OSVauco/agents/core-logic/agent.py

177 lines
6.3 KiB
Python

#!/usr/bin/env python3
"""
agent.py — OSVauco OPAX agent.
Modes:
light — gemini-2.5-flash, $1/task
heavy — gemini-2.5-pro, $3/task
Legacy 'A' / 'A+' normaliseres automatisk.
Authoriserte brukere for heavy: opax, admin
Gjeldende modell-tilgjengelighet (mai 2026):
gemini-2.0-flash-001 kun for eksisterende kunder — bruk IKKE.
gemini-2.5-flash / gemini-2.5-pro krever GOOGLE_CLOUD_LOCATION=global.
"""
import asyncio
import os
import logging
from typing import Literal
from google.adk.agents import Agent
from google.adk.runners import Runner
from google.adk.sessions.in_memory_session_service import InMemorySessionService
from google.genai import types
logger = logging.getLogger(__name__)
PROJECT_ID = os.environ.get("GOOGLE_CLOUD_PROJECT", "propane-will-491900-m5")
LOCATION = os.environ.get("GOOGLE_CLOUD_LOCATION", "global")
RAG_CORPUS = os.environ.get("RAG_CORPUS", "")
# Light mode — gemini-2.5-flash (GA, global)
ORCHESTRATOR_MODEL = os.environ.get("ORCHESTRATOR_MODEL", "gemini-2.5-flash")
SUBAGENT_MODEL = os.environ.get("SUBAGENT_MODEL", "gemini-2.5-flash")
REASONING_MODEL = os.environ.get("REASONING_MODEL", "gemini-2.5-flash")
# Heavy mode — gemini-2.5-pro (GA, global)
HEAVY_ORCHESTRATOR = os.environ.get("HEAVY_ORCHESTRATOR_MODEL", "gemini-2.5-pro")
HEAVY_SUBAGENT = os.environ.get("HEAVY_SUBAGENT_MODEL", "gemini-2.5-pro")
HEAVY_REASONING = os.environ.get("HEAVY_REASONING_MODEL", "gemini-2.5-flash")
BUDGET_LIGHT = float(os.environ.get("BUDGET_A_USD_PER_TASK", "1.0"))
BUDGET_HEAVY = float(os.environ.get("HEAVY_MODE_BUDGET_USD_PER_DAY", "3.0"))
HEAVY_MODE_ALLOWED_USERS = ["opax", "admin"]
Mode = Literal["light", "heavy"]
APP_NAME = "opax"
def _normalize_mode(mode: str) -> str:
mapping = {"A": "light", "A+": "heavy", "light": "light", "heavy": "heavy"}
if mode not in mapping:
raise ValueError(
f"Invalid mode '{mode}'. Must be 'light' or 'heavy' "
f"(also accepts legacy 'A' / 'A+')."
)
return mapping[mode]
def authorize_mode(user_id: str, mode: str) -> None:
mode = _normalize_mode(mode)
if mode == "heavy" and user_id not in HEAVY_MODE_ALLOWED_USERS:
raise PermissionError(
f"User '{user_id}' is not authorized for heavy mode. "
f"Authorized: {HEAVY_MODE_ALLOWED_USERS}"
)
rag_tool = None
if RAG_CORPUS:
try:
from google.adk.tools.retrieval.vertex_ai_rag_retrieval import VertexAiRagRetrieval
from vertexai.preview import rag
rag_tool = VertexAiRagRetrieval(
name="retrieve_knowledge",
description="Retrieve relevant documentation and context from the OSVauco knowledge base.",
rag_resources=[rag.RagResource(rag_corpus=RAG_CORPUS)],
similarity_top_k=10,
vector_distance_threshold=0.6,
)
logger.info(f"RAG tool initialised: {RAG_CORPUS}")
except ImportError as e:
logger.warning(f"VertexAiRagRetrieval ikke tilgjengelig: {e}")
else:
logger.warning("RAG_CORPUS ikke satt — kjører uten RAG")
def get_models_for_mode(mode: Mode) -> dict:
if mode == "heavy":
return {
"orchestrator": HEAVY_ORCHESTRATOR,
"subagent": HEAVY_SUBAGENT,
"reasoning": HEAVY_REASONING,
"budget_usd": BUDGET_HEAVY,
"multi_agent": True,
}
return {
"orchestrator": ORCHESTRATOR_MODEL,
"subagent": SUBAGENT_MODEL,
"reasoning": REASONING_MODEL,
"budget_usd": BUDGET_LIGHT,
"multi_agent": False,
}
def build_agent(mode: str = "light") -> Agent:
mode = _normalize_mode(mode)
models = get_models_for_mode(mode)
instruction = (
f"Du er OPAX — OSVauco AI-agent (kallenavn: Jason). Modus: {mode}. "
f"Du kjører på Vertex AI i region us-central1. "
f"Aktiv modell: {models['orchestrator']} "
f"(heavy = gemini-2.5-pro, light = gemini-2.5-flash). "
f"Oppgi ALDRI andre modellnavn enn disse. "
f"Budsjettgrense per oppgave: ${models['budget_usd']}. "
"Bruk retrieve_knowledge for å hente dokumentasjon. "
"Sanntids GCP-kostnader hentes fra /billing/summary, /billing/forecast "
"og /billing/anomalies. Hvis disse mangler data, er det fordi BigQuery "
"billing_export (OQ-15) ikke er aktivert ennå — si dette ærlig, ikke gjett tall. "
"HITL-grenser: du kan ikke kjøre terraform apply / onboarde kunder, "
"selge Vauco OS eller OPAX, eller passere godkjenningsporter uten Chris. "
"Svar på norsk (bokmål) med mindre annet er bedt om."
)
return Agent(
model=models["orchestrator"],
name="opax_agent",
description=f"OPAX — OSVauco enterprise agent [{mode}]",
instruction=instruction,
tools=[rag_tool] if rag_tool else [],
)
root_agent = build_agent(mode="light")
async def _run_async(message: str, user_id: str, session_id: str, mode: str) -> str:
mode = _normalize_mode(mode)
agent = build_agent(mode=mode)
session_service = InMemorySessionService()
session = await session_service.create_session(
app_name=APP_NAME, user_id=user_id, session_id=session_id,
)
runner = Runner(agent=agent, app_name=APP_NAME, session_service=session_service)
new_message = types.Content(role="user", parts=[types.Part(text=message)])
final_text = ""
async for event in runner.run_async(
user_id=user_id, session_id=session.id, new_message=new_message,
):
if event.is_final_response() and event.content and event.content.parts:
final_text = event.content.parts[0].text or ""
return final_text
def run(
message: str,
user_id: str = "opax",
session_id: str = "default",
mode: str = "light",
) -> str:
mode = _normalize_mode(mode)
authorize_mode(user_id, mode)
return asyncio.run(_run_async(
message=message, user_id=user_id, session_id=session_id, mode=mode,
))
if __name__ == "__main__":
import sys
logging.basicConfig(level=logging.WARNING)
query = sys.argv[1] if len(sys.argv) > 1 else "Hva er OPAX?"
mode = sys.argv[2] if len(sys.argv) > 2 else "light"
print(f"Mode: {mode} | Query: {query}")
print("-" * 60)
print(run(message=query, user_id="opax", mode=mode))