@gaiaverse/semantic-turning-point-detector
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Detects key semantic turning points in conversations using recursive semantic distance analysis. Ideal for conversation analysis, dialogue segmentation, insight detection, and AI-assisted reasoning tasks.
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TypeScript
import { ResponseFormatJSONSchema } from "openai/resources/shared";
import { Message, MetaMessage } from "./Message";
import { TurningPointDetectorConfig } from "./semanticTurningPointDetector";
export declare const emotionalTones: string[];
export declare const categories: {
topic: string;
insight: string;
emotion: string;
"meta-reflection": string;
decision: string;
question: string;
problem: string;
action: string;
clarification: string;
objection: string;
};
export declare function formSystemMessage({ distance, dimension, }: {
/** The semantic distance (via embeddings) between two messages */
distance: number;
/** The dimensionlity of the currentl potential turning point, where if dimension > 0, it means that it contains a group of turning points, recursively. */
dimension: number;
}): string;
export declare function formUserMessage({ beforeMessage, afterMessage, dimension, config, addUserInstructions, }: {
/** The dimensionlity of the currentl potential turning point, where if dimension > 0, it means that it contains a group of turning points, recursively. */
dimension: number;
/** The configuration settings for the turning point detector */
config: TurningPointDetectorConfig;
/** The first message to be analyzed */
beforeMessage: Message | MetaMessage;
/** The second message to be analyzed */
afterMessage: Message | MetaMessage;
/** Returns only the content to analyze if set to false, defaults to true */
addUserInstructions?: boolean;
}): string;
export declare const formResponseFormatSchema: (dimension: number) => ResponseFormatJSONSchema;
export declare const formSystemPromptEnding: (dimension: number) => string;
//# sourceMappingURL=prompt.d.ts.map