# ai.py
import os
import requests
import re
from dotenv import load_dotenv
from personality import load_persona
from logger import setup_logger

logger = setup_logger("ai")
load_dotenv()

BASE_API = os.getenv("OLLAMA_API").rstrip("/")  # ← ensures no trailing slash issue
GEN_ENDPOINT = f"{BASE_API}/generate"
PULL_ENDPOINT = f"{BASE_API}/pull"
#UNLOAD_ENDPOINT = f"{BASE_API}/unload"
TAGS_ENDPOINT = f"{BASE_API}/tags"

MODEL_NAME = os.getenv("MODEL_NAME", "llama3:latest")
SHOW_THINKING_BLOCKS = os.getenv("SHOW_THINKING_BLOCKS", "false").lower() == "true"

if not BASE_API:
    logger.error("❌ OLLAMA_API not set.")
    raise ValueError("❌ OLLAMA_API not set.")

def get_model_name():
    return MODEL_NAME

def strip_thinking_block(text: str) -> str:
    return re.sub(r"<think>.*?</think>\s*", "", text, flags=re.DOTALL)

def model_exists_locally(model_name: str) -> bool:
    try:
        resp = requests.get(TAGS_ENDPOINT)
        return model_name in resp.text
    except Exception as e:
        logger.error(f"❌ Failed to check local models: {e}")
        return False

def load_model(model_name: str) -> bool:
    try:
        logger.info(f"🧠 Preloading model: {model_name}")
        resp = requests.post(PULL_ENDPOINT, json={"name": model_name})
        logger.info(f"📨 Ollama pull response: {resp.status_code} - {resp.text}")
        return resp.status_code == 200
    except Exception as e:
        logger.error(f"❌ Exception during model load: {str(e)}")
        return False

def unload_model(model_name: str) -> bool:
    try:
        logger.info(f"🧹 Soft-unloading model from VRAM: {model_name}")
        resp = requests.post(GEN_ENDPOINT, json={
            "model": model_name,
            "keep_alive": 0,
            "prompt": ""
        })
        logger.info(f"🧽 Ollama unload response: {resp.status_code} - {resp.text}")
        return resp.status_code == 200
    except Exception as e:
        logger.error(f"❌ Exception during soft-unload: {str(e)}")
        return False

def get_current_model():
    return get_model_name()

def get_ai_response(user_prompt):
    model_name = get_model_name()
    load_model(model_name)

    persona = load_persona()
    if persona:
        safe_inject = persona["prompt_inject"].replace("“", "\"").replace("”", "\"").replace("’", "'")
        full_prompt = f"{safe_inject}\nUser: {user_prompt}\n{persona['name']}:"
    else:
        full_prompt = user_prompt

    payload = {
        "model": model_name,
        "prompt": full_prompt,
        "stream": False
    }

    logger.info("🛰️ SENDING TO OLLAMA /generate")
    logger.info(f"Payload: {payload}")

    try:
        response = requests.post(GEN_ENDPOINT, json=payload)
        logger.info(f"📨 Raw response: {response.text}")

        if response.status_code == 200:
            result = response.json()
            response_text = result.get("response", "[No message in response]")
            return strip_thinking_block(response_text) if not SHOW_THINKING_BLOCKS else response_text
        else:
            return f"[Error {response.status_code}] {response.text}"
    except Exception as e:
        return f"[Exception] {str(e)}"