sepehr 3c4b9d6176 feat(ai): implement intelligent auto-tagging system
- Added multi-provider AI infrastructure (OpenAI/Ollama)
- Implemented real-time tag suggestions with debounced analysis
- Created AI diagnostics and database maintenance tools in Settings
- Added automated garbage collection for orphan labels
- Refined UX with deterministic color hashing and interactive ghost tags
2026-01-08 22:59:52 +01:00

77 lines
2.4 KiB
TypeScript

import { AIProvider, TagSuggestion } from '../types';
export class OllamaProvider implements AIProvider {
private baseUrl: string;
private modelName: string;
constructor(baseUrl: string = 'http://localhost:11434/api', modelName: string = 'llama3') {
this.baseUrl = baseUrl.endsWith('/') ? baseUrl.slice(0, -1) : baseUrl;
this.modelName = modelName;
}
async generateTags(content: string): Promise<TagSuggestion[]> {
try {
const response = await fetch(`${this.baseUrl}/generate`, {
method: 'POST',
headers: { 'Content-Type': 'application/json' },
body: JSON.stringify({
model: this.modelName,
prompt: `Analyse la note suivante et extrais les concepts clés sous forme de tags courts (1-3 mots max).
Règles:
- Pas de mots de liaison (le, la, pour, et...).
- Garde les expressions composées ensemble (ex: "semaine prochaine", "New York").
- Normalise en minuscules sauf noms propres.
- Maximum 5 tags.
Réponds UNIQUEMENT sous forme de liste JSON d'objets : [{"tag": "string", "confidence": number}].
Contenu de la note: "${content}"`,
stream: false,
}),
});
if (!response.ok) throw new Error(`Ollama error: ${response.statusText}`);
const data = await response.json();
const text = data.response;
const jsonMatch = text.match(/\[\s*\{.*\}\s*\]/s);
if (jsonMatch) {
return JSON.parse(jsonMatch[0]);
}
// Support pour le format { "tags": [...] }
const objectMatch = text.match(/\{\s*"tags"\s*:\s*(\[.*\])\s*\}/s);
if (objectMatch && objectMatch[1]) {
return JSON.parse(objectMatch[1]);
}
return [];
} catch (e) {
console.error('Erreur API directe Ollama:', e);
return [];
}
}
async getEmbeddings(text: string): Promise<number[]> {
try {
const response = await fetch(`${this.baseUrl}/embeddings`, {
method: 'POST',
headers: { 'Content-Type': 'application/json' },
body: JSON.stringify({
model: this.modelName,
prompt: text,
}),
});
if (!response.ok) throw new Error(`Ollama error: ${response.statusText}`);
const data = await response.json();
return data.embedding;
} catch (e) {
console.error('Erreur embeddings directs Ollama:', e);
return [];
}
}
}