null) {
      warnings.push({
        type: "unsupported-setting",
        setting: "topK"
      });
    }
    if ((responseFormat == null ? void 0 : responseFormat.type) === "json" && responseFormat.schema != null && !structuredOutputs) {
      warnings.push({
        type: "unsupported-setting",
        setting: "responseFormat",
        details: "JSON response format schema is only supported with structuredOutputs"
      });
    }
    const { messages, warnings: messageWarnings } = convertToOpenAIChatMessages(
      {
        prompt,
        systemMessageMode: modelCapabilities.systemMessageMode
      }
    );
    warnings.push(...messageWarnings);
    const strictJsonSchema = (_c = openaiOptions.strictJsonSchema) != null ? _c : false;
    const baseArgs = {
      // model id:
      model: this.modelId,
      // model specific settings:
      logit_bias: openaiOptions.logitBias,
      logprobs: openaiOptions.logprobs === true || typeof openaiOptions.logprobs === "number" ? true : void 0,
      top_logprobs: typeof openaiOptions.logprobs === "number" ? openaiOptions.logprobs : typeof openaiOptions.logprobs === "boolean" ? openaiOptions.logprobs ? 0 : void 0 : void 0,
      user: openaiOptions.user,
      parallel_tool_calls: openaiOptions.parallelToolCalls,
      // standardized settings:
      max_tokens: maxOutputTokens,
      temperature,
      top_p: topP,
      frequency_penalty: frequencyPenalty,
      presence_penalty: presencePenalty,
      response_format: (responseFormat == null ? void 0 : responseFormat.type) === "json" ? structuredOutputs && responseFormat.schema != null ? {
        type: "json_schema",
        json_schema: {
          schema: responseFormat.schema,
          strict: strictJsonSchema,
          name: (_d = responseFormat.name) != null ? _d : "response",
          description: responseFormat.description
        }
      } : { type: "json_object" } : void 0,
      stop: stopSequences,
      seed,
      verbosity: openaiOptions.textVerbosity,
      // openai specific settings:
      // TODO AI SDK 6: remove, we auto-map maxOutputTokens now
      max_completion_tokens: openaiOptions.maxCompletionTokens,
      store: openaiOptions.store,
      metadata: openaiOptions.metadata,
      prediction: openaiOptions.prediction,
      reasoning_effort: openaiOptions.reasoningEffort,
      service_tier: openaiOptions.serviceTier,
      prompt_cache_key: openaiOptions.promptCacheKey,
      prompt_cache_retention: openaiOptions.promptCacheRetention,
      safety_identifier: openaiOptions.safetyIdentifier,
      // messages:
      messages
    };
    if (modelCapabilities.isReasoningModel) {
      if (openaiOptions.reasoningEffort !== "none" || !modelCapabilities.supportsNonReasoningParameters) {
        if (baseArgs.temperature != null) {
          baseArgs.temperature = void 0;
          warnings.push({
            type: "unsupported-setting",
            setting: "temperature",
            details: "temperature is not supported for reasoning models"
          });
        }
        if (baseArgs.top_p != null) {
          baseArgs.top_p = void 0;
          warnings.push({
            type: "unsupported-setting",
            setting: "topP",
            details: "topP is not supported for reasoning models"
          });
        }
        if (baseArgs.logprobs != null) {
          baseArgs.logprobs = void 0;
          warnings.push({
            type: "other",
            message: "logprobs is not supported for reasoning models"
          });
        }
      }
      if (baseArgs.frequency_penalty != null) {
        baseArgs.frequency_penalty = void 0;
        warnings.push({
          type: "unsupported-setting",
          setting: "frequencyPenalty",
          details: "frequencyPenalty is not supported for reasoning models"
        });
      }
      if (baseArgs.presence_penalty != null) {
        baseArgs.presence_penalty = void 0;
        warnings.push({
          type: "unsupported-setting",
          setting: "presencePenalty",
          details: "presencePenalty is not supported for reasoning models"
        });
      }
      if (baseArgs.logit_bias != null) {
        baseArgs.logit_bias = void 0;
        warnings.push({
          type: "other",
          message: "logitBias is not supported for reasoning models"
        });
      }
      if (baseArgs.top_logprobs != null) {
        baseArgs.top_logprobs = void 0;
        warnings.push({
          type: "other",
          message: "topLogprobs is not supported for reasoning models"
        });
      }
      if (baseArgs.max_tokens != null) {
        if (baseArgs.max_completion_tokens == null) {
          baseArgs.max_completion_tokens = baseArgs.max_tokens;
        }
        baseArgs.max_tokens = void 0;
      }
    } else if (this.modelId.startsWith("gpt-4o-search-preview") || this.modelId.startsWith("gpt-4o-mini-search-preview")) {
      if (baseArgs.temperature != null) {
        baseArgs.temperature = void 0;
        warnings.push({
          type: "unsupported-setting",
          setting: "temperature",
          details: "temperature is not supported for the search preview models and has been removed."
        });
      }
    }
    if (openaiOptions.serviceTier === "flex" && !modelCapabilities.supportsFlexProcessing) {
      warnings.push({
        type: "unsupported-setting",
        setting: "serviceTier",
        details: "flex processing is only available for o3, o4-mini, and gpt-5 models"
      });
      baseArgs.service_tier = void 0;
    }
    if (openaiOptions.serviceTier === "priority" && !modelCapabilities.supportsPriorityProcessing) {
      warnings.push({
        type: "unsupported-setting",
        setting: "serviceTier",
        details: "priority processing is only available for supported models (gpt-4, gpt-5, gpt-5-mini, o3, o4-mini) and requires Enterprise access. gpt-5-nano is not supported"
      });
      baseArgs.service_tier = void 0;
    }
    const {
      tools: openaiTools,
      toolChoice: openaiToolChoice,
      toolWarnings
    } = prepareChatTools({
      tools,
      toolChoice,
      structuredOutputs,
      strictJsonSchema
    });
    return {
      args: {
        ...baseArgs,
        tools: openaiTools,
        tool_choice: openaiToolChoice
      },
      warnings: [...warnings, ...toolWarnings]
    };
  }
  async doGenerate(options) {
    var _a, _b, _c, _d, _e, _f, _g, _h, _i, _j, _k, _l, _m, _n;
    const { args: body, warnings } = await this.getArgs(options);
    const {
      responseHeaders,
      value: response,
      rawValue: rawResponse
    } = await chunkOCS2GTEN_cjs.postJsonToApi({
      url: this.config.url({
        path: "/chat/completions",
        modelId: this.modelId
      }),
      headers: chunkOCS2GTEN_cjs.combineHeaders(this.config.headers(), options.headers),
      body,
      failedResponseHandler: openaiFailedResponseHandler,
      successfulResponseHandler: chunkOCS2GTEN_cjs.createJsonResponseHandler(
        openaiChatResponseSchema
      ),
      abortSignal: options.abortSignal,
      fetch: this.config.fetch
    });
    const choice = response.choices[0];
    const content = [];
    const text = choice.message.content;
    if (text != null && text.length > 0) {
      content.push({ type: "text", text });
    }
    for (const toolCall of (_a = choice.message.tool_calls) != null ? _a : []) {
      content.push({
        type: "tool-call",
        toolCallId: (_b = toolCall.id) != null ? _b : chunkOCS2GTEN_cjs.generateId(),
        toolName: toolCall.function.name,
        input: toolCall.function.arguments
      });
    }
    for (const annotation of (_c = choice.message.annotations) != null ? _c : []) {
      content.push({
        type: "source",
        sourceType: "url",
        id: chunkOCS2GTEN_cjs.generateId(),
        url: annotation.url_citation.url,
        title: annotation.url_citation.title
      });
    }
    const completionTokenDetails = (_d = response.usage) == null ? void 0 : _d.completion_tokens_details;
    const promptTokenDetails = (_e = response.usage) == null ? void 0 : _e.prompt_tokens_details;
    const providerMetadata = { openai: {} };
    if ((completionTokenDetails == null ? void 0 : completionTokenDetails.accepted_prediction_tokens) != null) {
      providerMetadata.openai.acceptedPredictionTokens = completionTokenDetails == null ? void 0 : completionTokenDetails.accepted_prediction_tokens;
    }
    if ((completionTokenDetails == null ? void 0 : completionTokenDetails.rejected_prediction_tokens) != null) {
      providerMetadata.openai.rejectedPredictionTokens = completionTokenDetails == null ? void 0 : completionTokenDetails.rejected_prediction_tokens;
    }
    if (((_f = choice.logprobs) == null ? void 0 : _f.content) != null) {
      providerMetadata.openai.logprobs = choice.logprobs.content;
    }
    return {
      content,
      finishReason: mapOpenAIFinishReason(choice.finish_reason),
      usage: {
        inputTokens: (_h = (_g = response.usage) == null ? void 0 : _g.prompt_tokens) != null ? _h : void 0,
        outputTokens: (_j = (_i = response.usage) == null ? void 0 : _i.completion_tokens) != null ? _j : void 0,
        totalTokens: (_l = (_k = response.usage) == null ? void 0 : _k.total_tokens) != null ? _l : void 0,
        reasoningTokens: (_m = completionTokenDetails == null ? void 0 : completionTokenDetails.reasoning_tokens) != null ? _m : void 0,
        cachedInputTokens: (_n = promptTokenDetails == null ? void 0 : promptTokenDetails.cached_tokens) != null ? _n : void 0
      },
      request: { body },
      response: {
        ...getResponseMetadata(response),
        headers: responseHeaders,
        body: rawResponse
      },
      warnings,
      providerMetadata
    };
  }
  async doStream(options) {
    const { args, warnings } = await this.getArgs(options);
    const body = {
      ...args,
      stream: true,
      stream_options: {
        include_usage: true
      }
    };
    const { responseHeaders, value: response } = await chunkOCS2GTEN_cjs.postJsonToApi({
      url: this.config.url({
        path: "/chat/completions",
        modelId: this.modelId
      }),
      headers: chunkOCS2GTEN_cjs.combineHeaders(this.config.headers(), options.headers),
      body,
      failedResponseHandler: openaiFailedResponseHandler,
      successfulResponseHandler: chunkOCS2GTEN_cjs.createEventSourceResponseHandler(
        openaiChatChunkSchema
      ),
      abortSignal: options.abortSignal,
      fetch: this.config.fetch
    });
    const toolCalls = [];
    let finishReason = "unknown";
    const usage = {
      inputTokens: void 0,
      outputTokens: void 0,
      totalTokens: void 0
    };
    let metadataExtracted = false;
    let isActiveText = false;
    const providerMetadata = { openai: {} };
    return {
      stream: response.pipeThrough(
        new TransformStream({
          start(controller) {
            controller.enqueue({ type: "stream-start", warnings });
          },
          transform(chunk, controller) {
            var _a, _b, _c, _d, _e, _f, _g, _h, _i, _j, _k, _l, _m, _n, _o, _p, _q, _r, _s, _t, _u, _v, _w, _x;
            if (options.includeRawChunks) {
              controller.enqueue({ type: "raw", rawValue: chunk.rawValue });
            }
            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 (!metadataExtracted) {
              const metadata = getResponseMetadata(value);
              if (Object.values(metadata).some(Boolean)) {
                metadataExtracted = true;
                controller.enqueue({
                  type: "response-metadata",
                  ...getResponseMetadata(value)
                });
              }
            }
            if (value.usage != null) {
              usage.inputTokens = (_a = value.usage.prompt_tokens) != null ? _a : void 0;
              usage.outputTokens = (_b = value.usage.completion_tokens) != null ? _b : void 0;
              usage.totalTokens = (_c = value.usage.total_tokens) != null ? _c : void 0;
              usage.reasoningTokens = (_e = (_d = value.usage.completion_tokens_details) == null ? void 0 : _d.reasoning_tokens) != null ? _e : void 0;
              usage.cachedInputTokens = (_g = (_f = value.usage.prompt_tokens_details) == null ? void 0 : _f.cached_tokens) != null ? _g : void 0;
              if (((_h = value.usage.completion_tokens_details) == null ? void 0 : _h.accepted_prediction_tokens) != null) {
                providerMetadata.openai.acceptedPredictionTokens = (_i = value.usage.completion_tokens_details) == null ? void 0 : _i.accepted_prediction_tokens;
              }
              if (((_j = value.usage.completion_tokens_details) == null ? void 0 : _j.rejected_prediction_tokens) != null) {
                providerMetadata.openai.rejectedPredictionTokens = (_k = value.usage.completion_tokens_details) == null ? void 0 : _k.rejected_prediction_tokens;
              }
            }
            const choice = value.choices[0];
            if ((choice == null ? void 0 : choice.finish_reason) != null) {
              finishReason = mapOpenAIFinishReason(choice.finish_reason);
            }
            if (((_l = choice == null ? void 0 : choice.logprobs) == null ? void 0 : _l.content) != null) {
              providerMetadata.openai.logprobs = choice.logprobs.content;
            }
            if ((choice == null ? void 0 : choice.delta) == null) {
              return;
            }
            const delta = choice.delta;
            if (delta.content != null) {
              if (!isActiveText) {
                controller.enqueue({ type: "text-start", id: "0" });
                isActiveText = true;
              }
              controller.enqueue({
                type: "text-delta",
                id: "0",
                delta: 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 != null && toolCallDelta.type !== "function") {
                    throw new chunkOCS2GTEN_cjs.InvalidResponseDataError({
                      data: toolCallDelta,
                      message: `Expected 'function' type.`
                    });
                  }
                  if (toolCallDelta.id == null) {
                    throw new chunkOCS2GTEN_cjs.InvalidResponseDataError({
                      data: toolCallDelta,
                      message: `Expected 'id' to be a string.`
                    });
                  }
                  if (((_m = toolCallDelta.function) == null ? void 0 : _m.name) == null) {
                    throw new chunkOCS2GTEN_cjs.InvalidResponseDataError({
                      data: toolCallDelta,
                      message: `Expected 'function.name' to be a string.`
                    });
                  }
                  controller.enqueue({
                    type: "tool-input-start",
                    id: toolCallDelta.id,
                    toolName: toolCallDelta.function.name
                  });
                  toolCalls[index] = {
                    id: toolCallDelta.id,
                    type: "function",
                    function: {
                      name: toolCallDelta.function.name,
                      arguments: (_n = toolCallDelta.function.arguments) != null ? _n : ""
                    },
                    hasFinished: false
                  };
                  const toolCall2 = toolCalls[index];
                  if (((_o = toolCall2.function) == null ? void 0 : _o.name) != null && ((_p = toolCall2.function) == null ? void 0 : _p.arguments) != null) {
                    if (toolCall2.function.arguments.length > 0) {
                      controller.enqueue({
                        type: "tool-input-delta",
                        id: toolCall2.id,
                        delta: toolCall2.function.arguments
                      });
                    }
                    if (chunkOCS2GTEN_cjs.isParsableJson(toolCall2.function.arguments)) {
                      controller.enqueue({
                        type: "tool-input-end",
                        id: toolCall2.id
                      });
                      controller.enqueue({
                        type: "tool-call",
                        toolCallId: (_q = toolCall2.id) != null ? _q : chunkOCS2GTEN_cjs.generateId(),
                        toolName: toolCall2.function.name,
                        input: toolCall2.function.arguments
                      });
                      toolCall2.hasFinished = true;
                    }
                  }
                  continue;
                }
                const toolCall = toolCalls[index];
                if (toolCall.hasFinished) {
                  continue;
                }
                if (((_r = toolCallDelta.function) == null ? void 0 : _r.arguments) != null) {
                  toolCall.function.arguments += (_t = (_s = toolCallDelta.function) == null ? void 0 : _s.arguments) != null ? _t : "";
                }
                controller.enqueue({
                  type: "tool-input-delta",
                  id: toolCall.id,
                  delta: (_u = toolCallDelta.function.arguments) != null ? _u : ""
                });
                if (((_v = toolCall.function) == null ? void 0 : _v.name) != null && ((_w = toolCall.function) == null ? void 0 : _w.arguments) != null && chunkOCS2GTEN_cjs.isParsableJson(toolCall.function.arguments)) {
                  controller.enqueue({
                    type: "tool-input-end",
                    id: toolCall.id
                  });
                  controller.enqueue({
                    type: "tool-call",
                    toolCallId: (_x = toolCall.id) != null ? _x : chunkOCS2GTEN_cjs.generateId(),
                    toolName: toolCall.function.name,
                    input: toolCall.function.arguments
                  });
                  toolCall.hasFinished = true;
                }
              }
            }
            if (delta.annotations != null) {
              for (const annotation of delta.annotations) {
                controller.enqueue({
                  type: "source",
                  sourceType: "url",
                  id: chunkOCS2GTEN_cjs.generateId(),
                  url: annotation.url_citation.url,
                  title: annotation.url_citation.title
                });
              }
            }
          },
          flush(controller) {
            if (isActiveText) {
              controller.enqueue({ type: "text-end", id: "0" });
            }
            controller.enqueue({
              type: "finish",
              finishReason,
              usage,
              ...providerMetadata != null ? { providerMetadata } : {}
            });
          }
        })
      ),
      request: { body },
      response: { headers: responseHeaders }
    };
  }
};
function convertToOpenAICompletionPrompt({
  prompt,
  user = "user",
  assistant = "assistant"
}) {
  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 chunkOCS2GTEN_cjs.InvalidPromptError({
          message: "Unexpected system message in prompt: ${content}",
          prompt
        });
      }
      case "user": {
        const userMessage = content.map((part) => {
          switch (part.type) {
            case "text": {
              return part.text;
            }
          }
        }).filter(Boolean).join("");
        text += `${user}:
${userMessage}

`;
        break;
      }
      case "assistant": {
        const assistantMessage = content.map((part) => {
          switch (part.type) {
            case "text": {
              return part.text;
            }
            case "tool-call": {
              throw new chunkOCS2GTEN_cjs.UnsupportedFunctionalityError({
                functionality: "tool-call messages"
              });
            }
          }
        }).join("");
        text += `${assistant}:
${assistantMessage}

`;
        break;
      }
      case "tool": {
        throw new chunkOCS2GTEN_cjs.UnsupportedFunctionalityError({
          functionality: "tool messages"
        });
      }
      default: {
        const _exhaustiveCheck = role;
        throw new Error(`Unsupported role: ${_exhaustiveCheck}`);
      }
    }
  }
  text += `${assistant}:
`;
  return {
    prompt: text,
    stopSequences: [`
${user}:`]
  };
}
function getResponseMetadata2({
  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
  };
}
function mapOpenAIFinishReason2(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";
  }
}
var openaiCompletionResponseSchema = chunkOCS2GTEN_cjs.lazyValidator(
  () => chunkOCS2GTEN_cjs.zodSchema(
    v4.z.object({
      id: v4.z.string().nullish(),
      created: v4.z.number().nullish(),
      model: v4.z.string().nullish(),
      choices: v4.z.array(
        v4.z.object({
          text: v4.z.string(),
          finish_reason: v4.z.string(),
          logprobs: v4.z.object({
            tokens: v4.z.array(v4.z.string()),
            token_logprobs: v4.z.array(v4.z.number()),
            top_logprobs: v4.z.array(v4.z.record(v4.z.string(), v4.z.number())).nullish()
          }).nullish()
        })
      ),
      usage: v4.z.object({
        prompt_tokens: v4.z.number(),
        completion_tokens: v4.z.number(),
        total_tokens: v4.z.number()
      }).nullish()
    })
  )
);
var openaiCompletionChunkSchema = chunkOCS2GTEN_cjs.lazyValidator(
  () => chunkOCS2GTEN_cjs.zodSchema(
    v4.z.union([
      v4.z.object({
        id: v4.z.string().nullish(),
        created: v4.z.number().nullish(),
        model: v4.z.string().nullish(),
        choices: v4.z.array(
          v4.z.object({
            text: v4.z.string(),
            finish_reason: v4.z.string().nullish(),
            index: v4.z.number(),
            logprobs: v4.z.object({
              tokens: v4.z.array(v4.z.string()),
              token_logprobs: v4.z.array(v4.z.number()),
              top_logprobs: v4.z.array(v4.z.record(v4.z.string(), v4.z.number())).nullish()
            }).nullish()
          })
        ),
        usage: v4.z.object({
          prompt_tokens: v4.z.number(),
          completion_tokens: v4.z.number(),
          total_tokens: v4.z.number()
        }).nullish()
      }),
      openaiErrorDataSchema
    ])
  )
);
var openaiCompletionProviderOptions = chunkOCS2GTEN_cjs.lazyValidator(
  () => chunkOCS2GTEN_cjs.zodSchema(
    v4.z.object({
      /**
      Echo back the prompt in addition to the completion.
         */
      echo: v4.z.boolean().optional(),
      /**
      Modify the likelihood of specified tokens appearing in the completion.
      
      Accepts a JSON object that maps tokens (specified by their token ID in
      the GPT tokenizer) to an associated bias value from -100 to 100. You
      can use this tokenizer tool to convert text to token IDs. Mathematically,
      the bias is added to the logits generated by the model prior to sampling.
      The exact effect will vary per model, but values between -1 and 1 should
      decrease or increase likelihood of selection; values like -100 or 100
      should result in a ban or exclusive selection of the relevant token.
      
      As an example, you can pass {"50256": -100} to prevent the <|endoftext|>
      token from being generated.
       */
      logitBias: v4.z.record(v4.z.string(), v4.z.number()).optional(),
      /**
      The suffix that comes after a completion of inserted text.
       */
      suffix: v4.z.string().optional(),
      /**
      A unique identifier representing your end-user, which can help OpenAI to
      monitor and detect abuse. Learn more.
       */
      user: v4.z.string().optional(),
      /**
      Return the log probabilities of the tokens. Including logprobs will increase
      the response size and can slow down response times. However, it can
      be useful to better understand how the model is behaving.
      Setting to true will return the log probabilities of the tokens that
      were generated.
      Setting to a number will return the log probabilities of the top n
      tokens that were generated.
         */
      logprobs: v4.z.union([v4.z.boolean(), v4.z.number()]).optional()
    })
  )
);
var OpenAICompletionLanguageModel = class {
  constructor(modelId, config) {
    this.specificationVersion = "v2";
    this.supportedUrls = {
      // No URLs are supported for completion models.
    };
    this.modelId = modelId;
    this.config = config;
  }
  get providerOptionsName() {
    return this.config.provider.split(".")[0].trim();
  }
  get provider() {
    return this.config.provider;
  }
  async getArgs({
    prompt,
    maxOutputTokens,
    temperature,
    topP,
    topK,
    frequencyPenalty,
    presencePenalty,
    stopSequences: userStopSequences,
    responseFormat,
    tools,
    toolChoice,
    seed,
    providerOptions
  }) {
    const warnings = [];
    const openaiOptions = {
      ...await chunkOCS2GTEN_cjs.parseProviderOptions({
        provider: "openai",
        providerOptions,
        schema: openaiCompletionProviderOptions
      }),
      ...await chunkOCS2GTEN_cjs.parseProviderOptions({
        provider: this.providerOptionsName,
        providerOptions,
        schema: openaiCompletionProviderOptions
      })
    };
    if (topK != null) {
      warnings.push({ type: "unsupported-setting", setting: "topK" });
    }
    if (tools == null ? void 0 : tools.length) {
      warnings.push({ type: "unsupported-setting", setting: "tools" });
    }
    if (toolChoice != null) {
      warnings.push({ type: "unsupported-setting", setting: "toolChoice" });
    }
    if (responseFormat != null && responseFormat.type !== "text") {
      warnings.push({
        type: "unsupported-setting",
        setting: "responseFormat",
        details: "JSON response format is not supported."
      });
    }
    const { prompt: completionPrompt, stopSequences } = convertToOpenAICompletionPrompt({ prompt });
    const stop = [...stopSequences != null ? stopSequences : [], ...userStopSequences != null ? userStopSequences : []];
    return {
      args: {
        // model id:
        model: this.modelId,
        // model specific settings:
        echo: openaiOptions.echo,
        logit_bias: openaiOptions.logitBias,
        logprobs: (openaiOptions == null ? void 0 : openaiOptions.logprobs) === true ? 0 : (openaiOptions == null ? void 0 : openaiOptions.logprobs) === false ? void 0 : openaiOptions == null ? void 0 : openaiOptions.logprobs,
        suffix: openaiOptions.suffix,
        user: openaiOptions.user,
        // standardized settings:
        max_tokens: maxOutputTokens,
        temperature,
        top_p: topP,
        frequency_penalty: frequencyPenalty,
        presence_penalty: presencePenalty,
        seed,
        // prompt:
        prompt: completionPrompt,
        // stop sequences:
        stop: stop.length > 0 ? stop : void 0
      },
      warnings
    };
  }
  async doGenerate(options) {
    var _a, _b, _c;
    const { args, warnings } = await this.getArgs(options);
    const {
      responseHeaders,
      value: response,
      rawValue: rawResponse
    } = await chunkOCS2GTEN_cjs.postJsonToApi({
      url: this.config.url({
        path: "/completions",
        modelId: this.modelId
      }),
      headers: chunkOCS2GTEN_cjs.combineHeaders(this.config.headers(), options.headers),
      body: args,
      failedResponseHandler: openaiFailedResponseHandler,
      successfulResponseHandler: chunkOCS2GTEN_cjs.createJsonResponseHandler(
        openaiCompletionResponseSchema
      ),
      abortSignal: options.abortSignal,
      fetch: this.config.fetch
    });
    const choice = response.choices[0];
    const providerMetadata = { openai: {} };
    if (choice.logprobs != null) {
      providerMetadata.openai.logprobs = choice.logprobs;
    }
    return {
      content: [{ type: "text", text: choice.text }],
      usage: {
        inputTokens: (_a = response.usage) == null ? void 0 : _a.prompt_tokens,
        outputTokens: (_b = response.usage) == null ? void 0 : _b.completion_tokens,
        totalTokens: (_c = response.usage) == null ? void 0 : _c.total_tokens
      },
      finishReason: mapOpenAIFinishReason2(choice.finish_reason),
      request: { body: args },
      response: {
        ...getResponseMetadata2(response),
        headers: responseHeaders,
        body: rawResponse
      },
      providerMetadata,
      warnings
    };
  }
  async doStream(options) {
    const { args, warnings } = await this.getArgs(options);
    const body = {
      ...args,
      stream: true,
      stream_options: {
        include_usage: true
      }
    };
    const { responseHeaders, value: response } = await chunkOCS2GTEN_cjs.postJsonToApi({
      url: this.config.url({
        path: "/completions",
        modelId: this.modelId
      }),
      headers: chunkOCS2GTEN_cjs.combineHeaders(this.config.headers(), options.headers),
      body,
      failedResponseHandler: openaiFailedResponseHandler,
      successfulResponseHandler: chunkOCS2GTEN_cjs.createEventSourceResponseHandler(
        openaiCompletionChunkSchema
      ),
      abortSignal: options.abortSignal,
      fetch: this.config.fetch
    });
    let finishReason = "unknown";
    const providerMetadata = { openai: {} };
    const usage = {
      inputTokens: void 0,
      outputTokens: void 0,
      totalTokens: void 0
    };
    let isFirstChunk = true;
    return {
      stream: response.pipeThrough(
        new TransformStream({
          start(controller) {
            controller.enqueue({ type: "stream-start", warnings });
          },
          transform(chunk, controller) {
            if (options.includeRawChunks) {
              controller.enqueue({ type: "raw", rawValue: chunk.rawValue });
            }
            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",
                ...getResponseMetadata2(value)
              });
              controller.enqueue({ type: "text-start", id: "0" });
            }
            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 == null ? void 0 : choice.finish_reason) != null) {
              finishReason = mapOpenAIFinishReason2(choice.finish_reason);
            }
            if ((choice == null ? void 0 : choice.logprobs) != null) {
              providerMetadata.openai.logprobs = choice.logprobs;
            }
            if ((choice == null ? void 0 : choice.text) != null && choice.text.length > 0) {
              controller.enqueue({
                type: "text-delta",
                id: "0",
                delta: choice.text
              });
            }
          },
          flush(controller) {
            if (!isFirstChunk) {
              controller.enqueue({ type: "text-end", id: "0" });
            }
            controller.enqueue({
              type: "finish",
              finishReason,
              providerMetadata,
              usage
            });
          }
        })
      ),
      request: { body },
      response: { headers: responseHeaders }
    };
  }
};
var openaiEmbeddingProviderOptions = chunkOCS2GTEN_cjs.lazyValidator(
  () => chunkOCS2GTEN_cjs.zodSchema(
    v4.z.object({
      /**
      The number of dimensions the resulting output embeddings should have.
      Only supported in text-embedding-3 and later models.
         */
      dimensions: v4.z.number().optional(),
      /**
      A unique identifier representing your end-user, which can help OpenAI to
      monitor and detect abuse. Learn more.
      */
      user: v4.z.string().optional()
    })
  )
);
var openaiTextEmbeddingResponseSchema = chunkOCS2GTEN_cjs.lazyValidator(
  () => chunkOCS2GTEN_cjs.zodSchema(
    v4.z.object({
      data: v4.z.array(v4.z.object({ embedding: v4.z.array(v4.z.number()) })),
      usage: v4.z.object({ prompt_tokens: v4.z.number() }).nullish()
    })
  )
);
var OpenAIEmbeddingModel = class {
  constructor(modelId, config) {
    this.specificationVersion = "v2";
    this.maxEmbeddingsPerCall = 2048;
    this.supportsParallelCalls = true;
    this.modelId = modelId;
    this.config = config;
  }
  get provider() {
    return this.config.provider;
  }
  async doEmbed({
    values,
    headers,
    abortSignal,
    providerOptions
  }) {
    var _a;
    if (values.length > this.maxEmbeddingsPerCall) {
      throw new chunkOCS2GTEN_cjs.TooManyEmbeddingValuesForCallError({
        provider: this.provider,
        modelId: this.modelId,
        maxEmbeddingsPerCall: this.maxEmbeddingsPerCall,
        values
      });
    }
    const openaiOptions = (_a = await chunkOCS2GTEN_cjs.parseProviderOptions({
      provider: "openai",
      providerOptions,
      schema: openaiEmbeddingProviderOptions
    })) != null ? _a : {};
    const {
      responseHeaders,
      value: response,
      rawValue
    } = await chunkOCS2GTEN_cjs.postJsonToApi({
      url: this.config.url({
        path: "/embeddings",
        modelId: this.modelId
      }),
      headers: chunkOCS2GTEN_cjs.combineHeaders(this.config.headers(), headers),
      body: {
        model: this.modelId,
        input: values,
        encoding_format: "float",
        dimensions: openaiOptions.dimensions,
        user: openaiOptions.user
      },
      failedResponseHandler: openaiFailedResponseHandler,
      successfulResponseHandler: chunkOCS2GTEN_cjs.createJsonResponseHandler(
        openaiTextEmbeddingResponseSchema
      ),
      abortSignal,
      fetch: this.config.fetch
    });
    return {
      embeddings: response.data.map((item) => item.embedding),
      usage: response.usage ? { tokens: response.usage.prompt_tokens } : void 0,
      response: { headers: responseHeaders, body: rawValue }
    };
  }
};
var openaiImageResponseSchema = chunkOCS2GTEN_cjs.lazyValidator(
  () => chunkOCS2GTEN_cjs.zodSchema(
    v4.z.object({
      created: v4.z.number().nullish(),
      data: v4.z.array(
        v4.z.object({
          b64_json: v4.z.string(),
          revised_prompt: v4.z.string().nullish()
        })
      ),
      background: v4.z.string().nullish(),
      output_format: v4.z.string().nullish(),
      size: v4.z.string().nullish(),
      quality: v4.z.string().nullish(),
      usage: v4.z.object({
        input_tokens: v4.z.number().nullish(),
        output_tokens: v4.z.number().nullish(),
        total_tokens: v4.z.number().nullish(),
        input_tokens_details: v4.z.object({
          image_tokens: v4.z.number().nullish(),
          text_tokens: v4.z.number().nullish()
        }).nullish()
      }).nullish()
    })
  )
);
var modelMaxImagesPerCall = {
  "dall-e-3": 1,
  "dall-e-2": 10,
  "gpt-image-1": 10,
  "gpt-image-1-mini": 10,
  "gpt-image-1.5": 10,
  "gpt-image-2": 10
};
var hasDefaultResponseFormat = /* @__PURE__ */ new Set([
  "gpt-image-1",
  "gpt-image-1-mini",
  "gpt-image-1.5",
  "gpt-image-2"
]);
var baseImageModelOptionsObject = v4.z.object({
  /**
   * Quality of the generated image(s).
   *
   * Valid values: `standard`, `hd`, `low`, `medium`, `high`, `auto`.
   */
  quality: v4.z.enum(["standard", "hd", "low", "medium", "high", "auto"]).optional(),
  /**
   * Background behavior for the generated image(s).
   *
   * If `transparent`, the output format must support transparency
   * (i.e. `png` or `webp`).
   */
  background: v4.z.enum(["transparent", "opaque", "auto"]).optional(),
  /**
   * Format in which the generated image(s) are returned.
   */
  outputFormat: v4.z.enum(["png", "jpeg", "webp"]).optional(),
  /**
   * Compression level (0-100) for the generated image(s). Applies to the
   * `jpeg` and `webp` output formats.
   */
  outputCompression: v4.z.number().int().min(0).max(100).optional(),
  /**
   * A unique identifier representing your end-user, which can help OpenAI
   * to monitor and detect abuse.
   */
  user: v4.z.string().optional()
});
chunkOCS2GTEN_cjs.lazyValidator(
  () => chunkOCS2GTEN_cjs.zodSchema(baseImageModelOptionsObject)
);
var openaiImageModelGenerationOptions = chunkOCS2GTEN_cjs.lazyValidator(
  () => chunkOCS2GTEN_cjs.zodSchema(
    baseImageModelOptionsObject.extend({
      /**
       * Style of the generated image. `vivid` produces hyper-real and
       * dramatic images; `natural` produces more subdued, less hyper-real
       * looking images.
       */
      style: v4.z.enum(["vivid", "natural"]).optional(),
      /**
       * Content moderation level for the generated image(s). `low` applies
       * less restrictive filtering.
       */
      moderation: v4.z.enum(["auto", "low"]).optional()
    })
  )
);
var OpenAIImageModel = class {
  constructor(modelId, config) {
    this.modelId = modelId;
    this.config = config;
    this.specificationVersion = "v2";
  }
  get maxImagesPerCall() {
    var _a;
    return (_a = modelMaxImagesPerCall[this.modelId]) != null ? _a : 1;
  }
  get provider() {
    return this.config.provider;
  }
  async doGenerate({
    prompt,
    n,
    size,
    aspectRatio,
    seed,
    providerOptions,
    headers,
    abortSignal
  }) {
    var _a, _b, _c, _d;
    const warnings = [];
    if (aspectRatio != null) {
      warnings.push({
        type: "unsupported-setting",
        setting: "aspectRatio",
        details: "This model does not support aspect ratio. Use `size` instead."
      });
    }
    if (seed != null) {
      warnings.push({ type: "unsupported-setting", setting: "seed" });
    }
    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 openaiOptions = (_d = await chunkOCS2GTEN_cjs.parseProviderOptions({
      provider: "openai",
      providerOptions,
      schema: openaiImageModelGenerationOptions
    })) != null ? _d : {};
    const { value: response, responseHeaders } = await chunkOCS2GTEN_cjs.postJsonToApi({
      url: this.config.url({
        path: "/images/generations",
        modelId: this.modelId
      }),
      headers: chunkOCS2GTEN_cjs.combineHeaders(this.config.headers(), headers),
      body: {
        model: this.modelId,
        prompt,
        n,
        size,
        quality: openaiOptions.quality,
        style: openaiOptions.style,
        background: openaiOptions.background,
        moderation: openaiOptions.moderation,
        output_format: openaiOptions.outputFormat,
        output_compression: openaiOptions.outputCompression,
        user: openaiOptions.user,
        ...!hasDefaultResponseFormat.has(this.modelId) ? { response_format: "b64_json" } : {}
      },
      failedResponseHandler: openaiFailedResponseHandler,
      successfulResponseHandler: chunkOCS2GTEN_cjs.createJsonResponseHandler(
        openaiImageResponseSchema
      ),
      abortSignal,
      fetch: this.config.fetch
    });
    return {
      images: response.data.map((item) => item.b64_json),
      warnings,
      response: {
        timestamp: currentDate,
        modelId: this.modelId,
        headers: responseHeaders
      },
      providerMetadata: {
        openai: {
          images: response.data.map((item, index) => ({
            ...item.revised_prompt ? { revisedPrompt: item.revised_prompt } : {},
            ...response.created != null ? { created: response.created } : {},
            ...response.size != null ? { size: response.size } : {},
            ...response.quality != null ? { quality: response.quality } : {},
            ...response.background != null ? { background: response.background } : {},
            ...response.output_format != null ? { outputFormat: response.output_format } : {},
            ...distributeTokenDetails(
              response.usage,
              index,
              response.data.length
            )
          }))
        }
      }
    };
  }
};
function distributeTokenDetails(usage, index, total) {
  if (usage == null) {
    return {};
  }
  const result = {};
  const details = usage.input_tokens_details;
  if ((details == null ? void 0 : details.image_tokens) != null) {
    const base = Math.floor(details.image_tokens / total);
    const remainder = details.image_tokens - base * (total - 1);
    result.imageTokens = index === total - 1 ? remainder : base;
  }
  if ((details == null ? void 0 : details.text_tokens) != null) {
    const base = Math.floor(details.text_tokens / total);
    const remainder = details.text_tokens - base * (total - 1);
    result.textTokens = index === total - 1 ? remainder : base;
  }
  if (usage.input_tokens != null) {
    const base = Math.floor(usage.input_tokens / total);
    const remainder = usage.input_tokens - base * (total - 1);
    result.inputTokens = index === total - 1 ? remainder : base;
  }
  if (usage.output_tokens != null) {
    const base = Math.floor(usage.output_tokens / total);
    const remainder = usage.output_tokens - base * (total - 1);
    result.outputTokens = index === total - 1 ? remainder : base;
  }
  return result;
}
var openaiTranscriptionResponseSchema = chunkOCS2GTEN_cjs.lazyValidator(
  () => chunkOCS2GTEN_cjs.zodSchema(
    v4.z.object({
      text: v4.z.string(),
      language: v4.z.string().nullish(),
      duration: v4.z.number().nullish(),
      words: v4.z.array(
        v4.z.object({
          word: v4.z.string(),
          start: v4.z.number(),
          end: v4.z.number()
        })
      ).nullish(),
      segments: v4.z.array(
        v4.z.object({
          id: v4.z.number(),
          seek: v4.z.number(),
          start: v4.z.number(),
          end: v4.z.number(),
          text: v4.z.string(),
          tokens: v4.z.array(v4.z.number()),
          temperature: v4.z.number(),
          avg_logprob: v4.z.number(),
          compression_ratio: v4.z.number(),
          no_speech_prob: v4.z.number()
        })
      ).nullish()
    })
  )
);
var openAITranscriptionProviderOptions = chunkOCS2GTEN_cjs.lazyValidator(
  () => chunkOCS2GTEN_cjs.zodSchema(
    v4.z.object({
      /**
       * Additional information to include in the transcription response.
       */
      include: v4.z.array(v4.z.string()).optional(),
      /**
       * The language of the input audio in ISO-639-1 format.
       */
      language: v4.z.string().optional(),
      /**
       * An optional text to guide the model's style or continue a previous audio segment.
       */
      prompt: v4.z.string().optional(),
      /**
       * The sampling temperature, between 0 and 1.
       * @default 0
       */
      temperature: v4.z.number().min(0).max(1).default(0).optional(),
      /**
       * The timestamp granularities to populate for this transcription.
       * @default ['segment']
       */
      timestampGranularities: v4.z.array(v4.z.enum(["word", "segment"])).default(["segment"]).optional()
    })
  )
);
var languageMap = {
  afrikaans: "af",
  arabic: "ar",
  armenian: "hy",
  azerbaijani: "az",
  belarusian: "be",
  bosnian: "bs",
  bulgarian: "bg",
  catalan: "ca",
  chinese: "zh",
  croatian: "hr",
  czech: "cs",
  danish: "da",
  dutch: "nl",
  english: "en",
  estonian: "et",
  finnish: "fi",
  french: "fr",
  galician: "gl",
  german: "de",
  greek: "el",
  hebrew: "he",
  hindi: "hi",
  hungarian: "hu",
  icelandic: "is",
  indonesian: "id",
  italian: "it",
  japanese: "ja",
  kannada: "kn",
  kazakh: "kk",
  korean: "ko",
  latvian: "lv",
  lithuanian: "lt",
  macedonian: "mk",
  malay: "ms",
  marathi: "mr",
  maori: "mi",
  nepali: "ne",
  norwegian: "no",
  persian: "fa",
  polish: "pl",
  portuguese: "pt",
  romanian: "ro",
  russian: "ru",
  serbian: "sr",
  slovak: "sk",
  slovenian: "sl",
  spanish: "es",
  swahili: "sw",
  swedish: "sv",
  tagalog: "tl",
  tamil: "ta",
  thai: "th",
  turkish: "tr",
  ukrainian: "uk",
  urdu: "ur",
  vietnamese: "vi",
  welsh: "cy"
};
var OpenAITranscriptionModel = class {
  constructor(modelId, config) {
    this.modelId = modelId;
    this.config = config;
    this.specificationVersion = "v2";
  }
  get provider() {
    return this.config.provider;
  }
  async getArgs({
    audio,
    mediaType,
    providerOptions
  }) {
    const warnings = [];
    const openAIOptions = await chunkOCS2GTEN_cjs.parseProviderOptions({
      provider: "openai",
      providerOptions,
      schema: openAITranscriptionProviderOptions
    });
    const formData = new FormData();
    const blob = audio instanceof Uint8Array ? new Blob([audio]) : new Blob([chunkOCS2GTEN_cjs.convertBase64ToUint8Array(audio)]);
    formData.append("model", this.modelId);
    const fileExtension = chunkOCS2GTEN_cjs.mediaTypeToExtension(mediaType);
    formData.append(
      "file",
      new File([blob], "audio", { type: mediaType }),
      `audio.${fileExtension}`
    );
    if (openAIOptions) {
      const transcriptionModelOptions = {
        include: openAIOptions.include,
        language: openAIOptions.language,
        prompt: openAIOptions.prompt,
        // https://platform.openai.com/docs/api-reference/audio/createTranscription#audio_createtranscription-response_format
        // prefer verbose_json to get segments for models that support it
        response_format: [
          "gpt-4o-transcribe",
          "gpt-4o-mini-transcribe"
        ].includes(this.modelId) ? "json" : "verbose_json",
        temperature: openAIOptions.temperature,
        timestamp_granularities: openAIOptions.timestampGranularities
      };
      for (const [key, value] of Object.entries(transcriptionModelOptions)) {
        if (value != null) {
          if (Array.isArray(value)) {
            for (const item of value) {
              formData.append(`${key}[]`, String(item));
            }
          } else {
            formData.append(key, String(value));
          }
        }
      }
    }
    return {
      formData,
      warnings
    };
  }
  async doGenerate(options) {
    var _a, _b, _c, _d, _e, _f, _g, _h;
    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 } = await this.getArgs(options);
    const {
      value: response,
      responseHeaders,
      rawValue: rawResponse
    } = await chunkOCS2GTEN_cjs.postFormDataToApi({
      url: this.config.url({
        path: "/audio/transcriptions",
        modelId: this.modelId
      }),
      headers: chunkOCS2GTEN_cjs.combineHeaders(this.config.headers(), options.headers),
      formData,
      failedResponseHandler: openaiFailedResponseHandler,
      successfulResponseHandler: chunkOCS2GTEN_cjs.createJsonResponseHandler(
        openaiTranscriptionResponseSchema
      ),
      abortSignal: options.abortSignal,
      fetch: this.config.fetch
    });
    const language = response.language != null && response.language in languageMap ? languageMap[response.language] : void 0;
    return {
      text: response.text,
      segments: (_g = (_f = (_d = response.segments) == null ? void 0 : _d.map((segment) => ({
        text: segment.text,
        startSecond: segment.start,
        endSecond: segment.end
      }))) != null ? _f : (_e = response.words) == null ? void 0 : _e.map((word) => ({
        text: word.word,
        startSecond: word.start,
        endSecond: word.end
      }))) != null ? _g : [],
      language,
      durationInSeconds: (_h = response.duration) != null ? _h : void 0,
      warnings,
      response: {
        timestamp: currentDate,
        modelId: this.modelId,
        headers: responseHeaders,
        body: rawResponse
      }
    };
  }
};
var openaiSpeechProviderOptionsSchema = chunkOCS2GTEN_cjs.lazyValidator(
  () => chunkOCS2GTEN_cjs.zodSchema(
    v4.z.object({
      instructions: v4.z.string().nullish(),
      speed: v4.z.number().min(0.25).max(4).default(1).nullish()
    })
  )
);
var OpenAISpeechModel = class {
  constructor(modelId, config) {
    this.modelId = modelId;
    this.config = config;
    this.specificationVersion = "v2";
  }
  get provider() {
    return this.config.provider;
  }
  async getArgs({
    text,
    voice = "alloy",
    outputFormat = "mp3",
    speed,
    instructions,
    language,
    providerOptions
  }) {
    const warnings = [];
    const openAIOptions = await chunkOCS2GTEN_cjs.parseProviderOptions({
      provider: "openai",
      providerOptions,
      schema: openaiSpeechProviderOptionsSchema
    });
    const requestBody = {
      model: this.modelId,
      input: text,
      voice,
      response_format: "mp3",
      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: ${outputFormat}. Using mp3 instead.`
        });
      }
    }
    if (openAIOptions) {
      const speechModelOptions = {};
      for (const key in speechModelOptions) {
        const value = speechModelOptions[key];
        if (value !== void 0) {
          requestBody[key] = value;
        }
      }
    }
    if (language) {
      warnings.push({
        type: "unsupported-setting",
        setting: "language",
        details: `OpenAI speech models do not support language selection. Language parameter "${language}" was ignored.`
      });
    }
    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 } = await this.getArgs(options);
    const {
      value: audio,
      responseHeaders,
      rawValue: rawResponse
    } = await chunkOCS2GTEN_cjs.postJsonToApi({
      url: this.config.url({
        path: "/audio/speech",
        modelId: this.modelId
      }),
      headers: chunkOCS2GTEN_cjs.combineHeaders(this.config.headers(), options.headers),
      body: requestBody,
      failedResponseHandler: openaiFailedResponseHandler,
      successfulResponseHandler: chunkOCS2GTEN_cjs.createBinaryResponseHandler(),
      abortSignal: options.abortSignal,
      fetch: this.config.fetch
    });
    return {
      audio,
      warnings,
      request: {
        body: JSON.stringify(requestBody)
      },
      response: {
        timestamp: currentDate,
        modelId: this.modelId,
        headers: responseHeaders,
        body: rawResponse
      }
    };
  }
};
var localShellInputSchema = chunkOCS2GTEN_cjs.lazySchema(
  () => chunkOCS2GTEN_cjs.zodSchema(
    v4.z.object({
      action: v4.z.object({
        type: v4.z.literal("exec"),
        command: v4.z.array(v4.z.string()),
        timeoutMs: v4.z.number().optional(),
        user: v4.z.string().optional(),
        workingDirectory: v4.z.string().optional(),
        env: v4.z.record(v4.z.string(), v4.z.string()).optional()
      })
    })
  )
);
var localShellOutputSchema = chunkOCS2GTEN_cjs.lazySchema(
  () => chunkOCS2GTEN_cjs.zodSchema(v4.z.object({ output: v4.z.string() }))
);
chunkOCS2GTEN_cjs.createProviderDefinedToolFactoryWithOutputSchema({
  id: "openai.local_shell",
  name: "local_shell",
  inputSchema: localShellInputSchema,
  outputSchema: localShellOutputSchema
});
function isFileId(data, prefixes) {
  if (!prefixes) return false;
  return prefixes.some((prefix) => data.startsWith(prefix));
}
async function convertToOpenAIResponsesInput({
  prompt,
  systemMessageMode,
  fileIdPrefixes,
  store,
  hasLocalShellTool = false
}) {
  var _a, _b, _c, _d, _e, _f;
  let input = [];
  const warnings = [];
  for (const { role, content } of prompt) {
    switch (role) {
      case "system": {
        switch (systemMessageMode) {
          case "system": {
            input.push({ role: "system", content });
            break;
          }
          case "developer": {
            input.push({ role: "developer", content });
            break;
          }
          case "remove": {
            warnings.push({
              type: "other",
              message: "system messages are removed for this model"
            });
            break;
          }
          default: {
            const _exhaustiveCheck = systemMessageMode;
            throw new Error(
              `Unsupported system message mode: ${_exhaustiveCheck}`
            );
          }
        }
        break;
      }
      case "user": {
        input.push({
          role: "user",
          content: content.map((part, index) => {
            var _a2, _b2, _c2;
            switch (part.type) {
              case "text": {
                return { type: "input_text", text: part.text };
              }
              case "file": {
                if (part.mediaType.startsWith("image/")) {
                  const mediaType = part.mediaType === "image/*" ? "image/jpeg" : part.mediaType;
                  return {
                    type: "input_image",
                    ...part.data instanceof URL ? { image_url: part.data.toString() } : typeof part.data === "string" && isFileId(part.data, fileIdPrefixes) ? { file_id: part.data } : {
                      image_url: `data:${mediaType};base64,${chunkOCS2GTEN_cjs.convertToBase64(part.data)}`
                    },
                    detail: (_b2 = (_a2 = part.providerOptions) == null ? void 0 : _a2.openai) == null ? void 0 : _b2.imageDetail
                  };
                } else if (part.mediaType === "application/pdf") {
                  if (part.data instanceof URL) {
                    return {
                      type: "input_file",
                      file_url: part.data.toString()
                    };
                  }
                  return {
                    type: "input_file",
                    ...typeof part.data === "string" && isFileId(part.data, fileIdPrefixes) ? { file_id: part.data } : {
                      filename: (_c2 = part.filename) != null ? _c2 : `part-${index}.pdf`,
                      file_data: `data:application/pdf;base64,${chunkOCS2GTEN_cjs.convertToBase64(part.data)}`
                    }
                  };
                } else {
                  throw new chunkOCS2GTEN_cjs.UnsupportedFunctionalityError({
                    functionality: `file part media type ${part.mediaType}`
                  });
                }
              }
            }
          })
        });
        break;
      }
      case "assistant": {
        const reasoningMessages = {};
        for (const part of content) {
          switch (part.type) {
            case "text": {
              const id = (_b = (_a = part.providerOptions) == null ? void 0 : _a.openai) == null ? void 0 : _b.itemId;
              const phase = (_d = (_c = part.providerOptions) == null ? void 0 : _c.openai) == null ? void 0 : _d.phase;
              if (store && id != null) {
                input.push({ type: "item_reference", id });
                break;
              }
              input.push({
                role: "assistant",
                content: [{ type: "output_text", text: part.text }],
                id,
                ...phase != null && { phase }
              });
              break;
            }
            case "tool-call": {
              if (part.providerExecuted) {
                break;
              }
              const id = (_f = (_e = part.providerOptions) == null ? void 0 : _e.openai) == null ? void 0 : _f.itemId;
              if (store && id != null) {
                input.push({ type: "item_reference", id });
                break;
              }
              if (hasLocalShellTool && part.toolName === "local_shell") {
                const parsedInput = await chunkOCS2GTEN_cjs.validateTypes({
                  value: part.input,
                  schema: localShellInputSchema
                });
                input.push({
                  type: "local_shell_call",
                  call_id: part.toolCallId,
                  id,
                  action: {
                    type: "exec",
                    command: parsedInput.action.command,
                    timeout_ms: parsedInput.action.timeoutMs,
                    user: parsedInput.action.user,
                    working_directory: parsedInput.action.workingDirectory,
                    env: parsedInput.action.env
                  }
                });
                break;
              }
              input.push({
                type: "function_call",
                call_id: part.toolCallId,
                name: part.toolName,
                arguments: JSON.stringify(part.input),
                id
              });
              break;
            }
            // assistant tool result parts are from provider-executed tools:
            case "tool-result": {
              if (store) {
                input.push({ type: "item_reference", id: part.toolCallId });
              } else {
                warnings.push({
                  type: "other",
                  message: `Results for OpenAI tool ${part.toolName} are not sent to the API when store is false`
                });
              }
              break;
            }
            case "reasoning": {
              const providerOptions = await chunkOCS2GTEN_cjs.parseProviderOptions({
                provider: "openai",
                providerOptions: part.providerOptions,
                schema: openaiResponsesReasoningProviderOptionsSchema
              });
              const reasoningId = providerOptions == null ? void 0 : providerOptions.itemId;
              if (reasoningId != null) {
                const reasoningMessage = reasoningMessages[reasoningId];
                if (store) {
                  if (reasoningMessage === void 0) {
                    input.push({ type: "item_reference", id: reasoningId });
                    reasoningMessages[reasoningId] = {
                      type: "reasoning",
                      id: reasoningId,
                      summary: []
                    };
                  }
                } else {
                  const summaryParts = [];
                  if (part.text.length > 0) {
                    summaryParts.push({
                      type: "summary_text",
                      text: part.text
                    });
                  } else if (reasoningMessage !== void 0) {
                    warnings.push({
                      type: "other",
                      message: `Cannot append empty reasoning part to existing reasoning sequence. Skipping reasoning part: ${JSON.stringify(part)}.`
                    });
                  }
                  if (reasoningMessage === void 0) {
                    reasoningMessages[reasoningId] = {
                      type: "reasoning",
                      id: reasoningId,
                      encrypted_content: providerOptions == null ? void 0 : providerOptions.reasoningEncryptedContent,
                      summary: summaryParts
                    };
                    input.push(reasoningMessages[reasoningId]);
                  } else {
                    reasoningMessage.summary.push(...summaryParts);
                    if ((providerOptions == null ? void 0 : providerOptions.reasoningEncryptedContent) != null) {
                      reasoningMessage.encrypted_content = providerOptions.reasoningEncryptedContent;
                    }
                  }
                }
              } else {
                warnings.push({
                  type: "other",
                  message: `Non-OpenAI reasoning parts are not supported. Skipping reasoning part: ${JSON.stringify(part)}.`
                });
              }
              break;
            }
          }
        }
        break;
      }
      case "tool": {
        for (const part of content) {
          const output = part.output;
          if (hasLocalShellTool && part.toolName === "local_shell" && output.type === "json") {
            const parsedOutput = await chunkOCS2GTEN_cjs.validateTypes({
              value: output.value,
              schema: localShellOutputSchema
            });
            input.push({
              type: "local_shell_call_output",
              call_id: part.toolCallId,
              output: parsedOutput.output
            });
            break;
          }
          let contentValue;
          switch (output.type) {
            case "text":
            case "error-text":
              contentValue = output.value;
              break;
            case "json":
            case "error-json":
              contentValue = JSON.stringify(output.value);
              break;
            case "content":
              contentValue = output.value.map((item) => {
                switch (item.type) {
                  case "text": {
                    return { type: "input_text", text: item.text };
                  }
                  case "media": {
                    return item.mediaType.startsWith("image/") ? {
                      type: "input_image",
                      image_url: `data:${item.mediaType};base64,${item.data}`
                    } : {
                      type: "input_file",
                      filename: "data",
                      file_data: `data:${item.mediaType};base64,${item.data}`
                    };
                  }
                }
              });
              break;
          }
          input.push({
            type: "function_call_output",
            call_id: part.toolCallId,
            output: contentValue
          });
        }
        break;
      }
      default: {
        const _exhaustiveCheck = role;
        throw new Error(`Unsupported role: ${_exhaustiveCheck}`);
      }
    }
  }
  if (!store && input.some(
    (item) => "type" in item && item.type === "reasoning" && item.encrypted_content == null
  )) {
    warnings.push({
      type: "other",
      message: "Reasoning parts without encrypted content are not supported when store is false. Skipping reasoning parts."
    });
    input = input.filter(
      (item) => !("type" in item) || item.type !== "reasoning" || item.encrypted_content != null
    );
  }
  return { input, warnings };
}
var openaiResponsesReasoningProviderOptionsSchema = v4.z.object({
  itemId: v4.z.string().nullish(),
  reasoningEncryptedContent: v4.z.string().nullish()
});
function mapOpenAIResponseFinishReason({
  finishReason,
  hasFunctionCall
}) {
  switch (finishReason) {
    case void 0:
    case null:
      return hasFunctionCall ? "tool-calls" : "stop";
    case "max_output_tokens":
      return "length";
    case "content_filter":
      return "content-filter";
    default:
      return hasFunctionCall ? "tool-calls" : "unknown";
  }
}
var openaiResponsesChunkSchema = chunkOCS2GTEN_cjs.lazyValidator(
  () => chunkOCS2GTEN_cjs.zodSchema(
    v4.z.union([
      v4.z.object({
        type: v4.z.literal("response.output_text.delta"),
        item_id: v4.z.string(),
        delta: v4.z.string(),
        logprobs: v4.z.array(
          v4.z.object({
            token: v4.z.string(),
            logprob: v4.z.number(),
            top_logprobs: v4.z.array(
              v4.z.object({
                token: v4.z.string(),
                logprob: v4.z.number()
              })
            )
          })
        ).nullish()
      }),
      v4.z.object({
        type: v4.z.enum(["response.completed", "response.incomplete"]),
        response: v4.z.object({
          incomplete_details: v4.z.object({ reason: v4.z.string() }).nullish(),
          usage: v4.z.object({
            input_tokens: v4.z.number(),
            input_tokens_details: v4.z.object({ cached_tokens: v4.z.number().nullish() }).nullish(),
            output_tokens: v4.z.number(),
            output_tokens_details: v4.z.object({ reasoning_tokens: v4.z.number().nullish() }).nullish()
          }),
          service_tier: v4.z.string().nullish()
        })
      }),
      v4.z.object({
        type: v4.z.literal("response.created"),
        response: v4.z.object({
          id: v4.z.string(),
          created_at: v4.z.number(),
          model: v4.z.string(),
          service_tier: v4.z.string().nullish()
        })
      }),
      v4.z.object({
        type: v4.z.literal("response.output_item.added"),
        output_index: v4.z.number(),
        item: v4.z.discriminatedUnion("type", [
          v4.z.object({
            type: v4.z.literal("message"),
            id: v4.z.string(),
            phase: v4.z.enum(["commentary", "final_answer"]).nullish()
          }),
          v4.z.object({
            type: v4.z.literal("reasoning"),
            id: v4.z.string(),
            encrypted_content: v4.z.string().nullish()
          }),
          v4.z.object({
            type: v4.z.literal("function_call"),
            id: v4.z.string(),
            call_id: v4.z.string(),
            name: v4.z.string(),
            arguments: v4.z.string()
          }),
          v4.z.object({
            type: v4.z.literal("web_search_call"),
            id: v4.z.string(),
            status: v4.z.string()
          }),
          v4.z.object({
            type: v4.z.literal("computer_call"),
            id: v4.z.string(),
            status: v4.z.string()
          }),
          v4.z.object({
            type: v4.z.literal("file_search_call"),
            id: v4.z.string()
          }),
          v4.z.object({
            type: v4.z.literal("image_generation_call"),
            id: v4.z.string()
          }),
          v4.z.object({
            type: v4.z.literal("code_interpreter_call"),
            id: v4.z.string(),
            container_id: v4.z.string(),
            code: v4.z.string().nullable(),
            outputs: v4.z.array(
              v4.z.discriminatedUnion("type", [
                v4.z.object({ type: v4.z.literal("logs"), logs: v4.z.string() }),
                v4.z.object({ type: v4.z.literal("image"), url: v4.z.string() })
              ])
            ).nullable(),
            status: v4.z.string()
          })
        ])
      }),
      v4.z.object({
        type: v4.z.literal("response.output_item.done"),
        output_index: v4.z.number(),
        item: v4.z.discriminatedUnion("type", [
          v4.z.object({
            type: v4.z.literal("message"),
            id: v4.z.string(),
            phase: v4.z.enum(["commentary", "final_answer"]).nullish()
          }),
          v4.z.object({
            type: v4.z.literal("reasoning"),
            id: v4.z.string(),
            encrypted_content: v4.z.string().nullish()
          }),
          v4.z.object({
            type: v4.z.literal("function_call"),
            id: v4.z.string(),
            call_id: v4.z.string(),
            name: v4.z.string(),
            arguments: v4.z.string(),
            status: v4.z.literal("completed")
          }),
          v4.z.object({
            type: v4.z.literal("code_interpreter_call"),
            id: v4.z.string(),
            code: v4.z.string().nullable(),
            container_id: v4.z.string(),
            outputs: v4.z.array(
              v4.z.discriminatedUnion("type", [
                v4.z.object({ type: v4.z.literal("logs"), logs: v4.z.string() }),
                v4.z.object({ type: v4.z.literal("image"), url: v4.z.string() })
              ])
            ).nullable()
          }),
          v4.z.object({
            type: v4.z.literal("image_generation_call"),
            id: v4.z.string(),
            result: v4.z.string()
          }),
          v4.z.object({
            type: v4.z.literal("web_search_call"),
            id: v4.z.string(),
            status: v4.z.string(),
            action: v4.z.discriminatedUnion("type", [
              v4.z.object({
                type: v4.z.literal("search"),
                query: v4.z.string().nullish(),
                sources: v4.z.array(
                  v4.z.discriminatedUnion("type", [
                    v4.z.object({ type: v4.z.literal("url"), url: v4.z.string() }),
                    v4.z.object({ type: v4.z.literal("api"), name: v4.z.string() })
                  ])
                ).nullish()
              }),
              v4.z.object({
                type: v4.z.literal("open_page"),
                url: v4.z.string().nullish()
              }),
              v4.z.object({
                type: v4.z.literal("find_in_page"),
                url: v4.z.string().nullish(),
                pattern: v4.z.string().nullish()
              })
            ]).nullish()
          }),
          v4.z.object({
            type: v4.z.literal("file_search_call"),
            id: v4.z.string(),
            queries: v4.z.array(v4.z.string()),
            results: v4.z.array(
              v4.z.object({
                attributes: v4.z.record(v4.z.string(), v4.z.unknown()),
                file_id: v4.z.string(),
                filename: v4.z.string(),
                score: v4.z.number(),
                text: v4.z.string()
              })
            ).nullish()
          }),
          v4.z.object({
            type: v4.z.literal("local_shell_call"),
            id: v4.z.string(),
            call_id: v4.z.string(),
            action: v4.z.object({
              type: v4.z.literal("exec"),
              command: v4.z.array(v4.z.string()),
              timeout_ms: v4.z.number().optional(),
              user: v4.z.string().optional(),
              working_directory: v4.z.string().optional(),
              env: v4.z.record(v4.z.string(), v4.z.string()).optional()
            })
          }),
          v4.z.object({
            type: v4.z.literal("computer_call"),
            id: v4.z.string(),
            status: v4.z.literal("completed")
          })
        ])
      }),
      v4.z.object({
        type: v4.z.literal("response.function_call_arguments.delta"),
        item_id: v4.z.string(),
        output_index: v4.z.number(),
        delta: v4.z.string()
      }),
      v4.z.object({
        type: v4.z.literal("response.image_generation_call.partial_image"),
        item_id: v4.z.string(),
        output_index: v4.z.number(),
        partial_image_b64: v4.z.string()
      }),
      v4.z.object({
        type: v4.z.literal("response.code_interpreter_call_code.delta"),
        item_id: v4.z.string(),
        output_index: v4.z.number(),
        delta: v4.z.string()
      }),
      v4.z.object({
        type: v4.z.literal("response.code_interpreter_call_code.done"),
        item_id: v4.z.string(),
        output_index: v4.z.number(),
        code: v4.z.string()
      }),
      v4.z.object({
        type: v4.z.literal("response.output_text.annotation.added"),
        annotation: v4.z.discriminatedUnion("type", [
          v4.z.object({
            type: v4.z.literal("url_citation"),
            start_index: v4.z.number(),
            end_index: v4.z.number(),
            url: v4.z.string(),
            title: v4.z.string()
          }),
          v4.z.object({
            type: v4.z.literal("file_citation"),
            file_id: v4.z.string(),
            filename: v4.z.string().nullish(),
            index: v4.z.number().nullish(),
            start_index: v4.z.number().nullish(),
            end_index: v4.z.number().nullish(),
            quote: v4.z.string().nullish()
          })
        ])
      }),
      v4.z.object({
        type: v4.z.literal("response.reasoning_summary_part.added"),
        item_id: v4.z.string(),
        summary_index: v4.z.number()
      }),
      v4.z.object({
        type: v4.z.literal("response.reasoning_summary_text.delta"),
        item_id: v4.z.string(),
        summary_index: v4.z.number(),
        delta: v4.z.string()
      }),
      v4.z.object({
        type: v4.z.literal("response.reasoning_summary_part.done"),
        item_id: v4.z.string(),
        summary_index: v4.z.number()
      }),
      v4.z.object({
        type: v4.z.literal("error"),
        sequence_number: v4.z.number(),
        error: v4.z.object({
          type: v4.z.string(),
          code: v4.z.string(),
          message: v4.z.string(),
          param: v4.z.string().nullish()
        })
      }),
      v4.z.object({ type: v4.z.string() }).loose().transform((value) => ({
        type: "unknown_chunk",
        message: value.type
      }))
      // fallback for unknown chunks
    ])
  )
);
var openaiResponsesResponseSchema = chunkOCS2GTEN_cjs.lazyValidator(
  () => chunkOCS2GTEN_cjs.zodSchema(
    v4.z.object({
      id: v4.z.string().optional(),
      created_at: v4.z.number().optional(),
      error: v4.z.object({
        message: v4.z.string(),
        type: v4.z.string(),
        param: v4.z.string().nullish(),
        code: v4.z.string()
      }).nullish(),
      model: v4.z.string().optional(),
      output: v4.z.array(
        v4.z.discriminatedUnion("type", [
          v4.z.object({
            type: v4.z.literal("message"),
            role: v4.z.literal("assistant"),
            id: v4.z.string(),
            phase: v4.z.enum(["commentary", "final_answer"]).nullish(),
            content: v4.z.array(
              v4.z.object({
                type: v4.z.literal("output_text"),
                text: v4.z.string(),
                logprobs: v4.z.array(
                  v4.z.object({
                    token: v4.z.string(),
                    logprob: v4.z.number(),
                    top_logprobs: v4.z.array(
                      v4.z.object({
                        token: v4.z.string(),
                        logprob: v4.z.number()
                      })
                    )
                  })
                ).nullish(),
                annotations: v4.z.array(
                  v4.z.discriminatedUnion("type", [
                    v4.z.object({
                      type: v4.z.literal("url_citation"),
                      start_index: v4.z.number(),
                      end_index: v4.z.number(),
                      url: v4.z.string(),
                      title: v4.z.string()
                    }),
                    v4.z.object({
                      type: v4.z.literal("file_citation"),
                      file_id: v4.z.string(),
                      filename: v4.z.string().nullish(),
                      index: v4.z.number().nullish(),
                      start_index: v4.z.number().nullish(),
                      end_index: v4.z.number().nullish(),
                      quote: v4.z.string().nullish()
                    }),
                    v4.z.object({
                      type: v4.z.literal("container_file_citation"),
                      container_id: v4.z.string(),
                      file_id: v4.z.string(),
                      filename: v4.z.string().nullish(),
                      start_index: v4.z.number().nullish(),
                      end_index: v4.z.number().nullish(),
                      index: v4.z.number().nullish()
                    }),
                    v4.z.object({
                      type: v4.z.literal("file_path"),
                      file_id: v4.z.string(),
                      index: v4.z.number().nullish()
                    })
                  ])
                )
              })
            )
          }),
          v4.z.object({
            type: v4.z.literal("web_search_call"),
            id: v4.z.string(),
            status: v4.z.string(),
            action: v4.z.discriminatedUnion("type", [
              v4.z.object({
                type: v4.z.literal("search"),
                query: v4.z.string().nullish(),
                sources: v4.z.array(
                  v4.z.discriminatedUnion("type", [
                    v4.z.object({ type: v4.z.literal("url"), url: v4.z.string() }),
                    v4.z.object({
                      type: v4.z.literal("api"),
                      name: v4.z.string()
                    })
                  ])
                ).nullish()
              }),
              v4.z.object({
                type: v4.z.literal("open_page"),
                url: v4.z.string().nullish()
              }),
              v4.z.object({
                type: v4.z.literal("find_in_page"),
                url: v4.z.string().nullish(),
                pattern: v4.z.string().nullish()
              })
            ]).nullish()
          }),
          v4.z.object({
            type: v4.z.literal("file_search_call"),
            id: v4.z.string(),
            queries: v4.z.array(v4.z.string()),
            results: v4.z.array(
              v4.z.object({
                attributes: v4.z.record(
                  v4.z.string(),
                  v4.z.union([v4.z.string(), v4.z.number(), v4.z.boolean()])
                ),
                file_id: v4.z.string(),
                filename: v4.z.string(),
                score: v4.z.number(),
                text: v4.z.string()
              })
            ).nullish()
          }),
          v4.z.object({
            type: v4.z.literal("code_interpreter_call"),
            id: v4.z.string(),
            code: v4.z.string().nullable(),
            container_id: v4.z.string(),
            outputs: v4.z.array(
              v4.z.discriminatedUnion("type", [
                v4.z.object({ type: v4.z.literal("logs"), logs: v4.z.string() }),
                v4.z.object({ type: v4.z.literal("image"), url: v4.z.string() })
              ])
            ).nullable()
          }),
          v4.z.object({
            type: v4.z.literal("image_generation_call"),
            id: v4.z.string(),
            result: v4.z.string()
          }),
          v4.z.object({
            type: v4.z.literal("local_shell_call"),
            id: v4.z.string(),
            call_id: v4.z.string(),
            action: v4.z.object({
              type: v4.z.literal("exec"),
              command: v4.z.array(v4.z.string()),
              timeout_ms: v4.z.number().optional(),
              user: v4.z.string().optional(),
              working_directory: v4.z.string().optional(),
              env: v4.z.record(v4.z.string(), v4.z.string()).optional()
            })
          }),
          v4.z.object({
            type: v4.z.literal("function_call"),
            call_id: v4.z.string(),
            name: v4.z.string(),
            arguments: v4.z.string(),
            id: v4.z.string()
          }),
          v4.z.object({
            type: v4.z.literal("computer_call"),
            id: v4.z.string(),
            status: v4.z.string().optional()
          }),
          v4.z.object({
            type: v4.z.literal("reasoning"),
            id: v4.z.string(),
            encrypted_content: v4.z.string().nullish(),
            summary: v4.z.array(
              v4.z.object({
                type: v4.z.literal("summary_text"),
                text: v4.z.string()
              })
            )
          })
        ])
      ).optional(),
      service_tier: v4.z.string().nullish(),
      incomplete_details: v4.z.object({ reason: v4.z.string() }).nullish(),
      usage: v4.z.object({
        input_tokens: v4.z.number(),
        input_tokens_details: v4.z.object({ cached_tokens: v4.z.number().nullish() }).nullish(),
        output_tokens: v4.z.number(),
        output_tokens_details: v4.z.object({ reasoning_tokens: v4.z.number().nullish() }).nullish()
      }).optional()
    })
  )
);
var TOP_LOGPROBS_MAX = 20;
var openaiResponsesProviderOptionsSchema = chunkOCS2GTEN_cjs.lazyValidator(
  () => chunkOCS2GTEN_cjs.zodSchema(
    v4.z.object({
      conversation: v4.z.string().nullish(),
      include: v4.z.array(
        v4.z.enum([
          "reasoning.encrypted_content",
          // handled internally by default, only needed for unknown reasoning models
          "file_search_call.results",
          "message.output_text.logprobs"
        ])
      ).nullish(),
      instructions: v4.z.string().nullish(),
      /**
       * Return the log probabilities of the tokens.
       *
       * Setting to true will return the log probabilities of the tokens that
       * were generated.
       *
       * Setting to a number will return the log probabilities of the top n
       * tokens that were generated.
       *
       * @see https://platform.openai.com/docs/api-reference/responses/create
       * @see https://cookbook.openai.com/examples/using_logprobs
       */
      logprobs: v4.z.union([v4.z.boolean(), v4.z.number().min(1).max(TOP_LOGPROBS_MAX)]).optional(),
      /**
       * The maximum number of total calls to built-in tools that can be processed in a response.
       * This maximum number applies across all built-in tool calls, not per individual tool.
       * Any further attempts to call a tool by the model will be ignored.
       */
      maxToolCalls: v4.z.number().nullish(),
      metadata: v4.z.any().nullish(),
      parallelToolCalls: v4.z.boolean().nullish(),
      previousResponseId: v4.z.string().nullish(),
      promptCacheKey: v4.z.string().nullish(),
      /**
       * The retention policy for the prompt cache.
       * - 'in_memory': Default. Standard prompt caching behavior.
       * - '24h': Extended prompt caching that keeps cached prefixes active for up to 24 hours.
       *          Currently only available for 5.1 series models.
       *
       * @default 'in_memory'
       */
      promptCacheRetention: v4.z.enum(["in_memory", "24h"]).nullish(),
      /**
       * Reasoning effort for reasoning models. Defaults to `medium`. If you use
       * `providerOptions` to set the `reasoningEffort` option, this model setting will be ignored.
       * Valid values: 'none' | 'minimal' | 'low' | 'medium' | 'high' | 'xhigh'
       *
       * The 'none' type for `reasoningEffort` is only available for OpenAI's GPT-5.1
       * models. Also, the 'xhigh' type for `reasoningEffort` is only available for
       * OpenAI's GPT-5.1-Codex-Max model. Setting `reasoningEffort` to 'none' or 'xhigh' with unsupported models will result in
       * an error.
       */
      reasoningEffort: v4.z.string().nullish(),
      reasoningSummary: v4.z.string().nullish(),
      safetyIdentifier: v4.z.string().nullish(),
      serviceTier: v4.z.enum(["auto", "flex", "priority", "default"]).nullish(),
      store: v4.z.boolean().nullish(),
      strictJsonSchema: v4.z.boolean().nullish(),
      textVerbosity: v4.z.enum(["low", "medium", "high"]).nullish(),
      truncation: v4.z.enum(["auto", "disabled"]).nullish(),
      user: v4.z.string().nullish()
    })
  )
);
var codeInterpreterInputSchema = chunkOCS2GTEN_cjs.lazySchema(
  () => chunkOCS2GTEN_cjs.zodSchema(
    v4.z.object({
      code: v4.z.string().nullish(),
      containerId: v4.z.string()
    })
  )
);
var codeInterpreterOutputSchema = chunkOCS2GTEN_cjs.lazySchema(
  () => chunkOCS2GTEN_cjs.zodSchema(
    v4.z.object({
      outputs: v4.z.array(
        v4.z.discriminatedUnion("type", [
          v4.z.object({ type: v4.z.literal("logs"), logs: v4.z.string() }),
          v4.z.object({ type: v4.z.literal("image"), url: v4.z.string() })
        ])
      ).nullish()
    })
  )
);
var codeInterpreterArgsSchema = chunkOCS2GTEN_cjs.lazySchema(
  () => chunkOCS2GTEN_cjs.zodSchema(
    v4.z.object({
      container: v4.z.union([
        v4.z.string(),
        v4.z.object({
          fileIds: v4.z.array(v4.z.string()).optional()
        })
      ]).optional()
    })
  )
);
var codeInterpreterToolFactory = chunkOCS2GTEN_cjs.createProviderDefinedToolFactoryWithOutputSchema({
  id: "openai.code_interpreter",
  name: "code_interpreter",
  inputSchema: codeInterpreterInputSchema,
  outputSchema: codeInterpreterOutputSchema
});
var codeInterpreter = (args = {}) => {
  return codeInterpreterToolFactory(args);
};
var comparisonFilterSchema = v4.z.object({
  key: v4.z.string(),
  type: v4.z.enum(["eq", "ne", "gt", "gte", "lt", "lte", "in", "nin"]),
  value: v4.z.union([v4.z.string(), v4.z.number(), v4.z.boolean(), v4.z.array(v4.z.string())])
});
var compoundFilterSchema = v4.z.object({
  type: v4.z.enum(["and", "or"]),
  filters: v4.z.array(
    v4.z.union([comparisonFilterSchema, v4.z.lazy(() => compoundFilterSchema)])
  )
});
var fileSearchArgsSchema = chunkOCS2GTEN_cjs.lazySchema(
  () => chunkOCS2GTEN_cjs.zodSchema(
    v4.z.object({
      vectorStoreIds: v4.z.array(v4.z.string()),
      maxNumResults: v4.z.number().optional(),
      ranking: v4.z.object({
        ranker: v4.z.string().optional(),
        scoreThreshold: v4.z.number().optional()
      }).optional(),
      filters: v4.z.union([comparisonFilterSchema, compoundFilterSchema]).optional()
    })
  )
);
var fileSearchOutputSchema = chunkOCS2GTEN_cjs.lazySchema(
  () => chunkOCS2GTEN_cjs.zodSchema(
    v4.z.object({
      queries: v4.z.array(v4.z.string()),
      results: v4.z.array(
        v4.z.object({
          attributes: v4.z.record(v4.z.string(), v4.z.unknown()),
          fileId: v4.z.string(),
          filename: v4.z.string(),
          score: v4.z.number(),
          text: v4.z.string()
        })
      ).nullable()
    })
  )
);
var fileSearch = chunkOCS2GTEN_cjs.createProviderDefinedToolFactoryWithOutputSchema({
  id: "openai.file_search",
  name: "file_search",
  inputSchema: v4.z.object({}),
  outputSchema: fileSearchOutputSchema
});
var webSearchArgsSchema = chunkOCS2GTEN_cjs.lazySchema(
  () => chunkOCS2GTEN_cjs.zodSchema(
    v4.z.object({
      externalWebAccess: v4.z.boolean().optional(),
      filters: v4.z.object({ allowedDomains: v4.z.array(v4.z.string()).optional() }).optional(),
      searchContextSize: v4.z.enum(["low", "medium", "high"]).optional(),
      userLocation: v4.z.object({
        type: v4.z.literal("approximate"),
        country: v4.z.string().optional(),
        city: v4.z.string().optional(),
        region: v4.z.string().optional(),
        timezone: v4.z.string().optional()
      }).optional()
    })
  )
);
var webSearchInputSchema = chunkOCS2GTEN_cjs.lazySchema(() => chunkOCS2GTEN_cjs.zodSchema(v4.z.object({})));
var webSearchOutputSchema = chunkOCS2GTEN_cjs.lazySchema(
  () => chunkOCS2GTEN_cjs.zodSchema(
    v4.z.object({
      action: v4.z.discriminatedUnion("type", [
        v4.z.object({
          type: v4.z.literal("search"),
          query: v4.z.string().optional()
        }),
        v4.z.object({
          type: v4.z.literal("openPage"),
          url: v4.z.string().nullish()
        }),
        v4.z.object({
          type: v4.z.literal("findInPage"),
          url: v4.z.string().nullish(),
          pattern: v4.z.string().nullish()
        })
      ]).optional(),
      sources: v4.z.array(
        v4.z.discriminatedUnion("type", [
          v4.z.object({ type: v4.z.literal("url"), url: v4.z.string() }),
          v4.z.object({ type: v4.z.literal("api"), name: v4.z.string() })
        ])
      ).optional()
    })
  )
);
chunkOCS2GTEN_cjs.createProviderDefinedToolFactoryWithOutputSchema({
  id: "openai.web_search",
  name: "web_search",
  inputSchema: webSearchInputSchema,
  outputSchema: webSearchOutputSchema
});
var webSearchPreviewArgsSchema = chunkOCS2GTEN_cjs.lazySchema(
  () => chunkOCS2GTEN_cjs.zodSchema(
    v4.z.object({
      searchContextSize: v4.z.enum(["low", "medium", "high"]).optional(),
      userLocation: v4.z.object({
        type: v4.z.literal("approximate"),
        country: v4.z.string().optional(),
        city: v4.z.string().optional(),
        region: v4.z.string().optional(),
        timezone: v4.z.string().optional()
      }).optional()
    })
  )
);
var webSearchPreviewInputSchema = chunkOCS2GTEN_cjs.lazySchema(
  () => chunkOCS2GTEN_cjs.zodSchema(v4.z.object({}))
);
var webSearchPreviewOutputSchema = chunkOCS2GTEN_cjs.lazySchema(
  () => chunkOCS2GTEN_cjs.zodSchema(
    v4.z.object({
      action: v4.z.discriminatedUnion("type", [
        v4.z.object({
          type: v4.z.literal("search"),
          query: v4.z.string().optional()
        }),
        v4.z.object({
          type: v4.z.literal("openPage"),
          url: v4.z.string().nullish()
        }),
        v4.z.object({
          type: v4.z.literal("findInPage"),
          url: v4.z.string().nullish(),
          pattern: v4.z.string().nullish()
        })
      ]).optional()
    })
  )
);
var webSearchPreview = chunkOCS2GTEN_cjs.createProviderDefinedToolFactoryWithOutputSchema({
  id: "openai.web_search_preview",
  name: "web_search_preview",
  inputSchema: webSearchPreviewInputSchema,
  outputSchema: webSearchPreviewOutputSchema
});
var imageGenerationArgsSchema = chunkOCS2GTEN_cjs.lazySchema(
  () => chunkOCS2GTEN_cjs.zodSchema(
    v4.z.object({
      background: v4.z.enum(["auto", "opaque", "transparent"]).optional(),
      inputFidelity: v4.z.enum(["low", "high"]).optional(),
      inputImageMask: v4.z.object({
        fileId: v4.z.string().optional(),
        imageUrl: v4.z.string().optional()
      }).optional(),
      model: v4.z.string().optional(),
      moderation: v4.z.enum(["auto"]).optional(),
      outputCompression: v4.z.number().int().min(0).max(100).optional(),
      outputFormat: v4.z.enum(["png", "jpeg", "webp"]).optional(),
      partialImages: v4.z.number().int().min(0).max(3).optional(),
      quality: v4.z.enum(["auto", "low", "medium", "high"]).optional(),
      size: v4.z.enum(["1024x1024", "1024x1536", "1536x1024", "auto"]).optional()
    }).strict()
  )
);
var imageGenerationInputSchema = chunkOCS2GTEN_cjs.lazySchema(() => chunkOCS2GTEN_cjs.zodSchema(v4.z.object({})));
var imageGenerationOutputSchema = chunkOCS2GTEN_cjs.lazySchema(
  () => chunkOCS2GTEN_cjs.zodSchema(v4.z.object({ result: v4.z.string() }))
);
var imageGenerationToolFactory = chunkOCS2GTEN_cjs.createProviderDefinedToolFactoryWithOutputSchema({
  id: "openai.image_generation",
  name: "image_generation",
  inputSchema: imageGenerationInputSchema,
  outputSchema: imageGenerationOutputSchema
});
var imageGeneration = (args = {}) => {
  return imageGenerationToolFactory(args);
};
async function prepareResponsesTools({
  tools,
  toolChoice,
  strictJsonSchema
}) {
  tools = (tools == null ? void 0 : tools.length) ? tools : void 0;
  const toolWarnings = [];
  if (tools == null) {
    return { tools: void 0, toolChoice: void 0, toolWarnings };
  }
  const openaiTools = [];
  for (const tool of tools) {
    switch (tool.type) {
      case "function":
        openaiTools.push({
          type: "function",
          name: tool.name,
          description: tool.description,
          parameters: tool.inputSchema,
          strict: strictJsonSchema
        });
        break;
      case "provider-defined": {
        switch (tool.id) {
          case "openai.file_search": {
            const args = await chunkOCS2GTEN_cjs.validateTypes({
              value: tool.args,
              schema: fileSearchArgsSchema
            });
            openaiTools.push({
              type: "file_search",
              vector_store_ids: args.vectorStoreIds,
              max_num_results: args.maxNumResults,
              ranking_options: args.ranking ? {
                ranker: args.ranking.ranker,
                score_threshold: args.ranking.scoreThreshold
              } : void 0,
              filters: args.filters
            });
            break;
          }
          case "openai.local_shell": {
            openaiTools.push({
              type: "local_shell"
            });
            break;
          }
          case "openai.web_search_preview": {
            const args = await chunkOCS2GTEN_cjs.validateTypes({
              value: tool.args,
              schema: webSearchPreviewArgsSchema
            });
            openaiTools.push({
              type: "web_search_preview",
              search_context_size: args.searchContextSize,
              user_location: args.userLocation
            });
            break;
          }
          case "openai.web_search": {
            const args = await chunkOCS2GTEN_cjs.validateTypes({
              value: tool.args,
              schema: webSearchArgsSchema
            });
            openaiTools.push({
              type: "web_search",
              filters: args.filters != null ? { allowed_domains: args.filters.allowedDomains } : void 0,
              external_web_access: args.externalWebAccess,
              search_context_size: args.searchContextSize,
              user_location: args.userLocation
            });
            break;
          }
          case "openai.code_interpreter": {
            const args = await chunkOCS2GTEN_cjs.validateTypes({
              value: tool.args,
              schema: codeInterpreterArgsSchema
            });
            openaiTools.push({
              type: "code_interpreter",
              container: args.container == null ? { type: "auto", file_ids: void 0 } : typeof args.container === "string" ? args.container : { type: "auto", file_ids: args.container.fileIds }
            });
            break;
          }
          case "openai.image_generation": {
            const args = await chunkOCS2GTEN_cjs.validateTypes({
              value: tool.args,
              schema: imageGenerationArgsSchema
            });
            openaiTools.push({
              type: "image_generation",
              background: args.background,
              input_fidelity: args.inputFidelity,
              input_image_mask: args.inputImageMask ? {
                file_id: args.inputImageMask.fileId,
                image_url: args.inputImageMask.imageUrl
              } : void 0,
              model: args.model,
              size: args.size,
              quality: args.quality,
              moderation: args.moderation,
              output_format: args.outputFormat,
              output_compression: args.outputCompression
            });
            break;
          }
        }
        break;
      }
      default:
        toolWarnings.push({ type: "unsupported-tool", tool });
        break;
    }
  }
  if (toolChoice == null) {
    return { tools: openaiTools, toolChoice: void 0, toolWarnings };
  }
  const type = toolChoice.type;
  switch (type) {
    case "auto":
    case "none":
    case "required":
      return { tools: openaiTools, toolChoice: type, toolWarnings };
    case "tool":
      return {
        tools: openaiTools,
        toolChoice: toolChoice.toolName === "code_interpreter" || toolChoice.toolName === "file_search" || toolChoice.toolName === "image_generation" || toolChoice.toolName === "web_search_preview" || toolChoice.toolName === "web_search" ? { type: toolChoice.toolName } : { type: "function", name: toolChoice.toolName },
        toolWarnings
      };
    default: {
      const _exhaustiveCheck = type;
      throw new chunkOCS2GTEN_cjs.UnsupportedFunctionalityError({
        functionality: `tool choice type: ${_exhaustiveCheck}`
      });
    }
  }
}
var OpenAIResponsesLanguageModel = class {
  constructor(modelId, config) {
    this.specificationVersion = "v2";
    this.supportedUrls = {
      "image/*": [/^https?:\/\/.*$/],
      "application/pdf": [/^https?:\/\/.*$/]
    };
    this.modelId = modelId;
    this.config = config;
  }
  get provider() {
    return this.config.provider;
  }
  async getArgs({
    maxOutputTokens,
    temperature,
    stopSequences,
    topP,
    topK,
    presencePenalty,
    frequencyPenalty,
    seed,
    prompt,
    providerOptions,
    tools,
    toolChoice,
    responseFormat
  }) {
    var _a, _b, _c, _d;
    const warnings = [];
    const modelCapabilities = getOpenAILanguageModelCapabilities(this.modelId);
    if (topK != null) {
      warnings.push({ type: "unsupported-setting", setting: "topK" });
    }
    if (seed != null) {
      warnings.push({ type: "unsupported-setting", setting: "seed" });
    }
    if (presencePenalty != null) {
      warnings.push({
        type: "unsupported-setting",
        setting: "presencePenalty"
      });
    }
    if (frequencyPenalty != null) {
      warnings.push({
        type: "unsupported-setting",
        setting: "frequencyPenalty"
      });
    }
    if (stopSequences != null) {
      warnings.push({ type: "unsupported-setting", setting: "stopSequences" });
    }
    const openaiOptions = await chunkOCS2GTEN_cjs.parseProviderOptions({
      provider: "openai",
      providerOptions,
      schema: openaiResponsesProviderOptionsSchema
    });
    if ((openaiOptions == null ? void 0 : openaiOptions.conversation) && (openaiOptions == null ? void 0 : openaiOptions.previousResponseId)) {
      warnings.push({
        type: "unsupported-setting",
        setting: "conversation",
        details: "conversation and previousResponseId cannot be used together"
      });
    }
    const { input, warnings: inputWarnings } = await convertToOpenAIResponsesInput({
      prompt,
      systemMessageMode: modelCapabilities.systemMessageMode,
      fileIdPrefixes: this.config.fileIdPrefixes,
      store: (_a = openaiOptions == null ? void 0 : openaiOptions.store) != null ? _a : true,
      hasLocalShellTool: hasOpenAITool("openai.local_shell")
    });
    warnings.push(...inputWarnings);
    const strictJsonSchema = (_b = openaiOptions == null ? void 0 : openaiOptions.strictJsonSchema) != null ? _b : false;
    let include = openaiOptions == null ? void 0 : openaiOptions.include;
    function addInclude(key) {
      if (include == null) {
        include = [key];
      } else if (!include.includes(key)) {
        include = [...include, key];
      }
    }
    function hasOpenAITool(id) {
      return (tools == null ? void 0 : tools.find(
        (tool) => tool.type === "provider-defined" && tool.id === id
      )) != null;
    }
    const topLogprobs = typeof (openaiOptions == null ? void 0 : openaiOptions.logprobs) === "number" ? openaiOptions == null ? void 0 : openaiOptions.logprobs : (openaiOptions == null ? void 0 : openaiOptions.logprobs) === true ? TOP_LOGPROBS_MAX : void 0;
    if (topLogprobs) {
      addInclude("message.output_text.logprobs");
    }
    const webSearchToolName = (_c = tools == null ? void 0 : tools.find(
      (tool) => tool.type === "provider-defined" && (tool.id === "openai.web_search" || tool.id === "openai.web_search_preview")
    )) == null ? void 0 : _c.name;
    if (webSearchToolName) {
      addInclude("web_search_call.action.sources");
    }
    if (hasOpenAITool("openai.code_interpreter")) {
      addInclude("code_interpreter_call.outputs");
    }
    const store = openaiOptions == null ? void 0 : openaiOptions.store;
    if (store === false && modelCapabilities.isReasoningModel) {
      addInclude("reasoning.encrypted_content");
    }
    const baseArgs = {
      model: this.modelId,
      input,
      temperature,
      top_p: topP,
      max_output_tokens: maxOutputTokens,
      ...((responseFormat == null ? void 0 : responseFormat.type) === "json" || (openaiOptions == null ? void 0 : openaiOptions.textVerbosity)) && {
        text: {
          ...(responseFormat == null ? void 0 : responseFormat.type) === "json" && {
            format: responseFormat.schema != null ? {
              type: "json_schema",
              strict: strictJsonSchema,
              name: (_d = responseFormat.name) != null ? _d : "response",
              description: responseFormat.description,
              schema: responseFormat.schema
            } : { type: "json_object" }
          },
          ...(openaiOptions == null ? void 0 : openaiOptions.textVerbosity) && {
            verbosity: openaiOptions.textVerbosity
          }
        }
      },
      // provider options:
      conversation: openaiOptions == null ? void 0 : openaiOptions.conversation,
      max_tool_calls: openaiOptions == null ? void 0 : openaiOptions.maxToolCalls,
      metadata: openaiOptions == null ? void 0 : openaiOptions.metadata,
      parallel_tool_calls: openaiOptions == null ? void 0 : openaiOptions.parallelToolCalls,
      previous_response_id: openaiOptions == null ? void 0 : openaiOptions.previousResponseId,
      store,
      user: openaiOptions == null ? void 0 : openaiOptions.user,
      instructions: openaiOptions == null ? void 0 : openaiOptions.instructions,
      service_tier: openaiOptions == null ? void 0 : openaiOptions.serviceTier,
      include,
      prompt_cache_key: openaiOptions == null ? void 0 : openaiOptions.promptCacheKey,
      prompt_cache_retention: openaiOptions == null ? void 0 : openaiOptions.promptCacheRetention,
      safety_identifier: openaiOptions == null ? void 0 : openaiOptions.safetyIdentifier,
      top_logprobs: topLogprobs,
      truncation: openaiOptions == null ? void 0 : openaiOptions.truncation,
      // model-specific settings:
      ...modelCapabilities.isReasoningModel && ((openaiOptions == null ? void 0 : openaiOptions.reasoningEffort) != null || (openaiOptions == null ? void 0 : openaiOptions.reasoningSummary) != null) && {
        reasoning: {
          ...(openaiOptions == null ? void 0 : openaiOptions.reasoningEffort) != null && {
            effort: openaiOptions.reasoningEffort
          },
          ...(openaiOptions == null ? void 0 : openaiOptions.reasoningSummary) != null && {
            summary: openaiOptions.reasoningSummary
          }
        }
      }
    };
    if (modelCapabilities.isReasoningModel) {
      if (!((openaiOptions == null ? void 0 : openaiOptions.reasoningEffort) === "none" && modelCapabilities.supportsNonReasoningParameters)) {
        if (baseArgs.temperature != null) {
          baseArgs.temperature = void 0;
          warnings.push({
            type: "unsupported-setting",
            setting: "temperature",
            details: "temperature is not supported for reasoning models"
          });
        }
        if (baseArgs.top_p != null) {
          baseArgs.top_p = void 0;
          warnings.push({
            type: "unsupported-setting",
            setting: "topP",
            details: "topP is not supported for reasoning models"
          });
        }
      }
    } else {
      if ((openaiOptions == null ? void 0 : openaiOptions.reasoningEffort) != null) {
        warnings.push({
          type: "unsupported-setting",
          setting: "reasoningEffort",
          details: "reasoningEffort is not supported for non-reasoning models"
        });
      }
      if ((openaiOptions == null ? void 0 : openaiOptions.reasoningSummary) != null) {
        warnings.push({
          type: "unsupported-setting",
          setting: "reasoningSummary",
          details: "reasoningSummary is not supported for non-reasoning models"
        });
      }
    }
    if ((openaiOptions == null ? void 0 : openaiOptions.serviceTier) === "flex" && !modelCapabilities.supportsFlexProcessing) {
      warnings.push({
        type: "unsupported-setting",
        setting: "serviceTier",
        details: "flex processing is only available for o3, o4-mini, and gpt-5 models"
      });
      delete baseArgs.service_tier;
    }
    if ((openaiOptions == null ? void 0 : openaiOptions.serviceTier) === "priority" && !modelCapabilities.supportsPriorityProcessing) {
      warnings.push({
        type: "unsupported-setting",
        setting: "serviceTier",
        details: "priority processing is only available for supported models (gpt-4, gpt-5, gpt-5-mini, o3, o4-mini) and requires Enterprise access. gpt-5-nano is not supported"
      });
      delete baseArgs.service_tier;
    }
    const {
      tools: openaiTools,
      toolChoice: openaiToolChoice,
      toolWarnings
    } = await prepareResponsesTools({
      tools,
      toolChoice,
      strictJsonSchema
    });
    return {
      webSearchToolName,
      args: {
        ...baseArgs,
        tools: openaiTools,
        tool_choice: openaiToolChoice
      },
      warnings: [...warnings, ...toolWarnings],
      store
    };
  }
  async doGenerate(options) {
    var _a, _b, _c, _d, _e, _f, _g, _h, _i, _j, _k, _l, _m, _n, _o, _p, _q, _r, _s, _t, _u, _v, _w, _x, _y, _z, _A, _B;
    const {
      args: body,
      warnings,
      webSearchToolName
    } = await this.getArgs(options);
    const url = this.config.url({
      path: "/responses",
      modelId: this.modelId
    });
    const providerKey = this.config.provider.replace(".responses", "");
    const {
      responseHeaders,
      value: response,
      rawValue: rawResponse
    } = await chunkOCS2GTEN_cjs.postJsonToApi({
      url,
      headers: chunkOCS2GTEN_cjs.combineHeaders(this.config.headers(), options.headers),
      body,
      failedResponseHandler: openaiFailedResponseHandler,
      successfulResponseHandler: chunkOCS2GTEN_cjs.createJsonResponseHandler(
        openaiResponsesResponseSchema
      ),
      abortSignal: options.abortSignal,
      fetch: this.config.fetch
    });
    if (response.error) {
      throw new chunkOCS2GTEN_cjs.APICallError({
        message: response.error.message,
        url,
        requestBodyValues: body,
        statusCode: 400,
        responseHeaders,
        responseBody: rawResponse,
        isRetryable: false
      });
    }
    const content = [];
    const logprobs = [];
    let hasFunctionCall = false;
    for (const part of response.output) {
      switch (part.type) {
        case "reasoning": {
          if (part.summary.length === 0) {
            part.summary.push({ type: "summary_text", text: "" });
          }
          for (const summary of part.summary) {
            content.push({
              type: "reasoning",
              text: summary.text,
              providerMetadata: {
                [providerKey]: {
                  itemId: part.id,
                  reasoningEncryptedContent: (_a = part.encrypted_content) != null ? _a : null
                }
              }
            });
          }
          break;
        }
        case "image_generation_call": {
          content.push({
            type: "tool-call",
            toolCallId: part.id,
            toolName: "image_generation",
            input: "{}",
            providerExecuted: true
          });
          content.push({
            type: "tool-result",
            toolCallId: part.id,
            toolName: "image_generation",
            result: {
              result: part.result
            },
            providerExecuted: true
          });
          break;
        }
        case "local_shell_call": {
          content.push({
            type: "tool-call",
            toolCallId: part.call_id,
            toolName: "local_shell",
            input: JSON.stringify({
              action: part.action
            }),
            providerMetadata: {
              [providerKey]: {
                itemId: part.id
              }
            }
          });
          break;
        }
        case "message": {
          for (const contentPart of part.content) {
            if (((_c = (_b = options.providerOptions) == null ? void 0 : _b.openai) == null ? void 0 : _c.logprobs) && contentPart.logprobs) {
              logprobs.push(contentPart.logprobs);
            }
            content.push({
              type: "text",
              text: contentPart.text,
              providerMetadata: {
                [providerKey]: {
                  itemId: part.id,
                  ...part.phase != null && { phase: part.phase }
                }
              }
            });
            for (const annotation of contentPart.annotations) {
              if (annotation.type === "url_citation") {
                content.push({
                  type: "source",
                  sourceType: "url",
                  id: (_f = (_e = (_d = this.config).generateId) == null ? void 0 : _e.call(_d)) != null ? _f : chunkOCS2GTEN_cjs.generateId(),
                  url: annotation.url,
                  title: annotation.title
                });
              } else if (annotation.type === "file_citation") {
                content.push({
                  type: "source",
                  sourceType: "document",
                  id: (_i = (_h = (_g = this.config).generateId) == null ? void 0 : _h.call(_g)) != null ? _i : chunkOCS2GTEN_cjs.generateId(),
                  mediaType: "text/plain",
                  title: (_k = (_j = annotation.quote) != null ? _j : annotation.filename) != null ? _k : "Document",
                  filename: (_l = annotation.filename) != null ? _l : annotation.file_id,
                  ...annotation.file_id ? {
                    providerMetadata: {
                      [providerKey]: {
                        fileId: annotation.file_id
                      }
                    }
                  } : {}
                });
              } else if (annotation.type === "container_file_citation") {
                content.push({
                  type: "source",
                  sourceType: "document",
                  id: (_o = (_n = (_m = this.config).generateId) == null ? void 0 : _n.call(_m)) != null ? _o : chunkOCS2GTEN_cjs.generateId(),
                  mediaType: "text/plain",
                  title: (_q = (_p = annotation.filename) != null ? _p : annotation.file_id) != null ? _q : "Document",
                  filename: (_r = annotation.filename) != null ? _r : annotation.file_id,
                  providerMetadata: {
                    [providerKey]: {
                      fileId: annotation.file_id,
                      containerId: annotation.container_id,
                      ...annotation.index != null ? { index: annotation.index } : {}
                    }
                  }
                });
              } else if (annotation.type === "file_path") {
                content.push({
                  type: "source",
                  sourceType: "document",
                  id: (_u = (_t = (_s = this.config).generateId) == null ? void 0 : _t.call(_s)) != null ? _u : chunkOCS2GTEN_cjs.generateId(),
                  mediaType: "application/octet-stream",
                  title: annotation.file_id,
                  filename: annotation.file_id,
                  providerMetadata: {
                    [providerKey]: {
                      fileId: annotation.file_id,
                      ...annotation.index != null ? { index: annotation.index } : {}
                    }
                  }
                });
              }
            }
          }
          break;
        }
        case "function_call": {
          hasFunctionCall = true;
          content.push({
            type: "tool-call",
            toolCallId: part.call_id,
            toolName: part.name,
            input: part.arguments,
            providerMetadata: {
              [providerKey]: {
                itemId: part.id
              }
            }
          });
          break;
        }
        case "web_search_call": {
          content.push({
            type: "tool-call",
            toolCallId: part.id,
            toolName: webSearchToolName != null ? webSearchToolName : "web_search",
            input: JSON.stringify({}),
            providerExecuted: true
          });
          content.push({
            type: "tool-result",
            toolCallId: part.id,
            toolName: webSearchToolName != null ? webSearchToolName : "web_search",
            result: mapWebSearchOutput(part.action),
            providerExecuted: true
          });
          break;
        }
        case "computer_call": {
          content.push({
            type: "tool-call",
            toolCallId: part.id,
            toolName: "computer_use",
            input: "",
            providerExecuted: true
          });
          content.push({
            type: "tool-result",
            toolCallId: part.id,
            toolName: "computer_use",
            result: {
              type: "computer_use_tool_result",
              status: part.status || "completed"
            },
            providerExecuted: true
          });
          break;
        }
        case "file_search_call": {
          content.push({
            type: "tool-call",
            toolCallId: part.id,
            toolName: "file_search",
            input: "{}",
            providerExecuted: true
          });
          content.push({
            type: "tool-result",
            toolCallId: part.id,
            toolName: "file_search",
            result: {
              queries: part.queries,
              results: (_w = (_v = part.results) == null ? void 0 : _v.map((result) => ({
                attributes: result.attributes,
                fileId: result.file_id,
                filename: result.filename,
                score: result.score,
                text: result.text
              }))) != null ? _w : null
            },
            providerExecuted: true
          });
          break;
        }
        case "code_interpreter_call": {
          content.push({
            type: "tool-call",
            toolCallId: part.id,
            toolName: "code_interpreter",
            input: JSON.stringify({
              code: part.code,
              containerId: part.container_id
            }),
            providerExecuted: true
          });
          content.push({
            type: "tool-result",
            toolCallId: part.id,
            toolName: "code_interpreter",
            result: {
              outputs: part.outputs
            },
            providerExecuted: true
          });
          break;
        }
      }
    }
    const providerMetadata = {
      [providerKey]: {
        ...response.id != null ? { responseId: response.id } : {}
      }
    };
    if (logprobs.length > 0) {
      providerMetadata[providerKey].logprobs = logprobs;
    }
    if (typeof response.service_tier === "string") {
      providerMetadata[providerKey].serviceTier = response.service_tier;
    }
    const usage = response.usage;
    return {
      content,
      finishReason: mapOpenAIResponseFinishReason({
        finishReason: (_x = response.incomplete_details) == null ? void 0 : _x.reason,
        hasFunctionCall
      }),
      usage: {
        inputTokens: usage.input_tokens,
        outputTokens: usage.output_tokens,
        totalTokens: usage.input_tokens + usage.output_tokens,
        reasoningTokens: (_z = (_y = usage.output_tokens_details) == null ? void 0 : _y.reasoning_tokens) != null ? _z : void 0,
        cachedInputTokens: (_B = (_A = usage.input_tokens_details) == null ? void 0 : _A.cached_tokens) != null ? _B : void 0
      },
      request: { body },
      response: {
        id: response.id,
        timestamp: new Date(response.created_at * 1e3),
        modelId: response.model,
        headers: responseHeaders,
        body: rawResponse
      },
      providerMetadata,
      warnings
    };
  }
  async doStream(options) {
    const {
      args: body,
      warnings,
      webSearchToolName,
      store
    } = await this.getArgs(options);
    const { responseHeaders, value: response } = await chunkOCS2GTEN_cjs.postJsonToApi({
      url: this.config.url({
        path: "/responses",
        modelId: this.modelId
      }),
      headers: chunkOCS2GTEN_cjs.combineHeaders(this.config.headers(), options.headers),
      body: {
        ...body,
        stream: true
      },
      failedResponseHandler: openaiFailedResponseHandler,
      successfulResponseHandler: chunkOCS2GTEN_cjs.createEventSourceResponseHandler(
        openaiResponsesChunkSchema
      ),
      abortSignal: options.abortSignal,
      fetch: this.config.fetch
    });
    const self = this;
    const providerKey = this.config.provider.replace(".responses", "");
    let finishReason = "unknown";
    const usage = {
      inputTokens: void 0,
      outputTokens: void 0,
      totalTokens: void 0
    };
    const logprobs = [];
    let responseId = null;
    const ongoingToolCalls = {};
    const ongoingAnnotations = [];
    let activeMessagePhase;
    let hasFunctionCall = false;
    const activeReasoning = {};
    let serviceTier;
    return {
      stream: response.pipeThrough(
        new TransformStream({
          start(controller) {
            controller.enqueue({ type: "stream-start", warnings });
          },
          transform(chunk, controller) {
            var _a, _b, _c, _d, _e, _f, _g, _h, _i, _j, _k, _l, _m, _n, _o, _p, _q, _r, _s, _t, _u, _v, _w, _x;
            if (options.includeRawChunks) {
              controller.enqueue({ type: "raw", rawValue: chunk.rawValue });
            }
            if (!chunk.success) {
              finishReason = "error";
              controller.enqueue({ type: "error", error: chunk.error });
              return;
            }
            const value = chunk.value;
            if (isResponseOutputItemAddedChunk(value)) {
              if (value.item.type === "function_call") {
                ongoingToolCalls[value.output_index] = {
                  toolName: value.item.name,
                  toolCallId: value.item.call_id
                };
                controller.enqueue({
                  type: "tool-input-start",
                  id: value.item.call_id,
                  toolName: value.item.name
                });
              } else if (value.item.type === "web_search_call") {
                ongoingToolCalls[value.output_index] = {
                  toolName: webSearchToolName != null ? webSearchToolName : "web_search",
                  toolCallId: value.item.id
                };
                controller.enqueue({
                  type: "tool-input-start",
                  id: value.item.id,
                  toolName: webSearchToolName != null ? webSearchToolName : "web_search",
                  providerExecuted: true
                });
                controller.enqueue({
                  type: "tool-input-end",
                  id: value.item.id
                });
                controller.enqueue({
                  type: "tool-call",
                  toolCallId: value.item.id,
                  toolName: webSearchToolName != null ? webSearchToolName : "web_search",
                  input: JSON.stringify({}),
                  providerExecuted: true
                });
              } else if (value.item.type === "computer_call") {
                ongoingToolCalls[value.output_index] = {
                  toolName: "computer_use",
                  toolCallId: value.item.id
                };
                controller.enqueue({
                  type: "tool-input-start",
                  id: value.item.id,
                  toolName: "computer_use",
                  providerExecuted: true
                });
              } else if (value.item.type === "code_interpreter_call") {
                ongoingToolCalls[value.output_index] = {
                  toolName: "code_interpreter",
                  toolCallId: value.item.id,
                  codeInterpreter: {
                    containerId: value.item.container_id
                  }
                };
                controller.enqueue({
                  type: "tool-input-start",
                  id: value.item.id,
                  toolName: "code_interpreter",
                  providerExecuted: true
                });
                controller.enqueue({
                  type: "tool-input-delta",
                  id: value.item.id,
                  delta: `{"containerId":"${value.item.container_id}","code":"`
                });
              } else if (value.item.type === "file_search_call") {
                controller.enqueue({
                  type: "tool-call",
                  toolCallId: value.item.id,
                  toolName: "file_search",
                  input: "{}",
                  providerExecuted: true
                });
              } else if (value.item.type === "image_generation_call") {
                controller.enqueue({
                  type: "tool-call",
                  toolCallId: value.item.id,
                  toolName: "image_generation",
                  input: "{}",
                  providerExecuted: true
                });
              } else if (value.item.type === "message") {
                ongoingAnnotations.splice(0, ongoingAnnotations.length);
                activeMessagePhase = (_a = value.item.phase) != null ? _a : void 0;
                controller.enqueue({
                  type: "text-start",
                  id: value.item.id,
                  providerMetadata: {
                    [providerKey]: {
                      itemId: value.item.id,
                      ...value.item.phase != null && {
                        phase: value.item.phase
                      }
                    }
                  }
                });
              } else if (isResponseOutputItemAddedChunk(value) && value.item.type === "reasoning") {
                activeReasoning[value.item.id] = {
                  encryptedContent: value.item.encrypted_content,
                  summaryParts: { 0: "active" }
                };
                controller.enqueue({
                  type: "reasoning-start",
                  id: `${value.item.id}:0`,
                  providerMetadata: {
                    [providerKey]: {
                      itemId: value.item.id,
                      reasoningEncryptedContent: (_b = value.item.encrypted_content) != null ? _b : null
                    }
                  }
                });
              }
            } else if (isResponseOutputItemDoneChunk(value)) {
              if (value.item.type === "message") {
                const phase = (_c = value.item.phase) != null ? _c : activeMessagePhase;
                activeMessagePhase = void 0;
                controller.enqueue({
                  type: "text-end",
                  id: value.item.id,
                  providerMetadata: {
                    [providerKey]: {
                      itemId: value.item.id,
                      ...phase != null && { phase },
                      ...ongoingAnnotations.length > 0 && {
                        annotations: ongoingAnnotations
                      }
                    }
                  }
                });
              } else if (value.item.type === "function_call") {
                ongoingToolCalls[value.output_index] = void 0;
                hasFunctionCall = true;
                controller.enqueue({
                  type: "tool-input-end",
                  id: value.item.call_id
                });
                controller.enqueue({
                  type: "tool-call",
                  toolCallId: value.item.call_id,
                  toolName: value.item.name,
                  input: value.item.arguments,
                  providerMetadata: {
                    [providerKey]: {
                      itemId: value.item.id
                    }
                  }
                });
              } else if (value.item.type === "web_search_call") {
                ongoingToolCalls[value.output_index] = void 0;
                controller.enqueue({
                  type: "tool-result",
                  toolCallId: value.item.id,
                  toolName: webSearchToolName != null ? webSearchToolName : "web_search",
                  result: mapWebSearchOutput(value.item.action),
                  providerExecuted: true
                });
              } else if (value.item.type === "computer_call") {
                ongoingToolCalls[value.output_index] = void 0;
                controller.enqueue({
                  type: "tool-input-end",
                  id: value.item.id
                });
                controller.enqueue({
                  type: "tool-call",
                  toolCallId: value.item.id,
                  toolName: "computer_use",
                  input: "",
                  providerExecuted: true
                });
                controller.enqueue({
                  type: "tool-result",
                  toolCallId: value.item.id,
                  toolName: "computer_use",
                  result: {
                    type: "computer_use_tool_result",
                    status: value.item.status || "completed"
                  },
                  providerExecuted: true
                });
              } else if (value.item.type === "file_search_call") {
                ongoingToolCalls[value.output_index] = void 0;
                controller.enqueue({
                  type: "tool-result",
                  toolCallId: value.item.id,
                  toolName: "file_search",
                  result: {
                    queries: value.item.queries,
                    results: (_e = (_d = value.item.results) == null ? void 0 : _d.map((result) => ({
                      attributes: result.attributes,
                      fileId: result.file_id,
                      filename: result.filename,
                      score: result.score,
                      text: result.text
                    }))) != null ? _e : null
                  },
                  providerExecuted: true
                });
              } else if (value.item.type === "code_interpreter_call") {
                ongoingToolCalls[value.output_index] = void 0;
                controller.enqueue({
                  type: "tool-result",
                  toolCallId: value.item.id,
                  toolName: "code_interpreter",
                  result: {
                    outputs: value.item.outputs
                  },
                  providerExecuted: true
                });
              } else if (value.item.type === "image_generation_call") {
                controller.enqueue({
                  type: "tool-result",
                  toolCallId: value.item.id,
                  toolName: "image_generation",
                  result: {
                    result: value.item.result
                  },
                  providerExecuted: true
                });
              } else if (value.item.type === "local_shell_call") {
                ongoingToolCalls[value.output_index] = void 0;
                controller.enqueue({
                  type: "tool-call",
                  toolCallId: value.item.call_id,
                  toolName: "local_shell",
                  input: JSON.stringify({
                    action: {
                      type: "exec",
                      command: value.item.action.command,
                      timeoutMs: value.item.action.timeout_ms,
                      user: value.item.action.user,
                      workingDirectory: value.item.action.working_directory,
                      env: value.item.action.env
                    }
                  }),
                  providerMetadata: {
                    [providerKey]: { itemId: value.item.id }
                  }
                });
              } else if (value.item.type === "reasoning") {
                const activeReasoningPart = activeReasoning[value.item.id];
                const summaryPartIndices = Object.entries(
                  activeReasoningPart.summaryParts
                ).filter(
                  ([_, status]) => status === "active" || status === "can-conclude"
                ).map(([summaryIndex]) => summaryIndex);
                for (const summaryIndex of summaryPartIndices) {
                  controller.enqueue({
                    type: "reasoning-end",
                    id: `${value.item.id}:${summaryIndex}`,
                    providerMetadata: {
                      [providerKey]: {
                        itemId: value.item.id,
                        reasoningEncryptedContent: (_f = value.item.encrypted_content) != null ? _f : null
                      }
                    }
                  });
                }
                delete activeReasoning[value.item.id];
              }
            } else if (isResponseFunctionCallArgumentsDeltaChunk(value)) {
              const toolCall = ongoingToolCalls[value.output_index];
              if (toolCall != null) {
                controller.enqueue({
                  type: "tool-input-delta",
                  id: toolCall.toolCallId,
                  delta: value.delta
                });
              }
            } else if (isResponseCodeInterpreterCallCodeDeltaChunk(value)) {
              const toolCall = ongoingToolCalls[value.output_index];
              if (toolCall != null) {
                controller.enqueue({
                  type: "tool-input-delta",
                  id: toolCall.toolCallId,
                  // The delta is code, which is embedding in a JSON string.
                  // To escape it, we use JSON.stringify and slice to remove the outer quotes.
                  delta: JSON.stringify(value.delta).slice(1, -1)
                });
              }
            } else if (isResponseCodeInterpreterCallCodeDoneChunk(value)) {
              const toolCall = ongoingToolCalls[value.output_index];
              if (toolCall != null) {
                controller.enqueue({
                  type: "tool-input-delta",
                  id: toolCall.toolCallId,
                  delta: '"}'
                });
                controller.enqueue({
                  type: "tool-input-end",
                  id: toolCall.toolCallId
                });
                controller.enqueue({
                  type: "tool-call",
                  toolCallId: toolCall.toolCallId,
                  toolName: "code_interpreter",
                  input: JSON.stringify({
                    code: value.code,
                    containerId: toolCall.codeInterpreter.containerId
                  }),
                  providerExecuted: true
                });
              }
            } else if (isResponseCreatedChunk(value)) {
              responseId = value.response.id;
              controller.enqueue({
                type: "response-metadata",
                id: value.response.id,
                timestamp: new Date(value.response.created_at * 1e3),
                modelId: value.response.model
              });
            } else if (isTextDeltaChunk(value)) {
              controller.enqueue({
                type: "text-delta",
                id: value.item_id,
                delta: value.delta
              });
              if (((_h = (_g = options.providerOptions) == null ? void 0 : _g.openai) == null ? void 0 : _h.logprobs) && value.logprobs) {
                logprobs.push(value.logprobs);
              }
            } else if (value.type === "response.reasoning_summary_part.added") {
              if (value.summary_index > 0) {
                const activeReasoningPart = activeReasoning[value.item_id];
                activeReasoningPart.summaryParts[value.summary_index] = "active";
                for (const summaryIndex of Object.keys(
                  activeReasoningPart.summaryParts
                )) {
                  if (activeReasoningPart.summaryParts[summaryIndex] === "can-conclude") {
                    controller.enqueue({
                      type: "reasoning-end",
                      id: `${value.item_id}:${summaryIndex}`,
                      providerMetadata: {
                        [providerKey]: { itemId: value.item_id }
                      }
                    });
                    activeReasoningPart.summaryParts[summaryIndex] = "concluded";
                  }
                }
                controller.enqueue({
                  type: "reasoning-start",
                  id: `${value.item_id}:${value.summary_index}`,
                  providerMetadata: {
                    [providerKey]: {
                      itemId: value.item_id,
                      reasoningEncryptedContent: (_j = (_i = activeReasoning[value.item_id]) == null ? void 0 : _i.encryptedContent) != null ? _j : null
                    }
                  }
                });
              }
            } else if (value.type === "response.reasoning_summary_text.delta") {
              controller.enqueue({
                type: "reasoning-delta",
                id: `${value.item_id}:${value.summary_index}`,
                delta: value.delta,
                providerMetadata: {
                  [providerKey]: {
                    itemId: value.item_id
                  }
                }
              });
            } else if (value.type === "response.reasoning_summary_part.done") {
              if (store) {
                controller.enqueue({
                  type: "reasoning-end",
                  id: `${value.item_id}:${value.summary_index}`,
                  providerMetadata: {
                    [providerKey]: { itemId: value.item_id }
                  }
                });
                activeReasoning[value.item_id].summaryParts[value.summary_index] = "concluded";
              } else {
                activeReasoning[value.item_id].summaryParts[value.summary_index] = "can-conclude";
              }
            } else if (isResponseFinishedChunk(value)) {
              finishReason = mapOpenAIResponseFinishReason({
                finishReason: (_k = value.response.incomplete_details) == null ? void 0 : _k.reason,
                hasFunctionCall
              });
              usage.inputTokens = value.response.usage.input_tokens;
              usage.outputTokens = value.response.usage.output_tokens;
              usage.totalTokens = value.response.usage.input_tokens + value.response.usage.output_tokens;
              usage.reasoningTokens = (_m = (_l = value.response.usage.output_tokens_details) == null ? void 0 : _l.reasoning_tokens) != null ? _m : void 0;
              usage.cachedInputTokens = (_o = (_n = value.response.usage.input_tokens_details) == null ? void 0 : _n.cached_tokens) != null ? _o : void 0;
              if (typeof value.response.service_tier === "string") {
                serviceTier = value.response.service_tier;
              }
            } else if (isResponseAnnotationAddedChunk(value)) {
              ongoingAnnotations.push(value.annotation);
              if (value.annotation.type === "url_citation") {
                controller.enqueue({
                  type: "source",
                  sourceType: "url",
                  id: (_r = (_q = (_p = self.config).generateId) == null ? void 0 : _q.call(_p)) != null ? _r : chunkOCS2GTEN_cjs.generateId(),
                  url: value.annotation.url,
                  title: value.annotation.title
                });
              } else if (value.annotation.type === "file_citation") {
                controller.enqueue({
                  type: "source",
                  sourceType: "document",
                  id: (_u = (_t = (_s = self.config).generateId) == null ? void 0 : _t.call(_s)) != null ? _u : chunkOCS2GTEN_cjs.generateId(),
                  mediaType: "text/plain",
                  title: (_w = (_v = value.annotation.quote) != null ? _v : value.annotation.filename) != null ? _w : "Document",
                  filename: (_x = value.annotation.filename) != null ? _x : value.annotation.file_id,
                  ...value.annotation.file_id ? {
                    providerMetadata: {
                      [providerKey]: {
                        fileId: value.annotation.file_id
                      }
                    }
                  } : {}
                });
              }
            } else if (isErrorChunk(value)) {
              controller.enqueue({ type: "error", error: value });
            }
          },
          flush(controller) {
            const providerMetadata = {
              [providerKey]: {
                responseId
              }
            };
            if (logprobs.length > 0) {
              providerMetadata[providerKey].logprobs = logprobs;
            }
            if (serviceTier !== void 0) {
              providerMetadata[providerKey].serviceTier = serviceTier;
            }
            controller.enqueue({
              type: "finish",
              finishReason,
              usage,
              providerMetadata
            });
          }
        })
      ),
      request: { body },
      response: { headers: responseHeaders }
    };
  }
};
function isTextDeltaChunk(chunk) {
  return chunk.type === "response.output_text.delta";
}
function isResponseOutputItemDoneChunk(chunk) {
  return chunk.type === "response.output_item.done";
}
function isResponseFinishedChunk(chunk) {
  return chunk.type === "response.completed" || chunk.type === "response.incomplete";
}
function isResponseCreatedChunk(chunk) {
  return chunk.type === "response.created";
}
function isResponseFunctionCallArgumentsDeltaChunk(chunk) {
  return chunk.type === "response.function_call_arguments.delta";
}
function isResponseCodeInterpreterCallCodeDeltaChunk(chunk) {
  return chunk.type === "response.code_interpreter_call_code.delta";
}
function isResponseCodeInterpreterCallCodeDoneChunk(chunk) {
  return chunk.type === "response.code_interpreter_call_code.done";
}
function isResponseOutputItemAddedChunk(chunk) {
  return chunk.type === "response.output_item.added";
}
function isResponseAnnotationAddedChunk(chunk) {
  return chunk.type === "response.output_text.annotation.added";
}
function isErrorChunk(chunk) {
  return chunk.type === "error";
}
function mapWebSearchOutput(action) {
  var _a;
  if (action == null) {
    return {};
  }
  switch (action.type) {
    case "search":
      return {
        action: { type: "search", query: (_a = action.query) != null ? _a : void 0 },
        // include sources when provided by the Responses API (behind include flag)
        ...action.sources != null && { sources: action.sources }
      };
    case "open_page":
      return { action: { type: "openPage", url: action.url } };
    case "find_in_page":
      return {
        action: {
          type: "findInPage",
          url: action.url,
          pattern: action.pattern
        }
      };
  }
}

// ../../../../../setup-pnpm/node_modules/.bin/store/v11/links/@ai-sdk/azure/2.0.108/b619578b5433f96e73335d3c59b38f31d90988cae8d0d17a40a0e35a5de905d1/node_modules/@ai-sdk/azure/dist/index.mjs
var azureOpenaiTools = {
  codeInterpreter,
  fileSearch,
  imageGeneration,
  webSearchPreview
};
var VERSION = "2.0.108" ;
function createAzure(options = {}) {
  var _a;
  const getHeaders = () => {
    const baseHeaders = {
      "api-key": chunkOCS2GTEN_cjs.loadApiKey({
        apiKey: options.apiKey,
        environmentVariableName: "AZURE_API_KEY",
        description: "Azure OpenAI"
      }),
      ...options.headers
    };
    return chunkOCS2GTEN_cjs.withUserAgentSuffix(baseHeaders, `ai-sdk/azure/${VERSION}`);
  };
  const getResourceName = () => chunkOCS2GTEN_cjs.loadSetting({
    settingValue: options.resourceName,
    settingName: "resourceName",
    environmentVariableName: "AZURE_RESOURCE_NAME",
    description: "Azure OpenAI resource name"
  });
  const apiVersion = (_a = options.apiVersion) != null ? _a : "v1";
  const url = ({ path: path2, modelId }) => {
    var _a2;
    const baseUrlPrefix = (_a2 = options.baseURL) != null ? _a2 : `https://${getResourceName()}.openai.azure.com/openai`;
    let fullUrl;
    if (options.useDeploymentBasedUrls) {
      fullUrl = new URL(`${baseUrlPrefix}/deployments/${modelId}${path2}`);
    } else {
      fullUrl = new URL(`${baseUrlPrefix}/v1${path2}`);
    }
    fullUrl.searchParams.set("api-version", apiVersion);
    return fullUrl.toString();
  };
  const createChatModel = (deploymentName) => new OpenAIChatLanguageModel(deploymentName, {
    provider: "azure.chat",
    url,
    headers: getHeaders,
    fetch: options.fetch
  });
  const createCompletionModel = (modelId) => new OpenAICompletionLanguageModel(modelId, {
    provider: "azure.completion",
    url,
    headers: getHeaders,
    fetch: options.fetch
  });
  const createEmbeddingModel = (modelId) => new OpenAIEmbeddingModel(modelId, {
    provider: "azure.embeddings",
    headers: getHeaders,
    url,
    fetch: options.fetch
  });
  const createResponsesModel = (modelId) => new OpenAIResponsesLanguageModel(modelId, {
    provider: "azure.responses",
    url,
    headers: getHeaders,
    fetch: options.fetch,
    fileIdPrefixes: ["assistant-"]
  });
  const createImageModel = (modelId) => new OpenAIImageModel(modelId, {
    provider: "azure.image",
    url,
    headers: getHeaders,
    fetch: options.fetch
  });
  const createTranscriptionModel = (modelId) => new OpenAITranscriptionModel(modelId, {
    provider: "azure.transcription",
    url,
    headers: getHeaders,
    fetch: options.fetch
  });
  const createSpeechModel = (modelId) => new OpenAISpeechModel(modelId, {
    provider: "azure.speech",
    url,
    headers: getHeaders,
    fetch: options.fetch
  });
  const provider = function(deploymentId) {
    if (new.target) {
      throw new Error(
        "The Azure OpenAI model function cannot be called with the new keyword."
      );
    }
    return createChatModel(deploymentId);
  };
  provider.languageModel = createChatModel;
  provider.chat = createChatModel;
  provider.completion = createCompletionModel;
  provider.embedding = createEmbeddingModel;
  provider.image = createImageModel;
  provider.imageModel = createImageModel;
  provider.textEmbedding = createEmbeddingModel;
  provider.textEmbeddingModel = createEmbeddingModel;
  provider.responses = createResponsesModel;
  provider.transcription = createTranscriptionModel;
  provider.speech = createSpeechModel;
  provider.tools = azureOpenaiTools;
  return provider;
}
createAzure();
var TERMINAL_RESPONSE_EVENTS = /* @__PURE__ */ new Set(["response.completed", "response.failed", "response.incomplete", "error"]);
function createOpenAIWebSocketFetch(options) {
  const wsUrl = options?.url ?? "wss://api.openai.com/v1/responses";
  const betaHeader = options?.betaHeader === void 0 ? "responses_websockets=2026-02-06" : options.betaHeader;
  const apiKeyQueryParam = options?.apiKeyQueryParam ?? false;
  let ws = null;
  let connecting = null;
  let connectionKey = null;
  let nextQueryCredentialId = 0;
  const queryCredentialIds = /* @__PURE__ */ new Map();
  let busy = false;
  function getQueryCredentialCacheId(value) {
    if (!value) return "";
    const existing = queryCredentialIds.get(value);
    if (existing) return existing;
    const id = String(++nextQueryCredentialId);
    queryCredentialIds.set(value, id);
    return id;
  }
  function getConnection(authorization, headers, signal) {
    if (signal?.aborted) {
      return Promise.reject(getAbortError(signal));
    }
    const normalizedHeaders = { ...normalizeHeaders(options?.headers), ...headers };
    const apiKey = normalizedHeaders["api-key"];
    delete normalizedHeaders["authorization"];
    delete normalizedHeaders["openai-beta"];
    if (options?.apiKeyAsBearer || apiKeyQueryParam) {
      delete normalizedHeaders["api-key"];
    }
    const queryCredential = apiKeyQueryParam ? `${apiKeyQueryParam}:${getQueryCredentialCacheId(apiKey)}` : "";
    const nextConnectionKey = buildConnectionKey(authorization, normalizedHeaders, queryCredential);
    if (ws?.readyState === WebSocket__default.default.OPEN && connectionKey === nextConnectionKey) {
      return Promise.resolve(ws);
    }
    if (ws?.readyState === WebSocket__default.default.OPEN && connectionKey !== nextConnectionKey) {
      ws.close();
      ws = null;
      connectionKey = null;
    }
    if (connecting && connectionKey === nextConnectionKey) return connecting;
    connectionKey = nextConnectionKey;
    connecting = new Promise((resolve, reject) => {
      let settled = false;
      const socket = new WebSocket__default.default(getWebSocketUrl(wsUrl, apiKeyQueryParam, apiKey), {
        headers: {
          ...normalizedHeaders,
          ...authorization ? { Authorization: authorization } : {},
          ...betaHeader ? { "OpenAI-Beta": betaHeader } : {}
        }
      });
      function cleanupAbortListener() {
        signal?.removeEventListener("abort", onAbort);
      }
      function rejectConnection(err, closeSocket = true) {
        if (settled) return;
        settled = true;
        connecting = null;
        connectionKey = null;
        cleanupAbortListener();
        if (closeSocket) socket.close();
        reject(err);
      }
      function onAbort() {
        rejectConnection(getAbortError(signal));
      }
      signal?.addEventListener("abort", onAbort, { once: true });
      socket.on("open", () => {
        if (signal?.aborted) {
          rejectConnection(getAbortError(signal));
          return;
        }
        settled = true;
        ws = socket;
        connecting = null;
        cleanupAbortListener();
        resolve(socket);
      });
      socket.on("error", (err) => {
        rejectConnection(err, false);
      });
      socket.on("close", () => {
        if (settled) return;
        rejectConnection(new Error("WebSocket closed before the connection opened"), false);
      });
      socket.on("close", () => {
        if (ws === socket) ws = null;
        if (ws === null) connectionKey = null;
      });
    });
    return connecting;
  }
  async function websocketFetch(input, init) {
    const url = input instanceof URL ? input.toString() : typeof input === "string" ? input : input.url;
    if (init?.method !== "POST" || !isResponsesUrl(url)) {
      return globalThis.fetch(input, init);
    }
    let body;
    try {
      body = JSON.parse(typeof init.body === "string" ? init.body : "");
    } catch {
      return globalThis.fetch(input, init);
    }
    if (!body.stream) {
      return globalThis.fetch(input, init);
    }
    if (busy) {
      if (body.previous_response_id) {
        throw new Error(
          "Cannot start an overlapping WebSocket Responses continuation. Wait for the active stream to finish before sending previous_response_id."
        );
      }
      return globalThis.fetch(input, init);
    }
    const headers = normalizeHeaders(init.headers);
    const authorization = headers["authorization"] ?? (options?.apiKeyAsBearer && headers["api-key"] ? `Bearer ${headers["api-key"]}` : "");
    busy = true;
    let connection;
    try {
      connection = await getConnection(authorization, headers, init?.signal);
    } catch (err) {
      busy = false;
      throw err;
    }
    const { stream: _stream, background: _background, ...requestBody } = body;
    const encoder = new TextEncoder();
    let cleanupActiveStream;
    const responseStream = new ReadableStream({
      start(controller) {
        let cleanedUp = false;
        let abortHandler;
        function cleanup({ closeSocket = false } = {}) {
          if (cleanedUp) return;
          cleanedUp = true;
          connection.off("message", onMessage);
          connection.off("error", onError);
          connection.off("close", onClose);
          if (abortHandler) {
            init?.signal?.removeEventListener("abort", abortHandler);
            abortHandler = void 0;
          }
          if (closeSocket && ws === connection) {
            connection.close();
            ws = null;
            connectionKey = null;
          }
          busy = false;
          cleanupActiveStream = void 0;
        }
        cleanupActiveStream = cleanup;
        function onMessage(data) {
          const text = data.toString();
          controller.enqueue(encoder.encode(formatSSEData(text)));
          try {
            const event = JSON.parse(text);
            if (isTerminalWebSocketEvent(event)) {
              controller.enqueue(encoder.encode("data: [DONE]\n\n"));
              cleanup({ closeSocket: shouldReconnectAfterEvent(event) });
              controller.close();
            }
          } catch {
          }
        }
        function onError(err) {
          cleanup();
          controller.error(err);
        }
        function onClose() {
          cleanup();
          try {
            controller.close();
          } catch {
          }
        }
        connection.on("message", onMessage);
        connection.on("error", onError);
        connection.on("close", onClose);
        const signal = init?.signal;
        if (signal) {
          if (signal.aborted) {
            cleanup({ closeSocket: true });
            controller.error(signal.reason ?? new DOMException("Aborted", "AbortError"));
            return;
          }
          abortHandler = () => {
            cleanup({ closeSocket: true });
            try {
              controller.error(signal.reason ?? new DOMException("Aborted", "AbortError"));
            } catch {
            }
          };
          signal.addEventListener("abort", abortHandler, { once: true });
        }
        connection.send(JSON.stringify({ type: "response.create", ...requestBody }));
      },
      cancel() {
        cleanupActiveStream?.({ closeSocket: true });
      }
    });
    return new Response(responseStream, {
      status: 200,
      headers: { "content-type": "text/event-stream" }
    });
  }
  return Object.assign(websocketFetch, {
    /** Close the underlying WebSocket connection. */
    close() {
      if (ws) {
        ws.close();
        ws = null;
      }
      connectionKey = null;
      connecting = null;
    }
  });
}
function isResponsesUrl(url) {
  try {
    return new URL(url).pathname.endsWith("/responses");
  } catch {
    return url.split("?")[0]?.endsWith("/responses") ?? false;
  }
}
function getWebSocketUrl(url, apiKeyQueryParam, apiKey) {
  if (!apiKeyQueryParam || !apiKey) return url;
  const parsedUrl = new URL(url);
  parsedUrl.searchParams.set(apiKeyQueryParam, apiKey);
  return parsedUrl.toString();
}
function formatSSEData(text) {
  return `${text.split(/\r?\n/).map((line) => `data: ${line}`).join("\n")}

`;
}
function buildConnectionKey(authorization, headers, queryCredential = "") {
  return JSON.stringify({
    authorization,
    queryCredential,
    headers: Object.entries(headers).sort(([a], [b]) => a.localeCompare(b))
  });
}
function isTerminalWebSocketEvent(event) {
  return typeof event === "object" && event !== null && "type" in event && typeof event.type === "string" && TERMINAL_RESPONSE_EVENTS.has(event.type);
}
function shouldReconnectAfterEvent(event) {
  if (typeof event !== "object" || event === null || !("error" in event)) return false;
  const error = event.error;
  return typeof error === "object" && error !== null && "code" in error && error.code === "websocket_connection_limit_reached";
}
function getAbortError(signal) {
  return signal?.reason ?? new DOMException("Aborted", "AbortError");
}
function normalizeHeaders(headers) {
  const result = {};
  if (!headers) return result;
  if (headers instanceof Headers) {
    headers.forEach((value, key) => {
      result[key.toLowerCase()] = value;
    });
  } else if (Array.isArray(headers)) {
    for (const [key, value] of headers) {
      result[key.toLowerCase()] = value;
    }
  } else {
    for (const [key, value] of Object.entries(headers)) {
      if (value != null) result[key.toLowerCase()] = value;
    }
  }
  return result;
}

// src/llm/model/gateways/azure.ts
function isRecord(value) {
  return typeof value === "object" && value !== null && !Array.isArray(value);
}
function mirrorAzureProviderOptionsForOpenAI(providerOptions) {
  if (!isRecord(providerOptions) || !isRecord(providerOptions.azure)) {
    return providerOptions;
  }
  const openai = isRecord(providerOptions.openai) ? providerOptions.openai : {};
  return {
    ...providerOptions,
    openai: {
      ...openai,
      ...providerOptions.azure
    }
  };
}
function mirrorAzureResponseProviderOptions(prompt) {
  let promptModified = false;
  const mirroredPrompt = prompt.map((message) => {
    const messageWithProviderOptions = message;
    const providerOptions = mirrorAzureProviderOptionsForOpenAI(messageWithProviderOptions.providerOptions);
    const providerOptionsModified = providerOptions !== messageWithProviderOptions.providerOptions;
    if (!Array.isArray(message.content)) {
      if (providerOptionsModified) {
        promptModified = true;
        return { ...message, providerOptions };
      }
      return message;
    }
    let contentModified = false;
    const content = message.content.map((part) => {
      if (!("providerOptions" in part)) {
        return part;
      }
      const providerOptions2 = mirrorAzureProviderOptionsForOpenAI(part.providerOptions);
      if (providerOptions2 === part.providerOptions) {
        return part;
      }
      contentModified = true;
      return { ...part, providerOptions: providerOptions2 };
    });
    if (!contentModified) {
      if (providerOptionsModified) {
        promptModified = true;
        return { ...message, providerOptions };
      }
      return message;
    }
    promptModified = true;
    return { ...message, ...providerOptionsModified ? { providerOptions } : {}, content };
  });
  return promptModified ? mirroredPrompt : prompt;
}
function withAzureResponsesInputCompatibility(model) {
  return new Proxy(model, {
    get(target, property, receiver) {
      if (property === "doGenerate") {
        return (options) => target.doGenerate({
          ...options,
          providerOptions: mirrorAzureProviderOptionsForOpenAI(options.providerOptions),
          prompt: mirrorAzureResponseProviderOptions(options.prompt)
        });
      }
      if (property === "doStream") {
        return (options) => target.doStream({
          ...options,
          providerOptions: mirrorAzureProviderOptionsForOpenAI(options.providerOptions),
          prompt: mirrorAzureResponseProviderOptions(options.prompt)
        });
      }
      return Reflect.get(target, property, receiver);
    }
  });
}
var AzureOpenAIGateway = class extends chunkOCS2GTEN_cjs.MastraModelGateway {
  constructor(config) {
    super();
    this.config = config;
    this.validateConfig();
  }
  config;
  id = "azure-openai";
  name = "azure-openai";
  tokenCache = new chunk6QR4RQID_cjs.InMemoryServerCache();
  entraIdTokenRequests = /* @__PURE__ */ new Map();
  validateConfig() {
    if (!this.config.resourceName) {
      throw new chunkXSOONORA_cjs.MastraError({
        id: "AZURE_GATEWAY_INVALID_CONFIG",
        domain: "LLM",
        category: "UNKNOWN",
        text: "resourceName is required for Azure OpenAI gateway"
      });
    }
    if (!this.config.apiKey && this.config.authentication?.type !== "entraId") {
      throw new chunkXSOONORA_cjs.MastraError({
        id: "AZURE_GATEWAY_INVALID_CONFIG",
        domain: "LLM",
        category: "UNKNOWN",
        text: "apiKey or Entra ID authentication is required for Azure OpenAI gateway"
      });
    }
    if (this.config.authentication?.type === "entraId" && !this.config.authentication.credential) {
      throw new chunkXSOONORA_cjs.MastraError({
        id: "AZURE_GATEWAY_INVALID_CONFIG",
        domain: "LLM",
        category: "UNKNOWN",
        text: "credential is required for Azure OpenAI Entra ID authentication"
      });
    }
    if (this.config.apiKey && this.config.authentication?.type === "entraId") {
      console.warn(
        "[AzureOpenAIGateway] Both apiKey and Entra ID authentication provided. Using Entra ID authentication and ignoring apiKey."
      );
    }
    if (this.config.useResponsesAPI && this.config.useDeploymentBasedUrls === true) {
      throw new chunkXSOONORA_cjs.MastraError({
        id: "AZURE_GATEWAY_INVALID_CONFIG",
        domain: "LLM",
        category: "UNKNOWN",
        text: "useResponsesAPI: true cannot be combined with useDeploymentBasedUrls: true. Omit useDeploymentBasedUrls or set it to false."
      });
    }
    if (this.config.useResponsesAPI && this.config.apiVersion && !["v1", "preview"].includes(this.config.apiVersion)) {
      throw new chunkXSOONORA_cjs.MastraError({
        id: "AZURE_GATEWAY_INVALID_CONFIG",
        domain: "LLM",
        category: "UNKNOWN",
        text: 'useResponsesAPI: true requires apiVersion: "v1" or apiVersion: "preview". Omit apiVersion to use "v1".'
      });
    }
    if (this.config.useDeploymentBasedUrls === false && this.config.apiVersion && !["v1", "preview"].includes(this.config.apiVersion)) {
      throw new chunkXSOONORA_cjs.MastraError({
        id: "AZURE_GATEWAY_INVALID_CONFIG",
        domain: "LLM",
        category: "UNKNOWN",
        text: 'useDeploymentBasedUrls: false requires apiVersion: "v1" or apiVersion: "preview". Omit apiVersion to use "v1".'
      });
    }
    const hasDeployments = this.config.deployments && this.config.deployments.length > 0;
    const hasManagement = this.config.management !== void 0;
    if (hasDeployments && hasManagement) {
      console.warn(
        "[AzureOpenAIGateway] Both deployments and management credentials provided. Using static deployments list and ignoring management API."
      );
    }
    if (hasManagement) {
      this.getManagementCredentials(this.config.management);
    }
  }
  async fetchProviders() {
    if (this.config.deployments && this.config.deployments.length > 0) {
      return {
        "azure-openai": {
          apiKeyEnvVar: [],
          apiKeyHeader: "api-key",
          name: "Azure OpenAI",
          models: this.config.deployments,
          docUrl: "https://learn.microsoft.com/en-us/azure/ai-services/openai/",
          gateway: "azure-openai"
        }
      };
    }
    if (!this.config.management) {
      return {
        "azure-openai": {
          apiKeyEnvVar: [],
          apiKeyHeader: "api-key",
          name: "Azure OpenAI",
          models: [],
          docUrl: "https://learn.microsoft.com/en-us/azure/ai-services/openai/",
          gateway: "azure-openai"
        }
      };
    }
    try {
      const credentials = this.getManagementCredentials(this.config.management);
      const token = await this.getAzureADToken({
        tenantId: credentials.tenantId,
        clientId: credentials.clientId,
        clientSecret: credentials.clientSecret
      });
      const deployments = await this.fetchDeployments(token, {
        subscriptionId: credentials.subscriptionId,
        resourceGroup: credentials.resourceGroup,
        resourceName: this.config.resourceName
      });
      return {
        "azure-openai": {
          apiKeyEnvVar: [],
          apiKeyHeader: "api-key",
          name: "Azure OpenAI",
          models: deployments.map((d) => d.name),
          docUrl: "https://learn.microsoft.com/en-us/azure/ai-services/openai/",
          gateway: "azure-openai"
        }
      };
    } catch (error) {
      const errorMsg = error instanceof Error ? error.message : String(error);
      console.warn(
        `[AzureOpenAIGateway] Deployment discovery failed: ${errorMsg}`,
        "\nReturning fallback configuration. Azure OpenAI can still be used by manually specifying deployment names."
      );
      return {
        "azure-openai": {
          apiKeyEnvVar: [],
          apiKeyHeader: "api-key",
          name: "Azure OpenAI",
          models: [],
          docUrl: "https://learn.microsoft.com/en-us/azure/ai-services/openai/",
          gateway: "azure-openai"
        }
      };
    }
  }
  getManagementCredentials(management) {
    const { tenantId, clientId, clientSecret, subscriptionId, resourceGroup } = management;
    const missing = [];
    if (!tenantId) missing.push("tenantId");
    if (!clientId) missing.push("clientId");
    if (!clientSecret) missing.push("clientSecret");
    if (!subscriptionId) missing.push("subscriptionId");
    if (!resourceGroup) missing.push("resourceGroup");
    if (missing.length > 0) {
      throw new chunkXSOONORA_cjs.MastraError({
        id: "AZURE_MANAGEMENT_CREDENTIALS_MISSING",
        domain: "LLM",
        category: "UNKNOWN",
        text: `Management credentials incomplete. Missing: ${missing.join(", ")}. Required fields: tenantId, clientId, clientSecret, subscriptionId, resourceGroup.`
      });
    }
    return {
      tenantId,
      clientId,
      clientSecret,
      subscriptionId,
      resourceGroup
    };
  }
  async getAzureADToken(credentials) {
    const { tenantId, clientId, clientSecret } = credentials;
    const cacheKey = `azure-mgmt-token:${tenantId}:${clientId}`;
    const cached = await this.tokenCache.get(cacheKey);
    if (cached && cached.expiresAt > Date.now() / 1e3 + 60) {
      return cached.token;
    }
    const tokenEndpoint = `https://login.microsoftonline.com/${tenantId}/oauth2/v2.0/token`;
    const body = new URLSearchParams({
      grant_type: "client_credentials",
      client_id: clientId,
      client_secret: clientSecret,
      scope: "https://management.azure.com/.default"
    });
    const response = await fetch(tokenEndpoint, {
      method: "POST",
      headers: {
        "Content-Type": "application/x-www-form-urlencoded"
      },
      body: body.toString()
    });
    if (!response.ok) {
      const error = await response.text();
      throw new chunkXSOONORA_cjs.MastraError({
        id: "AZURE_AD_TOKEN_ERROR",
        domain: "LLM",
        category: "UNKNOWN",
        text: `Failed to get Azure AD token: ${response.status} ${error}`
      });
    }
    const tokenResponse = await response.json();
    const expiresAt = Math.floor(Date.now() / 1e3) + tokenResponse.expires_in;
    await this.tokenCache.set(cacheKey, {
      token: tokenResponse.access_token,
      expiresAt
    });
    return tokenResponse.access_token;
  }
  async fetchDeployments(token, credentials) {
    const { subscriptionId, resourceGroup, resourceName } = credentials;
    let url = `https://management.azure.com/subscriptions/${subscriptionId}/resourceGroups/${resourceGroup}/providers/Microsoft.CognitiveServices/accounts/${resourceName}/deployments?api-version=2024-10-01`;
    const allDeployments = [];
    while (url) {
      const response = await fetch(url, {
        headers: {
          Authorization: `Bearer ${token}`,
          "Content-Type": "application/json"
        }
      });
      if (!response.ok) {
        const error = await response.text();
        throw new chunkXSOONORA_cjs.MastraError({
          id: "AZURE_DEPLOYMENTS_FETCH_ERROR",
          domain: "LLM",
          category: "UNKNOWN",
          text: `Failed to fetch Azure deployments: ${response.status} ${error}`
        });
      }
      const data = await response.json();
      allDeployments.push(...data.value);
      url = data.nextLink;
    }
    const successfulDeployments = allDeployments.filter((d) => d.properties.provisioningState === "Succeeded");
    return successfulDeployments;
  }
  buildUrl(_routerId, _envVars) {
    return void 0;
  }
  async getApiKey(_modelId) {
    return this.config.authentication?.type === "entraId" ? "" : this.config.apiKey ?? "";
  }
  async getEntraIdToken() {
    if (this.config.authentication?.type !== "entraId") {
      throw new chunkXSOONORA_cjs.MastraError({
        id: "AZURE_ENTRA_ID_AUTH_NOT_CONFIGURED",
        domain: "LLM",
        category: "UNKNOWN",
        text: "Entra ID authentication is not configured for Azure OpenAI gateway"
      });
    }
    const scope = this.config.authentication.scope ?? "https://cognitiveservices.azure.com/.default";
    const cacheKey = `azure-openai-token:${scope}`;
    const cached = await this.tokenCache.get(cacheKey);
    if (cached && cached.expiresAt > Date.now() / 1e3 + 60) {
      return cached.token;
    }
    let tokenRequest = this.entraIdTokenRequests.get(cacheKey);
    if (!tokenRequest) {
      tokenRequest = this.fetchEntraIdToken(scope, cacheKey);
      this.entraIdTokenRequests.set(cacheKey, tokenRequest);
    }
    try {
      const token = await tokenRequest;
      return token.token;
    } finally {
      this.entraIdTokenRequests.delete(cacheKey);
    }
  }
  async fetchEntraIdToken(scope, cacheKey) {
    if (this.config.authentication?.type !== "entraId") {
      throw new chunkXSOONORA_cjs.MastraError({
        id: "AZURE_ENTRA_ID_AUTH_NOT_CONFIGURED",
        domain: "LLM",
        category: "UNKNOWN",
        text: "Entra ID authentication is not configured for Azure OpenAI gateway"
      });
    }
    const accessToken = await this.config.authentication.credential.getToken(scope);
    if (!accessToken?.token) {
      throw new chunkXSOONORA_cjs.MastraError({
        id: "AZURE_ENTRA_ID_TOKEN_ERROR",
        domain: "LLM",
        category: "UNKNOWN",
        text: "Failed to get Entra ID token for Azure OpenAI gateway"
      });
    }
    const token = {
      token: accessToken.token,
      expiresAt: accessToken.expiresOnTimestamp ? Math.floor(accessToken.expiresOnTimestamp / 1e3) : Math.floor(Date.now() / 1e3) + 300
    };
    await this.tokenCache.set(cacheKey, token);
    return token;
  }
  createEntraIdFetch(innerFetch = fetch) {
    return async (input, init) => {
      const token = await this.getEntraIdToken();
      const headers = new Headers(init?.headers);
      headers.delete("api-key");
      headers.set("Authorization", `Bearer ${token}`);
      return innerFetch(input, {
        ...init,
        headers
      });
    };
  }
  createAzureResponsesWebSocketFetch({
    useEntraId,
    responsesWebSocket
  }) {
    const websocketFetch = createOpenAIWebSocketFetch({
      url: responsesWebSocket?.url ?? `wss://${this.config.resourceName}.openai.azure.com/openai/v1/responses`,
      headers: responsesWebSocket?.headers,
      apiKeyQueryParam: useEntraId ? false : "api-key",
      betaHeader: false
    });
    return useEntraId ? Object.assign(this.createEntraIdFetch(websocketFetch), { close: websocketFetch.close }) : websocketFetch;
  }
  async resolveLanguageModel({
    modelId,
    apiKey,
    headers,
    transport,
    responsesWebSocket
  }) {
    const useResponsesAPI = this.config.useResponsesAPI ?? false;
    const apiVersion = this.config.apiVersion || (useResponsesAPI || this.config.useDeploymentBasedUrls === false ? "v1" : "2024-04-01-preview");
    const useDeploymentBasedUrls = this.config.useDeploymentBasedUrls ?? (useResponsesAPI ? false : true);
    const useEntraId = this.config.authentication?.type === "entraId";
    const useWebSocket = useResponsesAPI && transport === "websocket";
    const websocketFetch = useWebSocket ? this.createAzureResponsesWebSocketFetch({
      useEntraId,
      responsesWebSocket
    }) : void 0;
    const azureConfig = {
      resourceName: this.config.resourceName,
      apiKey: useEntraId ? "" : apiKey,
      apiVersion,
      // Mastra's Azure gateway has historically used deployment-based URLs.
      // Keep that default for compatibility; set false with apiVersion: 'v1'
      // to use the newer Azure OpenAI v1 route.
      useDeploymentBasedUrls,
      headers: { "User-Agent": chunkOCS2GTEN_cjs.MASTRA_USER_AGENT, ...headers },
      ...websocketFetch && !useEntraId ? { fetch: websocketFetch } : {}
    };
    const azureProvider = createAzure(
      useEntraId ? {
        ...azureConfig,
        fetch: websocketFetch ?? this.createEntraIdFetch()
      } : azureConfig
    );
    if (useResponsesAPI) {
      const model = withAzureResponsesInputCompatibility(azureProvider.responses(modelId));
      if (websocketFetch) {
        Object.defineProperty(model, chunkOCS2GTEN_cjs.MASTRA_GATEWAY_STREAM_TRANSPORT, {
          configurable: true,
          value: {
            type: "openai-websocket",
            close: websocketFetch.close
          }
        });
      }
      return model;
    }
    return azureProvider(modelId);
  }
};

// src/llm/model/gateways/mastra.ts
var MastraGateway = class extends chunkOCS2GTEN_cjs.MastraModelGateway {
  constructor(config) {
    super();
    this.config = config;
  }
  config;
  id = "mastra";
  name = "Memory Gateway";
  getBaseUrl() {
    const raw = this.config?.baseUrl ?? process.env["MASTRA_GATEWAY_URL"] ?? "https://gateway-api.mastra.ai";
    return raw.replace(/\/+$/, "").replace(/\/v1$/, "");
  }
  shouldEnable() {
    return !!(this.config?.apiKey ?? process.env["MASTRA_GATEWAY_API_KEY"]);
  }
  async fetchProviders() {
    if (!this.shouldEnable()) {
      return {};
    }
    const openrouterConfig = PROVIDER_REGISTRY["openrouter"];
    const models = openrouterConfig?.models ?? [];
    const providers = {
      mastra: {
        apiKeyEnvVar: "MASTRA_GATEWAY_API_KEY",
        apiKeyHeader: "Authorization",
        name: "Memory Gateway",
        gateway: "mastra",
        models: [...models],
        docUrl: "https://mastra.ai/docs/gateway"
      }
    };
    return providers;
  }
  async buildUrl(_modelId) {
    return `${this.getBaseUrl()}/v1`;
  }
  async getApiKey() {
    const apiKey = this.config?.apiKey ?? process.env["MASTRA_GATEWAY_API_KEY"];
    if (!apiKey) {
      throw new chunkXSOONORA_cjs.MastraError({
        id: "MASTRA_GATEWAY_NO_API_KEY",
        domain: "LLM",
        category: "UNKNOWN",
        text: "Missing MASTRA_GATEWAY_API_KEY environment variable"
      });
    }
    return apiKey;
  }
  resolveLanguageModel({
    modelId,
    providerId,
    apiKey,
    headers
  }) {
    const baseURL = `${this.getBaseUrl()}/v1`;
    const fullModelId = `${providerId}/${modelId}`;
    if (this.config?.customFetch && providerId === "anthropic") {
      return chunkOCS2GTEN_cjs.createAnthropic({
        apiKey: "oauth-gateway-placeholder",
        baseURL,
        headers: {
          "User-Agent": chunkOCS2GTEN_cjs.MASTRA_USER_AGENT,
          [chunkOCS2GTEN_cjs.GATEWAY_AUTH_HEADER]: `Bearer ${apiKey}`,
          ...headers
        },
        fetch: this.config.customFetch
      })(modelId);
    }
    if (this.config?.customFetch) {
      return chunkDBTKQ3U2_cjs.createOpenRouter({
        apiKey: "oauth-gateway-placeholder",
        baseURL,
        headers: {
          "User-Agent": chunkOCS2GTEN_cjs.MASTRA_USER_AGENT,
          [chunkOCS2GTEN_cjs.GATEWAY_AUTH_HEADER]: `Bearer ${apiKey}`,
          ...headers
        },
        fetch: this.config.customFetch
      }).chat(fullModelId);
    }
    return chunkDBTKQ3U2_cjs.createOpenRouter({
      apiKey,
      baseURL,
      headers: {
        "User-Agent": chunkOCS2GTEN_cjs.MASTRA_USER_AGENT,
        ...headers
      }
    }).chat(fullModelId);
  }
};

// src/llm/model/gateways/index.ts
function getGatewayId(gateway) {
  return gateway.getId?.() ?? gateway.id;
}
function shouldEnableGateway(gateway) {
  return gateway.shouldEnable?.() ?? true;
}
function findGatewayForModel(gatewayId, gateways) {
  const prefixedGateway = gateways.find((g) => {
    const id = getGatewayId(g);
    return id !== "models.dev" && (id === gatewayId || gatewayId.startsWith(`${id}/`));
  });
  if (prefixedGateway) {
    return prefixedGateway;
  }
  const modelsDevGateway = gateways.find((g) => getGatewayId(g) === "models.dev");
  if (modelsDevGateway) {
    return modelsDevGateway;
  }
  throw new chunkXSOONORA_cjs.MastraError({
    id: "MODEL_ROUTER_NO_GATEWAY_FOUND",
    category: "USER",
    domain: "MODEL_ROUTER",
    text: `No Mastra model router gateway found for model id ${gatewayId}`
  });
}

// src/llm/model/provider-registry.json
var provider_registry_default = {
  providers: {
    helicone: {
      url: "https://ai-gateway.helicone.ai/v1",
      apiKeyEnvVar: "HELICONE_API_KEY",
      apiKeyHeader: "Authorization",
      name: "Helicone",
      models: [
        "chatgpt-4o-latest",
        "claude-3-haiku-20240307",
        "claude-3.5-haiku",
        "claude-3.5-sonnet-v2",
        "claude-3.7-sonnet",
        "claude-4.5-haiku",
        "claude-4.5-opus",
        "claude-4.5-sonnet",
        "claude-haiku-4-5-20251001",
        "claude-opus-4",
        "claude-opus-4-1",
        "claude-opus-4-1-20250805",
        "claude-sonnet-4",
        "claude-sonnet-4-5-20250929",
        "deepseek-r1-distill-llama-70b",
        "deepseek-reasoner",
        "deepseek-tng-r1t2-chimera",
        "deepseek-v3",
        "deepseek-v3.1-terminus",
        "deepseek-v3.2",
        "ernie-4.5-21b-a3b-thinking",
        "gemini-2.5-flash",
        "gemini-2.5-flash-lite",
        "gemini-2.5-pro",
        "gemini-3-pro-preview",
        "gemma-3-12b-it",
        "gemma2-9b-it",
        "glm-4.6",
        "gpt-4.1",
        "gpt-4.1-mini",
        "gpt-4.1-mini-2025-04-14",
        "gpt-4.1-nano",
        "gpt-4o",
        "gpt-4o-mini",
        "gpt-5",
        "gpt-5-chat-latest",
        "gpt-5-codex",
        "gpt-5-mini",
        "gpt-5-nano",
        "gpt-5-pro",
        "gpt-5.1",
        "gpt-5.1-chat-latest",
        "gpt-5.1-codex",
        "gpt-5.1-codex-mini",
        "gpt-oss-120b",
        "gpt-oss-20b",
        "grok-3",
        "grok-3-mini",
        "grok-4",
        "grok-4-1-fast-non-reasoning",
        "grok-4-1-fast-reasoning",
        "grok-4-fast-non-reasoning",
        "grok-4-fast-reasoning",
        "grok-code-fast-1",
        "hermes-2-pro-llama-3-8b",
        "kimi-k2-0711",
        "kimi-k2-0905",
        "kimi-k2-thinking",
        "llama-3.1-8b-instant",
        "llama-3.1-8b-instruct",
        "llama-3.1-8b-instruct-turbo",
        "llama-3.3-70b-instruct",
        "llama-3.3-70b-versatile",
        "llama-4-maverick",
        "llama-4-scout",
        "llama-guard-4",
        "llama-prompt-guard-2-22m",
        "llama-prompt-guard-2-86m",
        "mistral-large-2411",
        "mistral-nemo",
        "mistral-small",
        "o1",
        "o1-mini",
        "o3",
        "o3-mini",
        "o3-pro",
        "o4-mini",
        "qwen2.5-coder-7b-fast",
        "qwen3-235b-a22b-thinking",
        "qwen3-30b-a3b",
        "qwen3-32b",
        "qwen3-coder",
        "qwen3-coder-30b-a3b-instruct",
        "qwen3-next-80b-a3b-instruct",
        "qwen3-vl-235b-a22b-instruct",
        "sonar",
        "sonar-deep-research",
        "sonar-pro",
        "sonar-reasoning",
        "sonar-reasoning-pro"
      ],
      docUrl: "https://helicone.ai/models",
      gateway: "models.dev"
    },
    auriko: {
      url: "https://api.auriko.ai/v1",
      apiKeyEnvVar: "AURIKO_API_KEY",
      apiKeyHeader: "Authorization",
      name: "Auriko",
      models: [
        "claude-opus-4-6",
        "claude-opus-4-7",
        "claude-sonnet-4-6",
        "deepseek-v4-flash",
        "deepseek-v4-pro",
        "gemini-2.5-flash",
        "gemini-2.5-pro",
        "gemini-3.1-pro-preview",
        "glm-5.1",
        "grok-4.3",
        "kimi-k2.5",
        "kimi-k2.6",
        "minimax-m2-7",
        "minimax-m2-7-highspeed",
        "qwen-3.6-plus"
      ],
      docUrl: "https://docs.auriko.ai",
      gateway: "models.dev"
    },
    firepass: {
      url: "https://api.fireworks.ai/inference/v1/",
      apiKeyEnvVar: "FIREPASS_API_KEY",
      apiKeyHeader: "Authorization",
      name: "Fireworks (Firepass)",
      models: ["accounts/fireworks/routers/kimi-k2p6-turbo"],
      docUrl: "https://docs.fireworks.ai/firepass",
      gateway: "models.dev"
    },
    "nano-gpt": {
      url: "https://nano-gpt.com/api/v1",
      apiKeyEnvVar: "NANO_GPT_API_KEY",
      apiKeyHeader: "Authorization",
      name: "NanoGPT",
      models: [
        "Alibaba-NLP/Tongyi-DeepResearch-30B-A3B",
        "Baichuan-M2",
        "Baichuan4-Air",
        "Baichuan4-Turbo",
        "CrucibleLab/L3.3-70B-Loki-V2.0",
        "Doctor-Shotgun/MS3.2-24B-Magnum-Diamond",
        "EVA-UNIT-01/EVA-LLaMA-3.33-70B-v0.0",
        "EVA-UNIT-01/EVA-LLaMA-3.33-70B-v0.1",
        "EVA-UNIT-01/EVA-Qwen2.5-32B-v0.2",
        "EVA-UNIT-01/EVA-Qwen2.5-72B-v0.2",
        "Envoid/Llama-3.05-NT-Storybreaker-Ministral-70B",
        "Envoid/Llama-3.05-Nemotron-Tenyxchat-Storybreaker-70B",
        "GLM-4.5-Air-Derestricted",
        "GLM-4.5-Air-Derestricted-Iceblink",
        "GLM-4.5-Air-Derestricted-Iceblink-ReExtract",
        "GLM-4.5-Air-Derestricted-Iceblink-v2",
        "GLM-4.5-Air-Derestricted-Iceblink-v2-ReExtract",
        "GLM-4.5-Air-Derestricted-Steam",
        "GLM-4.5-Air-Derestricted-Steam-ReExtract",
        "GLM-4.6-Derestricted-v5",
        "GalrionSoftworks/MN-LooseCannon-12B-v1",
        "Gemma-3-27B-ArliAI-RPMax-v3",
        "Gemma-3-27B-Big-Tiger-v3",
        "Gemma-3-27B-CardProjector-v4",
        "Gemma-3-27B-Glitter",
        "Gemma-3-27B-Nidum-Uncensored",
        "Gemma-3-27B-it",
        "Gemma-3-27B-it-Abliterated",
        "Gryphe/MythoMax-L2-13b",
        "Infermatic/MN-12B-Inferor-v0.0",
        "KAT-Coder-Air-V1",
        "KAT-Coder-Exp-72B-1010",
        "KAT-Coder-Pro-V1",
        "LLM360/K2-Think",
        "LatitudeGames/Wayfarer-Large-70B-Llama-3.3",
        "Llama-3.3+(3.1v3.3)-70B-Hanami-x1",
        "Llama-3.3+(3.1v3.3)-70B-New-Dawn-v1.1",
        "Llama-3.3+(3v3.3)-70B-TenyxChat-DaybreakStorywriter",
        "Llama-3.3-70B-Anthrobomination",
        "Llama-3.3-70B-Argunaut-1-SFT",
        "Llama-3.3-70B-ArliAI-RPMax-v1.4",
        "Llama-3.3-70B-ArliAI-RPMax-v2",
        "Llama-3.3-70B-ArliAI-RPMax-v3",
        "Llama-3.3-70B-Aurora-Borealis",
        "Llama-3.3-70B-Bigger-Body",
        "Llama-3.3-70B-Cirrus-x1",
        "Llama-3.3-70B-Cu-Mai-R1",
        "Llama-3.3-70B-Damascus-R1",
        "Llama-3.3-70B-Dark-Ages-v0.1",
        "Llama-3.3-70B-Electra-R1",
        "Llama-3.3-70B-Electranova-v1.0",
        "Llama-3.3-70B-Fallen-R1-v1",
        "Llama-3.3-70B-Fallen-v1",
        "Llama-3.3-70B-Forgotten-Abomination-v5.0",
        "Llama-3.3-70B-Forgotten-Safeword-3.6",
        "Llama-3.3-70B-GeneticLemonade-Opus",
        "Llama-3.3-70B-GeneticLemonade-Unleashed-v3",
        "Llama-3.3-70B-Ignition-v0.1",
        "Llama-3.3-70B-Incandescent-Malevolence",
        "Llama-3.3-70B-Legion-V2.1",
        "Llama-3.3-70B-MS-Nevoria",
        "Llama-3.3-70B-Magnum-v4-SE",
        "Llama-3.3-70B-Magnum-v4-SE-Cirrus-x1-SLERP",
        "Llama-3.3-70B-Mhnnn-x1",
        "Llama-3.3-70B-MiraiFanfare",
        "Llama-3.3-70B-Mokume-Gane-R1",
        "Llama-3.3-70B-Nova",
        "Llama-3.3-70B-Predatorial-Extasy",
        "Llama-3.3-70B-Progenitor-V3.3",
        "Llama-3.3-70B-RAWMAW",
        "Llama-3.3-70B-Sapphira-0.1",
        "Llama-3.3-70B-Sapphira-0.2",
        "Llama-3.3-70B-Shakudo",
        "Llama-3.3-70B-StrawberryLemonade-v1.0",
        "Llama-3.3-70B-Strawberrylemonade-v1.2",
        "Llama-3.3-70B-The-Omega-Directive-Unslop-v2.0",
        "Llama-3.3-70B-The-Omega-Directive-Unslop-v2.1",
        "Llama-3.3-70B-Vulpecula-R1",
        "Magistral-Small-2506",
        "MarinaraSpaghetti/NemoMix-Unleashed-12B",
        "Meta-Llama-3-1-8B-Instruct-FP8",
        "MiniMax-M1",
        "MiniMax-M2",
        "MiniMaxAI/MiniMax-M1-80k",
        "Mistral-Nemo-12B-Instruct-2407",
        "NeverSleep/Llama-3-Lumimaid-70B-v0.1",
        "NeverSleep/Lumimaid-v0.2-70B",
        "NousResearch 2/DeepHermes-3-Mistral-24B-Preview",
        "NousResearch 2/Hermes-4-70B:thinking",
        "NousResearch 2/hermes-3-llama-3.1-70b",
        "NousResearch 2/hermes-4-405b",
        "NousResearch 2/hermes-4-405b:thinking",
        "NousResearch 2/hermes-4-70b",
        "QwQ-32B-ArliAI-RpR-v1",
        "Qwen2.5-32B-EVA-v0.2",
        "ReadyArt/MS3.2-The-Omega-Directive-24B-Unslop-v2.0",
        "ReadyArt/The-Omega-Abomination-L-70B-v1.0",
        "Salesforce/Llama-xLAM-2-70b-fc-r",
        "Sao10K/L3-8B-Stheno-v3.2",
        "Sao10K/L3.1-70B-Euryale-v2.2",
        "Sao10K/L3.1-70B-Hanami-x1",
        "Sao10K/L3.3-70B-Euryale-v2.3",
        "Steelskull/L3.3-Cu-Mai-R1-70b",
        "Steelskull/L3.3-Electra-R1-70b",
        "Steelskull/L3.3-MS-Evalebis-70b",
        "Steelskull/L3.3-MS-Evayale-70B",
        "Steelskull/L3.3-MS-Nevoria-70b",
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        "gpt-5.2-codex"
      ],
      docUrl: "https://www.qhaigc.net/docs",
      gateway: "models.dev"
    },
    lilac: {
      url: "https://api.getlilac.com/v1",
      apiKeyEnvVar: "LILAC_API_KEY",
      apiKeyHeader: "Authorization",
      name: "Lilac",
      models: ["google/gemma-4-31b-it", "minimaxai/minimax-m2.7", "moonshotai/kimi-k2.6", "zai-org/glm-5.1"],
      docUrl: "https://docs.getlilac.com/inference/models",
      gateway: "models.dev"
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      apiKeyHeader: "Authorization",
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        "deepseek-r1-0528",
        "deepseek-r1-distill-llama-70b",
        "deepseek-r1-distill-llama-8b",
        "deepseek-r1-distill-qwen-1-5b",
        "deepseek-r1-distill-qwen-14b",
        "deepseek-r1-distill-qwen-32b",
        "deepseek-r1-distill-qwen-7b",
        "deepseek-v3",
        "deepseek-v3-1",
        "deepseek-v3-2-exp",
        "deepseek-v4-flash",
        "deepseek-v4-pro",
        "glm-5",
        "glm-5.1",
        "kimi-k2-thinking",
        "kimi-k2.5",
        "kimi-k2.6",
        "kimi/kimi-k2.5",
        "moonshot-kimi-k2-instruct",
        "qvq-max",
        "qwen-deep-research",
        "qwen-doc-turbo",
        "qwen-flash",
        "qwen-long",
        "qwen-math-plus",
        "qwen-math-turbo",
        "qwen-max",
        "qwen-mt-plus",
        "qwen-mt-turbo",
        "qwen-omni-turbo",
        "qwen-omni-turbo-realtime",
        "qwen-plus",
        "qwen-plus-character",
        "qwen-turbo",
        "qwen-vl-max",
        "qwen-vl-ocr",
        "qwen-vl-plus",
        "qwen2-5-14b-instruct",
        "qwen2-5-32b-instruct",
        "qwen2-5-72b-instruct",
        "qwen2-5-7b-instruct",
        "qwen2-5-coder-32b-instruct",
        "qwen2-5-coder-7b-instruct",
        "qwen2-5-math-72b-instruct",
        "qwen2-5-math-7b-instruct",
        "qwen2-5-omni-7b",
        "qwen2-5-vl-72b-instruct",
        "qwen2-5-vl-7b-instruct",
        "qwen3-14b",
        "qwen3-235b-a22b",
        "qwen3-32b",
        "qwen3-8b",
        "qwen3-asr-flash",
        "qwen3-coder-30b-a3b-instruct",
        "qwen3-coder-480b-a35b-instruct",
        "qwen3-coder-flash",
        "qwen3-coder-plus",
        "qwen3-max",
        "qwen3-next-80b-a3b-instruct",
        "qwen3-next-80b-a3b-thinking",
        "qwen3-omni-flash",
        "qwen3-omni-flash-realtime",
        "qwen3-vl-235b-a22b",
        "qwen3-vl-30b-a3b",
        "qwen3-vl-plus",
        "qwen3.5-397b-a17b",
        "qwen3.5-flash",
        "qwen3.5-plus",
        "qwen3.6-max-preview",
        "qwen3.6-plus",
        "qwq-32b",
        "qwq-plus",
        "siliconflow/deepseek-r1-0528",
        "siliconflow/deepseek-v3-0324",
        "siliconflow/deepseek-v3.1-terminus",
        "siliconflow/deepseek-v3.2",
        "tongyi-intent-detect-v3"
      ],
      docUrl: "https://www.alibabacloud.com/help/en/model-studio/models",
      gateway: "models.dev"
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      apiKeyHeader: "Authorization",
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      models: ["public/deepseek-r1", "public/deepseek-v3", "public/minimax-m25"],
      docUrl: "https://www.d.run",
      gateway: "models.dev"
    },
    huggingface: {
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      apiKeyEnvVar: "HF_TOKEN",
      apiKeyHeader: "Authorization",
      name: "Hugging Face",
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        "MiniMaxAI/MiniMax-M2.7",
        "Qwen/Qwen3-235B-A22B-Thinking-2507",
        "Qwen/Qwen3-Coder-480B-A35B-Instruct",
        "Qwen/Qwen3-Coder-Next",
        "Qwen/Qwen3-Embedding-4B",
        "Qwen/Qwen3-Embedding-8B",
        "Qwen/Qwen3-Next-80B-A3B-Instruct",
        "Qwen/Qwen3-Next-80B-A3B-Thinking",
        "Qwen/Qwen3.5-397B-A17B",
        "XiaomiMiMo/MiMo-V2-Flash",
        "deepseek-ai/DeepSeek-R1-0528",
        "deepseek-ai/DeepSeek-V3.2",
        "deepseek-ai/DeepSeek-V4-Pro",
        "moonshotai/Kimi-K2-Instruct",
        "moonshotai/Kimi-K2-Instruct-0905",
        "moonshotai/Kimi-K2-Thinking",
        "moonshotai/Kimi-K2.5",
        "moonshotai/Kimi-K2.6",
        "zai-org/GLM-4.7",
        "zai-org/GLM-4.7-Flash",
        "zai-org/GLM-5",
        "zai-org/GLM-5.1"
      ],
      docUrl: "https://huggingface.co/docs/inference-providers",
      gateway: "models.dev"
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      apiKeyEnvVar: "UMANS_AI_CODING_PLAN_API_KEY",
      apiKeyHeader: "Authorization",
      name: "Umans AI Coding Plan",
      models: ["umans-coder", "umans-flash", "umans-glm-5.1", "umans-kimi-k2.6", "umans-qwen3.6-35b-a3b"],
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      gateway: "models.dev"
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      apiKeyEnvVar: "TENCENT_TOKENHUB_API_KEY",
      apiKeyHeader: "Authorization",
      name: "Tencent TokenHub",
      models: ["hy3-preview"],
      docUrl: "https://cloud.tencent.com/document/product/1823/130050",
      gateway: "models.dev"
    },
    nebius: {
      url: "https://api.tokenfactory.nebius.com/v1",
      apiKeyEnvVar: "NEBIUS_API_KEY",
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        "NousResearch/Hermes-4-405B",
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        "PrimeIntellect/INTELLECT-3",
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        "Qwen/Qwen3-235B-A22B-Instruct-2507",
        "Qwen/Qwen3-235B-A22B-Thinking-2507-fast",
        "Qwen/Qwen3-30B-A3B-Instruct-2507",
        "Qwen/Qwen3-32B",
        "Qwen/Qwen3-Embedding-8B",
        "Qwen/Qwen3-Next-80B-A3B-Thinking",
        "Qwen/Qwen3-Next-80B-A3B-Thinking-fast",
        "Qwen/Qwen3.5-397B-A17B",
        "Qwen/Qwen3.5-397B-A17B-fast",
        "deepseek-ai/DeepSeek-V3.2",
        "deepseek-ai/DeepSeek-V3.2-fast",
        "deepseek-ai/DeepSeek-V4-Pro",
        "google/gemma-2-2b-it",
        "google/gemma-3-27b-it",
        "meta-llama/Llama-3.3-70B-Instruct",
        "meta-llama/Meta-Llama-3.1-8B-Instruct",
        "moonshotai/Kimi-K2.5",
        "moonshotai/Kimi-K2.5-fast",
        "nvidia/Llama-3_1-Nemotron-Ultra-253B-v1",
        "nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B",
        "nvidia/Nemotron-3-Nano-Omni",
        "nvidia/nemotron-3-super-120b-a12b",
        "openai/gpt-oss-120b",
        "openai/gpt-oss-120b-fast",
        "zai-org/GLM-5"
      ],
      docUrl: "https://docs.tokenfactory.nebius.com/",
      gateway: "models.dev"
    },
    "hpc-ai": {
      url: "https://api.hpc-ai.com/inference/v1",
      apiKeyEnvVar: "HPC_AI_API_KEY",
      apiKeyHeader: "Authorization",
      name: "HPC-AI",
      models: ["minimax/minimax-m2.5", "moonshotai/kimi-k2.5", "zai-org/glm-5.1"],
      docUrl: "https://www.hpc-ai.com/doc/docs/quickstart/",
      gateway: "models.dev"
    },
    xiaomi: {
      url: "https://api.xiaomimimo.com/v1",
      apiKeyEnvVar: "XIAOMI_API_KEY",
      apiKeyHeader: "Authorization",
      name: "Xiaomi",
      models: ["mimo-v2-flash", "mimo-v2-omni", "mimo-v2-pro", "mimo-v2.5", "mimo-v2.5-pro"],
      docUrl: "https://platform.xiaomimimo.com/#/docs",
      gateway: "models.dev"
    },
    togetherai: {
      apiKeyEnvVar: "TOGETHER_API_KEY",
      name: "Together AI",
      models: [
        "MiniMaxAI/MiniMax-M2.5",
        "MiniMaxAI/MiniMax-M2.7",
        "Qwen/Qwen3-235B-A22B-Instruct-2507-tput",
        "Qwen/Qwen3-Coder-480B-A35B-Instruct-FP8",
        "Qwen/Qwen3-Coder-Next-FP8",
        "Qwen/Qwen3.5-397B-A17B",
        "Qwen/Qwen3.6-Plus",
        "deepseek-ai/DeepSeek-R1",
        "deepseek-ai/DeepSeek-V3",
        "deepseek-ai/DeepSeek-V3-1",
        "deepseek-ai/DeepSeek-V4-Pro",
        "essentialai/Rnj-1-Instruct",
        "google/gemma-4-31B-it",
        "meta-llama/Llama-3.3-70B-Instruct-Turbo",
        "moonshotai/Kimi-K2.5",
        "moonshotai/Kimi-K2.6",
        "openai/gpt-oss-120b",
        "zai-org/GLM-5.1"
      ],
      docUrl: "https://docs.together.ai/docs/serverless-models",
      gateway: "models.dev",
      npm: "@ai-sdk/togetherai"
    },
    "stepfun-ai": {
      url: "https://api.stepfun.ai/step_plan/v1",
      apiKeyEnvVar: "STEPFUN_API_KEY",
      apiKeyHeader: "Authorization",
      name: "StepFun",
      models: ["step-3.5-flash", "step-3.5-flash-2603"],
      docUrl: "https://platform.stepfun.ai/docs/en/step-plan/integrations/open-code",
      gateway: "models.dev"
    },
    inference: {
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      apiKeyEnvVar: "INFERENCE_API_KEY",
      apiKeyHeader: "Authorization",
      name: "Inference",
      models: [
        "google/gemma-3",
        "meta/llama-3.1-8b-instruct",
        "meta/llama-3.2-11b-vision-instruct",
        "meta/llama-3.2-1b-instruct",
        "meta/llama-3.2-3b-instruct",
        "mistral/mistral-nemo-12b-instruct",
        "osmosis/osmosis-structure-0.6b",
        "qwen/qwen-2.5-7b-vision-instruct",
        "qwen/qwen3-embedding-4b"
      ],
      docUrl: "https://inference.net/models",
      gateway: "models.dev"
    },
    netlify: {
      apiKeyEnvVar: ["NETLIFY_TOKEN", "NETLIFY_SITE_ID"],
      apiKeyHeader: "Authorization",
      name: "Netlify",
      gateway: "netlify",
      models: [
        "anthropic/claude-haiku-4-5",
        "anthropic/claude-haiku-4-5-20251001",
        "anthropic/claude-opus-4-1-20250805",
        "anthropic/claude-opus-4-20250514",
        "anthropic/claude-opus-4-5",
        "anthropic/claude-opus-4-5-20251101",
        "anthropic/claude-opus-4-6",
        "anthropic/claude-opus-4-7",
        "anthropic/claude-sonnet-4-0",
        "anthropic/claude-sonnet-4-20250514",
        "anthropic/claude-sonnet-4-5",
        "anthropic/claude-sonnet-4-5-20250929",
        "anthropic/claude-sonnet-4-6",
        "gemini/gemini-2.0-flash",
        "gemini/gemini-2.0-flash-lite",
        "gemini/gemini-2.5-flash",
        "gemini/gemini-2.5-flash-image",
        "gemini/gemini-2.5-flash-lite",
        "gemini/gemini-2.5-pro",
        "gemini/gemini-3-flash-preview",
        "gemini/gemini-3-pro-image-preview",
        "gemini/gemini-3.1-flash-image-preview",
        "gemini/gemini-3.1-flash-lite",
        "gemini/gemini-3.1-flash-lite-preview",
        "gemini/gemini-3.1-pro-preview",
        "gemini/gemini-3.1-pro-preview-customtools",
        "gemini/gemini-3.5-flash",
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        "gemini/gemini-flash-lite-latest",
        "openai/chat-latest",
        "openai/gpt-4.1",
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        "openai/gpt-4o-mini",
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        "openai/gpt-5-2025-08-07",
        "openai/gpt-5-codex",
        "openai/gpt-5-mini",
        "openai/gpt-5-mini-2025-08-07",
        "openai/gpt-5-nano",
        "openai/gpt-5-pro",
        "openai/gpt-5.1",
        "openai/gpt-5.1-2025-11-13",
        "openai/gpt-5.1-codex",
        "openai/gpt-5.1-codex-max",
        "openai/gpt-5.1-codex-mini",
        "openai/gpt-5.2",
        "openai/gpt-5.2-2025-12-11",
        "openai/gpt-5.2-codex",
        "openai/gpt-5.2-pro",
        "openai/gpt-5.2-pro-2025-12-11",
        "openai/gpt-5.3-chat-latest",
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        "openai/gpt-5.4-2026-03-05",
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        "openai/gpt-5.4-mini-2026-03-17",
        "openai/gpt-5.4-nano",
        "openai/gpt-5.4-nano-2026-03-17",
        "openai/gpt-5.4-pro",
        "openai/gpt-5.4-pro-2026-03-05",
        "openai/gpt-5.5",
        "openai/gpt-5.5-2026-04-23",
        "openai/gpt-5.5-pro",
        "openai/gpt-5.5-pro-2026-04-23",
        "openai/o3",
        "openai/o3-mini",
        "openai/o4-mini"
      ],
      docUrl: "https://docs.netlify.com/build/ai-gateway/overview/"
    }
  },
  models: {
    helicone: [
      "chatgpt-4o-latest",
      "claude-3-haiku-20240307",
      "claude-3.5-haiku",
      "claude-3.5-sonnet-v2",
      "claude-3.7-sonnet",
      "claude-4.5-haiku",
      "claude-4.5-opus",
      "claude-4.5-sonnet",
      "claude-haiku-4-5-20251001",
      "claude-opus-4",
      "claude-opus-4-1",
      "claude-opus-4-1-20250805",
      "claude-sonnet-4",
      "claude-sonnet-4-5-20250929",
      "deepseek-r1-distill-llama-70b",
      "deepseek-reasoner",
      "deepseek-tng-r1t2-chimera",
      "deepseek-v3",
      "deepseek-v3.1-terminus",
      "deepseek-v3.2",
      "ernie-4.5-21b-a3b-thinking",
      "gemini-2.5-flash",
      "gemini-2.5-flash-lite",
      "gemini-2.5-pro",
      "gemini-3-pro-preview",
      "gemma-3-12b-it",
      "gemma2-9b-it",
      "glm-4.6",
      "gpt-4.1",
      "gpt-4.1-mini",
      "gpt-4.1-mini-2025-04-14",
      "gpt-4.1-nano",
      "gpt-4o",
      "gpt-4o-mini",
      "gpt-5",
      "gpt-5-chat-latest",
      "gpt-5-codex",
      "gpt-5-mini",
      "gpt-5-nano",
      "gpt-5-pro",
      "gpt-5.1",
      "gpt-5.1-chat-latest",
      "gpt-5.1-codex",
      "gpt-5.1-codex-mini",
      "gpt-oss-120b",
      "gpt-oss-20b",
      "grok-3",
      "grok-3-mini",
      "grok-4",
      "grok-4-1-fast-non-reasoning",
      "grok-4-1-fast-reasoning",
      "grok-4-fast-non-reasoning",
      "grok-4-fast-reasoning",
      "grok-code-fast-1",
      "hermes-2-pro-llama-3-8b",
      "kimi-k2-0711",
      "kimi-k2-0905",
      "kimi-k2-thinking",
      "llama-3.1-8b-instant",
      "llama-3.1-8b-instruct",
      "llama-3.1-8b-instruct-turbo",
      "llama-3.3-70b-instruct",
      "llama-3.3-70b-versatile",
      "llama-4-maverick",
      "llama-4-scout",
      "llama-guard-4",
      "llama-prompt-guard-2-22m",
      "llama-prompt-guard-2-86m",
      "mistral-large-2411",
      "mistral-nemo",
      "mistral-small",
      "o1",
      "o1-mini",
      "o3",
      "o3-mini",
      "o3-pro",
      "o4-mini",
      "qwen2.5-coder-7b-fast",
      "qwen3-235b-a22b-thinking",
      "qwen3-30b-a3b",
      "qwen3-32b",
      "qwen3-coder",
      "qwen3-coder-30b-a3b-instruct",
      "qwen3-next-80b-a3b-instruct",
      "qwen3-vl-235b-a22b-instruct",
      "sonar",
      "sonar-deep-research",
      "sonar-pro",
      "sonar-reasoning",
      "sonar-reasoning-pro"
    ],
    auriko: [
      "claude-opus-4-6",
      "claude-opus-4-7",
      "claude-sonnet-4-6",
      "deepseek-v4-flash",
      "deepseek-v4-pro",
      "gemini-2.5-flash",
      "gemini-2.5-pro",
      "gemini-3.1-pro-preview",
      "glm-5.1",
      "grok-4.3",
      "kimi-k2.5",
      "kimi-k2.6",
      "minimax-m2-7",
      "minimax-m2-7-highspeed",
      "qwen-3.6-plus"
    ],
    firepass: ["accounts/fireworks/routers/kimi-k2p6-turbo"],
    "nano-gpt": [
      "Alibaba-NLP/Tongyi-DeepResearch-30B-A3B",
      "Baichuan-M2",
      "Baichuan4-Air",
      "Baichuan4-Turbo",
      "CrucibleLab/L3.3-70B-Loki-V2.0",
      "Doctor-Shotgun/MS3.2-24B-Magnum-Diamond",
      "EVA-UNIT-01/EVA-LLaMA-3.33-70B-v0.0",
      "EVA-UNIT-01/EVA-LLaMA-3.33-70B-v0.1",
      "EVA-UNIT-01/EVA-Qwen2.5-32B-v0.2",
      "EVA-UNIT-01/EVA-Qwen2.5-72B-v0.2",
      "Envoid/Llama-3.05-NT-Storybreaker-Ministral-70B",
      "Envoid/Llama-3.05-Nemotron-Tenyxchat-Storybreaker-70B",
      "GLM-4.5-Air-Derestricted",
      "GLM-4.5-Air-Derestricted-Iceblink",
      "GLM-4.5-Air-Derestricted-Iceblink-ReExtract",
      "GLM-4.5-Air-Derestricted-Iceblink-v2",
      "GLM-4.5-Air-Derestricted-Iceblink-v2-ReExtract",
      "GLM-4.5-Air-Derestricted-Steam",
      "GLM-4.5-Air-Derestricted-Steam-ReExtract",
      "GLM-4.6-Derestricted-v5",
      "GalrionSoftworks/MN-LooseCannon-12B-v1",
      "Gemma-3-27B-ArliAI-RPMax-v3",
      "Gemma-3-27B-Big-Tiger-v3",
      "Gemma-3-27B-CardProjector-v4",
      "Gemma-3-27B-Glitter",
      "Gemma-3-27B-Nidum-Uncensored",
      "Gemma-3-27B-it",
      "Gemma-3-27B-it-Abliterated",
      "Gryphe/MythoMax-L2-13b",
      "Infermatic/MN-12B-Inferor-v0.0",
      "KAT-Coder-Air-V1",
      "KAT-Coder-Exp-72B-1010",
      "KAT-Coder-Pro-V1",
      "LLM360/K2-Think",
      "LatitudeGames/Wayfarer-Large-70B-Llama-3.3",
      "Llama-3.3+(3.1v3.3)-70B-Hanami-x1",
      "Llama-3.3+(3.1v3.3)-70B-New-Dawn-v1.1",
      "Llama-3.3+(3v3.3)-70B-TenyxChat-DaybreakStorywriter",
      "Llama-3.3-70B-Anthrobomination",
      "Llama-3.3-70B-Argunaut-1-SFT",
      "Llama-3.3-70B-ArliAI-RPMax-v1.4",
      "Llama-3.3-70B-ArliAI-RPMax-v2",
      "Llama-3.3-70B-ArliAI-RPMax-v3",
      "Llama-3.3-70B-Aurora-Borealis",
      "Llama-3.3-70B-Bigger-Body",
      "Llama-3.3-70B-Cirrus-x1",
      "Llama-3.3-70B-Cu-Mai-R1",
      "Llama-3.3-70B-Damascus-R1",
      "Llama-3.3-70B-Dark-Ages-v0.1",
      "Llama-3.3-70B-Electra-R1",
      "Llama-3.3-70B-Electranova-v1.0",
      "Llama-3.3-70B-Fallen-R1-v1",
      "Llama-3.3-70B-Fallen-v1",
      "Llama-3.3-70B-Forgotten-Abomination-v5.0",
      "Llama-3.3-70B-Forgotten-Safeword-3.6",
      "Llama-3.3-70B-GeneticLemonade-Opus",
      "Llama-3.3-70B-GeneticLemonade-Unleashed-v3",
      "Llama-3.3-70B-Ignition-v0.1",
      "Llama-3.3-70B-Incandescent-Malevolence",
      "Llama-3.3-70B-Legion-V2.1",
      "Llama-3.3-70B-MS-Nevoria",
      "Llama-3.3-70B-Magnum-v4-SE",
      "Llama-3.3-70B-Magnum-v4-SE-Cirrus-x1-SLERP",
      "Llama-3.3-70B-Mhnnn-x1",
      "Llama-3.3-70B-MiraiFanfare",
      "Llama-3.3-70B-Mokume-Gane-R1",
      "Llama-3.3-70B-Nova",
      "Llama-3.3-70B-Predatorial-Extasy",
      "Llama-3.3-70B-Progenitor-V3.3",
      "Llama-3.3-70B-RAWMAW",
      "Llama-3.3-70B-Sapphira-0.1",
      "Llama-3.3-70B-Sapphira-0.2",
      "Llama-3.3-70B-Shakudo",
      "Llama-3.3-70B-StrawberryLemonade-v1.0",
      "Llama-3.3-70B-Strawberrylemonade-v1.2",
      "Llama-3.3-70B-The-Omega-Directive-Unslop-v2.0",
      "Llama-3.3-70B-The-Omega-Directive-Unslop-v2.1",
      "Llama-3.3-70B-Vulpecula-R1",
      "Magistral-Small-2506",
      "MarinaraSpaghetti/NemoMix-Unleashed-12B",
      "Meta-Llama-3-1-8B-Instruct-FP8",
      "MiniMax-M1",
      "MiniMax-M2",
      "MiniMaxAI/MiniMax-M1-80k",
      "Mistral-Nemo-12B-Instruct-2407",
      "NeverSleep/Llama-3-Lumimaid-70B-v0.1",
      "NeverSleep/Lumimaid-v0.2-70B",
      "NousResearch 2/DeepHermes-3-Mistral-24B-Preview",
      "NousResearch 2/Hermes-4-70B:thinking",
      "NousResearch 2/hermes-3-llama-3.1-70b",
      "NousResearch 2/hermes-4-405b",
      "NousResearch 2/hermes-4-405b:thinking",
      "NousResearch 2/hermes-4-70b",
      "QwQ-32B-ArliAI-RpR-v1",
      "Qwen2.5-32B-EVA-v0.2",
      "ReadyArt/MS3.2-The-Omega-Directive-24B-Unslop-v2.0",
      "ReadyArt/The-Omega-Abomination-L-70B-v1.0",
      "Salesforce/Llama-xLAM-2-70b-fc-r",
      "Sao10K/L3-8B-Stheno-v3.2",
      "Sao10K/L3.1-70B-Euryale-v2.2",
      "Sao10K/L3.1-70B-Hanami-x1",
      "Sao10K/L3.3-70B-Euryale-v2.3",
      "Steelskull/L3.3-Cu-Mai-R1-70b",
      "Steelskull/L3.3-Electra-R1-70b",
      "Steelskull/L3.3-MS-Evalebis-70b",
      "Steelskull/L3.3-MS-Evayale-70B",
      "Steelskull/L3.3-MS-Nevoria-70b",
      "Steelskull/L3.3-Nevoria-R1-70b",
      "TEE/deepseek-r1-0528",
      "TEE/deepseek-v3.1",
      "TEE/deepseek-v3.2",
      "TEE/gemma-3-27b-it",
      "TEE/glm-4.6",
      "TEE/glm-4.7",
      "TEE/glm-4.7-flash",
      "TEE/glm-5",
      "TEE/gpt-oss-120b",
      "TEE/gpt-oss-20b",
      "TEE/kimi-k2-thinking",
      "TEE/kimi-k2.5",
      "TEE/kimi-k2.5-thinking",
      "TEE/llama3-3-70b",
      "TEE/minimax-m2.1",
      "TEE/qwen2.5-vl-72b-instruct",
      "TEE/qwen3-30b-a3b-instruct-2507",
      "TEE/qwen3-coder",
      "TEE/qwen3.5-397b-a17b",
      "THUDM/GLM-4-32B-0414",
      "THUDM/GLM-4-9B-0414",
      "THUDM/GLM-Z1-32B-0414",
      "THUDM/GLM-Z1-9B-0414",
      "THUDM/GLM-Z1-Rumination-32B-0414",
      "TheDrummer 2/Anubis-70B-v1",
      "TheDrummer 2/Anubis-70B-v1.1",
      "TheDrummer 2/Cydonia-24B-v2",
      "TheDrummer 2/Cydonia-24B-v4",
      "TheDrummer 2/Cydonia-24B-v4.1",
      "TheDrummer 2/Cydonia-24B-v4.3",
      "TheDrummer 2/Magidonia-24B-v4.3",
      "TheDrummer 2/Rocinante-12B-v1.1",
      "TheDrummer 2/UnslopNemo-12B-v4.1",
      "TheDrummer 2/skyfall-36b-v2",
      "Tongyi-Zhiwen/QwenLong-L1-32B",
      "VongolaChouko/Starcannon-Unleashed-12B-v1.0",
      "abacusai/Dracarys-72B-Instruct",
      "aion-labs/aion-1.0",
      "aion-labs/aion-1.0-mini",
      "aion-labs/aion-rp-llama-3.1-8b",
      "alibaba/qwen3.6-flash",
      "allenai/molmo-2-8b",
      "allenai/olmo-3-32b-think",
      "allenai/olmo-3.1-32b-instruct",
      "allenai/olmo-3.1-32b-think",
      "amazon/nova-2-lite-v1",
      "amazon/nova-lite-v1",
      "amazon/nova-micro-v1",
      "amazon/nova-pro-v1",
      "anthracite-org/magnum-v2-72b",
      "anthracite-org/magnum-v4-72b",
      "anthropic/claude-opus-4.6",
      "anthropic/claude-opus-4.6:thinking",
      "anthropic/claude-opus-4.6:thinking:low",
      "anthropic/claude-opus-4.6:thinking:max",
      "anthropic/claude-opus-4.6:thinking:medium",
      "anthropic/claude-sonnet-4.6",
      "anthropic/claude-sonnet-4.6:thinking",
      "arcee-ai/trinity-large",
      "arcee-ai/trinity-mini",
      "asi1-mini",
      "auto-model",
      "auto-model-basic",
      "auto-model-premium",
      "auto-model-standard",
      "azure-gpt-4-turbo",
      "azure-gpt-4o",
      "azure-gpt-4o-mini",
      "azure-o1",
      "azure-o3-mini",
      "baidu/ernie-4.5-300b-a47b",
      "baidu/ernie-4.5-vl-28b-a3b",
      "baseten/Kimi-K2-Instruct-FP4",
      "brave",
      "brave-pro",
      "brave-research",
      "chroma",
      "chutesai/Mistral-Small-3.2-24B-Instruct-2506",
      "claude-3-5-haiku-20241022",
      "claude-3-5-sonnet-20240620",
      "claude-3-5-sonnet-20241022",
      "claude-3-7-sonnet-20250219",
      "claude-3-7-sonnet-reasoner",
      "claude-3-7-sonnet-thinking",
      "claude-3-7-sonnet-thinking:1024",
      "claude-3-7-sonnet-thinking:128000",
      "claude-3-7-sonnet-thinking:32768",
      "claude-3-7-sonnet-thinking:8192",
      "claude-haiku-4-5-20251001",
      "claude-opus-4-1-20250805",
      "claude-opus-4-1-thinking",
      "claude-opus-4-1-thinking:1024",
      "claude-opus-4-1-thinking:32000",
      "claude-opus-4-1-thinking:32768",
      "claude-opus-4-1-thinking:8192",
      "claude-opus-4-20250514",
      "claude-opus-4-5-20251101",
      "claude-opus-4-5-20251101:thinking",
      "claude-opus-4-thinking",
      "claude-opus-4-thinking:1024",
      "claude-opus-4-thinking:32000",
      "claude-opus-4-thinking:32768",
      "claude-opus-4-thinking:8192",
      "claude-sonnet-4-20250514",
      "claude-sonnet-4-5-20250929",
      "claude-sonnet-4-5-20250929-thinking",
      "claude-sonnet-4-thinking",
      "claude-sonnet-4-thinking:1024",
      "claude-sonnet-4-thinking:32768",
      "claude-sonnet-4-thinking:64000",
      "claude-sonnet-4-thinking:8192",
      "cognitivecomputations/dolphin-2.9.2-qwen2-72b",
      "cohere/command-r",
      "cohere/command-r-plus-08-2024",
      "command-a-reasoning-08-2025",
      "deepclaude",
      "deepcogito/cogito-v1-preview-qwen-32B",
      "deepcogito/cogito-v2.1-671b",
      "deepseek-ai/DeepSeek-R1-0528",
      "deepseek-ai/DeepSeek-V3.1",
      "deepseek-ai/DeepSeek-V3.1-Terminus",
      "deepseek-ai/DeepSeek-V3.1-Terminus:thinking",
      "deepseek-ai/DeepSeek-V3.1:thinking",
      "deepseek-ai/deepseek-v3.2-exp",
      "deepseek-ai/deepseek-v3.2-exp-thinking",
      "deepseek-chat",
      "deepseek-chat-cheaper",
      "deepseek-math-v2",
      "deepseek-r1",
      "deepseek-r1-sambanova",
      "deepseek-reasoner",
      "deepseek-reasoner-cheaper",
      "deepseek-v3-0324",
      "deepseek/deepseek-prover-v2-671b",
      "deepseek/deepseek-v3.2",
      "deepseek/deepseek-v3.2-speciale",
      "deepseek/deepseek-v3.2:thinking",
      "dmind/dmind-1",
      "dmind/dmind-1-mini",
      "doubao-1-5-thinking-pro-250415",
      "doubao-1-5-thinking-pro-vision-250415",
      "doubao-1-5-thinking-vision-pro-250428",
      "doubao-1.5-pro-256k",
      "doubao-1.5-pro-32k",
      "doubao-1.5-vision-pro-32k",
      "doubao-seed-1-6-250615",
      "doubao-seed-1-6-flash-250615",
      "doubao-seed-1-6-thinking-250615",
      "doubao-seed-1-8-251215",
      "doubao-seed-2-0-code-preview-260215",
      "doubao-seed-2-0-lite-260215",
      "doubao-seed-2-0-mini-260215",
      "doubao-seed-2-0-pro-260215",
      "doubao-seed-code-preview-latest",
      "ernie-4.5-8k-preview",
      "ernie-4.5-turbo-128k",
      "ernie-4.5-turbo-vl-32k",
      "ernie-5.0-thinking-latest",
      "ernie-5.0-thinking-preview",
      "ernie-x1-32k",
      "ernie-x1-32k-preview",
      "ernie-x1-turbo-32k",
      "ernie-x1.1-preview",
      "essentialai/rnj-1-instruct",
      "exa-answer",
      "exa-research",
      "exa-research-pro",
      "failspy/Meta-Llama-3-70B-Instruct-abliterated-v3.5",
      "fastgpt",
      "featherless-ai/Qwerky-72B",
      "gemini-2.0-flash-001",
      "gemini-2.0-flash-exp-image-generation",
      "gemini-2.0-flash-lite",
      "gemini-2.0-flash-thinking-exp-01-21",
      "gemini-2.0-flash-thinking-exp-1219",
      "gemini-2.0-pro-exp-02-05",
      "gemini-2.0-pro-reasoner",
      "gemini-2.5-flash",
      "gemini-2.5-flash-lite",
      "gemini-2.5-flash-lite-preview-06-17",
      "gemini-2.5-flash-lite-preview-09-2025",
      "gemini-2.5-flash-lite-preview-09-2025-thinking",
      "gemini-2.5-flash-nothinking",
      "gemini-2.5-flash-preview-04-17",
      "gemini-2.5-flash-preview-04-17:thinking",
      "gemini-2.5-flash-preview-05-20",
      "gemini-2.5-flash-preview-05-20:thinking",
      "gemini-2.5-flash-preview-09-2025",
      "gemini-2.5-flash-preview-09-2025-thinking",
      "gemini-2.5-pro",
      "gemini-2.5-pro-exp-03-25",
      "gemini-2.5-pro-preview-03-25",
      "gemini-2.5-pro-preview-05-06",
      "gemini-2.5-pro-preview-06-05",
      "gemini-3-pro-image-preview",
      "gemini-3-pro-preview",
      "gemini-3-pro-preview-thinking",
      "gemini-exp-1206",
      "glm-4",
      "glm-4-air",
      "glm-4-air-0111",
      "glm-4-airx",
      "glm-4-flash",
      "glm-4-long",
      "glm-4-plus",
      "glm-4-plus-0111",
      "glm-4.1v-thinking-flash",
      "glm-4.1v-thinking-flashx",
      "glm-z1-air",
      "glm-z1-airx",
      "glm-zero-preview",
      "google/gemini-3-flash-preview",
      "google/gemini-3-flash-preview-thinking",
      "google/gemini-flash-1.5",
      "grok-3-beta",
      "grok-3-fast-beta",
      "grok-3-mini-beta",
      "grok-3-mini-fast-beta",
      "hidream",
      "huihui-ai/DeepSeek-R1-Distill-Llama-70B-abliterated",
      "huihui-ai/DeepSeek-R1-Distill-Qwen-32B-abliterated",
      "huihui-ai/Llama-3.1-Nemotron-70B-Instruct-HF-abliterated",
      "huihui-ai/Llama-3.3-70B-Instruct-abliterated",
      "huihui-ai/Qwen2.5-32B-Instruct-abliterated",
      "hunyuan-t1-latest",
      "hunyuan-turbos-20250226",
      "inflatebot/MN-12B-Mag-Mell-R1",
      "inflection/inflection-3-pi",
      "inflection/inflection-3-productivity",
      "jamba-large",
      "jamba-large-1.6",
      "jamba-large-1.7",
      "jamba-mini",
      "jamba-mini-1.6",
      "jamba-mini-1.7",
      "kimi-k2-instruct-fast",
      "kimi-thinking-preview",
      "learnlm-1.5-pro-experimental",
      "meganova-ai/manta-flash-1.0",
      "meganova-ai/manta-mini-1.0",
      "meganova-ai/manta-pro-1.0",
      "meituan-longcat/LongCat-Flash-Chat-FP8",
      "meta-llama/llama-3.1-8b-instruct",
      "meta-llama/llama-3.2-3b-instruct",
      "meta-llama/llama-3.2-90b-vision-instruct",
      "meta-llama/llama-3.3-70b-instruct",
      "meta-llama/llama-4-maverick",
      "meta-llama/llama-4-scout",
      "microsoft/MAI-DS-R1-FP8",
      "microsoft/wizardlm-2-8x22b",
      "minimax/minimax-01",
      "minimax/minimax-m2-her",
      "minimax/minimax-m2.1",
      "minimax/minimax-m2.5",
      "minimax/minimax-m2.7",
      "miromind-ai/mirothinker-v1.5-235b",
      "mistral-small-31-24b-instruct",
      "mistralai/Devstral-Small-2505",
      "mistralai/Mistral-Nemo-Instruct-2407",
      "mistralai/codestral-2508",
      "mistralai/devstral-2-123b-instruct-2512",
      "mistralai/ministral-14b-2512",
      "mistralai/ministral-14b-instruct-2512",
      "mistralai/ministral-3b-2512",
      "mistralai/ministral-8b-2512",
      "mistralai/mistral-7b-instruct",
      "mistralai/mistral-large",
      "mistralai/mistral-large-3-675b-instruct-2512",
      "mistralai/mistral-medium-3",
      "mistralai/mistral-medium-3.1",
      "mistralai/mistral-saba",
      "mistralai/mistral-small-creative",
      "mistralai/mistral-tiny",
      "mistralai/mixtral-8x22b-instruct-v0.1",
      "mistralai/mixtral-8x7b-instruct-v0.1",
      "mlabonne/NeuralDaredevil-8B-abliterated",
      "moonshotai/Kimi-Dev-72B",
      "moonshotai/Kimi-K2-Instruct-0905",
      "moonshotai/kimi-k2-instruct",
      "moonshotai/kimi-k2-instruct-0711",
      "moonshotai/kimi-k2-thinking",
      "moonshotai/kimi-k2-thinking-original",
      "moonshotai/kimi-k2-thinking-turbo-original",
      "moonshotai/kimi-k2.5",
      "moonshotai/kimi-k2.5:thinking",
      "moonshotai/kimi-k2.6",
      "moonshotai/kimi-k2.6:thinking",
      "nex-agi/deepseek-v3.1-nex-n1",
      "nothingiisreal/L3.1-70B-Celeste-V0.1-BF16",
      "nvidia/Llama-3.1-Nemotron-70B-Instruct-HF",
      "nvidia/Llama-3.1-Nemotron-Ultra-253B-v1",
      "nvidia/Llama-3.3-Nemotron-Super-49B-v1",
      "nvidia/Llama-3_3-Nemotron-Super-49B-v1_5",
      "nvidia/nemotron-3-nano-30b-a3b",
      "nvidia/nvidia-nemotron-nano-9b-v2",
      "openai/chatgpt-4o-latest",
      "openai/gpt-3.5-turbo",
      "openai/gpt-4-turbo",
      "openai/gpt-4-turbo-preview",
      "openai/gpt-4.1",
      "openai/gpt-4.1-mini",
      "openai/gpt-4.1-nano",
      "openai/gpt-4o",
      "openai/gpt-4o-2024-08-06",
      "openai/gpt-4o-2024-11-20",
      "openai/gpt-4o-mini",
      "openai/gpt-4o-mini-search-preview",
      "openai/gpt-4o-search-preview",
      "openai/gpt-5",
      "openai/gpt-5-chat-latest",
      "openai/gpt-5-codex",
      "openai/gpt-5-mini",
      "openai/gpt-5-nano",
      "openai/gpt-5-pro",
      "openai/gpt-5.1",
      "openai/gpt-5.1-2025-11-13",
      "openai/gpt-5.1-chat",
      "openai/gpt-5.1-chat-latest",
      "openai/gpt-5.1-codex",
      "openai/gpt-5.1-codex-max",
      "openai/gpt-5.1-codex-mini",
      "openai/gpt-5.2",
      "openai/gpt-5.2-chat",
      "openai/gpt-5.2-codex",
      "openai/gpt-5.2-pro",
      "openai/gpt-oss-120b",
      "openai/gpt-oss-20b",
      "openai/gpt-oss-safeguard-20b",
      "openai/o1",
      "openai/o1-preview",
      "openai/o1-pro",
      "openai/o3",
      "openai/o3-deep-research",
      "openai/o3-mini",
      "openai/o3-mini-high",
      "openai/o3-mini-low",
      "openai/o3-pro-2025-06-10",
      "openai/o4-mini",
      "openai/o4-mini-deep-research",
      "openai/o4-mini-high",
      "pamanseau/OpenReasoning-Nemotron-32B",
      "phi-4-mini-instruct",
      "phi-4-multimodal-instruct",
      "qvq-max",
      "qwen-3.6-plus",
      "qwen-image",
      "qwen-long",
      "qwen-max",
      "qwen-plus",
      "qwen-turbo",
      "qwen/Qwen3.6-35B-A3B",
      "qwen/Qwen3.6-35B-A3B:thinking",
      "qwen/qwen3.5-397b-a17b",
      "qwen25-vl-72b-instruct",
      "qwen3-30b-a3b-instruct-2507",
      "qwen3-coder-30b-a3b-instruct",
      "qwen3-max-2026-01-23",
      "qwen3-vl-235b-a22b-instruct-original",
      "qwen3-vl-235b-a22b-thinking",
      "qwen3.6-max-preview",
      "qwq-32b",
      "raifle/sorcererlm-8x22b",
      "sarvan-medium",
      "shisa-ai/shisa-v2-llama3.3-70b",
      "shisa-ai/shisa-v2.1-llama3.3-70b",
      "sonar",
      "sonar-deep-research",
      "sonar-pro",
      "sonar-reasoning-pro",
      "soob3123/GrayLine-Qwen3-8B",
      "soob3123/Veiled-Calla-12B",
      "soob3123/amoral-gemma3-27B-v2",
      "step-2-16k-exp",
      "step-2-mini",
      "step-3",
      "step-r1-v-mini",
      "stepfun-ai/step-3.5-flash",
      "stepfun-ai/step-3.5-flash:thinking",
      "study_gpt-chatgpt-4o-latest",
      "tencent/Hunyuan-MT-7B",
      "tngtech/DeepSeek-TNG-R1T2-Chimera",
      "tngtech/tng-r1t-chimera",
      "undi95/remm-slerp-l2-13b",
      "universal-summarizer",
      "unsloth/gemma-3-12b-it",
      "unsloth/gemma-3-1b-it",
      "unsloth/gemma-3-27b-it",
      "unsloth/gemma-3-4b-it",
      "v0-1.0-md",
      "v0-1.5-lg",
      "v0-1.5-md",
      "venice-uncensored",
      "venice-uncensored:web",
      "x-ai/grok-4-07-09",
      "x-ai/grok-4-fast",
      "x-ai/grok-4-fast:thinking",
      "x-ai/grok-4.1-fast",
      "x-ai/grok-4.1-fast-reasoning",
      "x-ai/grok-code-fast-1",
      "xiaomi/mimo-v2-flash",
      "xiaomi/mimo-v2-flash-original",
      "xiaomi/mimo-v2-flash-thinking",
      "xiaomi/mimo-v2-flash-thinking-original",
      "yi-large",
      "yi-lightning",
      "yi-medium-200k",
      "z-ai/glm-4.5v",
      "z-ai/glm-4.5v:thinking",
      "z-ai/glm-4.6",
      "z-ai/glm-4.6:thinking",
      "z-image-turbo",
      "zai-org/glm-4.7",
      "zai-org/glm-4.7-flash",
      "zai-org/glm-5",
      "zai-org/glm-5.1",
      "zai-org/glm-5.1:thinking",
      "zai-org/glm-5:thinking"
    ],
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      "Intel/Qwen3-Coder-480B-A35B-Instruct-int4-mixed-ar",
      "Qwen/Qwen2.5-VL-32B-Instruct",
      "Qwen/Qwen3-235B-A22B-Thinking-2507",
      "Qwen/Qwen3-Next-80B-A3B-Instruct",
      "deepseek-ai/DeepSeek-R1-0528",
      "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/Devstral-Small-2505",
      "mistralai/Magistral-Small-2506",
      "mistralai/Mistral-Large-Instruct-2411",
      "mistralai/Mistral-Nemo-Instruct-2407",
      "moonshotai/Kimi-K2-Instruct-0905",
      "moonshotai/Kimi-K2-Thinking",
      "openai/gpt-oss-120b",
      "openai/gpt-oss-20b",
      "zai-org/GLM-4.6"
    ],
    inception: ["mercury-2", "mercury-edit-2"],
    submodel: [
      "Qwen/Qwen3-235B-A22B-Instruct-2507",
      "Qwen/Qwen3-235B-A22B-Thinking-2507",
      "Qwen/Qwen3-Coder-480B-A35B-Instruct-FP8",
      "deepseek-ai/DeepSeek-R1-0528",
      "deepseek-ai/DeepSeek-V3-0324",
      "deepseek-ai/DeepSeek-V3.1",
      "openai/gpt-oss-120b",
      "zai-org/GLM-4.5-Air",
      "zai-org/GLM-4.5-FP8"
    ],
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      "anthropic/claude-3-7-sonnet",
      "anthropic/claude-haiku-4-5",
      "anthropic/claude-opus-4",
      "anthropic/claude-opus-4-1",
      "anthropic/claude-opus-4-5",
      "anthropic/claude-opus-4-6",
      "anthropic/claude-sonnet-4",
      "anthropic/claude-sonnet-4-5",
      "anthropic/claude-sonnet-4-6",
      "google/gemini-2.5-flash",
      "google/gemini-2.5-pro",
      "google/gemini-3-flash-preview",
      "google/gemini-3-pro-preview",
      "openai/gpt-4.1",
      "openai/gpt-4.1-mini",
      "openai/gpt-4o-mini",
      "openai/gpt-5",
      "openai/gpt-5-chat",
      "openai/gpt-5-codex",
      "openai/gpt-5-image",
      "openai/gpt-5-mini",
      "openai/gpt-5-nano",
      "openai/gpt-5-pro",
      "openai/gpt-5.1",
      "openai/gpt-5.1-chat",
      "openai/gpt-5.1-codex",
      "openai/gpt-5.1-codex-max",
      "openai/gpt-5.1-codex-mini",
      "openai/gpt-5.2",
      "openai/gpt-5.2-chat",
      "openai/gpt-5.2-codex",
      "openai/gpt-5.2-pro",
      "openai/gpt-5.3-codex",
      "openai/gpt-5.4",
      "openai/gpt-5.4-pro",
      "openai/o4-mini",
      "xai/grok-4",
      "xai/grok-4-fast"
    ],
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      "glm-4.5-air",
      "glm-4.5-flash",
      "glm-4.5v",
      "glm-4.6",
      "glm-4.6v",
      "glm-4.7",
      "glm-4.7-flash",
      "glm-4.7-flashx",
      "glm-5",
      "glm-5-turbo",
      "glm-5.1",
      "glm-5v-turbo"
    ],
    "zai-coding-plan": ["glm-4.5-air", "glm-4.7", "glm-5-turbo", "glm-5.1", "glm-5v-turbo"],
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      "MiniMaxAI/MiniMax-M2.1",
      "MiniMaxAI/MiniMax-M2.5",
      "Qwen/Qwen3-Coder-480B-A35B-Instruct",
      "Qwen/Qwen3-Coder-480B-A35B-Instruct-Turbo",
      "Qwen/Qwen3.5-35B-A3B",
      "Qwen/Qwen3.5-397B-A17B",
      "Qwen/Qwen3.6-35B-A3B",
      "anthropic/claude-3-7-sonnet-latest",
      "anthropic/claude-4-opus",
      "deepseek-ai/DeepSeek-R1-0528",
      "deepseek-ai/DeepSeek-V3.2",
      "deepseek-ai/DeepSeek-V4-Flash",
      "deepseek-ai/DeepSeek-V4-Pro",
      "google/gemma-4-26B-A4B-it",
      "google/gemma-4-31B-it",
      "meta-llama/Llama-3.1-70B-Instruct",
      "meta-llama/Llama-3.1-70B-Instruct-Turbo",
      "meta-llama/Llama-3.1-8B-Instruct",
      "meta-llama/Llama-3.1-8B-Instruct-Turbo",
      "meta-llama/Llama-3.3-70B-Instruct-Turbo",
      "meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8",
      "meta-llama/Llama-4-Scout-17B-16E-Instruct",
      "moonshotai/Kimi-K2-Instruct",
      "moonshotai/Kimi-K2-Instruct-0905",
      "moonshotai/Kimi-K2-Thinking",
      "moonshotai/Kimi-K2.5",
      "moonshotai/Kimi-K2.6",
      "openai/gpt-oss-120b",
      "openai/gpt-oss-20b",
      "xiaomi/mimo-v2.5",
      "xiaomi/mimo-v2.5-pro",
      "zai-org/GLM-4.6",
      "zai-org/GLM-4.6V",
      "zai-org/GLM-4.7",
      "zai-org/GLM-4.7-Flash",
      "zai-org/GLM-5",
      "zai-org/GLM-5.1"
    ],
    clarifai: [
      "arcee_ai/AFM/models/trinity-mini",
      "clarifai/main/models/mm-poly-8b",
      "deepseek-ai/deepseek-ocr/models/DeepSeek-OCR",
      "minimaxai/chat-completion/models/MiniMax-M2_5-high-throughput",
      "mistralai/completion/models/Ministral-3-14B-Reasoning-2512",
      "mistralai/completion/models/Ministral-3-3B-Reasoning-2512",
      "moonshotai/chat-completion/models/Kimi-K2_6",
      "openai/chat-completion/models/gpt-oss-120b-high-throughput",
      "openai/chat-completion/models/gpt-oss-20b",
      "qwen/qwenCoder/models/Qwen3-Coder-30B-A3B-Instruct",
      "qwen/qwenLM/models/Qwen3-30B-A3B-Instruct-2507",
      "qwen/qwenLM/models/Qwen3-30B-A3B-Thinking-2507"
    ],
    moark: ["GLM-4.7", "MiniMax-M2.1"],
    frogbot: [
      "claude-haiku-4-5",
      "claude-opus-4-6",
      "claude-opus-4-7",
      "claude-sonnet-4-6",
      "deepseek-v4-pro",
      "gemini-2.5-flash",
      "gemini-2.5-pro",
      "gemini-3-1-pro-preview",
      "gemini-3-flash-preview",
      "gpt-4o",
      "gpt-5-3-codex",
      "gpt-5-4-mini",
      "gpt-5-4-nano",
      "gpt-5-5",
      "gpt-oss-120b",
      "gpt-oss-20b",
      "grok-4-1-fast-non-reasoning",
      "grok-4-1-fast-reasoning",
      "grok-4-3",
      "grok-code-fast-1",
      "kimi-k2-6",
      "kimi-k2.5",
      "minimax-m2-5",
      "minimax-m2-7",
      "qwen-3-6-plus",
      "zai-glm-5-1"
    ],
    wandb: [
      "MiniMaxAI/MiniMax-M2.5",
      "OpenPipe/Qwen3-14B-Instruct",
      "Qwen/Qwen3-235B-A22B-Instruct-2507",
      "Qwen/Qwen3-235B-A22B-Thinking-2507",
      "Qwen/Qwen3-30B-A3B-Instruct-2507",
      "Qwen/Qwen3-Coder-480B-A35B-Instruct",
      "deepseek-ai/DeepSeek-V3.1",
      "meta-llama/Llama-3.1-70B-Instruct",
      "meta-llama/Llama-3.1-8B-Instruct",
      "meta-llama/Llama-3.3-70B-Instruct",
      "meta-llama/Llama-4-Scout-17B-16E-Instruct",
      "microsoft/Phi-4-mini-instruct",
      "moonshotai/Kimi-K2.5",
      "nvidia/NVIDIA-Nemotron-3-Super-120B-A12B-FP8",
      "openai/gpt-oss-120b",
      "openai/gpt-oss-20b",
      "zai-org/GLM-5-FP8",
      "zai-org/GLM-5.1"
    ],
    gmicloud: [
      "anthropic/claude-opus-4.6",
      "anthropic/claude-opus-4.7",
      "anthropic/claude-sonnet-4.6",
      "deepseek-ai/DeepSeek-V4-Flash",
      "deepseek-ai/DeepSeek-V4-Pro",
      "moonshotai/Kimi-K2.6",
      "zai-org/GLM-5-FP8",
      "zai-org/GLM-5.1-FP8"
    ],
    crof: [
      "deepseek-v3.2",
      "deepseek-v4-flash",
      "deepseek-v4-pro",
      "deepseek-v4-pro-precision",
      "gemma-4-31b-it",
      "glm-4.7",
      "glm-4.7-flash",
      "glm-5",
      "glm-5.1",
      "glm-5.1-precision",
      "greg",
      "kimi-k2.5",
      "kimi-k2.5-lightning",
      "kimi-k2.6",
      "kimi-k2.6-precision",
      "mimo-v2.5-pro",
      "mimo-v2.5-pro-precision",
      "minimax-m2.5",
      "qwen3.5-397b-a17b",
      "qwen3.5-9b",
      "qwen3.6-27b"
    ],
    ambient: ["moonshotai/kimi-k2.6", "zai-org/GLM-5.1-FP8"],
    "routing-run": [
      "route/deepseek-v3.2",
      "route/deepseek-v4-flash",
      "route/deepseek-v4-flash-6bit",
      "route/deepseek-v4-pro",
      "route/deepseek-v4-pro-6bit",
      "route/gemma-4-31b-it",
      "route/glm-5.1",
      "route/glm-5.1-6bit",
      "route/kimi-k2.5",
      "route/kimi-k2.6",
      "route/kimi-k2.6-6bit",
      "route/mimo-v2.5-pro",
      "route/mimo-v2.5-pro-6bit",
      "route/minimax-m2.5",
      "route/minimax-m2.5-highspeed",
      "route/minimax-m2.7",
      "route/minimax-m2.7-highspeed",
      "route/mistral-large-3",
      "route/mistral-medium-2505",
      "route/mistral-small-2503",
      "route/qwen3.6-27b",
      "route/step-3.5-flash",
      "route/step-3.5-flash-2603",
      "route/stepfun-3.5-flash"
    ],
    "the-grid-ai": [
      "agent-max",
      "agent-prime",
      "agent-standard",
      "code-max",
      "code-prime",
      "code-standard",
      "text-max",
      "text-prime",
      "text-standard"
    ],
    fastrouter: [
      "anthropic/claude-opus-4.1",
      "anthropic/claude-sonnet-4",
      "deepseek-ai/deepseek-r1-distill-llama-70b",
      "google/gemini-2.5-flash",
      "google/gemini-2.5-pro",
      "moonshotai/kimi-k2",
      "openai/gpt-4.1",
      "openai/gpt-5",
      "openai/gpt-5-mini",
      "openai/gpt-5-nano",
      "openai/gpt-oss-120b",
      "openai/gpt-oss-20b",
      "qwen/qwen3-coder",
      "x-ai/grok-4",
      "z-ai/glm-5"
    ],
    "tencent-coding-plan": [
      "glm-5",
      "hunyuan-2.0-instruct",
      "hunyuan-2.0-thinking",
      "hunyuan-t1",
      "hunyuan-turbos",
      "kimi-k2.5",
      "minimax-m2.5",
      "tc-code-latest"
    ],
    cortecs: [
      "claude-4-5-sonnet",
      "claude-4-6-sonnet",
      "claude-haiku-4-5",
      "claude-opus4-5",
      "claude-opus4-6",
      "claude-opus4-7",
      "claude-sonnet-4",
      "codestral-2508",
      "deepseek-r1-0528",
      "deepseek-v3-0324",
      "deepseek-v3.2",
      "deepseek-v4-flash",
      "deepseek-v4-pro",
      "devstral-2512",
      "devstral-small-2512",
      "gemini-2.5-pro",
      "glm-4.5",
      "glm-4.5-air",
      "glm-4.7",
      "glm-4.7-flash",
      "glm-5",
      "glm-5.1",
      "gpt-4.1",
      "gpt-oss-120b",
      "hermes-4-70b",
      "intellect-3",
      "kimi-k2-instruct",
      "kimi-k2-thinking",
      "kimi-k2.5",
      "kimi-k2.6",
      "llama-3.1-405b-instruct",
      "llama-3.3-70b-instruct",
      "minimax-m2",
      "minimax-m2.1",
      "minimax-m2.5",
      "minimax-m2.7",
      "mistral-large-2512",
      "mixtral-8x7B-instruct-v0.1",
      "nemotron-3-super-120b-a12b",
      "nova-pro-v1",
      "qwen-2.5-72b-instruct",
      "qwen3-235b-a22b-instruct-2507",
      "qwen3-32b",
      "qwen3-coder-30b-a3b-instruct",
      "qwen3-coder-480b-a35b-instruct",
      "qwen3-coder-next",
      "qwen3-next-80b-a3b-thinking",
      "qwen3.5-122b-a10b",
      "qwen3.5-397b-a17b"
    ],
    baseten: [
      "MiniMaxAI/MiniMax-M2.5",
      "deepseek-ai/DeepSeek-V3-0324",
      "deepseek-ai/DeepSeek-V3.1",
      "deepseek-ai/DeepSeek-V4-Pro",
      "moonshotai/Kimi-K2.5",
      "moonshotai/Kimi-K2.6",
      "nvidia/Nemotron-120B-A12B",
      "openai/gpt-oss-120b",
      "zai-org/GLM-4.6",
      "zai-org/GLM-4.7",
      "zai-org/GLM-5"
    ],
    llama: [
      "cerebras-llama-4-maverick-17b-128e-instruct",
      "cerebras-llama-4-scout-17b-16e-instruct",
      "groq-llama-4-maverick-17b-128e-instruct",
      "llama-3.3-70b-instruct",
      "llama-3.3-8b-instruct",
      "llama-4-maverick-17b-128e-instruct-fp8",
      "llama-4-scout-17b-16e-instruct-fp8"
    ],
    "novita-ai": [
      "baichuan/baichuan-m2-32b",
      "baidu/ernie-4.5-21B-a3b",
      "baidu/ernie-4.5-21B-a3b-thinking",
      "baidu/ernie-4.5-300b-a47b-paddle",
      "baidu/ernie-4.5-vl-28b-a3b",
      "baidu/ernie-4.5-vl-28b-a3b-thinking",
      "baidu/ernie-4.5-vl-424b-a47b",
      "deepseek/deepseek-ocr",
      "deepseek/deepseek-ocr-2",
      "deepseek/deepseek-prover-v2-671b",
      "deepseek/deepseek-r1-0528",
      "deepseek/deepseek-r1-0528-qwen3-8b",
      "deepseek/deepseek-r1-distill-llama-70b",
      "deepseek/deepseek-r1-distill-qwen-14b",
      "deepseek/deepseek-r1-distill-qwen-32b",
      "deepseek/deepseek-r1-turbo",
      "deepseek/deepseek-v3-0324",
      "deepseek/deepseek-v3-turbo",
      "deepseek/deepseek-v3.1",
      "deepseek/deepseek-v3.1-terminus",
      "deepseek/deepseek-v3.2",
      "deepseek/deepseek-v3.2-exp",
      "deepseek/deepseek-v4-flash",
      "deepseek/deepseek-v4-pro",
      "google/gemma-3-12b-it",
      "google/gemma-3-27b-it",
      "google/gemma-4-26b-a4b-it",
      "google/gemma-4-31b-it",
      "gryphe/mythomax-l2-13b",
      "inclusionai/ling-2.6-1t",
      "inclusionai/ling-2.6-flash",
      "kwaipilot/kat-coder-pro",
      "meta-llama/llama-3-70b-instruct",
      "meta-llama/llama-3-8b-instruct",
      "meta-llama/llama-3.1-8b-instruct",
      "meta-llama/llama-3.2-3b-instruct",
      "meta-llama/llama-3.3-70b-instruct",
      "meta-llama/llama-4-maverick-17b-128e-instruct-fp8",
      "meta-llama/llama-4-scout-17b-16e-instruct",
      "microsoft/wizardlm-2-8x22b",
      "minimax/minimax-m2",
      "minimax/minimax-m2.1",
      "minimax/minimax-m2.5",
      "minimax/minimax-m2.5-highspeed",
      "minimax/minimax-m2.7",
      "minimaxai/minimax-m1-80k",
      "mistralai/mistral-nemo",
      "moonshotai/kimi-k2-0905",
      "moonshotai/kimi-k2-instruct",
      "moonshotai/kimi-k2-thinking",
      "moonshotai/kimi-k2.5",
      "moonshotai/kimi-k2.6",
      "nousresearch/hermes-2-pro-llama-3-8b",
      "openai/gpt-oss-120b",
      "openai/gpt-oss-20b",
      "paddlepaddle/paddleocr-vl",
      "qwen/qwen-2.5-72b-instruct",
      "qwen/qwen-mt-plus",
      "qwen/qwen2.5-7b-instruct",
      "qwen/qwen2.5-vl-72b-instruct",
      "qwen/qwen3-235b-a22b-fp8",
      "qwen/qwen3-235b-a22b-instruct-2507",
      "qwen/qwen3-235b-a22b-thinking-2507",
      "qwen/qwen3-30b-a3b-fp8",
      "qwen/qwen3-32b-fp8",
      "qwen/qwen3-4b-fp8",
      "qwen/qwen3-8b-fp8",
      "qwen/qwen3-coder-30b-a3b-instruct",
      "qwen/qwen3-coder-480b-a35b-instruct",
      "qwen/qwen3-coder-next",
      "qwen/qwen3-max",
      "qwen/qwen3-next-80b-a3b-instruct",
      "qwen/qwen3-next-80b-a3b-thinking",
      "qwen/qwen3-omni-30b-a3b-instruct",
      "qwen/qwen3-omni-30b-a3b-thinking",
      "qwen/qwen3-vl-235b-a22b-instruct",
      "qwen/qwen3-vl-235b-a22b-thinking",
      "qwen/qwen3-vl-30b-a3b-instruct",
      "qwen/qwen3-vl-30b-a3b-thinking",
      "qwen/qwen3-vl-8b-instruct",
      "qwen/qwen3.5-122b-a10b",
      "qwen/qwen3.5-27b",
      "qwen/qwen3.5-35b-a3b",
      "qwen/qwen3.5-397b-a17b",
      "sao10K/L3-8B-stheno-v3.2",
      "sao10K/l3-70b-euryale-v2.1",
      "sao10K/l3-8b-lunaris",
      "sao10K/l31-70b-euryale-v2.2",
      "xiaomimimo/mimo-v2-flash",
      "zai-org/autoglm-phone-9b-multilingual",
      "zai-org/glm-4.5",
      "zai-org/glm-4.5-air",
      "zai-org/glm-4.5v",
      "zai-org/glm-4.6",
      "zai-org/glm-4.6v",
      "zai-org/glm-4.7",
      "zai-org/glm-4.7-flash",
      "zai-org/glm-5",
      "zai-org/glm-5.1"
    ],
    digitalocean: [
      "alibaba-qwen3-32b",
      "all-mini-lm-l6-v2",
      "anthropic-claude-4.1-opus",
      "anthropic-claude-4.5-haiku",
      "anthropic-claude-4.5-sonnet",
      "anthropic-claude-4.6-sonnet",
      "anthropic-claude-haiku-4.5",
      "anthropic-claude-opus-4",
      "anthropic-claude-opus-4.5",
      "anthropic-claude-opus-4.6",
      "anthropic-claude-opus-4.7",
      "anthropic-claude-sonnet-4",
      "arcee-trinity-large-thinking",
      "bge-m3",
      "bge-reranker-v2-m3",
      "deepseek-3.2",
      "deepseek-r1-distill-llama-70b",
      "deepseek-v3",
      "deepseek-v4-pro",
      "e5-large-v2",
      "fal-ai/elevenlabs/tts/multilingual-v2",
      "fal-ai/fast-sdxl",
      "fal-ai/flux/schnell",
      "fal-ai/stable-audio-25/text-to-audio",
      "gemma-4-31B-it",
      "glm-5",
      "gte-large-en-v1.5",
      "kimi-k2.5",
      "kimi-k2.6",
      "llama-4-maverick",
      "llama3-8b-instruct",
      "llama3.3-70b-instruct",
      "minimax-m2.5",
      "ministral-3-8b-instruct-2512",
      "mistral-3-14B",
      "mistral-7b-instruct-v0.3",
      "multi-qa-mpnet-base-dot-v1",
      "nemotron-3-nano-30b",
      "nemotron-3-nano-omni",
      "nemotron-nano-12b-v2-vl",
      "nvidia-nemotron-3-super-120b",
      "openai-gpt-4.1",
      "openai-gpt-4o",
      "openai-gpt-4o-mini",
      "openai-gpt-5",
      "openai-gpt-5-mini",
      "openai-gpt-5-nano",
      "openai-gpt-5.1-codex-max",
      "openai-gpt-5.2",
      "openai-gpt-5.2-pro",
      "openai-gpt-5.3-codex",
      "openai-gpt-5.4",
      "openai-gpt-5.4-mini",
      "openai-gpt-5.4-nano",
      "openai-gpt-5.4-pro",
      "openai-gpt-5.5",
      "openai-gpt-image-1",
      "openai-gpt-image-1.5",
      "openai-gpt-image-2",
      "openai-gpt-oss-120b",
      "openai-gpt-oss-20b",
      "openai-o1",
      "openai-o3",
      "openai-o3-mini",
      "qwen-2.5-14b-instruct",
      "qwen3-coder-flash",
      "qwen3-embedding-0.6b",
      "qwen3-tts-voicedesign",
      "qwen3.5-397b-a17b",
      "stable-diffusion-3.5-large",
      "wan2-2-t2v-a14b"
    ],
    moonshotai: [
      "kimi-k2-0711-preview",
      "kimi-k2-0905-preview",
      "kimi-k2-thinking",
      "kimi-k2-thinking-turbo",
      "kimi-k2-turbo-preview",
      "kimi-k2.5",
      "kimi-k2.6"
    ],
    mistral: [
      "codestral-latest",
      "devstral-2512",
      "devstral-medium-2507",
      "devstral-medium-latest",
      "devstral-small-2505",
      "devstral-small-2507",
      "labs-devstral-small-2512",
      "magistral-medium-latest",
      "magistral-small",
      "ministral-3b-latest",
      "ministral-8b-latest",
      "mistral-embed",
      "mistral-large-2411",
      "mistral-large-2512",
      "mistral-large-latest",
      "mistral-medium-2505",
      "mistral-medium-2508",
      "mistral-medium-2604",
      "mistral-medium-latest",
      "mistral-nemo",
      "mistral-small-2506",
      "mistral-small-2603",
      "mistral-small-latest",
      "open-mistral-7b",
      "open-mixtral-8x22b",
      "open-mixtral-8x7b",
      "pixtral-12b",
      "pixtral-large-latest"
    ],
    kilo: [
      "ai21/jamba-large-1.7",
      "aion-labs/aion-1.0",
      "aion-labs/aion-1.0-mini",
      "aion-labs/aion-2.0",
      "aion-labs/aion-rp-llama-3.1-8b",
      "alfredpros/codellama-7b-instruct-solidity",
      "alibaba/tongyi-deepresearch-30b-a3b",
      "allenai/olmo-3-32b-think",
      "amazon/nova-2-lite-v1",
      "amazon/nova-lite-v1",
      "amazon/nova-micro-v1",
      "amazon/nova-premier-v1",
      "amazon/nova-pro-v1",
      "anthracite-org/magnum-v4-72b",
      "anthropic/claude-3-haiku",
      "anthropic/claude-3.5-haiku",
      "anthropic/claude-haiku-4.5",
      "anthropic/claude-opus-4",
      "anthropic/claude-opus-4.1",
      "anthropic/claude-opus-4.5",
      "anthropic/claude-opus-4.6",
      "anthropic/claude-opus-4.6-fast",
      "anthropic/claude-opus-4.7",
      "anthropic/claude-opus-4.7-fast",
      "anthropic/claude-sonnet-4",
      "anthropic/claude-sonnet-4.5",
      "anthropic/claude-sonnet-4.6",
      "arcee-ai/coder-large",
      "arcee-ai/maestro-reasoning",
      "arcee-ai/spotlight",
      "arcee-ai/trinity-large-preview",
      "arcee-ai/trinity-large-thinking",
      "arcee-ai/trinity-mini",
      "arcee-ai/virtuoso-large",
      "baidu/cobuddy:free",
      "baidu/ernie-4.5-21b-a3b",
      "baidu/ernie-4.5-21b-a3b-thinking",
      "baidu/ernie-4.5-300b-a47b",
      "baidu/ernie-4.5-vl-28b-a3b",
      "baidu/ernie-4.5-vl-424b-a47b",
      "baidu/qianfan-ocr-fast",
      "bytedance-seed/seed-1.6",
      "bytedance-seed/seed-1.6-flash",
      "bytedance-seed/seed-2.0-lite",
      "bytedance-seed/seed-2.0-mini",
      "bytedance/ui-tars-1.5-7b",
      "cohere/command-a",
      "cohere/command-r-08-2024",
      "cohere/command-r-plus-08-2024",
      "cohere/command-r7b-12-2024",
      "deepcogito/cogito-v2.1-671b",
      "deepseek/deepseek-chat",
      "deepseek/deepseek-chat-v3-0324",
      "deepseek/deepseek-chat-v3.1",
      "deepseek/deepseek-r1",
      "deepseek/deepseek-r1-0528",
      "deepseek/deepseek-r1-distill-llama-70b",
      "deepseek/deepseek-r1-distill-qwen-32b",
      "deepseek/deepseek-v3.1-terminus",
      "deepseek/deepseek-v3.2",
      "deepseek/deepseek-v3.2-exp",
      "deepseek/deepseek-v3.2-speciale",
      "deepseek/deepseek-v4-flash",
      "deepseek/deepseek-v4-flash:free",
      "deepseek/deepseek-v4-pro",
      "essentialai/rnj-1-instruct",
      "google/gemini-2.0-flash-001",
      "google/gemini-2.0-flash-lite-001",
      "google/gemini-2.5-flash",
      "google/gemini-2.5-flash-image",
      "google/gemini-2.5-flash-lite",
      "google/gemini-2.5-flash-lite-preview-09-2025",
      "google/gemini-2.5-pro",
      "google/gemini-2.5-pro-preview",
      "google/gemini-2.5-pro-preview-05-06",
      "google/gemini-3-flash-preview",
      "google/gemini-3-pro-image-preview",
      "google/gemini-3.1-flash-image-preview",
      "google/gemini-3.1-flash-lite",
      "google/gemini-3.1-flash-lite-preview",
      "google/gemini-3.1-pro-preview",
      "google/gemini-3.1-pro-preview-customtools",
      "google/gemma-2-27b-it",
      "google/gemma-3-12b-it",
      "google/gemma-3-27b-it",
      "google/gemma-3-4b-it",
      "google/gemma-3n-e4b-it",
      "google/gemma-4-26b-a4b-it",
      "google/gemma-4-31b-it",
      "google/lyria-3-clip-preview",
      "google/lyria-3-pro-preview",
      "gryphe/mythomax-l2-13b",
      "ibm-granite/granite-4.0-h-micro",
      "ibm-granite/granite-4.1-8b",
      "inception/mercury-2",
      "inclusionai/ling-2.6-1t",
      "inclusionai/ling-2.6-flash",
      "inclusionai/ring-2.6-1t",
      "inflection/inflection-3-pi",
      "inflection/inflection-3-productivity",
      "kilo-auto/balanced",
      "kilo-auto/free",
      "kilo-auto/frontier",
      "kilo-auto/small",
      "kwaipilot/kat-coder-pro-v2",
      "liquid/lfm-2-24b-a2b",
      "mancer/weaver",
      "meta-llama/llama-3-70b-instruct",
      "meta-llama/llama-3-8b-instruct",
      "meta-llama/llama-3.1-70b-instruct",
      "meta-llama/llama-3.1-8b-instruct",
      "meta-llama/llama-3.2-11b-vision-instruct",
      "meta-llama/llama-3.2-1b-instruct",
      "meta-llama/llama-3.2-3b-instruct",
      "meta-llama/llama-3.3-70b-instruct",
      "meta-llama/llama-4-maverick",
      "meta-llama/llama-4-scout",
      "meta-llama/llama-guard-3-8b",
      "meta-llama/llama-guard-4-12b",
      "microsoft/phi-4",
      "microsoft/phi-4-mini-instruct",
      "microsoft/wizardlm-2-8x22b",
      "minimax/minimax-01",
      "minimax/minimax-m1",
      "minimax/minimax-m2",
      "minimax/minimax-m2-her",
      "minimax/minimax-m2.1",
      "minimax/minimax-m2.5",
      "minimax/minimax-m2.7",
      "mistralai/codestral-2508",
      "mistralai/devstral-2512",
      "mistralai/devstral-medium",
      "mistralai/devstral-small",
      "mistralai/ministral-14b-2512",
      "mistralai/ministral-3b-2512",
      "mistralai/ministral-8b-2512",
      "mistralai/mistral-7b-instruct-v0.1",
      "mistralai/mistral-large",
      "mistralai/mistral-large-2407",
      "mistralai/mistral-large-2411",
      "mistralai/mistral-large-2512",
      "mistralai/mistral-medium-3",
      "mistralai/mistral-medium-3-5",
      "mistralai/mistral-medium-3.1",
      "mistralai/mistral-nemo",
      "mistralai/mistral-saba",
      "mistralai/mistral-small-24b-instruct-2501",
      "mistralai/mistral-small-2603",
      "mistralai/mistral-small-3.1-24b-instruct",
      "mistralai/mistral-small-3.2-24b-instruct",
      "mistralai/mixtral-8x22b-instruct",
      "mistralai/pixtral-large-2411",
      "mistralai/voxtral-small-24b-2507",
      "moonshotai/kimi-k2",
      "moonshotai/kimi-k2-0905",
      "moonshotai/kimi-k2-thinking",
      "moonshotai/kimi-k2.5",
      "moonshotai/kimi-k2.6",
      "morph/morph-v3-fast",
      "morph/morph-v3-large",
      "nex-agi/deepseek-v3.1-nex-n1",
      "nousresearch/hermes-2-pro-llama-3-8b",
      "nousresearch/hermes-3-llama-3.1-405b",
      "nousresearch/hermes-3-llama-3.1-70b",
      "nousresearch/hermes-4-405b",
      "nousresearch/hermes-4-70b",
      "nvidia/llama-3.3-nemotron-super-49b-v1.5",
      "nvidia/nemotron-3-nano-30b-a3b",
      "nvidia/nemotron-3-nano-omni-30b-a3b-reasoning:free",
      "nvidia/nemotron-3-super-120b-a12b",
      "nvidia/nemotron-3-super-120b-a12b:free",
      "nvidia/nemotron-nano-9b-v2",
      "openai/gpt-3.5-turbo",
      "openai/gpt-3.5-turbo-0613",
      "openai/gpt-3.5-turbo-16k",
      "openai/gpt-3.5-turbo-instruct",
      "openai/gpt-4",
      "openai/gpt-4-0314",
      "openai/gpt-4-1106-preview",
      "openai/gpt-4-turbo",
      "openai/gpt-4-turbo-preview",
      "openai/gpt-4.1",
      "openai/gpt-4.1-mini",
      "openai/gpt-4.1-nano",
      "openai/gpt-4o",
      "openai/gpt-4o-2024-05-13",
      "openai/gpt-4o-2024-08-06",
      "openai/gpt-4o-2024-11-20",
      "openai/gpt-4o-audio-preview",
      "openai/gpt-4o-mini",
      "openai/gpt-4o-mini-2024-07-18",
      "openai/gpt-4o-mini-search-preview",
      "openai/gpt-4o-search-preview",
      "openai/gpt-5",
      "openai/gpt-5-chat",
      "openai/gpt-5-codex",
      "openai/gpt-5-image",
      "openai/gpt-5-image-mini",
      "openai/gpt-5-mini",
      "openai/gpt-5-nano",
      "openai/gpt-5-pro",
      "openai/gpt-5.1",
      "openai/gpt-5.1-chat",
      "openai/gpt-5.1-codex",
      "openai/gpt-5.1-codex-max",
      "openai/gpt-5.1-codex-mini",
      "openai/gpt-5.2",
      "openai/gpt-5.2-chat",
      "openai/gpt-5.2-codex",
      "openai/gpt-5.2-pro",
      "openai/gpt-5.3-chat",
      "openai/gpt-5.3-codex",
      "openai/gpt-5.4",
      "openai/gpt-5.4-image-2",
      "openai/gpt-5.4-mini",
      "openai/gpt-5.4-nano",
      "openai/gpt-5.4-pro",
      "openai/gpt-5.5",
      "openai/gpt-5.5-pro",
      "openai/gpt-audio",
      "openai/gpt-audio-mini",
      "openai/gpt-chat-latest",
      "openai/gpt-oss-120b",
      "openai/gpt-oss-20b",
      "openai/gpt-oss-safeguard-20b",
      "openai/o1",
      "openai/o1-pro",
      "openai/o3",
      "openai/o3-deep-research",
      "openai/o3-mini",
      "openai/o3-mini-high",
      "openai/o3-pro",
      "openai/o4-mini",
      "openai/o4-mini-deep-research",
      "openai/o4-mini-high",
      "openrouter/auto",
      "openrouter/bodybuilder",
      "openrouter/free",
      "openrouter/owl-alpha",
      "openrouter/pareto-code",
      "perceptron/perceptron-mk1",
      "perplexity/sonar",
      "perplexity/sonar-deep-research",
      "perplexity/sonar-pro",
      "perplexity/sonar-pro-search",
      "perplexity/sonar-reasoning-pro",
      "poolside/laguna-m.1:free",
      "poolside/laguna-xs.2:free",
      "prime-intellect/intellect-3",
      "qwen/qwen-2.5-72b-instruct",
      "qwen/qwen-2.5-7b-instruct",
      "qwen/qwen-2.5-coder-32b-instruct",
      "qwen/qwen-plus",
      "qwen/qwen-plus-2025-07-28",
      "qwen/qwen-plus-2025-07-28:thinking",
      "qwen/qwen2.5-vl-72b-instruct",
      "qwen/qwen3-14b",
      "qwen/qwen3-235b-a22b",
      "qwen/qwen3-235b-a22b-2507",
      "qwen/qwen3-235b-a22b-thinking-2507",
      "qwen/qwen3-30b-a3b",
      "qwen/qwen3-30b-a3b-instruct-2507",
      "qwen/qwen3-30b-a3b-thinking-2507",
      "qwen/qwen3-32b",
      "qwen/qwen3-8b",
      "qwen/qwen3-coder",
      "qwen/qwen3-coder-30b-a3b-instruct",
      "qwen/qwen3-coder-flash",
      "qwen/qwen3-coder-next",
      "qwen/qwen3-coder-plus",
      "qwen/qwen3-max",
      "qwen/qwen3-max-thinking",
      "qwen/qwen3-next-80b-a3b-instruct",
      "qwen/qwen3-next-80b-a3b-thinking",
      "qwen/qwen3-vl-235b-a22b-instruct",
      "qwen/qwen3-vl-235b-a22b-thinking",
      "qwen/qwen3-vl-30b-a3b-instruct",
      "qwen/qwen3-vl-30b-a3b-thinking",
      "qwen/qwen3-vl-32b-instruct",
      "qwen/qwen3-vl-8b-instruct",
      "qwen/qwen3-vl-8b-thinking",
      "qwen/qwen3.5-122b-a10b",
      "qwen/qwen3.5-27b",
      "qwen/qwen3.5-35b-a3b",
      "qwen/qwen3.5-397b-a17b",
      "qwen/qwen3.5-9b",
      "qwen/qwen3.5-flash-02-23",
      "qwen/qwen3.5-plus-02-15",
      "qwen/qwen3.5-plus-20260420",
      "qwen/qwen3.6-27b",
      "qwen/qwen3.6-35b-a3b",
      "qwen/qwen3.6-flash",
      "qwen/qwen3.6-max-preview",
      "qwen/qwen3.6-plus",
      "rekaai/reka-edge",
      "rekaai/reka-flash-3",
      "relace/relace-apply-3",
      "relace/relace-search",
      "sao10k/l3-euryale-70b",
      "sao10k/l3-lunaris-8b",
      "sao10k/l3.1-70b-hanami-x1",
      "sao10k/l3.1-euryale-70b",
      "sao10k/l3.3-euryale-70b",
      "stepfun/step-3.5-flash",
      "stepfun/step-3.5-flash:free",
      "switchpoint/router",
      "tencent/hunyuan-a13b-instruct",
      "tencent/hy3-preview",
      "thedrummer/cydonia-24b-v4.1",
      "thedrummer/rocinante-12b",
      "thedrummer/skyfall-36b-v2",
      "thedrummer/unslopnemo-12b",
      "undi95/remm-slerp-l2-13b",
      "upstage/solar-pro-3",
      "writer/palmyra-x5",
      "x-ai/grok-4.20",
      "x-ai/grok-4.20-multi-agent",
      "x-ai/grok-4.3",
      "x-ai/grok-code-fast-1:optimized:free",
      "xiaomi/mimo-v2-flash",
      "xiaomi/mimo-v2-omni",
      "xiaomi/mimo-v2-pro",
      "xiaomi/mimo-v2.5",
      "xiaomi/mimo-v2.5-pro",
      "z-ai/glm-4-32b",
      "z-ai/glm-4.5",
      "z-ai/glm-4.5-air",
      "z-ai/glm-4.5v",
      "z-ai/glm-4.6",
      "z-ai/glm-4.6v",
      "z-ai/glm-4.7",
      "z-ai/glm-4.7-flash",
      "z-ai/glm-5",
      "z-ai/glm-5-turbo",
      "z-ai/glm-5.1",
      "z-ai/glm-5v-turbo",
      "~anthropic/claude-haiku-latest",
      "~anthropic/claude-opus-latest",
      "~anthropic/claude-sonnet-latest",
      "~google/gemini-flash-latest",
      "~google/gemini-pro-latest",
      "~moonshotai/kimi-latest",
      "~openai/gpt-latest",
      "~openai/gpt-mini-latest"
    ],
    "cloudflare-workers-ai": [
      "@cf/aisingapore/gemma-sea-lion-v4-27b-it",
      "@cf/deepseek-ai/deepseek-r1-distill-qwen-32b",
      "@cf/google/gemma-3-12b-it",
      "@cf/google/gemma-4-26b-a4b-it",
      "@cf/ibm-granite/granite-4.0-h-micro",
      "@cf/meta/llama-2-7b-chat-fp16",
      "@cf/meta/llama-3-8b-instruct",
      "@cf/meta/llama-3-8b-instruct-awq",
      "@cf/meta/llama-3.1-8b-instruct-awq",
      "@cf/meta/llama-3.1-8b-instruct-fp8",
      "@cf/meta/llama-3.2-11b-vision-instruct",
      "@cf/meta/llama-3.2-1b-instruct",
      "@cf/meta/llama-3.2-3b-instruct",
      "@cf/meta/llama-3.3-70b-instruct-fp8-fast",
      "@cf/meta/llama-4-scout-17b-16e-instruct",
      "@cf/meta/llama-guard-3-8b",
      "@cf/mistral/mistral-7b-instruct-v0.1",
      "@cf/mistralai/mistral-small-3.1-24b-instruct",
      "@cf/moonshotai/kimi-k2.5",
      "@cf/moonshotai/kimi-k2.6",
      "@cf/nvidia/nemotron-3-120b-a12b",
      "@cf/openai/gpt-oss-120b",
      "@cf/openai/gpt-oss-20b",
      "@cf/qwen/qwen2.5-coder-32b-instruct",
      "@cf/qwen/qwen3-30b-a3b-fp8",
      "@cf/qwen/qwq-32b",
      "@cf/zai-org/glm-4.7-flash"
    ],
    lmstudio: ["openai/gpt-oss-20b", "qwen/qwen3-30b-a3b-2507", "qwen/qwen3-coder-30b"],
    "xiaomi-token-plan-cn": [
      "mimo-v2-flash",
      "mimo-v2-omni",
      "mimo-v2-pro",
      "mimo-v2-tts",
      "mimo-v2.5",
      "mimo-v2.5-pro"
    ],
    morph: ["auto", "morph-v3-fast", "morph-v3-large"],
    nearai: [
      "Qwen/Qwen3-30B-A3B-Instruct-2507",
      "Qwen/Qwen3-Embedding-0.6B",
      "Qwen/Qwen3-Reranker-0.6B",
      "Qwen/Qwen3-VL-30B-A3B-Instruct",
      "Qwen/Qwen3.5-122B-A10B",
      "anthropic/claude-haiku-4-5",
      "anthropic/claude-opus-4-6",
      "anthropic/claude-opus-4-7",
      "anthropic/claude-sonnet-4-5",
      "anthropic/claude-sonnet-4-6",
      "black-forest-labs/FLUX.2-klein-4B",
      "google/gemini-2.5-flash",
      "google/gemini-2.5-flash-lite",
      "google/gemini-2.5-pro",
      "google/gemini-3.1-flash-lite",
      "openai/gpt-4.1",
      "openai/gpt-4.1-mini",
      "openai/gpt-4.1-nano",
      "openai/gpt-5",
      "openai/gpt-5-mini",
      "openai/gpt-5-nano",
      "openai/gpt-5.1",
      "openai/gpt-5.2",
      "openai/gpt-5.4",
      "openai/gpt-5.4-mini",
      "openai/gpt-5.4-nano",
      "openai/gpt-5.5",
      "openai/gpt-oss-120b",
      "openai/o3",
      "openai/o3-mini",
      "openai/o4-mini",
      "openai/whisper-large-v3",
      "zai-org/GLM-5.1-FP8"
    ],
    abacus: [
      "Qwen/QwQ-32B",
      "Qwen/Qwen2.5-72B-Instruct",
      "Qwen/Qwen3-235B-A22B-Instruct-2507",
      "Qwen/Qwen3-32B",
      "Qwen/qwen3-coder-480b-a35b-instruct",
      "claude-3-7-sonnet-20250219",
      "claude-haiku-4-5-20251001",
      "claude-opus-4-1-20250805",
      "claude-opus-4-20250514",
      "claude-opus-4-5-20251101",
      "claude-opus-4-6",
      "claude-sonnet-4-20250514",
      "claude-sonnet-4-5-20250929",
      "claude-sonnet-4-6",
      "deepseek-ai/DeepSeek-R1",
      "deepseek-ai/DeepSeek-V3.1-Terminus",
      "deepseek-ai/DeepSeek-V3.2",
      "deepseek/deepseek-v3.1",
      "gemini-2.5-flash",
      "gemini-2.5-pro",
      "gemini-3-flash-preview",
      "gemini-3.1-flash-lite-preview",
      "gemini-3.1-pro-preview",
      "gpt-4.1",
      "gpt-4.1-mini",
      "gpt-4.1-nano",
      "gpt-4o-2024-11-20",
      "gpt-4o-mini",
      "gpt-5",
      "gpt-5-codex",
      "gpt-5-mini",
      "gpt-5-nano",
      "gpt-5.1",
      "gpt-5.1-chat-latest",
      "gpt-5.1-codex",
      "gpt-5.1-codex-max",
      "gpt-5.2",
      "gpt-5.2-chat-latest",
      "gpt-5.2-codex",
      "gpt-5.3-chat-latest",
      "gpt-5.3-codex",
      "gpt-5.3-codex-xhigh",
      "gpt-5.4",
      "grok-4-0709",
      "grok-4-1-fast-non-reasoning",
      "grok-4-fast-non-reasoning",
      "grok-code-fast-1",
      "kimi-k2-turbo-preview",
      "kimi-k2.5",
      "llama-3.3-70b-versatile",
      "meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8",
      "meta-llama/Meta-Llama-3.1-405B-Instruct-Turbo",
      "meta-llama/Meta-Llama-3.1-8B-Instruct",
      "o3",
      "o3-mini",
      "o3-pro",
      "o4-mini",
      "openai/gpt-oss-120b",
      "qwen-2.5-coder-32b",
      "qwen3-max",
      "route-llm",
      "zai-org/glm-4.5",
      "zai-org/glm-4.6",
      "zai-org/glm-4.7",
      "zai-org/glm-5"
    ],
    "privatemode-ai": ["gemma-3-27b", "gpt-oss-120b", "qwen3-coder-30b-a3b", "qwen3-embedding-4b", "whisper-large-v3"],
    "minimax-cn-coding-plan": [
      "MiniMax-M2",
      "MiniMax-M2.1",
      "MiniMax-M2.5",
      "MiniMax-M2.5-highspeed",
      "MiniMax-M2.7",
      "MiniMax-M2.7-highspeed"
    ],
    "xiaomi-token-plan-ams": [
      "mimo-v2-flash",
      "mimo-v2-omni",
      "mimo-v2-pro",
      "mimo-v2-tts",
      "mimo-v2.5",
      "mimo-v2.5-pro"
    ],
    "cloudferro-sherlock": [
      "MiniMaxAI/MiniMax-M2.5",
      "meta-llama/Llama-3.3-70B-Instruct",
      "openai/gpt-oss-120b",
      "speakleash/Bielik-11B-v2.6-Instruct",
      "speakleash/Bielik-11B-v3.0-Instruct"
    ],
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      "chatgpt-image-latest",
      "gpt-3.5-turbo",
      "gpt-4",
      "gpt-4-turbo",
      "gpt-4.1",
      "gpt-4.1-mini",
      "gpt-4.1-nano",
      "gpt-4o",
      "gpt-4o-2024-05-13",
      "gpt-4o-2024-08-06",
      "gpt-4o-2024-11-20",
      "gpt-4o-mini",
      "gpt-5",
      "gpt-5-chat-latest",
      "gpt-5-codex",
      "gpt-5-mini",
      "gpt-5-nano",
      "gpt-5-pro",
      "gpt-5.1",
      "gpt-5.1-chat-latest",
      "gpt-5.1-codex",
      "gpt-5.1-codex-max",
      "gpt-5.1-codex-mini",
      "gpt-5.2",
      "gpt-5.2-chat-latest",
      "gpt-5.2-codex",
      "gpt-5.2-pro",
      "gpt-5.3-chat-latest",
      "gpt-5.3-codex",
      "gpt-5.3-codex-spark",
      "gpt-5.4",
      "gpt-5.4-mini",
      "gpt-5.4-nano",
      "gpt-5.4-pro",
      "gpt-5.5",
      "gpt-5.5-pro",
      "gpt-image-1",
      "gpt-image-1-mini",
      "gpt-image-1.5",
      "o1",
      "o1-mini",
      "o1-preview",
      "o1-pro",
      "o3",
      "o3-deep-research",
      "o3-mini",
      "o3-pro",
      "o4-mini",
      "o4-mini-deep-research",
      "text-embedding-3-large",
      "text-embedding-3-small",
      "text-embedding-ada-002"
    ],
    dinference: ["glm-4.7", "glm-5", "glm-5.1", "gpt-oss-120b", "minimax-m2.5"],
    vivgrid: [
      "deepseek-v3.2",
      "deepseek-v4-pro",
      "gemini-3.1-flash-lite-preview",
      "gemini-3.1-pro-preview",
      "gpt-5-mini",
      "gpt-5.1-codex",
      "gpt-5.1-codex-max",
      "gpt-5.2-codex",
      "gpt-5.3-codex",
      "gpt-5.4",
      "gpt-5.4-mini",
      "gpt-5.4-nano",
      "gpt-5.5"
    ],
    cerebras: ["gpt-oss-120b", "llama3.1-8b", "qwen-3-235b-a22b-instruct-2507", "zai-glm-4.7"],
    vultr: ["DeepSeek-V3.2", "GLM-5-FP8", "Kimi-K2.5", "MiniMax-M2.5", "gpt-oss-120b"],
    "kuae-cloud-coding-plan": ["GLM-4.7"],
    modelscope: [
      "Qwen/Qwen3-235B-A22B-Instruct-2507",
      "Qwen/Qwen3-235B-A22B-Thinking-2507",
      "Qwen/Qwen3-30B-A3B-Instruct-2507",
      "Qwen/Qwen3-30B-A3B-Thinking-2507",
      "Qwen/Qwen3-Coder-30B-A3B-Instruct",
      "ZhipuAI/GLM-4.5",
      "ZhipuAI/GLM-4.6"
    ],
    "kimi-for-coding": ["k2p5", "k2p6", "kimi-k2-thinking"],
    lucidquery: ["lucidnova-rf1-100b", "lucidquery-nexus-coder"],
    neuralwatt: [
      "MiniMaxAI/MiniMax-M2.5",
      "Qwen/Qwen3.5-397B-A17B-FP8",
      "Qwen/Qwen3.6-35B-A3B",
      "glm-5-fast",
      "glm-5.1-fast",
      "kimi-k2.5-fast",
      "kimi-k2.6-fast",
      "mistralai/Devstral-Small-2-24B-Instruct-2512",
      "moonshotai/Kimi-K2.5",
      "moonshotai/Kimi-K2.6",
      "openai/gpt-oss-20b",
      "qwen3.5-397b-fast",
      "qwen3.6-35b-fast",
      "zai-org/GLM-5.1-FP8"
    ],
    jiekou: [
      "baidu/ernie-4.5-300b-a47b-paddle",
      "baidu/ernie-4.5-vl-424b-a47b",
      "claude-haiku-4-5-20251001",
      "claude-opus-4-1-20250805",
      "claude-opus-4-20250514",
      "claude-opus-4-5-20251101",
      "claude-opus-4-6",
      "claude-sonnet-4-20250514",
      "claude-sonnet-4-5-20250929",
      "deepseek/deepseek-r1-0528",
      "deepseek/deepseek-v3-0324",
      "deepseek/deepseek-v3.1",
      "gemini-2.5-flash",
      "gemini-2.5-flash-lite",
      "gemini-2.5-flash-lite-preview-06-17",
      "gemini-2.5-flash-lite-preview-09-2025",
      "gemini-2.5-flash-preview-05-20",
      "gemini-2.5-pro",
      "gemini-2.5-pro-preview-06-05",
      "gemini-3-flash-preview",
      "gemini-3-pro-preview",
      "gpt-5-chat-latest",
      "gpt-5-codex",
      "gpt-5-mini",
      "gpt-5-nano",
      "gpt-5-pro",
      "gpt-5.1",
      "gpt-5.1-codex",
      "gpt-5.1-codex-max",
      "gpt-5.1-codex-mini",
      "gpt-5.2",
      "gpt-5.2-codex",
      "gpt-5.2-pro",
      "grok-4-0709",
      "grok-4-1-fast-non-reasoning",
      "grok-4-1-fast-reasoning",
      "grok-4-fast-non-reasoning",
      "grok-4-fast-reasoning",
      "grok-code-fast-1",
      "minimax/minimax-m2.1",
      "minimaxai/minimax-m1-80k",
      "moonshotai/kimi-k2-0905",
      "moonshotai/kimi-k2-instruct",
      "moonshotai/kimi-k2.5",
      "o3",
      "o3-mini",
      "o4-mini",
      "qwen/qwen3-235b-a22b-fp8",
      "qwen/qwen3-235b-a22b-instruct-2507",
      "qwen/qwen3-235b-a22b-thinking-2507",
      "qwen/qwen3-30b-a3b-fp8",
      "qwen/qwen3-32b-fp8",
      "qwen/qwen3-coder-480b-a35b-instruct",
      "qwen/qwen3-coder-next",
      "qwen/qwen3-next-80b-a3b-instruct",
      "qwen/qwen3-next-80b-a3b-thinking",
      "xiaomimimo/mimo-v2-flash",
      "zai-org/glm-4.5",
      "zai-org/glm-4.5v",
      "zai-org/glm-4.7",
      "zai-org/glm-4.7-flash"
    ],
    ovhcloud: [
      "gpt-oss-120b",
      "gpt-oss-20b",
      "llama-3.1-8b-instruct",
      "meta-llama-3_3-70b-instruct",
      "mistral-7b-instruct-v0.3",
      "mistral-nemo-instruct-2407",
      "mistral-small-3.2-24b-instruct-2506",
      "qwen2.5-vl-72b-instruct",
      "qwen3-32b",
      "qwen3-coder-30b-a3b-instruct",
      "qwen3.5-9b"
    ],
    friendli: [
      "MiniMaxAI/MiniMax-M2.5",
      "Qwen/Qwen3-235B-A22B-Instruct-2507",
      "meta-llama/Llama-3.1-8B-Instruct",
      "meta-llama/Llama-3.3-70B-Instruct",
      "zai-org/GLM-5",
      "zai-org/GLM-5.1"
    ],
    openrouter: [
      "ai21/jamba-large-1.7",
      "aion-labs/aion-1.0",
      "aion-labs/aion-1.0-mini",
      "aion-labs/aion-2.0",
      "aion-labs/aion-rp-llama-3.1-8b",
      "alfredpros/codellama-7b-instruct-solidity",
      "alibaba/tongyi-deepresearch-30b-a3b",
      "allenai/olmo-3-32b-think",
      "amazon/nova-2-lite-v1",
      "amazon/nova-lite-v1",
      "amazon/nova-micro-v1",
      "amazon/nova-premier-v1",
      "amazon/nova-pro-v1",
      "anthracite-org/magnum-v4-72b",
      "anthropic/claude-3-haiku",
      "anthropic/claude-3.5-haiku",
      "anthropic/claude-haiku-4.5",
      "anthropic/claude-opus-4",
      "anthropic/claude-opus-4.1",
      "anthropic/claude-opus-4.5",
      "anthropic/claude-opus-4.6",
      "anthropic/claude-opus-4.6-fast",
      "anthropic/claude-opus-4.7",
      "anthropic/claude-opus-4.7-fast",
      "anthropic/claude-sonnet-4",
      "anthropic/claude-sonnet-4.5",
      "anthropic/claude-sonnet-4.6",
      "arcee-ai/coder-large",
      "arcee-ai/maestro-reasoning",
      "arcee-ai/spotlight",
      "arcee-ai/trinity-large-thinking",
      "arcee-ai/trinity-large-thinking:free",
      "arcee-ai/trinity-mini",
      "arcee-ai/virtuoso-large",
      "baidu/cobuddy:free",
      "baidu/ernie-4.5-21b-a3b",
      "baidu/ernie-4.5-21b-a3b-thinking",
      "baidu/ernie-4.5-300b-a47b",
      "baidu/ernie-4.5-vl-28b-a3b",
      "baidu/ernie-4.5-vl-424b-a47b",
      "baidu/qianfan-ocr-fast",
      "bytedance-seed/seed-1.6",
      "bytedance-seed/seed-1.6-flash",
      "bytedance-seed/seed-2.0-lite",
      "bytedance-seed/seed-2.0-mini",
      "bytedance/ui-tars-1.5-7b",
      "cognitivecomputations/dolphin-mistral-24b-venice-edition:free",
      "cohere/command-a",
      "cohere/command-r-08-2024",
      "cohere/command-r-plus-08-2024",
      "cohere/command-r7b-12-2024",
      "deepcogito/cogito-v2.1-671b",
      "deepseek/deepseek-chat",
      "deepseek/deepseek-chat-v3-0324",
      "deepseek/deepseek-chat-v3.1",
      "deepseek/deepseek-r1",
      "deepseek/deepseek-r1-0528",
      "deepseek/deepseek-r1-distill-llama-70b",
      "deepseek/deepseek-r1-distill-qwen-32b",
      "deepseek/deepseek-v3.1-terminus",
      "deepseek/deepseek-v3.2",
      "deepseek/deepseek-v3.2-exp",
      "deepseek/deepseek-v3.2-speciale",
      "deepseek/deepseek-v4-flash",
      "deepseek/deepseek-v4-flash:free",
      "deepseek/deepseek-v4-pro",
      "essentialai/rnj-1-instruct",
      "google/gemini-2.0-flash-001",
      "google/gemini-2.0-flash-lite-001",
      "google/gemini-2.5-flash",
      "google/gemini-2.5-flash-image",
      "google/gemini-2.5-flash-lite",
      "google/gemini-2.5-flash-lite-preview-09-2025",
      "google/gemini-2.5-pro",
      "google/gemini-2.5-pro-preview",
      "google/gemini-2.5-pro-preview-05-06",
      "google/gemini-3-flash-preview",
      "google/gemini-3-pro-image-preview",
      "google/gemini-3.1-flash-image-preview",
      "google/gemini-3.1-flash-lite",
      "google/gemini-3.1-flash-lite-preview",
      "google/gemini-3.1-pro-preview",
      "google/gemini-3.1-pro-preview-customtools",
      "google/gemini-3.5-flash",
      "google/gemma-2-27b-it",
      "google/gemma-3-12b-it",
      "google/gemma-3-27b-it",
      "google/gemma-3-4b-it",
      "google/gemma-3n-e4b-it",
      "google/gemma-4-26b-a4b-it",
      "google/gemma-4-26b-a4b-it:free",
      "google/gemma-4-31b-it",
      "google/gemma-4-31b-it:free",
      "google/lyria-3-clip-preview",
      "google/lyria-3-pro-preview",
      "gryphe/mythomax-l2-13b",
      "ibm-granite/granite-4.0-h-micro",
      "ibm-granite/granite-4.1-8b",
      "inception/mercury-2",
      "inclusionai/ling-2.6-1t",
      "inclusionai/ling-2.6-flash",
      "inclusionai/ring-2.6-1t",
      "inflection/inflection-3-pi",
      "inflection/inflection-3-productivity",
      "kwaipilot/kat-coder-pro-v2",
      "liquid/lfm-2-24b-a2b",
      "liquid/lfm-2.5-1.2b-instruct:free",
      "liquid/lfm-2.5-1.2b-thinking:free",
      "mancer/weaver",
      "meta-llama/llama-3-70b-instruct",
      "meta-llama/llama-3-8b-instruct",
      "meta-llama/llama-3.1-70b-instruct",
      "meta-llama/llama-3.1-8b-instruct",
      "meta-llama/llama-3.2-11b-vision-instruct",
      "meta-llama/llama-3.2-1b-instruct",
      "meta-llama/llama-3.2-3b-instruct",
      "meta-llama/llama-3.2-3b-instruct:free",
      "meta-llama/llama-3.3-70b-instruct",
      "meta-llama/llama-3.3-70b-instruct:free",
      "meta-llama/llama-4-maverick",
      "meta-llama/llama-4-scout",
      "meta-llama/llama-guard-3-8b",
      "meta-llama/llama-guard-4-12b",
      "microsoft/phi-4",
      "microsoft/phi-4-mini-instruct",
      "microsoft/wizardlm-2-8x22b",
      "minimax/minimax-01",
      "minimax/minimax-m1",
      "minimax/minimax-m2",
      "minimax/minimax-m2-her",
      "minimax/minimax-m2.1",
      "minimax/minimax-m2.5",
      "minimax/minimax-m2.5:free",
      "minimax/minimax-m2.7",
      "mistralai/codestral-2508",
      "mistralai/devstral-2512",
      "mistralai/devstral-medium",
      "mistralai/devstral-small",
      "mistralai/ministral-14b-2512",
      "mistralai/ministral-3b-2512",
      "mistralai/ministral-8b-2512",
      "mistralai/mistral-7b-instruct-v0.1",
      "mistralai/mistral-large",
      "mistralai/mistral-large-2407",
      "mistralai/mistral-large-2411",
      "mistralai/mistral-large-2512",
      "mistralai/mistral-medium-3",
      "mistralai/mistral-medium-3-5",
      "mistralai/mistral-medium-3.1",
      "mistralai/mistral-nemo",
      "mistralai/mistral-saba",
      "mistralai/mistral-small-24b-instruct-2501",
      "mistralai/mistral-small-2603",
      "mistralai/mistral-small-3.1-24b-instruct",
      "mistralai/mistral-small-3.2-24b-instruct",
      "mistralai/mixtral-8x22b-instruct",
      "mistralai/pixtral-large-2411",
      "mistralai/voxtral-small-24b-2507",
      "moonshotai/kimi-k2",
      "moonshotai/kimi-k2-0905",
      "moonshotai/kimi-k2-thinking",
      "moonshotai/kimi-k2.5",
      "moonshotai/kimi-k2.6",
      "morph/morph-v3-fast",
      "morph/morph-v3-large",
      "nex-agi/deepseek-v3.1-nex-n1",
      "nousresearch/hermes-2-pro-llama-3-8b",
      "nousresearch/hermes-3-llama-3.1-405b",
      "nousresearch/hermes-3-llama-3.1-405b:free",
      "nousresearch/hermes-3-llama-3.1-70b",
      "nousresearch/hermes-4-405b",
      "nousresearch/hermes-4-70b",
      "nvidia/llama-3.3-nemotron-super-49b-v1.5",
      "nvidia/nemotron-3-nano-30b-a3b",
      "nvidia/nemotron-3-nano-30b-a3b:free",
      "nvidia/nemotron-3-nano-omni-30b-a3b-reasoning:free",
      "nvidia/nemotron-3-super-120b-a12b",
      "nvidia/nemotron-3-super-120b-a12b:free",
      "nvidia/nemotron-nano-12b-v2-vl:free",
      "nvidia/nemotron-nano-9b-v2",
      "nvidia/nemotron-nano-9b-v2:free",
      "openai/gpt-3.5-turbo",
      "openai/gpt-3.5-turbo-0613",
      "openai/gpt-3.5-turbo-16k",
      "openai/gpt-3.5-turbo-instruct",
      "openai/gpt-4",
      "openai/gpt-4-0314",
      "openai/gpt-4-1106-preview",
      "openai/gpt-4-turbo",
      "openai/gpt-4-turbo-preview",
      "openai/gpt-4.1",
      "openai/gpt-4.1-mini",
      "openai/gpt-4.1-nano",
      "openai/gpt-4o",
      "openai/gpt-4o-2024-05-13",
      "openai/gpt-4o-2024-08-06",
      "openai/gpt-4o-2024-11-20",
      "openai/gpt-4o-audio-preview",
      "openai/gpt-4o-mini",
      "openai/gpt-4o-mini-2024-07-18",
      "openai/gpt-4o-mini-search-preview",
      "openai/gpt-4o-search-preview",
      "openai/gpt-5",
      "openai/gpt-5-chat",
      "openai/gpt-5-codex",
      "openai/gpt-5-image",
      "openai/gpt-5-image-mini",
      "openai/gpt-5-mini",
      "openai/gpt-5-nano",
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      "qwen3.5-122b",
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      "qwen-coder-plus",
      "qwen-flash",
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      "qwen-omni-turbo",
      "qwen-plus",
      "qwen-plus-latest",
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      "qwen-vl-max",
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      "qwen25-coder-7b",
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      "qwen3-next-80b-a3b-instruct",
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      "seed-1-6-250615",
      "seed-1-6-250915",
      "seed-1-6-flash-250715",
      "seed-1-8-251228",
      "sonar",
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      "sonar-reasoning-pro"
    ],
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      "anthropic/claude-haiku-3.5",
      "anthropic/claude-haiku-4.5",
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      "anthropic/claude-opus-4.7",
      "anthropic/claude-sonnet-3.7",
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      "anthropic/claude-sonnet-4.5",
      "anthropic/claude-sonnet-4.6",
      "cerebras/gpt-oss-120b-cs",
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      "elevenlabs/elevenlabs-music",
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      "empiriolabs/deepseek-v4-pro-el",
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      "google/imagen-3",
      "google/imagen-3-fast",
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      "google/veo-3.1-fast",
      "ideogramai/ideogram",
      "ideogramai/ideogram-v2",
      "ideogramai/ideogram-v2a",
      "ideogramai/ideogram-v2a-turbo",
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      "novita/minimax-m2.1",
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      "openai/gpt-5.4-pro",
      "openai/gpt-5.5",
      "openai/gpt-5.5-pro",
      "openai/gpt-image-1",
      "openai/gpt-image-1-mini",
      "openai/gpt-image-1.5",
      "openai/gpt-image-2",
      "openai/o1",
      "openai/o1-pro",
      "openai/o3",
      "openai/o3-deep-research",
      "openai/o3-mini",
      "openai/o3-mini-high",
      "openai/o3-pro",
      "openai/o4-mini",
      "openai/o4-mini-deep-research",
      "openai/sora-2",
      "openai/sora-2-pro",
      "poetools/claude-code",
      "runwayml/runway",
      "runwayml/runway-gen-4-turbo",
      "stabilityai/stablediffusionxl",
      "topazlabs-co/topazlabs",
      "trytako/tako",
      "xai/grok-3",
      "xai/grok-3-mini",
      "xai/grok-4",
      "xai/grok-4-fast-non-reasoning",
      "xai/grok-4-fast-reasoning",
      "xai/grok-4.1-fast-non-reasoning",
      "xai/grok-4.1-fast-reasoning",
      "xai/grok-4.20-multi-agent",
      "xai/grok-code-fast-1"
    ],
    minimax: [
      "MiniMax-M2",
      "MiniMax-M2.1",
      "MiniMax-M2.5",
      "MiniMax-M2.5-highspeed",
      "MiniMax-M2.7",
      "MiniMax-M2.7-highspeed"
    ],
    groq: [
      "allam-2-7b",
      "canopylabs/orpheus-arabic-saudi",
      "canopylabs/orpheus-v1-english",
      "groq/compound",
      "groq/compound-mini",
      "llama-3.1-8b-instant",
      "llama-3.3-70b-versatile",
      "meta-llama/llama-4-scout-17b-16e-instruct",
      "meta-llama/llama-prompt-guard-2-22m",
      "meta-llama/llama-prompt-guard-2-86m",
      "moonshotai/kimi-k2-instruct-0905",
      "openai/gpt-oss-120b",
      "openai/gpt-oss-20b",
      "openai/gpt-oss-safeguard-20b",
      "qwen/qwen3-32b",
      "whisper-large-v3",
      "whisper-large-v3-turbo"
    ],
    "xiaomi-token-plan-sgp": [
      "mimo-v2-flash",
      "mimo-v2-omni",
      "mimo-v2-pro",
      "mimo-v2-tts",
      "mimo-v2.5",
      "mimo-v2.5-pro"
    ],
    siliconflow: [
      "ByteDance-Seed/Seed-OSS-36B-Instruct",
      "MiniMaxAI/MiniMax-M2.1",
      "MiniMaxAI/MiniMax-M2.5",
      "Qwen/QwQ-32B",
      "Qwen/Qwen2.5-14B-Instruct",
      "Qwen/Qwen2.5-32B-Instruct",
      "Qwen/Qwen2.5-72B-Instruct",
      "Qwen/Qwen2.5-72B-Instruct-128K",
      "Qwen/Qwen2.5-7B-Instruct",
      "Qwen/Qwen2.5-Coder-32B-Instruct",
      "Qwen/Qwen2.5-VL-32B-Instruct",
      "Qwen/Qwen2.5-VL-72B-Instruct",
      "Qwen/Qwen2.5-VL-7B-Instruct",
      "Qwen/Qwen3-14B",
      "Qwen/Qwen3-235B-A22B",
      "Qwen/Qwen3-235B-A22B-Instruct-2507",
      "Qwen/Qwen3-235B-A22B-Thinking-2507",
      "Qwen/Qwen3-30B-A3B-Instruct-2507",
      "Qwen/Qwen3-30B-A3B-Thinking-2507",
      "Qwen/Qwen3-32B",
      "Qwen/Qwen3-8B",
      "Qwen/Qwen3-Coder-30B-A3B-Instruct",
      "Qwen/Qwen3-Coder-480B-A35B-Instruct",
      "Qwen/Qwen3-Next-80B-A3B-Instruct",
      "Qwen/Qwen3-Next-80B-A3B-Thinking",
      "Qwen/Qwen3-Omni-30B-A3B-Captioner",
      "Qwen/Qwen3-Omni-30B-A3B-Instruct",
      "Qwen/Qwen3-Omni-30B-A3B-Thinking",
      "Qwen/Qwen3-VL-235B-A22B-Instruct",
      "Qwen/Qwen3-VL-235B-A22B-Thinking",
      "Qwen/Qwen3-VL-30B-A3B-Instruct",
      "Qwen/Qwen3-VL-30B-A3B-Thinking",
      "Qwen/Qwen3-VL-32B-Instruct",
      "Qwen/Qwen3-VL-32B-Thinking",
      "Qwen/Qwen3-VL-8B-Instruct",
      "Qwen/Qwen3-VL-8B-Thinking",
      "THUDM/GLM-4-32B-0414",
      "THUDM/GLM-4-9B-0414",
      "THUDM/GLM-Z1-32B-0414",
      "THUDM/GLM-Z1-9B-0414",
      "baidu/ERNIE-4.5-300B-A47B",
      "deepseek-ai/DeepSeek-R1",
      "deepseek-ai/DeepSeek-R1-Distill-Qwen-14B",
      "deepseek-ai/DeepSeek-R1-Distill-Qwen-32B",
      "deepseek-ai/DeepSeek-V3",
      "deepseek-ai/DeepSeek-V3.1",
      "deepseek-ai/DeepSeek-V3.1-Terminus",
      "deepseek-ai/DeepSeek-V3.2",
      "deepseek-ai/DeepSeek-V3.2-Exp",
      "deepseek-ai/deepseek-v4-flash",
      "deepseek-ai/deepseek-v4-pro",
      "deepseek-ai/deepseek-vl2",
      "inclusionAI/Ling-flash-2.0",
      "inclusionAI/Ling-mini-2.0",
      "inclusionAI/Ring-flash-2.0",
      "meta-llama/Meta-Llama-3.1-8B-Instruct",
      "moonshotai/Kimi-K2-Instruct",
      "moonshotai/Kimi-K2-Instruct-0905",
      "moonshotai/Kimi-K2-Thinking",
      "moonshotai/Kimi-K2.5",
      "moonshotai/Kimi-K2.6",
      "nex-agi/DeepSeek-V3.1-Nex-N1",
      "openai/gpt-oss-120b",
      "openai/gpt-oss-20b",
      "stepfun-ai/Step-3.5-Flash",
      "tencent/Hunyuan-A13B-Instruct",
      "tencent/Hunyuan-MT-7B",
      "zai-org/GLM-4.5",
      "zai-org/GLM-4.5-Air",
      "zai-org/GLM-4.5V",
      "zai-org/GLM-4.6",
      "zai-org/GLM-4.6V",
      "zai-org/GLM-4.7",
      "zai-org/GLM-5",
      "zai-org/GLM-5.1",
      "zai-org/GLM-5V-Turbo"
    ],
    "ollama-cloud": [
      "cogito-2.1:671b",
      "deepseek-v3.1:671b",
      "deepseek-v3.2",
      "deepseek-v4-flash",
      "deepseek-v4-pro",
      "devstral-2:123b",
      "devstral-small-2:24b",
      "gemini-3-flash-preview",
      "gemma3:12b",
      "gemma3:27b",
      "gemma3:4b",
      "gemma4:31b",
      "glm-4.6",
      "glm-4.7",
      "glm-5",
      "glm-5.1",
      "gpt-oss:120b",
      "gpt-oss:20b",
      "kimi-k2-thinking",
      "kimi-k2.5",
      "kimi-k2.6",
      "kimi-k2:1t",
      "minimax-m2",
      "minimax-m2.1",
      "minimax-m2.5",
      "minimax-m2.7",
      "ministral-3:14b",
      "ministral-3:3b",
      "ministral-3:8b",
      "mistral-large-3:675b",
      "nemotron-3-nano:30b",
      "nemotron-3-super",
      "qwen3-coder-next",
      "qwen3-coder:480b",
      "qwen3-next:80b",
      "qwen3-vl:235b",
      "qwen3-vl:235b-instruct",
      "qwen3.5:397b",
      "rnj-1:8b"
    ],
    databricks: [
      "databricks-claude-haiku-4-5",
      "databricks-claude-opus-4-1",
      "databricks-claude-opus-4-5",
      "databricks-claude-opus-4-6",
      "databricks-claude-opus-4-7",
      "databricks-claude-sonnet-4",
      "databricks-claude-sonnet-4-5",
      "databricks-claude-sonnet-4-6",
      "databricks-gemini-2-5-flash",
      "databricks-gemini-2-5-pro",
      "databricks-gemini-3-1-flash-lite",
      "databricks-gemini-3-1-pro",
      "databricks-gemini-3-flash",
      "databricks-gemini-3-pro",
      "databricks-gpt-5",
      "databricks-gpt-5-1",
      "databricks-gpt-5-2",
      "databricks-gpt-5-4",
      "databricks-gpt-5-4-mini",
      "databricks-gpt-5-4-nano",
      "databricks-gpt-5-5",
      "databricks-gpt-5-mini",
      "databricks-gpt-5-nano",
      "databricks-gpt-oss-120b",
      "databricks-gpt-oss-20b"
    ],
    berget: [
      "google/gemma-4-31B-it",
      "meta-llama/Llama-3.3-70B-Instruct",
      "mistralai/Mistral-Medium-3.5-128B",
      "mistralai/Mistral-Small-3.2-24B-Instruct-2506",
      "moonshotai/Kimi-K2.6",
      "openai/gpt-oss-120b",
      "zai-org/GLM-4.7"
    ],
    "moonshotai-cn": [
      "kimi-k2-0711-preview",
      "kimi-k2-0905-preview",
      "kimi-k2-thinking",
      "kimi-k2-thinking-turbo",
      "kimi-k2-turbo-preview",
      "kimi-k2.5",
      "kimi-k2.6"
    ],
    "alibaba-coding-plan-cn": [
      "MiniMax-M2.5",
      "glm-4.7",
      "glm-5",
      "kimi-k2.5",
      "qwen3-coder-next",
      "qwen3-coder-plus",
      "qwen3-max-2026-01-23",
      "qwen3.5-plus",
      "qwen3.6-plus"
    ],
    "minimax-cn": [
      "MiniMax-M2",
      "MiniMax-M2.1",
      "MiniMax-M2.5",
      "MiniMax-M2.5-highspeed",
      "MiniMax-M2.7",
      "MiniMax-M2.7-highspeed"
    ],
    chutes: [
      "MiniMaxAI/MiniMax-M2.5-TEE",
      "NousResearch/DeepHermes-3-Mistral-24B-Preview",
      "NousResearch/Hermes-4-14B",
      "Qwen/Qwen2.5-72B-Instruct",
      "Qwen/Qwen2.5-Coder-32B-Instruct",
      "Qwen/Qwen2.5-VL-32B-Instruct",
      "Qwen/Qwen3-235B-A22B-Instruct-2507-TEE",
      "Qwen/Qwen3-235B-A22B-Thinking-2507",
      "Qwen/Qwen3-30B-A3B",
      "Qwen/Qwen3-32B-TEE",
      "Qwen/Qwen3-Coder-Next-TEE",
      "Qwen/Qwen3-Next-80B-A3B-Instruct",
      "Qwen/Qwen3.5-397B-A17B-TEE",
      "Qwen/Qwen3.6-27B-TEE",
      "Qwen/Qwen3Guard-Gen-0.6B",
      "XiaomiMiMo/MiMo-V2-Flash-TEE",
      "deepseek-ai/DeepSeek-R1-0528-TEE",
      "deepseek-ai/DeepSeek-R1-Distill-Llama-70B",
      "deepseek-ai/DeepSeek-V3-0324-TEE",
      "deepseek-ai/DeepSeek-V3.1-TEE",
      "deepseek-ai/DeepSeek-V3.2-TEE",
      "google/gemma-4-31B-turbo-TEE",
      "moonshotai/Kimi-K2.5-TEE",
      "moonshotai/Kimi-K2.6-TEE",
      "openai/gpt-oss-120b-TEE",
      "rednote-hilab/dots.ocr",
      "tngtech/DeepSeek-TNG-R1T2-Chimera-TEE",
      "unsloth/Llama-3.2-1B-Instruct",
      "unsloth/Llama-3.2-3B-Instruct",
      "unsloth/Mistral-Nemo-Instruct-2407",
      "unsloth/gemma-3-12b-it",
      "unsloth/gemma-3-27b-it",
      "unsloth/gemma-3-4b-it",
      "zai-org/GLM-4.6V",
      "zai-org/GLM-4.7-FP8",
      "zai-org/GLM-4.7-TEE",
      "zai-org/GLM-5-TEE",
      "zai-org/GLM-5-Turbo",
      "zai-org/GLM-5.1-TEE"
    ],
    "siliconflow-cn": [
      "ByteDance-Seed/Seed-OSS-36B-Instruct",
      "Kwaipilot/KAT-Dev",
      "PaddlePaddle/PaddleOCR-VL",
      "PaddlePaddle/PaddleOCR-VL-1.5",
      "Pro/MiniMaxAI/MiniMax-M2.1",
      "Pro/MiniMaxAI/MiniMax-M2.5",
      "Pro/deepseek-ai/DeepSeek-R1",
      "Pro/deepseek-ai/DeepSeek-V3",
      "Pro/deepseek-ai/DeepSeek-V3.1-Terminus",
      "Pro/deepseek-ai/DeepSeek-V3.2",
      "Pro/moonshotai/Kimi-K2-Instruct-0905",
      "Pro/moonshotai/Kimi-K2-Thinking",
      "Pro/moonshotai/Kimi-K2.5",
      "Pro/moonshotai/Kimi-K2.6",
      "Pro/zai-org/GLM-4.7",
      "Pro/zai-org/GLM-5",
      "Pro/zai-org/GLM-5.1",
      "Qwen/QwQ-32B",
      "Qwen/Qwen2.5-14B-Instruct",
      "Qwen/Qwen2.5-32B-Instruct",
      "Qwen/Qwen2.5-72B-Instruct",
      "Qwen/Qwen2.5-72B-Instruct-128K",
      "Qwen/Qwen2.5-7B-Instruct",
      "Qwen/Qwen2.5-Coder-32B-Instruct",
      "Qwen/Qwen2.5-VL-32B-Instruct",
      "Qwen/Qwen2.5-VL-72B-Instruct",
      "Qwen/Qwen3-14B",
      "Qwen/Qwen3-235B-A22B-Instruct-2507",
      "Qwen/Qwen3-235B-A22B-Thinking-2507",
      "Qwen/Qwen3-30B-A3B-Instruct-2507",
      "Qwen/Qwen3-30B-A3B-Thinking-2507",
      "Qwen/Qwen3-32B",
      "Qwen/Qwen3-8B",
      "Qwen/Qwen3-Coder-30B-A3B-Instruct",
      "Qwen/Qwen3-Coder-480B-A35B-Instruct",
      "Qwen/Qwen3-Next-80B-A3B-Instruct",
      "Qwen/Qwen3-Next-80B-A3B-Thinking",
      "Qwen/Qwen3-Omni-30B-A3B-Captioner",
      "Qwen/Qwen3-Omni-30B-A3B-Instruct",
      "Qwen/Qwen3-Omni-30B-A3B-Thinking",
      "Qwen/Qwen3-VL-235B-A22B-Instruct",
      "Qwen/Qwen3-VL-235B-A22B-Thinking",
      "Qwen/Qwen3-VL-30B-A3B-Instruct",
      "Qwen/Qwen3-VL-30B-A3B-Thinking",
      "Qwen/Qwen3-VL-32B-Instruct",
      "Qwen/Qwen3-VL-32B-Thinking",
      "Qwen/Qwen3-VL-8B-Instruct",
      "Qwen/Qwen3-VL-8B-Thinking",
      "Qwen/Qwen3.5-122B-A10B",
      "Qwen/Qwen3.5-27B",
      "Qwen/Qwen3.5-35B-A3B",
      "Qwen/Qwen3.5-397B-A17B",
      "Qwen/Qwen3.5-4B",
      "Qwen/Qwen3.5-9B",
      "Qwen/Qwen3.6-35B-A3B",
      "THUDM/GLM-4-32B-0414",
      "THUDM/GLM-4-9B-0414",
      "THUDM/GLM-Z1-32B-0414",
      "THUDM/GLM-Z1-9B-0414",
      "ascend-tribe/pangu-pro-moe",
      "baidu/ERNIE-4.5-300B-A47B",
      "deepseek-ai/DeepSeek-OCR",
      "deepseek-ai/DeepSeek-R1",
      "deepseek-ai/DeepSeek-R1-Distill-Qwen-14B",
      "deepseek-ai/DeepSeek-R1-Distill-Qwen-32B",
      "deepseek-ai/DeepSeek-V3",
      "deepseek-ai/DeepSeek-V3.1-Terminus",
      "deepseek-ai/DeepSeek-V3.2",
      "deepseek-ai/deepseek-vl2",
      "inclusionAI/Ling-flash-2.0",
      "inclusionAI/Ling-mini-2.0",
      "inclusionAI/Ring-flash-2.0",
      "moonshotai/Kimi-K2-Instruct-0905",
      "moonshotai/Kimi-K2-Thinking",
      "stepfun-ai/Step-3.5-Flash",
      "tencent/Hunyuan-A13B-Instruct",
      "tencent/Hunyuan-MT-7B",
      "zai-org/GLM-4.5-Air",
      "zai-org/GLM-4.5V",
      "zai-org/GLM-4.6",
      "zai-org/GLM-4.6V"
    ],
    nvidia: [
      "abacusai/dracarys-llama-3_1-70b-instruct",
      "baai/bge-m3",
      "black-forest-labs/flux.1-dev",
      "black-forest-labs/flux_1-kontext-dev",
      "black-forest-labs/flux_1-schnell",
      "black-forest-labs/flux_2-klein-4b",
      "bytedance/seed-oss-36b-instruct",
      "deepseek-ai/deepseek-v3.1-terminus",
      "deepseek-ai/deepseek-v3.2",
      "deepseek-ai/deepseek-v4-flash",
      "deepseek-ai/deepseek-v4-pro",
      "google/gemma-2-2b-it",
      "google/gemma-3-27b-it",
      "google/gemma-3n-e2b-it",
      "google/gemma-3n-e4b-it",
      "google/gemma-4-31b-it",
      "google/google-paligemma",
      "meta/esm2-650m",
      "meta/esmfold",
      "meta/llama-3.1-70b-instruct",
      "meta/llama-3.1-8b-instruct",
      "meta/llama-3.2-11b-vision-instruct",
      "meta/llama-3.2-1b-instruct",
      "meta/llama-3.2-3b-instruct",
      "meta/llama-3.2-90b-vision-instruct",
      "meta/llama-3.3-70b-instruct",
      "meta/llama-4-maverick-17b-128e-instruct",
      "meta/llama-guard-4-12b",
      "microsoft/phi-4-mini-instruct",
      "microsoft/phi-4-multimodal-instruct",
      "minimaxai/minimax-m2.5",
      "minimaxai/minimax-m2.7",
      "mistralai/devstral-2-123b-instruct-2512",
      "mistralai/magistral-small-2506",
      "mistralai/mistral-7b-instruct-v03",
      "mistralai/mistral-large-3-675b-instruct-2512",
      "mistralai/mistral-medium-3-instruct",
      "mistralai/mistral-nemotron",
      "mistralai/mistral-small-4-119b-2603",
      "mistralai/mixtral-8x22b-instruct",
      "mistralai/mixtral-8x7b-instruct",
      "moonshotai/kimi-k2-instruct",
      "moonshotai/kimi-k2-instruct-0905",
      "moonshotai/kimi-k2-thinking",
      "moonshotai/kimi-k2.6",
      "nvidia/active-speaker-detection",
      "nvidia/bevformer",
      "nvidia/cosmos-predict1-5b",
      "nvidia/cosmos-transfer1-7b",
      "nvidia/cosmos-transfer2_5-2b",
      "nvidia/gliner-pii",
      "nvidia/llama-3_1-nemotron-safety-guard-8b-v3",
      "nvidia/llama-3_2-nemoretriever-300m-embed-v1",
      "nvidia/llama-3_3-nemotron-super-49b-v1",
      "nvidia/llama-3_3-nemotron-super-49b-v1_5",
      "nvidia/llama-nemotron-embed-vl-1b-v2",
      "nvidia/llama-nemotron-rerank-vl-1b-v2",
      "nvidia/magpie-tts-zeroshot",
      "nvidia/nemotron-3-content-safety",
      "nvidia/nemotron-3-nano-30b-a3b",
      "nvidia/nemotron-3-nano-omni-30b-a3b-reasoning",
      "nvidia/nemotron-3-super-120b-a12b",
      "nvidia/nemotron-content-safety-reasoning-4b",
      "nvidia/nemotron-mini-4b-instruct",
      "nvidia/nemotron-voicechat",
      "nvidia/nv-embed-v1",
      "nvidia/nv-embedcode-7b-v1",
      "nvidia/nvidia-nemotron-nano-9b-v2",
      "nvidia/rerank-qa-mistral-4b",
      "nvidia/riva-translate-4b-instruct-v1_1",
      "nvidia/sparsedrive",
      "nvidia/streampetr",
      "nvidia/studiovoice",
      "nvidia/synthetic-video-detector",
      "nvidia/usdcode",
      "nvidia/usdvalidate",
      "openai/gpt-oss-120b",
      "openai/gpt-oss-20b",
      "openai/whisper-large-v3",
      "qwen/qwen-image",
      "qwen/qwen-image-edit",
      "qwen/qwen2.5-coder-32b-instruct",
      "qwen/qwen3-coder-480b-a35b-instruct",
      "qwen/qwen3-next-80b-a3b-instruct",
      "qwen/qwen3-next-80b-a3b-thinking",
      "qwen/qwen3.5-122b-a10b",
      "qwen/qwen3.5-397b-a17b",
      "sarvamai/sarvam-m",
      "stepfun-ai/step-3.5-flash",
      "upstage/solar-10_7b-instruct",
      "z-ai/glm-5.1",
      "z-ai/glm4.7"
    ],
    anthropic: [
      "claude-3-5-haiku-20241022",
      "claude-3-5-haiku-latest",
      "claude-3-5-sonnet-20240620",
      "claude-3-5-sonnet-20241022",
      "claude-3-7-sonnet-20250219",
      "claude-3-haiku-20240307",
      "claude-3-opus-20240229",
      "claude-3-sonnet-20240229",
      "claude-haiku-4-5",
      "claude-haiku-4-5-20251001",
      "claude-opus-4-0",
      "claude-opus-4-1",
      "claude-opus-4-1-20250805",
      "claude-opus-4-20250514",
      "claude-opus-4-5",
      "claude-opus-4-5-20251101",
      "claude-opus-4-6",
      "claude-opus-4-7",
      "claude-sonnet-4-0",
      "claude-sonnet-4-20250514",
      "claude-sonnet-4-5",
      "claude-sonnet-4-5-20250929",
      "claude-sonnet-4-6"
    ],
    "zhipuai-coding-plan": ["glm-4.5-air", "glm-4.7", "glm-5-turbo", "glm-5.1", "glm-5v-turbo"],
    "atomic-chat": [
      "Meta-Llama-3_1-8B-Instruct-GGUF",
      "Qwen3_5-9B-MLX-4bit",
      "Qwen3_5-9B-Q4_K_M",
      "gemma-4-E4B-it-IQ4_XS",
      "gemma-4-E4B-it-MLX-4bit"
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    "github-models": [
      "ai21-labs/ai21-jamba-1.5-large",
      "ai21-labs/ai21-jamba-1.5-mini",
      "cohere/cohere-command-a",
      "cohere/cohere-command-r",
      "cohere/cohere-command-r-08-2024",
      "cohere/cohere-command-r-plus",
      "cohere/cohere-command-r-plus-08-2024",
      "core42/jais-30b-chat",
      "deepseek/deepseek-r1",
      "deepseek/deepseek-r1-0528",
      "deepseek/deepseek-v3-0324",
      "meta/llama-3.2-11b-vision-instruct",
      "meta/llama-3.2-90b-vision-instruct",
      "meta/llama-3.3-70b-instruct",
      "meta/llama-4-maverick-17b-128e-instruct-fp8",
      "meta/llama-4-scout-17b-16e-instruct",
      "meta/meta-llama-3-70b-instruct",
      "meta/meta-llama-3-8b-instruct",
      "meta/meta-llama-3.1-405b-instruct",
      "meta/meta-llama-3.1-70b-instruct",
      "meta/meta-llama-3.1-8b-instruct",
      "microsoft/mai-ds-r1",
      "microsoft/phi-3-medium-128k-instruct",
      "microsoft/phi-3-medium-4k-instruct",
      "microsoft/phi-3-mini-128k-instruct",
      "microsoft/phi-3-mini-4k-instruct",
      "microsoft/phi-3-small-128k-instruct",
      "microsoft/phi-3-small-8k-instruct",
      "microsoft/phi-3.5-mini-instruct",
      "microsoft/phi-3.5-moe-instruct",
      "microsoft/phi-3.5-vision-instruct",
      "microsoft/phi-4",
      "microsoft/phi-4-mini-instruct",
      "microsoft/phi-4-mini-reasoning",
      "microsoft/phi-4-multimodal-instruct",
      "microsoft/phi-4-reasoning",
      "mistral-ai/codestral-2501",
      "mistral-ai/ministral-3b",
      "mistral-ai/mistral-large-2411",
      "mistral-ai/mistral-medium-2505",
      "mistral-ai/mistral-nemo",
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      "openai/gpt-4.1",
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      "openai/gpt-4.1-nano",
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      "openai/o1",
      "openai/o1-mini",
      "openai/o1-preview",
      "openai/o3",
      "openai/o3-mini",
      "openai/o4-mini",
      "xai/grok-3",
      "xai/grok-3-mini"
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      "claude-3.5-sonnet",
      "claude-3.7-sonnet",
      "claude-4.0-opus",
      "claude-4.0-sonnet",
      "claude-4.1-opus",
      "claude-4.5-haiku",
      "claude-4.5-opus",
      "claude-4.5-sonnet",
      "deepseek-r1",
      "deepseek-r1-0528",
      "deepseek-v3",
      "deepseek-v3-0324",
      "deepseek-v3.1",
      "deepseek/deepseek-math-v2",
      "deepseek/deepseek-v3.1-terminus",
      "deepseek/deepseek-v3.1-terminus-thinking",
      "deepseek/deepseek-v3.2-251201",
      "deepseek/deepseek-v3.2-exp",
      "deepseek/deepseek-v3.2-exp-thinking",
      "doubao-1.5-pro-32k",
      "doubao-1.5-thinking-pro",
      "doubao-1.5-vision-pro",
      "doubao-seed-1.6",
      "doubao-seed-1.6-flash",
      "doubao-seed-1.6-thinking",
      "doubao-seed-2.0-code",
      "doubao-seed-2.0-lite",
      "doubao-seed-2.0-mini",
      "doubao-seed-2.0-pro",
      "gemini-2.0-flash",
      "gemini-2.0-flash-lite",
      "gemini-2.5-flash",
      "gemini-2.5-flash-image",
      "gemini-2.5-flash-lite",
      "gemini-2.5-pro",
      "gemini-3.0-flash-preview",
      "gemini-3.0-pro-image-preview",
      "gemini-3.0-pro-preview",
      "glm-4.5",
      "glm-4.5-air",
      "gpt-oss-120b",
      "gpt-oss-20b",
      "kimi-k2",
      "kling-v2-6",
      "meituan/longcat-flash-chat",
      "meituan/longcat-flash-lite",
      "mimo-v2-flash",
      "minimax/minimax-m2",
      "minimax/minimax-m2.1",
      "minimax/minimax-m2.5",
      "minimax/minimax-m2.5-highspeed",
      "moonshotai/kimi-k2-0905",
      "moonshotai/kimi-k2-thinking",
      "moonshotai/kimi-k2.5",
      "openai/gpt-5",
      "openai/gpt-5.2",
      "qwen-max-2025-01-25",
      "qwen-turbo",
      "qwen-vl-max-2025-01-25",
      "qwen2.5-vl-72b-instruct",
      "qwen2.5-vl-7b-instruct",
      "qwen3-235b-a22b",
      "qwen3-235b-a22b-instruct-2507",
      "qwen3-235b-a22b-thinking-2507",
      "qwen3-30b-a3b",
      "qwen3-30b-a3b-instruct-2507",
      "qwen3-30b-a3b-thinking-2507",
      "qwen3-32b",
      "qwen3-coder-480b-a35b-instruct",
      "qwen3-max",
      "qwen3-max-preview",
      "qwen3-next-80b-a3b-instruct",
      "qwen3-next-80b-a3b-thinking",
      "qwen3-vl-30b-a3b-thinking",
      "qwen3.5-397b-a17b",
      "stepfun-ai/gelab-zero-4b-preview",
      "stepfun/step-3.5-flash",
      "x-ai/grok-4-fast",
      "x-ai/grok-4-fast-non-reasoning",
      "x-ai/grok-4-fast-reasoning",
      "x-ai/grok-4.1-fast",
      "x-ai/grok-4.1-fast-non-reasoning",
      "x-ai/grok-4.1-fast-reasoning",
      "x-ai/grok-code-fast-1",
      "xiaomi/mimo-v2-flash",
      "z-ai/autoglm-phone-9b",
      "z-ai/glm-4.6",
      "z-ai/glm-4.7",
      "z-ai/glm-5"
    ],
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      "gemini-2.0-flash-lite",
      "gemini-2.5-flash",
      "gemini-2.5-flash-image",
      "gemini-2.5-flash-lite",
      "gemini-2.5-flash-preview-tts",
      "gemini-2.5-pro",
      "gemini-2.5-pro-preview-tts",
      "gemini-3-flash-preview",
      "gemini-3-pro-preview",
      "gemini-3.1-flash-image-preview",
      "gemini-3.1-flash-lite",
      "gemini-3.1-flash-lite-preview",
      "gemini-3.1-pro-preview",
      "gemini-3.1-pro-preview-customtools",
      "gemini-3.5-flash",
      "gemini-embedding-001",
      "gemini-flash-latest",
      "gemini-flash-lite-latest",
      "gemma-4-26b-a4b-it",
      "gemma-4-31b-it"
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    scaleway: [
      "bge-multilingual-gemma2",
      "deepseek-r1-distill-llama-70b",
      "devstral-2-123b-instruct-2512",
      "gemma-3-27b-it",
      "gpt-oss-120b",
      "llama-3.1-8b-instruct",
      "llama-3.3-70b-instruct",
      "mistral-medium-3.5-128b",
      "mistral-nemo-instruct-2407",
      "mistral-small-3.2-24b-instruct-2506",
      "pixtral-12b-2409",
      "qwen3-235b-a22b-instruct-2507",
      "qwen3-coder-30b-a3b-instruct",
      "qwen3-embedding-8b",
      "qwen3.5-397b-a17b",
      "voxtral-small-24b-2507",
      "whisper-large-v3"
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      "claude-haiku-4-5",
      "claude-opus-4-1",
      "claude-opus-4-5",
      "claude-opus-4-6",
      "claude-opus-4-7",
      "claude-sonnet-4",
      "claude-sonnet-4-5",
      "claude-sonnet-4-6",
      "deepseek-v4-flash-free",
      "gemini-3-flash",
      "gemini-3.1-pro",
      "gemini-3.5-flash",
      "glm-5",
      "glm-5.1",
      "gpt-5",
      "gpt-5-codex",
      "gpt-5-nano",
      "gpt-5.1",
      "gpt-5.1-codex",
      "gpt-5.1-codex-max",
      "gpt-5.1-codex-mini",
      "gpt-5.2",
      "gpt-5.2-codex",
      "gpt-5.3-codex",
      "gpt-5.3-codex-spark",
      "gpt-5.4",
      "gpt-5.4-mini",
      "gpt-5.4-nano",
      "gpt-5.4-pro",
      "gpt-5.5",
      "gpt-5.5-pro",
      "grok-build-0.1",
      "kimi-k2.5",
      "kimi-k2.6",
      "minimax-m2.5",
      "minimax-m2.7",
      "nemotron-3-super-free",
      "qwen3.5-plus",
      "qwen3.6-plus"
    ],
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      "qwen/qwen3.5-122b-a10b",
      "qwen/qwen3.5-27b",
      "qwen/qwen3.5-35b-a3b",
      "qwen/qwen3.5-397b-a17b",
      "qwen/qwen3.5-9b"
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      "anthropic/claude-3.7-sonnet",
      "anthropic/claude-haiku-4.5",
      "anthropic/claude-opus-4",
      "anthropic/claude-opus-4.1",
      "anthropic/claude-opus-4.5",
      "anthropic/claude-opus-4.6",
      "anthropic/claude-opus-4.7",
      "anthropic/claude-sonnet-4",
      "anthropic/claude-sonnet-4.5",
      "anthropic/claude-sonnet-4.6",
      "baidu/ernie-5.0-thinking-preview",
      "deepseek/deepseek-chat",
      "deepseek/deepseek-v3.2",
      "deepseek/deepseek-v3.2-exp",
      "deepseek/deepseek-v4-flash",
      "deepseek/deepseek-v4-pro",
      "google/gemini-2.5-flash",
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      "google/gemini-3-flash-preview",
      "google/gemini-3.1-flash-lite-preview",
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      "inclusionai/ling-1t",
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      "kuaishou/kat-coder-pro-v2",
      "minimax/minimax-m2",
      "minimax/minimax-m2.1",
      "minimax/minimax-m2.5",
      "minimax/minimax-m2.5-lightning",
      "minimax/minimax-m2.7",
      "minimax/minimax-m2.7-highspeed",
      "moonshotai/kimi-k2-0905",
      "moonshotai/kimi-k2-thinking",
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      "openai/gpt-5.5",
      "openai/gpt-5.5-pro",
      "qwen/qwen3-coder-plus",
      "qwen/qwen3-max",
      "qwen/qwen3.5-flash",
      "qwen/qwen3.5-plus",
      "qwen/qwen3.6-plus",
      "sapiens-ai/agnes-1.5-lite",
      "sapiens-ai/agnes-1.5-pro",
      "stepfun/step-3",
      "stepfun/step-3.5-flash",
      "stepfun/step-3.5-flash-free",
      "tencent/hy3-preview",
      "volcengine/doubao-seed-1.8",
      "volcengine/doubao-seed-2.0-code",
      "volcengine/doubao-seed-2.0-lite",
      "volcengine/doubao-seed-2.0-mini",
      "volcengine/doubao-seed-2.0-pro",
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      "x-ai/grok-4",
      "x-ai/grok-4-fast",
      "x-ai/grok-4.1-fast",
      "x-ai/grok-4.1-fast-non-reasoning",
      "x-ai/grok-4.2-fast",
      "x-ai/grok-4.2-fast-non-reasoning",
      "x-ai/grok-code-fast-1",
      "xiaomi/mimo-v2-flash",
      "xiaomi/mimo-v2-omni",
      "xiaomi/mimo-v2-pro",
      "xiaomi/mimo-v2.5",
      "xiaomi/mimo-v2.5-pro",
      "z-ai/glm-4.5",
      "z-ai/glm-4.5-air",
      "z-ai/glm-4.6",
      "z-ai/glm-4.6v",
      "z-ai/glm-4.6v-flash",
      "z-ai/glm-4.6v-flash-free",
      "z-ai/glm-4.7",
      "z-ai/glm-4.7-flash-free",
      "z-ai/glm-4.7-flashx",
      "z-ai/glm-5",
      "z-ai/glm-5-turbo",
      "z-ai/glm-5.1",
      "z-ai/glm-5v-turbo"
    ],
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      "anthropic/claude-opus-4-5",
      "anthropic/claude-opus-4-6",
      "anthropic/claude-opus-4-7",
      "anthropic/claude-sonnet-4-5",
      "anthropic/claude-sonnet-4-6",
      "google/gemini-2.5-flash",
      "google/gemini-2.5-pro",
      "google/gemini-3-flash-preview",
      "google/gemini-3.1-pro-preview",
      "nvidia/nemotron-3-super-120b-a12b",
      "openai/gpt-5-mini",
      "openai/gpt-5.1",
      "openai/gpt-5.2",
      "openai/gpt-5.4",
      "openai/gpt-5.5",
      "perplexity/sonar",
      "xai/grok-4-1-fast-non-reasoning"
    ],
    "alibaba-coding-plan": [
      "MiniMax-M2.5",
      "glm-4.7",
      "glm-5",
      "kimi-k2.5",
      "qwen3-coder-next",
      "qwen3-coder-plus",
      "qwen3-max-2026-01-23",
      "qwen3.5-plus",
      "qwen3.6-plus"
    ],
    meganova: [
      "MiniMaxAI/MiniMax-M2.1",
      "MiniMaxAI/MiniMax-M2.5",
      "Qwen/Qwen2.5-VL-32B-Instruct",
      "Qwen/Qwen3-235B-A22B-Instruct-2507",
      "Qwen/Qwen3.5-Plus",
      "XiaomiMiMo/MiMo-V2-Flash",
      "deepseek-ai/DeepSeek-R1-0528",
      "deepseek-ai/DeepSeek-V3-0324",
      "deepseek-ai/DeepSeek-V3.1",
      "deepseek-ai/DeepSeek-V3.2",
      "deepseek-ai/DeepSeek-V3.2-Exp",
      "meta-llama/Llama-3.3-70B-Instruct",
      "mistralai/Mistral-Nemo-Instruct-2407",
      "mistralai/Mistral-Small-3.2-24B-Instruct-2506",
      "moonshotai/Kimi-K2-Thinking",
      "moonshotai/Kimi-K2.5",
      "zai-org/GLM-4.6",
      "zai-org/GLM-4.7",
      "zai-org/GLM-5"
    ],
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      "hf:MiniMaxAI/MiniMax-M2.5",
      "hf:Qwen/Qwen2.5-Coder-32B-Instruct",
      "hf:Qwen/Qwen3-235B-A22B-Instruct-2507",
      "hf:Qwen/Qwen3-235B-A22B-Thinking-2507",
      "hf:Qwen/Qwen3-Coder-480B-A35B-Instruct",
      "hf:Qwen/Qwen3.5-397B-A17B",
      "hf:deepseek-ai/DeepSeek-R1",
      "hf:deepseek-ai/DeepSeek-R1-0528",
      "hf:deepseek-ai/DeepSeek-V3",
      "hf:deepseek-ai/DeepSeek-V3-0324",
      "hf:deepseek-ai/DeepSeek-V3.1",
      "hf:deepseek-ai/DeepSeek-V3.1-Terminus",
      "hf:deepseek-ai/DeepSeek-V3.2",
      "hf:meta-llama/Llama-3.1-405B-Instruct",
      "hf:meta-llama/Llama-3.1-70B-Instruct",
      "hf:meta-llama/Llama-3.1-8B-Instruct",
      "hf:meta-llama/Llama-3.3-70B-Instruct",
      "hf:meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8",
      "hf:meta-llama/Llama-4-Scout-17B-16E-Instruct",
      "hf:moonshotai/Kimi-K2-Instruct-0905",
      "hf:moonshotai/Kimi-K2-Thinking",
      "hf:moonshotai/Kimi-K2.5",
      "hf:moonshotai/Kimi-K2.6",
      "hf:nvidia/Kimi-K2.5-NVFP4",
      "hf:nvidia/NVIDIA-Nemotron-3-Super-120B-A12B-NVFP4",
      "hf:openai/gpt-oss-120b",
      "hf:zai-org/GLM-4.6",
      "hf:zai-org/GLM-4.7",
      "hf:zai-org/GLM-4.7-Flash",
      "hf:zai-org/GLM-5",
      "hf:zai-org/GLM-5.1"
    ],
    inceptron: [
      "MiniMaxAI/MiniMax-M2.5",
      "moonshotai/Kimi-K2.6",
      "nvidia/llama-3.3-70b-instruct-fp8",
      "zai-org/GLM-5.1-FP8"
    ],
    "minimax-coding-plan": [
      "MiniMax-M2",
      "MiniMax-M2.1",
      "MiniMax-M2.5",
      "MiniMax-M2.5-highspeed",
      "MiniMax-M2.7",
      "MiniMax-M2.7-highspeed"
    ],
    upstage: ["solar-mini", "solar-pro2", "solar-pro3"],
    vercel: [
      "alibaba/qwen-3-14b",
      "alibaba/qwen-3-235b",
      "alibaba/qwen-3-30b",
      "alibaba/qwen-3-32b",
      "alibaba/qwen-3.6-max-preview",
      "alibaba/qwen3-235b-a22b-thinking",
      "alibaba/qwen3-coder",
      "alibaba/qwen3-coder-30b-a3b",
      "alibaba/qwen3-coder-next",
      "alibaba/qwen3-coder-plus",
      "alibaba/qwen3-embedding-0.6b",
      "alibaba/qwen3-embedding-4b",
      "alibaba/qwen3-embedding-8b",
      "alibaba/qwen3-max",
      "alibaba/qwen3-max-preview",
      "alibaba/qwen3-max-thinking",
      "alibaba/qwen3-next-80b-a3b-instruct",
      "alibaba/qwen3-next-80b-a3b-thinking",
      "alibaba/qwen3-vl-235b-a22b-instruct",
      "alibaba/qwen3-vl-instruct",
      "alibaba/qwen3-vl-thinking",
      "alibaba/qwen3.5-flash",
      "alibaba/qwen3.5-plus",
      "alibaba/qwen3.6-27b",
      "alibaba/qwen3.6-plus",
      "alibaba/qwen3.7-max",
      "amazon/nova-2-lite",
      "amazon/nova-lite",
      "amazon/nova-micro",
      "amazon/nova-pro",
      "amazon/titan-embed-text-v2",
      "anthropic/claude-3-haiku",
      "anthropic/claude-3-opus",
      "anthropic/claude-3.5-haiku",
      "anthropic/claude-3.5-sonnet",
      "anthropic/claude-3.5-sonnet-20240620",
      "anthropic/claude-3.7-sonnet",
      "anthropic/claude-haiku-4.5",
      "anthropic/claude-opus-4",
      "anthropic/claude-opus-4.1",
      "anthropic/claude-opus-4.5",
      "anthropic/claude-opus-4.6",
      "anthropic/claude-opus-4.7",
      "anthropic/claude-sonnet-4",
      "anthropic/claude-sonnet-4.5",
      "anthropic/claude-sonnet-4.6",
      "arcee-ai/trinity-large-preview",
      "arcee-ai/trinity-large-thinking",
      "arcee-ai/trinity-mini",
      "bfl/flux-kontext-max",
      "bfl/flux-kontext-pro",
      "bfl/flux-pro-1.0-fill",
      "bfl/flux-pro-1.1",
      "bfl/flux-pro-1.1-ultra",
      "bytedance/seed-1.6",
      "bytedance/seed-1.8",
      "cohere/command-a",
      "cohere/embed-v4.0",
      "deepseek/deepseek-r1",
      "deepseek/deepseek-v3",
      "deepseek/deepseek-v3.1",
      "deepseek/deepseek-v3.1-terminus",
      "deepseek/deepseek-v3.2",
      "deepseek/deepseek-v3.2-exp",
      "deepseek/deepseek-v3.2-thinking",
      "deepseek/deepseek-v4-flash",
      "deepseek/deepseek-v4-pro",
      "google/gemini-2.0-flash",
      "google/gemini-2.0-flash-lite",
      "google/gemini-2.5-flash",
      "google/gemini-2.5-flash-image",
      "google/gemini-2.5-flash-image-preview",
      "google/gemini-2.5-flash-lite",
      "google/gemini-2.5-flash-lite-preview-09-2025",
      "google/gemini-2.5-flash-preview-09-2025",
      "google/gemini-2.5-pro",
      "google/gemini-3-flash",
      "google/gemini-3-pro-image",
      "google/gemini-3-pro-preview",
      "google/gemini-3.1-flash-image-preview",
      "google/gemini-3.1-flash-lite",
      "google/gemini-3.1-flash-lite-preview",
      "google/gemini-3.1-pro-preview",
      "google/gemini-3.5-flash",
      "google/gemini-embedding-001",
      "google/gemini-embedding-2",
      "google/gemma-4-26b-a4b-it",
      "google/gemma-4-31b-it",
      "google/imagen-4.0-fast-generate-001",
      "google/imagen-4.0-generate-001",
      "google/imagen-4.0-ultra-generate-001",
      "google/text-embedding-005",
      "google/text-multilingual-embedding-002",
      "inception/mercury-2",
      "inception/mercury-coder-small",
      "inception/mercury-edit-2",
      "interfaze/interfaze-beta",
      "kwaipilot/kat-coder-pro-v1",
      "kwaipilot/kat-coder-pro-v2",
      "meituan/longcat-flash-chat",
      "meituan/longcat-flash-thinking",
      "meituan/longcat-flash-thinking-2601",
      "meta/llama-3.1-70b",
      "meta/llama-3.1-8b",
      "meta/llama-3.2-11b",
      "meta/llama-3.2-1b",
      "meta/llama-3.2-3b",
      "meta/llama-3.2-90b",
      "meta/llama-3.3-70b",
      "meta/llama-4-maverick",
      "meta/llama-4-scout",
      "minimax/minimax-m2",
      "minimax/minimax-m2.1",
      "minimax/minimax-m2.1-lightning",
      "minimax/minimax-m2.5",
      "minimax/minimax-m2.5-highspeed",
      "minimax/minimax-m2.7",
      "minimax/minimax-m2.7-highspeed",
      "mistral/codestral",
      "mistral/codestral-embed",
      "mistral/devstral-2",
      "mistral/devstral-small",
      "mistral/devstral-small-2",
      "mistral/magistral-medium",
      "mistral/magistral-small",
      "mistral/ministral-14b",
      "mistral/ministral-3b",
      "mistral/ministral-8b",
      "mistral/mistral-embed",
      "mistral/mistral-large-3",
      "mistral/mistral-medium",
      "mistral/mistral-medium-3.5",
      "mistral/mistral-nemo",
      "mistral/mistral-small",
      "mistral/mixtral-8x22b-instruct",
      "mistral/pixtral-12b",
      "mistral/pixtral-large",
      "moonshotai/kimi-k2-0905",
      "moonshotai/kimi-k2-thinking",
      "moonshotai/kimi-k2-thinking-turbo",
      "moonshotai/kimi-k2-turbo",
      "moonshotai/kimi-k2.5",
      "moonshotai/kimi-k2.6",
      "morph/morph-v3-fast",
      "morph/morph-v3-large",
      "nvidia/nemotron-3-nano-30b-a3b",
      "nvidia/nemotron-3-super-120b-a12b",
      "nvidia/nemotron-nano-12b-v2-vl",
      "nvidia/nemotron-nano-9b-v2",
      "openai/codex-mini",
      "openai/gpt-3.5-turbo",
      "openai/gpt-3.5-turbo-instruct",
      "openai/gpt-4-turbo",
      "openai/gpt-4.1",
      "openai/gpt-4.1-mini",
      "openai/gpt-4.1-nano",
      "openai/gpt-4o",
      "openai/gpt-4o-mini",
      "openai/gpt-4o-mini-search-preview",
      "openai/gpt-5",
      "openai/gpt-5-chat",
      "openai/gpt-5-codex",
      "openai/gpt-5-mini",
      "openai/gpt-5-nano",
      "openai/gpt-5-pro",
      "openai/gpt-5.1-codex",
      "openai/gpt-5.1-codex-max",
      "openai/gpt-5.1-codex-mini",
      "openai/gpt-5.1-instant",
      "openai/gpt-5.1-thinking",
      "openai/gpt-5.2",
      "openai/gpt-5.2-chat",
      "openai/gpt-5.2-codex",
      "openai/gpt-5.2-pro",
      "openai/gpt-5.3-chat",
      "openai/gpt-5.3-codex",
      "openai/gpt-5.4",
      "openai/gpt-5.4-mini",
      "openai/gpt-5.4-nano",
      "openai/gpt-5.4-pro",
      "openai/gpt-5.5",
      "openai/gpt-5.5-pro",
      "openai/gpt-oss-120b",
      "openai/gpt-oss-20b",
      "openai/gpt-oss-safeguard-20b",
      "openai/o1",
      "openai/o3",
      "openai/o3-deep-research",
      "openai/o3-mini",
      "openai/o3-pro",
      "openai/o4-mini",
      "openai/text-embedding-3-large",
      "openai/text-embedding-3-small",
      "openai/text-embedding-ada-002",
      "perplexity/sonar",
      "perplexity/sonar-pro",
      "perplexity/sonar-reasoning",
      "perplexity/sonar-reasoning-pro",
      "prime-intellect/intellect-3",
      "recraft/recraft-v2",
      "recraft/recraft-v3",
      "vercel/v0-1.0-md",
      "vercel/v0-1.5-md",
      "voyage/voyage-3-large",
      "voyage/voyage-3.5",
      "voyage/voyage-3.5-lite",
      "voyage/voyage-4",
      "voyage/voyage-4-large",
      "voyage/voyage-4-lite",
      "voyage/voyage-code-2",
      "voyage/voyage-code-3",
      "voyage/voyage-finance-2",
      "voyage/voyage-law-2",
      "xai/grok-4-fast-reasoning",
      "xai/grok-4.1-fast-non-reasoning",
      "xai/grok-4.1-fast-reasoning",
      "xai/grok-4.20-multi-agent",
      "xai/grok-4.20-multi-agent-beta",
      "xai/grok-4.20-non-reasoning",
      "xai/grok-4.20-non-reasoning-beta",
      "xai/grok-4.20-reasoning",
      "xai/grok-4.20-reasoning-beta",
      "xai/grok-4.3",
      "xai/grok-build-0.1",
      "xai/grok-imagine-image",
      "xai/grok-imagine-image-pro",
      "xiaomi/mimo-v2-flash",
      "xiaomi/mimo-v2-pro",
      "xiaomi/mimo-v2.5",
      "xiaomi/mimo-v2.5-pro",
      "zai/glm-4.5",
      "zai/glm-4.5-air",
      "zai/glm-4.5v",
      "zai/glm-4.6",
      "zai/glm-4.6v",
      "zai/glm-4.6v-flash",
      "zai/glm-4.7",
      "zai/glm-4.7-flash",
      "zai/glm-4.7-flashx",
      "zai/glm-5",
      "zai/glm-5-turbo",
      "zai/glm-5.1",
      "zai/glm-5v-turbo"
    ],
    "abliteration-ai": ["abliterated-model"],
    deepseek: ["deepseek-chat", "deepseek-reasoner", "deepseek-v4-flash", "deepseek-v4-pro"],
    perplexity: ["sonar", "sonar-deep-research", "sonar-pro", "sonar-reasoning-pro"],
    iflowcn: [
      "deepseek-r1",
      "deepseek-v3",
      "deepseek-v3.2",
      "glm-4.6",
      "kimi-k2",
      "kimi-k2-0905",
      "qwen3-235b",
      "qwen3-235b-a22b-instruct",
      "qwen3-235b-a22b-thinking-2507",
      "qwen3-32b",
      "qwen3-coder-plus",
      "qwen3-max",
      "qwen3-max-preview",
      "qwen3-vl-plus"
    ],
    stackit: [
      "Qwen/Qwen3-VL-235B-A22B-Instruct-FP8",
      "Qwen/Qwen3-VL-Embedding-8B",
      "cortecs/Llama-3.3-70B-Instruct-FP8-Dynamic",
      "google/gemma-3-27b-it",
      "intfloat/e5-mistral-7b-instruct",
      "neuralmagic/Meta-Llama-3.1-8B-Instruct-FP8",
      "neuralmagic/Mistral-Nemo-Instruct-2407-FP8",
      "openai/gpt-oss-120b"
    ],
    "wafer.ai": ["GLM-5.1", "Qwen3.5-397B-A17B"],
    evroc: [
      "KBLab/kb-whisper-large",
      "Qwen/Qwen3-30B-A3B-Instruct-2507-FP8",
      "Qwen/Qwen3-Embedding-8B",
      "Qwen/Qwen3-VL-30B-A3B-Instruct",
      "intfloat/multilingual-e5-large-instruct",
      "microsoft/Phi-4-multimodal-instruct",
      "mistralai/Magistral-Small-2509",
      "mistralai/Voxtral-Small-24B-2507",
      "mistralai/devstral-small-2-24b-instruct-2512",
      "moonshotai/Kimi-K2.5",
      "nvidia/Llama-3.3-70B-Instruct-FP8",
      "openai/gpt-oss-120b",
      "openai/whisper-large-v3"
    ],
    nova: ["nova-2-lite-v1", "nova-2-pro-v1"],
    "fireworks-ai": [
      "accounts/fireworks/models/deepseek-v3p1",
      "accounts/fireworks/models/deepseek-v3p2",
      "accounts/fireworks/models/deepseek-v4-flash",
      "accounts/fireworks/models/deepseek-v4-pro",
      "accounts/fireworks/models/glm-4p5",
      "accounts/fireworks/models/glm-4p5-air",
      "accounts/fireworks/models/glm-4p7",
      "accounts/fireworks/models/glm-5",
      "accounts/fireworks/models/glm-5p1",
      "accounts/fireworks/models/gpt-oss-120b",
      "accounts/fireworks/models/gpt-oss-20b",
      "accounts/fireworks/models/kimi-k2-instruct",
      "accounts/fireworks/models/kimi-k2-thinking",
      "accounts/fireworks/models/kimi-k2p5",
      "accounts/fireworks/models/kimi-k2p6",
      "accounts/fireworks/models/minimax-m2p1",
      "accounts/fireworks/models/minimax-m2p5",
      "accounts/fireworks/models/minimax-m2p7",
      "accounts/fireworks/models/qwen3p6-plus",
      "accounts/fireworks/routers/kimi-k2p5-turbo"
    ],
    alibaba: [
      "qvq-max",
      "qwen-flash",
      "qwen-max",
      "qwen-mt-plus",
      "qwen-mt-turbo",
      "qwen-omni-turbo",
      "qwen-omni-turbo-realtime",
      "qwen-plus",
      "qwen-plus-character-ja",
      "qwen-turbo",
      "qwen-vl-max",
      "qwen-vl-ocr",
      "qwen-vl-plus",
      "qwen2-5-14b-instruct",
      "qwen2-5-32b-instruct",
      "qwen2-5-72b-instruct",
      "qwen2-5-7b-instruct",
      "qwen2-5-omni-7b",
      "qwen2-5-vl-72b-instruct",
      "qwen2-5-vl-7b-instruct",
      "qwen3-14b",
      "qwen3-235b-a22b",
      "qwen3-32b",
      "qwen3-8b",
      "qwen3-asr-flash",
      "qwen3-coder-30b-a3b-instruct",
      "qwen3-coder-480b-a35b-instruct",
      "qwen3-coder-flash",
      "qwen3-coder-plus",
      "qwen3-livetranslate-flash-realtime",
      "qwen3-max",
      "qwen3-next-80b-a3b-instruct",
      "qwen3-next-80b-a3b-thinking",
      "qwen3-omni-flash",
      "qwen3-omni-flash-realtime",
      "qwen3-vl-235b-a22b",
      "qwen3-vl-30b-a3b",
      "qwen3-vl-plus",
      "qwen3.5-122b-a10b",
      "qwen3.5-27b",
      "qwen3.5-35b-a3b",
      "qwen3.5-397b-a17b",
      "qwen3.5-plus",
      "qwen3.6-27b",
      "qwen3.6-35b-a3b",
      "qwen3.6-max-preview",
      "qwen3.6-plus",
      "qwen3.7-max",
      "qwq-plus"
    ],
    "302ai": [
      "MiniMax-M1",
      "MiniMax-M2",
      "MiniMax-M2.1",
      "MiniMax-M2.7",
      "MiniMax-M2.7-highspeed",
      "chatgpt-4o-latest",
      "claude-3-5-haiku-20241022",
      "claude-3-5-haiku-latest",
      "claude-haiku-4-5",
      "claude-haiku-4-5-20251001",
      "claude-opus-4-1-20250805",
      "claude-opus-4-1-20250805-thinking",
      "claude-opus-4-20250514",
      "claude-opus-4-5",
      "claude-opus-4-5-20251101",
      "claude-opus-4-5-20251101-thinking",
      "claude-opus-4-6",
      "claude-opus-4-6-thinking",
      "claude-opus-4-7",
      "claude-sonnet-4-20250514",
      "claude-sonnet-4-5",
      "claude-sonnet-4-5-20250929",
      "claude-sonnet-4-5-20250929-thinking",
      "claude-sonnet-4-6",
      "claude-sonnet-4-6-thinking",
      "deepseek-chat",
      "deepseek-reasoner",
      "deepseek-v3.2",
      "deepseek-v3.2-thinking",
      "doubao-seed-1-6-thinking-250715",
      "doubao-seed-1-6-vision-250815",
      "doubao-seed-1-8-251215",
      "doubao-seed-code-preview-251028",
      "gemini-2.0-flash-lite",
      "gemini-2.5-flash",
      "gemini-2.5-flash-image",
      "gemini-2.5-flash-lite-preview-09-2025",
      "gemini-2.5-flash-nothink",
      "gemini-2.5-flash-preview-09-2025",
      "gemini-2.5-pro",
      "gemini-3-flash-preview",
      "gemini-3-pro-image-preview",
      "gemini-3-pro-preview",
      "gemini-3.1-flash-image-preview",
      "glm-4.5",
      "glm-4.5-air",
      "glm-4.5-airx",
      "glm-4.5-x",
      "glm-4.5v",
      "glm-4.6",
      "glm-4.6v",
      "glm-4.7",
      "glm-4.7-flashx",
      "glm-5",
      "glm-5-turbo",
      "glm-5.1",
      "glm-5v-turbo",
      "glm-for-coding",
      "gpt-4.1",
      "gpt-4.1-mini",
      "gpt-4.1-nano",
      "gpt-4o",
      "gpt-5",
      "gpt-5-mini",
      "gpt-5-pro",
      "gpt-5-thinking",
      "gpt-5.1",
      "gpt-5.1-chat-latest",
      "gpt-5.2",
      "gpt-5.2-chat-latest",
      "gpt-5.4",
      "gpt-5.4-mini",
      "gpt-5.4-mini-2026-03-17",
      "gpt-5.4-nano",
      "gpt-5.4-nano-2026-03-17",
      "gpt-5.4-pro",
      "grok-4-1-fast-non-reasoning",
      "grok-4-1-fast-reasoning",
      "grok-4-fast-non-reasoning",
      "grok-4-fast-reasoning",
      "grok-4.1",
      "grok-4.20-beta-0309-non-reasoning",
      "grok-4.20-beta-0309-reasoning",
      "grok-4.20-multi-agent-beta-0309",
      "kimi-k2-0905-preview",
      "kimi-k2-thinking",
      "kimi-k2-thinking-turbo",
      "ministral-14b-2512",
      "mistral-large-2512",
      "qwen-flash",
      "qwen-max-latest",
      "qwen-plus",
      "qwen3-235b-a22b",
      "qwen3-235b-a22b-instruct-2507",
      "qwen3-30b-a3b",
      "qwen3-coder-480b-a35b-instruct",
      "qwen3-max-2025-09-23"
    ],
    xpersona: ["xpersona-frieren-coder"],
    stepfun: ["step-1-32k", "step-2-16k", "step-3.5-flash", "step-3.5-flash-2603"],
    xai: [
      "grok-4.20-0309-non-reasoning",
      "grok-4.20-0309-reasoning",
      "grok-4.20-multi-agent-0309",
      "grok-4.3",
      "grok-build-0.1",
      "grok-imagine-image",
      "grok-imagine-image-quality",
      "grok-imagine-video"
    ],
    sarvam: ["sarvam-105b", "sarvam-30b"],
    zhipuai: [
      "glm-4.5",
      "glm-4.5-air",
      "glm-4.5-flash",
      "glm-4.5v",
      "glm-4.6",
      "glm-4.6v",
      "glm-4.7",
      "glm-4.7-flash",
      "glm-4.7-flashx",
      "glm-5",
      "glm-5.1",
      "glm-5v-turbo"
    ],
    bailing: ["Ling-1T", "Ring-1T"],
    "qihang-ai": [
      "claude-haiku-4-5-20251001",
      "claude-opus-4-5-20251101",
      "claude-sonnet-4-5-20250929",
      "gemini-2.5-flash",
      "gemini-3-flash-preview",
      "gemini-3-pro-preview",
      "gpt-5-mini",
      "gpt-5.2",
      "gpt-5.2-codex"
    ],
    lilac: ["google/gemma-4-31b-it", "minimaxai/minimax-m2.7", "moonshotai/kimi-k2.6", "zai-org/glm-5.1"],
    "alibaba-cn": [
      "MiniMax-M2.5",
      "MiniMax/MiniMax-M2.7",
      "deepseek-r1",
      "deepseek-r1-0528",
      "deepseek-r1-distill-llama-70b",
      "deepseek-r1-distill-llama-8b",
      "deepseek-r1-distill-qwen-1-5b",
      "deepseek-r1-distill-qwen-14b",
      "deepseek-r1-distill-qwen-32b",
      "deepseek-r1-distill-qwen-7b",
      "deepseek-v3",
      "deepseek-v3-1",
      "deepseek-v3-2-exp",
      "deepseek-v4-flash",
      "deepseek-v4-pro",
      "glm-5",
      "glm-5.1",
      "kimi-k2-thinking",
      "kimi-k2.5",
      "kimi-k2.6",
      "kimi/kimi-k2.5",
      "moonshot-kimi-k2-instruct",
      "qvq-max",
      "qwen-deep-research",
      "qwen-doc-turbo",
      "qwen-flash",
      "qwen-long",
      "qwen-math-plus",
      "qwen-math-turbo",
      "qwen-max",
      "qwen-mt-plus",
      "qwen-mt-turbo",
      "qwen-omni-turbo",
      "qwen-omni-turbo-realtime",
      "qwen-plus",
      "qwen-plus-character",
      "qwen-turbo",
      "qwen-vl-max",
      "qwen-vl-ocr",
      "qwen-vl-plus",
      "qwen2-5-14b-instruct",
      "qwen2-5-32b-instruct",
      "qwen2-5-72b-instruct",
      "qwen2-5-7b-instruct",
      "qwen2-5-coder-32b-instruct",
      "qwen2-5-coder-7b-instruct",
      "qwen2-5-math-72b-instruct",
      "qwen2-5-math-7b-instruct",
      "qwen2-5-omni-7b",
      "qwen2-5-vl-72b-instruct",
      "qwen2-5-vl-7b-instruct",
      "qwen3-14b",
      "qwen3-235b-a22b",
      "qwen3-32b",
      "qwen3-8b",
      "qwen3-asr-flash",
      "qwen3-coder-30b-a3b-instruct",
      "qwen3-coder-480b-a35b-instruct",
      "qwen3-coder-flash",
      "qwen3-coder-plus",
      "qwen3-max",
      "qwen3-next-80b-a3b-instruct",
      "qwen3-next-80b-a3b-thinking",
      "qwen3-omni-flash",
      "qwen3-omni-flash-realtime",
      "qwen3-vl-235b-a22b",
      "qwen3-vl-30b-a3b",
      "qwen3-vl-plus",
      "qwen3.5-397b-a17b",
      "qwen3.5-flash",
      "qwen3.5-plus",
      "qwen3.6-max-preview",
      "qwen3.6-plus",
      "qwq-32b",
      "qwq-plus",
      "siliconflow/deepseek-r1-0528",
      "siliconflow/deepseek-v3-0324",
      "siliconflow/deepseek-v3.1-terminus",
      "siliconflow/deepseek-v3.2",
      "tongyi-intent-detect-v3"
    ],
    drun: ["public/deepseek-r1", "public/deepseek-v3", "public/minimax-m25"],
    huggingface: [
      "MiniMaxAI/MiniMax-M2.1",
      "MiniMaxAI/MiniMax-M2.5",
      "MiniMaxAI/MiniMax-M2.7",
      "Qwen/Qwen3-235B-A22B-Thinking-2507",
      "Qwen/Qwen3-Coder-480B-A35B-Instruct",
      "Qwen/Qwen3-Coder-Next",
      "Qwen/Qwen3-Embedding-4B",
      "Qwen/Qwen3-Embedding-8B",
      "Qwen/Qwen3-Next-80B-A3B-Instruct",
      "Qwen/Qwen3-Next-80B-A3B-Thinking",
      "Qwen/Qwen3.5-397B-A17B",
      "XiaomiMiMo/MiMo-V2-Flash",
      "deepseek-ai/DeepSeek-R1-0528",
      "deepseek-ai/DeepSeek-V3.2",
      "deepseek-ai/DeepSeek-V4-Pro",
      "moonshotai/Kimi-K2-Instruct",
      "moonshotai/Kimi-K2-Instruct-0905",
      "moonshotai/Kimi-K2-Thinking",
      "moonshotai/Kimi-K2.5",
      "moonshotai/Kimi-K2.6",
      "zai-org/GLM-4.7",
      "zai-org/GLM-4.7-Flash",
      "zai-org/GLM-5",
      "zai-org/GLM-5.1"
    ],
    "umans-ai-coding-plan": ["umans-coder", "umans-flash", "umans-glm-5.1", "umans-kimi-k2.6", "umans-qwen3.6-35b-a3b"],
    "tencent-tokenhub": ["hy3-preview"],
    nebius: [
      "MiniMaxAI/MiniMax-M2.5",
      "MiniMaxAI/MiniMax-M2.5-fast",
      "NousResearch/Hermes-4-405B",
      "NousResearch/Hermes-4-70B",
      "PrimeIntellect/INTELLECT-3",
      "Qwen/Qwen2.5-VL-72B-Instruct",
      "Qwen/Qwen3-235B-A22B-Instruct-2507",
      "Qwen/Qwen3-235B-A22B-Thinking-2507-fast",
      "Qwen/Qwen3-30B-A3B-Instruct-2507",
      "Qwen/Qwen3-32B",
      "Qwen/Qwen3-Embedding-8B",
      "Qwen/Qwen3-Next-80B-A3B-Thinking",
      "Qwen/Qwen3-Next-80B-A3B-Thinking-fast",
      "Qwen/Qwen3.5-397B-A17B",
      "Qwen/Qwen3.5-397B-A17B-fast",
      "deepseek-ai/DeepSeek-V3.2",
      "deepseek-ai/DeepSeek-V3.2-fast",
      "deepseek-ai/DeepSeek-V4-Pro",
      "google/gemma-2-2b-it",
      "google/gemma-3-27b-it",
      "meta-llama/Llama-3.3-70B-Instruct",
      "meta-llama/Meta-Llama-3.1-8B-Instruct",
      "moonshotai/Kimi-K2.5",
      "moonshotai/Kimi-K2.5-fast",
      "nvidia/Llama-3_1-Nemotron-Ultra-253B-v1",
      "nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B",
      "nvidia/Nemotron-3-Nano-Omni",
      "nvidia/nemotron-3-super-120b-a12b",
      "openai/gpt-oss-120b",
      "openai/gpt-oss-120b-fast",
      "zai-org/GLM-5"
    ],
    "hpc-ai": ["minimax/minimax-m2.5", "moonshotai/kimi-k2.5", "zai-org/glm-5.1"],
    xiaomi: ["mimo-v2-flash", "mimo-v2-omni", "mimo-v2-pro", "mimo-v2.5", "mimo-v2.5-pro"],
    togetherai: [
      "MiniMaxAI/MiniMax-M2.5",
      "MiniMaxAI/MiniMax-M2.7",
      "Qwen/Qwen3-235B-A22B-Instruct-2507-tput",
      "Qwen/Qwen3-Coder-480B-A35B-Instruct-FP8",
      "Qwen/Qwen3-Coder-Next-FP8",
      "Qwen/Qwen3.5-397B-A17B",
      "Qwen/Qwen3.6-Plus",
      "deepseek-ai/DeepSeek-R1",
      "deepseek-ai/DeepSeek-V3",
      "deepseek-ai/DeepSeek-V3-1",
      "deepseek-ai/DeepSeek-V4-Pro",
      "essentialai/Rnj-1-Instruct",
      "google/gemma-4-31B-it",
      "meta-llama/Llama-3.3-70B-Instruct-Turbo",
      "moonshotai/Kimi-K2.5",
      "moonshotai/Kimi-K2.6",
      "openai/gpt-oss-120b",
      "zai-org/GLM-5.1"
    ],
    "stepfun-ai": ["step-3.5-flash", "step-3.5-flash-2603"],
    inference: [
      "google/gemma-3",
      "meta/llama-3.1-8b-instruct",
      "meta/llama-3.2-11b-vision-instruct",
      "meta/llama-3.2-1b-instruct",
      "meta/llama-3.2-3b-instruct",
      "mistral/mistral-nemo-12b-instruct",
      "osmosis/osmosis-structure-0.6b",
      "qwen/qwen-2.5-7b-vision-instruct",
      "qwen/qwen3-embedding-4b"
    ],
    netlify: [
      "anthropic/claude-haiku-4-5",
      "anthropic/claude-haiku-4-5-20251001",
      "anthropic/claude-opus-4-1-20250805",
      "anthropic/claude-opus-4-20250514",
      "anthropic/claude-opus-4-5",
      "anthropic/claude-opus-4-5-20251101",
      "anthropic/claude-opus-4-6",
      "anthropic/claude-opus-4-7",
      "anthropic/claude-sonnet-4-0",
      "anthropic/claude-sonnet-4-20250514",
      "anthropic/claude-sonnet-4-5",
      "anthropic/claude-sonnet-4-5-20250929",
      "anthropic/claude-sonnet-4-6",
      "gemini/gemini-2.0-flash",
      "gemini/gemini-2.0-flash-lite",
      "gemini/gemini-2.5-flash",
      "gemini/gemini-2.5-flash-image",
      "gemini/gemini-2.5-flash-lite",
      "gemini/gemini-2.5-pro",
      "gemini/gemini-3-flash-preview",
      "gemini/gemini-3-pro-image-preview",
      "gemini/gemini-3.1-flash-image-preview",
      "gemini/gemini-3.1-flash-lite",
      "gemini/gemini-3.1-flash-lite-preview",
      "gemini/gemini-3.1-pro-preview",
      "gemini/gemini-3.1-pro-preview-customtools",
      "gemini/gemini-3.5-flash",
      "gemini/gemini-flash-latest",
      "gemini/gemini-flash-lite-latest",
      "openai/chat-latest",
      "openai/gpt-4.1",
      "openai/gpt-4.1-mini",
      "openai/gpt-4.1-nano",
      "openai/gpt-4o",
      "openai/gpt-4o-mini",
      "openai/gpt-5",
      "openai/gpt-5-2025-08-07",
      "openai/gpt-5-codex",
      "openai/gpt-5-mini",
      "openai/gpt-5-mini-2025-08-07",
      "openai/gpt-5-nano",
      "openai/gpt-5-pro",
      "openai/gpt-5.1",
      "openai/gpt-5.1-2025-11-13",
      "openai/gpt-5.1-codex",
      "openai/gpt-5.1-codex-max",
      "openai/gpt-5.1-codex-mini",
      "openai/gpt-5.2",
      "openai/gpt-5.2-2025-12-11",
      "openai/gpt-5.2-codex",
      "openai/gpt-5.2-pro",
      "openai/gpt-5.2-pro-2025-12-11",
      "openai/gpt-5.3-chat-latest",
      "openai/gpt-5.3-codex",
      "openai/gpt-5.4",
      "openai/gpt-5.4-2026-03-05",
      "openai/gpt-5.4-mini",
      "openai/gpt-5.4-mini-2026-03-17",
      "openai/gpt-5.4-nano",
      "openai/gpt-5.4-nano-2026-03-17",
      "openai/gpt-5.4-pro",
      "openai/gpt-5.4-pro-2026-03-05",
      "openai/gpt-5.5",
      "openai/gpt-5.5-2026-04-23",
      "openai/gpt-5.5-pro",
      "openai/gpt-5.5-pro-2026-04-23",
      "openai/o3",
      "openai/o3-mini",
      "openai/o4-mini"
    ]
  },
  version: "1.0.0"
};

// src/llm/model/provider-registry.ts
function isOfflineMode() {
  const value = process.env.MASTRA_OFFLINE;
  return value === "true" || value === "1";
}
function getEnabledGatewayIds(gateways) {
  const enabledGatewayIds = /* @__PURE__ */ new Set();
  for (const gateway of gateways) {
    const enabled = shouldEnableGateway(gateway);
    if (enabled) {
      enabledGatewayIds.add(getGatewayId(gateway));
    }
  }
  return enabledGatewayIds;
}
function sanitizeRegistryDataForRuntime(data, enabledGatewayIds) {
  const providers = Object.fromEntries(
    Object.entries(data.providers).filter(([, config]) => enabledGatewayIds.has(config.gateway))
  );
  const models = Object.fromEntries(Object.entries(data.models).filter(([providerId]) => providerId in providers));
  return {
    ...data,
    providers,
    models
  };
}
var registryData = null;
var CACHE_DIR = () => path__default.default.join(os__default.default.homedir(), ".cache", "mastra");
var CACHE_FILE = () => path__default.default.join(CACHE_DIR(), "gateway-refresh-time");
var GLOBAL_PROVIDER_REGISTRY_JSON = () => path__default.default.join(CACHE_DIR(), "provider-registry.json");
var GLOBAL_PROVIDER_TYPES_DTS = () => path__default.default.join(CACHE_DIR(), "provider-types.generated.d.ts");
var GLOBAL_CAPABILITIES_DIR = () => path__default.default.join(CACHE_DIR(), "capabilities");
var modelRouterCacheFailed = false;
function atomicWriteFileSync(filePath, content, encoding = "utf-8") {
  const randomSuffix = Math.random().toString(36).substring(2, 15);
  const tempPath = `${filePath}.${process.pid}.${Date.now()}.${randomSuffix}.tmp`;
  try {
    fs__default.default.writeFileSync(tempPath, content, encoding);
    fs__default.default.renameSync(tempPath, filePath);
  } catch (error) {
    try {
      fs__default.default.unlinkSync(tempPath);
    } catch {
    }
    throw error;
  }
}
function syncGlobalCacheToLocal() {
  try {
    const globalJsonExists = fs__default.default.existsSync(GLOBAL_PROVIDER_REGISTRY_JSON());
    const globalDtsExists = fs__default.default.existsSync(GLOBAL_PROVIDER_TYPES_DTS());
    if (!globalJsonExists && !globalDtsExists) {
      return;
    }
    const packageRoot = getPackageRoot();
    const localJsonPath = path__default.default.join(packageRoot, "dist", "provider-registry.json");
    const localDtsPath = path__default.default.join(packageRoot, "dist", "llm", "model", "provider-types.generated.d.ts");
    fs__default.default.mkdirSync(path__default.default.dirname(localJsonPath), { recursive: true });
    fs__default.default.mkdirSync(path__default.default.dirname(localDtsPath), { recursive: true });
    if (globalJsonExists) {
      const globalJsonContent = fs__default.default.readFileSync(GLOBAL_PROVIDER_REGISTRY_JSON(), "utf-8");
      try {
        JSON.parse(globalJsonContent);
      } catch {
        try {
          fs__default.default.unlinkSync(GLOBAL_PROVIDER_REGISTRY_JSON());
        } catch {
        }
        return;
      }
      let shouldCopyJson = true;
      if (fs__default.default.existsSync(localJsonPath)) {
        const localJsonContent = fs__default.default.readFileSync(localJsonPath, "utf-8");
        shouldCopyJson = globalJsonContent !== localJsonContent;
      }
      if (shouldCopyJson) {
        atomicWriteFileSync(localJsonPath, globalJsonContent, "utf-8");
      }
    }
    if (globalDtsExists) {
      const globalDtsContent = fs__default.default.readFileSync(GLOBAL_PROVIDER_TYPES_DTS(), "utf-8");
      if (/readonly\s+\d/.test(globalDtsContent)) {
        try {
          fs__default.default.unlinkSync(GLOBAL_PROVIDER_TYPES_DTS());
        } catch {
        }
      } else {
        let shouldCopyDts = true;
        if (fs__default.default.existsSync(localDtsPath)) {
          const localDtsContent = fs__default.default.readFileSync(localDtsPath, "utf-8");
          shouldCopyDts = globalDtsContent !== localDtsContent;
        }
        if (shouldCopyDts) {
          atomicWriteFileSync(localDtsPath, globalDtsContent, "utf-8");
        }
      }
    }
  } catch {
  }
}
function getLastRefreshTimeFromDisk() {
  try {
    if (!fs__default.default.existsSync(CACHE_FILE())) {
      return null;
    }
    const timestamp = fs__default.default.readFileSync(CACHE_FILE(), "utf-8").trim();
    return new Date(parseInt(timestamp, 10));
  } catch (err) {
    console.warn("[GatewayRegistry] Failed to read cache file:", err);
    modelRouterCacheFailed = true;
    return null;
  }
}
function saveLastRefreshTimeToDisk(date) {
  try {
    if (!fs__default.default.existsSync(CACHE_DIR())) {
      fs__default.default.mkdirSync(CACHE_DIR(), { recursive: true });
    }
    fs__default.default.writeFileSync(CACHE_FILE(), date.getTime().toString(), "utf-8");
  } catch (err) {
    modelRouterCacheFailed = true;
    console.warn("[GatewayRegistry] Failed to write cache file:", err);
  }
}
function getPackageRoot() {
  try {
    const require2 = module$1.createRequire((typeof document === 'undefined' ? require('u' + 'rl').pathToFileURL(__filename).href : (_documentCurrentScript && _documentCurrentScript.tagName.toUpperCase() === 'SCRIPT' && _documentCurrentScript.src || new URL('chunk-DURT53SS.cjs', document.baseURI).href)) || "file://");
    const packageJsonPath = require2.resolve("@mastra/core/package.json");
    return path__default.default.dirname(packageJsonPath);
  } catch {
    return process.cwd();
  }
}
function loadRegistry(useDynamicLoading, customGateways = []) {
  const enabledGatewayIds = getEnabledGatewayIds([
    new chunkDBTKQ3U2_cjs.ModelsDevGateway({}),
    new chunkZMNN3DOV_cjs.NetlifyGateway(),
    new MastraGateway(),
    ...customGateways
  ]);
  if (!useDynamicLoading) {
    return sanitizeRegistryDataForRuntime(provider_registry_default, enabledGatewayIds);
  }
  syncGlobalCacheToLocal();
  if (registryData) {
    return registryData;
  }
  const packageRoot = getPackageRoot();
  const possiblePaths = [
    // Built: in dist/ relative to package root (first priority - what gets distributed)
    path__default.default.join(packageRoot, "dist", "provider-registry.json"),
    // Development: in src/ relative to package root
    path__default.default.join(packageRoot, "src", "llm", "model", "provider-registry.json"),
    // Fallback: relative to cwd (for monorepo setups)
    path__default.default.join(process.cwd(), "packages/core/src/llm/model/provider-registry.json"),
    path__default.default.join(process.cwd(), "src/llm/model/provider-registry.json")
  ];
  const errors = [];
  for (const jsonPath of possiblePaths) {
    try {
      const content = fs__default.default.readFileSync(jsonPath, "utf-8");
      const parsed = JSON.parse(content);
      registryData = sanitizeRegistryDataForRuntime(parsed, enabledGatewayIds);
      return registryData;
    } catch (err) {
      const errorMessage = err instanceof Error ? err.message : String(err);
      errors.push(`${jsonPath}: ${errorMessage}`);
      const isFileNotFound = err instanceof Error && "code" in err && err.code === "ENOENT";
      const isJsonParseError = err instanceof SyntaxError;
      if (!isFileNotFound && isJsonParseError) {
        console.warn(
          `[GatewayRegistry] Detected corrupted provider-registry.json at ${jsonPath}. Deleting corrupted file and falling back to static registry.`
        );
        try {
          fs__default.default.unlinkSync(jsonPath);
        } catch {
        }
        registryData = sanitizeRegistryDataForRuntime(provider_registry_default, enabledGatewayIds);
        return registryData;
      }
      continue;
    }
  }
  console.warn(
    `[GatewayRegistry] Could not load provider registry from any path. Falling back to static registry.
Tried paths:
${errors.join("\n")}`
  );
  registryData = sanitizeRegistryDataForRuntime(provider_registry_default, enabledGatewayIds);
  return registryData;
}
var PROVIDER_REGISTRY = new Proxy({}, {
  get(_target, prop) {
    const registry = GatewayRegistry.getInstance();
    const providers = registry.getProviders();
    return providers[prop];
  },
  ownKeys() {
    const registry = GatewayRegistry.getInstance();
    const providers = registry.getProviders();
    return Object.keys(providers);
  },
  has(_target, prop) {
    const registry = GatewayRegistry.getInstance();
    const providers = registry.getProviders();
    return prop in providers;
  },
  getOwnPropertyDescriptor(_target, prop) {
    const registry = GatewayRegistry.getInstance();
    const providers = registry.getProviders();
    if (prop in providers) {
      return {
        enumerable: true,
        configurable: true
      };
    }
    return void 0;
  }
});
var PROVIDER_MODELS = new Proxy({}, {
  get(_target, prop) {
    const registry = GatewayRegistry.getInstance();
    const models = registry.getModels();
    return models[prop];
  },
  ownKeys() {
    const registry = GatewayRegistry.getInstance();
    const models = registry.getModels();
    return Object.keys(models);
  },
  has(_target, prop) {
    const registry = GatewayRegistry.getInstance();
    const models = registry.getModels();
    return prop in models;
  },
  getOwnPropertyDescriptor(_target, prop) {
    const registry = GatewayRegistry.getInstance();
    const models = registry.getModels();
    if (prop in models) {
      return {
        enumerable: true,
        configurable: true
      };
    }
    return void 0;
  }
});
function parseModelString(modelString) {
  const firstSlashIndex = modelString.indexOf("/");
  if (firstSlashIndex !== -1) {
    const provider = modelString.substring(0, firstSlashIndex);
    const modelId = modelString.substring(firstSlashIndex + 1);
    if (provider && modelId) {
      return {
        provider,
        modelId
      };
    }
  }
  return {
    provider: null,
    modelId: modelString
  };
}
function getProviderConfig(providerId) {
  const registry = GatewayRegistry.getInstance();
  return registry.getProviderConfig(providerId);
}
function isProviderRegistered(providerId) {
  const registry = GatewayRegistry.getInstance();
  return registry.isProviderRegistered(providerId);
}
function getRegisteredProviders() {
  const registry = GatewayRegistry.getInstance();
  const providers = registry.getProviders();
  return Object.keys(providers);
}
var providerCapCache = /* @__PURE__ */ new Map();
function isDirectory(dir) {
  try {
    return fs__default.default.existsSync(dir) && fs__default.default.statSync(dir).isDirectory();
  } catch {
    return false;
  }
}
function findCapabilitiesDirs(useDynamicLoading) {
  const packageRoot = getPackageRoot();
  const distCapabilitiesDir = path__default.default.join(packageRoot, "dist", "capabilities");
  const sourceCapabilitiesDir = path__default.default.join(packageRoot, "src", "llm", "model", "capabilities");
  const workspaceSourceCapabilitiesDir = path__default.default.join(process.cwd(), "packages/core/src/llm/model/capabilities");
  const dirs = [];
  if (useDynamicLoading) {
    const globalCapDir = GLOBAL_CAPABILITIES_DIR();
    if (isDirectory(globalCapDir)) dirs.push(globalCapDir);
  }
  if (isDirectory(distCapabilitiesDir)) dirs.push(distCapabilitiesDir);
  if (isDirectory(sourceCapabilitiesDir)) dirs.push(sourceCapabilitiesDir);
  if (workspaceSourceCapabilitiesDir !== sourceCapabilitiesDir && isDirectory(workspaceSourceCapabilitiesDir)) {
    dirs.push(workspaceSourceCapabilitiesDir);
  }
  return dirs;
}
var capabilitiesDirCache;
function loadProviderAttachmentModels(provider, useDynamicLoading) {
  if (providerCapCache.has(provider)) return providerCapCache.get(provider);
  if (capabilitiesDirCache === void 0) {
    capabilitiesDirCache = findCapabilitiesDirs(useDynamicLoading);
  }
  for (const capabilitiesDir of capabilitiesDirCache) {
    const filePath = path__default.default.join(capabilitiesDir, `${provider}.json`);
    try {
      const content = fs__default.default.readFileSync(filePath, "utf-8");
      const data = JSON.parse(content);
      providerCapCache.set(provider, data.attachment);
      return data.attachment;
    } catch {
      continue;
    }
  }
  providerCapCache.set(provider, null);
  return null;
}
function getProviderAttachmentSupport(provider, modelId, useDynamicLoading) {
  const models = loadProviderAttachmentModels(provider, useDynamicLoading);
  if (!models) return void 0;
  return models.includes(modelId);
}
function modelSupportsAttachments(modelRouterId) {
  const { provider, modelId } = parseModelString(modelRouterId);
  if (!provider) return void 0;
  const registry = GatewayRegistry.getInstance();
  const useDynamicLoading = registry["useDynamicLoading"];
  const directSupport = getProviderAttachmentSupport(provider, modelId, useDynamicLoading);
  if (directSupport !== void 0) return directSupport;
  const nestedProviderDelimiter = modelId.indexOf("/");
  if (nestedProviderDelimiter !== -1) {
    const nestedProvider = modelId.substring(0, nestedProviderDelimiter);
    const nestedModelId = modelId.substring(nestedProviderDelimiter + 1);
    if (nestedProvider && nestedModelId) {
      const nestedSupport = getProviderAttachmentSupport(nestedProvider, nestedModelId, useDynamicLoading);
      if (nestedSupport !== void 0) return nestedSupport;
    }
  }
  return directSupport;
}
function isValidModelId(modelId) {
  const { provider } = parseModelString(modelId);
  return provider !== null && isProviderRegistered(provider);
}
var GatewayRegistry = class _GatewayRegistry {
  static instance = null;
  lastRefreshTime = null;
  refreshInterval = null;
  isRefreshing = false;
  useDynamicLoading;
  customGateways = [];
  constructor(options = {}) {
    const isDev2 = process.env.MASTRA_DEV === "true" || process.env.MASTRA_DEV === "1";
    this.useDynamicLoading = options.useDynamicLoading ?? isDev2;
  }
  /**
   * Get the singleton instance
   */
  static getInstance(options) {
    if (!_GatewayRegistry.instance) {
      _GatewayRegistry.instance = new _GatewayRegistry(options);
      return _GatewayRegistry.instance;
    }
    if (options?.useDynamicLoading === true) {
      _GatewayRegistry.instance.useDynamicLoading = true;
    }
    return _GatewayRegistry.instance;
  }
  /**
   * Register custom gateways for type generation
   * @param gateways - Array of custom gateway instances
   */
  registerCustomGateways(gateways) {
    this.customGateways = gateways;
  }
  /**
   * Get all registered custom gateways
   */
  getCustomGateways() {
    return this.customGateways;
  }
  /**
   * Sync providers from all gateways
   * Requires dynamic loading to be enabled (useDynamicLoading=true).
   * @param forceRefresh - Force refresh even if recently synced
   * @param writeToSrc - Write to src/ directory in addition to dist/ (useful for manual generation in repo)
   */
  async syncGateways(forceRefresh = false, writeToSrc = false) {
    if (!this.useDynamicLoading && !writeToSrc) {
      return;
    }
    if (isOfflineMode()) {
      return;
    }
    if (this.isRefreshing && !forceRefresh) {
      return;
    }
    this.isRefreshing = true;
    try {
      const { ModelsDevGateway: ModelsDevGateway2 } = await import('./models-dev-55YSMHB6.cjs');
      const { NetlifyGateway: NetlifyGateway2 } = await import('./netlify-UPFSCOO7.cjs');
      const { MastraGateway: MastraGateway2 } = await import('./mastra-SC7RDMUN.cjs');
      const { fetchProvidersFromGateways, writeRegistryFiles } = await import('./registry-generator-LJFBZ6Z3.cjs');
      const defaultGateways = [
        new ModelsDevGateway2({}),
        new NetlifyGateway2(),
        ...writeToSrc ? [] : [new MastraGateway2()]
      ];
      const gateways = [...defaultGateways, ...this.customGateways];
      const { providers, models, attachmentCapabilities } = await fetchProvidersFromGateways(gateways);
      const packageRoot = getPackageRoot();
      try {
        fs__default.default.mkdirSync(CACHE_DIR(), { recursive: true });
        await writeRegistryFiles(
          GLOBAL_PROVIDER_REGISTRY_JSON(),
          GLOBAL_PROVIDER_TYPES_DTS(),
          providers,
          models,
          attachmentCapabilities
        );
      } catch (error) {
        console.warn("[GatewayRegistry] Failed to write to global cache:", error);
      }
      const distJsonPath = path__default.default.join(packageRoot, "dist", "provider-registry.json");
      const distTypesPath = path__default.default.join(packageRoot, "dist", "llm", "model", "provider-types.generated.d.ts");
      await writeRegistryFiles(distJsonPath, distTypesPath, providers, models, attachmentCapabilities);
      const shouldWriteToSrc = writeToSrc;
      if (shouldWriteToSrc) {
        const srcJsonPath = path__default.default.join(packageRoot, "src", "llm", "model", "provider-registry.json");
        const srcTypesPath = path__default.default.join(packageRoot, "src", "llm", "model", "provider-types.generated.d.ts");
        await fs__default.default.promises.copyFile(distJsonPath, srcJsonPath);
        await fs__default.default.promises.copyFile(distTypesPath, srcTypesPath);
        const distCapDir = path__default.default.join(packageRoot, "dist", "capabilities");
        const srcCapDir = path__default.default.join(packageRoot, "src", "llm", "model", "capabilities");
        if (fs__default.default.existsSync(distCapDir)) {
          await fs__default.default.promises.mkdir(srcCapDir, { recursive: true });
          const capFiles = fs__default.default.readdirSync(distCapDir).filter((f) => f.endsWith(".json"));
          for (const file of capFiles) {
            await fs__default.default.promises.copyFile(path__default.default.join(distCapDir, file), path__default.default.join(srcCapDir, file));
          }
        }
      }
      if (this.useDynamicLoading) {
        registryData = null;
        providerCapCache.clear();
        capabilitiesDirCache = void 0;
      }
      this.lastRefreshTime = /* @__PURE__ */ new Date();
      saveLastRefreshTimeToDisk(this.lastRefreshTime);
    } catch {
    } finally {
      this.isRefreshing = false;
    }
  }
  /**
   * Get the last refresh time (from memory or disk cache)
   */
  getLastRefreshTime() {
    return this.lastRefreshTime || getLastRefreshTimeFromDisk();
  }
  /**
   * Start auto-refresh on an interval
   * Requires dynamic loading to be enabled (useDynamicLoading=true).
   * @param intervalMs - Interval in milliseconds (default: 1 hour)
   */
  startAutoRefresh(intervalMs = 60 * 60 * 1e3) {
    if (!this.useDynamicLoading) {
      return;
    }
    if (isOfflineMode()) {
      return;
    }
    if (this.refreshInterval) {
      return;
    }
    const lastRefresh = getLastRefreshTimeFromDisk();
    const now = Date.now();
    const shouldRefresh = !modelRouterCacheFailed && (!lastRefresh || now - lastRefresh.getTime() > intervalMs);
    if (shouldRefresh) {
      this.syncGateways().catch(() => {
      });
    }
    this.refreshInterval = setInterval(() => {
      if (modelRouterCacheFailed && this.refreshInterval) {
        clearInterval(this.refreshInterval);
        this.refreshInterval = null;
        return;
      }
      this.syncGateways().catch(() => {
      });
    }, intervalMs);
    if (this.refreshInterval.unref) {
      this.refreshInterval.unref();
    }
  }
  /**
   * Stop auto-refresh
   */
  stopAutoRefresh() {
    if (this.refreshInterval) {
      clearInterval(this.refreshInterval);
      this.refreshInterval = null;
    }
  }
  /**
   * Get provider configuration by ID
   */
  getProviderConfig(providerId) {
    const data = loadRegistry(this.useDynamicLoading, this.customGateways);
    return data.providers[providerId];
  }
  /**
   * Check if a provider is registered
   */
  isProviderRegistered(providerId) {
    const data = loadRegistry(this.useDynamicLoading, this.customGateways);
    return providerId in data.providers;
  }
  /**
   * Get all registered providers
   */
  getProviders() {
    const data = loadRegistry(this.useDynamicLoading, this.customGateways);
    return data.providers;
  }
  /**
   * Get all models
   */
  getModels() {
    return loadRegistry(this.useDynamicLoading, this.customGateways).models;
  }
};
var isDev = process.env.MASTRA_DEV === "true" || process.env.MASTRA_DEV === "1";
var autoRefreshEnabled = !isOfflineMode() && (process.env.MASTRA_AUTO_REFRESH_PROVIDERS === "true" || process.env.MASTRA_AUTO_REFRESH_PROVIDERS !== "false" && isDev);
if (autoRefreshEnabled) {
  GatewayRegistry.getInstance({ useDynamicLoading: isDev }).startAutoRefresh();
}

exports.AzureOpenAIGateway = AzureOpenAIGateway;
exports.GatewayRegistry = GatewayRegistry;
exports.MastraGateway = MastraGateway;
exports.PROVIDER_MODELS = PROVIDER_MODELS;
exports.PROVIDER_REGISTRY = PROVIDER_REGISTRY;
exports.createOpenAIWebSocketFetch = createOpenAIWebSocketFetch;
exports.findGatewayForModel = findGatewayForModel;
exports.getGatewayId = getGatewayId;
exports.getProviderConfig = getProviderConfig;
exports.getRegisteredProviders = getRegisteredProviders;
exports.isOfflineMode = isOfflineMode;
exports.isProviderRegistered = isProviderRegistered;
exports.isValidModelId = isValidModelId;
exports.modelSupportsAttachments = modelSupportsAttachments;
exports.parseModelString = parseModelString;
exports.shouldEnableGateway = shouldEnableGateway;
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