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from __future__ import annotations |
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import json |
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import requests |
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from ..typing import Any, CreateResult |
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from .base_provider import BaseProvider |
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class Lockchat(BaseProvider): |
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url: str = "http://supertest.lockchat.app" |
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supports_stream = True |
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supports_gpt_35_turbo = True |
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supports_gpt_4 = True |
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@staticmethod |
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def create_completion( |
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model: str, |
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messages: list[dict[str, str]], |
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stream: bool, **kwargs: Any) -> CreateResult: |
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temperature = float(kwargs.get("temperature", 0.7)) |
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payload = { |
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"temperature": temperature, |
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"messages" : messages, |
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"model" : model, |
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"stream" : True, |
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} |
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headers = { |
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"user-agent": "ChatX/39 CFNetwork/1408.0.4 Darwin/22.5.0", |
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} |
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response = requests.post("http://supertest.lockchat.app/v1/chat/completions", |
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json=payload, headers=headers, stream=True) |
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response.raise_for_status() |
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for token in response.iter_lines(): |
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if b"The model: `gpt-4` does not exist" in token: |
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print("error, retrying...") |
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Lockchat.create_completion( |
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model = model, |
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messages = messages, |
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stream = stream, |
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temperature = temperature, |
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**kwargs) |
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if b"content" in token: |
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token = json.loads(token.decode("utf-8").split("data: ")[1]) |
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token = token["choices"][0]["delta"].get("content") |
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if token: |
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yield (token) |
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@classmethod |
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@property |
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def params(cls): |
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params = [ |
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("model", "str"), |
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("messages", "list[dict[str, str]]"), |
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("stream", "bool"), |
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("temperature", "float"), |
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] |
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param = ", ".join([": ".join(p) for p in params]) |
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return f"g4f.provider.{cls.__name__} supports: ({param})" |
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