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Add Janus_Pro_7B provider
Add proof of DeepSeekAPI provider Add BackendApi provider from HuggingSpace
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hlohaus
parent
efacc15d92
commit
30381f687e
29 changed files with 415 additions and 28 deletions
187
g4f/Provider/template/OpenaiTemplate.py
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187
g4f/Provider/template/OpenaiTemplate.py
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from __future__ import annotations
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import json
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import time
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import requests
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from ..helper import filter_none
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from ..base_provider import AsyncGeneratorProvider, ProviderModelMixin, RaiseErrorMixin
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from ...typing import Union, Optional, AsyncResult, Messages, ImagesType
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from ...requests import StreamSession, raise_for_status
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from ...providers.response import FinishReason, ToolCalls, Usage, Reasoning, ImageResponse
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from ...errors import MissingAuthError, ResponseError
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from ...image import to_data_uri
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from ... import debug
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class OpenaiTemplate(AsyncGeneratorProvider, ProviderModelMixin, RaiseErrorMixin):
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api_base = ""
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supports_message_history = True
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supports_system_message = True
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default_model = ""
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fallback_models = []
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sort_models = True
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ssl = None
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@classmethod
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def get_models(cls, api_key: str = None, api_base: str = None) -> list[str]:
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if not cls.models:
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try:
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headers = {}
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if api_base is None:
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api_base = cls.api_base
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if api_key is not None:
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headers["authorization"] = f"Bearer {api_key}"
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response = requests.get(f"{api_base}/models", headers=headers, verify=cls.ssl)
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raise_for_status(response)
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data = response.json()
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data = data.get("data") if isinstance(data, dict) else data
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cls.image_models = [model.get("id") for model in data if model.get("image")]
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cls.models = [model.get("id") for model in data]
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if cls.sort_models:
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cls.models.sort()
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except Exception as e:
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debug.log(e)
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return cls.fallback_models
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return cls.models
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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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timeout: int = 120,
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images: ImagesType = None,
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api_key: str = None,
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api_endpoint: str = None,
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api_base: str = None,
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temperature: float = None,
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max_tokens: int = None,
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top_p: float = None,
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stop: Union[str, list[str]] = None,
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stream: bool = False,
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prompt: str = None,
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headers: dict = None,
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impersonate: str = None,
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tools: Optional[list] = None,
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extra_data: dict = {},
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**kwargs
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) -> AsyncResult:
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if cls.needs_auth and api_key is None:
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raise MissingAuthError('Add a "api_key"')
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async with StreamSession(
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proxy=proxy,
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headers=cls.get_headers(stream, api_key, headers),
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timeout=timeout,
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impersonate=impersonate,
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) as session:
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model = cls.get_model(model, api_key=api_key, api_base=api_base)
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if api_base is None:
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api_base = cls.api_base
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# Proxy for image generation feature
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if model and model in cls.image_models:
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data = {
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"prompt": messages[-1]["content"] if prompt is None else prompt,
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"model": model,
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}
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async with session.post(f"{api_base.rstrip('/')}/images/generations", json=data, ssl=cls.ssl) as response:
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data = await response.json()
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cls.raise_error(data)
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await raise_for_status(response)
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yield ImageResponse([image["url"] for image in data["data"]], prompt)
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return
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if images is not None and messages:
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if not model and hasattr(cls, "default_vision_model"):
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model = cls.default_vision_model
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last_message = messages[-1].copy()
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last_message["content"] = [
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*[{
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"type": "image_url",
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"image_url": {"url": to_data_uri(image)}
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} for image, _ in images],
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{
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"type": "text",
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"text": messages[-1]["content"]
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}
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]
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messages[-1] = last_message
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data = filter_none(
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messages=messages,
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model=model,
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temperature=temperature,
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max_tokens=max_tokens,
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top_p=top_p,
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stop=stop,
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stream=stream,
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tools=tools,
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**extra_data
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)
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if api_endpoint is None:
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api_endpoint = f"{api_base.rstrip('/')}/chat/completions"
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async with session.post(api_endpoint, json=data, ssl=cls.ssl) as response:
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content_type = response.headers.get("content-type", "text/event-stream" if stream else "application/json")
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if content_type.startswith("application/json"):
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data = await response.json()
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cls.raise_error(data)
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await raise_for_status(response)
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choice = data["choices"][0]
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if "content" in choice["message"] and choice["message"]["content"]:
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yield choice["message"]["content"].strip()
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elif "tool_calls" in choice["message"]:
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yield ToolCalls(choice["message"]["tool_calls"])
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if "usage" in data:
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yield Usage(**data["usage"])
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if "finish_reason" in choice and choice["finish_reason"] is not None:
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yield FinishReason(choice["finish_reason"])
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return
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elif content_type.startswith("text/event-stream"):
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await raise_for_status(response)
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first = True
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is_thinking = 0
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async for line in response.iter_lines():
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if line.startswith(b"data: "):
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chunk = line[6:]
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if chunk == b"[DONE]":
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break
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data = json.loads(chunk)
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cls.raise_error(data)
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choice = data["choices"][0]
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if "content" in choice["delta"] and choice["delta"]["content"]:
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delta = choice["delta"]["content"]
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if first:
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delta = delta.lstrip()
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if delta:
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first = False
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if is_thinking:
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if "</think>" in delta:
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yield Reasoning(None, f"Finished in {round(time.time()-is_thinking, 2)} seconds")
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is_thinking = 0
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else:
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yield Reasoning(delta)
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elif "<think>" in delta:
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is_thinking = time.time()
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yield Reasoning(None, "Is thinking...")
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else:
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yield delta
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if "usage" in data and data["usage"]:
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yield Usage(**data["usage"])
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if "finish_reason" in choice and choice["finish_reason"] is not None:
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yield FinishReason(choice["finish_reason"])
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break
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else:
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await raise_for_status(response)
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raise ResponseError(f"Not supported content-type: {content_type}")
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@classmethod
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def get_headers(cls, stream: bool, api_key: str = None, headers: dict = None) -> dict:
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return {
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"Accept": "text/event-stream" if stream else "application/json",
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"Content-Type": "application/json",
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**(
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{"Authorization": f"Bearer {api_key}"}
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if api_key else {}
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),
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**({} if headers is None else headers)
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}
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