"""agent/llm.py — provider-agnostic LLM factory.

The only module in the codebase that knows about specific LLM providers
(Anthropic Claude vs OpenAI). Every other agent module (graph, chat_agent,
translate) goes through `make_chat_model` / `build_system_message` and never
imports `ChatAnthropic` / `ChatOpenAI` directly.

Security note (public HF Space): a `RunConfig.api_key`, when set, is a value
the visitor pasted into the sidebar for THIS session only. It must never be
cached (st.cache_*), logged, or written to disk — see dashboard/model_picker.py
and app.py for how the config is threaded through as a per-run snapshot.
"""
from __future__ import annotations

import os
from dataclasses import dataclass
from typing import Optional

from langchain_core.messages import SystemMessage

ANTHROPIC_DEFAULT_MODEL = "claude-haiku-4-5-20251001"
OPENAI_DEFAULT_MODEL = "gpt-5-mini"

# (model_id, display_label) — data-driven so the sidebar picker and pricing
# table (agent/cost_log.py) stay in sync. Edit here to add/remove models.
MODEL_CATALOG: dict[str, list[tuple[str, str]]] = {
    "anthropic": [
        ("claude-haiku-4-5-20251001", "Claude Haiku 4.5 — fast (default)"),
        ("claude-sonnet-4-6", "Claude Sonnet 4.6 — deeper analysis"),
        ("claude-opus-4-8", "Claude Opus 4.8 — highest quality"),
    ],
    "openai": [
        ("gpt-5-mini", "GPT-5 mini — fast (default)"),
        ("gpt-5.1", "GPT-5.1 — deeper analysis"),
    ],
}

PROVIDER_LABELS: dict[str, str] = {
    "anthropic": "Anthropic Claude",
    "openai": "OpenAI",
}

_ENV_VARS: dict[str, str] = {
    "anthropic": "ANTHROPIC_API_KEY",
    "openai": "OPENAI_API_KEY",
}

_KEY_PREFIXES: dict[str, str] = {
    "anthropic": "sk-ant-",
    "openai": "sk-",
}

_CONSOLE_URLS: dict[str, str] = {
    "anthropic": "console.anthropic.com",
    "openai": "platform.openai.com",
}


@dataclass(frozen=True)
class RunConfig:
    """Frozen snapshot of provider/model/key for a single run.

    Built once (in the main Streamlit thread, at the moment of the user
    action) and passed as a plain argument into background threads and agent
    functions — never re-read from st.session_state after construction, so a
    mid-run change in the sidebar picker cannot affect an in-flight run.
    """
    provider: str = "anthropic"
    model: str = ANTHROPIC_DEFAULT_MODEL
    api_key: Optional[str] = None  # None → the provider's own env var at construction


def default_config() -> RunConfig:
    """Today's behavior: Anthropic Haiku, key from ANTHROPIC_API_KEY env var."""
    return RunConfig(provider="anthropic", model=ANTHROPIC_DEFAULT_MODEL, api_key=None)


def resolve_api_key(provider: str, user_key: Optional[str]) -> tuple[Optional[str], str]:
    """Resolve which key to use for *provider*.

    Precedence: non-empty pasted key > env var > missing.
    Returns (key_or_None, source) where source is one of "user", "env", "missing".
    """
    user_key = (user_key or "").strip()
    if user_key:
        return user_key, "user"
    env_key = os.environ.get(_ENV_VARS.get(provider, ""), "").strip()
    if env_key:
        return env_key, "env"
    return None, "missing"


def key_looks_valid(provider: str, key: str) -> bool:
    """Cheap, no-network sanity check — catches pasting a key into the wrong provider."""
    prefix = _KEY_PREFIXES.get(provider)
    if not prefix or not key:
        return True
    return key.startswith(prefix)


def console_url(provider: str) -> str:
    return _CONSOLE_URLS.get(provider, "")


def make_chat_model(
    cfg: RunConfig,
    *,
    temperature: float = 0,
    max_retries: int = 5,
    max_tokens: Optional[int] = None,
):
    """Build a ChatAnthropic or ChatOpenAI client from *cfg*.

    `api_key` is passed explicitly only when `cfg.api_key` is set — otherwise
    the LangChain class reads its own provider env var, preserving today's
    behavior exactly when no key was pasted in the UI.
    """
    key, _source = resolve_api_key(cfg.provider, cfg.api_key)
    kwargs: dict = {"model": cfg.model, "temperature": temperature, "max_retries": max_retries}
    if max_tokens is not None:
        kwargs["max_tokens"] = max_tokens
    if key:
        kwargs["api_key"] = key

    if cfg.provider == "openai":
        from langchain_openai import ChatOpenAI
        return ChatOpenAI(**kwargs)

    from langchain_anthropic import ChatAnthropic
    return ChatAnthropic(**kwargs)


def build_system_message(
    cfg: RunConfig,
    primary_text: str,
    extra_texts: Optional[list[str]] = None,
) -> SystemMessage:
    """Build a provider-appropriate SystemMessage.

    Anthropic: content is a list of blocks; the primary block carries
    `cache_control: {type: ephemeral}` so prompt caching keeps working.
    Extra blocks (e.g. a language directive) are appended uncached, exactly
    matching the byte layout the app used before this refactor.

    OpenAI: plain string content — `cache_control` is an Anthropic-only
    extension and would be ignored at best, rejected at worst.
    """
    extra_texts = extra_texts or []
    if cfg.provider == "openai":
        parts = [primary_text] + list(extra_texts)
        return SystemMessage(content="\n\n".join(parts))

    content: list[dict] = [{
        "type": "text",
        "text": primary_text,
        "cache_control": {"type": "ephemeral"},
    }]
    for text in extra_texts:
        content.append({"type": "text", "text": text})
    return SystemMessage(content=content)


_AUTH_MARKERS = ("authentication_error", "401", "invalid x-api-key", "incorrect api key", "invalid_api_key")
_OVERLOAD_MARKERS = ("overloaded_error", "529")
_RATE_LIMIT_MARKERS = ("rate_limit", "429", "quota")


def classify_llm_error(exc, provider: str) -> Optional[str]:
    """Map a raw exception/message to a friendly, provider-aware string.

    Returns None when the error isn't recognized — the caller shows the raw
    message in that case. Never interpolates the API key.
    """
    text = str(exc).lower()
    label = PROVIDER_LABELS.get(provider, provider)

    if any(marker in text for marker in _AUTH_MARKERS):
        return (
            f"Your {label} API key was rejected (authentication error). "
            f"Check it in Model settings — get a key at {console_url(provider)}."
        )
    if any(marker in text for marker in _OVERLOAD_MARKERS):
        return f"{label} is temporarily overloaded. Please try again in a moment."
    if any(marker in text for marker in _RATE_LIMIT_MARKERS):
        return f"{label} rate limit reached. Please wait a moment and try again."
    return None