import os
from typing import Dict, Any

CANADA_RESIDENCY_REQUIRED = True
CLOUD_REGION = os.getenv("CLOUD_REGION", "ca-central-1")

COHERE_API_KEY = os.getenv("COHERE_API_KEY", "")
OPENAI_API_KEY = os.getenv("OPENAI_API_KEY", "")
ANTHROPIC_API_KEY = os.getenv("ANTHROPIC_API_KEY", "")

COHERE_MODEL_PRIMARY = os.getenv("COHERE_MODEL_PRIMARY", "command-r")
COHERE_EMBED_MODEL = os.getenv("COHERE_EMBED_MODEL", "embed-english-v3.0")

OPENAI_MODEL_FALLBACK = os.getenv("OPENAI_MODEL_FALLBACK", "gpt-4o-mini")
ANTHROPIC_MODEL_FALLBACK = os.getenv("ANTHROPIC_MODEL_FALLBACK", "claude-3-5-sonnet-latest")

LOCAL_MODEL_ID = os.getenv("LOCAL_MODEL_ID", "meta-llama/Meta-Llama-3.1-8B-Instruct")
LOCAL_ENABLE = os.getenv("LOCAL_ENABLE", "0") not in ("0", "false", "False")

USE_SCENARIO_ENGINE = True

MODEL_SETTINGS: Dict[str, Any] = {
    "temperature": float(os.getenv("TEMP", "0.2")),
    "top_p": float(os.getenv("TOP_P", "0.9")),
    "repetition_penalty": float(os.getenv("REP_PEN", "1.1")),
    "max_new_tokens": int(os.getenv("MAX_NEW_TOKENS", "1500")),
}

HEALTHCARE_SETTINGS = {
    "supported_file_types": [".csv", ".txt", ".md", ".pdf"],
    "healthcare_keywords": [
        "hospital", "clinic", "surgery", "wait time", "consult",
        "beds", "icu", "zone", "health authority", "triage",
    ],
}

GENERAL_CONVERSATION_PROMPT = "You are a helpful assistant. Be concise, accurate, and friendly."

HEALTHCARE_SYSTEM_PROMPT = (
    "You are a Canadian healthcare operations analysis copilot. "
    "Read the entire scenario. Output only a structured JSON plan of tasks. "
    "Each task must define dataset, filters, grouping, aggregations, joins, pivots, "
    "and formatting exactly as the scenario requires. "
    "Do not invent numbers; computations will be executed deterministically."
)

DATA_DIR = os.getenv("DATA_DIR", "./data")
RAG_INDEX_DIR = os.getenv("RAG_INDEX_DIR", "./rag_index")
SNAPSHOT_PATH = os.getenv("SNAPSHOT_PATH", "./snapshots")