import os
import time
from urllib.parse import urlsplit

import requests

from ._vectors import validate_vectors


def api_settings():
    endpoint = os.getenv('EMBEDDING_BASE_URL', '').rstrip('/')
    model = os.getenv('EMBEDDING_MODEL', '')
    if not endpoint or not model:
        raise ValueError('Set EMBEDDING_BASE_URL and EMBEDDING_MODEL before calling the API.')
    if not endpoint.endswith('/embeddings'):
        endpoint += '/embeddings'
    parsed = urlsplit(endpoint)
    if parsed.scheme not in {'http', 'https'} or not parsed.hostname or parsed.username or parsed.password:
        raise ValueError('Use an HTTP(S) endpoint without credentials in the URL.')
    dimension = int(os.getenv('EMBEDDING_DIMENSIONS', '0'))
    max_chars = int(os.getenv('EMBEDDING_MAX_CHARS', '8000'))
    if dimension < 0 or max_chars < 1:
        raise ValueError('Dimensions must be nonnegative and max chars positive.')
    return {'endpoint': endpoint, 'model': model, 'dimensions': dimension, 'max_chars': max_chars,
            'prefix': os.getenv('EMBEDDING_DOCUMENT_PREFIX', ''), 'normalize': True}


def response_vectors(payload, count, dimension):
    items = payload.get('data')
    if not isinstance(items, list) or len(items) != count:
        raise ValueError('Embedding response count does not match the request.')
    indexes = [item.get('index') for item in items]
    if any(type(index) is not int for index in indexes) or sorted(indexes) != list(range(count)):
        raise ValueError('Embedding response indexes are missing, duplicated or out of range.')
    ordered = sorted(items, key=lambda item: item['index'])
    return validate_vectors([item['embedding'] for item in ordered], dimension, normalize=True)


def embed(settings, texts):
    payload = {'model': settings['model'], 'input': [settings['prefix'] + text[:settings['max_chars']] for text in texts], 'encoding_format': 'float'}
    if settings['dimensions']:
        payload['dimensions'] = settings['dimensions']
    headers = {'Content-Type': 'application/json'}
    if os.getenv('EMBEDDING_API_KEY'):
        headers['Authorization'] = 'Bearer ' + os.environ['EMBEDDING_API_KEY']
    for attempt in range(5):
        try:
            response = requests.post(settings['endpoint'], json=payload, headers=headers, timeout=(15, 120))
        except (requests.ConnectionError, requests.Timeout):
            if attempt == 4:
                raise RuntimeError('Embedding endpoint connection failed after five attempts.') from None
        else:
            if response.status_code == 200:
                return response_vectors(response.json(), len(texts), settings['dimensions'])
            if response.status_code not in {408, 429, 500, 502, 503, 504} or attempt == 4:
                raise RuntimeError(f'Embedding endpoint returned HTTP {response.status_code}; check model, credentials and limits.')
        time.sleep(min(2 ** attempt, 16))
    raise RuntimeError('Embedding retries exhausted.')