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100% Google Gemini API 兼容 — APIXO 实现标准 Google Gemini API。只需将 baseURL 改为 https://api.apixo.ai 并使用 APIXO authkey。可与任何 Gemini 兼容 SDK 或工具无缝集成，无需修改代码。
Gemini 3 Pro 是 Google 旗舰多模态推理模型，支持文本、图像、视频和音频输入，具备长上下文对话、函数调用和结构化输出等能力。

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快速开始

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Direct API Call

curl -X POST https://api.apixo.ai/api/v1/google/models/gemini-3-pro:generateContent \
  -H "Authorization: Bearer YOUR_APIXO_AUTHKEY" \
  -H "Content-Type: application/json" \
  -d '{
    "contents": [
      {
        "role": "user",
        "parts": [{"text": "Explain quantum computing in simple terms."}]
      }
    ],
    "generationConfig": {
      "maxOutputTokens": 1024,
      "temperature": 0.7
    }
  }'

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JavaScript/TypeScript

const response = await fetch(
  "https://api.apixo.ai/api/v1/google/models/gemini-3-pro:generateContent",
  {
    method: "POST",
    headers: {
      "Authorization": "Bearer YOUR_APIXO_AUTHKEY",
      "Content-Type": "application/json"
    },
    body: JSON.stringify({
      contents: [
        {
          role: "user",
          parts: [{ text: "What is artificial intelligence?" }]
        }
      ],
      generationConfig: {
        temperature: 0.7,
        maxOutputTokens: 1024
      }
    })
  }
);

const result = await response.json();
console.log(result.candidates[0].content.parts[0].text);

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接口

APIXO 使用标准 Google Gemini API 接口格式：
  • Non-streaming: POST /api/v1/google/models/{model}:generateContent
  • Streaming: POST /api/v1/google/models/{model}:streamGenerateContent
其中 {model} 为模型名称（如 gemini-3-pro、gemini-3-flash 等）

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第三方 SDK 集成

APIXO 与 Google 官方 SDK 完全兼容。只需配置 base URL 和 API key：

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Python (Google SDK)

import google.generativeai as genai

genai.configure(
    api_key="YOUR_APIXO_AUTHKEY",
    transport="rest",
    client_options={
        "api_endpoint": "https://api.apixo.ai"
    }
)

model = genai.GenerativeModel('gemini-3-pro')
response = model.generate_content("What is quantum computing?")
print(response.text)

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Node.js (Google SDK)

const { GoogleGenerativeAI } = require("@google/generative-ai");

const genAI = new GoogleGenerativeAI("YOUR_APIXO_AUTHKEY");
genAI.baseUrl = "https://api.apixo.ai";

const model = genAI.getGenerativeModel({ model: "gemini-3-pro" });
const result = await model.generateContent("Explain neural networks");
console.log(result.response.text());

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LangChain

from langchain_google_genai import ChatGoogleGenerativeAI

llm = ChatGoogleGenerativeAI(
    model="gemini-3-pro",
    google_api_key="YOUR_APIXO_AUTHKEY",
    base_url="https://api.apixo.ai"
)

response = llm.invoke("What are transformers in AI?")

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Request Format

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Basic Request

{
  "contents": [
    {
      "role": "user",
      "parts": [
        {"text": "Your message here"}
      ]
    }
  ],
  "generationConfig": {
    "temperature": 0.7,
    "maxOutputTokens": 1024
  }
}

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With System Instruction

{
  "systemInstruction": {
    "parts": [
      {"text": "You are a helpful assistant specialized in..."}
    ]
  },
  "contents": [
    {
      "role": "user",
      "parts": [{"text": "Your message"}]
    }
  ]
}

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Multimodal Input (Image Analysis)

{
  "contents": [
    {
      "role": "user",
      "parts": [
        {"text": "Analyze this image and describe what you see."},
        {
          "fileData": {
            "mimeType": "image/jpeg",
            "fileUri": "https://example.com/image.jpg"
          }
        }
      ]
    }
  ]
}

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Parameters

​
contents
array
必填
Array of conversation messages with role and parts
​
systemInstruction
object
System prompt to guide model behavior
​
generationConfig
object
Generation settings

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Content Structure

Each message in contents has:
  • role: "user", "model", or "tool"
  • parts: Array of content parts (text, images, videos, etc.)

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Response Format

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Non-streaming Response

{
  "candidates": [
    {
      "content": {
        "role": "model",
        "parts": [
          {"text": "Generated response text..."}
        ]
      },
      "finishReason": "STOP",
      "safetyRatings": [...]
    }
  ],
  "usageMetadata": {
    "promptTokenCount": 10,
    "candidatesTokenCount": 150,
    "totalTokenCount": 160
  }
}

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Streaming Response

Streaming returns Server-Sent Events (SSE) with incremental chunks. Each chunk has the same structure, with the last chunk containing finishReason: "STOP".

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Multi-turn Conversations

Include previous messages in the contents array to maintain conversation context: 
{
  "contents": [
    {
      "role": "user",
      "parts": [{"text": "What is machine learning?"}]
    },
    {
      "role": "model",
      "parts": [{"text": "Machine learning is a subset of AI that..."}]
    },
    {
      "role": "user",
      "parts": [{"text": "Can you give me an example?"}]
    }
  ]
}
thoughtSignature Handling — If a response contains a thoughtSignature field, you must include it verbatim in subsequent requests to maintain reasoning context.

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Streaming

To enable streaming, use the streaming endpoint: 
const response = await fetch(
  "https://api.apixo.ai/api/v1/google/models/gemini-3-pro:streamGenerateContent",
  {
    method: "POST",
    headers: {
      "Authorization": "Bearer YOUR_APIXO_AUTHKEY",
      "Content-Type": "application/json"
    },
    body: JSON.stringify({
      contents: [
        {
          role: "user",
          parts: [{ text: "Write a short story about AI." }]
        }
      ]
    })
  }
);

// Process SSE stream
const reader = response.body.getReader();
const decoder = new TextDecoder();

while (true) {
  const { done, value } = await reader.read();
  if (done) break;
  
  const chunk = decoder.decode(value);
  console.log(chunk);
}

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Advanced Features

APIXO supports all Google Gemini API advanced features:
  • Function Calling (Tools): Enable models to call external functions
  • Structured Output: Define JSON Schema for return format
  • Thinking Mode: Enable reasoning traces
  • Safety Settings: Configure content filtering
  • Grounding: Connect to external knowledge sources
For detailed documentation on advanced features, see the Google Gemini API Official Documentation.

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Token Limits

  • Input tokens: Up to 1,000,000+ tokens (long context)
  • Output tokens: Up to 8,192 tokens (configurable via maxOutputTokens)

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Migration Guide

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From Google Cloud

Change two configuration values:
  1. Base URL: https://generativelanguage.googleapis.com → https://api.apixo.ai
  2. API Key: Google API key → APIXO authkey
Everything else remains identical.

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From OpenAI

APIXO uses Google’s API format which differs from OpenAI’s. Key differences:
AspectOpenAIGoogle/APIXO
Endpoint/v1/chat/completions/api/v1/google/models/{model}:generateContent
Message formatmessages: [{role, content}]contents: [{role, parts: [{text}]}]
Model fieldmodel: "gpt-4"URL path: /models/gemini-3-pro:...

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Notes

  • API Format: 100% Google Gemini API standard - no custom wrappers
  • Authentication: Bearer token with APIXO authkey
  • Base URL: https://api.apixo.ai
  • SDKs: Works with official Google SDKs by configuring base URL