nova-api/api/responder.py
2023-09-14 18:18:19 +02:00

155 lines
5.6 KiB
Python

"""This module contains the streaming logic for the API."""
import os
import json
import yaml
import dhooks
import asyncio
import aiohttp
import starlette
from rich import print
from dotenv import load_dotenv
import proxies
import provider_auth
import after_request
import load_balancing
from helpers import network, chat, errors
load_dotenv()
async def respond(
path: str='/v1/chat/completions',
user: dict=None,
payload: dict=None,
credits_cost: int=0,
input_tokens: int=0,
incoming_request: starlette.requests.Request=None,
):
"""Stream the completions request. Sends data in chunks
If not streaming, it sends the result in its entirety.
"""
is_chat = False
model = None
is_stream = False
if 'chat/completions' in path:
is_chat = True
model = payload['model']
json_response = {}
headers = {
'Content-Type': 'application/json',
'User-Agent': 'axios/0.21.1',
}
for _ in range(10):
# Load balancing: randomly selecting a suitable provider
# If the request is a chat completion, then we need to load balance between chat providers
# If the request is an organic request, then we need to load balance between organic providers
try:
if is_chat:
target_request = await load_balancing.balance_chat_request(payload)
else:
# In this case we are doing a organic request. "organic" means that it's not using a reverse engineered front-end, but rather ClosedAI's API directly
# churchless.tech is an example of an organic provider, because it redirects the request to ClosedAI.
target_request = await load_balancing.balance_organic_request({
'method': incoming_request.method,
'path': path,
'payload': payload,
'headers': headers,
'cookies': incoming_request.cookies
})
except ValueError as exc:
if model in ['gpt-3.5-turbo', 'gpt-4', 'gpt-4-32k']:
webhook = dhooks.Webhook(os.environ['DISCORD_WEBHOOK__API_ISSUE'])
webhook.send(content=f'API Issue: **`{exc}`**\nhttps://i.imgflip.com/7uv122.jpg')
yield await errors.yield_error(500, 'Sorry, the API has no working keys anymore.', 'The admins have been messaged automatically.')
return
target_request['headers'].update(target_request.get('headers', {}))
if target_request['method'] == 'GET' and not payload:
target_request['payload'] = None
# We haven't done any requests as of right now, everything until now was just preparation
# Here, we process the request
async with aiohttp.ClientSession(connector=proxies.get_proxy().connector) as session:
try:
async with session.request(
method=target_request.get('method', 'POST'),
url=target_request['url'],
data=target_request.get('data'),
json=target_request.get('payload'),
headers=target_request.get('headers', {}),
cookies=target_request.get('cookies'),
ssl=False,
timeout=aiohttp.ClientTimeout(
connect=0.3,
total=float(os.getenv('TRANSFER_TIMEOUT', '500'))
),
) as response:
is_stream = response.content_type == 'text/event-stream'
if response.status == 429:
continue
if response.content_type == 'application/json':
data = await response.json()
if 'method_not_supported' in str(data):
await errors.error(500, 'Sorry, this endpoint does not support this method.', data['error']['message'])
if 'invalid_api_key' in str(data) or 'account_deactivated' in str(data):
print('[!] invalid api key', target_request.get('provider_auth'))
await provider_auth.invalidate_key(target_request.get('provider_auth'))
continue
if response.ok:
json_response = data
if is_stream:
try:
response.raise_for_status()
except Exception as exc:
if 'Too Many Requests' in str(exc):
continue
async for chunk in response.content.iter_any():
chunk = chunk.decode('utf8').strip()
yield chunk + '\n\n'
break
except Exception as exc:
continue
if (not json_response) and is_chat:
print('[!] chat response is empty')
continue
else:
yield await errors.yield_error(500, 'Sorry, the provider is not responding. We\'re possibly getting rate-limited.', 'Please try again later.')
return
if (not is_stream) and json_response:
yield json.dumps(json_response)
print(f'[+] {path} -> {model or ""}')
await after_request.after_request(
incoming_request=incoming_request,
target_request=target_request,
user=user,
credits_cost=credits_cost,
input_tokens=input_tokens,
path=path,
is_chat=is_chat,
model=model,
)