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Antigravity
2026-06-14 14:06:05 +00:00
parent a8785ed4f1
commit a623454347
120 changed files with 12301 additions and 785 deletions
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78
memento-note/lib/ai/providers/anthropic.ts
View File

@@ -23,19 +23,36 @@ export class AnthropicProvider implements AIProvider {
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('Short tag name in lowercase'),
confidence: z.number().min(0).max(1).describe('Confidence level between 0 and 1'),
})),
}),
prompt: `Analyze the following note and suggest 1 to 5 relevant tags.
Note content: "${content}"`,
});
try {
const { object } = await generateObject({
model: this.model,
schema: z.object({
tags: z.array(z.object({
tag: z.string().describe('Short tag name in lowercase'),
confidence: z.number().min(0).max(1).describe('Confidence level between 0 and 1'),
})),
}),
prompt: `Analyze the following note and suggest 1 to 5 relevant tags.
Note content: "${content}"`,
});
return object.tags;
return object.tags;
} catch (err) {
console.warn('Anthropic generateObject tags failed, falling back to generateText:', err);
const { text } = await aiGenerateText({
model: this.model,
prompt: `Analyze the following note and suggest 1 to 5 relevant tags.
Note content: "${content.substring(0, 1500)}"
Return ONLY a JSON array of tag objects, like: [{"tag":"example","confidence":0.9}]`,
});
const cleaned = text.replace(/<think>[\s\S]*?<\/think>/gi, '').replace(/^```json\n?/, '').replace(/\n?```$/, '').trim();
const parsed = JSON.parse(cleaned);
const arr = Array.isArray(parsed) ? parsed : (parsed.tags || parsed.suggestions || []);
return arr.map((t: any) => ({
tag: t.tag || t.label || t.name || '',
confidence: t.confidence || t.score || 0.7,
}));
}
} catch (e) {
console.error('Error generating tags (Anthropic):', e);
return [];
@@ -50,18 +67,33 @@ export class AnthropicProvider implements AIProvider {
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('Suggested title'),
confidence: z.number().min(0).max(1).describe('Confidence level between 0 and 1'),
})),
}),
prompt,
});
try {
const { object } = await generateObject({
model: this.model,
schema: z.object({
titles: z.array(z.object({
title: z.string().describe('Suggested title'),
confidence: z.number().min(0).max(1).describe('Confidence level between 0 and 1'),
})),
}),
prompt,
});
return object.titles;
return object.titles;
} catch (err) {
console.warn('Anthropic generateObject titles failed, falling back to generateText:', err);
const { text } = await aiGenerateText({
model: this.model,
prompt: prompt + '\n\nRespond ONLY as a JSON array of title suggestions: [{"title": "Suggested title", "confidence": 0.9}]',
});
const cleaned = text.replace(/<think>[\s\S]*?<\/think>/gi, '').replace(/^```json\n?/, '').replace(/\n?```$/, '').trim();
const parsed = JSON.parse(cleaned);
const arr = Array.isArray(parsed) ? parsed : (parsed.titles || parsed.suggestions || []);
return arr.map((t: any) => ({
title: typeof t === 'string' ? t : t.title || t.name || '',
confidence: typeof t === 'number' ? t : (t.confidence || t.score || 0.8),
}));
}
} catch (e) {
console.error('Error generating titles (Anthropic):', e);
return [];

33
memento-note/lib/ai/providers/custom-openai.ts
View File

@@ -1,7 +1,7 @@
import { createOpenAI } from '@ai-sdk/openai';
import { generateObject, generateText as aiGenerateText, embed, stepCountIs } from 'ai';
import { z } from 'zod';
import { generateText as aiGenerateText, embed, stepCountIs } from 'ai';
import { AIProvider, TagSuggestion, TitleSuggestion, ToolUseOptions, ToolCallResult } from '../types';
import { cleanAIJsonResponse, cleanAITextResponse } from '../utils/clean-ai-response';
export class CustomOpenAIProvider implements AIProvider {
private model: any;
@@ -49,19 +49,20 @@ export class CustomOpenAIProvider implements AIProvider {
async generateTags(content: string): Promise<TagSuggestion[]> {
try {
const { object } = await generateObject({
const { text } = await aiGenerateText({
model: this.model,
schema: z.object({
tags: z.array(z.object({
tag: z.string().describe('Short tag name in lowercase'),
confidence: z.number().min(0).max(1).describe('Confidence level between 0 and 1')
}))
}),
prompt: `Analyze the following note and suggest 1 to 5 relevant tags.
Note content: "${content}"`,
Note content: "${content.substring(0, 1500)}"
Return ONLY a JSON array of tag objects, like: [{"tag":"example","confidence":0.9}]`,
});
return object.tags;
const cleaned = cleanAIJsonResponse(text)
const parsed = JSON.parse(cleaned);
const arr = Array.isArray(parsed) ? parsed : (parsed.tags || parsed.suggestions || []);
return arr.map((t: any) => ({
tag: t.tag || t.label || t.name || '',
confidence: t.confidence || t.score || 0.7,
}));
} catch (e) {
console.error('Error generating tags (Custom OpenAI):', e);
return [];
@@ -83,15 +84,15 @@ export class CustomOpenAIProvider implements AIProvider {
async generateTitles(prompt: string): Promise<TitleSuggestion[]> {
try {
// Use generateText instead of generateObject — DeepSeek doesn't support
// Use generateText instead of generateObject — DeepSeek/MiniMax don't support
// response_format: json_schema via the OpenAI compat layer
const { text } = await aiGenerateText({
model: this.model,
prompt: prompt,
})
// Parse the JSON array from the text response — strip markdown code fences if present
const parsed = JSON.parse(text.replace(/^```json\n?/,'').replace(/\n?```$/,'').trim())
const cleaned = cleanAIJsonResponse(text)
const parsed = JSON.parse(cleaned)
const titles = Array.isArray(parsed) ? parsed : (parsed.titles || parsed.suggestions || [])
return titles.map((t: any) => ({
title: typeof t === 'string' ? t : t.title || t.name || '',
@@ -103,6 +104,8 @@ export class CustomOpenAIProvider implements AIProvider {
}
}
async generateText(prompt: string): Promise<string> {
try {
const { text } = await aiGenerateText({
@@ -110,7 +113,7 @@ export class CustomOpenAIProvider implements AIProvider {
prompt: prompt,
});
return text.trim();
return cleanAITextResponse(text).trim();
} catch (e) {
console.error('Error generating text (Custom OpenAI):', e);
throw e;

26
memento-note/lib/ai/providers/deepseek.ts
View File

@@ -1,7 +1,7 @@
import { createOpenAI } from '@ai-sdk/openai';
import { generateObject, generateText as aiGenerateText, embed, stepCountIs } from 'ai';
import { z } from 'zod';
import { generateText as aiGenerateText, embed, stepCountIs } from 'ai';
import { AIProvider, TagSuggestion, TitleSuggestion, ToolUseOptions, ToolCallResult } from '../types';
import { cleanAIJsonResponse, cleanAITextResponse } from '../utils/clean-ai-response';
export class DeepSeekProvider implements AIProvider {
private model: any;
@@ -41,7 +41,7 @@ Return ONLY a JSON array like: [{"tag":"example","confidence":0.9}]
Note content: "${content.substring(0, 1500)}"`,
});
const clean = text.replace(/^```json\n?/, '').replace(/\n?```$/, '').trim();
const clean = cleanAIJsonResponse(text)
const parsed = JSON.parse(clean);
const arr = Array.isArray(parsed) ? parsed : (parsed.tags || []);
return arr.map((t: any) => ({
@@ -69,18 +69,18 @@ Note content: "${content.substring(0, 1500)}"`,
async generateTitles(prompt: string): Promise<TitleSuggestion[]> {
try {
const { object } = await generateObject({
// Utiliser generateText + parse manuel (generateObject échoue avec les modèles reasoning)
const { text } = await aiGenerateText({
model: this.model,
schema: z.object({
titles: z.array(z.object({
title: z.string().describe('Suggested title'),
confidence: z.number().min(0).max(1).describe('Confidence level between 0 and 1')
}))
}),
prompt: prompt,
});
return object.titles;
const cleaned = cleanAIJsonResponse(text)
const parsed = JSON.parse(cleaned)
const titles = Array.isArray(parsed) ? parsed : (parsed.titles || parsed.suggestions || [])
return titles.map((t: any) => ({
title: typeof t === 'string' ? t : t.title || t.name || '',
confidence: typeof t === 'number' ? t : (t.confidence || t.score || 0.5),
}))
} catch (e) {
console.error('Error generating titles (DeepSeek):', e);
return [];
@@ -94,7 +94,7 @@ Note content: "${content.substring(0, 1500)}"`,
prompt: prompt,
});
return text.trim();
return cleanAITextResponse(text).trim();
} catch (e) {
console.error('Error generating text (DeepSeek):', e);
throw e;

78
memento-note/lib/ai/providers/google.ts
View File

@@ -18,19 +18,36 @@ export class GoogleProvider implements AIProvider {
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('Short tag name in lowercase'),
confidence: z.number().min(0).max(1).describe('Confidence level between 0 and 1')
}))
}),
prompt: `Analyze the following note and suggest 1 to 5 relevant tags.
Note content: "${content}"`,
});
try {
const { object } = await generateObject({
model: this.model,
schema: z.object({
tags: z.array(z.object({
tag: z.string().describe('Short tag name in lowercase'),
confidence: z.number().min(0).max(1).describe('Confidence level between 0 and 1')
}))
}),
prompt: `Analyze the following note and suggest 1 to 5 relevant tags.
Note content: "${content}"`,
});
return object.tags;
return object.tags;
} catch (err) {
console.warn('Google generateObject tags failed, falling back to generateText:', err);
const { text } = await aiGenerateText({
model: this.model,
prompt: `Analyze the following note and suggest 1 to 5 relevant tags.
Note content: "${content.substring(0, 1500)}"
Return ONLY a JSON array of tag objects, like: [{"tag":"example","confidence":0.9}]`,
});
const cleaned = text.replace(/<think>[\s\S]*?<\/think>/gi, '').replace(/^```json\n?/, '').replace(/\n?```$/, '').trim();
const parsed = JSON.parse(cleaned);
const arr = Array.isArray(parsed) ? parsed : (parsed.tags || parsed.suggestions || []);
return arr.map((t: any) => ({
tag: t.tag || t.label || t.name || '',
confidence: t.confidence || t.score || 0.7,
}));
}
} catch (e) {
console.error('Error generating tags (Google):', e);
return [];
@@ -52,18 +69,33 @@ export class GoogleProvider implements AIProvider {
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('Suggested title'),
confidence: z.number().min(0).max(1).describe('Confidence level between 0 and 1')
}))
}),
prompt: prompt,
});
try {
const { object } = await generateObject({
model: this.model,
schema: z.object({
titles: z.array(z.object({
title: z.string().describe('Suggested title'),
confidence: z.number().min(0).max(1).describe('Confidence level between 0 and 1')
}))
}),
prompt: prompt,
});
return object.titles;
return object.titles;
} catch (err) {
console.warn('Google generateObject titles failed, falling back to generateText:', err);
const { text } = await aiGenerateText({
model: this.model,
prompt: prompt + '\n\nRespond ONLY as a JSON array of title suggestions: [{"title": "Suggested title", "confidence": 0.9}]',
});
const cleaned = text.replace(/<think>[\s\S]*?<\/think>/gi, '').replace(/^```json\n?/, '').replace(/\n?```$/, '').trim();
const parsed = JSON.parse(cleaned);
const arr = Array.isArray(parsed) ? parsed : (parsed.titles || parsed.suggestions || []);
return arr.map((t: any) => ({
title: typeof t === 'string' ? t : t.title || t.name || '',
confidence: typeof t === 'number' ? t : (t.confidence || t.score || 0.8),
}));
}
} catch (e) {
console.error('Error generating titles (Google):', e);
return [];

6
memento-note/lib/ai/providers/ollama.ts
View File

@@ -78,7 +78,7 @@ Note content: "${content}"`;
if (!response.ok) throw new Error(`Ollama error: ${response.statusText}`);
const data = await response.json();
const text = data.response;
const text = (data.response || '').replace(/<think>[\s\S]*?<\/think>/gi, '').trim();
const jsonMatch = text.match(/\[\s*\{[\s\S]*\}\s*\]/);
if (jsonMatch) {
@@ -133,7 +133,7 @@ Note content: "${content}"`;
if (!response.ok) throw new Error(`Ollama error: ${response.statusText}`);
const data = await response.json();
const text = data.response;
const text = (data.response || '').replace(/<think>[\s\S]*?<\/think>/gi, '').trim();
const jsonMatch = text.match(/\[\s*\{[\s\S]*\}\s*\]/);
if (jsonMatch) {
@@ -162,7 +162,7 @@ Note content: "${content}"`;
if (!response.ok) throw new Error(`Ollama error: ${response.statusText}`);
const data = await response.json();
return data.response.trim();
return (data.response || '').replace(/<think>[\s\S]*?<\/think>/gi, '').trim();
} catch (e) {
console.error('Error generating text (Ollama):', e);
throw e;

78
memento-note/lib/ai/providers/openai.ts
View File

@@ -24,19 +24,36 @@ export class OpenAIProvider implements AIProvider {
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('Short tag name in lowercase'),
confidence: z.number().min(0).max(1).describe('Confidence level between 0 and 1')
}))
}),
prompt: `Analyze the following note and suggest 1 to 5 relevant tags.
Note content: "${content}"`,
});
try {
const { object } = await generateObject({
model: this.model,
schema: z.object({
tags: z.array(z.object({
tag: z.string().describe('Short tag name in lowercase'),
confidence: z.number().min(0).max(1).describe('Confidence level between 0 and 1')
}))
}),
prompt: `Analyze the following note and suggest 1 to 5 relevant tags.
Note content: "${content}"`,
});
return object.tags;
return object.tags;
} catch (err) {
console.warn('OpenAI generateObject tags failed, falling back to generateText:', err);
const { text } = await aiGenerateText({
model: this.model,
prompt: `Analyze the following note and suggest 1 to 5 relevant tags.
Note content: "${content.substring(0, 1500)}"
Return ONLY a JSON array of tag objects, like: [{"tag":"example","confidence":0.9}]`,
});
const cleaned = text.replace(/<think>[\s\S]*?<\/think>/gi, '').replace(/^```json\n?/, '').replace(/\n?```$/, '').trim();
const parsed = JSON.parse(cleaned);
const arr = Array.isArray(parsed) ? parsed : (parsed.tags || parsed.suggestions || []);
return arr.map((t: any) => ({
tag: t.tag || t.label || t.name || '',
confidence: t.confidence || t.score || 0.7,
}));
}
} catch (e) {
console.error('Error generating tags (OpenAI):', e);
return [];
@@ -58,18 +75,33 @@ export class OpenAIProvider implements AIProvider {
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('Suggested title'),
confidence: z.number().min(0).max(1).describe('Confidence level between 0 and 1')
}))
}),
prompt: prompt,
});
try {
const { object } = await generateObject({
model: this.model,
schema: z.object({
titles: z.array(z.object({
title: z.string().describe('Suggested title'),
confidence: z.number().min(0).max(1).describe('Confidence level between 0 and 1')
}))
}),
prompt: prompt,
});
return object.titles;
return object.titles;
} catch (err) {
console.warn('OpenAI generateObject titles failed, falling back to generateText:', err);
const { text } = await aiGenerateText({
model: this.model,
prompt: prompt + '\n\nRespond ONLY as a JSON array of title suggestions: [{"title": "Suggested title", "confidence": 0.9}]',
});
const cleaned = text.replace(/<think>[\s\S]*?<\/think>/gi, '').replace(/^```json\n?/, '').replace(/\n?```$/, '').trim();
const parsed = JSON.parse(cleaned);
const arr = Array.isArray(parsed) ? parsed : (parsed.titles || parsed.suggestions || []);
return arr.map((t: any) => ({
title: typeof t === 'string' ? t : t.title || t.name || '',
confidence: typeof t === 'number' ? t : (t.confidence || t.score || 0.8),
}));
}
} catch (e) {
console.error('Error generating titles (OpenAI):', e);
return [];