/**
 * Text-generation provider for knowledge summarization — the CLI/`dim knowledge sync`
 * "LLM fallback" when no MCP agent is in the loop. Auto-detects the same way the
 * embedding provider does: OpenAI if OPENAI_API_KEY is set, else a local Ollama, else
 * none (in which case docs simply wait in the inbox until a provider/agent appears).
 *
 *   AIDIMAG_LLM = auto (default) | openai | ollama | bedrock | off
 *   AIDIMAG_OPENAI_CHAT_MODEL   (default gpt-4o-mini)
 *   AIDIMAG_OLLAMA_CHAT_MODEL   (default llama3.1)
 *   AIDIMAG_OLLAMA_URL          (default http://localhost:11434)
 *   AIDIMAG_BEDROCK_CHAT_MODEL  (default us.anthropic.claude-sonnet-4-5-20250929-v1:0)
 *   AIDIMAG_BEDROCK_REGION      (default: AWS SDK resolution — env/profile/config)
 *
 * Bedrock is explicit-only (never auto-detected): probing it would make a billable
 * AWS call, and ambient credentials on a machine are no signal the user wants them
 * used. Set AIDIMAG_LLM=bedrock to opt in; credentials come from the standard AWS
 * chain (env vars, ~/.aws profiles, SSO, instance roles).
 */
export interface TextProvider {
    readonly name: string;
    readonly model: string;
    /** Returns the model's raw text response (expected to be JSON for our prompts). */
    generate(system: string, user: string): Promise<string>;
}
/** Check if running inside an MCP client (e.g., Cursor AI with MCP enabled). */
export declare function isMcpAvailable(): boolean;
/** Resolve the text/LLM provider (cached per process). null = none available. */
export declare function getTextProvider(): Promise<TextProvider | null>;
/** Reset the cached provider so the next call re-detects (e.g. after Ollama setup). */
export declare function resetTextProviderCache(): void;