# bot/recommender.py

import openai
import os
from dotenv import load_dotenv
from typing import List, Dict, Literal
from library_cache import LibraryCache
from config import OPENAI_API_KEY, OPENAI_MODEL

load_dotenv()

openai.api_key = OPENAI_API_KEY

MediaType = Literal["movie", "show"]

class Recommender:
    def __init__(self):
        self.cache = LibraryCache()

    def recommend(self, watched_titles: List[str], media_type: MediaType = "movie", max_recs: int = 5) -> Dict[str, List[str]]:
        if not watched_titles:
            raise ValueError("No watched titles provided.")

        prompt = self.build_prompt(watched_titles, media_type, max_recs)
        response = self.query_openai(prompt)

        print("🧠 Prompt:", prompt)
        print("📥 Raw response:", response)

        all_titles = self.parse_titles(response)
        print("📦 Parsed titles:", all_titles)

        available = [title for title in all_titles if self.cache.search(title, media_type)]
        requestable = [title for title in all_titles if title not in available]

        return {
            "available": available,
            "requestable": requestable
        }

    def build_prompt(self, watched: List[str], media_type: str, max_recs: int) -> str:
        type_text = "movies" if media_type == "movie" else "TV shows"
        
        # You could optionally summarize genres here
        genre_summary = self.extract_common_genres(watched, media_type)

        return (
            f"A user has watched the following {type_text}: {', '.join(watched[:20])}. "
            f"These shows are mostly {genre_summary}. "
            f"Recommend {max_recs} similar {type_text} based on theme and tone. "
            f"Return only a plain comma-separated list of titles — no numbers, no explanations."
        )

    def extract_common_genres(self, watched: List[str], media_type: str) -> str:
        genre_counts = {}
        for item in self.cache.data:
            if item["title"] in watched and item["type"] == media_type:
                for genre in item.get("genres", []):
                    genre_counts[genre] = genre_counts.get(genre, 0) + 1
        sorted_genres = sorted(genre_counts.items(), key=lambda x: x[1], reverse=True)
        top_genres = [g for g, _ in sorted_genres[:3]]
        return ", ".join(top_genres) if top_genres else "varied genres"


    def query_openai(self, prompt: str) -> str:
        try:
            response = openai.ChatCompletion.create(
                model=OPENAI_MODEL,
                messages=[
                    {"role": "system", "content": "You're a helpful and precise media recommender."},
                    {"role": "user", "content": prompt}
                ],
                temperature=0.4,
                max_tokens=150
            )
            return response.choices[0].message.content
        except Exception as e:
            print("⚠️ OpenAI API error:", e)
            return ""

    def parse_titles(self, response: str) -> List[str]:
        lines = response.replace("\n", ",").split(",")
        cleaned = []
        for item in lines:
            item = item.strip()
            item = item.lstrip("-•*0123456789. ").strip()
            if item:
                cleaned.append(item)
        return cleaned