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99 lines
4.4 KiB
TypeScript
99 lines
4.4 KiB
TypeScript
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/**
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* LLM Prompt Constants
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*
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* This file centralizes all LLM/AI prompts used throughout the application.
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* When adding new prompts, please add them here rather than hardcoding them in other files.
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*
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* Prompts are organized by their usage context (e.g., service, feature, etc.)
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*/
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// Base system prompt used when no custom prompt is provided
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export const DEFAULT_SYSTEM_PROMPT =
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"You are a helpful assistant embedded in the Trilium Notes application. " +
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"You can help users with their notes, answer questions, and provide information. " +
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"Keep your responses concise and helpful. " +
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"You're currently chatting with the user about their notes.";
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// Context-specific prompts
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export const CONTEXT_PROMPTS = {
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// Query enhancer prompt for generating better search terms
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QUERY_ENHANCER:
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`You are an AI assistant that decides what information needs to be retrieved from a user's knowledge base called TriliumNext Notes to answer the user's question.
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Given the user's question, generate 3-5 specific search queries that would help find relevant information.
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Each query should be focused on a different aspect of the question.
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Format your answer as a JSON array of strings, with each string being a search query.
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Example: ["exact topic mentioned", "related concept 1", "related concept 2"]`,
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// Used to format notes context when providing responses
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CONTEXT_NOTES_WRAPPER:
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`I'll provide you with relevant information from my notes to help answer your question.
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{noteContexts}
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When referring to information from these notes in your response, please cite them by their titles (e.g., "According to your note on [Title]...") rather than using labels like "Note 1" or "Note 2".
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Now, based on the above information, please answer: {query}`,
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// Default fallback when no notes are found
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NO_NOTES_CONTEXT:
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"I am an AI assistant helping you with your Trilium notes. " +
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"I couldn't find any specific notes related to your query, but I'll try to assist you " +
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"with general knowledge about Trilium or other topics you're interested in.",
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// Fallback when context building fails
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ERROR_FALLBACK_CONTEXT:
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"I'm your AI assistant helping with your Trilium notes. I'll try to answer based on what I know.",
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// Headers for context (by provider)
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CONTEXT_HEADERS: {
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ANTHROPIC: (query: string) =>
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`I'm your AI assistant helping with your Trilium notes database. For your query: "${query}", I found these relevant notes:\n\n`,
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DEFAULT: (query: string) =>
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`I've found some relevant information in your notes that may help answer: "${query}"\n\n`
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},
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// Closings for context (by provider)
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CONTEXT_CLOSINGS: {
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ANTHROPIC:
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"\n\nPlease use this information to answer the user's query. If the notes don't contain enough information, you can use your general knowledge as well.",
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DEFAULT:
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"\n\nBased on this information from the user's notes, please provide a helpful response."
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},
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// Context for index service
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INDEX_NO_NOTES_CONTEXT:
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"I'm an AI assistant helping with your Trilium notes. I couldn't find specific notes related to your query, but I'll try to assist based on general knowledge."
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};
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// Agent tool prompts
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export const AGENT_TOOL_PROMPTS = {
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// Prompts for query decomposition
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QUERY_DECOMPOSITION: {
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SUB_QUERY_DIRECT: 'Direct question that can be answered without decomposition',
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SUB_QUERY_GENERIC: 'Generic exploration to find related content',
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SUB_QUERY_ERROR: 'Error in decomposition, treating as simple query',
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SUB_QUERY_DIRECT_ANALYSIS: 'Direct analysis of note details',
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ORIGINAL_QUERY: 'Original query'
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},
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// Prompts for contextual thinking tool
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CONTEXTUAL_THINKING: {
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STARTING_ANALYSIS: (query: string) => `Starting analysis of the query: "${query}"`,
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KEY_COMPONENTS: 'What are the key components of this query that need to be addressed?',
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BREAKING_DOWN: 'Breaking down the query to understand its requirements and context.'
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}
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};
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// Provider-specific prompt modifiers
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export const PROVIDER_PROMPTS = {
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ANTHROPIC: {
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// Any Anthropic Claude-specific prompt modifications would go here
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},
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OPENAI: {
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// Any OpenAI-specific prompt modifications would go here
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},
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OLLAMA: {
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// Any Ollama-specific prompt modifications would go here
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}
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};
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