documente/prompts/4-content-generation.md

Prompt Sprint 4 - Content Generation

🎯 Sprint 4: Content Generation

Iniziato: 2026-04-06
Stato: 🟡 In Progress
Assegnato: @sprint-lead

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📋 Obiettivo

Implementare la generazione di contenuti multi-formato da parte di NotebookLM. Supportare audio (podcast), video, slide, infografiche, quiz, flashcard, report, mappe mentali e tabelle dati.

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🏗️ Architettura

Pattern (stesso di Sprint 1-3)

API Layer (FastAPI Routes)
    ↓
Service Layer (ArtifactService)
    ↓
External Layer (notebooklm-py client)

Endpoints da implementare (9 totali)

1. POST /api/v1/notebooks/{id}/generate/audio - Generare podcast
2. POST /api/v1/notebooks/{id}/generate/video - Generare video
3. POST /api/v1/notebooks/{id}/generate/slide-deck - Generare slide
4. POST /api/v1/notebooks/{id}/generate/infographic - Generare infografica
5. POST /api/v1/notebooks/{id}/generate/quiz - Generare quiz
6. POST /api/v1/notebooks/{id}/generate/flashcards - Generare flashcard
7. POST /api/v1/notebooks/{id}/generate/report - Generare report
8. POST /api/v1/notebooks/{id}/generate/mind-map - Generare mappa mentale
9. POST /api/v1/notebooks/{id}/generate/data-table - Generare tabella

Endpoints gestione artifacts

10. GET /api/v1/notebooks/{id}/artifacts - Listare artifacts
11. GET /api/v1/artifacts/{id}/status - Controllare stato
12. GET /api/v1/artifacts/{id}/download - Scaricare artifact

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📊 Task Breakdown Sprint 4

Fase 1: Specifiche

• SPEC-007: Analisi requisiti Content Generation
• Definire parametri per ogni tipo di contenuto
• Definire stati artifact (pending, processing, completed, failed)

Fase 2: API Design

• API-006: Modelli Pydantic per ogni tipo di generazione
• Documentazione endpoints

Fase 3: Implementazione

• DEV-015: ArtifactService
• DEV-016: Tutti gli endpoint POST /generate/*
• DEV-017: GET /artifacts
• DEV-018: GET /artifacts/{id}/status

Fase 4: Testing

• TEST-008: Unit tests ArtifactService
• TEST-009: Integration tests generation API

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🔧 Implementazione

ArtifactService Methods

class ArtifactService:
    async def generate_audio(notebook_id, instructions, format, length, language)
    async def generate_video(notebook_id, instructions, style, language)
    async def generate_slide_deck(notebook_id, format, length)
    async def generate_infographic(notebook_id, orientation, detail, style)
    async def generate_quiz(notebook_id, difficulty, quantity)
    async def generate_flashcards(notebook_id, difficulty, quantity)
    async def generate_report(notebook_id, format)
    async def generate_mind_map(notebook_id)
    async def generate_data_table(notebook_id, description)
    
    async def list_artifacts(notebook_id)
    async def get_status(artifact_id)
    async def download_artifact(artifact_id)

Modelli

# Request models
class AudioGenerationRequest(BaseModel):
    instructions: str
    format: str  # deep-dive, brief, critique, debate
    length: str  # short, default, long
    language: str

class VideoGenerationRequest(BaseModel):
    instructions: str
    style: str  # whiteboard, classic, anime, etc.
    language: str

class QuizGenerationRequest(BaseModel):
    difficulty: str  # easy, medium, hard
    quantity: str  # fewer, standard, more

# Response models
class Artifact(BaseModel):
    id: UUID
    notebook_id: UUID
    type: str  # audio, video, quiz, etc.
    title: str
    status: str  # pending, processing, completed, failed
    created_at: datetime
    completed_at: datetime | None
    download_url: str | None

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🎨 Content Types

Audio (Podcast)

• Formats: deep-dive, brief, critique, debate
• Length: short, default, long
• Languages: en, it, es, fr, de

Video

• Styles: whiteboard, classic, anime, kawaii, watercolor, etc.
• Languages: multi-language support

Slide Deck

• Formats: detailed, presenter
• Length: default, short

Infographic

• Orientation: landscape, portrait, square
• Detail: concise, standard, detailed
• Styles: professional, editorial, scientific, etc.

Quiz / Flashcards

• Difficulty: easy, medium, hard
• Quantity: fewer, standard, more

Mind Map

• Instant generation (no async)

Data Table

• Custom description for data extraction

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🚀 Prossimi Passi

1. @sprint-lead: Attivare @api-designer per API-006
2. @api-designer: Definire tutti i modelli generation
3. @tdd-developer: Iniziare implementazione ArtifactService

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Dipende da: Sprint 3 (Chat) ✅
Blocca: Sprint 5 (Webhooks) 🔴

Nota: Questo è lo sprint più complesso con 12 endpoint da implementare!