I’m looking to add an image to my conversation with the OpenAI assistant. I want to ensure that this image is only analyzed for vision-related tasks and not used for the code_interpreter or file_search features. I’m having difficulty with this because it seems like the assistant automatically defaults to other functions when I upload a file. Can someone guide me on how to set this up correctly? Are there any specific options I need to use when I upload the image to ensure it’s processed strictly for vision analysis?
Manual approaches work but they’re a pain to maintain once you scale up. I’ve hit this same issue across several projects - automating the entire vision workflow cuts out all the headaches.
Build an automation that runs your image processing pipeline. Set up a flow that grabs your image, converts it to base64, structures the API call with proper vision parameters, and hits OpenAI directly. No file endpoints needed.
Best part? Configure it once with the right settings - disable tools, format messages correctly, vision-only processing. After that, just trigger the flow instead of manually building API calls every time.
I built something like this for our team’s UI screenshot analysis. The automation chews through dozens of images daily while everyone stays hands-off. No tool conflicts or formatting headaches.
Latenode makes building these workflows dead simple. Check it out: https://latenode.com
Don’t upload images to OpenAI’s servers if you want vision-only analysis. Encode your image as base64 and stick it directly in the message content instead of using the file upload endpoint. This stops the assistant from treating it like a document that code_interpreter or file_search might grab. Structure your API call with the image_url type and pass the base64 data using the proper format: data:image/jpeg;base64,your_encoded_string. The image gets processed purely through vision this way - no file tools triggered. I’ve used this method tons of times and it works every time.
Here’s what worked for me: use the messages parameter when calling the API. Don’t bother with the files endpoint - just pass the image directly in the user message with type set to image_url. Make sure your assistant has zero tools enabled. Create it with an empty tools array or skip the tools parameter completely. This stops any confusion about which feature handles your image. The big difference from other suggestions? Be explicit about your assistant’s capabilities upfront instead of trying to override them later. I get way more predictable results this way than disabling tools after I’ve already created the assistant.
You’re probably structuring the request wrong. With the Assistants API, vision is tied to your model choice, not tool setup. Use gpt-4-vision-preview or gpt-4o - they handle images natively through the messages array. No tools needed. I had the same issue until I stopped overthinking it. Create your assistant with zero tools, then send images through the content parameter using image_url type. The model automatically processes vision requests when it sees image content - totally separate from file handling. This setup’s been bulletproof for my document analysis projects.
you can also disable the code_interpreter and file_search tools when you create the thread or assistant. just set them to false in your api call - this stops the vision model from automatically trying to use them. works great when i want pure image analysis without background processing getting in the way.
just make sure you’re using the right content type in your message. I had the same issue - was mixing up file uploads with direct image passing. put the image in message content as image_url and skip the files parameter completely. that’ll route it straight to vision processing instead of other tools.