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86 lines
2.5 KiB
Python
86 lines
2.5 KiB
Python
from __future__ import annotations
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import json
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import requests
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from ...typing import CreateResult, Messages
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from ..base_provider import ProviderModelMixin, AbstractProvider
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from ..helper import format_prompt
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class NexraGeminiPro(AbstractProvider, ProviderModelMixin):
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label = "Nexra Gemini PRO"
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url = "https://nexra.aryahcr.cc/documentation/gemini-pro/en"
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api_endpoint = "https://nexra.aryahcr.cc/api/chat/complements"
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working = True
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supports_stream = True
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default_model = 'gemini-pro'
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models = [default_model]
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@classmethod
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def get_model(cls, model: str) -> str:
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return cls.default_model
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@classmethod
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def create_completion(
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cls,
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model: str,
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messages: Messages,
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stream: bool,
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markdown: bool = False,
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**kwargs
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) -> CreateResult:
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model = cls.get_model(model)
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headers = {
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'Content-Type': 'application/json'
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}
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data = {
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"messages": [
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{
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"role": "user",
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"content": format_prompt(messages)
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}
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],
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"stream": stream,
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"markdown": markdown,
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"model": model
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}
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response = requests.post(cls.api_endpoint, headers=headers, json=data, stream=stream)
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if stream:
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return cls.process_streaming_response(response)
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else:
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return cls.process_non_streaming_response(response)
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@classmethod
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def process_non_streaming_response(cls, response):
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if response.status_code == 200:
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try:
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content = response.text.lstrip('')
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data = json.loads(content)
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return data.get('message', '')
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except json.JSONDecodeError:
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return "Error: Unable to decode JSON response"
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else:
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return f"Error: {response.status_code}"
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@classmethod
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def process_streaming_response(cls, response):
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full_message = ""
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for line in response.iter_lines(decode_unicode=True):
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if line:
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try:
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line = line.lstrip('')
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data = json.loads(line)
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if data.get('finish'):
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break
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message = data.get('message', '')
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if message:
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yield message[len(full_message):]
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full_message = message
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except json.JSONDecodeError:
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pass
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