| 1 | # -*- coding: utf-8 -*- |
| 2 | """ |
| 3 | Google Gemini LLM 客户端 (OpenAI 兼容格式) |
| 4 | 支持 gemini-2.5-flash, gemini-2.5-pro 等模型 |
| 5 | |
| 6 | 可用模型: |
| 7 | - gemini-2.5-flash (性价比高) |
| 8 | - gemini-2.5-flash-preview |
| 9 | - gemini-2.5-pro (效果最好) |
| 10 | - gemini-2.5-pro-preview |
| 11 | - gemini-2.0-flash |
| 12 | """ |
| 13 | |
| 14 | import os |
| 15 | import sys |
| 16 | |
| 17 | models_dir = os.path.dirname(os.path.abspath(__file__)) |
| 18 | backend_dir = os.path.dirname(models_dir) |
| 19 | if backend_dir not in sys.path: |
| 20 | sys.path.insert(0, backend_dir) |
| 21 | |
| 22 | import time |
| 23 | import logging |
| 24 | import httpx |
| 25 | from openai import OpenAI |
| 26 | from typing import List |
| 27 | from config import Config |
| 28 | |
| 29 | logger = logging.getLogger(__name__) |
| 30 | |
| 31 | |
| 32 | class Gemini: |
| 33 | """ |
| 34 | Gemini LLM 客户端，使用 OpenAI 兼容格式调用 |
| 35 | """ |
| 36 | def __init__(self, base_url: str = "", api_key: str = ""): |
| 37 | """ |
| 38 | 初始化 Gemini 客户端 |
| 39 | :param base_url: OpenAI 兼容的 Base URL |
| 40 | :param api_key: Gemini API Key |
| 41 | """ |
| 42 | # 确保 base_url 以 /v1 结尾 |
| 43 | default_url = "https://generativelanguage.googleapis.com/v1beta" |
| 44 | self.base_url = base_url or Config.GOOGLE_GEMINI_BASE_URL or default_url |
| 45 | if self.base_url and not self.base_url.endswith("/v1"): |
| 46 | self.base_url = self.base_url.rstrip("/") + "/v1" |
| 47 | self.api_key = api_key or Config.GEMINI_API_KEY |
| 48 | kwargs = {"api_key": self.api_key, "base_url": self.base_url} |
| 49 | proxy = Config.provider_proxy("gemini") |
| 50 | if proxy: |
| 51 | kwargs["http_client"] = httpx.Client(proxy=proxy) |
| 52 | self.client = OpenAI(**kwargs) |
| 53 | self.max_attempts = 10 |
| 54 | |
| 55 | def query(self, prompt: str, image_urls: List[str] = [], model: str = "gemini-2.5-flash") -> str: |
| 56 | """ |
| 57 | 调用 Gemini LLM |
| 58 | :param prompt: 文本提示 |
| 59 | :param image_urls: 图片 URL 列表（可选，用于多模态模型） |
| 60 | :param model: 模型名 |
| 61 | :return: 生成的文本 |
| 62 | """ |
| 63 | if not model: |
| 64 | model = "gemini-2.5-flash" |
| 65 | |
| 66 | # 构建消息格式 |
| 67 | content: list = [{"type": "text", "text": prompt}] |
| 68 | |
| 69 | # 添加图片 (如果有多模态模型支持) |
| 70 | if image_urls: |
| 71 | for img_url in image_urls: |
| 72 | if img_url.startswith("http"): |
| 73 | content.append({ |
| 74 | "type": "image_url", |
| 75 | "image_url": {"url": img_url} |
| 76 | }) |
| 77 | |
| 78 | messages = [{"role": "user", "content": content}] |
| 79 | |
| 80 | attempts = 0 |
| 81 | while attempts < self.max_attempts: |
| 82 | try: |
| 83 | # 直接使用模型名（代理服务会处理格式转换） |
| 84 | response = self.client.chat.completions.create( |
| 85 | model=model, |
| 86 | messages=messages, |
| 87 | temperature=0.7 |
| 88 | ) |
| 89 | |
| 90 | # 检查响应类型 |
| 91 | if isinstance(response, str): |
| 92 | logger.error("Gemini returned a string response: %s", response) |
| 93 | raise Exception(f"API 返回错误: {response}") |
| 94 | |
| 95 | if response.choices and len(response.choices) > 0: |
| 96 | return response.choices[0].message.content |
| 97 | |
| 98 | except Exception as e: |
| 99 | logger.warning("Gemini request failed: %s", e) |
| 100 | attempts += 1 |
| 101 | if attempts < self.max_attempts: |
| 102 | time.sleep(10) |
| 103 | |
| 104 | raise Exception("Gemini: 达到最大重试次数，仍未获得有效响应。") |
| 105 | |
| 106 | |
| 107 | if __name__ == "__main__": |
| 108 | import sys |
| 109 | sys.path.insert(0, os.path.dirname(os.path.dirname(os.path.abspath(__file__)))) |
| 110 | from config import Config |
| 111 | |
| 112 | # 支持的模型列表 |
| 113 | MODELS = ["gemini-2.5-flash", "gemini-2.0-flash"] |
| 114 | |
| 115 | print("=== Gemini LLM 可用性测试 ===") |
| 116 | api_key = Config.GEMINI_API_KEY |
| 117 | base_url = Config.GOOGLE_GEMINI_BASE_URL |
| 118 | if not api_key: |
| 119 | print("✗ GEMINI_API_KEY 未设置，跳过") |
| 120 | sys.exit(1) |
| 121 | print(f" API Key: {api_key[:6]}***") |
| 122 | print(f" Base URL: {base_url}") |
| 123 | client = Gemini(api_key=api_key, base_url=base_url) |
| 124 | prompt = "用一句话介绍你自己。" |
| 125 | print(f" Prompt: {prompt}") |
| 126 | |
| 127 | for model in MODELS: |
| 128 | print(f"\n--- 测试模型: {model} ---") |
| 129 | t0 = time.time() |
| 130 | try: |
| 131 | resp = client.query(prompt, model=model) |
| 132 | elapsed = time.time() - t0 |
| 133 | print(f"✓ 响应 ({elapsed:.1f}s): {resp.strip()[:200]}") |
| 134 | except Exception as e: |
| 135 | print(f"✗ 失败: {e}") |
| 136 |