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Update (g4f/Provider/airforce/AirforceChat.py)
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@kqlio67
kqlio67 committed Nov 10, 2024
1 parent 5d75ab6 commit 9a03461
Showing 1 changed file with 93 additions and 93 deletions.
186 changes: 93 additions & 93 deletions g4f/Provider/airforce/AirforceChat.py
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Original file line number Diff line number Diff line change
@@ -1,50 +1,43 @@
from __future__ import annotations
import re
from aiohttp import ClientSession
import json
from typing import List
from aiohttp import ClientSession
import requests
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)
return text.strip()

def split_message(message: dict, chunk_size: int = 995) -> List[dict]:
"""Split a message into chunks of specified size."""
content = message.get('content', '')
if len(content) <= chunk_size:
return [message]

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 content:
chunk = content[:chunk_size]
content = content[chunk_size:]
chunks.append({
'role': message['role'],
'content': chunk
})
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

def split_messages(messages: Messages, chunk_size: int = 995) -> Messages:
"""Split all messages that exceed chunk_size into smaller messages."""
result = []
for message in messages:
result.extend(split_message(message, chunk_size))
return result

class AirforceChat(AsyncGeneratorProvider, ProviderModelMixin):
label = "AirForce Chat"
api_endpoint = "https://api.airforce/chat/completions"
Expand All @@ -57,45 +50,44 @@ class AirforceChat(AsyncGeneratorProvider, ProviderModelMixin):
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",
# 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
Expand All @@ -112,8 +104,6 @@ async def create_async_generator(
) -> AsyncResult:
model = cls.get_model(model)

chunked_messages = split_messages(messages)

headers = {
'accept': '*/*',
'accept-language': 'en-US,en;q=0.9',
Expand All @@ -133,36 +123,46 @@ async def create_async_generator(
'user-agent': 'Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/130.0.0.0 Safari/537.36'
}

data = {
"messages": chunked_messages,
"model": model,
"max_tokens": max_tokens,
"temperature": temperature,
"top_p": top_p,
"stream": stream
}
# 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()

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')
if line.startswith('data: '):
json_str = line[6:]
try:
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.strip() == "[DONE]":
break
yield clean_response(text)
else:
response_json = await response.json()
text = response_json["choices"][0]["message"]["content"]
yield clean_response(text)
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

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