from __future__ import annotations
import re
import json
import requests
from aiohttp import ClientSession
from typing import List
from ...typing import AsyncResult, Messages
from ..base_provider import AsyncGeneratorProvider, ProviderModelMixin
from ..helper import format_prompt
# Helper function to clean the response
def clean_response(text: str) -> str:
"""Clean response from unwanted patterns."""
patterns = [
r"One message exceeds the \d+chars per message limit\..+https:\/\/discord\.com\/invite\/\S+",
r"Rate limit \(\d+\/minute\) exceeded\. Join our discord for more: .+https:\/\/discord\.com\/invite\/\S+",
r"Rate limit \(\d+\/hour\) exceeded\. Join our discord for more: https:\/\/discord\.com\/invite\/\S+",
r"</s>", # zephyr-7b-beta
r"\[ERROR\] '\w{8}-\w{4}-\w{4}-\w{4}-\w{12}'", # Matches [ERROR] 'UUID'
]
for pattern in patterns:
text = re.sub(pattern, '', text)
# Remove the <|im_end|> token if present
text = text.replace("<|im_end|>", "").strip()
return text
def split_message(message: str, max_length: int = 1000) -> List[str]:
"""Splits the message into chunks of a given length (max_length)"""
# Split the message into smaller chunks to avoid exceeding the limit
chunks = []
while len(message) > max_length:
# Find the last space or punctuation before max_length to avoid cutting words
split_point = message.rfind(' ', 0, max_length)
if split_point == -1: # No space found, split at max_length
split_point = max_length
chunks.append(message[:split_point])
message = message[split_point:].strip()
if message:
chunks.append(message) # Append the remaining part of the message
return chunks
class AirforceChat(AsyncGeneratorProvider, ProviderModelMixin):
label = "AirForce Chat"
api_endpoint = "https://api.airforce/chat/completions"
supports_stream = True
supports_system_message = True
supports_message_history = True
default_model = 'llama-3.1-70b-chat'
response = requests.get('https://api.airforce/models')
data = response.json()
text_models = [model['id'] for model in data['data']]
models = [*text_models]
model_aliases = {
# openchat
"openchat-3.5": "openchat-3.5-0106",
# deepseek-ai
"deepseek-coder": "deepseek-coder-6.7b-instruct",
# NousResearch
"hermes-2-dpo": "Nous-Hermes-2-Mixtral-8x7B-DPO",
"hermes-2-pro": "hermes-2-pro-mistral-7b",
# teknium
"openhermes-2.5": "openhermes-2.5-mistral-7b",
# liquid
"lfm-40b": "lfm-40b-moe",
# DiscoResearch
"german-7b": "discolm-german-7b-v1",
# meta-llama
"llama-2-7b": "llama-2-7b-chat-int8",
"llama-2-7b": "llama-2-7b-chat-fp16",
"llama-3.1-70b": "llama-3.1-70b-chat",
"llama-3.1-8b": "llama-3.1-8b-chat",
"llama-3.1-70b": "llama-3.1-70b-turbo",
"llama-3.1-8b": "llama-3.1-8b-turbo",
# inferless
"neural-7b": "neural-chat-7b-v3-1",
# HuggingFaceH4
"zephyr-7b": "zephyr-7b-beta",
# llmplayground.net
#"any-uncensored": "any-uncensored",
}
@classmethod
async def create_async_generator(
cls,
model: str,
messages: Messages,
stream: bool = False,
proxy: str = None,
max_tokens: str = 4096,
temperature: str = 1,
top_p: str = 1,
**kwargs
) -> AsyncResult:
model = cls.get_model(model)
headers = {
'accept': '*/*',
'accept-language': 'en-US,en;q=0.9',
'authorization': 'Bearer missing api key',
'cache-control': 'no-cache',
'content-type': 'application/json',
'origin': 'https://llmplayground.net',
'pragma': 'no-cache',
'priority': 'u=1, i',
'referer': 'https://llmplayground.net/',
'sec-ch-ua': '"Not?A_Brand";v="99", "Chromium";v="130"',
'sec-ch-ua-mobile': '?0',
'sec-ch-ua-platform': '"Linux"',
'sec-fetch-dest': 'empty',
'sec-fetch-mode': 'cors',
'sec-fetch-site': 'cross-site',
'user-agent': 'Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/130.0.0.0 Safari/537.36'
}
# Format the messages for the API
formatted_messages = format_prompt(messages)
message_chunks = split_message(formatted_messages)
full_response = ""
for chunk in message_chunks:
data = {
"messages": [{"role": "user", "content": chunk}],
"model": model,
"max_tokens": max_tokens,
"temperature": temperature,
"top_p": top_p,
"stream": stream
}
async with ClientSession(headers=headers) as session:
async with session.post(cls.api_endpoint, json=data, proxy=proxy) as response:
response.raise_for_status()
text = ""
if stream:
async for line in response.content:
line = line.decode('utf-8').strip()
if line.startswith('data: '):
json_str = line[6:]
try:
if json_str and json_str != "[DONE]":
chunk = json.loads(json_str)
if 'choices' in chunk and chunk['choices']:
content = chunk['choices'][0].get('delta', {}).get('content', '')
text += content
except json.JSONDecodeError as e:
print(f"Error decoding JSON: {json_str}, Error: {e}")
elif line == "[DONE]":
break
full_response += clean_response(text)
else:
response_json = await response.json()
text = response_json["choices"][0]["message"]["content"]
full_response += clean_response(text)
# Return the complete response after all chunks
yield full_response
