If you want faster iteration in image generation in ComfyUI, use this practical technique to quickly refine your images and streamline your workflow.

Steps for Faster Iteration in Image Generation in ComfyUI

1. Fix the seed to ensure output consistency when generating images.
2. Use converging samplers like euler or dpmpp_2m for reliable, repeatable results.
   Tip: Avoid non-converging or stochastic samplers (such as euler_a or ddpm) if you want to keep the same image for a given seed.
3. Start with a low number of steps (for example, 10–20) to generate images faster and get a quick preview of the composition.
4. Generate an image and review the output. If you’re not satisfied, increment the seed by one or try a different value to explore more options rapidly.
5. When you like a result, keep the same seed and increase the number of steps (e.g., 30–50 or higher) to produce a more detailed and higher-quality image.
6. Advanced: For your final render, try samplers like DPM++ 2M Karras for even higher quality. You can also experiment with ComfyUI custom nodes and extensions for greater control over the sampling process.

Why This Technique Enables Faster Iteration in Image Generation in ComfyUI

Converging samplers such as euler and dpmpp_2m produce nearly identical images for the same seed, no matter the step count. This allows you to iterate rapidly with fewer steps, find a composition you like, and then enhance image quality simply by increasing the step count—without losing the image you prefer.

This workflow does not work with non-converging or stochastic samplers like euler_a or ddpm, which can create different images even for the same seed and prompt. That’s why this approach to faster iteration in image generation in ComfyUI is focused on converging samplers.

Using this method saves time, reduces frustration, and lets you efficiently reach your ideal output.

Conclusion

Faster iteration in image generation in ComfyUI allows you to experiment quickly, lock in your favorite composition, and then boost quality without losing your progress. As the gallery shows, even a single step produces impressive results with the right sampler and seed, while a few extra steps add significant detail. By following this technique, you can save time and consistently achieve high-quality AI art

The post Faster Iteration in Image Generation in ComfyUI Using This Technique – Beginner Tip appeared first on Pushakar Gaikwad.

Converting a video file to audio is a common need for podcasters, content creators, and anyone who wants to extract soundtracks, lectures, or podcasts from their videos. The easiest and most powerful way to do this is with the command-line tool ffmpeg, which works on Linux, Windows, and Mac.

Why Extract Audio from Video?

• Save storage space by keeping only the audio
• Share podcasts or lectures as audio files
• Use audio in music players or editing software
• Repurpose content for reels, shorts, or radio

What You Need

• ffmpeg installed (on Linux, Windows, or Mac)
• Your video file (mp4, mkv, avi, mov, etc.)

Installing FFmpeg

Linux (Ubuntu example):

sudo apt install ffmpeg

Windows:

• Download a static build from ffmpeg.org/download
• Extract and add to your system PATH for command-line use

Basic Conversion Command

To extract audio from any video file (MP4, MKV, AVI, MOV, etc.):

ffmpeg -i "inputfilename.ext" -q:a 0 -map a "outputfilename.audioext"

• Replace inputfilename.ext with your video file (any supported format such as .mp4, .mkv, .avi, .mov, etc.)
• Replace outputfilename.audioext with your desired audio filename and extension, such as .mp3, .wav, .ogg, or .m4a.

Note: The output file extension tells ffmpeg what audio format to use. For most common cases, you can just change the extension for the format you want:

• .mp3 for MP3
• .wav for WAV
• .ogg for OGG/Vorbis
• .m4a for AAC/M4A (optionally add -c:a aac -b:a 192k for best results)

Example

Suppose you have a file called 2025-05-30 17-21-02.mkv and want to create an MP3:

ffmpeg -i "2025-05-30 17-21-02.mkv" -q:a 0 -map a "2025-05-30 17-21-02.mp3"

Or to create a WAV file:

ffmpeg -i "2025-05-30 17-21-02.mkv" -map a "2025-05-30 17-21-02.wav"

Or to create an M4A file (with explicit AAC encoding and quality):

ffmpeg -i "2025-05-30 17-21-02.mkv" -c:a aac -b:a 192k "2025-05-30 17-21-02.m4a"

Bonus: zsh Function for Linux Power Users

If you often need to convert videos, add this function to your ~/.zshrc:

videotoaudio() {
  if [[ $# -lt 1 ]]; then
    echo "Usage: videotoaudio <video_filename> [audio_filename.ext]"
    return 1
  fi
  input="$1"
  if [[ ! -f "$input" ]]; then
    echo "File '$input' not found!"
    return 2
  fi
  if [[ $# -eq 1 ]]; then
    output="${input%.*}.mp3"
    echo "No output filename specified. Defaulting to $output."
  else
    output="$2"
  fi
  ffmpeg -i "$input" -q:a 0 -map a "$output"
}

After editing .zshrc, reload with:

source ~/.zshrc

Usage Examples:

1. Specify Both Input and Output (Choose Any Audio Format)

videotoaudio "Your Video File.mkv" "MyAudio.wav"

This will convert Your Video File.mkv to a WAV file named MyAudio.wav (or use any extension you choose for the output).

2. Specify Only the Video File (Default to MP3 Output)

videotoaudio "Your Video File.mkv"

This will automatically create an MP3 file named Your Video File.mp3 in the same directory.

Troubleshooting

• File not found or small output: Always quote or escape filenames with spaces.
• File manager (Dolphin, Explorer) not updating: Press F5 to refresh the directory after conversion to see new file sizes and names. Close and reopen properties dialogs to get the latest info.

Conclusion

With ffmpeg and a simple shell function, extracting audio from any video is fast and reliable on Linux, Windows, or Mac. Choose your desired audio format simply by specifying the output extension, and automate the process to save time on repetitive tasks!

The post Extract Audio (MP3, WAV) from Video: Convert MP4, MKV, AVI, MOV to Audio with FFmpeg appeared first on Pushakar Gaikwad.

Are you seeing Error: EMFILE: too many open files when you start your web app with npm run dev in VS Code on Linux? This common issue happens because the default file-descriptor limit is too low for modern build tools like Vite, Webpack, or Rollup. In this guide you’ll learn:

• Why the EMFILE error occurs
• How to temporarily raise your ulimit
• How to make the change permanent
• Additional tips for Vite and VS Code users

What Causes “EMFILE: too many open files”?

The Linux kernel restricts how many files a single process can open simultaneously. Build tools that watch many source files will quickly hit that limit, leading to:

Error: EMFILE: too many open files

On VS Code’s integrated terminal, you may not notice until you start npm run dev. Vite’s file-watcher can require hundreds or thousands of file descriptors.

Temporary Fix: Increase File Descriptors with ulimit

To quickly raise your soft limit for the current session:

ulimit -Sn 10000
npm run dev

This sets your soft limit to 10,000. Adjust the number as needed based on your project’s file-watch requirements.

Make the Change Permanent

To avoid resetting ulimit every session, update your system limits:

1. Edit /etc/security/limits.conf (requires sudo):
   

   sudo nano /etc/security/limits.conf

   
   
2. Add at the end:
   

   # Increase file descriptors for all users
   *               soft    nofile          10000
   *               hard    nofile          30000
     

   
   
3. Save and logout/login, or reboot.
4. Verify with:
   

   ulimit -Sn   # soft limit
   ulimit -Hn   # hard limit
     

   
   

Vite Troubleshooting Tips

If increasing ulimit doesn’t resolve stalls or frozen hot-reload, try:

• Clearing Vite cache: npm run dev -- --force
• Upgrading to the latest Vite version
• Reviewing the Vite Troubleshooting Guide

Frequently Asked Questions (FAQ)

What is the difference between soft and hard limits?

Soft limits can be raised by any user process up to the hard limit. Hard limits act as an absolute ceiling and can only be raised by root.

Does this affect Docker containers?

Yes. In Docker, set --ulimit nofile=10000:30000 in your run command or Compose file.

Wrap Up

By increasing your file-descriptor limits with ulimit—temporarily or permanently—you’ll eliminate the EMFILE error when running npm run dev. Combine this with Vite’s own troubleshooting tips to keep development smooth. If this helped, share this post, leave a comment below, or explore more tips on Linux, JavaScript, and Web Development.

The post How to Fix “EMFILE: too many open files” When Running npm run dev in VS Code on Linux appeared first on Pushakar Gaikwad.

Record Audio/ Voice over directly in Blender Sequencer (VSE)

Overview of Push-to-Talk Addon

What it does: Simplifies recording audio directly into the Video Sequencer Editor.Features of the addon:

• Easy integration into Blender’s VSE.
• Push-to-Talk functionality for live audio recording.

Use Cases and Benefits

• Creating voiceovers for animation projects without needing external software.
• Streamlining the workflow for video editors and content creators.

https://github.com/britalmeida/push_to_talk

Reference https://www.youtube.com/watch?v=Pj5e2GY7msM

Manage Python Packages in Blender

Overview of Blender Pip Addon

Purpose of the addon: Simplify the management of Python libraries within Blender.

Features

• Install, update, and manage Python packages directly from Blender’s interface.
• Enhanced compatibility with Blender’s scripting environment.

https://github.com/amb/blender_pip

Subtitle Editor with Automatic Subtitle Generation

Overview of Subtitle Editor Addon

Automatic subtitle generation using OpenAI’s Whisper (local open-source model).

Features and Capabilities

• Edit and sync subtitles within Blender’s interface.
• AI-powered transcription for precise subtitle creation.

Applications for Video Creators

• Time-saving tool for creating subtitles for tutorials, vlogs, or animations.
• Improves accessibility for viewers.

https://github.com/tin2tin/Subtitle_Editor

The post Blender Addons appeared first on Pushakar Gaikwad.

Express yourself with LLMs

Imagine a world where every message you type is refined instantly by a Language Learning Model (LLM). This vision is no longer a futuristic dream; it’s rapidly becoming reality. Social platforms like X (formerly Twitter) are introducing in-built proofreading via LLMs, following Instagram’s lead, which has already integrated this feature into its messaging system.

The LLM Revolution in Digital Communication

LLMs are poised to revolutionize how we communicate digitally. Beyond simple autocorrect or predictive text, these advanced systems rewrite and enhance your messages, turning fragmented thoughts into coherent, eloquent expressions. It’s like having a personal editor for every message you send.

A New Layer in Human Language Processing

The human brain is a natural language processor, converting abstract thoughts into structured sentences. Each person’s linguistic style is uniquely shaped by their cognitive and cultural background. LLMs add a transformative layer to this process, acting as an AI-powered co-creator to refine and elevate communication.

Benefits for Native Speakers

Native speakers, particularly those educated in their mother tongue, are significant beneficiaries of LLM technology. Complex ideas can now be articulated effortlessly, with LLMs translating nuanced thoughts into globally understood languages like English. This minimizes miscommunication and preserves cultural context. In the past, individuals schooled in their native language often struggled to formulate English sentences while speaking. Despite possessing a rich vocabulary in their mother tongue, they found it difficult to express themselves directly in English. However, with the advent of LLMs, the dynamic has shifted. Now, native language speakers can type complex thoughts in their mother tongue, leveraging their deep linguistic knowledge, and rely on LLMs to translate those ideas accurately into English.

Challenges for Second-Language Speakers

For individuals educated in a second language, interacting with LLMs might initially feel intimidating—akin to navigating a language class for the first time. The quality of LLM-generated output depends on the quality of input, which poses a challenge for those still developing their linguistic skills. Conversely, second-language speakers, who once had the advantage in public speaking due to their familiarity with English, may now face diminishing returns. Their vocabulary is often limited in both their native language and English, making it harder to craft rich, complex inputs for LLMs to refine. This initial challenge mirrors the difficulties native-language speakers faced in the past, effectively reversing the tables in the digital communication landscape.

Empowering Non-English Speakers

LLMs have the potential to dramatically empower non-English speakers, particularly students and professionals. These individuals often face barriers when expressing their ideas in English, a language that dominates global discourse. With LLMs, they can confidently leverage their native linguistic richness, producing faster and more accurate translations that level the playing field.

The Neuralink Connection: A Glimpse into the Future

The potential of LLMs extends far beyond social media. Integrating LLMs with emerging technologies like Neuralink could redefine human interaction. Imagine thinking a message and having it translated instantly into any language, breaking barriers of not only geography but also cognition.

Conclusion

The integration of LLMs into platforms like X is not just about fixing typos—it heralds a paradigm shift in communication. These tools can bridge linguistic divides, enhance self-expression, and create a more inclusive digital landscape. While the journey comes with its challenges, the potential rewards for a globally connected world are immense.

The post The Dawn of LLM-Driven Communication: Breaking Language Barriers on Social Platforms appeared first on Pushakar Gaikwad.

Tutorial/Commands on How to enable wireless debugging on android. This will let you use adb using Wi-Fi on your android

Most of the times android developers connect their android devices using usb cable for debugging and developing their applications. It might not be ideal to keep the device connected. In this short tutorial you will get to see how to enable wireless debugging on your android and then connect to the android device using adb using Wi-Fi from your computer

Connecting to your Android Device

Prerequisites

• Make sure developer mode is on
• Both mobile device and computer are connected to the same network
• adb is installed and in system path of the computer

Steps

• In Settings search for “Wireless debugging”
  • Turn on the toggle
• It will display ip address and port
  • Here for example it shows 192.168.1.11:40369
• On your computer, in the terminal run the following command using the ip address and port from previous step
  • adb connect 192.168.1.11:40369
• You will get a confirmation output `connected to 192.168.1.11:40369`
  • You can also manually get a list of connected devices just to verify
    • adb devices

Disconnecting your Android

Type the following command using the ip address and port from previous steps.

adb disconnect 192.168.1.11:40369

Additionally if you dont know the ip address and port you can check it using the command adb devices

The post Wireless debugging on Android – Use ADB using Wi-Fi appeared first on Pushakar Gaikwad.

Python Cheatsheet

PIP (Python Package Installer)

Update a pip package

pip install --upgrade package-name

Clean pip cache

pip cache purge

Anaconda / miniconda Command-Line Tips

Managing Environments

Create new conda environment

conda create --name environment_name python=3.11 

You can replace the 3.11 with any the python version as required

Remove conda environment

conda env remove --name environment_name

Make sure to deactivate the environment if you are trying to remove the active environment using conda deactivate

Reclaim Storage

Clean cache, reclaim storage, and remove unused or temporary packages:

conda clean --all

That’s it for now, adding more soon

Boost your Python development efficiency with these quick commands! Whether you use pip or Anaconda, keeping your environment clean and up-to-date is essential for smooth workflows. Save this cheatsheet for your next Python project.

Looking for more Python tips? Stay tuned for regular updates on mastering Python!

The post Boost Your Python Workflow: Pip and Anaconda Tips appeared first on Pushakar Gaikwad.

Here is a list of Shortcuts that I use regularly in VS Code. Some maybe obvious and basic and some can be hidden gems

In no particular order:

Alt+Shift+F => Format current document (requires Prettier installed

Ctrl+Shift+P => Command Pallet

The post VS Code Shortcuts Cheatsheet appeared first on Pushakar Gaikwad.

React Native has made it incredibly easy to develop cross-platform apps that work on both mobile and web using frameworks like Expo. However, there are times when a native plugin (designed for iOS or Android) isn’t compatible with the web platform. One common example is Google AdMob (react-native-google-mobile-ads), which can cause crashes when trying to build for the web with errors like:

Error: Module not found: Can’t resolve ‘../Utilities/Platform’

This type of error can be frustrating, especially when you’re trying to maintain a shared codebase for both mobile and web. In this guide, I’ll show you how to “mock” or disable incompatible modules for specific platforms using a simple configuration tweak in your metro.config.js file.

The Problem: Incompatible Plugins on Web

When working with React Native apps, you might want to include certain modules, like Google AdMob, to monetize your app. However, plugins like react-native-google-mobile-ads rely on native iOS and Android APIs and will throw errors when included in a web build because the required native code doesn’t exist in the web environment. For example, you might encounter this error during a web build:

Error: Module not found: Can’t resolve ‘../Utilities/Platform’

In this case, the app crashes because it’s trying to resolve native utilities that are unavailable on the web platform.

The goal is to disable the incompatible plugin from the web build so the rest of the app can function properly without issues.

The Solution: Customizing Metro Bundler to Skip Web-Incompatible Modules

Luckily, Metro bundler (the JavaScript bundler used by React Native) provides a way to conditionally exclude or mock modules based on the platform. We can use a clever hack by modifying the metro.config.js file to instruct Metro to skip loading certain modules when building for the web.

Let’s walk through the solution step by step.

Modify metro.config.js :

In your React Native project, locate the metro.config.js file. If it doesn’t exist, create one in the root of your project.

Add the following code to your metro.config.js:

Explanation of the Code:

1. Get the Default Metro Config:
   We’re first getting the default Metro configuration using getDefaultConfig from expo/metro-config.
2. Resolver Override:
   The resolver.resolveRequest function allows us to customize how modules are resolved for different platforms. This is the key to our solution.
3. Platform-Specific Module Exclusion:
   We’re adding a condition to check if the current platform is 'web' and the module name is 'react-native-google-mobile-ads'. If these conditions are true, we return an object with type: 'empty'. This effectively mocks the module, making it appear as an empty module for the web platform, preventing the app from crashing due to missing dependencies.
4. Fallback to Default Resolver:
   After our custom condition, we ensure the default resolver is called to handle other modules that are not problematic.

Why This Approach Works

React Native modules like react-native-google-mobile-ads are built to interact with native APIs on Android and iOS, but web platforms don’t have access to these APIs. By instructing Metro to return an empty module for web builds, we can safely bypass the need for these plugins without affecting the mobile versions of the app.

This method is:

• Simple: You only need to modify one file, metro.config.js, to skip incompatible modules.
• Safe: This approach doesn’t impact mobile builds, so you can continue using native plugins on iOS and Android without issues.
• Flexible: You can extend this method to handle multiple incompatible plugins or modules across different platforms (e.g., web, desktop).

Additional Use Cases

This technique is not limited to react-native-google-mobile-ads. You can use it for any plugin or module that is incompatible with a specific platform. Here’s an example of how you could apply it to other modules:

config.resolver.resolveRequest = (context, moduleName, platform) => {
  if (platform === 'web' && moduleName === 'react-native-some-other-module') {
    return {
      type: 'empty',
    };
  }

  return context.resolveRequest(context, moduleName, platform);
};

Simply replace 'react-native-some-other-module' with the name of the plugin you want to mock.

Conclusion

If you’re building a cross-platform React Native app that targets both mobile and web, dealing with incompatible plugins can be frustrating. Thankfully, Metro’s resolveRequest functionality allows you to mock incompatible modules like react-native-google-mobile-ads, enabling you to create web builds that work seamlessly alongside mobile ones.

This approach saves time, prevents crashes, and makes your development process smoother. Happy coding!

Key Takeaways:

• You can mock or skip incompatible plugins on specific platforms using metro.config.js.
• This solution works by checking the platform and conditionally returning an empty module.
• The approach doesn’t affect mobile builds, so your native modules will still work as intended on iOS and Android.

You can now implement this solution and even share it with your developer peers if they face similar issues. It’s a simple yet effective way to ensure your app remains stable across multiple platforms.

The post Fixing Plugin Compatibility in React Native Web with Expo: How to Disable Google AdMob and Other Native Modules appeared first on Pushakar Gaikwad.

Creating and managing social media content can be a daunting task, but with the right tools, it becomes much easier. Here’s a curated list of resources that can help streamline your social media workflow.

1. AnyVideo Downloader Flow Plugin
   Download videos from any website, including YouTube and Instagram. Requires Flow Launcher.
2. Playphrase.me
   Search and download clips from movies based on dialogue text. Perfect for finding that exact phrase to enhance your content.
3. Veed Hashtag Generator
   Generate relevant hashtags for your posts to boost visibility and engagement.
4. WordPress
   A battle-tested open-source platform for self-hosting websites and blogs. Highly customizable with a vast array of plugins.
5. Unsplash, Pixabay, Pexels
   Access thousands of high-quality, free-to-use stock photos, videos, music and audio effects to enhance your social media content. Whether you need them for posts, blogs, or ads, these platforms provide an excellent selection without the worry of copyright issues.

The post Essential Resources for Social Media Content Creation and Management appeared first on Pushakar Gaikwad.