u/epabafree

​

I've been seeing reports about a major controversy in India involving alleged irregularities in voter lists, demands for the resignation of the Chief Election Commissioner, and protesters being detained in Delhi.

From what I've read, the Election Commission of India has been conducting a large-scale voter verification exercise, reportedly resulting in around 130 million names being removed from electoral rolls. The Commission says the revisions are intended to address issues such as duplicate registrations, deaths and people moving away.

However, opposition parties and activists have raised concerns about eligible voters being excluded, and almost every single protestor, opposition and even film actors are now detained?

Reuters — [Why has a drive to verify India's billion voters put the poll body under scrutiny?](https://www.reuters.com/world/india/why-has-drive-verify-indias-billion-voters-put-poll-body-under-scrutiny-2026-10-09/)

Reuters — [India to deploy thousands of security forces in Delhi for protest over poll chief](https://www.reuters.com/world/india/indian-youth-leader-says-protest-will-go-ahead-despite-detentions-2026-10-09/)

The New York Times — [Live coverage of the protests and controversy](https://www.nytimes.com/live/2026/10/09/world/india-cjp-cockroach-protest)

Times of India - [Bollywood Actor detained from Protests](https://timesofindia.indiatimes.com/entertainment/hindi/bollywood/news/imran-khan-and-his-girlfriend-lekha-washington-detained-by-mumbai-police-at-august-kranti-maidan-during-protest-report/articleshow/134854832.cms)

I’ve spent over a week going through posts, comments, and different approaches, but I still haven’t been able to figure out the workflow I actually need.

I have a large collection of PDFs containing exam preparation material (CAT/XAT) in Multiple Choice Question format. Many of these PDFs are massive, so I’ve already started cutting some of them down into smaller files containing only specific exam papers or sections.

The problem is that the source material is structured inconsistently. Some PDFs are individual chapters, while others are huge compilations containing several different sections, such as:

• Reading Comprehension questions
• Logical Reasoning / Matching questions
• GK questions
• Answer keys
• Explanation sections

Some of these compilations are 40+ pages long. Others are shorter, but the material is poorly structured, for example, some questions have explanations while others only have an answer key.

What I ultimately want is to turn all of this into a well-organized, manually manageable question bank, ideally in an Excel/Google Sheets-style format that I can later use to create an Anki deck.

For every question, I want to be able to properly label and organize things such as:

• Exam / year (e.g. CAT 2023 PYQ)
• Section (VARC, DILR, Quant, GK, etc.)
• Topic / subtopic
• Question type
• Question
• Options
• Correct answer
• Explanation
• Source / paper / question number
• Any relevant tags

I also want the formatting to be good, especially for things like Reading Comprehension passages, mathematical expressions, tables, matching questions, and other questions where simple plain-text extraction makes everything messy.

Ideally, I want AI to help me take the original PDFs and turn them into this structured format while preserving the actual question, options, passages, mathematical notation, and explanations. Where the original material doesn't contain an explanation, I would also like AI to generate a clear, accurate explanation based on the question and answer.

I’ve tried doing this with both Google AI Studio and ChatGPT, and I’ve spent a considerable amount of time experimenting with prompts and different workflows, but I still haven’t found a reliable way to do it.

What I’m looking for is not necessarily an automated Python pipeline. I’m perfectly fine with a semi-manual workflow where I provide an AI with a PDF or a smaller chunk of a PDF, have it process the material into a structured spreadsheet/document, review the output, and then continue with the next chunk.

What would be the most reliable workflow for doing this?

Specifically, I’d like to know:

1. How should I split and organize these large PDFs before giving them to AI?
2. What structure/schema should I use for the question bank?
3. How should I prompt AI so that it correctly separates passages, questions, options, answers, and explanations instead of mixing them together?
4. How can I preserve proper formatting for mathematics, tables, RC passages, and other complicated question types?
5. How should I handle questions where the source PDF has an answer but no explanation?
6. How can I consistently tag questions by exam, year, section, topic, and question type?
7. What is the best way to do this using ChatGPT and/or Google AI Studio, without requiring me to build a complicated Python program?
8. Most importantly, how can I make the workflow reliable enough that I can process hundreds or thousands of questions without constantly having to fix formatting errors manually?

I’ve spent over a week going through posts, comments, and different approaches, but I still haven’t been able to figure out the workflow I actually need.

I have a large collection of PDFs containing exam preparation material in Multiple Choice Question format. Many of these PDFs are massive, so I’ve already started cutting some of them down into smaller files containing only specific exam papers or sections.

The problem is that the source material is structured inconsistently. Some PDFs are individual chapters, while others are huge compilations containing several different sections, such as:

• Reading Comprehension questions
• Logical Reasoning / Matching questions
• GK questions
• Answer keys
• Explanation sections

Some of these compilations are 40+ pages long. Others are shorter, but the material is poorly structured, for example, some questions have explanations while others only have an answer key.

What I ultimately want is to turn all of this into a well-organized, manually manageable question bank, ideally in an Excel/Google Sheets-style format that I can later use to create an Anki deck.

For every question, I want to be able to properly label and organize things such as:

• Exam / year (e.g. CAT 2023 PYQ)
• Section (VARC, DILR, Quant, GK, etc.)
• Topic / subtopic
• Question type
• Question
• Options
• Correct answer
• Explanation
• Source / paper / question number
• Any relevant tags

I also want the formatting to be good, especially for things like Reading Comprehension passages, mathematical expressions, tables, matching questions, and other questions where simple plain-text extraction makes everything messy.

Ideally, I want AI to help me take the original PDFs and turn them into this structured format while preserving the actual question, options, passages, mathematical notation, and explanations. Where the original material doesn't contain an explanation, I would also like AI to generate a clear, accurate explanation based on the question and answer.

I’ve tried doing this with both Google AI Studio and ChatGPT, and I’ve spent a considerable amount of time experimenting with prompts and different workflows, but I still haven’t found a reliable way to do it.

What I’m looking for is not necessarily an automated Python pipeline. I’m perfectly fine with a semi-manual workflow where I provide an AI with a PDF or a smaller chunk of a PDF, have it process the material into a structured spreadsheet/document, review the output, and then continue with the next chunk.

What would be the most reliable workflow for doing this?

Specifically, I’d like to know:

1. How should I split and organize these large PDFs before giving them to AI?
2. What structure/schema should I use for the question bank?
3. How should I prompt AI so that it correctly separates passages, questions, options, answers, and explanations instead of mixing them together?
4. How can I preserve proper formatting for mathematics, tables, RC passages, and other complicated question types?
5. How should I handle questions where the source PDF has an answer but no explanation?
6. How can I consistently tag questions by exam, year, section, topic, and question type?
7. What is the best way to do this using ChatGPT and/or Google AI Studio, without requiring me to build a complicated Python program?
8. Most importantly, how can I make the workflow reliable enough that I can process hundreds or thousands of questions without constantly having to fix formatting errors manually?

I’ve spent over a week going through posts, comments, and different approaches, but I still haven’t been able to figure out the workflow I actually need.

I have a large collection of PDFs containing exam preparation material in Multiple Choice Question format. Many of these PDFs are massive, so I’ve already started cutting some of them down into smaller files containing only specific exam papers or sections.

The problem is that the source material is structured inconsistently. Some PDFs are individual chapters, while others are huge compilations containing several different sections, such as:

• Reading Comprehension questions
• Logical Reasoning / Matching questions
• GK questions
• Answer keys
• Explanation sections

Some of these compilations are 40+ pages long. Others are shorter, but the material is poorly structured, for example, some questions have explanations while others only have an answer key.

What I ultimately want is to turn all of this into a well-organized, manually manageable question bank, ideally in an Excel/Google Sheets-style format that I can later use to create an Anki deck.

For every question, I want to be able to properly label and organize things such as:

• Exam / year (e.g. CAT 2023 PYQ)
• Section (VARC, DILR, Quant, GK, etc.)
• Topic / subtopic
• Question type
• Question
• Options
• Correct answer
• Explanation
• Source / paper / question number
• Any relevant tags

I also want the formatting to be good, especially for things like Reading Comprehension passages, mathematical expressions, tables, matching questions, and other questions where simple plain-text extraction makes everything messy.

Ideally, I want AI to help me take the original PDFs and turn them into this structured format while preserving the actual question, options, passages, mathematical notation, and explanations. Where the original material doesn't contain an explanation, I would also like AI to generate a clear, accurate explanation based on the question and answer.

I’ve tried doing this with both Google AI Studio and ChatGPT, and I’ve spent a considerable amount of time experimenting with prompts and different workflows, but I still haven’t found a reliable way to do it.

What I’m looking for is not necessarily an automated Python pipeline. I’m perfectly fine with a semi-manual workflow where I provide an AI with a PDF or a smaller chunk of a PDF, have it process the material into a structured spreadsheet/document, review the output, and then continue with the next chunk.

What would be the most reliable workflow for doing this?

Specifically, I’d like to know:

1. How should I split and organize these large PDFs before giving them to AI?
2. What structure/schema should I use for the question bank?
3. How should I prompt AI so that it correctly separates passages, questions, options, answers, and explanations instead of mixing them together?
4. How can I preserve proper formatting for mathematics, tables, RC passages, and other complicated question types?
5. How should I handle questions where the source PDF has an answer but no explanation?
6. How can I consistently tag questions by exam, year, section, topic, and question type?
7. What is the best way to do this using ChatGPT and/or Google AI Studio, without requiring me to build a complicated Python program?
8. Most importantly, how can I make the workflow reliable enough that I can process hundreds or thousands of questions without constantly having to fix formatting errors manually?

There is absolutely no reason to uphold this 20 year old annoying practise of waiting 1-2 years before the PC Release.

The game will most definitely run a lot better on PC now. I am not buying PS5 just for GTA6 man.

I am preparing for the CAT exam and want to create Anki decks out of standard MCQ preparation books (like the Arun Sharma / CL / CrackUseries). I have some massive PDFs, and I am searching for more, some spanning 800+ pages each, covering Quantitative Aptitude (QA), Verbal Ability & Reading Comprehension (VARC), and Data Interpretation & Logical Reasoning (DILR).

What is the most optimal way to extract and convert these into Anki flashcards using AI?

The formatting of these books makes it tricky. A typical chapter looks like this:

• Concept theory at the start.
• A block of 100+ MCQs (often divided by Difficulty Levels).
• An answer key at the very end of the chapter (e.g., 1-B, 2-C).
• Detailed step-by-step explanations/solutions following the answer key.

My goal is to create a workflow that links the question, the options, the correct answer, and the explanation into a single Anki card.

Any tips or add-on recommendations would be hugely appreciated. Thanks!

I want to make Anki Deck out of MCQ Books. These books are divided into Reading Comprehension tests, Maths, Quants, GK. There shall be different sections of all of these.

The PDFs I have are sort of like, 100 Questions, and once that ends, there are answers pointing to which question's correction option was which, and sometimes it is like the explanation of XYZ Question was this.

I want to make a workflow for this. Any tips would be appreciated.

I have used the phone for 20 hours with still juice to go. And now it is demanding 3 charges in a day.

​

I've been trying to figure this out for a while now, and I still dont understand how to fix it..

My laptop doesn't feel like it's running CachyOS properly. The desktop itself is mostly smooth, but browser-based applications and anything relying on GPU acceleration seem completely broken.

# Hardware

* ASUS ROG Zephyrus laptop

* Intel Alder Lake-P (Iris Xe iGPU)

* NVIDIA RTX 3060 Mobile

* 1TB Micron 3400 NVMe SSD

* CachyOS + Niri (Wayland)

* Proprietary NVIDIA driver 610.43.02

# Issues I'm experiencing

Almost everything browser-related stutters or becomes unusable.

* Firefox/Waterfox stutters while browsing.

* Pages often struggle to load or become extremely sluggish.

* Browser-based software crashes if I open more than one tab.

* WhatsApp Web is practically unusable. And kills every app running.

* Canva has never worked smoothly.

* Video playback becomes heavily corrupted/glitched after closing and reopening the laptop lid.

* DaVinci Resolve performance is terrible.

* GPU-accelerated applications feel inconsistent in general.

Overall, the system doesn't feel like it's utilizing the hardware correctly.

# What I've checked so far

`nvidia-smi` detects the RTX 3060 correctly:

Driver: 610.43.02

CUDA: 13.3

GPU Utilization: ~25%

VRAM usage: ~314 MiB

`lspci -k` shows both GPUs using the expected drivers:

Intel Iris Xe -> i915

NVIDIA RTX 3060 -> nvidia

My Wayland session also looks correct:

XDG_SESSION_TYPE=wayland

XDG_SESSION_DESKTOP=niri

MOZ_ENABLE_WAYLAND=1

The SSD appears healthy:

* SMART: PASSED

* 0 media/data integrity errors

* Overall health looks normal

I also checked for NVIDIA/DRM errors:

sudo dmesg | grep -iE "nvidia|drm|fallback|error"

This returns nothing relevant.

I also checked the NVIDIA power management services:

* `nvidia-suspend.service`

* `nvidia-hibernate.service`

* `nvidia-resume.service`

# ___________________________

Has anyone with a hybrid Intel/NVIDIA laptop running CachyOS experienced similar issues?

Should I be manually choosing between the integrated and dedicated GPU for applications, or should everything "just work" under Wayland?

I've been trying to find a good Japanese language institute or private tutor in Mumbai, but I've had a difficult time finding one that focuses on actually teaching the language well.

Many places I've come across either rush through the syllabus or seem more interested in helping students pass JLPT exams than building a solid understanding of Japanese.

I'm looking for recommendations from people with personal experience. Private tutors are absolutely fine too.

Any recommendations would be greatly appreciated. Thanks!