Beyond Chat: Processing Images, PDFs, and Documents with the OpenAI Adapter in Oracle Integration… Oracle introduced the OpenAI Adapter in Oracle Integration Cloud (OIC), enabling native file upload and processing of images, PDFs, and documents without custom REST calls. The adapter supports operations like Upload File and Responses API, allowing users to extract structured data from invoices and documents. This pattern simplifies AI-powered integrations by reusing uploaded files for multiple analyses. When Oracle introduced the OpenAI Adapter in Oracle Integration Cloud OIC , most of the examples I came across focused on text generation and chatbot-style interactions. Naturally, I assumed that if I wanted to process files such as images, PDFs, or Word documents, I would probably need to build custom REST integrations and call the OpenAI APIs directly. While exploring the adapter, I noticed a few operations related to file management. That got me curious. Can the OpenAI Adapter upload files ? Can those files be processed later using a File ID? Can we extract structured data from invoices , images , or PDF documents without building custom REST calls? To answer these questions, I decided to build a small proof of concept. The results were quite interesting. Using only the native OpenAI Adapter, I was able to: In this article, I’ll walk through the approach, the architecture, and a few practical use cases that I tested while building the POC. By the end, you’ll have a reusable pattern that can be applied to invoice extraction, document processing, content analysis, and many other AI-powered integration scenarios. While building the POC, I decided to separate the solution into two integrations. The first integration is responsible for uploading a file to OpenAI and obtaining a File ID. The second integration uses that File ID together with a prompt to process the document and return a structured response. I found this approach cleaner because the uploaded file becomes a reusable asset. The same file can be analyzed multiple times using different prompts without uploading it again. The first integration accepts a file and uploads it using the OpenAI Adapter’s Upload File operation. Supported examples include: The adapter returns a unique File ID similar to: file-xxxxxxxxxxxxxxxx This File ID can then be stored, logged, or passed to another integration for processing. The second integration receives: It then invokes the OpenAI Adapter using the Responses operation. Depending on the type of document and the prompt provided, OpenAI can: The response can be consumed directly within OIC and mapped to downstream systems. The overall process looks like this: Document Image/PDF/DOCX | v+------------------+| Upload File || OpenAI Adapter |+------------------+ | v File ID | v+------------------+| Responses API || OpenAI Adapter |+------------------+ | v Structured Output JSON One thing I particularly liked about this pattern is that it relies entirely on the native OpenAI Adapter. There are no custom REST calls, no manual API payload construction, and no need to manage Base64-encoded content. The first integration is responsible for uploading a document to OpenAI and obtaining a File ID that can be reused later. In my case, I tested the following file types: Start by creating a connection using the OpenAI Adapter. Provide: Once the connection is successfully tested, it can be used within your integration. Create an App-Driven Orchestration. 2.1 Add Trigger Rest Adapter to Accept File as input with : - Select the multipart attachment processing options 2.2 Add the OpenAI Adapter and select the following operation : Upload File This operation allows OIC to upload a file directly to OpenAI without invoking the REST API manually. The Upload File operation expects two important pieces of information: The purpose determines how the uploaded file will be used. For image processing: vision For document processing PDF, DOCX, TXT, etc. : user data Map the incoming attachment or file reference to the adapter’s File element. Example mapping: RequestWrapper ├── Purpose └── File └── streamReference The adapter handles the upload process and stores the file within OpenAI. After activation, invoke the integration with a sample document. If the upload succeeds, the response contains a File ID. Example: file-3UoRxBRyqV7pJRgPC4WSgi This File ID becomes the bridge between the upload step and the document processing step. While testing the Upload File operation, I ran into an issue that took a little time to troubleshoot. Some uploads failed when the file name contained spaces or special characters. For example: WhatsApp Image 2026-06-05 at 7.25.23 PM.jpeg After renaming the file to a simpler format without spaces or special characters, the upload completed successfully. Example: invoice 20260605.jpeg If you encounter unexpected upload failures, one of the first things to check is the file name. Although this may vary depending on the adapter version and environment, using clean file names is a good practice and helped avoid issues during testing. Initially, I assumed I would need to send Base64 content to OpenAI every time I wanted to analyze a document. The File ID approach is much cleaner. Once the document is uploaded: This makes the pattern both efficient and easy to maintain. At this stage, we have successfully uploaded a document and obtained a File ID. The next step is where things become interesting: using that File ID to extract meaningful information from the document. “This was the point where I realized the adapter was capable of much more than chat-based interactions. The File ID effectively turns the uploaded document into a reusable asset that can be processed multiple times.” Now that the document has been uploaded and we have a File ID, the next step is to ask OpenAI to process the file. This is where the Responses operation comes into play. The Responses API allows us to provide: and receive a structured response. Create a second integration. This integration accepts: FileId — Contains the OpenAI File ID returned by the Upload File integration. FileType — Determines the type of file being processed. For images, I passed input image, while for PDFs and Word documents, I passed input file. instruction — Contains the prompt or instructions that should be sent to the model. Add the OpenAI Adapter and select: Responses The request consists of two content elements: The first content item contains the instructions we want the model to follow. Example: Extract invoice information from the attached document.Return valid JSON only.Include:- Invoice Number- Date- Items- Tax- Total Amount In the mapper: Type = input textText =