How can I handle long articles for summarization using the OpenAI API?

Below is some guidance on handling long texts with the API:

Understanding Token Limits

• Token count vs. sending tokens:
  The API automatically tokenizes your input text. Tools or libraries that count tokens are meant to help you estimate whether your prompt might exceed the limit—they don’t imply that you can “send tokens” separately. You must send full text (or chunks of it) instead of raw token counts.

• No concept of a context ID:
  The API endpoints (whether completions or chat) do not require or support a context ID. Any reference to that is likely a misunderstanding or relates to a different context (e.g., certain embedding workflows). For text summarization, you simply send your full prompt or its chunks.

Approaches for Handling Long Articles

Since you sometimes exceed the token limit, common strategies include:

1. Preprocessing and Chunking:

   • Break up your article into smaller parts (you can use a third-party library to split text intelligently, e.g., by paragraphs or sections).
   • Process each chunk separately through the API (e.g., ask for summaries of each chunk).
   • Optionally, combine these summaries into an overall summary in a follow-up API call.

2. Summarize Recursively:

   • First, summarize sections of the text.
   • Then, feed those summaries into another summarization call to produce a final summary.

Using the API (e.g., Chat or Completions Endpoint)

• Chat endpoint:
  Use the chat endpoint (for models like gpt-3.5-turbo) if you want a conversational style. You send messages as whole strings (i.e., each message can be a chunk of the article if needed). For example, in PHP your request might look like this (using a generic HTTP client):

  PHPCopied
  <?php
  $apiKey = 'YOUR_API_KEY';
  $url = 'https://api.openai.com/v1/chat/completions';
  
  $data = [
      'model' => 'gpt-3.5-turbo',
      'messages' => [
          ['role' => 'system', 'content' => 'You are a helpful assistant.'],
          ['role' => 'user', 'content' => 'Summarize this article: [Insert text chunk here]']
      ]
  ];
  
  $headers = [
      "Authorization: Bearer {$apiKey}",
      "Content-Type: application/json"
  ];
  
  $ch = curl_init($url);
  curl_setopt($ch, CURLOPT_POSTFIELDS, json_encode($data));
  curl_setopt($ch, CURLOPT_HTTPHEADER, $headers);
  curl_setopt($ch, CURLOPT_RETURNTRANSFER, true);
  $response = curl_exec($ch);
  curl_close($ch);
  
  echo $response;
  ?>

• Text completions endpoint:
  Similarly, if you use the text completion endpoint, you simply pass the full text or a chunk as the prompt; there is no special parameter to send token counts.

Is There an Official Guide?

Currently, the documentation does not include a guide specifically for sending pieces of text (i.e., chunking text or “streaming” tokens across calls). The official guides and quickstarts focus on making requests with complete prompts. For tasks like summarizing very long articles, you’ll need to implement your own logic in your PHP code to split the content into manageable sections. You can refer to the OpenAI API documentation for details on request structure and best practices.

Summary

• There is no built-in mechanism to “send tokens” or use a context ID with current API endpoints.
• To handle long articles, split them into smaller chunks and process each chunk individually.
• Use the chat endpoint (or text completion endpoint) by sending complete strings in your request.
• No official guide exists for chunking text — you’ll need to create your own preprocessing logic.

I hope this helps you adapt your workflow without exceeding token limits!