mirror of
https://github.com/xtekky/gpt4free.git
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116 lines
3.8 KiB
Python
116 lines
3.8 KiB
Python
from __future__ import annotations
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import json
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from ..typing import AsyncResult, Messages
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from ..providers.response import Reasoning
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from ..requests import StreamSession
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from .base_provider import AsyncGeneratorProvider, ProviderModelMixin
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class GradientNetwork(AsyncGeneratorProvider, ProviderModelMixin):
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"""
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Provider for chat.gradient.network
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Supports streaming text generation with Qwen and GPT OSS models.
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"""
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label = "Gradient Network"
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url = "https://chat.gradient.network"
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api_endpoint = "https://chat.gradient.network/api/generate"
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working = True
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needs_auth = False
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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 = "Qwen3 235B"
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models = [
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default_model,
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"GPT OSS 120B",
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]
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model_aliases = {
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"qwen-3-235b": "Qwen3 235B",
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"qwen3-235b": "Qwen3 235B",
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"gpt-oss-120b": "GPT OSS 120B",
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}
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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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temperature: float = None,
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max_tokens: int = None,
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enable_thinking: bool = False,
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**kwargs
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) -> AsyncResult:
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"""
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Create an async generator for streaming chat responses.
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Args:
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model: The model name to use
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messages: List of message dictionaries
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proxy: Optional proxy URL
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temperature: Optional temperature parameter
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max_tokens: Optional max tokens parameter
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enable_thinking: Enable the thinking/analysis channel (maps to enableThinking in API)
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**kwargs: Additional arguments
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Yields:
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str: Content chunks from the response
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Reasoning: Reasoning content when enable_thinking is True
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"""
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model = cls.get_model(model)
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headers = {
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"Accept": "application/x-ndjson",
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"Content-Type": "application/json",
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"User-Agent": "Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/131.0.0.0 Safari/537.36",
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"Origin": cls.url,
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"Referer": f"{cls.url}/",
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}
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payload = {
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"model": model,
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"messages": messages,
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}
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if temperature is not None:
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payload["temperature"] = temperature
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if max_tokens is not None:
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payload["max_tokens"] = max_tokens
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if enable_thinking:
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payload["enableThinking"] = enable_thinking
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async with StreamSession(headers=headers, proxy=proxy) as session:
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async with session.post(
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cls.api_endpoint,
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json=payload,
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) as response:
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response.raise_for_status()
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async for line in response.iter_lines():
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if not line:
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continue
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try:
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data = json.loads(line)
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msg_type = data.get("type")
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if msg_type == "reply":
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# Response chunks with content or reasoningContent
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reply_data = data.get("data", {})
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content = reply_data.get("content")
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reasoning_content = reply_data.get("reasoningContent")
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if reasoning_content:
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yield Reasoning(reasoning_content)
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if content:
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yield content
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# Skip clusterInfo and blockUpdate GPU visualization messages
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except json.JSONDecodeError:
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# Skip non-JSON lines (may be partial data or empty)
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continue
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