Gemini generateContent and streaming via Anyone

Anyone exposes Google Gemini-compatible endpoints at the /v1beta/models/{model} path, matching the format used by the Google AI SDKs and the Gemini REST API. You authenticate with your Anyone API key using the x-goog-api-key header or a key query parameter — no Google credentials needed. Anyone routes the request to whichever upstream channel is configured for the model you specify in the URL path.

Endpoints

Method	Path	Description
`POST`	`/v1beta/models/{model}:generateContent`	Generate a response (non-streaming)
`POST`	`/v1beta/models/{model}:streamGenerateContent`	Generate a response as a stream

The model name is part of the URL path, not the request body. For example, to use gemini-3.1-pro-preview, send a POST to /v1beta/models/gemini-3.1-pro-preview:generateContent.

Authentication

Pass your Anyone API key using either method: Header (recommended):

x-goog-api-key: YOUR_TOKEN

Query parameter:

POST /v1beta/models/gemini-3.1-pro-preview:generateContent?key=YOUR_TOKEN

Request parameters

object[]

required

The conversation history as an array of content objects. Each object has a role and a parts array.

Show content properties

string

The role of the content author. Use "user" for user turns and "model" for model turns. Omit for single-turn requests.

object[]

required

An array of content parts that make up this turn.

Show part properties

string

A text part. Pass this for plain text input or to provide text alongside other modalities.

object

Inline binary data (e.g. an image or audio clip encoded in base64).

Show inlineData properties

string

required

The MIME type of the data, for example "image/jpeg", "audio/mp3", or "video/mp4".

string

required

Base64-encoded bytes.

object

Reference to a file by URI, for example a Google Cloud Storage URI or a Files API URI.

Show fileData properties

string

The MIME type of the file.

string

required

The URI of the file.

object

A function call the model wants to make. Contains name and args.

object

The result of a function call. Contains name and response.

object

A system prompt. Structure is the same as a contents item: an object with a parts array. Only text parts are supported for system instructions.

{
  "systemInstruction": {
    "parts": [{"text": "You are a helpful assistant."}]
  }
}

Also accepted as system_instruction (snake_case).

object

Parameters that control how the model generates output. Also accepted as generation_config.

Show generationConfig properties

number

Sampling temperature. Higher values are more creative; lower values are more deterministic.

number

Nucleus sampling probability mass. Also accepted as top_p.

number

Top-k sampling. Also accepted as top_k.

integer

The maximum number of tokens to generate. Also accepted as max_output_tokens.

integer

Number of candidate responses to generate. Defaults to 1.

string[]

Sequences at which the model stops generating. Also accepted as stop_sequences.

string

The MIME type for the response. Use "application/json" to request JSON output. Also accepted as response_mime_type.

object

A JSON Schema that the response must conform to. Requires responseMimeType to be "application/json". Also accepted as response_schema.

string[]

Output modalities to request, for example ["TEXT"] or ["TEXT", "IMAGE"]. Also accepted as response_modalities.

object

Configuration for extended thinking. Also accepted as thinking_config.

Show thinkingConfig properties

boolean

Whether to include the model’s thoughts in the response. Also accepted as include_thoughts.

integer

Maximum number of tokens to use for thinking. Also accepted as thinking_budget.

string

Reasoning effort level: "low", "medium", or "high". Also accepted as thinking_level.

object[]

Tools the model may use. Supports functionDeclarations, googleSearch, googleSearchRetrieval, codeExecution, and urlContext.

object

Controls how the model selects tools.

Show toolConfig properties

object

Function calling configuration.

Show functionCallingConfig properties

string

Function calling mode: "AUTO", "ANY", or "NONE".

string[]

When mode is "ANY", restricts tool calls to this list of function names.

object[]

Override the default safety filters. Each entry specifies a category and threshold.

Response fields

object[]

An array of generated response candidates.

Show candidate properties

object

The generated content.

Show content properties

string

Always "model" for generated content.

object[]

An array of content parts. Each part has a text field for text output, or functionCall for tool invocations. Parts with thought: true contain the model’s internal reasoning when thinking is enabled.

string

Why the model stopped. Common values: "STOP" (natural end), "MAX_TOKENS" (token limit), "SAFETY" (safety filter), "RECITATION".

integer

The index of this candidate.

object[]

Safety ratings for each harm category.

object

Token usage for the request.

Show usageMetadata properties

integer

Tokens in the input contents.

integer

Tokens in the generated candidates.

integer

Total tokens used.

integer

Tokens used for thinking, when extended thinking is enabled.

object

Feedback about the prompt, including safety ratings and any block reason if the prompt was blocked.

Examples

Non-streaming
Streaming
Multi-turn

curl "https://api.anyone.ai/v1beta/models/gemini-3.1-pro-preview:generateContent" \
  -H "x-goog-api-key: YOUR_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{
    "contents": [
      {
        "role": "user",
        "parts": [{"text": "Explain the difference between RAM and ROM."}]
      }
    ],
    "generationConfig": {
      "temperature": 0.7,
      "maxOutputTokens": 512
    }
  }'

import google.generativeai as genai

genai.configure(
    api_key="YOUR_TOKEN",
    client_options={"api_endpoint": "https://api.anyone.ai"},
)

model = genai.GenerativeModel("gemini-3.1-pro-preview")
response = model.generate_content("Explain the difference between RAM and ROM.")

print(response.text)

Example response:

{
  "candidates": [
    {
      "content": {
        "role": "model",
        "parts": [
          {
            "text": "RAM (Random Access Memory) is volatile memory used for temporary storage while your computer is running..."
          }
        ]
      },
      "finishReason": "STOP",
      "index": 0,
      "safetyRatings": []
    }
  ],
  "usageMetadata": {
    "promptTokenCount": 11,
    "candidatesTokenCount": 142,
    "totalTokenCount": 153
  }
}

cURL

curl "https://api.anyone.ai/v1beta/models/gemini-3.1-pro-preview:streamGenerateContent" \
  -H "x-goog-api-key: YOUR_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{
    "contents": [
      {"role": "user", "parts": [{"text": "Count from 1 to 5."}]}
    ]
  }'

The server returns a newline-delimited stream of JSON objects, each representing a partial response chunk. Each chunk has the same structure as a non-streaming response, with partial candidates[].content.parts[].text.

cURL

curl "https://api.anyone.ai/v1beta/models/gemini-3.1-pro-preview:generateContent" \
  -H "x-goog-api-key: YOUR_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{
    "systemInstruction": {
      "parts": [{"text": "You are a geography expert."}]
    },
    "contents": [
      {"role": "user", "parts": [{"text": "What is the longest river in Africa?"}]},
      {"role": "model", "parts": [{"text": "The Nile is the longest river in Africa."}]},
      {"role": "user", "parts": [{"text": "How long is it in kilometers?"}]}
    ]
  }'

Thinking models

Anyone supports Gemini thinking models, which perform additional reasoning before generating a response. You have three ways to enable thinking: 1. Thinking model suffix — append -thinking to any supported model name:

POST /v1beta/models/gemini-3.1-pro-preview-thinking:generateContent
POST /v1beta/models/gemini-3.1-pro-preview-thinking:generateContent

2. Effort suffix — append -low, -medium, or -high for fine-grained control:

POST /v1beta/models/gemini-3.1-pro-preview-high:generateContent

3. thinkingConfig in generationConfig — pass the configuration explicitly:

{
  "contents": [...],
  "generationConfig": {
    "thinkingConfig": {
      "includeThoughts": true,
      "thinkingBudget": 8192
    }
  }
}

When thinking is active, parts with "thought": true in the response contain the model’s reasoning. These parts are not shown to end users by default — your application decides whether to display them.

If you only need text output and do not want to process thinking parts, set includeThoughts: false and let the model reason internally without including those tokens in the response body.

Overview

Chat & Completions

Media & Multimodal

Other Endpoints

Gemini generateContent and streaming via Anyone

Endpoints

Authentication

Request parameters

Response fields

Examples

Thinking models

​Endpoints

​Authentication

​Request parameters

​Response fields

​Examples

​Thinking models

Endpoints

Authentication

Request parameters

Response fields

Examples

Thinking models