Keep/keep-notes/lib/ai/services/paragraph-refactor.service.ts
sepehr 5d315a6bdd fix: make paragraph refactor service use configured AI provider
The paragraph-refactor service was using OLLAMA_BASE_URL directly from
environment variables instead of using the configured AI provider from
the database. This caused "OLLAMA error" even when OpenAI was configured
in the admin interface.

Changes:
- paragraph-refactor.service.ts: Now uses getSystemConfig() and
  getTagsProvider() from factory instead of direct Ollama calls
- factory.ts: Added proper error messages when API keys are missing
- .env.docker.example: Updated with new provider configuration
  variables (AI_PROVIDER_TAGS, AI_PROVIDER_EMBEDDING)

This fixes the issue where AI reformulation features (Clarify, Shorten,
Improve Style) would fail with OLLAMA errors even when OpenAI was
properly configured in the admin settings.

Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>
2026-01-12 22:51:24 +01:00

314 lines
10 KiB
TypeScript

/**
* Paragraph Refactor Service
* Provides AI-powered text reformulation with 3 options:
* 1. Clarify - Make ambiguous text clearer
* 2. Shorten - Condense while keeping meaning
* 3. Improve Style - Enhance readability and flow
*/
import { LanguageDetectionService } from './language-detection.service'
import { getTagsProvider } from '../factory'
import { getSystemConfig } from '@/lib/config'
export type RefactorMode = 'clarify' | 'shorten' | 'improveStyle'
export interface RefactorOption {
mode: RefactorMode
label: string
description: string
icon: string
}
export interface RefactorResult {
original: string
refactored: string
mode: RefactorMode
language: string
wordCountChange: {
original: number
refactored: number
difference: number
percentage: number
}
}
export const REFACTOR_OPTIONS: RefactorOption[] = [
{
mode: 'clarify',
label: 'Clarify',
description: 'Make the text clearer and easier to understand',
icon: '💡'
},
{
mode: 'shorten',
label: 'Shorten',
description: 'Condense the text while keeping key information',
icon: '✂️'
},
{
mode: 'improveStyle',
label: 'Improve Style',
description: 'Enhance readability, flow, and expression',
icon: '✨'
}
]
export class ParagraphRefactorService {
private languageDetection: LanguageDetectionService
private readonly MIN_WORDS = 10
private readonly MAX_WORDS = 500
constructor() {
this.languageDetection = new LanguageDetectionService()
}
/**
* Refactor a paragraph with the specified mode
*/
async refactor(
content: string,
mode: RefactorMode
): Promise<RefactorResult> {
// Validate word count
const wordCount = content.split(/\s+/).length
if (wordCount < this.MIN_WORDS || wordCount > this.MAX_WORDS) {
throw new Error(
`Please select ${this.MIN_WORDS}-${this.MAX_WORDS} words to reformulate`
)
}
// Detect language
const { language } = await this.languageDetection.detectLanguage(content)
try {
// Build prompts
const systemPrompt = this.getSystemPrompt(mode)
const userPrompt = this.getUserPrompt(mode, content, language)
// Get AI provider from factory
const config = await getSystemConfig()
const provider = getTagsProvider(config)
// Use provider's generateText method
const fullPrompt = `${systemPrompt}\n\n${userPrompt}`
const refactored = await provider.generateText(fullPrompt)
// Calculate word count change
const refactoredWordCount = refactored.split(/\s+/).length
const wordCountChange = {
original: wordCount,
refactored: refactoredWordCount,
difference: refactoredWordCount - wordCount,
percentage: ((refactoredWordCount - wordCount) / wordCount) * 100
}
return {
original: content,
refactored,
mode,
language,
wordCountChange
}
} catch (error) {
throw new Error('Failed to refactor paragraph. Please try again.')
}
}
/**
* Get all 3 refactor options for a paragraph at once
* More efficient than calling refactor() 3 times
*/
async refactorAllModes(content: string): Promise<RefactorResult[]> {
// Validate word count
const wordCount = content.split(/\s+/).length
if (wordCount < this.MIN_WORDS || wordCount > this.MAX_WORDS) {
throw new Error(
`Please select ${this.MIN_WORDS}-${this.MAX_WORDS} words to reformulate`
)
}
// Detect language
const { language } = await this.languageDetection.detectLanguage(content)
try {
// System prompt for all modes
const systemPrompt = `You are an expert text editor who can improve text in multiple ways.
Your task is to provide 3 different reformulations of the user's text.
For each reformulation:
1. Clarify: Make the text clearer, more explicit, easier to understand
2. Shorten: Condense the text while preserving all key information and meaning
3. Improve Style: Enhance readability, flow, vocabulary, and expression
CRITICAL LANGUAGE RULE: You MUST respond in the EXACT SAME LANGUAGE as the input text.
- If input is French, ALL 3 outputs MUST be in French
- If input is German, ALL 3 outputs MUST be in German
- If input is Spanish, ALL 3 outputs MUST be in Spanish
- NEVER translate to English unless the input is in English
Maintain the original meaning and intent:
- For "shorten", aim to reduce by 30-50% while keeping all key points
- For "clarify", expand where necessary but keep it natural
- For "improve style", keep similar length but enhance quality
Output Format (JSON):
{
"clarify": "clarified text here...",
"shorten": "shortened text here...",
"improveStyle": "improved text here..."
}`
const userPrompt = `CRITICAL LANGUAGE INSTRUCTION: The text below is in ${language}. Your response MUST be in ${language}. Do NOT translate to English.
Please provide 3 reformulations of this ${language} text:
${content}
Original language: ${language}
IMPORTANT: Provide all 3 versions in ${language}. No English, no explanations.`
// Get AI provider from factory
const config = await getSystemConfig()
const provider = getTagsProvider(config)
// Use provider's generateText method
const fullPrompt = `${systemPrompt}\n\n${userPrompt}`
const response = await provider.generateText(fullPrompt)
// Parse JSON response
const jsonResponse = JSON.parse(response)
const modes: RefactorMode[] = ['clarify', 'shorten', 'improveStyle']
const results: RefactorResult[] = []
for (const mode of modes) {
if (!jsonResponse[mode]) continue
const refactored = this.extractRefactoredText(jsonResponse[mode])
const refactoredWordCount = refactored.split(/\s+/).length
results.push({
original: content,
refactored,
mode,
language,
wordCountChange: {
original: wordCount,
refactored: refactoredWordCount,
difference: refactoredWordCount - wordCount,
percentage: ((refactoredWordCount - wordCount) / wordCount) * 100
}
})
}
return results
} catch (error) {
throw new Error('Failed to generate refactor options. Please try again.')
}
}
/**
* Get mode-specific system prompt
*/
private getSystemPrompt(mode: RefactorMode): string {
const prompts = {
clarify: `You are an expert at making text clearer and more understandable.
Your goal: Rewrite the text to eliminate ambiguity, add necessary context, and improve clarity.
CRITICAL LANGUAGE RULE: You MUST respond in the EXACT SAME LANGUAGE as the input text. If input is French, output MUST be French. If input is German, output MUST be German. NEVER translate to English.
Maintain the original meaning and tone, just make it clearer.`,
shorten: `You are an expert at concise writing.
Your goal: Reduce the text length by 30-50% while preserving ALL key information and meaning.
CRITICAL LANGUAGE RULE: You MUST respond in the EXACT SAME LANGUAGE as the input text. If input is French, output MUST be French. If input is German, output MUST be German. NEVER translate to English.
Remove fluff, repetition, and unnecessary words, but keep the substance.`,
improveStyle: `You are an expert editor with a focus on readability and flow.
Your goal: Enhance the text's style, vocabulary, sentence structure, and overall quality.
CRITICAL LANGUAGE RULE: You MUST respond in the EXACT SAME LANGUAGE as the input text. If input is French, output MUST be French. If input is German, output MUST be German. NEVER translate to English.
Maintain similar length but make it sound more professional and polished.`
}
return prompts[mode]
}
/**
* Get mode-specific user prompt
*/
private getUserPrompt(mode: RefactorMode, content: string, language: string): string {
const instructions = {
clarify: `IMPORTANT: The text below is in ${language}. Your response MUST be in ${language}. Do NOT translate to English.
Please clarify and make this ${language} text easier to understand:`,
shorten: `IMPORTANT: The text below is in ${language}. Your response MUST be in ${language}. Do NOT translate to English.
Please shorten this ${language} text while keeping all key information:`,
improveStyle: `IMPORTANT: The text below is in ${language}. Your response MUST be in ${language}. Do NOT translate to English.
Please improve the style and readability of this ${language} text:`
}
return `${instructions[mode]}
${content}
CRITICAL: Respond ONLY with the refactored text in ${language}. No explanations, no meta-commentary, no English.`
}
/**
* Extract refactored text from AI response
* Handles JSON, markdown code blocks, or plain text
*/
private extractRefactoredText(response: string): string {
// Try JSON first
if (response.trim().startsWith('{')) {
try {
const parsed = JSON.parse(response)
// Look for common response fields
return parsed.refactored || parsed.text || parsed.result || response
} catch {
// Not valid JSON, continue
}
}
// Try markdown code block
const codeBlockMatch = response.match(/```(?:markdown)?\n([\s\S]+?)\n```/)
if (codeBlockMatch) {
return codeBlockMatch[1].trim()
}
// Fallback: trim whitespace and quotes
return response.trim().replace(/^["']|["']$/g, '')
}
/**
* Validate that text is within acceptable word count range
*/
validateWordCount(content: string): { valid: boolean; error?: string } {
const wordCount = content.split(/\s+/).length
if (wordCount < this.MIN_WORDS) {
return {
valid: false,
error: `Please select at least ${this.MIN_WORDS} words to reformulate (currently ${wordCount} words)`
}
}
if (wordCount > this.MAX_WORDS) {
return {
valid: false,
error: `Please select at most ${this.MAX_WORDS} words to reformulate (currently ${wordCount} words)`
}
}
return { valid: true }
}
}
// Singleton instance
export const paragraphRefactorService = new ParagraphRefactorService()