Files
Momento/memento-note/lib/ai/providers/deepseek.ts
Sepehr Ramezani aa6a214f37 feat: rename keep-notes to memento-note, migrate to PostgreSQL, fix MCP bugs
- Rename directory keep-notes -> memento-note with all code references
- Prisma: SQLite -> PostgreSQL (both app and MCP server schemas)
- Sync MCP schema with main app (add missing fields, relations, indexes)
- Delete 17 SQLite migrations (clean slate for PostgreSQL)
- Remove SQLite dependencies (@libsql/client, better-sqlite3, etc.)
- Fix MCP server: hardcoded Windows DB paths -> DATABASE_URL env var
- Fix MCP server: .dockerignore excluded index-sse.js (SSE mode broken)
- MCP Dockerfile: node:20 -> node:22
- Docker Compose: add postgres service, remove SQLite volume
- Generate favicon.ico, icon-192.png, icon-512.png, apple-icon.png
- Update layout.tsx icons and manifest.json for PNG icons
- Update all .env files for PostgreSQL
- Rewrite README.md with updated sections
- Remove mcp-server/node_modules and prisma/client-generated from git tracking

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
2026-04-20 20:58:04 +02:00

89 lines
2.5 KiB
TypeScript

import { createOpenAI } from '@ai-sdk/openai';
import { generateObject, generateText, embed } from 'ai';
import { z } from 'zod';
import { AIProvider, TagSuggestion, TitleSuggestion } from '../types';
export class DeepSeekProvider implements AIProvider {
private model: any;
private embeddingModel: any;
constructor(apiKey: string, modelName: string = 'deepseek-chat', embeddingModelName: string = 'deepseek-embedding') {
// Create OpenAI-compatible client for DeepSeek
const deepseek = createOpenAI({
baseURL: 'https://api.deepseek.com/v1',
apiKey: apiKey,
});
this.model = deepseek(modelName);
this.embeddingModel = deepseek.embedding(embeddingModelName);
}
async generateTags(content: string): Promise<TagSuggestion[]> {
try {
const { object } = await generateObject({
model: this.model,
schema: z.object({
tags: z.array(z.object({
tag: z.string().describe('Le nom du tag, court et en minuscules'),
confidence: z.number().min(0).max(1).describe('Le niveau de confiance entre 0 et 1')
}))
}),
prompt: `Analyse la note suivante et suggère entre 1 et 5 tags pertinents.
Contenu de la note: "${content}"`,
});
return object.tags;
} catch (e) {
console.error('Erreur génération tags DeepSeek:', e);
return [];
}
}
async getEmbeddings(text: string): Promise<number[]> {
try {
const { embedding } = await embed({
model: this.embeddingModel,
value: text,
});
return embedding;
} catch (e) {
console.error('Erreur embeddings DeepSeek:', e);
return [];
}
}
async generateTitles(prompt: string): Promise<TitleSuggestion[]> {
try {
const { object } = await generateObject({
model: this.model,
schema: z.object({
titles: z.array(z.object({
title: z.string().describe('Le titre suggéré'),
confidence: z.number().min(0).max(1).describe('Le niveau de confiance entre 0 et 1')
}))
}),
prompt: prompt,
});
return object.titles;
} catch (e) {
console.error('Erreur génération titres DeepSeek:', e);
return [];
}
}
async generateText(prompt: string): Promise<string> {
try {
const { text } = await generateText({
model: this.model,
prompt: prompt,
});
return text.trim();
} catch (e) {
console.error('Erreur génération texte DeepSeek:', e);
throw e;
}
}
}