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from __future__ import annotations |
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import uuid |
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import requests |
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from ..typing import AsyncResult, Messages |
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from ..providers.response import Usage, Reasoning |
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from ..requests import StreamSession, raise_for_status |
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from .base_provider import AsyncGeneratorProvider, ProviderModelMixin |
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class GLM(AsyncGeneratorProvider, ProviderModelMixin): |
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url = "https://chat.z.ai" |
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api_endpoint = "https://chat.z.ai/api/chat/completions" |
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working = True |
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active_by_default = True |
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default_model = "GLM-4.5" |
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api_key = None |
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@classmethod |
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def get_models(cls, **kwargs) -> str: |
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if not cls.models: |
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response = requests.get(f"{cls.url}/api/v1/auths/") |
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cls.api_key = response.json().get("token") |
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response = requests.get(f"{cls.url}/api/models", headers={"Authorization": f"Bearer {cls.api_key}"}) |
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data = response.json().get("data", []) |
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cls.model_aliases = {data.get("name", "").replace("\u4efb\u52a1\u4e13\u7528", "ChatGLM"): data.get("id") for data in data} |
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cls.models = list(cls.model_aliases.keys()) |
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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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**kwargs |
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) -> AsyncResult: |
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cls.get_models() |
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model = cls.get_model(model) |
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data = { |
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"chat_id": "local", |
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"id": str(uuid.uuid4()), |
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"stream": True, |
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"model": model, |
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"messages": messages, |
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"params": {}, |
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"tool_servers": [], |
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"features": { |
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"enable_thinking": True |
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} |
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} |
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async with StreamSession( |
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impersonate="chrome", |
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proxy=proxy, |
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) as session: |
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async with session.post( |
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cls.api_endpoint, |
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json=data, |
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headers={"Authorization": f"Bearer {cls.api_key}", "x-fe-version": "prod-fe-1.0.57"}, |
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) as response: |
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await raise_for_status(response) |
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usage = None |
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async for chunk in response.sse(): |
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if chunk.get("type") == "chat:completion": |
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if not usage: |
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usage = chunk.get("data", {}).get("usage") |
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if usage: |
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yield Usage(**usage) |
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if chunk.get("data", {}).get("phase") == "thinking": |
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delta_content = chunk.get("data", {}).get("delta_content") |
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delta_content = delta_content.split("</summary>\n>")[-1] if delta_content else "" |
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if delta_content: |
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yield Reasoning(delta_content) |
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else: |
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edit_content = chunk.get("data", {}).get("edit_content") |
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if edit_content: |
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yield edit_content.split("\n</details>\n")[-1] |
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else: |
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delta_content = chunk.get("data", {}).get("delta_content") |
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if delta_content: |
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yield delta_content |
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