Video Input

Requesty supports sending video to AI models that accept video input, such as Google Gemini models. Videos are sent through the standard Chat Completions API using the input_file content type — the same format used for PDF support.

Browse supported models in the Requesty Console. Look for models with input_video pricing — currently this is primarily Gemini models (google/... and vertex/google/...).

How It Works

Video is sent as part of the message content, either as a public URL or as base64-encoded data. Requesty translates the request into the provider’s native format — for Gemini, a video URL becomes a fileData part and base64 data becomes an inlineData part.

Using a Video URL

Provide a public http/https URL via file_url. For Gemini models, YouTube URLs are also supported.

curl https://router.requesty.ai/v1/chat/completions \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer YOUR_REQUESTY_API_KEY" \
  -d '{
    "model": "google/gemini-2.5-flash",
    "messages": [
      {
        "role": "user",
        "content": [
          {
            "type": "text",
            "text": "Describe what happens in this video"
          },
          {
            "type": "input_file",
            "filename": "video.mp4",
            "mime_type": "video/mp4",
            "file_url": "https://example.com/video.mp4"
          }
        ]
      }
    ]
  }'

mime_type is required when the URL has no recognizable file extension (for example, a YouTube URL or a signed URL without .mp4).

Using Base64-Encoded Video

For smaller videos, embed the content directly as a data URL in file_data:

curl https://router.requesty.ai/v1/chat/completions \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer YOUR_REQUESTY_API_KEY" \
  -d '{
    "model": "google/gemini-2.5-flash",
    "messages": [
      {
        "role": "user",
        "content": [
          {
            "type": "text",
            "text": "Summarize this video"
          },
          {
            "type": "input_file",
            "filename": "video.mp4",
            "file_data": "data:video/mp4;base64,AAAAFGZ0eXBpc29t..."
          }
        ]
      }
    ]
  }'

Analyzing a Segment

Use start_offset and end_offset to analyze only part of a video. Values are durations like "0s", "15s", or "1m30s".

{
  "type": "input_file",
  "filename": "video.mp4",
  "mime_type": "video/mp4",
  "file_url": "https://example.com/video.mp4",
  "start_offset": "0s",
  "end_offset": "15s"
}

Parameters

type: Must be "input_file"
filename: The name of the video file (e.g., "video.mp4")
mime_type: The MIME type of the video (e.g., "video/mp4"). Required when the URL has no recognizable file extension
file_url: Public URL of the video (http/https only)
file_data: Base64-encoded video content as a data URL (e.g., data:video/mp4;base64,...)
start_offset: Optional start of the segment to analyze (e.g., "10s")
end_offset: Optional end of the segment to analyze (e.g., "25s")

Provide either file_url or file_data, not both.

Python Example

import base64
from openai import OpenAI

client = OpenAI(
    api_key="YOUR_REQUESTY_API_KEY",
    base_url="https://router.requesty.ai/v1",
)

# Option 1: Using a video URL
response = client.chat.completions.create(
    model="google/gemini-2.5-flash",
    messages=[
        {
            "role": "user",
            "content": [
                {
                    "type": "text",
                    "text": "Describe what happens in this video"
                },
                {
                    "type": "input_file",
                    "filename": "video.mp4",
                    "mime_type": "video/mp4",
                    "file_url": "https://example.com/video.mp4"
                }
            ]
        }
    ]
)

print(response.choices[0].message.content)

# Option 2: Using base64-encoded video from a file
with open("video.mp4", "rb") as video_file:
    video_data = base64.b64encode(video_file.read()).decode('utf-8')

response = client.chat.completions.create(
    model="google/gemini-2.5-flash",
    messages=[
        {
            "role": "user",
            "content": [
                {
                    "type": "text",
                    "text": "Summarize this video"
                },
                {
                    "type": "input_file",
                    "filename": "video.mp4",
                    "file_data": f"data:video/mp4;base64,{video_data}"
                }
            ]
        }
    ]
)

print(response.choices[0].message.content)

JavaScript/TypeScript Example

import OpenAI from 'openai';
import fs from 'fs';

const client = new OpenAI({
  apiKey: 'YOUR_REQUESTY_API_KEY',
  baseURL: 'https://router.requesty.ai/v1',
});

// Option 1: Using a video URL
const response = await client.chat.completions.create({
  model: 'google/gemini-2.5-flash',
  messages: [
    {
      role: 'user',
      content: [
        {
          type: 'text',
          text: 'Describe what happens in this video'
        },
        {
          type: 'input_file',
          filename: 'video.mp4',
          mime_type: 'video/mp4',
          file_url: 'https://example.com/video.mp4'
        }
      ]
    }
  ]
});

console.log(response.choices[0].message.content);

// Option 2: Using base64-encoded video from a file
const videoData = fs.readFileSync('video.mp4').toString('base64');

const b64Response = await client.chat.completions.create({
  model: 'google/gemini-2.5-flash',
  messages: [
    {
      role: 'user',
      content: [
        {
          type: 'text',
          text: 'Summarize this video'
        },
        {
          type: 'input_file',
          filename: 'video.mp4',
          file_data: `data:video/mp4;base64,${videoData}`
        }
      ]
    }
  ]
});

console.log(b64Response.choices[0].message.content);

Pricing

Video input is billed per token according to the model’s input_video price, shown in the Model Library and returned by the /v1/models endpoint.

Limitations

Video input is only supported by models with video capability (primarily Gemini). Sending video to other models will result in an error.
file_url must be a public http or https URL — the provider fetches it directly.
Base64 video counts toward the request size limit, so prefer file_url for larger files.

Getting Started

LLM Gateway

Model Capabilities

Analytics & Monitoring

Access Control

Organization

MCP Gateway

How It Works

Using a Video URL

Using Base64-Encoded Video

Analyzing a Segment

Parameters

Python Example

JavaScript/TypeScript Example

Pricing

Limitations

​How It Works

​Using a Video URL

​Using Base64-Encoded Video

​Analyzing a Segment

​Parameters

​Python Example

​JavaScript/TypeScript Example

​Pricing

​Limitations

How It Works

Using a Video URL

Using Base64-Encoded Video

Analyzing a Segment

Parameters

Python Example

JavaScript/TypeScript Example

Pricing

Limitations