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Added
g4f/Provider/hf_space/Qwen_Qwen_2_5M_Demo.py
+118
-0
Modified
g4f/Provider/hf_space/__init__.py
+5
-1
XFEstudio/gpt4free
Add Qwen_Qwen_2_5M_Demo provider
246b86fe
代码差异
2 个文件
+123
-1
@@ -0,0 +1,118 @@
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from __future__ import annotations
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import aiohttp
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import json
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import uuid
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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 ...providers.response import JsonConversation, Reasoning
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from ... import debug
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class Qwen_Qwen_2_5M_Demo(AsyncGeneratorProvider, ProviderModelMixin):
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url = "https://qwen-qwen2-5-1m-demo.hf.space"
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api_endpoint = f"{url}/run/predict?__theme=light"
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working = True
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supports_stream = True
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supports_system_message = True
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supports_message_history = False
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default_model = "qwen-qwen2-5m-demo"
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models = [default_model]
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model_aliases = {"qwen-2-5m": default_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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return_conversation: bool = False,
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conversation: JsonConversation = None,
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**kwargs
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) -> AsyncResult:
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def generate_session_hash():
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"""Generate a unique session hash."""
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return str(uuid.uuid4()).replace('-', '')[:12]
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# Generate a unique session hash
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session_hash = generate_session_hash() if conversation is None else getattr(conversation, "session_hash")
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if return_conversation:
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yield JsonConversation(session_hash=session_hash)
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prompt = format_prompt(messages) if conversation is None else messages[-1]["content"]
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headers = {
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'accept': '*/*',
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'accept-language': 'en-US',
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'content-type': 'application/json',
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'origin': cls.url,
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'referer': f'{cls.url}/?__theme=light',
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'user-agent': 'Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/132.0.0.0 Safari/537.36'
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}
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payload_predict = {
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"data":[{"files":[],"text":prompt},[],[]],
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"event_data": None,
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"fn_index": 1,
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"trigger_id": 5,
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"session_hash": session_hash
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}
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async with aiohttp.ClientSession() as session:
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# Send join request
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async with session.post(cls.api_endpoint, headers=headers, json=payload_predict) as response:
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data = (await response.json())['data']
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join_url = f"{cls.url}/queue/join?__theme=light"
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join_data = {"data":[[[{"id":None,"elem_id":None,"elem_classes":None,"name":None,"text":prompt,"flushing":None,"avatar":"","files":[]},None]],None,0],"event_data":None,"fn_index":2,"trigger_id":5,"session_hash":session_hash}
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async with session.post(join_url, headers=headers, json=join_data) as response:
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event_id = (await response.json())['event_id']
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# Prepare data stream request
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url_data = f'{cls.url}/queue/data?session_hash={session_hash}'
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headers_data = {
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'accept': 'text/event-stream',
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'referer': f'{cls.url}/?__theme=light',
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'user-agent': 'Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/132.0.0.0 Safari/537.36'
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}
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# Send data stream request
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async with session.get(url_data, headers=headers_data) as response:
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yield_response = ""
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yield_response_len = 0
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async for line in response.content:
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decoded_line = line.decode('utf-8')
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if decoded_line.startswith('data: '):
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try:
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json_data = json.loads(decoded_line[6:])
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# Look for generation stages
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if json_data.get('msg') == 'process_generating':
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if 'output' in json_data and 'data' in json_data['output'] and json_data['output']['data'][0]:
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output_data = json_data['output']['data'][0][0]
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if len(output_data) > 2:
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text = output_data[2].split("\n<summary>")[0]
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if text == "Qwen is thinking...":
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yield Reasoning(None, text)
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elif text.startswith(yield_response):
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yield text[yield_response_len:]
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else:
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yield text
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yield_response_len = len(text)
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yield_response = text
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# Check for completion
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if json_data.get('msg') == 'process_completed':
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# Final check to ensure we get the complete response
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if 'output' in json_data and 'data' in json_data['output']:
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output_data = json_data['output']['data'][0][0][1][0]["text"].split("\n<summary>")[0]
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yield output_data[yield_response_len:]
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yield_response_len = len(text)
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break
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except json.JSONDecodeError:
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debug.log("Could not parse JSON:", decoded_line)
@@ -11,6 +11,7 @@ from .BlackForestLabsFlux1Schnell import BlackForestLabsFlux1Schnell
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from .VoodoohopFlux1Schnell import VoodoohopFlux1Schnell
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from .CohereForAI import CohereForAI
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from .Qwen_QVQ_72B import Qwen_QVQ_72B
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from .Qwen_Qwen_2_5M_Demo import Qwen_Qwen_2_5M_Demo
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from .Qwen_Qwen_2_72B_Instruct import Qwen_Qwen_2_72B_Instruct
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from .StableDiffusion35Large import StableDiffusion35Large
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@@ -23,7 +24,10 @@ class HuggingSpace(AsyncGeneratorProvider, ProviderModelMixin):
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default_model = Qwen_Qwen_2_72B_Instruct.default_model
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default_image_model = BlackForestLabsFlux1Dev.default_model
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default_vision_model = Qwen_QVQ_72B.default_model
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providers = [BlackForestLabsFlux1Dev, BlackForestLabsFlux1Schnell, VoodoohopFlux1Schnell, CohereForAI, Qwen_QVQ_72B, Qwen_Qwen_2_72B_Instruct, StableDiffusion35Large]
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providers = [
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BlackForestLabsFlux1Dev, BlackForestLabsFlux1Schnell, VoodoohopFlux1Schnell,
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CohereForAI, Qwen_QVQ_72B, Qwen_Qwen_2_5M_Demo, Qwen_Qwen_2_72B_Instruct, StableDiffusion35Large
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]
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@classmethod
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def get_parameters(cls, **kwargs) -> dict: