"""Configuration for the LLM Council."""

import os
from dotenv import load_dotenv

load_dotenv()

# Helpers
def _parse_int_env(name: str, default: int) -> int:
    raw = os.getenv(name)
    if raw is None or raw.strip() == "":
        return default
    try:
        return int(raw.strip())
    except ValueError:
        return default


def _parse_float_env(name: str, default: float) -> float:
    raw = os.getenv(name)
    if raw is None or raw.strip() == "":
        return default
    try:
        return float(raw.strip())
    except ValueError:
        return default


def _parse_list_env(name: str) -> list[str] | None:
    """
    Parses a list from an env var.

    Supported formats:
    - Comma-separated: "a,b,c"
    - Newline-separated: "a\\nb\\nc"
    """
    raw = os.getenv(name)
    if raw is None:
        return None
    raw = raw.strip()
    if raw == "":
        return []

    # Allow either commas or newlines.
    parts = []
    for chunk in raw.replace("\r\n", "\n").split("\n"):
        parts.extend(chunk.split(","))
    return [p.strip() for p in parts if p.strip()]


# Council members - list of model identifiers (Ollama model names)
# Can be overridden via env var COUNCIL_MODELS (comma or newline separated).
_DEFAULT_COUNCIL_MODELS = [
    "llama3.2:3b",
    "qwen2.5:3b",
    "gemma2:2b",
]
COUNCIL_MODELS = _parse_list_env("COUNCIL_MODELS") or _DEFAULT_COUNCIL_MODELS

# Chairman model - synthesizes final response
CHAIRMAN_MODEL = os.getenv("CHAIRMAN_MODEL") or "llama3.2:3b"

# Maximum tokens per request
# Default: 2048 tokens (reasonable for most responses)
# Increase if you need longer responses
MAX_TOKENS = _parse_int_env("MAX_TOKENS", 2048)

# Request timeout configuration (in seconds)
# Default timeout for general LLM queries (Stage 1: council responses)
# Used by llm_client.py and passed to openai_compat.query_model()
LLM_TIMEOUT_SECONDS = _parse_float_env("LLM_TIMEOUT_SECONDS", 120.0)
# Timeout for chairman synthesis (may need longer for complex responses)
CHAIRMAN_TIMEOUT_SECONDS = _parse_float_env("CHAIRMAN_TIMEOUT_SECONDS", 180.0)
# Timeout for title generation (short responses)
TITLE_GENERATION_TIMEOUT_SECONDS = _parse_float_env("TITLE_GENERATION_TIMEOUT_SECONDS", 120.0)

# OpenAI-compatible provider tuning (Ollama / vLLM / TGI)
# If USE_LOCAL_OLLAMA=true, automatically set base URL to localhost:11434 (convenience flag)
if os.getenv("USE_LOCAL_OLLAMA", "").strip().lower() in ("true", "1", "yes"):
    _openai_compat_base_url = "http://localhost:11434"
else:
    _openai_compat_base_url = os.getenv("OPENAI_COMPAT_BASE_URL")
OPENAI_COMPAT_BASE_URL = _openai_compat_base_url

# HTTP client timeout (fallback when timeout not explicitly passed to openai_compat functions)
# Used by: list_models() and as fallback in query_model() if called directly without timeout
# Should be >= LLM_TIMEOUT_SECONDS for safety, but list_models() is fast so can be lower
OPENAI_COMPAT_TIMEOUT_SECONDS = _parse_float_env("OPENAI_COMPAT_TIMEOUT_SECONDS", 300.0)
# HTTP client connection timeout (time to establish connection)
OPENAI_COMPAT_CONNECT_TIMEOUT_SECONDS = _parse_float_env("OPENAI_COMPAT_CONNECT_TIMEOUT_SECONDS", 10.0)
# HTTP client write timeout (time to send request)
OPENAI_COMPAT_WRITE_TIMEOUT_SECONDS = _parse_float_env("OPENAI_COMPAT_WRITE_TIMEOUT_SECONDS", 10.0)
# HTTP client pool timeout (time to get connection from pool)
OPENAI_COMPAT_POOL_TIMEOUT_SECONDS = _parse_float_env("OPENAI_COMPAT_POOL_TIMEOUT_SECONDS", 10.0)
# Number of retries for failed requests (retryable HTTP errors: 408, 409, 425, 429, 500, 502, 503, 504)
OPENAI_COMPAT_RETRIES = _parse_int_env("OPENAI_COMPAT_RETRIES", 2)
# Exponential backoff base delay between retries (seconds) - actual delay is backoff * (2^attempt)
OPENAI_COMPAT_RETRY_BACKOFF_SECONDS = _parse_float_env("OPENAI_COMPAT_RETRY_BACKOFF_SECONDS", 0.5)

# Debug mode - show debug logs in console (set DEBUG=true in .env)
DEBUG = os.getenv("DEBUG", "").strip().lower() in ("true", "1", "yes")

# Markdown uploads (per-conversation)
DOCS_DIR = os.getenv("DOCS_DIR") or "data/docs"
MAX_DOC_BYTES = _parse_int_env("MAX_DOC_BYTES", 1_000_000)  # 1MB
MAX_DOC_PREVIEW_CHARS = _parse_int_env("MAX_DOC_PREVIEW_CHARS", 20_000)

# Data directory for conversation storage
DATA_DIR = "data/conversations"