Video Inputs

Send video files to compatible models for analysis, description, object detection, and action recognition. AgnicPay supports multiple video formats for comprehensive video understanding tasks.

Overview

Video requests are available via the /v1/chat/completions API with the video_url content type. Videos can be sent as URLs or base64-encoded data URLs.

Video URL support varies by provider. Some providers only support specific URL types (e.g., YouTube links for certain Google models).

Using Video URLs

For publicly accessible videos:

Python

from openai import OpenAI
 
client = OpenAI(
    api_key="agnic_tok_YOUR_TOKEN",
    base_url="https://api.agnic.ai/v1"
)
 
response = client.chat.completions.create(
    model="google/gemini-2.0-flash",
    messages=[
        {
            "role": "user",
            "content": [
                {
                    "type": "text",
                    "text": "Please describe what's happening in this video."
                },
                {
                    "type": "video_url",
                    "video_url": {
                        "url": "https://www.youtube.com/watch?v=dQw4w9WgXcQ"
                    }
                }
            ]
        }
    ]
)
 
print(response.choices[0].message.content)

JavaScript

import OpenAI from 'openai';
 
const client = new OpenAI({
  apiKey: 'agnic_tok_YOUR_TOKEN',
  baseURL: 'https://api.agnic.ai/v1'
});
 
const response = await client.chat.completions.create({
  model: 'google/gemini-2.0-flash',
  messages: [
    {
      role: 'user',
      content: [
        {
          type: 'text',
          text: "Please describe what's happening in this video."
        },
        {
          type: 'video_url',
          video_url: {
            url: 'https://www.youtube.com/watch?v=dQw4w9WgXcQ'
          }
        }
      ]
    }
  ]
});
 
console.log(response.choices[0].message.content);

Using Base64 Encoded Videos

For local video files:

Python

from openai import OpenAI
import base64
 
def encode_video(video_path):
    with open(video_path, "rb") as video_file:
        return base64.b64encode(video_file.read()).decode('utf-8')
 
client = OpenAI(
    api_key="agnic_tok_YOUR_TOKEN",
    base_url="https://api.agnic.ai/v1"
)
 
# Read and encode the video
video_path = "path/to/your/video.mp4"
base64_video = encode_video(video_path)
data_url = f"data:video/mp4;base64,{base64_video}"
 
response = client.chat.completions.create(
    model="google/gemini-2.0-flash",
    messages=[
        {
            "role": "user",
            "content": [
                {
                    "type": "text",
                    "text": "What's happening in this video?"
                },
                {
                    "type": "video_url",
                    "video_url": {
                        "url": data_url
                    }
                }
            ]
        }
    ]
)
 
print(response.choices[0].message.content)

JavaScript

import OpenAI from 'openai';
import fs from 'fs';
 
const client = new OpenAI({
  apiKey: 'agnic_tok_YOUR_TOKEN',
  baseURL: 'https://api.agnic.ai/v1'
});
 
// Read and encode the video
const videoPath = 'path/to/your/video.mp4';
const videoBuffer = fs.readFileSync(videoPath);
const base64Video = videoBuffer.toString('base64');
const dataUrl = `data:video/mp4;base64,${base64Video}`;
 
const response = await client.chat.completions.create({
  model: 'google/gemini-2.0-flash',
  messages: [
    {
      role: 'user',
      content: [
        {
          type: 'text',
          text: "What's happening in this video?"
        },
        {
          type: 'video_url',
          video_url: {
            url: dataUrl
          }
        }
      ]
    }
  ]
});
 
console.log(response.choices[0].message.content);