Dikaya Flash: a practical image-review workflow

Minimal API example

Illustrative Python, not an executed model response. The key comes from the environment and automatic retries are disabled. A lost connection can leave both outcome and cost unknown: do not retry blindly.

import os
from openai import OpenAI

client = OpenAI(
    base_url="https://dikaya.cc/v1",
    api_key=os.environ["DIKAYA_API_KEY"],
    max_retries=0,
)
response = client.chat.completions.create(
    model="seller-flash",
    max_tokens=512,
    messages=[{"role": "user", "content": "Create a checklist for my task. Separate source facts from assumptions."}],
)
print(response.choices[0].message.content)

Choose a visual question with a checkable answer

Consider a support team documenting an application settings screen. The useful question is not whether the interface looks professional. It is whether the screenshot shows the expected account name, an enabled notification control and an error message after saving. These observations can be checked against the image. They do not establish that the underlying account was updated, that an email arrived or that the application is accessible to every visitor.

Write the acceptance checklist before attaching the screenshot. Give controls human-readable names and explain which state you expect. If a checkbox is too small to inspect, ask for an uncertain finding rather than a guess. The public foundation of Dikaya Flash is unspecified, so another product’s visual reasoning claims are not evidence here. Evaluate the response against your own visible material instead of assuming capabilities from the Flash name.

Prepare screenshots that preserve the evidence

Capture the complete panel first, then crop the specific control or error. Keep a small margin around a crop so its location remains understandable. Label the images Overview and Save error in your message, and describe whether they represent the same moment. Two screenshots from different sessions can appear contradictory unless that difference is stated. Remove irrelevant private information before uploading; the model does not need unrelated account details to inspect a button.

Paid browser attachments accept supported, validated PNG, JPEG and WebP images within the current upload limits. This is not a promise to open every design file or document format. Check the image locally at normal size: if you cannot read a label, requesting certainty from the model will not restore it. For API requests, follow Dikaya’s documented image format rather than assuming that every media extension from another service is supported.

Ask for findings you can verify individually

A compact finding should contain the checklist item, image label, approximate location, observation and uncertainty. For example, request that the model distinguish a disabled control from an absent control. Do not ask it to infer server permissions solely from a grey appearance. A screen can display stale data or a temporary loading state, and a screenshot cannot reveal what a click would do. Those questions need a separate application check.

After receiving the response, inspect each claimed label and state yourself. Record corrections next to the original finding instead of replacing the source image with the model’s description. Ask which checklist items could not be assessed and why. An explicit unresolved item is more useful than an unearned pass. Keep any quoted error text literal, including punctuation when legible, and mark unreadable characters rather than allowing plausible autocomplete to change the message.

Make the next turn a targeted inspection

If the uncertain finding concerns a toggle, submit a closer crop of that toggle and repeat the relevant checklist item. Avoid requesting a complete new review when only one detail changed. If you compare before and after screenshots, name their order explicitly and ask for visible differences only. A changed success banner can support an observation about the interface; it does not by itself prove a durable database write.

A model context window is not the same as the browser’s transmitted conversation. Stored messages may exceed the bounded history assembled for a new request. Include the important label and expected state in the current turn so an omitted earlier instruction does not silently change the task. Output limits are separate again: a long image discussion does not entitle the response to unlimited length. Prioritize the unresolved checklist items when requesting a shorter result.

Control the request rather than hiding retries

Use seller-flash explicitly in an API integration and supply an output cap suitable for the finding list. This branded tier does not declare low, high and max effort settings; do not copy them from GLM Flash examples. The OpenAI Python SDK supports a custom base URL and max_retries=0. Those documented client mechanics help make attempts deliberate, but they say nothing about Dikaya Flash image accuracy or present serving availability.

Treat a returned HTTP rejection differently from a connection failure with no reliable outcome. MDN documents that Fetch can return an HTTP error response without rejecting the promise, while network failures reject it. Neither a disconnected tab nor an aborted read proves that processing or accounting never happened. Check available request state and usage before deciding on another attempt. Do not assume a public API idempotency contract merely because you attach your own local request label.

Run a small, deliberate review before relying on it

Build a small personal check set containing a readable screen, a blurred control and a screenshot with a deliberately missing element. Write the expected observations first. If you choose to send paid requests, compare unsupported findings and omissions, not just polished wording. This exercise can reveal weaknesses in your capture process and prompt. It is not a general model ranking, and this article has not run those requests or generated example model answers.

The article handoff prepares a draft rather than sending it. Account permissions determine whether Flash can be selected; the current demo uses Pro 2, with legacy Flash conditions preserved separately. A stored draft can take precedence over the article text. Inspect the selector, attachments and question before sending. When current external information is needed, the paid browser’s explicit search is a separate action, not an internet capability implied by the screenshot or by a public API model name.

Questions and answers

Is Dikaya Flash the same as GLM 5.3 Flash?

No. Dikaya Flash uses seller-flash, while GLM 5.3 Flash uses seller-glm-5-3-flash. They are separate catalogue identities with different image paths. This article concerns native image support in Dikaya Flash, not a claim that all models called Flash share a foundation, measured speed or interchangeable request settings.

Can a screenshot prove that a setting was saved?

A screenshot can show a visible state or confirmation message, but it cannot independently prove a durable server-side change. Ask the model to describe what is visible, then verify the saved setting through the application’s normal checks. Keep that distinction in the report instead of turning an interface observation into a backend guarantee.

Does native image support mean there is no image cost?

No. Native means seller-flash processes the image without the separate text-description bridge used for other models. The request remains subject to the applicable rates, reservation rules and account permissions. Consult current first-party conditions rather than treating a short text quote as the cost of an image request.

Should I immediately resend after a stream disconnects?

Not automatically. The disconnect may leave the processing and accounting outcome unknown. Check the available run state, history and usage first, preserving the original image and prompt. A fresh submission can be another request; disabling SDK retries helps avoid hidden repetitions but does not resolve uncertainty about the first attempt.

Sources

AI-assisted editorial material. Examples are illustrative, not captured model responses or comparative tests. External sources do not replace the service terms.

• Dikaya documentation: requests and supported images
  dikaya.cc
• Dikaya model catalogue and public identities
  dikaya.cc
• OpenAI Python SDK: retry configuration
  github.com
• MDN: using Fetch and checking HTTP responses
  developer.mozilla.org