docs: reorganize README with improved documentation links

Reorganize documentation section in README.md: - Add direct link to integration guide in Panoramica section - Remove duplicate documentation references - Organize docs into logical categories: * Guide Principali (integration guide, API overview) * NotebookLM Agent (SKILL.md, PRD, AGENTS.md) * DocuMente (prd-v2, frontend-plan, test coverage) * Generale (contributing, changelog, license) - Add table format for better readability - Update provider list to include Ollama and LM Studio - Add emojis for visual organization - Include Local LLM provider config in .env example Improves discoverability of documentation and provides clear navigation for users.
2026-04-06 18:36:19 +02:00
parent fbbd3ed50c
commit e239829938
1 changed files with 59 additions and 42 deletions
--- a/README.md
+++ b/README.md
@@ -17,6 +17,7 @@ Questo repository contiene **due sistemi AI complementari**:
 ## Indice

 - [Panoramica](#panoramica)
+- [Integrazione NotebookLM + RAG](#integrazione-notebooklm--rag)
 - [Componenti](#componenti)
 - [Requisiti](#requisiti)
 - [Installazione](#installazione)
@@ -31,9 +32,6 @@ Questo repository contiene **due sistemi AI complementari**:

 ## Panoramica

-### Integrazione
- [docs/integration.md](./docs/integration.md) - Guida integrazione NotebookLM + RAG
-
 ### NotebookLM Agent

 Interfaccia API e webhook per **Google NotebookLM** che permette:
@@ -47,10 +45,11 @@ Interfaccia API e webhook per **Google NotebookLM** che permette:
 ### DocuMente (Agentic RAG)

 Sistema **Retrieval-Augmented Generation** standalone con:
- Supporto per 8 provider LLM diversi
+- Supporto per 8+ provider LLM (cloud e locali)
 - Upload e indicizzazione documenti (PDF, DOCX, TXT, MD)
 - Chat conversazionale con i tuoi documenti
 - Interfaccia web moderna (React + TypeScript)
+- **Integrazione con NotebookLM** - Ricerca semantica sui notebook

 **Ideale per:** Knowledge management, Document analysis, Research assistant

@@ -82,17 +81,12 @@ NotebookLM → NotebookLMIndexerService → Qdrant Vector Store
 3. **Ricerca**: Le query RAG possono filtrare per notebook_id specifici
 4. **Risposta**: Il LLM riceve contesto dai notebook selezionati

---
-
-
+📚 **[Guida Completa Integrazione](./docs/integration.md)** - API, esempi, best practices

 ---

 ## Componenti

-### Integrazione
- [docs/integration.md](./docs/integration.md) - Guida integrazione NotebookLM + RAG
-
 ### NotebookLM Agent

 ```
@@ -140,12 +134,12 @@ src/agentic_rag/
 │       ├── query.py      # Query RAG
 │       ├── chat.py       # Chat conversazionale
 │       ├── providers.py  # Gestione provider LLM
-│       └── notebooklm_sync.py  # [NUOVO] Sync NotebookLM
+│       └── notebooklm_sync.py  # Sync NotebookLM
 ├── services/             # Business logic
 │   ├── rag_service.py    # Core RAG logic
 │   ├── vector_store.py   # Qdrant integration
 │   ├── document_service.py
-│   └── notebooklm_indexer.py  # [NUOVO] Indexing service
+│   └── notebooklm_indexer.py  # Indexing service
 └── core/                 # Configurazioni
    ├── config.py        # Multi-provider config
    └── llm_factory.py   # LLM factory pattern
@@ -181,16 +175,18 @@ POST /api/v1/query/notebooks

 **Provider LLM Supportati:**

-| Provider | Modelli Principali | Stato |
-|----------|-------------------|-------|
-| **OpenAI** | GPT-4o, GPT-4, GPT-3.5 | ✅ |
-| **Z.AI** | zai-large, zai-medium | ✅ |
-| **OpenCode Zen** | zen-1, zen-lite | ✅ |
-| **OpenRouter** | Multi-model access | ✅ |
-| **Anthropic** | Claude 3.5, Claude 3 | ✅ |
-| **Google** | Gemini 1.5 Pro/Flash | ✅ |
-| **Mistral** | Mistral Large/Medium | ✅ |
-| **Azure** | GPT-4, GPT-4o | ✅ |
+| Provider | Tipo | Modelli Principali |
+|----------|------|-------------------|
+| **OpenAI** | Cloud | GPT-4o, GPT-4, GPT-3.5 |
+| **Anthropic** | Cloud | Claude 3.5, Claude 3 |
+| **Google** | Cloud | Gemini 1.5 Pro/Flash |
+| **Mistral** | Cloud | Mistral Large/Medium |
+| **Azure** | Cloud | GPT-4, GPT-4o |
+| **Z.AI** | Cloud | zai-large, zai-medium |
+| **OpenCode Zen** | Cloud | zen-1, zen-lite |
+| **OpenRouter** | Cloud | Multi-model access |
+| **Ollama** | 🏠 Locale | llama3.2, mistral, qwen |
+| **LM Studio** | 🏠 Locale | Any loaded model |

 ---

@@ -261,6 +257,10 @@ MISTRAL_API_KEY=...
 AZURE_API_KEY=...
 AZURE_ENDPOINT=https://your-resource.openai.azure.com

+# Local LLM Providers (no API key needed)
+OLLAMA_BASE_URL=http://localhost:11434
+LMSTUDIO_BASE_URL=http://localhost:1234
+
 # Vector Store (Qdrant)
 QDRANT_HOST=localhost
 QDRANT_PORT=6333
@@ -285,9 +285,6 @@ DEBUG=false

 ## Avvio

-### Integrazione
- [docs/integration.md](./docs/integration.md) - Guida integrazione NotebookLM + RAG
-
 ### NotebookLM Agent

 ```bash
@@ -363,7 +360,9 @@ curl -X POST http://localhost:8000/api/v1/query \
    "provider": "openai",
    "model": "gpt-4o-mini"
  }'
+```

+---

 ### Integrazione NotebookLM + RAG

@@ -382,7 +381,9 @@ curl -X DELETE http://localhost:8000/api/v1/notebooklm/sync/{notebook_id}
 **Query sui notebook:**
 ```bash
 # Query solo sui notebook (senza documenti locali)
-curl -X POST http://localhost:8000/api/v1/query/notebooks   -H "Content-Type: application/json"   -d '{
+curl -X POST http://localhost:8000/api/v1/query/notebooks \
+  -H "Content-Type: application/json" \
+  -d '{
    "question": "Quali sono le conclusioni principali?",
    "notebook_ids": ["uuid-del-notebook"],
    "k": 10,
@@ -390,7 +391,9 @@ curl -X POST http://localhost:8000/api/v1/query/notebooks   -H "Content-Type: ap
  }'

 # Query mista (documenti + notebook)
-curl -X POST http://localhost:8000/api/v1/query   -H "Content-Type: application/json"   -d '{
+curl -X POST http://localhost:8000/api/v1/query \
+  -H "Content-Type: application/json" \
+  -d '{
    "question": "Confronta le informazioni tra i documenti e i notebook",
    "notebook_ids": ["uuid-1", "uuid-2"],
    "include_documents": true,
@@ -455,22 +458,36 @@ documente/

 ## Documentazione

-### Integrazione
- [docs/integration.md](./docs/integration.md) - Guida integrazione NotebookLM + RAG
+### 📚 Guide Principali

-### NotebookLM Agent
- [SKILL.md](./SKILL.md) - Skill definition per agenti AI
- [prd.md](./prd.md) - Product Requirements Document
- [AGENTS.md](./AGENTS.md) - Linee guida per sviluppo
+| Documento | Descrizione |
+|-----------|-------------|
+| **[docs/integration.md](./docs/integration.md)** | Guida completa integrazione NotebookLM + RAG - API, esempi, best practices |
+| **[docs/README.md](./docs/README.md)** | Panoramica documentazione API e endpoint |

-### DocuMente
- [prd-v2.md](./prd-v2.md) - Product Requirements Document
- [frontend-plan.md](./frontend-plan.md) - Piano sviluppo frontend
- [TEST_COVERAGE_REPORT.md](./TEST_COVERAGE_REPORT.md) - Report coverage
+### 🤖 NotebookLM Agent

-### Generale
- [CONTRIBUTING.md](./CONTRIBUTING.md) - Come contribuire
- [CHANGELOG.md](./CHANGELOG.md) - Cronologia modifiche
+| Documento | Descrizione |
+|-----------|-------------|
+| **[SKILL.md](./SKILL.md)** | Skill definition per agenti AI - API reference completo |
+| **[prd.md](./prd.md)** | Product Requirements Document |
+| **[AGENTS.md](./AGENTS.md)** | Linee guida per sviluppo |
+
+### 🧠 DocuMente (Agentic RAG)
+
+| Documento | Descrizione |
+|-----------|-------------|
+| **[prd-v2.md](./prd-v2.md)** | Product Requirements Document v2 |
+| **[frontend-plan.md](./frontend-plan.md)** | Piano sviluppo frontend |
+| **[TEST_COVERAGE_REPORT.md](./TEST_COVERAGE_REPORT.md)** | Report coverage test |
+
+### 📝 Generale
+
+| Documento | Descrizione |
+|-----------|-------------|
+| **[CONTRIBUTING.md](./CONTRIBUTING.md)** | Come contribuire al progetto |
+| **[CHANGELOG.md](./CHANGELOG.md)** | Cronologia modifiche e release |
+| **[LICENSE](./LICENSE)** | Termini di licenza |

 ---