#!/usr/bin/env python3
"""
agent.py — OSVauco root agent using ADK 2.0.
Requires: google-adk >= 1.29, google-cloud-aiplatform >= 1.111.0
"""

import os
from google.adk.agents import Agent
from google.adk.integrations.secret_manager.secret_client import SecretManagerClient
from vertexai.preview import rag

PROJECT_ID = "propane-will-491900-m5"
LOCATION = "us-central1"

# --- Secret Manager integration (ADK >= 1.29) ---
_sm = SecretManagerClient()
def _get_secret(name: str) -> str:
    return _sm.get_secret(
        f"projects/{PROJECT_ID}/secrets/{name}/versions/latest"
    )

# --- RAG retrieval tool ---
RAG_CORPUS = os.environ.get("RAG_CORPUS", "")  # set via Secret Manager or env

rag_tool = None
if RAG_CORPUS:
    from google.adk.tools import VertexAiRagRetrieval
    rag_tool = VertexAiRagRetrieval(
        name="retrieve_knowledge",
        description="Retrieve relevant documentation from the knowledge base.",
        rag_resources=[rag.RagResource(rag_corpus=RAG_CORPUS)],
        similarity_top_k=10,
        vector_distance_threshold=0.6,
    )

# --- Root agent ---
root_agent = Agent(
    model="gemini-2.5-flash",   # cost-optimized default
    name="oavauco_root",
    description="OSVauco enterprise agent for propane-will-491900-m5",
    instruction=(
        "You are OSVauco, a GCP knowledge and workflow agent. "
        "Use the retrieve_knowledge tool to answer questions from the knowledge base. "
        "Always prefer grounded, documented answers over speculation."
    ),
    tools=[rag_tool] if rag_tool else [],
)