"""Langfuse observability — singleton client and prompt helpers.

If LANGFUSE_SECRET_KEY / LANGFUSE_PUBLIC_KEY are not set,
all helpers are no-ops so the app works without Langfuse configured.

Usage
-----
Tracing::

    from app.core.langfuse_client import get_langfuse

    lf = get_langfuse()
    if lf:
        with lf.start_as_current_observation(as_type="span", name="my-agent") as span:
            span.update(input=user_message)
            # ... do work ...
            span.update(output=result)
        lf.flush()

Prompt management::

    from app.core.langfuse_client import get_prompt_or_fallback

    text, prompt_obj = get_prompt_or_fallback("home_system", FALLBACK_PROMPT)
    # Use text as the system prompt; pass prompt_obj to generations for linking.

Linking a prompt to a generation::

    with lf.start_as_current_observation(
        as_type="generation",
        name="llm-call",
        model="gpt-4o",
        prompt=prompt_obj,   # links generation → prompt version in the UI
        input=messages,
    ) as gen:
        response = await llm.ainvoke(messages)
        gen.update(output=response.content, usage=_usage(response))
"""

from __future__ import annotations

import logging
from typing import Any

logger = logging.getLogger(__name__)

_client: Any = None
_initialized: bool = False


def get_langfuse() -> Any | None:
    """Return the Langfuse singleton, or ``None`` when not configured."""
    global _client, _initialized
    if _initialized:
        return _client
    _initialized = True

    from app.config.settings import settings  # local import to avoid circular deps

    if not settings.LANGFUSE_SECRET_KEY or not settings.LANGFUSE_PUBLIC_KEY:
        logger.debug("langfuse: not configured — observability disabled")
        return None

    try:
        from langfuse import Langfuse

        _client = Langfuse(
            secret_key=settings.LANGFUSE_SECRET_KEY,
            public_key=settings.LANGFUSE_PUBLIC_KEY,
            host=settings.LANGFUSE_HOST,
        )
        logger.info("langfuse: client initialized host=%s", settings.LANGFUSE_HOST)
    except Exception as exc:
        logger.warning("langfuse: failed to initialize: %s", exc)
        _client = None

    return _client


def get_prompt_or_fallback(name: str, fallback: str) -> tuple[str, Any]:
    """Fetch a text prompt from Langfuse; fall back to ``fallback`` on any error.

    Returns ``(prompt_text, prompt_obj_or_None)``.

    * ``prompt_text`` — the raw template string (variables not yet substituted).
      Callers perform variable substitution with Python's ``.format()``.
    * ``prompt_obj`` — the Langfuse prompt object, or ``None`` when Langfuse is
      unavailable / the fetch failed.  Pass this to generation observations so
      Langfuse links the generation to the exact prompt version in the UI.
    """
    lf = get_langfuse()
    if lf is None:
        return fallback, None

    try:
        prompt = lf.get_prompt(name, label="production", fallback=fallback)
        # For text-type prompts .prompt holds the raw template string.
        raw = prompt.prompt if hasattr(prompt, "prompt") and isinstance(prompt.prompt, str) else fallback
        return raw, prompt
    except Exception as exc:
        logger.warning("langfuse: get_prompt %r failed: %s — using fallback", name, exc)
        return fallback, None


def extract_usage(response: Any) -> dict[str, int]:
    """Extract token usage from a LangChain AI message into Langfuse format."""
    meta = getattr(response, "usage_metadata", None)
    if not meta:
        return {}
    return {
        "input": int(meta.get("input_tokens", 0)),
        "output": int(meta.get("output_tokens", 0)),
        "total": int(meta.get("total_tokens", 0)),
    }