#!/usr/bin/env python3
"""
agent.py — OSVauco root agent using ADK 1.x.
Requires: google-adk >= 1.0.0,<2.0.0
         google-cloud-aiplatform >= 1.112.0
"""

import os
import logging

from google.adk.agents import Agent

logger = logging.getLogger(__name__)

PROJECT_ID = os.environ.get("GOOGLE_CLOUD_PROJECT", "propane-will-491900-m5")
LOCATION   = os.environ.get("GOOGLE_CLOUD_LOCATION", "us-central1")

# RAG corpus resource name — injected via Secret Manager as env-var RAG_CORPUS
RAG_CORPUS = os.environ.get("RAG_CORPUS", "")

rag_tool = None
if RAG_CORPUS:
    try:
        # ADK 1.x: VertexAiRagRetrieval lives in google.adk.tools.retrieval
        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 with corpus: {RAG_CORPUS}")
    except ImportError as e:
        logger.warning(f"VertexAiRagRetrieval not available — running without RAG: {e}")
        rag_tool = None
else:
    logger.warning("RAG_CORPUS env var not set — running without RAG retrieval")

# Root agent
root_agent = Agent(
    model="gemini-2.5-flash",
    name="osvauco_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. "
        "Always respond in Norwegian (Bokmål) regardless of the language used in the query."
    ),
    tools=[rag_tool] if rag_tool else [],
)