"""Configuration and safety limits for the sentiment agent.

All guardrails are centralized here so they can be tuned from one place
or overridden via CLI flags / env vars.
"""

from __future__ import annotations

import os
from dataclasses import dataclass, field


@dataclass(frozen=True)
class RateLimitConfig:
    """Per-platform rate limiting."""

    requests_per_minute: int = 10
    burst_size: int = 3  # max concurrent requests
    cooldown_after_429: float = 30.0  # seconds to wait after a 429


@dataclass(frozen=True)
class SafetyConfig:
    """Top-level safety rails for the agent."""

    # --- Agent-level limits ---
    max_turns: int = 20
    max_budget_usd: float = 0.50  # hard cap on Claude API spend per run
    max_total_api_calls: int = 50  # across ALL platforms combined
    max_results_per_call: int = 50  # cap the `limit` param sent to any API

    # --- Per-platform rate limits ---
    bluesky_rate: RateLimitConfig = field(default_factory=lambda: RateLimitConfig(
        requests_per_minute=10, burst_size=2,
    ))
    reddit_rate: RateLimitConfig = field(default_factory=lambda: RateLimitConfig(
        requests_per_minute=10, burst_size=2,
    ))
    hackernews_rate: RateLimitConfig = field(default_factory=lambda: RateLimitConfig(
        requests_per_minute=15, burst_size=3,  # HN Algolia is more generous
    ))

    # --- Content size limits ---
    max_post_text_chars: int = 2000  # truncate individual posts beyond this
    max_total_content_bytes: int = 500_000  # ~500KB total data gathered before agent stops

    # --- Timeout ---
    api_timeout_seconds: float = 15.0

    # --- Credibility thresholds ---
    min_credibility_score: float = 0.3  # posts below this are flagged/excluded
    flag_bot_threshold: float = 0.5  # posts between min and this are flagged but included

    @classmethod
    def from_env(cls) -> SafetyConfig:
        """Build config with env var overrides.

        Env vars: SENTIMENT_MAX_TURNS, SENTIMENT_MAX_BUDGET_USD,
        SENTIMENT_MAX_API_CALLS, SENTIMENT_MIN_CREDIBILITY.
        """
        kwargs: dict = {}
        if v := os.environ.get("SENTIMENT_MAX_TURNS"):
            kwargs["max_turns"] = int(v)
        if v := os.environ.get("SENTIMENT_MAX_BUDGET_USD"):
            kwargs["max_budget_usd"] = float(v)
        if v := os.environ.get("SENTIMENT_MAX_API_CALLS"):
            kwargs["max_total_api_calls"] = int(v)
        if v := os.environ.get("SENTIMENT_MIN_CREDIBILITY"):
            kwargs["min_credibility_score"] = float(v)
        return cls(**kwargs)