简体中文
cURL
curl --request POST \ --url https://ai.kaiho.cc/v1/models/{model}:generateContent \ --header 'Content-Type: application/json' \ --data ' { "contents": [ { "role": "<string>", "parts": [ {} ] } ], "generationConfig": { "temperature": 123, "maxOutputTokens": 123, "topP": 123, "topK": 123 } } '
使用 Google Gemini 原生 API 格式
gemini-2.0-flash-exp
gemini-1.5-pro
gemini-1.5-flash
显示 内容对象
user
model
显示 配置选项
curl https://ai.kaiho.cc/v1/models/gemini-2.0-flash-exp:generateContent \ -H "Content-Type: application/json" \ -H "x-goog-api-key: YOUR_API_KEY" \ -d '{ "contents": [ { "role": "user", "parts": [ { "text": "解释量子计算的基本原理" } ] } ], "generationConfig": { "temperature": 0.7, "maxOutputTokens": 1000, "topP": 0.95 } }'
{ "candidates": [ { "content": { "role": "model", "parts": [ { "text": "量子计算是一种利用量子力学原理..." } ] }, "finishReason": "STOP", "safetyRatings": [...] } ], "usageMetadata": { "promptTokenCount": 12, "candidatesTokenCount": 156, "totalTokenCount": 168 } }
import PIL.Image # 加载图像 img = PIL.Image.open('image.jpg') # 发送文本和图像 response = model.generate_content([ "描述这张图片中的内容", img ]) print(response.text)
response = model.generate_content( "写一个关于AI的故事", stream=True ) for chunk in response: print(chunk.text, end="")
from google.generativeai.types import HarmCategory, HarmBlockThreshold response = model.generate_content( "你的提示词", safety_settings={ HarmCategory.HARM_CATEGORY_HATE_SPEECH: HarmBlockThreshold.BLOCK_ONLY_HIGH, HarmCategory.HARM_CATEGORY_HARASSMENT: HarmBlockThreshold.BLOCK_ONLY_HIGH, } )