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>
148 lines
5.3 KiB
Python
148 lines
5.3 KiB
Python
"""
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ActiveBlue AI Agent — Odoo 18 RAG Specialist
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=============================================
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Drop-in specialist agent for the ActiveBlue AI system.
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Implements the PeerBus interface defined in ACTIVEBLUE_AI_SPEC.md.
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Usage:
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from api.odoo_rag_agent import OdooRagAgent
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agent = OdooRagAgent(rag_url="http://localhost:8000")
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result = await agent.ask("How do I run a payroll batch?")
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print(result["answer"])
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"""
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import json
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import httpx
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import logging
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from typing import AsyncIterator
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log = logging.getLogger(__name__)
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class OdooRagAgent:
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name = "odoo18_rag"
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description = "Answers Odoo 18 questions using RAG over official documentation"
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capabilities = [
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"odoo_how_to",
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"odoo_configuration",
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"odoo_troubleshooting",
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"odoo_workflow",
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]
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privacy_mode = "local" # uses local Ollama — HIPAA safe
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def __init__(
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self,
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rag_url: str = "http://localhost:8000",
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timeout: int = 120,
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default_model: str | None = None,
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):
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self.rag_url = rag_url.rstrip("/")
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self.timeout = timeout
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self.default_model = default_model
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async def ask(
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self,
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question: str,
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module: str | None = None,
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top_k: int = 6,
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temperature: float = 0.3,
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) -> dict:
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payload = {"question": question, "top_k": top_k, "temperature": temperature}
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if module:
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payload["module"] = module
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if self.default_model:
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payload["model"] = self.default_model
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async with httpx.AsyncClient(timeout=self.timeout) as client:
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resp = await client.post(f"{self.rag_url}/ask", json=payload)
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resp.raise_for_status()
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return resp.json()
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async def ask_stream(
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self,
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question: str,
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module: str | None = None,
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top_k: int = 6,
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temperature: float = 0.3,
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) -> AsyncIterator[str]:
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payload = {"question": question, "top_k": top_k, "temperature": temperature}
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if module:
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payload["module"] = module
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async with httpx.AsyncClient(timeout=self.timeout) as client:
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async with client.stream("POST", f"{self.rag_url}/ask/stream", json=payload) as resp:
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async for line in resp.aiter_lines():
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if line.startswith("data: "):
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data_str = line[6:]
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if data_str == "[DONE]":
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break
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try:
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data = json.loads(data_str)
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if data.get("type") == "token":
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yield data["content"]
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elif data.get("type") == "sources":
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yield json.dumps(data)
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except json.JSONDecodeError:
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continue
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async def handle_peer_message(self, message: dict) -> dict:
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"""PeerBus message handler for the ActiveBlue Master AI."""
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action = message.get("action")
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payload = message.get("payload", {})
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req_id = message.get("request_id")
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if action == "ask":
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result = await self.ask(
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question = payload.get("question", ""),
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module = payload.get("module"),
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top_k = payload.get("top_k", 6),
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temperature = payload.get("temperature", 0.3),
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)
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return {"request_id": req_id, "agent": self.name, "status": "ok", "result": result}
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elif action == "capabilities":
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return {
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"request_id": req_id,
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"agent": self.name,
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"capabilities": self.capabilities,
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"description": self.description,
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"privacy_mode": self.privacy_mode,
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}
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elif action == "health":
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return await self.health()
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return {"request_id": req_id, "agent": self.name, "status": "error", "error": f"Unknown action: {action}"}
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async def health(self) -> dict:
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try:
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async with httpx.AsyncClient(timeout=5) as client:
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resp = await client.get(f"{self.rag_url}/health")
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return {"agent": self.name, "status": "ok", "rag": resp.json()}
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except Exception as e:
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return {"agent": self.name, "status": "error", "error": str(e)}
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# ── Module convenience wrappers ───────────────────────────────────────────
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async def ask_accounting(self, question: str) -> dict:
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return await self.ask(question, module="accounting")
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async def ask_payroll(self, question: str) -> dict:
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return await self.ask(question, module="payroll")
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async def ask_inventory(self, question: str) -> dict:
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return await self.ask(question, module="inventory")
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async def ask_crm(self, question: str) -> dict:
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return await self.ask(question, module="crm")
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async def ask_hr(self, question: str) -> dict:
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return await self.ask(question, module="employees")
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async def ask_manufacturing(self, question: str) -> dict:
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return await self.ask(question, module="manufacturing")
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async def ask_helpdesk(self, question: str) -> dict:
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return await self.ask(question, module="helpdesk")
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