How does it work ?
Important: these capabilities are available only on Chat Model 2.Preparing photo usage
For Chat Model 2 to understand photos, DumGum must first analyze the available images. To enable this, use thereplyParameters.vision parameter.
See parameter API reference.
Through this parameter, you define which images should be analyzed:
userProfilePictureAnalysis– analyzes the User’s main profile photopersonaProfilePictureAnalysis– analyzes the Persona’s main profile photosharedPicturesAnalysis– analyzes photos shared by the User so the AI can react to their content
Why is profile photo analysis useful ?
When we analyze profile photos, we examine both the content and the physical characteristics of the person. Most importantly, we memorize the person’s face. This allows the AI to understand whether a photo shared by the User is of themselves, of the Persona, or of someone else. Again, we strongly advise enabling this feature if you moderate your users’ profile pictures. It substantially improves response quality.How does shared photo analysis work ?
Basic principle
WhensharedPictures is enabled, our model analyzes the photos shared by Users and can then react to their content in a realistic and coherent way.
Error feedback
For each image, our platform performs a content analysis. If we detect problematic content, your incoming webhook will receive an event of typechat.image.rejected.
We recommend handling these events through your moderation service.
Possible moderation reasons:
VIOLENT_CONTENTSELF_HARMILLEGAL_CONTENT
How much does it cost ?
Basic principles
The base price is €0.015 per analyzed photo. To avoid unnecessary costs, each photo is analyzed only once per unique URL. For example, a Persona’s main profile picture is analyzed only once and then reused across all conversations without additional charges.Technical details
Images are identified by their URL, and our system respects the HTTPCache-Control headers to determine whether an image needs to be analyzed again.
When a cached image expires and is used again, we compare its fingerprint (SHA-256) with the version stored in our database.
If identical, no new analysis is performed and the cache is refreshed.
If different, a new analysis is triggered.
Technical Guide
Step #1: Using the V2 model
To use the V2 model, you need to use thereplyParameters.chatModel parameter.
For its value, choose chat-2-smart or chat-2-pro depending on the version you are using.
Step #2: Enabling vision
You must enable vision support through thereplyParameters.vision parameter as follows:
Step #3: Updating chat history
In the “Chat History” API endpoint that you integrate on your side, you must return a new message attribute,pictureUrls, which should contain the URLs of all images associated with the message.
The model will automatically analyze this image (provided the sharedPictures option in the vision settings is set to true) and will be able to respond accordingly.
Note that a message may contain both images (pictureUrls) and text (text attribute), or simply one/multiple image(s).