Interface: IPromptEngineUtilityAI
Defined in: packages/agentos/src/core/llm/IPromptEngine.ts:381
Interface for utility AI services that assist the PromptEngine with complex content processing tasks like summarization and relevance analysis, specifically tailored for prompt construction needs. This is a focused interface used internally by the PromptEngine. IPromptEngineUtilityAI
Methods
analyzeContentRelevance()?
optionalanalyzeContentRelevance(content,executionContext,modelInfo):Promise<{importanceScore:number;keywords?:string[];relevanceScore:number;topics?:string[]; }>
Defined in: packages/agentos/src/core/llm/IPromptEngine.ts:424
Analyzes a piece of content for its relevance and importance within the current execution context. This can be used to prioritize which content to include or how to emphasize it.
Parameters
content
string
The text content to analyze.
executionContext
Readonly<PromptExecutionContext>
The current execution context.
modelInfo
Readonly<ModelTargetInfo>
Information about the model.
Returns
Promise<{ importanceScore: number; keywords?: string[]; relevanceScore: number; topics?: string[]; }>
Scores and extracted metadata.
summarizeConversationHistory()
summarizeConversationHistory(
messages,targetTokenCount,modelInfo,preserveImportantMessages?):Promise<{finalTokenCount:number;messagesSummarized:number;originalTokenCount:number;summaryMessages:ConversationMessage[]; }>
Defined in: packages/agentos/src/core/llm/IPromptEngine.ts:392
Summarizes conversation history to fit within token constraints, attempting to preserve key information.
Parameters
messages
readonly ConversationMessage[]
The array of conversation messages to summarize.
targetTokenCount
number
The desired maximum token count for the summary.
modelInfo
Readonly<ModelTargetInfo>
Information about the model for which the summary is being prepared.
preserveImportantMessages?
boolean
If true, attempt to identify and keep important messages verbatim.
Returns
Promise<{ finalTokenCount: number; messagesSummarized: number; originalTokenCount: number; summaryMessages: ConversationMessage[]; }>
A summary (which might be a single system message or a condensed list of messages), and metadata about the summarization.
summarizeRAGContext()
summarizeRAGContext(
context,targetTokenCount,modelInfo,preserveSourceAttribution?):Promise<{finalTokenCount:number;originalTokenCount:number;preservedSources?:string[];summary:string; }>
Defined in: packages/agentos/src/core/llm/IPromptEngine.ts:408
Summarizes retrieved RAG context to fit token limits, ideally preserving source attribution if possible.
Parameters
context
The RAG context to summarize.
string | readonly object[]
targetTokenCount
number
The desired maximum token count for the summarized context.
modelInfo
Readonly<ModelTargetInfo>
Information about the model.
preserveSourceAttribution?
boolean
If true, attempt to retain source information in the summary.
Returns
Promise<{ finalTokenCount: number; originalTokenCount: number; preservedSources?: string[]; summary: string; }>
The summarized text and metadata.