Skip to content
| Marketplace
Sign in
Visual Studio Code>Other>OmniChat AINew to Visual Studio Code? Get it now.
OmniChat AI

OmniChat AI

VaidikV

|
10 installs
| (1) | Free
Include any LLM in your VSCode workflow. Search for code, documentation, and more using the power of LLMs.
Installation
Launch VS Code Quick Open (Ctrl+P), paste the following command, and press enter.
Copied to clipboard
More Info

OmniChat AI 🧠💻

A privacy-first VS Code extension that integrates with any local LLM through Ollama. Chat with AI models directly in your editor without sending data to the cloud.

demo1 demo2

  • Works with Any LLM: Use DeepSeek, Gemma, Llama, or any other model available through Ollama
  • Real-Time AI Interaction: Get coding assistance, brainstorm ideas, and debug issues without leaving VS Code
  • Privacy-First: All processing happens locally - your code and data never leave your machine
  • Beautifully Formatted Responses: Clean markdown rendering for better readability
  • Seamless Integration: Matches VS Code's themes for a consistent experience

Installation

Prerequisites

  • Visual Studio Code
  • Ollama installed and running locally

Quick Install

  1. Install from VS Code Marketplace:

    • Open VS Code
    • Go to Extensions (Ctrl+Shift+X)
    • Search for "OmniChat AI"
    • Click Install
  2. Install your preferred LLM with Ollama:

    ollama pull deepseek-r1:1.5b
    # Or any other model you prefer
    

Usage

  1. Start Ollama in your terminal:

    ollama serve
    
  2. In VS Code:

    • Open Command Palette (Ctrl+Shift+P)
    • Run OmniChat: Start
    • A chat panel will open
  3. Set your preferred model:

    • Open Command Palette (Ctrl+Shift+P)
    • Run OmniChat: Set Model
    • Enter the model name (e.g., deepseek-r1:1.5b, gemma:7b, etc.)
  4. Start chatting!

    • Type your question and click "Ask"
    • Receive beautifully formatted responses

Models

OmniChat AI works with any model available through Ollama. Some popular options:

  • deepseek-r1:1.5b - Fast, lightweight coding assistant
  • deepseek-r1:8b - Good balance of speed and capability
  • deepseek-r1:32b - Most capable DeepSeek model
  • gemma:7b - Google's lightweight model
  • llama3:8b - Meta's efficient model

Credits

This project was inspired by Fireship's video on building VS Code extensions.

Special thanks to Ollama for enabling local AI capabilities.

License

This project is licensed under the MIT License.

  • Contact us
  • Jobs
  • Privacy
  • Manage cookies
  • Terms of use
  • Trademarks
© 2025 Microsoft