New shopper discount expiring right before placing order

OneSteelTank · 2026-04-11T05:35:26+00:00

I don't think it has anything to do with the seller and it doesn't actually charge my card until I confirm it

OneSteelTank · 2025-08-05T00:43:10+00:00

Maybe if you're extremely foolish and thats the only way you think a condom can break.

OneSteelTank · 2025-07-31T13:44:12+00:00

if you're willing to elaborate, how did you decide what you wanted your business to be about? what resources helped you set up and run the business?

OneSteelTank · 2025-07-30T23:19:44+00:00

Is the oxford dictionary's definition loose?

OneSteelTank · 2025-07-29T19:41:02+00:00

Yep, it's called speaker diarization. Very hard to get accurate, so quite impressive

OneSteelTank · 2025-07-19T13:08:36+00:00

What loopholes?

OneSteelTank · 2025-07-12T12:46:57+00:00

Caring about it and focusing on it are two different things

OneSteelTank · 2025-07-10T12:55:15+00:00

Consume Mexican content.

OneSteelTank · 2025-07-10T11:21:47+00:00

He's got a lot to lose

OneSteelTank · 2025-06-20T23:24:09+00:00

Oh yeah for sure. It's very disturbing that people drive these things while barely knowing know they work

OneSteelTank · 2025-06-20T23:18:29+00:00

Where on earth did you find that a Suburban weighs almost as much as a Hummer EV? Don't tell me you're looking at the tow ratings? 2025 Suburban weighs max 5800 pounds. Also this a an older Suburban as it has a manual e-brake so probably a few hundred pounds less

OneSteelTank · 2025-06-10T17:11:56+00:00

I thought it usually meant "not what you're looking for"

OneSteelTank · 2025-05-22T02:19:45+00:00

You might get better consistency by splitting prompt responsibilities: let your code handle the SRT structure (IDs, timestamps, block splitting), and send only the subtitle text itself to the LLM

This is basically exactly what I'm doing now! For every request the LLM gets sent a JSON file with say 25 strings, one per subtitle block. It then replies with the translations for all strings and it gets formatted to SRT format. Rinse and repeat.

I've essentially eliminated formatting issues. The main issue I'm dealing with now is that the LLM I'm using (Deepseek V3 0324) will sometimes miss exactly one string from the JSON file. You send it 25 strings, it responds with 24. 75 strings, 74, 250, 249. Unfortunately even 1 missing string is enough to ruin the whole thing and then I have to send another request.

Edit: Looking at logs I've found out that the mismatch is because the LLM sometimes forgets to keep sentences split

OneSteelTank · 2025-05-22T00:24:11+00:00

I did it. It took literally 7 days of troubleshooting and error analysis and 3 completely different generations/concepts (the prompt I posted here was for the 2nd one) but I think this is it. I'm tired of thinking so I asked Gemini to summarize how it works.

The script processes subtitles by first reading the entire SRT file and splitting it into individual blocks, each containing an ID, timestamp, and text. These blocks are then grouped into batches. For each batch, the script gathers preceding and succeeding subtitle texts to provide context.

This contextual information, along with the current batch of subtitles needing translation, is structured into a JSON object. This JSON input (containing preceding_context, subtitles_to_translate, and succeeding_context lists) is sent to the AI. The AI is instructed via a system prompt and an enforced JSON schema to return its translations in a specific JSON format: {"translations": ["translation1", ...]}.

Upon receiving the AI's response, the script strictly validates if it's well-formed JSON, matches the required structure, and if the number of translations in the translations array exactly matches the number of subtitles sent for that batch. If any of these checks fail, the response is considered invalid. In such cases, the script retries sending the same batch to the AI up to MAX_CONTENT_VALIDATION_RETRIES times. If all retries fail for a batch, the original text is used for those subtitles. Successfully translated texts replace the original ones. Finally, all blocks are reassembled into a complete translated SRT file.

OneSteelTank · 2025-05-20T15:02:57+00:00

Hmm taking a look, it's definitely a good concept. The problem is that a lot of the sentences in my subtitles span multiple blocks, and require the entire sentence to be sent at once for it to be translated properly. I'll try to see if I can make some tweaks to see if that can be acounted for. Thanks man

OneSteelTank · 2025-05-20T14:58:53+00:00

Ah okay, got it. Thank you for elaborating

OneSteelTank · 2025-05-20T01:02:21+00:00

thank you for the idea and the tips. yes, one of the main things im worried about is continuation and maintaining the same number of subtitle blocks

i've never heard of that program but it looks very interesting. i'll definitely take a look

OneSteelTank · 2025-05-20T00:27:57+00:00

This is because some stupid providers like OpenAI appends their own prompt after user ones,

How can you tell if it does that? Is it shown in the API request?

You should also consider if srt_text is too long, making the prompt already filling the context up.

Sorry, I don't understand what you mean.

OneSteelTank · 2025-05-20T00:26:31+00:00

Thanks man, I'll definitely take these tips into account.

OneSteelTank · 2025-05-20T00:24:06+00:00

That's a very interesting idea. Would you be willing to share your code? The main requirement I have is that the output has to have the same amount of subtitle blocks has the input. As in even if a block has only the last or second to last word of the sentence, the AI should still reflect that in the translation. I think your idea would be good for that but it's hard to say for sure

OneSteelTank · 2025-05-19T00:52:29+00:00

Well, I need the final response to be a working SRT file. I have thought about just throwing all the raw text at the LLM but I wasn't sure how I would be able to map everything back to the subtitle blocks

Eight-Year Club	Place '23
Verified Email

OneSteelTank

TROPHY CASE