> ## Documentation Index
> Fetch the complete documentation index at: https://docs.mixroute.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Gemini Native (Text)

> Use Google Gemini native format to call API

## Introduction

The Gemini Native API uses Google Gemini's request and response format, suitable for Google official clients (such as `google-generativeai` SDK) or scenarios requiring direct use of Gemini data structures.

If using OpenAI-compatible clients (such as OpenAI SDK), please use the `/v1/chat/completions` endpoint.

### Differences from OpenAI Format

| Feature             | Gemini Native         | OpenAI Compatible            |
| ------------------- | --------------------- | ---------------------------- |
| Message Structure   | `contents[].parts[]`  | `messages[].content`         |
| Role Names          | `user` / `model`      | `user` / `assistant`         |
| Streaming Parameter | URL param `?alt=sse`  | Body param `stream: true`    |
| System Prompt       | `systemInstruction`   | `messages[0].role: "system"` |
| Multimodal          | Mixed `parts[]` array | Mixed `content[]` array      |

## API Endpoints

| Function                        | Method | Path                                                   |
| ------------------------------- | ------ | ------------------------------------------------------ |
| Text Generation (Non-streaming) | POST   | `/v1beta/models/{model}:generateContent`               |
| Text Generation (Streaming)     | POST   | `/v1beta/models/{model}:streamGenerateContent?alt=sse` |
| Single Embedding                | POST   | `/v1beta/models/{model}:embedContent`                  |
| Batch Embedding                 | POST   | `/v1beta/models/{model}:batchEmbedContents`            |

## Authentication

Two authentication methods are supported:

| Method                     | Header           | Example                |
| -------------------------- | ---------------- | ---------------------- |
| Bearer Token (Recommended) | `Authorization`  | `Bearer sk-xxxxxxxxxx` |
| Google Style               | `x-goog-api-key` | `sk-xxxxxxxxxx`        |

## Request Parameters

| Parameter           | Type   | Required | Description                                       |
| ------------------- | ------ | -------- | ------------------------------------------------- |
| `contents`          | array  | Yes      | Conversation content array                        |
| `generationConfig`  | object | No       | Generation configuration                          |
| `safetySettings`    | array  | No       | Safety filter settings                            |
| `systemInstruction` | object | No       | System instruction                                |
| `tools`             | array  | No       | Tool definitions (function calling, search, etc.) |
| `cachedContent`     | string | No       | Cached content name                               |

### generationConfig Parameters

| Parameter         | Type    | Description                   |
| ----------------- | ------- | ----------------------------- |
| `temperature`     | number  | Randomness (0-2)              |
| `topP`            | number  | Nucleus sampling (0-1)        |
| `topK`            | integer | Top-K sampling                |
| `maxOutputTokens` | integer | Maximum output tokens         |
| `stopSequences`   | array   | Stop sequences                |
| `candidateCount`  | integer | Number of candidate responses |
| `thinkingConfig`  | object  | Thinking mode configuration   |

## Basic Examples

<Tabs>
  <Tab title="cURL (Non-streaming)">
    ```bash theme={null}
    curl -X POST "https://api.mixroute.ai/v1beta/models/gemini-2.5-pro:generateContent" \
      -H "Content-Type: application/json" \
      -H "Authorization: Bearer sk-xxxxxxxxxx" \
      -d '{
        "contents": [
          {"role": "user", "parts": [{"text": "Explain artificial intelligence in one sentence"}]}
        ],
        "generationConfig": {
          "temperature": 0.7,
          "maxOutputTokens": 1024
        }
      }'
    ```
  </Tab>

  <Tab title="cURL (Streaming)">
    ```bash theme={null}
    curl -X POST "https://api.mixroute.ai/v1beta/models/gemini-2.5-pro:streamGenerateContent?alt=sse" \
      -H "Content-Type: application/json" \
      -H "Authorization: Bearer sk-xxxxxxxxxx" \
      -d '{
        "contents": [
          {"role": "user", "parts": [{"text": "Write a poem about spring"}]}
        ],
        "generationConfig": {
          "temperature": 0.8,
          "maxOutputTokens": 2048
        }
      }'
    ```
  </Tab>

  <Tab title="Python">
    ```python theme={null}
    import google.generativeai as genai

    genai.configure(
        api_key="sk-xxxxxxxxxx",
        transport="rest",
        client_options={"api_endpoint": "https://api.mixroute.ai"}
    )

    model = genai.GenerativeModel("gemini-2.5-pro")
    response = model.generate_content("Explain artificial intelligence in one sentence")
    print(response.text)
    ```
  </Tab>

  <Tab title="Node.js">
    ```javascript theme={null}
    import { GoogleGenerativeAI } from "@google/generative-ai";

    const genAI = new GoogleGenerativeAI("sk-xxxxxxxxxx");

    // Custom endpoint
    const model = genAI.getGenerativeModel(
      { model: "gemini-2.5-pro" },
      { baseUrl: "https://api.mixroute.ai/v1beta" }
    );

    const result = await model.generateContent("Explain artificial intelligence in one sentence");
    console.log(result.response.text());
    ```
  </Tab>
</Tabs>

## Advanced Features

<Tabs>
  <Tab title="Thinking Mode">
    ### Thinking Mode

    Gemini 2.5 Pro and Gemini 3 Pro support thinking mode, allowing the model to perform deep reasoning before answering.

    **Gemini 2.5 Pro** - Using `thinkingBudget`:

    ```json theme={null}
    {
      "contents": [{"role": "user", "parts": [{"text": "Solve this geometry problem step by step"}]}],
      "generationConfig": {
        "maxOutputTokens": 16384,
        "thinkingConfig": {
          "includeThoughts": true,
          "thinkingBudget": 8192
        }
      }
    }
    ```

    **Gemini 3 Pro** - Using `thinkingLevel`:

    ```json theme={null}
    {
      "contents": [{"role": "user", "parts": [{"text": "Explain the principles of quantum entanglement"}]}],
      "generationConfig": {
        "maxOutputTokens": 16384,
        "thinkingConfig": {
          "includeThoughts": true,
          "thinkingLevel": "MEDIUM"
        }
      }
    }
    ```

    | Parameter        | Applicable Model | Options                   |
    | ---------------- | ---------------- | ------------------------- |
    | `thinkingBudget` | Gemini 2.5 Pro   | 1-24576 (token count)     |
    | `thinkingLevel`  | Gemini 3 Pro     | `LOW` / `MEDIUM` / `HIGH` |
  </Tab>

  <Tab title="Multimodal Input">
    ### Multimodal Input

    Supports multiple input formats including images, audio, and video.

    **Image Input (Base64):**

    ```json theme={null}
    {
      "contents": [
        {
          "role": "user",
          "parts": [
            {
              "inlineData": {
                "mimeType": "image/jpeg",
                "data": "BASE64_ENCODED_IMAGE"
              }
            },
            {"text": "Describe the content of this image"}
          ]
        }
      ]
    }
    ```

    **Image Input (URL):**

    ```json theme={null}
    {
      "contents": [
        {
          "role": "user",
          "parts": [
            {
              "fileData": {
                "mimeType": "image/jpeg",
                "fileUri": "https://example.com/image.jpg"
              }
            },
            {"text": "What's in this image?"}
          ]
        }
      ]
    }
    ```

    **Supported MIME Types:**

    * Images: `image/jpeg`, `image/png`, `image/gif`, `image/webp`
    * Audio: `audio/mp3`, `audio/wav`, `audio/aac`
    * Video: `video/mp4`, `video/webm`
    * Documents: `application/pdf`
  </Tab>

  <Tab title="Function Calling">
    ### Function Calling

    ```json theme={null}
    {
      "contents": [{"role": "user", "parts": [{"text": "What's the weather like in Shanghai today?"}]}],
      "tools": [
        {
          "functionDeclarations": [
            {
              "name": "get_weather",
              "description": "Get weather information for a specified city",
              "parameters": {
                "type": "object",
                "properties": {
                  "location": {
                    "type": "string",
                    "description": "City name"
                  },
                  "unit": {
                    "type": "string",
                    "enum": ["celsius", "fahrenheit"],
                    "description": "Temperature unit"
                  }
                },
                "required": ["location"]
              }
            }
          ]
        }
      ],
      "toolConfig": {
        "functionCallingConfig": {
          "mode": "AUTO"
        }
      }
    }
    ```

    **Function Calling Modes:**

    * `AUTO`: Model automatically decides whether to call
    * `ANY`: Force tool invocation
    * `NONE`: Disable tool invocation
  </Tab>

  <Tab title="Google Search">
    ### Google Search (Grounding)

    Enable Google Search for real-time information:

    ```json theme={null}
    {
      "contents": [{"role": "user", "parts": [{"text": "What's the weather like in Beijing today?"}]}],
      "tools": [
        {
          "googleSearch": {}
        }
      ]
    }
    ```

    **Dynamic Retrieval Configuration:**

    ```json theme={null}
    {
      "contents": [{"role": "user", "parts": [{"text": "Latest AI news"}]}],
      "tools": [
        {
          "googleSearch": {
            "dynamicRetrievalConfig": {
              "mode": "MODE_DYNAMIC",
              "dynamicThreshold": 0.5
            }
          }
        }
      ]
    }
    ```
  </Tab>

  <Tab title="Streaming">
    ### Streaming Output

    **Python Streaming:**

    ```python theme={null}
    import google.generativeai as genai

    genai.configure(
        api_key="sk-xxxxxxxxxx",
        transport="rest",
        client_options={"api_endpoint": "https://api.mixroute.ai"}
    )

    model = genai.GenerativeModel("gemini-2.5-pro")
    response = model.generate_content(
        "Write an article about artificial intelligence",
        stream=True
    )

    for chunk in response:
        print(chunk.text, end="", flush=True)
    ```

    **cURL Streaming:**

    ```bash theme={null}
    curl -X POST "https://api.mixroute.ai/v1beta/models/gemini-2.5-pro:streamGenerateContent?alt=sse" \
      -H "Content-Type: application/json" \
      -H "Authorization: Bearer sk-xxxxxxxxxx" \
      -d '{
        "contents": [{"role": "user", "parts": [{"text": "Tell me a story"}]}]
      }'
    ```
  </Tab>

  <Tab title="Context Caching">
    ### Context Caching

    For long texts or multi-turn conversations, caching can save token consumption.

    **Create Cache:**

    ```bash theme={null}
    curl -X POST "https://api.mixroute.ai/v1beta/cachedContents" \
      -H "Content-Type: application/json" \
      -H "Authorization: Bearer sk-xxxxxxxxxx" \
      -d '{
        "model": "models/gemini-2.5-pro",
        "displayName": "my-cache",
        "contents": [
          {
            "role": "user",
            "parts": [{"text": "This is a long document content..."}]
          }
        ],
        "ttl": "3600s"
      }'
    ```

    **Use Cache:**

    ```json theme={null}
    {
      "cachedContent": "cachedContents/abc123",
      "contents": [
        {"role": "user", "parts": [{"text": "Based on the above document, summarize the key points"}]}
      ]
    }
    ```
  </Tab>

  <Tab title="Image Generation">
    ### Image Generation

    Generate images using Gemini 2.0 Flash or Imagen models:

    ```json theme={null}
    {
      "contents": [
        {
          "role": "user",
          "parts": [{"text": "Generate an image of a sunset at the beach"}]
        }
      ],
      "generationConfig": {
        "responseModalities": ["TEXT", "IMAGE"]
      }
    }
    ```

    **Imagen Model:**

    ```bash theme={null}
    curl -X POST "https://api.mixroute.ai/v1beta/models/imagen-3.0-generate-002:predict" \
      -H "Content-Type: application/json" \
      -H "Authorization: Bearer sk-xxxxxxxxxx" \
      -d '{
        "instances": [
          {"prompt": "A cute cat in the sunshine"}
        ],
        "parameters": {
          "sampleCount": 1
        }
      }'
    ```
  </Tab>
</Tabs>

## Embedding API

### Single Embedding

```bash theme={null}
curl -X POST "https://api.mixroute.ai/v1beta/models/text-embedding-004:embedContent" \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer sk-xxxxxxxxxx" \
  -d '{
    "content": {
      "parts": [{"text": "This is text to be vectorized"}]
    }
  }'
```

**Response Example:**

```json theme={null}
{
  "embedding": {
    "values": [0.0123, -0.0456, 0.0789, ...]
  }
}
```

### Batch Embedding

```bash theme={null}
curl -X POST "https://api.mixroute.ai/v1beta/models/text-embedding-004:batchEmbedContents" \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer sk-xxxxxxxxxx" \
  -d '{
    "requests": [
      {
        "model": "models/text-embedding-004",
        "content": {"parts": [{"text": "First text"}]}
      },
      {
        "model": "models/text-embedding-004",
        "content": {"parts": [{"text": "Second text"}]}
      }
    ]
  }'
```

**Response Example:**

```json theme={null}
{
  "embeddings": [
    {"values": [0.0123, -0.0456, ...]},
    {"values": [0.0234, -0.0567, ...]}
  ]
}
```

## Response Format

```json theme={null}
{
  "candidates": [
    {
      "content": {
        "parts": [{"text": "Response text"}],
        "role": "model"
      },
      "finishReason": "STOP",
      "safetyRatings": [
        {
          "category": "HARM_CATEGORY_HARASSMENT",
          "probability": "NEGLIGIBLE"
        }
      ]
    }
  ],
  "usageMetadata": {
    "promptTokenCount": 10,
    "candidatesTokenCount": 20,
    "totalTokenCount": 30
  }
}
```

## Error Handling

| HTTP Status | Error Type          | Description                |
| ----------- | ------------------- | -------------------------- |
| 400         | INVALID\_ARGUMENT   | Invalid request parameter  |
| 401         | UNAUTHENTICATED     | Invalid or missing API key |
| 403         | PERMISSION\_DENIED  | No access to this model    |
| 404         | NOT\_FOUND          | Model not found            |
| 429         | RESOURCE\_EXHAUSTED | Rate limit exceeded        |
| 500         | INTERNAL            | Internal server error      |

**Error Response Example:**

```json theme={null}
{
  "error": {
    "code": 400,
    "message": "Invalid value at 'contents[0].parts[0]'",
    "status": "INVALID_ARGUMENT"
  }
}
```

## Comparison with OpenAI Format

| Feature           | Gemini Native                    | OpenAI Compatible            |
| ----------------- | -------------------------------- | ---------------------------- |
| Base URL          | `https://api.mixroute.ai/v1beta` | `https://api.mixroute.ai/v1` |
| Message Structure | `contents[].parts[]`             | `messages[].content`         |
| Role Names        | `user` / `model`                 | `user` / `assistant`         |
| System Prompt     | `systemInstruction`              | `messages[0].role: "system"` |
| Streaming Request | URL param `?alt=sse`             | Body param `stream: true`    |
| Temperature Range | 0-2                              | 0-2                          |
| Function Calling  | `tools[].functionDeclarations`   | `tools[].function`           |
| Search Grounding  | `tools[].googleSearch`           | Not supported                |
| Thinking Mode     | `thinkingConfig`                 | Not supported                |

<RequestExample>
  ```bash cURL theme={null}
  curl --request POST \
    --url 'https://api.mixroute.ai/v1beta/models/gemini-2.5-pro:generateContent' \
    --header 'Authorization: Bearer sk-xxxxxxxxxx' \
    --header 'Content-Type: application/json' \
    --data '{
      "contents": [
        {"role": "user", "parts": [{"text": "Explain artificial intelligence in one sentence"}]}
      ],
      "generationConfig": {
        "temperature": 0.7,
        "maxOutputTokens": 1024
      }
    }'
  ```

  ```python Python theme={null}
  import google.generativeai as genai

  genai.configure(
      api_key="sk-xxxxxxxxxx",
      transport="rest",
      client_options={"api_endpoint": "https://api.mixroute.ai"}
  )

  model = genai.GenerativeModel("gemini-2.5-pro")
  response = model.generate_content("Explain artificial intelligence in one sentence")
  print(response.text)
  ```

  ```javascript JavaScript theme={null}
  import { GoogleGenerativeAI } from "@google/generative-ai";

  const genAI = new GoogleGenerativeAI("sk-xxxxxxxxxx");
  const model = genAI.getGenerativeModel(
    { model: "gemini-2.5-pro" },
    { baseUrl: "https://api.mixroute.ai/v1beta" }
  );

  const result = await model.generateContent("Explain artificial intelligence in one sentence");
  console.log(result.response.text());
  ```

  ```php PHP theme={null}
  <?php
  $client = new GuzzleHttp\Client();
  $response = $client->post('https://api.mixroute.ai/v1beta/models/gemini-2.5-pro:generateContent', [
      'headers' => [
          'Authorization' => 'Bearer sk-xxxxxxxxxx',
          'Content-Type' => 'application/json',
      ],
      'json' => [
          'contents' => [
              ['role' => 'user', 'parts' => [['text' => 'Explain artificial intelligence in one sentence']]]
          ],
          'generationConfig' => [
              'temperature' => 0.7,
              'maxOutputTokens' => 1024
          ]
      ]
  ]);
  echo $response->getBody();
  ```

  ```go Go theme={null}
  package main

  import (
      "bytes"
      "encoding/json"
      "net/http"
  )

  func main() {
      payload := map[string]interface{}{
          "contents": []map[string]interface{}{
              {"role": "user", "parts": []map[string]string{{"text": "Explain artificial intelligence in one sentence"}}},
          },
          "generationConfig": map[string]interface{}{
              "temperature": 0.7,
              "maxOutputTokens": 1024,
          },
      }
      body, _ := json.Marshal(payload)
      req, _ := http.NewRequest("POST", "https://api.mixroute.ai/v1beta/models/gemini-2.5-pro:generateContent", bytes.NewBuffer(body))
      req.Header.Set("Authorization", "Bearer sk-xxxxxxxxxx")
      req.Header.Set("Content-Type", "application/json")
      http.DefaultClient.Do(req)
  }
  ```

  ```java Java theme={null}
  import java.net.http.*;
  import java.net.URI;

  HttpClient client = HttpClient.newHttpClient();
  String json = """
      {
        "contents": [
          {"role": "user", "parts": [{"text": "Explain artificial intelligence in one sentence"}]}
        ],
        "generationConfig": {
          "temperature": 0.7,
          "maxOutputTokens": 1024
        }
      }
      """;
  HttpRequest request = HttpRequest.newBuilder()
      .uri(URI.create("https://api.mixroute.ai/v1beta/models/gemini-2.5-pro:generateContent"))
      .header("Authorization", "Bearer sk-xxxxxxxxxx")
      .header("Content-Type", "application/json")
      .POST(HttpRequest.BodyPublishers.ofString(json))
      .build();
  HttpResponse<String> response = client.send(request, HttpResponse.BodyHandlers.ofString());
  System.out.println(response.body());
  ```

  ```ruby Ruby theme={null}
  require 'net/http'
  require 'json'

  uri = URI('https://api.mixroute.ai/v1beta/models/gemini-2.5-pro:generateContent')
  http = Net::HTTP.new(uri.host, uri.port)
  http.use_ssl = true

  request = Net::HTTP::Post.new(uri)
  request['Authorization'] = 'Bearer sk-xxxxxxxxxx'
  request['Content-Type'] = 'application/json'
  request.body = {
    contents: [
      { role: 'user', parts: [{ text: 'Explain artificial intelligence in one sentence' }] }
    ],
    generationConfig: {
      temperature: 0.7,
      maxOutputTokens: 1024
    }
  }.to_json

  response = http.request(request)
  puts response.body
  ```
</RequestExample>

<ResponseExample>
  ```json Response theme={null}
  {
    "candidates": [
      {
        "content": {
          "parts": [{"text": "Artificial intelligence is a discipline that studies how to make computers simulate and implement human intelligence."}],
          "role": "model"
        },
        "finishReason": "STOP",
        "index": 0,
        "safetyRatings": []
      }
    ],
    "usageMetadata": {
      "promptTokenCount": 10,
      "candidatesTokenCount": 20,
      "totalTokenCount": 30
    },
    "modelVersion": "gemini-2.5-pro"
  }
  ```
</ResponseExample>