import type { Span } from '@opentelemetry/api';
import type { AgentInternalTool } from '../AgentTool/types';
import type { AgentLLMIntegrationOutput } from '../Integrations/types';
import type { IMCPClient } from '../interfaces.mcp';
import type { OtelInfoType } from '../types';
import type { AgentMessage, AgentServiceContract, AgentToolCallContent, AgentToolDefinition } from './types.js';
/**
 * Transforms a map of Arvo Service Contracts into LLM-compatible Tool Definitions.
 *
 * This function extracts the `accepts` schema from the contract, strips out internal
 * Arvo fields (like `parentSubject$$`), and formats it for the LLM's context window.
 */
export declare const generateServiceToolDefinitions: <TServiceContract extends Record<string, AgentServiceContract>>(services: TServiceContract) => { [K in keyof TServiceContract]: AgentToolDefinition<TServiceContract[K]["contract"]>; };
/**
 * Fetches available tools from a connected MCP Client and adapts them to the Agent's internal format.
 *
 * This runs at runtime during the Agent execution loop to ensure the tool list is current.
 */
export declare const generateMcpToolDefinitions: (mcp: IMCPClient | null, config: {
    otelInfo: OtelInfoType;
}) => Promise<Record<string, AgentToolDefinition<null>>>;
/**
 * Converts local `AgentInternalTool` definitions (Zod schemas) into JSON Schema for the LLM.
 * Uses `zod-to-json-schema` for the conversion.
 */
export declare const generateAgentInternalToolDefinitions: <TTools extends Record<string, AgentInternalTool>>(tools: Record<string, AgentInternalTool>) => { [K in keyof TTools]: AgentToolDefinition<TTools[K]>; };
/** Helper utility to truncate long strings (e.g. Base64 images) in logs/traces. */
export declare const clampStr: (s: string, len: number) => string;
/**
 * Populates the OpenTelemetry Span with all LLM Input data using OpenInference Semantic Conventions.
 *
 * This records:
 * 1. The LLM Config (Provider, Model, System Prompt).
 * 2. The full Conversation History (mapped from Arvo format to OpenInference format).
 * 3. Tool Definitions (so traces show what tools were available).
 * 4. Multi-modal content (Image/File placeholders).
 */
export declare const setOpenInferenceInputAttr: (param: {
    llm: {
        provider: string;
        system: string;
        model: string;
        invocationParam: Record<string, unknown>;
    };
    messages: AgentMessage[];
    system: string | null;
    tools: AgentToolDefinition[];
}, span: Span) => void;
/**
 * Records the LLM's generated Tool Calls to the OpenTelemetry Span.
 * Adds attributes for Function Name and JSON Arguments.
 */
export declare const setOpenInferenceToolCallOutputAttr: (param: {
    toolCalls: Omit<AgentToolCallContent, "type">[];
}, span: Span) => void;
/**
 * Records Token Usage metrics (Prompt, Completion, Total) to the OpenTelemetry Span.
 */
export declare const setOpenInferenceUsageOutputAttr: (param: AgentLLMIntegrationOutput["usage"], span: Span) => void;
/**
 * Records the LLM's final textual response to the OpenTelemetry Span.
 */
export declare const setOpenInferenceResponseOutputAttr: (param: {
    response: string;
}, span: Span) => void;
/** Safe wrapper around JSON.parse that returns null instead of throwing. */
export declare const tryParseJson: (str: string) => Record<string, unknown> | null;
/**
 * Implements the Priority-Based Execution logic.
 *
 * Takes a list of requested tool calls, groups them by their configured priority,
 * and returns **only** the batch with the highest priority. All lower priority
 * calls are discarded.
 */
export declare const prioritizeToolCalls: (toolCalls: Omit<AgentToolCallContent, "type">[], nameToToolMap: Record<string, AgentToolDefinition>) => Omit<AgentToolCallContent, "type">[];
/**
 * Apply the enablement on the available tools. By default
 * all the tools are enabled. Tools are removed only when they
 * are explicitly marked as false
 */
export declare const applyToolEnablement: (tools: AgentToolDefinition[], toolEnablementMap: Record<string, boolean>) => AgentToolDefinition[];
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