from __future__ import annotations import json import requests from ...typing import CreateResult, Messages from ..base_provider import ProviderModelMixin, AbstractProvider from ..helper import format_prompt class NexraGeminiPro(AbstractProvider, ProviderModelMixin): label = "Nexra Gemini PRO" url = "https://nexra.aryahcr.cc/documentation/gemini-pro/en" api_endpoint = "https://nexra.aryahcr.cc/api/chat/complements" working = True supports_stream = True default_model = 'gemini-pro' models = [default_model] @classmethod def get_model(cls, model: str) -> str: return cls.default_model @classmethod def create_completion( cls, model: str, messages: Messages, stream: bool, proxy: str = None, markdown: bool = False, **kwargs ) -> CreateResult: model = cls.get_model(model) headers = { 'Content-Type': 'application/json' } data = { "messages": [ { "role": "user", "content": format_prompt(messages) } ], "stream": stream, "markdown": markdown, "model": model } response = requests.post(cls.api_endpoint, headers=headers, json=data, stream=stream) if stream: return cls.process_streaming_response(response) else: return cls.process_non_streaming_response(response) @classmethod def process_non_streaming_response(cls, response): if response.status_code == 200: try: content = response.text.lstrip('') data = json.loads(content) return data.get('message', '') except json.JSONDecodeError: return "Error: Unable to decode JSON response" else: return f"Error: {response.status_code}" @classmethod def process_streaming_response(cls, response): full_message = "" for line in response.iter_lines(decode_unicode=True): if line: try: line = line.lstrip('') data = json.loads(line) if data.get('finish'): break message = data.get('message', '') if message: yield message[len(full_message):] full_message = message except json.JSONDecodeError: pass