import { z } from "zod";
import {
  type SupportedProvider,
  SupportedProvidersSchema,
} from "./model-constants";

// =============================================================================
// Archestra-Normalized Internal Error Codes
// =============================================================================

/**
 * Archestra-normalized error codes emitted by an adapter's
 * `extractInternalCode` classifier. The value flows through
 * `ApiError.internalCode` → the `internal_code` field on the error response
 * body → the chat-error mapper, which uses it as a uniform cross-provider
 * signal.
 *
 * Providers differ in how they surface categories like "context too long":
 * some return a structured `error.code`, others only a message. Classifying
 * in the adapter and emitting a normalized code keeps the mapper a simple
 * lookup and lets each provider's idiosyncrasies stay local to its adapter.
 */
export const ArchestraInternalErrorCode = {
  ContextLengthExceeded: "context_length_exceeded",
} as const;

export type ArchestraInternalErrorCode =
  (typeof ArchestraInternalErrorCode)[keyof typeof ArchestraInternalErrorCode];

// =============================================================================
// Provider-Specific Error Types (from official documentation)
// =============================================================================

/**
 * OpenAI API error types (from response body `error.type` field)
 * @see https://platform.openai.com/docs/guides/error-codes
 */
export const OpenAIErrorTypes = {
  INVALID_REQUEST: "invalid_request_error",
  AUTHENTICATION: "authentication_error",
  INVALID_API_KEY: "invalid_api_key",
  PERMISSION_DENIED: "insufficient_quota", // OpenAI uses this for permission issues
  NOT_FOUND: "not_found_error",
  CONFLICT: "conflict_error",
  UNPROCESSABLE_ENTITY: "unprocessable_entity_error",
  RATE_LIMIT: "rate_limit_exceeded",
  SERVER_ERROR: "server_error",
  SERVICE_UNAVAILABLE: "service_unavailable",
  API_VALIDATION_ERROR: "api_validation_error",
  // Additional codes that appear in error.code field
  INVALID_API_KEY_CODE: "invalid_api_key",
  MODEL_NOT_FOUND: "model_not_found",
  CONTEXT_LENGTH_EXCEEDED: "context_length_exceeded",
} as const;

/**
 * Anthropic API error types (from response body `error.type` field)
 * @see https://docs.anthropic.com/en/api/errors
 */
export const AnthropicErrorTypes = {
  INVALID_REQUEST: "invalid_request_error",
  AUTHENTICATION: "authentication_error",
  PERMISSION: "permission_error",
  NOT_FOUND: "not_found_error",
  REQUEST_TOO_LARGE: "request_too_large",
  RATE_LIMIT: "rate_limit_error",
  API_ERROR: "api_error",
  OVERLOADED: "overloaded_error",
} as const;

/**
 * Gemini/Vertex AI gRPC status codes (from response body `error.status` field)
 * @see https://ai.google.dev/gemini-api/docs/troubleshooting
 * @see https://cloud.google.com/apis/design/errors
 */
export const GeminiErrorCodes = {
  INVALID_ARGUMENT: "INVALID_ARGUMENT",
  UNAUTHENTICATED: "UNAUTHENTICATED",
  PERMISSION_DENIED: "PERMISSION_DENIED",
  NOT_FOUND: "NOT_FOUND",
  RESOURCE_EXHAUSTED: "RESOURCE_EXHAUSTED",
  INTERNAL: "INTERNAL",
  UNAVAILABLE: "UNAVAILABLE",
  // Additional codes for specific scenarios
  FAILED_PRECONDITION: "FAILED_PRECONDITION",
  OUT_OF_RANGE: "OUT_OF_RANGE",
  DEADLINE_EXCEEDED: "DEADLINE_EXCEEDED",
} as const;

/**
 * vLLM API error types
 * vLLM uses OpenAI-compatible error format, so types are similar to OpenAI.
 * @see https://docs.vllm.ai/en/latest/features/openai_api.html
 */
export const VllmErrorTypes = {
  INVALID_REQUEST: "invalid_request_error",
  AUTHENTICATION: "authentication_error",
  INVALID_API_KEY: "invalid_api_key",
  NOT_FOUND: "not_found_error",
  SERVER_ERROR: "server_error",
  SERVICE_UNAVAILABLE: "service_unavailable",
  // vLLM-specific error codes
  MODEL_NOT_LOADED: "model_not_loaded",
  CONTEXT_LENGTH_EXCEEDED: "context_length_exceeded",
} as const;

/**
 * AWS Bedrock Converse API exception types (from response body `__type` field)
 * @see https://docs.aws.amazon.com/bedrock/latest/APIReference/API_runtime_Converse.html
 */
export const BedrockErrorTypes = {
  ACCESS_DENIED: "AccessDeniedException",
  INTERNAL_SERVER: "InternalServerException",
  MODEL_ERROR: "ModelErrorException",
  MODEL_NOT_READY: "ModelNotReadyException",
  MODEL_TIMEOUT: "ModelTimeoutException",
  RESOURCE_NOT_FOUND: "ResourceNotFoundException",
  SERVICE_UNAVAILABLE: "ServiceUnavailableException",
  THROTTLING: "ThrottlingException",
  VALIDATION: "ValidationException",
} as const;

/**
 * Ollama API error types
 * Ollama uses OpenAI-compatible error format, so types are similar to OpenAI.
 * @see https://github.com/ollama/ollama/blob/main/docs/openai.md
 */
export const OllamaErrorTypes = {
  INVALID_REQUEST: "invalid_request_error",
  AUTHENTICATION: "authentication_error",
  INVALID_API_KEY: "invalid_api_key",
  NOT_FOUND: "not_found_error",
  SERVER_ERROR: "server_error",
  SERVICE_UNAVAILABLE: "service_unavailable",
  // Ollama-specific error codes
  MODEL_NOT_FOUND: "model_not_found",
  CONTEXT_LENGTH_EXCEEDED: "context_length_exceeded",
} as const;

/**
 * Gemini/Vertex AI ErrorInfo reason codes (from `error.details[].reason` field)
 * These provide more specific error reasons extracted from google.rpc.ErrorInfo.
 *
 * @see https://cloud.google.com/apis/design/errors#error_info
 * @see https://googleapis.dev/nodejs/spanner/latest/google.rpc.ErrorInfo.html
 */
export const GeminiErrorReasons = {
  // Authentication/Authorization reasons
  API_KEY_INVALID: "API_KEY_INVALID",
  API_KEY_NOT_FOUND: "API_KEY_NOT_FOUND",
  API_KEY_EXPIRED: "API_KEY_EXPIRED",
  ACCESS_TOKEN_EXPIRED: "ACCESS_TOKEN_EXPIRED",
  ACCESS_TOKEN_INVALID: "ACCESS_TOKEN_INVALID",
  SERVICE_ACCOUNT_INVALID: "SERVICE_ACCOUNT_INVALID",

  // Quota/Rate limit reasons
  RATE_LIMIT_EXCEEDED: "RATE_LIMIT_EXCEEDED",
  RESOURCE_EXHAUSTED: "RESOURCE_EXHAUSTED",
  QUOTA_EXCEEDED: "QUOTA_EXCEEDED",

  // Resource reasons
  MODEL_NOT_FOUND: "MODEL_NOT_FOUND",
  RESOURCE_NOT_FOUND: "RESOURCE_NOT_FOUND",

  // Content/Safety reasons
  SAFETY_BLOCKED: "SAFETY_BLOCKED",
  RECITATION_BLOCKED: "RECITATION_BLOCKED",
  CONTENT_FILTERED: "CONTENT_FILTERED",

  // Request reasons
  INVALID_ARGUMENT: "INVALID_ARGUMENT",
  CONTEXT_LENGTH_EXCEEDED: "CONTEXT_LENGTH_EXCEEDED",
} as const;

/**
 * DeepSeek API error types
 * DeepSeek uses OpenAI-compatible error format.
 * @see https://api-docs.deepseek.com/
 */
export const DeepSeekErrorTypes = {
  INVALID_REQUEST: "invalid_request_error",
  AUTHENTICATION: "authentication_error",
  INVALID_API_KEY: "invalid_api_key",
  NOT_FOUND: "not_found_error",
  RATE_LIMIT: "rate_limit_exceeded",
  SERVER_ERROR: "server_error",
  SERVICE_UNAVAILABLE: "service_unavailable",
  MODEL_NOT_FOUND: "model_not_found",
  CONTEXT_LENGTH_EXCEEDED: "context_length_exceeded",
} as const;

/**
 * Zhipuai API error codes (from response body `error.code` field)
 * Zhipuai uses numeric string codes for errors
 * @see https://docs.z.ai/api-reference/api-code#errors
 */
export const ZhipuaiErrorTypes = {
  // Basic errors
  INTERNAL_ERROR: "500",

  // Authentication errors (1000-1004)
  AUTHENTICATION_FAILED: "1000",
  INVALID_AUTH_TOKEN: "1002",
  AUTH_TOKEN_EXPIRED: "1003",

  // Account errors (1110-1121)
  ACCOUNT_LOCKED: "1112",
  INSUFFICIENT_BALANCE: "1113",

  // API call errors (1200-1234)
  INVALID_API_PARAMETERS: "1210",
  MODEL_NOT_FOUND: "1211",
  INVALID_PARAMETER: "1214",
  NO_PERMISSION: "1220",
  API_OFFLINE: "1221",
  NETWORK_ERROR: "1234",
  CONTEXT_LENGTH_EXCEEDED: "1261", // "Prompt exceeds max length"

  // Policy block errors (1300-1309)
  CONTENT_FILTERED: "1301", // Unsafe or sensitive content detected
  HIGH_CONCURRENCY: "1302",
  HIGH_FREQUENCY: "1303",
  RATE_LIMIT: "1305",
} as const;

/**
 * MiniMax API error types
 * MiniMax uses OpenAI-compatible error format, so types are similar to OpenAI.
 * @see https://www.minimax.io/platform/document/api-reference
 */
export const MinimaxErrorTypes = {
  INVALID_REQUEST: "invalid_request_error",
  AUTHENTICATION: "authentication_error",
  INVALID_API_KEY: "invalid_api_key",
  PERMISSION_DENIED: "insufficient_quota",
  INSUFFICIENT_BALANCE: "insufficient_balance_error", // MiniMax error 1008
  NOT_FOUND: "not_found_error",
  RATE_LIMIT: "rate_limit_exceeded",
  SERVER_ERROR: "server_error",
  SERVICE_UNAVAILABLE: "service_unavailable",
  // Additional codes that appear in error.code field
  MODEL_NOT_FOUND: "model_not_found",
  CONTEXT_LENGTH_EXCEEDED: "context_length_exceeded",
} as const;

// =============================================================================
// Normalized Chat Error Codes
// =============================================================================

/**
 * Normalized error codes for chat errors across all LLM providers.
 * These provide a consistent set of error categories regardless of the underlying provider.
 */
export enum ChatErrorCode {
  /** Rate/quota exceeded - retryable after delay */
  RateLimit = "rate_limit",
  /** Invalid or missing API key */
  Authentication = "authentication",
  /** API key lacks permissions for the requested resource */
  PermissionDenied = "permission_denied",
  /** Malformed or invalid request */
  InvalidRequest = "invalid_request",
  /** Model or resource not found */
  NotFound = "not_found",
  /** Input exceeds the model's context window */
  ContextTooLong = "context_too_long",
  /** Content blocked by safety filters */
  ContentFiltered = "content_filtered",
  /** Provider server error - retryable */
  ServerError = "server_error",
  /** Network/connection issues - retryable */
  NetworkError = "network_error",
  /** Catch-all for unrecognized errors */
  Unknown = "unknown",
}

/**
 * User-friendly error messages for each error code
 */
export const ChatErrorMessages: Record<ChatErrorCode, string> = {
  [ChatErrorCode.RateLimit]:
    "Too many requests. Please wait a moment and try again.",
  [ChatErrorCode.Authentication]:
    "Invalid API key. Please check your Chat Settings.",
  [ChatErrorCode.PermissionDenied]:
    "Your API key doesn't have permission for this model.",
  [ChatErrorCode.InvalidRequest]:
    "There was an issue with your request. Please try again.",
  [ChatErrorCode.NotFound]:
    "The selected model is not available. Please choose a different model.",
  [ChatErrorCode.ContextTooLong]:
    "Your conversation is too long. Please start a new chat or remove some messages.",
  [ChatErrorCode.ContentFiltered]:
    "Your message was blocked by content filters. Please rephrase your request.",
  [ChatErrorCode.ServerError]: "The AI provider is experiencing issues.",
  [ChatErrorCode.NetworkError]:
    "Connection error. Please check your network and try again.",
  [ChatErrorCode.Unknown]: "An unexpected error occurred. Please try again.",
};

/**
 * Error codes that indicate the operation can be retried
 */
export const RetryableErrorCodes: Set<ChatErrorCode> = new Set([
  ChatErrorCode.RateLimit,
  ChatErrorCode.ServerError,
  ChatErrorCode.NetworkError,
]);

/**
 * Structured error response returned by the chat API for error conditions.
 * Provides both user-friendly messaging and technical details for debugging.
 */
export interface ChatErrorResponse {
  /** Normalized error code */
  code: ChatErrorCode;
  /** User-friendly error message */
  message: string;
  /** Whether the operation can be retried */
  isRetryable: boolean;
  /** Session ID for correlating the error with backend logs and traces */
  sessionId?: string;
  /** OpenTelemetry trace ID for correlating with backend logs */
  traceId?: string;
  /** OpenTelemetry span ID for correlating with backend logs */
  spanId?: string;
  /** Original error details for debugging (provider-specific) */
  originalError?: {
    /** Provider name (anthropic, openai, gemini) */
    provider?: SupportedProvider;
    /** HTTP status code if applicable */
    status?: number;
    /** Original error message from provider */
    message?: string;
    /** Error type from provider */
    type?: string;
    /** Full error object for detailed debugging */
    raw?: unknown;
  };
}

export const ChatErrorResponseSchema: z.ZodType<ChatErrorResponse> = z.object({
  code: z.nativeEnum(ChatErrorCode),
  message: z.string(),
  isRetryable: z.boolean(),
  sessionId: z.string().optional(),
  traceId: z.string().optional(),
  spanId: z.string().optional(),
  originalError: z
    .object({
      provider: SupportedProvidersSchema.optional(),
      status: z.number().optional(),
      message: z.string().optional(),
      type: z.string().optional(),
      raw: z.unknown().optional(),
    })
    .optional(),
});

/**
 * Type guard to check if an object is a ChatErrorResponse
 */
export function isChatErrorResponse(obj: unknown): obj is ChatErrorResponse {
  if (typeof obj !== "object" || obj === null) {
    return false;
  }
  const response = obj as ChatErrorResponse;
  return (
    typeof response.code === "string" &&
    Object.values(ChatErrorCode).includes(response.code as ChatErrorCode) &&
    typeof response.message === "string" &&
    typeof response.isRetryable === "boolean"
  );
}
