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srikanth235

privy

An open-source alternative to GitHub copilot that runs locally.

ApplicationsCodingTypeScript
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Created 2023-12-18 · Updated 2026-10-13 · #12181 today
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srikanth235eltociear

srikanth235/privy is ranked 12,181 with 993 stars.

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srikanth235/privy is ranked 12,181 among these 8 peers; Ayush0Chaudhary/blurr is ranked 12,178.

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Key parameters and specifications
Key parameters and specifications
ParameterValue
LanguageTypeScript
CategoryApplications
SubcategoryCoding
KeywordsIDE, LocalAI
Stars993
Forks51
Contributors2
Created date2023-12-18
Updated date2026-10-13
Stars in 1 day0
Stars in 7 days-2
Rank12,181
Previous rank12,111
Rank change-70
7-day stars rank18,382
Previous 7-day stars rank18,323
7-day stars rank change-59
Total stars rank11,208
Previous total stars rank11,188
Total stars rank change-20
CountryIndia
README summary

💬 Privy 👀 See it in action Real time code completion Chat with AI about your code 🛠️ Pre-requisites If you haven't done already, please pick one of the following platforms to run LLM of your choice on your system **locally**. Ollama (Highly Recommended) llamafile (Experimental) llama. cpp (Experimental) 👍 LLM Recommendations Please note that you need to configure LLM for code completion and chat feature **separately**. Some of the popular LLMs that we recommend are as follows. 3b, 7b, 13b or 34b

) of the model based on your hardware capabilities. 7b or 33b}-instruct | Ollama Tags, Home | | codellama:{7b or 13b or 34b}-code | codellama:{7b or 13b or 34b}-instruct | Ollama Tags, Home | | | mistral:{7b}-instruct | Ollama Tags, Home | You can also pick a model by evaluating your local LLMs using Benchllama. 🚀 Quick Install You can install Privy extension from the Visual Studio Code Marketplace or from the Open VSX Registry. Visual Studio Code Marketplace Open VSX Registry ⚙️ Configuration Options Please

set the following options in the **settings** for Privy extension. provider**( ): Pick the platform that is being used for running LLMs locally. There is support for using OpenAI, but this will affect the privacy aspects of the solution. providerUrl**( ): The URL of the platform that is being used for running LLMs locally. mode**: Use this setting for enabling/disabling autocompletion feature. model**: Input the name of local Ollama model that you want to use for autocompletion. Supported formats are DeepSeek

Coder, LLama & Stable Code. 3b-base as it requires least amount of VRAM. You can customize based on your hardware setup. debounceWait**: Use this for setting the time gap before triggering the next completion in milliseconds. model**: Select the LLM that you want to chat with. Currently, supports DeepSeek, Mistral and CodeLLama. If you want to use other LLMs, please select and configure accordingly. customModel**: If you want to pick any other models running on your Ollama, please input their

name. , code changes, include concrete names and describe the desired outcome. You can include the programming language ("in Rust") or other relevant contexts for basic questions. You can select a meaningful code snippet for code explanations and error diagnosis. It's a big step for Privy to be able to respond to your questions. It might respond with inaccurate answers, especially when talking about less well-known topics or when the conversation gets too detailed. **Use different chat threads for different

topics**. Shorter threads with specific topics will help Privy respond more accurately. 🤝 Credits RubberDuck AI - This project is heavily inspired by RubberDuck AI's work, and we're indebted to them for building on top of it. The following is the list of contributors to this project and we extend our sincere gratitude to all of them. 🎉 Code Contributions Contributing Guide Read our contributing guide to learn about our development process, how to propose bugfixes and improvements, and how to build and

test your changes. Good First Issues To help you get your feet wet and become familiar with our contribution process

Frequently asked questions

How many stars and forks are recorded?

srikanth235/privy has 993 stars and 51 forks.

What is the repository rank?

srikanth235/privy is ranked 12,181.

What language and category are recorded?

srikanth235/privy has 993 stars, uses TypeScript and belongs to Applications.

Which repository is closest in rank?

srikanth235/privy is compared with Ayush0Chaudhary/blurr, ranked 12,178 with 993 stars.

README

💬 Privy

An open-source alternative to GitHub copilot that runs locally.

👀 See it in action

Real time code completion

Chat with AI about your code

🛠️ Pre-requisites

If you haven't done already, please pick one of the following platforms to run LLM of your choice on your system locally.

👍 LLM Recommendations

Please note that you need to configure LLM for code completion and chat feature separately. Some of the popular LLMs that we recommend are as follows. Please pick the size (i.e. 1.3b, 7b, 13b or 34b) of the model based on your hardware capabilities.

Code Completion Chat Links
deepseek-coder:{1.3b or 6.7b or 33b }-base deepseek-coder:{1.3b or 6.7b or 33b}-instruct Ollama Tags, Home
codellama:{7b or 13b or 34b}-code codellama:{7b or 13b or 34b}-instruct Ollama Tags, Home
mistral:{7b}-instruct Ollama Tags, Home

You can also pick a model by evaluating your local LLMs using Benchllama.

🚀 Quick Install

You can install Privy extension from the Visual Studio Code Marketplace or from the Open VSX Registry.

⚙️ Configuration Options

Please set the following options in the settings for Privy extension.

  • privy.provider(required): Pick the platform that is being used for running LLMs locally. There is support for using OpenAI, but this will affect the privacy aspects of the solution. The default is Ollama.
  • privy.providerUrl(required): The URL of the platform that is being used for running LLMs locally. The default is http://localhost:11434.
  • privy.autocomplete.mode: Use this setting for enabling/disabling autocompletion feature.
  • privy.autocomplete.model: Input the name of local Ollama model that you want to use for autocompletion. Supported formats are DeepSeek Coder, LLama & Stable Code. We have chosen deepseek-coder:1.3b-base as it requires least amount of VRAM. You can customize based on your hardware setup.
  • privy.autocomplete.debounceWait: Use this for setting the time gap before triggering the next completion in milliseconds. Default is 300 ms.
  • privy.model: Select the LLM that you want to chat with. Currently, supports DeepSeek, Mistral and CodeLLama. If you want to use other LLMs, please select custom and configure privy.customModel accordingly.
  • privy.customModel: If you want to pick any other models running on your Ollama, please input their name.

✨ Key Features

  • 👍 Open Source
  • 🔐 Privacy first
  • 🚀 Auto code completion
  • 🤖 Copilot style chat
  • 💬 Threaded conversations
  • 💻 Support for code explanation, unit tests, finding bugs, diagnosing errors etc

⌨️ Keyboard shortcuts

Shortcut (Mac) Description
Alt + \ (for Windows/Linux) or Cmd + \ (for Mac) Trigger inline code completion
Ctrl + Alt + c (for Windows/Linux) or Ctrl + Cmd + c(for Mac) Start Chat

💡 Tips and Tricks

Understanding these concepts will help you get the most out of Privy.

  • Be specific. When you ask for, e.g., code changes, include concrete names and describe the desired outcome. Avoid vague references.
  • Provide context. You can include the programming language ("in Rust") or other relevant contexts for basic questions. You can select a meaningful code snippet for code explanations and error diagnosis.
  • Do not trust answers blindly. It's a big step for Privy to be able to respond to your questions. It might respond with inaccurate answers, especially when talking about less well-known topics or when the conversation gets too detailed.
  • Use different chat threads for different topics. Shorter threads with specific topics will help Privy respond more accurately.

🤝 Credits

  • RubberDuck AI - This project is heavily inspired by RubberDuck AI's work, and we're indebted to them for building on top of it. The following is the list of contributors to this project and we extend our sincere gratitude to all of them.


Lars Grammel

🤔 💻 📖 👀 💬 🐛


Iain Majer

🐛 💻


Nicolas Carlo

💻 📖 🐛


RatoGBM

🐛


Lionel Okpeicha

🐛


MercerK

🐛


Lundeen.Bryan

🤔


DucoG

🤔


sbstn87

🤔


Manuel

🤔


alessandro-newzoo

🤔


Void&Null

🤔


WittyDingo

🤔


Eva

🤔


AlexeyLavrentev

🤔


linshu123

📖


Michael Adams

💻 🐛


restlessronin

💻

🎉 Code Contributions

Contributing Guide

Read our contributing guide to learn about our development process, how to propose bugfixes and improvements, and how to build and test your changes.

Good First Issues

To help you get your feet wet and become familiar with our contribution process, we have a list of good first issues that contains things with a relatively limited scope. This is a great place to get started!

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