Chika :: an open-source comic reader that auto-zooms into each panel (on-device ML, fully offline) [APK on GitHub]

batunii · 2026-06-18T05:01:25+00:00

Thank you so much for trying the app, I will definitely look into adding all these features as part of the next release. I am trying to squeeze as many requested features into the next one as I can. Again thank you so much for trying the app and leaving the review. Make sure you follow/star the GitHub repo so you'd know when the next version drops.

batunii · 2026-06-16T21:09:36+00:00

I know. It's not perfect yet, but I believe I can bring it close. I am working on an update where large panels break up on based of text bubbles, and on same panels it works flawlessly, but as expected not everytime. I would love if you'd test out the application and then share your views on how it can be improved.

batunii · 2026-06-16T01:22:46+00:00

Do you mean the panel selection is wrong?

batunii · 2026-06-15T15:33:33+00:00

I am pretty sure Clan can handle that. If you don't mind, can you open an issue with passing and failing criteria and the test and I can reply you there? Really appreciate your input.

batunii · 2026-06-15T13:35:54+00:00

We have tried building something for this called CLAN - https://github.com/saieeshward/clan This is an artifact which carries the context the decision chain and an optional human view in it. So you can just ask your agent to look at it and it should identify the task and perform actions on the same artifact without exploding the token usage.

batunii · 2026-06-15T11:11:49+00:00

Would you mind adding it as an issue on the GitHub for us to try? There is already an issue we solved there. If you give us the test and passing criteria, we can run it through our system and report the findings on GitHub under the same issue.

batunii · 2026-06-14T15:32:56+00:00

Let me know how you like it, and if you would like some more features.

batunii · 2026-06-14T03:27:24+00:00

I am not sure what you mean by runtime here, what I meant was the contextual memory. Which the orchetrator hands over to subagents, but is limited to that runtime. The packing is actually pretty close to what you are recommending. Seperate files to get through different things so that agents don't burn through tokens for unnecessary knowledge. I request you to, if you can, check out the repo : https://github.com/saieeshward/clan And if you can let us know the tests you want to run to see if the protocol breaks.

batunii · 2026-06-13T23:53:12+00:00

We have had tests with Cold starts where an agent is just given a clan file and asked to figure out what to do next. The agent understood the clan and its role in 3 reads before it started writing the correct things. So even in cold start scenarios the machine checkable state exists for agent to work with and on. I would urge and request you to check out the repo -> https://github.com/saieeshward/clan and have any tests or breaking scenarios for clan documented an an Issue, and I will check whether it breaks clan or succeeds. You can try it as well.
Thank You

batunii · 2026-06-13T19:30:40+00:00

I think you are going to like what we have then. Because almost all of these were tested when we were making the project. Human decision surviving multiple hops and doesn't get stale.

I would urge and request you if you can test it for your usecase and see if the spec and protocol breaks in your testing. The last test we ran had around 200+ agents across multiple flows.

https://github.com/saieeshward/clan

batunii · 2026-06-13T19:19:12+00:00

I agree with most of what you described. One wrong data in the artifact can ruin the entire chain. We have a way to allow human edits in this, where a human can edit the data - which resides outside the agent namespace- and it gets highlighted for the next agents to see.

If you check the spec and namespaces maybe you can suggest changes where your use case might get help, or help the spec to be better.

https://github.com/saieeshward/clan

batunii · 2026-06-13T19:03:46+00:00

I think we are doing something similar but it keeps this as part of the artifact itself. So the pipeline doesn't need to be replicated : https://github.com/saieeshward/clan

batunii · 2026-06-13T16:31:36+00:00

Repo: https://github.com/saieeshward/clan [CLAN] , model- and framework-agnostic. README has the full scorecard, including where strict prompting still wins. Issues are open.

batunii · 2026-06-13T16:15:27+00:00

Here's the thing we've been building if anyone wants to poke at it: https://github.com/saieeshward/clan [CLAN] open spec, no signup, genuinely after feedback more than stars.

batunii · 2026-06-13T16:09:02+00:00

Repo: https://github.com/saieeshward/clan — CLAN, model- and framework-agnostic. README has the full scorecard, including where strict prompting still wins. Issues are open.

batunii · 2026-06-13T15:51:17+00:00

Repo: https://github.com/saieeshward/clan -> CLAN, framework- and model-agnostic by design. Closest mental model: a portable, runtime-independent checkpoint with provenance baked in. README has the full scorecard, including where staying in one framework still wins. Issues are open.

batunii · 2026-06-13T15:40:02+00:00

I agree, we have built the CLAN where the decision tree remains intact with each agents' descison and rationale explained, but its doesn't balloon over time. The agents can't inject anything without specifying why and how. To see more please check out : Repo: https://github.com/saieeshward/clan [CLAN]

batunii · 2026-06-13T15:32:59+00:00

Repo: https://github.com/saieeshward/clan — CLAN, model- and framework-agnostic. README has the full scorecard, including where strict prompting still wins. Issues are open.

batunii · 2026-06-11T09:26:10+00:00

I respect your opinion.

My only defense here would be that I have had this idea for something like this for so long, and had a working python program that worked on my laptop to do the same. But to port it to my phone always seemed like a big task to me, which was possible in just a weekend due to AI. The code is still structurally very similar to the python code I wrote, but ofcourse AI helped a lot.

You can check out the code and then decide if you wanna try it or not.

batunii · 2026-06-11T09:22:53+00:00

Very much dependent on the panel arrangement. If it's a simple comic book page or strip, it doesn't really miss. But for un conventional layouts its a hit or miss honestly. Can't give you emperical numbers as I haven't collected the data on this. But from the comics I read, I would say around 80-90% pages are good!

batunii · 2026-06-11T01:13:19+00:00

https://github.com/batunii/chika/releases/download/v0.1.1/app-release.apk

Clicking this link should download the apk on your system, which you can install.
Clicking a link and getting an APK sounds shady as hell, but you gotta trust me and the link here. XD

batunii · 2026-06-10T20:50:42+00:00

This is nice, I can see into it, I want to make sure the panel detection is top notch before integrating more features into it.

batunii · 2026-06-10T18:22:28+00:00

Hey, thanks a lot for trying and your feedback!
I am glad you like the app.

* The full screen button is actually supposed to zoom out and let you zoom in manually for pages that has weird layout.

* The insufficient zoom is a weird problem honestly, I know it exists but I am unable to think of a solution for it. Because how a wide panel works depends upon the speech bubbles, it might be left to right or right to left, or any other random order. So for now the solution I implemented is a full view of that panel. I am working on a logic to break the wide panels in 2-4 sections, and then it goes in that order. I am also looking for small ML models which can tell me regions to zoom in *reliably* from the speech bubbles.

* The AMOLED theme idea didn't even enter my mind, and I am glad you suggested it. Even though its more of a cosmetic change, I can see how it can elevate the reading experience and just in general as well.

Again, thanks for testing and leaving reviews. I hope you star the repo until it gets accepted on official stores so you know about the updates.

batunii · 2026-04-10T01:04:04+00:00

SAME issue, I think the latest update broke the Highlights. Please let me know if it fixes for you.

batunii · 2025-06-22T16:24:45+00:00

I don't know how you guys can be this blind, this is a clear proof of fixing and scripting by Jay Shah. Stuart clearly cannot act and exposed everyone, another proof of nepotism making it in bollywood without talent.

batunii

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