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Adapt it to the work

Handle images without hidden degradation

Use image context when the chosen model supports it and make incompatibility visible when it does not.

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Accept image input on vision-capable models and disclose explicitly when the selected model cannot see it.

What this changes for your team.

Image attachments can enter a turn for models whose route declares vision support. When the pinned model lacks that support, Yekar.AI discloses the mismatch rather than silently pretending the image was understood.

How it works in practice.

  1. 01

    Attach a supported image to the session message.

  2. 02

    Check the pinned model route's declared vision support while planning the turn.

  3. 03

    Send the image to a compatible route or return an explicit limitation disclosure for an incompatible one.

What you can plan around.

The behaviour you can design against, stated concretely.

Vision support is model-catalog metadata checked before provider request assembly.

The pinned model is not silently substituted merely to gain image support.

Provider file limits, formats, and content handling still apply to compatible routes.

Complete the operating path

View all capabilities
Adapt it to the workTest changes against real past cases

Review a changed agent beside representative recorded runs before trusting the new release.

Adapt it to the workKeep long-running agents within context limits

Control how much conversation, knowledge, memory, and tool material the turn planner tries to fit.

Build the agentBuild agents with AI

Turn a working brief into a reviewable agent draft without starting from a blank setup.

Bring one real process

See how Yekar.AI fits the way you work.

Start with a job your team already owns, plus the tools and decisions around it.

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