sepehr e6bcdea641 fix: remove hardcoded localhost fallbacks, require explicit config
Critical fix for Docker deployment where AI features were trying to connect
to localhost:11434 instead of using configured provider (Ollama Docker service
or OpenAI).

Problems fixed:
1. Reformulation (clarify/shorten/improve) failing with ECONNREFUSED 127.0.0.1:11434
2. Auto-labels failing with same error
3. Notebook summaries failing
4. Could not switch from Ollama to OpenAI in admin

Root cause:
- Code had hardcoded fallback to 'http://localhost:11434' in multiple places
- .env.docker file not created on server (gitignore'd)
- No validation that required environment variables were set

Changes:

1. lib/ai/factory.ts:
   - Remove hardcoded 'http://localhost:11434' fallback
   - Only use localhost for local development (NODE_ENV !== 'production')
   - Throw error if OLLAMA_BASE_URL not set in production

2. lib/ai/providers/ollama.ts:
   - Remove default parameter 'http://localhost:11434' from constructor
   - Require baseUrl to be explicitly passed
   - Throw error if baseUrl is missing

3. lib/ai/services/paragraph-refactor.service.ts:
   - Remove 'http://localhost:11434' fallback (2 locations)
   - Require OLLAMA_BASE_URL to be set
   - Throw clear error if not configured

4. app/(main)/admin/settings/admin-settings-form.tsx:
   - Add debug info showing current provider state
   - Display database config value for transparency
   - Help troubleshoot provider selection issues

5. DOCKER-SETUP.md:
   - Complete guide for Docker configuration
   - Instructions for .env.docker setup
   - Examples for Ollama Docker, OpenAI, and external Ollama
   - Troubleshooting common issues

Usage:
On server, create .env.docker with proper provider configuration:
- Ollama in Docker: OLLAMA_BASE_URL="http://ollama:11434"
- OpenAI: OPENAI_API_KEY="sk-..."
- External Ollama: OLLAMA_BASE_URL="http://SERVER_IP:11434"

Then in admin interface, users can independently configure:
- Tags Provider (for auto-labels, AI features)
- Embeddings Provider (for semantic search)

Result:
✓ Clear errors if Ollama not configured
✓ Can switch to OpenAI freely in admin
✓ No more hardcoded localhost in production
✓ Proper separation between local dev and Docker production

Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>
2026-01-12 22:28:39 +01:00

138 lines
4.2 KiB
TypeScript

import { AIProvider, TagSuggestion, TitleSuggestion } from '../types';
export class OllamaProvider implements AIProvider {
private baseUrl: string;
private modelName: string;
private embeddingModelName: string;
constructor(baseUrl: string, modelName: string = 'llama3', embeddingModelName?: string) {
if (!baseUrl) {
throw new Error('baseUrl is required for OllamaProvider')
}
// Ensure baseUrl ends with /api for Ollama API
this.baseUrl = baseUrl.endsWith('/api') ? baseUrl : `${baseUrl}/api`;
this.modelName = modelName;
this.embeddingModelName = embeddingModelName || modelName;
}
async generateTags(content: string): Promise<TagSuggestion[]> {
try {
const response = await fetch(`${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(/\[\s*\{[\s\S]*\}\s*\]/);
if (jsonMatch) {
return JSON.parse(jsonMatch[0]);
}
// Support pour le format { "tags": [...] }
const objectMatch = text.match(/\{\s*"tags"\s*:\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.embeddingModelName,
prompt: text,
}),
});
if (!response.ok) throw new Error(`Ollama error: ${response.statusText}`);
const data = await response.json();
return data.embedding;
} catch (e) {
console.error('Erreur embeddings directs Ollama:', e);
return [];
}
}
async generateTitles(prompt: string): Promise<TitleSuggestion[]> {
try {
const response = await fetch(`${this.baseUrl}/generate`, {
method: 'POST',
headers: { 'Content-Type': 'application/json' },
body: JSON.stringify({
model: this.modelName,
prompt: `${prompt}
Réponds UNIQUEMENT sous forme de tableau JSON : [{"title": "string", "confidence": number}]`,
stream: false,
}),
});
if (!response.ok) throw new Error(`Ollama error: ${response.statusText}`);
const data = await response.json();
const text = data.response;
// Extraire le JSON de la réponse
const jsonMatch = text.match(/\[\s*\{[\s\S]*\}\s*\]/);
if (jsonMatch) {
return JSON.parse(jsonMatch[0]);
}
return [];
} catch (e) {
console.error('Erreur génération titres Ollama:', e);
return [];
}
}
async generateText(prompt: string): Promise<string> {
try {
const response = await fetch(`${this.baseUrl}/generate`, {
method: 'POST',
headers: { 'Content-Type': 'application/json' },
body: JSON.stringify({
model: this.modelName,
prompt: prompt,
stream: false,
}),
});
if (!response.ok) throw new Error(`Ollama error: ${response.statusText}`);
const data = await response.json();
return data.response.trim();
} catch (e) {
console.error('Erreur génération texte Ollama:', e);
throw e;
}
}
}