Welcome to AlwaysReddy 🔊

Hey, I'm Josh, the creator of AlwaysReddy. I am still a little bit of a noob when it comes to programming and I'm really trying to develop my skills over the next year, I'm treating this project as an attempt to better develop my skills, with that in mind I would really appreciate it if you could point out issues and bad practices in my code (of which I'm sure there will be plenty). I would also appreciate if you would make your own improvements to the project so I can learn from your changes. Twitter: https://twitter.com/MindofMachine1

Contact me: joshlikesai@gmail.com

I'm looking for work, if you know of anyone needing a skillset like mine, please let me know! :)

Important notice:

The code base is a mess right now, I am in the middle of transforming AlwaysReddy from just being a voice chat bot into something that will allow users to create their own chatbots and extensions. This transition will be a little messy until I find solutions that I like, then I will start cleaning things up.

Sections

• Meet AlwaysReddy
• Philosophy of the project
• Setup
• Known Issues
• How to add custom actions
• Troubleshooting
• How to
• Supported LLM servers
• Supported TTS systems

Meet AlwaysReddy

AlwaysReddy is a simple LLM assistant with the perfect amount of UI... None! You interact with it entirely using hotkeys, it can easily read from or write to your clipboard. It's like having voice ChatGPT running on your computer at all times, you just press a hotkey and it will listen to any questions you have, no need to swap windows or tabs, and if you want to give it context of some extra text, just copy the text and double tap the hotkey!

Future of AlwaysReddy I would like to make AlwaysReddy an extensible interface where you can easily voice chat with a range of AIs, these AIs could be given the ability to access custom tools or applications so that they can do tasks for you on the fly, all of this with as little friction as possible.

Pull Requests Welcome!

Join the discord: https://discord.gg/su44drSBzb

Here is a demo video of me using it with Llama3 https://www.reddit.com/r/LocalLLaMA/comments/1ca510h/voice_chatting_with_llama_3_8b/

Philosophy of the project

• Friction is the enemy
• I am building this for myself first but sharing it in case other people get value from it too
• Practicality first, I want this system to help me be as effective as possible
• I will change directions freely, when I think of a more useful direction for the code base I will start working in that direction, even if that makes things messy in the short term
• Help is always welcome, if you have an idea of how you could improve AlwaysReddy, jump in and get your hands dirty!

Features:

You interact with AlwaysReddy entirely with hotkeys, it has the ability to:

• Voice chat with you via TTS and STT.
• Read from your clipboard (with Ctrl + Alt + R + R rapidly double tapping R).
• Write text to your clipboard on request.
• Can be run 100% locally!!!
• Supports Windows, Mac (experimental), linux (super duper experimental, see Known Issues).
• You can create your own hotkeys to fire custom code using AlwaysReddy's inbuilt systems like TTS and STT.
• Image capabilities, it can detect images in your clipboard and pass them to supported LLMs.

Are you a linux wizard?

If you are and you're willing to help please consider look at the Known Issues, I'm pretty stuck here!

Use cases:

I often use AlwaysReddy for the following things:

• When I have just learned a new concept I will often explain the concept aloud to AlwaysReddy and have it save the concept (in roughly my words) into a note.
• "What is X called?" Often I know how to roughly describe something but cant remember what it is called, AlwaysReddy is handy for quickly giving me the answer without me having to open the browser.
• "Can you proof read the text in my clipboard before I send it?"
• "What do the r/LocalLLaMA users think of X, based on the comments in my clipboard?"
• Quick journal entries, I speedily list what I have done today and get it to write a journal entry to my clipboard before I shutdown the computer for the day.

Supported LLM servers:

• OpenAI
• Anthropic
• TogetherAI
• LM Studio (local) - Setup Guide
• Ollama (local) - Setup Guide
• Perplexity
• TabbyAPI (local)

Supported TTS systems:

• Piper TTS (local and fast) See how to change voice model
• OpenAI TTS API
• Default mac TTS

Setup:

GPU Setup Instructions

GPU Acceleration

To use GPU acceleration with the faster-whisper API, follow these steps:

1. Check if CUDA is already installed:

   • Open a terminal or command prompt.
   • Run the following command:

     nvcc --version
     

   • If CUDA is installed, you should see output similar to:

     nvcc: NVIDIA (R) Cuda compiler driver
     Copyright (c) 2005-2021 NVIDIA Corporation
     Built on Sun_Feb_14_21:12:58_PST_2021
     Cuda compilation tools, release 11.2, V11.2.152
     Build cuda_11.2.r11.2/compiler.29618528_0
     

   • Note down the CUDA version (e.g., 11.2 in the example above).

2. If CUDA is not installed or you want to install a different version:

   • Visit the official NVIDIA CUDA Toolkit website: CUDA Toolkit
   • Download and install the appropriate CUDA Toolkit version for your system.

3. Install PyTorch with CUDA support based on your system and CUDA version. Follow the instructions on the official PyTorch website: PyTorch Installation

   Example command for CUDA 11.6:

   pip install torch==1.12.0+cu116 -f https://download.pytorch.org/whl/torch_stable.html
   

4. In the config.py file, set USE_GPU = True to enable GPU acceleration.

Setup for Windows, macOS, and Linux:

Note for MacOS: it is expected that you have Brew installed on your system, look here for setup

1. Clone this repo with git clone https://github.com/ILikeAI/AlwaysReddy
2. Navigate into the directory: cd AlwaysReddy
3. Run the setup script with python setup.py on windows or python3 setup.py on mac and linux.
4. Open the config.py and .env files and update them with your settings and API keys.

If you get module 'requests' not found run pip install requests or pip3 install requests

If you encounter any issues during the setup process, please refer to the Troubleshooting section below.

How to Run

Running on Windows:

• Double-click on the run_AlwaysReddy.bat file created during the setup process.

OR run python main.py from the command prompt or terminal.

• Activate the venv venv\Scripts\activate then run the main script directly python main.py.

Running on macOS and Linux:

• Open a terminal, navigate to the AlwaysReddy directory, and run ./run_AlwaysReddy.sh.

OR run python3 main.py from the command prompt or terminal.

• Activate the venv source venv/bin/activate then run the main script directly python3 main.py.

Known Issues:

• On linux it only detects hotkey presses when the application is in foucs, this is a major issue as the whole point of the project is to have it run in the background, if you want to help out this would be a great place to start poking around! -- this may only be an issue with systems using wayland
• Using AlwaysReddy in the terminal on ubuntu does not work for me, when I press the hotkey it just prints the key in the terminal, running it in my IDE works.

Troubleshooting:

If you have issues try deleting the venv folder and starting again. Set VERBOSE = True in the config to get more detailed logs and error traces

How to:

How to use AlwaysReddy:

There are currently only main 2 actions:

Voice chat:

• Press Ctrl + Alt + R to start dictating, you can talk for as long as you want, then press Ctrl + Alt + R again to stop recording, a few seconds later you will get a voice response from the AI
• You can also hold Ctrl + Alt + R to record and release it when you're done to get the transcription.

Voice chat with context of your clipboard:

• Double tap Ctrl + Alt + R (or just hold Ctrl + Alt and quickly press R Twice) This will give the AI the content of your clipboard so you can ask it to reference it, rewrite it, answer questions from its contents... whatever you like!
• Clear the assistants memory with Ctrl + Alt + W.
• Cancel recording or TTS with Ctrl + Alt + E

Get AlwaysReddy to output to your clipboard:

• Just ask it to! It is prompted to know how to save text to the clipboard instead of speaking it aloud.

Please let me know if you think of better hotkey defaults!

All hotkeys can be edited in config.py

How to add new voices for Piper TTS:

1. Go to https://huggingface.co/rhasspy/piper-voices/tree/main and navigate to your desired language.
2. Click on the name of the voice you want to try. There are different sized models available; I suggest using the medium size as it's pretty fast but still sounds great (for a locally run model).
3. Listen to the sample in the "sample" folder to ensure you like the voice.
4. Download the .onnx and .json files for the chosen voice.
5. Create a new folder in the piper_tts\voices directory and give it a descriptive name. You will need to enter the name of this folder into the config.py file. For example: PIPER_VOICE = "default_female_voice".
6. Move the two downloaded files (.onnx and .json) into your newly created folder within the piper_tts\voices directory.

How to use local faster-whisper transcription:

1. Open the config.py file.
2. Locate the "Transcription API Settings" section.
3. Comment out the line TRANSCRIPTION_API = "openai" by adding a # at the beginning of the line.
4. Uncomment the line TRANSCRIPTION_API = "faster-whisper" by removing the # at the beginning of the line.
5. Adjust the WHISPER_MODEL and TRANSCRIPTION_LANGUAGE settings according to your preferences.
6. Save the config.py file.

Available models with faster-whisper: tiny.en, tiny, base.en, base, small.en, small, medium.en, medium, large-v1, large-v2, large-v3, large, distil-large-v2, distil-medium.en, distil-small.en, distil-large-v3

Here's an example of how your config.py file should look like for local whisper transcription:

### Transcription API Settings ###

## OPENAI API TRANSCRIPTION EXAMPLE ##
# TRANSCRIPTION_API = "openai"  # this will use the hosted openai api

## Faster Whisper local transcription ###
TRANSCRIPTION_API = "FasterWhisper" # this will use the local whisper model

# Supported models: 
WHISPER_MODEL = "tiny.en" # If you prefer not to use english set it to "tiny", if the transcription quality is too low then set it to "base" but this will be a little slower

Note: The default whisper model is english only, try setting WHISPER_MODEL to 'tiny' or 'base' for other languages

How to swap servers or models

To swap models open the config.py file and uncomment the sections for the API you want to use. For example this is how you would use Claude 3 sonnet, if you wanted to use LM studio you would comment out the Anthropic section and uncomment the LM studio section.

### COMPLETIONS API SETTINGS ###

## LM Studio COMPLETIONS API EXAMPLE ##
# COMPLETIONS_API = "lm_studio" 
# COMPLETION_MODEL = "local-model" #This stays as local-model no matter what model you are using

## ANTHROPIC COMPLETIONS API EXAMPLE ##
COMPLETIONS_API = "anthropic" 
COMPLETION_MODEL = "claude-3-sonnet-20240229" 

## TOGETHER COMPLETIONS API EXAMPLE ##
# COMPLETIONS_API = "together"
# COMPLETION_MODEL = "NousResearch/Nous-Hermes-2-Mixtral-8x7B-SFT" 

## OPENAI COMPLETIONS API EXAMPLE ##
# COMPLETIONS_API = "openai"
# COMPLETION_MODEL = "gpt-4-0125-preview"

How to use local TTS

To use local TTS just open the config file and set TTS_ENGINE="piper"

How to make a custom system prompt

1. Navigate to the system_prompts directory.
2. Make a copy of an existing prompt file.
3. Open the copy in a text or code editor and edit the prompt inside the two ''' as you like.
4. Edit your config.py file by setting the ACTIVE_PROMPT option to the name of your new prompt file (without the .py extension) as a string.
   • For example, if your new prompt file is custom_prompt.py, then set in config.py: ACTIVE_PROMPT = "custom_prompt"

System prompt modules

An alternative way to customize the system prompt is to create a new "system prompt module". These modules, found in the system_prompts\modules directory, are additional instructions that can be appended to your base system prompt.

For example, the default 'clipboard' module contains the instructions that gives the assistant the ability to copy generated text into your clipboard.

How to make a custom system prompt module:

1. Navigate to the system_prompts\modules directory.
2. Make a copy of an existing module file.
3. Open the copy in a text or code editor and edit the prompt inside the two ''' as you like.
4. Edit your config.py file by adding your module file name (without the .py extension) to the ACTIVE_PROMPT_MODULES list option.

How to add AlwaysReddy to Startup List (Windows)

To add AlwaysReddy to your startup list so it starts automatically on your computer startup, follow these steps:

1. run venv\Scripts\activate
2. Run python setup.py, follow the prompts, it will ask you if you want to add AlwaysReddy to the startup list, press Y the confrim

If you want to remove AlwaysReddy from the startup list you can follow the same steps again, only say no when asked if you want to add AlwaysReddy to the startup list and it will ask if you would like to remove it, press Y.

Custom Actions

PLEASE NOTE: Custom actions is a very experimental feature that I am likely to chnage a lot, any actions you make will in all likelyhood need to be updated in some way as I update and change the actions system

What is an action?

The action system allows you to easily define new functionality and bind it to a hotkey event, it allows you to easily use the following functionalitys from the AlwayReddy code base:

• Record audio
• Transcribe audio
• Run and play TTS
• Generate responses from any of the supported LLM servers
• Read and save to the clipboard

This video shows the process of making an action from scratch: https://youtu.be/X0Bd20EDxfQ Example action: https://github.com/ILikeAI/alwaysreddy_add_to_md_note

How to record audio or transcribe in your custom action

The toggle_recording method starts or stops audio recording. When called the first time, it starts recording. The next call stops recording and returns the audio file path.

By default, if the recording times out, it's stopped and deleted. However, you can provide a callback function that will be executed on timeout instead. In the code example, transcription_action is passed as the callback. When the recording times out, transcription_action is called, which calls toggle_recording again, thereby stopping the recording and returning the audio file for transcription.

def transcription_action(self):
    """Handle the transcription process."""
    recording_filename = self.AR.toggle_recording(self.transcription_action)
    if recording_filename:
        transcript = self.AR.transcription_manager.transcribe_audio(recording_filename)
        to_clipboard(transcript)
        print("Transcription copied to clipboard.")

How to bind your action to a hotkey

The setup method of your action will run when AlwaysReddy starts, this is where you use the add_action_hotkey method to bind your code to a hotkey press, below is an example of binding hotkeys to the transcription_action method.

self.AR.add_action_hotkey("ctrl+alt+t", 
                  pressed=self.transcription_action,
                  held_release=self.transcription_action)

Here we are binding the pressed and held_release hotkey events to our function.

Below are the arguments for add_action_hotkey:

hotkey (str): The hotkey combination.
pressed (callable, optional): Callback for when the hotkey is pressed.
released (callable, optional): Callback for when the hotkey is released.
held (callable, optional): Callback for when the hotkey is held.
held_release (callable, optional): Callback for when the hotkey is released after being held.
double_tap (callable, optional): Callback for when the hotkey is double-tapped.