Initial commit: Odoo 18 RAG stack

Scraper, indexer, and FastAPI query service for Retrieval-Augmented Generation over Odoo 18 documentation. Uses Qdrant + Ollama (nomic-embed-text + llama3.1). Integrates with ActiveBlue PeerBus agent interface. Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
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+# odoo18-rag
+
+Retrieval-Augmented Generation over the full Odoo 18 documentation.
+Built for the ActiveBlue AI agent stack.
+
+## Stack
+
+| Component | What it does |
+|---|---|
+| `scraper/` | Crawls odoo.com/documentation/18.0, outputs clean JSONL |
+| `indexer/` | Chunks pages, embeds with `nomic-embed-text`, loads Qdrant |
+| `api/` | FastAPI — `/ask`, `/ask/stream`, `/agent/ask`, `/health` |
+| Qdrant | Vector database (Docker) |
+| Ollama @ `miaai:11434` | Embeddings + generation (local, HIPAA-safe) |
+
+## Quick start
+
+```bash
+# 1. Pull the embedding model on miaai
+ollama pull nomic-embed-text
+
+# 2. Start Qdrant + RAG API
+docker compose up -d
+
+# 3. Scrape the docs (~800 pages, ~20 min)
+docker compose run --rm scraper
+
+# 4. Index into Qdrant (~30-40 min)
+docker compose run --rm indexer
+
+# 5. Test
+curl http://localhost:8000/health
+curl -X POST http://localhost:8000/ask \
+  -H "Content-Type: application/json" \
+  -d '{"question": "How do I run a payroll batch in Odoo 18?"}'
+```
+
+## Endpoints
+
+| Method | Path | Description |
+|---|---|---|
+| GET | `/health` | Qdrant + Ollama connectivity |
+| GET | `/stats` | Vector count, models in use |
+| GET | `/modules` | List indexed Odoo modules |
+| POST | `/ask` | Blocking answer + sources |
+| POST | `/ask/stream` | SSE token stream |
+| POST | `/agent/ask` | ActiveBlue PeerBus integration |
+
+### Ask with module filter
+
+```bash
+curl -X POST http://localhost:8000/ask \
+  -H "Content-Type: application/json" \
+  -d '{"question": "How do reordering rules work?", "module": "inventory"}'
+```
+
+### Streaming
+
+```bash
+curl -N -X POST http://localhost:8000/ask/stream \
+  -H "Content-Type: application/json" \
+  -d '{"question": "Explain the Quote-to-Cash workflow"}'
+```
+
+## Agent integration
+
+```python
+from api.odoo_rag_agent import OdooRagAgent
+
+agent = OdooRagAgent(rag_url="http://localhost:8000")
+
+# Generic
+result = await agent.ask("How do I configure NACHA payments?")
+
+# Module-scoped
+result = await agent.ask_payroll("How do I generate a payslip batch?")
+result = await agent.ask_accounting("What is the chart of accounts?")
+result = await agent.ask_inventory("How does MTO work?")
+
+# Streaming
+async for token in agent.ask_stream("Explain the CRM pipeline"):
+    print(token, end="", flush=True)
+
+# PeerBus
+response = await agent.handle_peer_message({
+    "action": "ask",
+    "payload": {"question": "How do I set up taxes?", "module": "accounting"},
+    "request_id": "req-001"
+})
+```
+
+## Re-indexing
+
+Odoo releases doc updates regularly. Re-index to stay current:
+
+```bash
+docker compose run --rm scraper
+docker compose run --rm indexer python /app/indexer/indexer.py --reset
+```
+
+Or add a monthly cron on the host:
+
+```cron
+0 3 1 * * cd /opt/odoo18-rag && docker compose run --rm scraper && docker compose run --rm indexer python /app/indexer/indexer.py --reset
+```
+
+## Scraper options
+
+```bash
+# Single module only
+docker compose run --rm scraper python /app/scraper/scraper.py --module accounting
+
+# Quick test (first 50 pages)
+docker compose run --rm scraper python /app/scraper/scraper.py --limit 50
+```
+
+## Environment variables
+
+All configurable via `docker-compose.yml` environment section:
+
+| Variable | Default | Description |
+|---|---|---|
+| `OLLAMA_URL` | `http://miaai:11434` | Ollama endpoint |
+| `QDRANT_URL` | `http://qdrant:6333` | Qdrant endpoint |
+| `EMBED_MODEL` | `nomic-embed-text` | Embedding model |
+| `GEN_MODEL` | `llama3.1` | Generation model |
+| `COLLECTION_NAME` | `odoo18_docs` | Qdrant collection |