import type { AgentHarnessStreamOptions } from '@earendil-works/pi-agent-core';
import type { Model } from '@earendil-works/pi-ai';
import type { AgentAdapter, AgentAdapterKind, AgentSendOpts, ChatMessage } from '../../../core/types.js';
import type { ApprovalGate } from '../../../core/llm/agent-loop.js';
import type { ToolDef } from '../../../core/llm/provider-base.js';
import type { ToolDispatcher } from '../../../core/llm/tool-dispatcher.js';
/** Resolved LLM binding for one turn: a pi-ai Model + how to authenticate it. */
export interface NativeModelBinding {
    model: Model<string>;
    /** Whether model.cost came from a known catalog entry. */
    costKnown?: boolean;
    getApiKeyAndHeaders: () => Promise<{
        apiKey: string;
        headers: Record<string, string>;
    }>;
}
export interface NativeModelChoice {
    name: string;
    providerType?: string;
    model?: string;
}
export interface NativeAgentDeps {
    /** Adapter name to register under. Defaults to 'agim'. */
    name?: string;
    /** Adapter aliases. Defaults to the public Agim Agent aliases. */
    aliases?: string[];
    /** Directory under which per-session JSONL files live. */
    sessionsRoot: string;
    /** agim BackendConfig → pi-ai Model + auth. Returns null when no backend is
     *  configured (adapter then reports unavailable / fails the turn cleanly). */
    resolveModel: (opts?: AgentSendOpts) => Promise<NativeModelBinding | null>;
    /** Optional model roster for direct adapter slash-command fallback. The
     *  normal web/IM path handles `/models` in the router; this keeps REST/job
     *  style direct calls from sending the command to the LLM as plain text. */
    listModels?: () => NativeModelChoice[];
    /** The agim tool surface (schemas + dispatcher) to expose this turn. Receives
     *  the session id so per-thread tool state (todo tracker, plan-exit) keys
     *  correctly. */
    resolveTools?: (opts: AgentSendOpts | undefined, sessionId: string) => {
        tools: ToolDef[];
        dispatch: ToolDispatcher;
        parallelSafe?: (toolName: string) => boolean;
    } | null;
    /** Tools allowed under Plan Mode. Unknown tools fail closed. */
    planModeAllowedTools?: ReadonlySet<string>;
    /** Read-only verdict for parallel tool execution. */
    parallelSafe?: (toolName: string) => boolean;
    /** Per-turn agim policy approval gate (read-only / allow-list / deny-all +
     *  IM approval-card escalation). Consulted from the beforeToolCall hook. */
    resolveApprovalGate?: (opts: AgentSendOpts | undefined, sessionId: string) => ApprovalGate | null;
    /** Per-turn system prompt (runtime identity: real backend + model + role,
     *  operator role, skill routing, tool guides). Without it the model has no
     *  idea what it is and hallucinates its identity. */
    resolveSystemPrompt?: (opts: AgentSendOpts | undefined, sessionId: string) => string | undefined;
    /** Max tool-call rounds per turn before the loop is force-stopped. pi's loop
     *  has no built-in cap, so we enforce one (mirrors agim's
     *  AGIM_NATIVE_AGENT_MAX_ITER). Defaults to 50; clamped to [1, 100]. */
    maxIterations?: number;
    /** Hard cap on tool calls declared by assistant messages in one run. A batch
     *  that would exceed it is aborted before dispatch. Defaults to maxIterations. */
    maxToolCalls?: number;
    /** Proactive context compaction before each turn. pi never auto-compacts, so
     *  when a durable session grows past the model window (minus reserve) the
     *  adapter summarizes old history — without this, long-lived IM sessions grow
     *  the JSONL unbounded until the context overflows. Defaults to enabled; set
     *  false (factory reads AGIM_CTX_COMPACT=off) to disable. */
    compactionEnabled?: boolean;
    /** Provider request resilience + caching, snapshotted per turn by pi:
     *  maxRetries / maxRetryDelayMs / timeoutMs (ride out transient 429/5xx from
     *  the LLM provider) + cacheRetention (provider prompt cache → cuts the repeat
     *  token cost of the system prompt + history). Factory builds it from
     *  AGIM_NATIVE_* envs; omit to use pi defaults. */
    streamOptions?: AgentHarnessStreamOptions;
    /** Active AgentHarness loop watchdog in milliseconds, resolved per turn so
     *  goal-aware callers can extend it. Starts after optional compaction because
     *  pi 0.79.x does not expose a cancellable compaction signal. 0 disables. */
    resolveRunTimeoutMs?: (opts: AgentSendOpts | undefined) => number;
}
/**
 * Build the user-facing reply for one harness turn.
 *
 * Models often emit the full report in a mid-turn assistant message that also
 * carries tool calls (e.g. todo_write), then end with a short "盘点完成".
 * `harness.prompt()`'s result only contains that last hop — so without this
 * merge the conversation stream loses the body. See composeDeliveredAssistantText
 * tests / CHANGELOG.
 */
export declare function composeDeliveredAssistantText(midTurnTexts: readonly string[], finalText: string): string;
export declare class NativeAgentAdapter implements AgentAdapter {
    private deps;
    readonly name: string;
    readonly aliases: string[];
    readonly kind: AgentAdapterKind;
    readonly handlesAgimSkillsPrompt = true;
    readonly handlesEphemeralContext = true;
    private readonly sessionMeta;
    private readonly sessionModelOverrides;
    private readonly sessionLocks;
    constructor(deps: NativeAgentDeps);
    /** True while a turn for this session id is queued or running. */
    isSessionBusy(sessionId: string): boolean;
    /** Drop cached JSONL metadata / model override after quarantine or external delete. */
    invalidateSessionMeta(sessionId: string): void;
    isAvailable(): Promise<boolean>;
    describe(): string | undefined;
    sendPrompt(sessionId: string, prompt: string, history?: ChatMessage[], opts?: AgentSendOpts): AsyncGenerator<string>;
    private runTurn;
    private tryHandleModelSlash;
}
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