import requests
import json
import logging
from typing import Dict, Optional, List

logger = logging.getLogger(__name__)

class LLMClient:
    def __init__(self, endpoint: str = 'http://localhost:11434', model: str = 'llama3', use_local: bool = True):
        self.endpoint = endpoint
        self.model = model
        self.use_local = use_local
        self.lm_studio_endpoint = 'http://192.168.1.74:1234'
        self.lm_studio_model = 'openai/gpt-oss-20b'

    def summarize(self, text: str, max_length: int = 200) -> Dict:
        prompt = f"Summarize this concisely in under {max_length} characters:\n\n{text[:3000]}"
        return self._query(prompt)

    def extract_topics(self, text: str) -> Dict:
        prompt = f"Extract 5-10 key topics/tags. Return ONLY comma-separated words:\n\n{text[:3000]}"
        result = self._query(prompt)
        if result.get('success'):
            topics = [t.strip() for t in result['text'].split(',')]
            result['topics'] = topics[:10]
        return result

    def extract_intent(self, text: str) -> Dict:
        prompt = f"What is the main purpose/intent of this code/document? Answer in 1-2 sentences:\n\n{text[:3000]}"
        return self._query(prompt)

    def detect_project_type(self, text: str, file_list: List[str]) -> Dict:
        files_str = ', '.join(file_list[:20])
        prompt = f"Based on these files: {files_str}\nAnd this content:\n{text[:2000]}\n\nWhat type of project is this? (e.g. web app, ml/ai, transcription, data processing, etc.)"
        return self._query(prompt)

    def _query(self, prompt: str, timeout: int = 30) -> Dict:
        try:
            if self.use_local:
                response = requests.post(
                    f'{self.endpoint}/api/generate',
                    json={'model': self.model, 'prompt': prompt, 'stream': False},
                    timeout=timeout
                )
                if response.status_code == 200:
                    data = response.json()
                    return {'success': True, 'text': data.get('response', '').strip()}
            else:
                response = requests.post(
                    f'{self.lm_studio_endpoint}/v1/chat/completions',
                    json={
                        'model': self.lm_studio_model,
                        'messages': [{'role': 'user', 'content': prompt}],
                        'max_tokens': 500,
                        'temperature': 0.7
                    },
                    timeout=timeout
                )
                if response.status_code == 200:
                    data = response.json()
                    return {'success': True, 'text': data['choices'][0]['message']['content'].strip()}

            return {'success': False, 'error': f'HTTP {response.status_code}'}

        except requests.Timeout:
            logger.warning(f'LLM request timeout after {timeout}s')
            return {'success': False, 'error': 'timeout'}
        except Exception as e:
            logger.error(f'LLM query failed: {e}')
            return {'success': False, 'error': str(e)}