PDF Inputs

Siraya Model Router supports PDF processing through the /v1/chat/completions API. PDFs can be sent as direct URLs or base64-encoded data URLs in the messages array, via the file content type.

Sending PDFs

Using PDF URLs

PythonTypeScript

import requests
import json

url = "https://llm.siraya.ai/v1/chat/completions"
headers = {
    "Authorization": f"Bearer <API_KEY>",
    "Content-Type": "application/json"
}

messages = [
    {
        "role": "user",
        "content": [
            {
                "type": "text",
                "text": "Summarize this document."
            },
            {
                "type": "file",
                "file": {
                    "file_data": "https://example.com/document.pdf"
                }
            }
        ]
    }
]

payload = {
    "model": "claude-sonnet-4.5",
    "messages": messages
}

response = requests.post(url, headers=headers, json=payload)
print(response.json()["choices"][0]["message"]["content"])

const response = await fetch('https://llm.siraya.ai/v1/chat/completions', {
  method: 'POST',
  headers: {
    Authorization: `Bearer <API_KEY>`,
    'Content-Type': 'application/json',
  },
  body: JSON.stringify({
    model: 'claude-sonnet-4.5',
    messages: [
      {
        role: 'user',
        content: [
          { type: 'text', text: 'Summarize this document.' },
          { type: 'file', file: { file_data: 'https://example.com/document.pdf' } },
        ],
      },
    ],
  }),
});

const data = await response.json();
console.log(data);

Using Base64 Encoded PDFs

For locally stored PDFs, encode them as base64 data URLs:

Python

import requests
import json
import base64

def encode_pdf_to_base64(pdf_path):
    with open(pdf_path, "rb") as pdf_file:
        return base64.b64encode(pdf_file.read()).decode('utf-8')

url = "https://llm.siraya.ai/v1/chat/completions"
headers = {
    "Authorization": f"Bearer <API_KEY>",
    "Content-Type": "application/json"
}

pdf_path = "path/to/your/document.pdf"
base64_pdf = encode_pdf_to_base64(pdf_path)
data_url = f"data:application/pdf;base64,{base64_pdf}"

messages = [
    {
        "role": "user",
        "content": [
            {
                "type": "text",
                "text": "What are the key points in this document?"
            },
            {
                "type": "file",
                "file": {
                    "file_data": data_url
                }
            }
        ]
    }
]

payload = {
    "model": "claude-sonnet-4.5",
    "messages": messages
}

response = requests.post(url, headers=headers, json=payload)
print(response.json()["choices"][0]["message"]["content"])

Supported Document Formats

Provider	Supported Formats
Bedrock	pdf, csv, doc, docx, xls, xlsx, html, txt, md
Vertex AI	pdf, csv, txt, html, md
OpenAI	Passes through as-is