File size: 2,983 Bytes
daa5e64 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 | 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.')
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