import json
import logging

from openai import AsyncOpenAI

from app.config import settings
from app.models import Movie
from app.services.llm.base import SYSTEM_PROMPT, LLMProvider, build_user_message

logger = logging.getLogger("movie-night.llm.ollama")


class OllamaProvider(LLMProvider):
    def __init__(self):
        base_url = settings.llm_base_url or "http://localhost:11434/v1"
        self.client = AsyncOpenAI(api_key="ollama", base_url=base_url)
        self.model = settings.llm_model or "llama3"

    async def get_recommendations(self, mood: str, candidates: list[Movie], max_results: int = 6) -> list[dict]:
        system = SYSTEM_PROMPT.format(max_results=max_results)
        user_msg = build_user_message(mood, candidates)

        logger.info(f"Calling Ollama ({self.model}) with {len(candidates)} candidates")

        response = await self.client.chat.completions.create(
            model=self.model,
            max_tokens=2048,
            messages=[
                {"role": "system", "content": system},
                {"role": "user", "content": user_msg},
            ],
        )

        text = response.choices[0].message.content.strip()

        try:
            data = json.loads(text)
            return data.get("recommendations", [])
        except json.JSONDecodeError:
            # Try to extract JSON from response
            start = text.find("{")
            end = text.rfind("}") + 1
            if start >= 0 and end > start:
                try:
                    data = json.loads(text[start:end])
                    return data.get("recommendations", [])
                except json.JSONDecodeError:
                    pass
            logger.error(f"Failed to parse Ollama response: {text[:200]}")
            return []