Roadmap di Sviluppo¶
La roadmap di SearchMuse è organizzata in milestone versionate che progressivamente aggiungono funzionalità, migliorano qualità, e espandono capability. Questa roadmap riflette priorità della comunità e feedback utenti.
Metodologia di Versioning¶
SearchMuse segue Semantic Versioning: - MAJOR (X.0.0): Breaking changes, rearchitecture - MINOR (0.X.0): Nuove features, backward compatible - PATCH (0.0.X): Bug fixes, performance improvements
v0.1.0 - MVP (Minimum Viable Product)¶
Timeline: Febbraio-Marzo 2026 Status: In Development
Obiettivi Principali¶
Rilasciare un prodotto funzionante che supporta il caso d'uso principale: ricerca iterativa con citazioni verificabili.
Featuree¶
Core Search: - ✓ Query parsing e concetto extraction - ✓ Single-round ricerca DuckDuckGo - ✓ HTML scraping (trafilatura) - ✓ Content extraction e cleaning - ✓ Basic LLM relevance scoring (Mistral)
Iteration Support: - ✓ Query refinement basato su coverage analysis - ✓ Max 3 iterazioni (hardcoded) - ✓ Coverage e relevance scoring - ✓ Convergence detection
Citation & Output: - ✓ Citazione automatica (URL, titolo, author, date) - ✓ Markdown output (default) - ✓ Plain text output - ✓ JSON output (structured)
CLI Interface:
- ✓ Simple string input: searchmuse "query"
- ✓ JSON config input
- ✓ Output to file
- ✓ Basic logging
Documentation: - ✓ README e quick start - ✓ Vision e goals - ✓ Use cases - ✓ Architecture overview
Deliverables¶
- Repositorio GitHub public
- Docker image per easy setup
- Ollama integration (Mistral default)
- 50+ pagine documentazione
Success Criteria¶
- ✓ Ricerca basic funziona < 2 minuti
- ✓ Coverage >= 75% per query semplici
- ✓ Citazioni sono 95% accurate
- ✓ Zero dati inviati a servizi cloud
v0.2.0 - Iterative Refinement¶
Timeline: Marzo-Maggio 2026 Status: Planned
Obiettivi Principali¶
Migliorare drasticamente la qualità iterativa, supportare più modelli LLM, aggiungere API.
Features Nuove¶
Iterazione Avanzata: - [ ] Dynamic max_iterations (basato su query complexity) - [ ] Multi-strategy query generation (non solo LLM) - [ ] Aspect-driven iteration (enfatizza aspetti missing) - [ ] Early termination se coverage converge rapidamente
Modelli LLM: - [ ] Support per Llama3, Phi3, Neural Chat - [ ] Model auto-selection basato su hardware - [ ] Fallback chain (model failure) - [ ] Quantization support (4-bit, 8-bit)
Scraping Avanzato: - [ ] JavaScript rendering (Playwright) - [ ] Wayback Machine integration - [ ] Cookie handling - [ ] User-Agent rotation
API HTTP: - [ ] REST API (FastAPI) - [ ] Streaming SSE (progress events) - [ ] Batch query processing - [ ] Rate limiting
Output Formats: - [ ] HTML output - [ ] APA/MLA citation formats - [ ] PDF export - [ ] Markdown with table of contents
Configurazione: - [ ] YAML config file support - [ ] Environment variable override - [ ] Persistent settings (home dir) - [ ] Model caching management
Quality Improvements¶
- [ ] Reduce hallucinations (temperature tuning)
- [ ] Better source authority scoring
- [ ] Duplicate detection (fuzzy matching)
- [ ] Content confidence scoring
Documentation¶
- [ ] API documentation (OpenAPI)
- [ ] Deployment guides (Docker, Kubernetes)
- [ ] Troubleshooting guide
- [ ] Video tutorials
Success Criteria¶
- [ ] Coverage >= 80% per 80% di query
- [ ] API latency < 200ms (per request)
- [ ] Memory usage < 8GB (Mistral)
- [ ] Support 4+ modelli LLM
v0.3.0 - Polish & Optimization¶
Timeline: Maggio-Giugno 2026 Status: Planned
Obiettivi Principali¶
Ottimizzare performance, migliorare UX, aggiungere avanzate features, production-ready stability.
Features Nuove¶
Performance: - [ ] Request parallelization (async) - [ ] Caching strategy (Redis-compatible) - [ ] Embedding-based result re-ranking - [ ] Batch processing optimization
Ricerca Avanzata: - [ ] Source-specific search operators - [ ] Temporal filtering (data range) - [ ] Language-specific search - [ ] Domain whitelisting/blacklisting
Feature Specializzate: - [ ] Comparison mode (template-based) - [ ] Trend detection mode - [ ] Literature review mode (bibliography) - [ ] FAQ generation mode
User Experience: - [ ] CLI color output, progress bars - [ ] Interactive mode (refine iteratively) - [ ] Syntax highlighting per language - [ ] Better error messages
Extensibility: - [ ] Plugin system per custom LLM models - [ ] Custom scraper registration - [ ] Hook-based customization - [ ] Python SDK package
Monitoring: - [ ] Quality metrics dashboard - [ ] Performance benchmarking - [ ] Error tracking e logging - [ ] Usage analytics (local)
Security & Privacy¶
- [ ] Input sanitization (injection prevention)
- [ ] Output escaping (XSS prevention)
- [ ] Rate limiting per source
- [ ] Offline-first mode verification
Quality Assurance¶
- [ ] Automated test suite (80%+ coverage)
- [ ] Integration tests
- [ ] E2E test suite
- [ ] Performance regression tests
Documentation¶
- [ ] Advanced user guide
- [ ] Architecture deep-dive
- [ ] Plugin development guide
- [ ] Performance tuning guide
Success Criteria¶
- [ ] Quality score >= 85 per ricerca
- [ ] P95 latency < 3 minuti
- [ ] 99.5% uptime (self-hosted)
- [ ] Zero known security issues
v1.0.0 - Production Release¶
Timeline: Giugno-Luglio 2026 Status: Planned
Obiettivi Principali¶
Rilascio stabile, enterprise-ready, con community support robusto.
Features Nuove¶
Enterprise Features: - [ ] Multi-user support - [ ] Role-based access control (RBAC) - [ ] Audit logging - [ ] Data retention policies
Integration: - [ ] Zapier integration - [ ] Slack bot integration - [ ] VS Code extension - [ ] Browser extension
Advanced LLM: - [ ] Fine-tuning support (domain-specific) - [ ] Embedding-based search enhancement - [ ] Retrieval-augmented generation (RAG) - [ ] Multi-model ensemble
Accessibility: - [ ] Mobile-responsive web UI - [ ] Voice input support - [ ] Screen reader optimization - [ ] Multiple language UI
Community: - [ ] Model sharing registry - [ ] Scraper sharing registry - [ ] Plugin marketplace - [ ] Community forum
Product Stability¶
- [ ] Long-term support (LTS) commitment
- [ ] Backwards compatibility guarantee
- [ ] Migration guides per version
- [ ] Deprecation policy
Documentation¶
- [ ] Complete API reference
- [ ] Complete user manual
- [ ] Complete admin manual
- [ ] Enterprise deployment guide
Success Criteria¶
- [ ] 1000+ GitHub stars
- [ ] 50+ community extensions
- [ ] 95%+ citation accuracy
- [ ] Production deployments (known)
Futuro (Post v1.0.0)¶
v1.1.0 - Advanced Search Modes¶
- Real-time search (live web monitoring)
- Deep web search (academic databases)
- Image search support
- Video transcript search
v1.2.0 - Multi-Language Support¶
- Native support 10+ lingue
- Translation of results
- Multilingual source mixing
- Language-specific LLM models
v2.0.0 - Knowledge Graph Integration¶
- Entity extraction e linking
- Knowledge graph construction
- Semantic search capabilities
- Fact verification against KG
v2.1.0 - AI-Assisted Research¶
- Research paper recommendation
- Study guide generation
- Question generation da topics
- Concept map visualization
v3.0.0 - Proprietary Model Integration¶
- Fine-tuned model per domain (science, tech, news)
- Domain-specific evaluation metrics
- Transfer learning capabilities
- Model marketplace integration
Community Roadmap Input¶
SearchMuse roadmap è driven da community. Se hai feature request:
- Verifica existing issues: Potrebbe già essere planned
- Apri GitHub discussion: Describe use case, motivation
- Vota existing features: Upvote reactions su popular issues
- Contribuisci: Se puoi, implementa e proponi PR
Most Requested Features (From Community)¶
Basato su GitHub issues e discussions:
1. [POPULAR] Browser extension (50 upvotes)
Timeline: Potentially v1.0.0 if developer available
2. [POPULAR] Slack bot (48 upvotes)
Timeline: v1.0.0
3. [REQUESTED] Support per siti specifici (30 upvotes)
Timeline: Continuous (v0.2.0+)
4. [REQUESTED] Comparison mode template (25 upvotes)
Timeline: v0.3.0
5. [REQUESTED] Citation import in Zotero (20 upvotes)
Timeline: v1.1.0
6. [REQUESTED] Fine-tune model per dominio (15 upvotes)
Timeline: v2.0.0
Fattori che Potrebbero Impattare Roadmap¶
Fattori Positivi (Accelerare)¶
- Significante community contribution
- Sponsored development (grants, donations)
- Strategic partnership (con Ollama, HuggingFace)
- Critical security discovery (forcing accelerated release)
Fattori Negativi (Ritardare)¶
- Breaking changes in dependencies (Ollama API)
- Scarsa community adoption
- Impossibilità di risolvere technical debt
- Burnout di maintainer
Wildcard Fattori¶
- Availability di nuovi modelli LLM (potrebbero cambiare priorities)
- Changes in web scraping landscape (legal, technical)
- Regulatory changes (privacy, data protection)
- Nuovo competitor (forcing feature acceleration)
Version Support Matrix¶
| Version | Release | Support End | Status |
|---|---|---|---|
| 0.1.x | Mar 2026 | Sep 2026 | Early |
| 0.2.x | May 2026 | Nov 2026 | Beta |
| 0.3.x | Jun 2026 | Dec 2026 | Beta |
| 1.0.x | Jul 2026 | Jul 2027 | LTS |
| 1.1.x | Sep 2026 | Mar 2027 | Current |
LTS Versions: Ricevono security fixes fino a expiry date
Migration Paths¶
Da v0.1.x a v0.2.x¶
- Backward compatible
- Semplice:
pip install searchmuse==0.2.0 - Config file optional
Da v0.x a v1.0.0¶
- Potenziali breaking changes
- Migration guide provided
- Deprecation warnings in v0.3.x
Da v1.x a v2.0.0¶
- Garantita migration path
- Deprecation periode (6 months)
- Automated migration tools se possibile
Come Stare Aggiornato¶
- Watch GitHub Repository: Get notified di releases
- Subscribe Newsletter: Monthly updates
- Join Discord Community: Real-time development discussion
- Follow Twitter: Latest announcements
Versione Roadmap: 1.0 Ultimo aggiornamento: 2026-02-28 Prossimo Review: 2026-04-30