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feat(g4f/Provider/AmigoChat.py): add new AmigoChat text and image models
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kqlio67
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178
g4f/Provider/AmigoChat.py
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178
g4f/Provider/AmigoChat.py
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from __future__ import annotations
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import json
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import uuid
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from aiohttp import ClientSession, ClientTimeout
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from ..typing import AsyncResult, Messages
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from .base_provider import AsyncGeneratorProvider, ProviderModelMixin
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from .helper import format_prompt
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from ..image import ImageResponse
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class AmigoChat(AsyncGeneratorProvider, ProviderModelMixin):
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url = "https://amigochat.io/chat/"
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chat_api_endpoint = "https://api.amigochat.io/v1/chat/completions"
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image_api_endpoint = "https://api.amigochat.io/v1/images/generations"
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working = True
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supports_gpt_4 = True
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supports_stream = True
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supports_system_message = True
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supports_message_history = True
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default_model = 'gpt-4o-mini'
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chat_models = [
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'gpt-4o',
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default_model,
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'o1-preview',
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'o1-mini',
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'meta-llama/Meta-Llama-3.1-405B-Instruct-Turbo',
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'meta-llama/Llama-3.2-90B-Vision-Instruct-Turbo',
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'claude-3-sonnet-20240229',
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'gemini-1.5-pro',
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]
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image_models = [
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'flux-pro/v1.1',
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'flux-realism',
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'flux-pro',
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'dalle-e-3',
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]
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models = [*chat_models, *image_models]
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model_aliases = {
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"o1": "o1-preview",
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"llama-3.1-405b": "meta-llama/Meta-Llama-3.1-405B-Instruct-Turbo",
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"llama-3.2-90b": "meta-llama/Llama-3.2-90B-Vision-Instruct-Turbo",
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"claude-3.5-sonnet": "claude-3-sonnet-20240229",
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"gemini-pro": "gemini-1.5-pro",
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"flux-pro": "flux-pro/v1.1",
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"dalle-3": "dalle-e-3",
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}
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persona_ids = {
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'gpt-4o': "gpt",
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'gpt-4o-mini': "amigo",
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'o1-preview': "openai-o-one",
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'o1-mini': "openai-o-one-mini",
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'meta-llama/Meta-Llama-3.1-405B-Instruct-Turbo': "llama-three-point-one",
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'meta-llama/Llama-3.2-90B-Vision-Instruct-Turbo': "llama-3-2",
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'claude-3-sonnet-20240229': "claude",
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'gemini-1.5-pro': "gemini-1-5-pro",
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'flux-pro/v1.1': "flux-1-1-pro",
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'flux-realism': "flux-realism",
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'flux-pro': "flux-pro",
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'dalle-e-3': "dalle-three",
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}
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@classmethod
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def get_model(cls, model: str) -> str:
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if model in cls.models:
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return model
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elif model in cls.model_aliases:
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return cls.model_aliases[model]
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else:
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return cls.default_chat_model if model in cls.chat_models else cls.default_image_model
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@classmethod
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def get_personaId(cls, model: str) -> str:
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return cls.persona_ids[model]
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@classmethod
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async def create_async_generator(
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cls,
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model: str,
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messages: Messages,
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proxy: str = None,
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stream: bool = False,
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**kwargs
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) -> AsyncResult:
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model = cls.get_model(model)
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device_uuid = str(uuid.uuid4())
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headers = {
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"accept": "*/*",
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"accept-language": "en-US,en;q=0.9",
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"authorization": "Bearer", # You need to implement proper authorization
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"cache-control": "no-cache",
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"content-type": "application/json",
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"origin": cls.url,
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"pragma": "no-cache",
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"priority": "u=1, i",
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"referer": f"{cls.url}/",
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"sec-ch-ua": '"Chromium";v="129", "Not=A?Brand";v="8"',
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"sec-ch-ua-mobile": "?0",
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"sec-ch-ua-platform": '"Linux"',
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"user-agent": "Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/129.0.0.0 Safari/537.36",
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"x-device-language": "en-US",
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"x-device-platform": "web",
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"x-device-uuid": device_uuid,
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"x-device-version": "1.0.32"
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}
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async with ClientSession(headers=headers) as session:
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if model in cls.chat_models:
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# Chat completion
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data = {
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"messages": [{"role": m["role"], "content": m["content"]} for m in messages],
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"model": model,
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"personaId": cls.get_personaId(model),
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"frequency_penalty": 0,
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"max_tokens": 4000,
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"presence_penalty": 0,
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"stream": stream,
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"temperature": 0.5,
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"top_p": 0.95
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}
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timeout = ClientTimeout(total=300) # 5 minutes timeout
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async with session.post(cls.chat_api_endpoint, json=data, proxy=proxy, timeout=timeout) as response:
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if response.status not in (200, 201):
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error_text = await response.text()
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raise Exception(f"Error {response.status}: {error_text}")
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async for line in response.content:
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line = line.decode('utf-8').strip()
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if line.startswith('data: '):
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if line == 'data: [DONE]':
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break
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try:
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chunk = json.loads(line[6:]) # Remove 'data: ' prefix
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if 'choices' in chunk and len(chunk['choices']) > 0:
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choice = chunk['choices'][0]
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if 'delta' in choice:
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content = choice['delta'].get('content')
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elif 'text' in choice:
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content = choice['text']
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else:
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content = None
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if content:
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yield content
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except json.JSONDecodeError:
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pass
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else:
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# Image generation
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prompt = messages[0]['content']
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data = {
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"prompt": prompt,
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"model": model,
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"personaId": cls.get_personaId(model)
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}
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async with session.post(cls.image_api_endpoint, json=data, proxy=proxy) as response:
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response.raise_for_status()
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response_data = await response.json()
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if "data" in response_data:
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image_urls = []
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for item in response_data["data"]:
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if "url" in item:
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image_url = item["url"]
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image_urls.append(image_url)
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if image_urls:
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yield ImageResponse(image_urls, prompt)
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else:
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yield None
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