import type { LanguageModelV2 } from '@ai-sdk/provider-v5';
import type { CoreMessage as CoreMessageV4 } from '../_types/@internal_ai-sdk-v4/dist/index.js';
import type { CallSettings, StepResult, ToolChoice } from '../_types/@internal_ai-sdk-v5/dist/index.js';
import type { MessageList, MastraDBMessage } from '../agent/message-list/index.js';
import type { TripWireOptions } from '../agent/trip-wire.js';
import type { ModelRouterModelId } from '../llm/model/index.js';
import type { MastraLanguageModel, OpenAICompatibleConfig, SharedProviderOptions } from '../llm/model/shared.types.js';
import type { Mastra } from '../mastra/index.js';
import type { ObservabilityContext } from '../observability/index.js';
import type { RequestContext } from '../request-context/index.js';
import type { InferStandardSchemaOutput, StandardSchemaWithJSON } from '../schema/index.js';
import type { ChunkType } from '../stream/index.js';
import type { DataChunkType, LanguageModelUsage, LLMStepResult } from '../stream/types.js';
import type { Workflow } from '../workflows/index.js';
import type { StructuredOutputOptions } from './processors/index.js';
import type { ProcessorStepOutput } from './step-schema.js';
/**
 * Writer interface for processors to emit custom data chunks to the stream.
 * This enables real-time streaming of processor-specific data (e.g., observation markers).
 */
export interface ProcessorStreamWriter {
    /**
     * Emit a custom data chunk to the stream.
     * The chunk type must start with 'data-' prefix.
     * @param data - The data chunk to emit
     */
    custom<T extends {
        type: string;
    }>(data: T extends {
        type: `data-${string}`;
    } ? DataChunkType : T): Promise<void>;
}
/**
 * Base context shared by all processor methods
 */
export interface ProcessorContext<TTripwireMetadata = unknown> extends Partial<ObservabilityContext> {
    /**
     * Function to abort processing with an optional reason and options.
     * @param reason - The reason for aborting
     * @param options - Options including retry flag and metadata
     */
    abort: (reason?: string, options?: TripWireOptions<TTripwireMetadata>) => never;
    /** Optional runtime context with execution metadata */
    requestContext?: RequestContext;
    /**
     * Number of times processors have triggered retry for this generation.
     * Use this to implement retry limits within your processor.
     */
    retryCount: number;
    /**
     * Optional stream writer for emitting custom data chunks.
     * Available when the agent is streaming and outputWriter is provided.
     * Use writer.custom() to emit data-* chunks that will be streamed to the client.
     */
    writer?: ProcessorStreamWriter;
    /**
     * Optional abort signal from the parent agent execution.
     * Processors should pass this to any long-running operations (e.g., LLM calls)
     * so they can be canceled when the parent agent is aborted.
     */
    abortSignal?: AbortSignal;
}
/**
 * Context for message-based processor methods (processInput, processOutputResult, processInputStep)
 */
export interface ProcessorMessageContext<TTripwireMetadata = unknown> extends ProcessorContext<TTripwireMetadata> {
    /** The current messages being processed */
    messages: MastraDBMessage[];
    /** MessageList instance for managing message sources */
    messageList: MessageList;
}
/**
 * Return type for processInput that includes modified system messages
 */
export interface ProcessInputResultWithSystemMessages {
    messages: MastraDBMessage[];
    systemMessages: CoreMessageV4[];
}
/**
 * Return type for message-based processor methods
 * - MessageList: Return the same messageList instance passed in (indicates you've mutated it)
 * - MastraDBMessage[]: Return transformed messages array (for simple transformations)
 */
export type ProcessorMessageResult = Promise<MessageList | MastraDBMessage[]> | MessageList | MastraDBMessage[];
/**
 * Possible return types from processInput
 */
export type ProcessInputResult = MessageList | MastraDBMessage[] | ProcessInputResultWithSystemMessages;
/**
 * Arguments for processInput method
 */
export interface ProcessInputArgs<TTripwireMetadata = unknown> extends ProcessorMessageContext<TTripwireMetadata> {
    /** All system messages (agent instructions, user-provided, memory) for read/modify access */
    systemMessages: CoreMessageV4[];
    /** Per-processor state that persists across all method calls within this request */
    state: Record<string, unknown>;
}
/**
 * Resolved generation result passed to processOutputResult.
 * Contains the same data available in the onFinish callback.
 */
export interface OutputResult {
    /** The accumulated text from all steps */
    text: string;
    /** Token usage (cumulative across all steps) */
    usage: LanguageModelUsage;
    /** Why the generation finished (e.g. 'stop', 'tool-calls', 'length') */
    finishReason: string;
    /** All LLM step results (each contains text, toolCalls, toolResults, usage, sources, files, reasoning, etc.) */
    steps: LLMStepResult[];
}
/**
 * Arguments for processOutputResult method
 */
export interface ProcessOutputResultArgs<TTripwireMetadata = unknown> extends ProcessorMessageContext<TTripwireMetadata> {
    /** Per-processor state that persists across all method calls within this request */
    state: Record<string, unknown>;
    /** Resolved generation result with usage, text, steps, and finish reason */
    result: OutputResult;
}
/**
 * Arguments for processInputStep method
 *
 * Note: structuredOutput.schema is typed as OutputSchema (not the specific OUTPUT type) because
 * processors run in a chain and any previous processor may have modified structuredOutput.
 * The actual schema type is only known at the generate()/stream() call site.
 */
export interface ProcessInputStepArgs<TTripwireMetadata = unknown> extends ProcessorMessageContext<TTripwireMetadata> {
    /** The current step number (0-indexed) */
    stepNumber: number;
    steps: Array<StepResult<any>>;
    /** The active assistant response message ID for this step, when this processor is running inside an agent loop */
    messageId?: string;
    /** Mark the current assistant response message ID as complete and rotate to a fresh one, when supported by the caller */
    rotateResponseMessageId?: () => string;
    /** All system messages (agent instructions, user-provided, memory) for read/modify access */
    systemMessages: CoreMessageV4[];
    /** Per-processor state that persists across all method calls within this request */
    state: Record<string, unknown>;
    /**
     * Current model for this step.
     * Can be a resolved MastraLanguageModelV2 or an unresolved config (string, OpenAI-compatible config).
     */
    model: MastraLanguageModel;
    /** Current tools available for this step */
    tools?: Record<string, unknown>;
    toolChoice?: ToolChoice<any>;
    activeTools?: string[];
    providerOptions?: SharedProviderOptions;
    modelSettings?: Omit<CallSettings, 'abortSignal'>;
    /**
     * Structured output configuration. The schema type is StandardSchemaWithJSON (not the specific OUTPUT)
     * because processors can modify it, and the actual type is only known at runtime.
     */
    structuredOutput?: StructuredOutputOptions<InferStandardSchemaOutput<StandardSchemaWithJSON>>;
    /**
     * Number of times processors have triggered retry for this generation.
     * Use this to implement retry limits within your processor.
     */
    retryCount: number;
}
export type RunProcessInputStepArgs = Omit<ProcessInputStepArgs, 'messages' | 'systemMessages' | 'abort' | 'state' | 'messageId' | 'rotateResponseMessageId' | 'retryCount'> & {
    messageId?: string;
    rotateResponseMessageId?: () => string;
    retryCount?: number;
};
/**
 * Result from processInputStep method
 *
 * Note: structuredOutput.schema is typed as StandardSchemaWithJSON (not the specific OUTPUT type) because
 * processors can modify it dynamically, and the actual type is only known at runtime.
 */
export type ProcessInputStepResult = {
    model?: LanguageModelV2 | ModelRouterModelId | OpenAICompatibleConfig | MastraLanguageModel;
    /** Override the active assistant response message ID for this step */
    messageId?: string;
    /** Replace tools for this step - accepts both AI SDK tools and Mastra createTool results */
    tools?: Record<string, unknown>;
    toolChoice?: ToolChoice<any>;
    activeTools?: string[];
    messages?: MastraDBMessage[];
    messageList?: MessageList;
    /** Replace all system messages with these */
    systemMessages?: CoreMessageV4[];
    providerOptions?: SharedProviderOptions;
    modelSettings?: Omit<CallSettings, 'abortSignal'>;
    /**
     * Structured output configuration. The schema type is StandardSchemaWithJSON (not the specific OUTPUT)
     * because processors can modify it, and the actual type is only known at runtime.
     */
    structuredOutput?: StructuredOutputOptions<InferStandardSchemaOutput<StandardSchemaWithJSON>>;
    /**
     * Number of times processors have triggered retry for this generation.
     * Use this to implement retry limits within your processor.
     */
    retryCount?: number;
};
export type RunProcessInputStepResult = Omit<ProcessInputStepResult, 'model'> & {
    model?: MastraLanguageModel;
};
/**
 * Arguments for processOutputStream method
 */
export interface ProcessOutputStreamArgs<TTripwireMetadata = unknown> extends ProcessorContext<TTripwireMetadata> {
    /** The current chunk being processed */
    part: ChunkType;
    /** All chunks seen so far */
    streamParts: ChunkType[];
    /** Mutable state object that persists across chunks */
    state: Record<string, unknown>;
    /** Optional MessageList instance for accessing conversation history */
    messageList?: MessageList;
}
/**
 * Tool call information for processOutputStep
 */
export interface ToolCallInfo {
    toolName: string;
    toolCallId: string;
    args: unknown;
}
/**
 * Arguments for processOutputStep method.
 * Called after each LLM response in the agentic loop, before tool execution.
 */
export interface ProcessOutputStepArgs<TTripwireMetadata = unknown> extends ProcessorMessageContext<TTripwireMetadata> {
    /** The current step number (0-indexed) */
    stepNumber: number;
    /** The finish reason from the LLM (stop, tool-use, length, etc.) */
    finishReason?: string;
    /** Tool calls made in this step (if any) */
    toolCalls?: ToolCallInfo[];
    /** Generated text from this step */
    text?: string;
    /** All system messages */
    systemMessages: CoreMessageV4[];
    /** All completed steps so far (including the current step) */
    steps: Array<StepResult<any>>;
    /** Mutable state object that persists across steps */
    state: Record<string, unknown>;
}
/**
 * Arguments for processAPIError method.
 * Called when the LLM API call fails with a non-retryable error (API rejection).
 * This is distinct from network errors or retryable server errors (which are handled by p-retry).
 */
export interface ProcessAPIErrorArgs<TTripwireMetadata = unknown> extends ProcessorMessageContext<TTripwireMetadata> {
    /** The error that occurred during the LLM API call */
    error: unknown;
    /** The current step number (0-indexed) */
    stepNumber: number;
    /** All completed steps so far */
    steps: Array<StepResult<any>>;
    /** The active assistant response message ID for this step, when this processor is running inside an agent loop */
    messageId?: string;
    /** Mark the current assistant response message ID as complete and rotate to a fresh one, when supported by the caller */
    rotateResponseMessageId?: () => string;
    /** Per-processor state that persists across all method calls within this request */
    state: Record<string, unknown>;
    /** The current retry count for this error handler */
    retryCount: number;
}
/**
 * Result from processAPIError method.
 */
export type ProcessAPIErrorResult = {
    /** Whether to retry the LLM call after applying modifications */
    retry: boolean;
};
/**
 * Processor interface for transforming messages and stream chunks.
 *
 * @template TId - The processor's unique identifier type
 * @template TTripwireMetadata - The type of metadata passed when calling abort()
 */
export interface Processor<TId extends string = string, TTripwireMetadata = unknown> {
    readonly id: TId;
    readonly name?: string;
    readonly description?: string;
    /** Index of this processor in the workflow (set at runtime when combining processors) */
    processorIndex?: number;
    /** When true, this processor will also receive `data-*` chunks in processOutputStream. Default: false. */
    processDataParts?: boolean;
    /**
     * Process input messages before they are sent to the LLM
     *
     * @returns Either:
     *  - MessageList: The same messageList instance passed in (indicates you've mutated it)
     *  - MastraDBMessage[]: Transformed messages array (for simple transformations)
     *  - { messages, systemMessages }: Object with both messages and modified system messages
     */
    processInput?(args: ProcessInputArgs<TTripwireMetadata>): Promise<ProcessInputResult> | ProcessInputResult;
    /**
     * Process output stream chunks with built-in state management
     * This allows processors to accumulate chunks and make decisions based on larger context
     * Return null or undefined to skip emitting the part
     */
    processOutputStream?(args: ProcessOutputStreamArgs<TTripwireMetadata>): Promise<ChunkType | null | undefined>;
    /**
     * Process the complete output result after streaming/generate is finished
     *
     * @returns Either:
     *  - MessageList: The same messageList instance passed in (indicates you've mutated it)
     *  - MastraDBMessage[]: Transformed messages array (for simple transformations)
     */
    processOutputResult?(args: ProcessOutputResultArgs<TTripwireMetadata>): ProcessorMessageResult;
    /**
     * Process input messages at each step of the agentic loop, before they are sent to the LLM.
     * Unlike processInput which runs once at the start, this runs at every step (including tool call continuations).
     *
     * @returns Either:
     *  - ProcessInputStepResult object with model, toolChoice, messages, etc.
     *  - MessageList: The same messageList instance passed in (indicates you've mutated it)
     *  - MastraDBMessage[]: Transformed messages array (for simple transformations)
     *  - undefined/void: No changes
     */
    processInputStep?(args: ProcessInputStepArgs<TTripwireMetadata>): Promise<ProcessInputStepResult | MessageList | MastraDBMessage[] | undefined | void> | ProcessInputStepResult | MessageList | MastraDBMessage[] | void | undefined;
    /**
     * Process output after each LLM response in the agentic loop, before tool execution.
     * Unlike processOutputResult which runs once at the end, this runs at every step.
     *
     * This is the ideal place to implement guardrails that can trigger retries:
     * - Validate tone, format, or content of LLM responses
     * - Check for policy violations before tools are executed
     * - Implement self-correction by calling abort({ retry: true })
     *
     * @returns Either:
     *  - MessageList: The same messageList instance passed in (indicates you've mutated it)
     *  - MastraDBMessage[]: Transformed messages array (for simple transformations)
     */
    processOutputStep?(args: ProcessOutputStepArgs<TTripwireMetadata>): ProcessorMessageResult;
    /**
     * Process an LLM API rejection error before it's surfaced as a final error.
     * Only called for non-retryable API rejections (e.g., 400/422 status codes),
     * NOT for network errors or retryable server errors (which are handled by p-retry).
     *
     * This allows processors to inspect the error, modify the request (e.g., append messages),
     * and signal a retry. Unlike processOutputStep which runs after successful responses,
     * this runs when the API call is rejected.
     *
     * @returns ProcessAPIErrorResult indicating whether to retry with the modified state,
     *          or void/undefined to not handle the error
     */
    processAPIError?(args: ProcessAPIErrorArgs<TTripwireMetadata>): Promise<ProcessAPIErrorResult | void> | ProcessAPIErrorResult | void;
    /**
     * Internal method called when the processor is registered with a Mastra instance.
     * This allows processors to access Mastra services like knowledge, storage, etc.
     * @internal
     */
    __registerMastra?(mastra: Mastra<any, any, any, any, any, any, any, any, any, any>): void;
}
/**
 * Base class for processors that need access to Mastra services.
 * Extend this class to automatically get access to the Mastra instance
 * when the processor is registered with an agent.
 *
 * @example
 * ```typescript
 * class MyProcessor extends BaseProcessor<'my-processor'> {
 *   readonly id = 'my-processor';
 *
 *   async processInput(args: ProcessInputArgs) {
 *     // Access Mastra services via this.mastra
 *     const knowledge = this.mastra?.getKnowledge();
 *     // ...
 *   }
 * }
 * ```
 */
export declare abstract class BaseProcessor<TId extends string = string, TTripwireMetadata = unknown> implements Processor<TId, TTripwireMetadata> {
    abstract readonly id: TId;
    readonly name?: string;
    /**
     * The Mastra instance this processor is registered with.
     * Available after the processor is registered via __registerMastra.
     */
    protected mastra?: Mastra<any, any, any, any, any, any, any, any, any, any>;
    /**
     * Called when the processor is registered with a Mastra instance.
     * @internal
     */
    __registerMastra(mastra: Mastra<any, any, any, any, any, any, any, any, any, any>): void;
}
type WithRequired<T, K extends keyof T> = T & {
    [P in K]-?: NonNullable<T[P]>;
};
export type InputProcessor<TTripwireMetadata = unknown> = (WithRequired<Processor<string, TTripwireMetadata>, 'id' | 'processInput'> & Processor<string, TTripwireMetadata>) | (WithRequired<Processor<string, TTripwireMetadata>, 'id' | 'processInputStep'> & Processor<string, TTripwireMetadata>);
export type OutputProcessor<TTripwireMetadata = unknown> = (WithRequired<Processor<string, TTripwireMetadata>, 'id' | 'processOutputStream'> & Processor<string, TTripwireMetadata>) | (WithRequired<Processor<string, TTripwireMetadata>, 'id' | 'processOutputResult'> & Processor<string, TTripwireMetadata>) | (WithRequired<Processor<string, TTripwireMetadata>, 'id' | 'processOutputStep'> & Processor<string, TTripwireMetadata>);
export type ErrorProcessor<TTripwireMetadata = unknown> = WithRequired<Processor<string, TTripwireMetadata>, 'id' | 'processAPIError'> & Processor<string, TTripwireMetadata>;
export type ProcessorTypes<TTripwireMetadata = unknown> = InputProcessor<TTripwireMetadata> | OutputProcessor<TTripwireMetadata> | ErrorProcessor<TTripwireMetadata>;
/**
 * A Workflow that can be used as a processor.
 * The workflow must accept ProcessorStepInput and return ProcessorStepOutput.
 */
export type ProcessorWorkflow = Workflow<any, any, string, any, ProcessorStepOutput, ProcessorStepOutput, any>;
/**
 * Input processor config: can be a Processor or a Workflow.
 */
export type InputProcessorOrWorkflow<TTripwireMetadata = unknown> = InputProcessor<TTripwireMetadata> | ProcessorWorkflow;
/**
 * Output processor config: can be a Processor or a Workflow.
 */
export type OutputProcessorOrWorkflow<TTripwireMetadata = unknown> = OutputProcessor<TTripwireMetadata> | ProcessorWorkflow;
/**
 * Error processor config: must be a processor with processAPIError.
 * Workflows are not supported because LLM API rejection handling only invokes processor methods.
 */
export type ErrorProcessorOrWorkflow<TTripwireMetadata = unknown> = ErrorProcessor<TTripwireMetadata>;
/**
 * Type guard to check if an object is a Workflow that can be used as a processor.
 * A ProcessorWorkflow must have 'id', 'inputSchema', 'outputSchema', and 'execute' properties.
 */
export declare function isProcessorWorkflow(obj: unknown): obj is ProcessorWorkflow;
export * from './processors/index.js';
export { PrefillErrorHandler } from './prefill-error-handler.js';
export { ProcessorState, ProcessorRunner } from './runner.js';
export * from './memory/index.js';
export type { TripWireOptions } from '../agent/trip-wire.js';
export { ProcessorStepSchema, ProcessorStepInputSchema, ProcessorStepOutputSchema, ProcessorInputPhaseSchema, ProcessorInputStepPhaseSchema, ProcessorOutputStreamPhaseSchema, ProcessorOutputResultPhaseSchema, ProcessorOutputStepPhaseSchema, ProcessorMessageSchema, ProcessorMessageContentSchema, MessageContentSchema, MessagePartSchema, TextPartSchema, ImagePartSchema, FilePartSchema, ToolInvocationPartSchema, ReasoningPartSchema, SourcePartSchema, StepStartPartSchema, } from './step-schema.js';
export type { ProcessorStepData, ProcessorStepDataFlexible, ProcessorStepInput, ProcessorStepOutput, ProcessorMessage, MessageContent, MessagePart, } from './step-schema.js';
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