backend/utils.py

import json
import re
from typing import Any


def safe_invoke(llm, prompt: str) -> str:
    """
    Safely invoke any LangChain LLM and always return a string.
    Handles:
    - AIMessage (ChatOpenAI, etc.)
    - raw string outputs
    - dict / list responses
    """

    if not prompt or not isinstance(prompt, str):
        raise ValueError("Prompt must be a non-empty string")

    try:
        response = llm.invoke(prompt)

        # Case 1: Chat models (AIMessage)
        if hasattr(response, "content"):
            return str(response.content)

        # Case 2: Already string
        if isinstance(response, str):
            return response

        # Case 3: dict / list → stringify safely
        return json.dumps(response, indent=2)

    except Exception as e:
        return f"[LLM_ERROR] {str(e)}"


# ---------------------------------------------------

def safe_json_parse(text: str) -> dict:
    """
    Try to parse LLM output into JSON safely.
    If fails, return fallback structure.
    """
    if not isinstance(text, str):
        return {
            "error": "Invalid JSON from model",
            "raw_output": text,
        }

    candidates = []
    stripped = text.strip()
    candidates.append(stripped)

    fence_match = re.search(r"```(?:json)?\s*(.*?)\s*```", stripped, re.DOTALL | re.IGNORECASE)
    if fence_match:
        candidates.append(fence_match.group(1).strip())

    first_object = stripped.find("{")
    last_object = stripped.rfind("}")
    if first_object != -1 and last_object != -1 and last_object > first_object:
        candidates.append(stripped[first_object:last_object + 1].strip())

    first_array = stripped.find("[")
    last_array = stripped.rfind("]")
    if first_array != -1 and last_array != -1 and last_array > first_array:
        candidates.append(stripped[first_array:last_array + 1].strip())

    seen = set()
    for candidate in candidates:
        if not candidate or candidate in seen:
            continue
        seen.add(candidate)
        try:
            return json.loads(candidate)
        except Exception:
            continue

    return {
        "error": "Invalid JSON from model",
        "raw_output": text
    }


# ---------------------------------------------------

def safe_merge(*args: Any) -> str:
    """
    Safely merge multiple inputs into one string.
    Handles:
    - None
    - dict
    - list
    - string
    """

    merged_parts = []

    for arg in args:
        if arg is None:
            continue

        if isinstance(arg, (dict, list)):
            merged_parts.append(json.dumps(arg, indent=2))
        else:
            merged_parts.append(str(arg))

    return "\n".join(merged_parts)


# ---------------------------------------------------

def safe_input(text: Any, fallback: str) -> str:
    """
    Normalize optional user inputs (chat / feelings).
    """

    if text is None:
        return fallback

    if isinstance(text, str) and text.strip() == "":
        return fallback

    return str(text)