Your local AI coding copilot — any model, any provider, zero cloud.
Project description
Your local AI coding assistant — any model, any provider. Your AI. Your Rules.
Airvo runs on your machine, connects to any AI model simultaneously, and integrates directly into VS Code via continue.dev. No cloud lock-in. No subscriptions. Your API keys stay local.
Table of Contents
- What is Airvo?
- Quick Start
- Features
- Supported Models
- Dashboard
- Multi-Model Modes
- VS Code Integration
- Configuration
- Use Cases
- Roadmap
- Security
- FAQ
- Community
- License
What is Airvo?
Airvo is a local server that sits between your editor and any AI model. Install it once, configure your API keys in the dashboard, and start coding with AI — without changing your workflow.
Your Editor (VS Code)
│
│ OpenAI-compatible API
▼
Airvo Server ←─── runs on localhost:5000
│
├── Groq (Llama 3.1, Llama 3.3)
├── OpenAI (GPT-4o, GPT-4o mini)
├── Anthropic (Claude Sonnet, Haiku)
├── Ollama (100% local, no API key)
├── LM Studio (100% local)
└── Any LiteLLM-compatible provider
Why Airvo?
- ✅ Any model, any provider — no lock-in
- ✅ Up to 3 models simultaneously — parallel, race, vote or review
- ✅ 4 multi-model modes — Parallel, Race, Vote, Review
- ✅ Your API keys stored locally — never shared
- ✅ 100% local option — zero internet, zero cost
- ✅ Works with free tiers — Groq, Ollama, LM Studio
- ✅ No subscription required
- ✅ Works natively inside VS Code
Quick Start
1. Install Airvo
pip install airvo
2. Start the server
airvo start
That's it. Airvo will:
- Create your config at
~/.airvo/models.json - Auto-configure continue.dev at
~/.continue/config.yaml - Open the dashboard at
http://localhost:5000
3. Add your first model
Open the dashboard → Add Model → fill in the model details → Save.
Not sure where to start? Add Groq — it's free and fast:
- Model ID:
groq/llama-3.3-70b-versatile - Provider:
groq - API Key: get one free at console.groq.com — no credit card required
4. Install continue.dev in VS Code
Install the Continue extension from the VS Code marketplace. Airvo already configured it for you.
5. Start coding
Open VS Code → press Ctrl+L → ask anything.
Features
🤖 Any Model, Any Provider Add any model supported by LiteLLM — over 100 providers. Groq, OpenAI, Anthropic, Ollama, LM Studio, DeepSeek, Mistral, Gemini, and more.
⚡ Multi-Model Modes Run up to 3 models simultaneously in 4 modes: Parallel (see all answers), Race (fastest wins), Vote (consensus), Review (one generates, others refine).
🔒 100% Local Option Use Ollama or LM Studio with no API key, no internet, no cost. Your code never leaves your machine.
🎛️ Visual Dashboard
Manage models, configure API keys, toggle models on/off — all from a clean dark UI at localhost:8765.
🧠 Project Context Write your stack, preferences and constraints once. Airvo injects it into every request so the model always knows your project — without you repeating yourself.
🌡️ Tunable Behavior Adjust temperature (0.0 → 1.0) and max tokens per request directly from the dashboard. Precise and deterministic for code, creative for brainstorming.
📊 Usage Stats See requests and tokens used per model — all stored locally. Know exactly what you're using and reset anytime.
🌍 7 Languages Dashboard available in English, Español, Français, Deutsch, 中文, 日本語, Português.
🔌 VS Code Native Works through continue.dev — chat, edit, and apply code changes without leaving your editor.
Supported Models
| Provider | Model ID | Free | Notes |
|---|---|---|---|
| Groq | groq/llama-3.1-8b-instant |
✅ | Fast, free tier |
| Groq | groq/llama-3.3-70b-versatile |
✅ | Powerful, free tier |
| OpenAI | openai/gpt-4o |
❌ | Requires API key |
| OpenAI | openai/gpt-4o-mini |
❌ | Cheaper option |
| Anthropic | anthropic/claude-sonnet-4-5 |
❌ | Requires API key |
| Anthropic | anthropic/claude-haiku-4-5 |
❌ | Fastest Claude |
| Ollama | ollama/llama3 |
✅ | 100% local |
| Ollama | ollama/codellama |
✅ | Code-optimized |
| LM Studio | lmstudio/local |
✅ | 100% local |
| DeepSeek | deepseek/deepseek-chat |
❌ | Very affordable |
| Mistral | mistral/mistral-large-latest |
❌ | Requires API key |
| Gemini | gemini/gemini-1.5-pro |
❌ | Requires API key |
Any model supported by LiteLLM works with Airvo.
Dashboard
The Airvo dashboard runs at http://localhost:5000 and lets you manage everything visually.
Models page — activate/deactivate models, save API keys, see requests and tokens per model.
Configuration page — set multi-model mode, adjust temperature and max tokens, enable project context, view usage stats.
Add Model page — add any model with contextual tooltips on every field.
Help page — full reference guide, field-by-field documentation, FAQ.
Multi-Model Modes
Airvo supports running multiple models at once. Configure the mode in the Configuration page.
Parallel (default) — All active models respond to every message. See all answers side by side. Best for comparing outputs.
Race — All models receive the message simultaneously. The first to finish wins. Best for speed.
Vote — Models generate responses and the consensus answer is shown. Best for accuracy.
Review — One model generates a response, another critiques it. Best for quality.
VS Code Integration
Airvo works through continue.dev — a VS Code extension for AI-assisted coding.
What you can do:
Chat → ask questions, get explanations, generate code
Edit → select code and ask Airvo to modify it
Apply → apply suggested changes directly in your file
The continue.dev config is created automatically by airvo start:
models:
- name: Airvo
provider: openai
model: airvo-auto
apiBase: http://localhost:5000/v1
apiKey: local
roles:
- chat
- edit
- apply
Configuration
CLI options
airvo start # default: localhost:5000, opens browser
airvo start --port 9000 # custom port
airvo start --host 0.0.0.0 # accessible from local network
airvo start --no-browser # don't open browser automatically
airvo start --reload # hot reload (development)
airvo config --show # show current config
airvo version # show version
Models config — stored at ~/.airvo/models.json
[
{
"id": "groq/llama-3.3-70b-versatile",
"name": "Llama 3.3 70B (Groq)",
"provider": "groq",
"api_key": "your-api-key",
"base_url": null,
"active": true,
"notes": "More powerful, still free"
}
]
Adding a local model (Ollama)
# 1. Install Ollama from ollama.com
# 2. Pull a model
ollama pull llama3
# 3. Add it in the Airvo dashboard
# Model ID: ollama/llama3
# Provider: ollama
# Base URL: http://localhost:11434
# API Key: (leave empty)
Use Cases
Generate a function
"create a Python function that validates an email address with regex"
→ Airvo generates the function with tests
→ click Apply to add it directly to your file
Explain legacy code
"explain what this function does and why it might be slow"
→ if you have two models active, both analyze in parallel
→ you see both perspectives and choose the best explanation
Refactor on the fly
select code → "refactor this to use async/await"
→ Airvo rewrites it
→ Apply the change with one click
100% offline workflow
add ollama/llama3 → no API key, no internet, no cost
→ full AI coding experience with zero data leaving your machine
Roadmap
v0.2.0 — Available now
- ✅ Local FastAPI server with OpenAI-compatible API
- ✅ LiteLLM integration — any provider, any model
- ✅ Multi-model parallel mode — up to 3 models simultaneously
- ✅ Race mode — fastest model wins
- ✅ Vote mode — consensus from all models
- ✅ Review mode — chain refinement across models
- ✅ Continue.dev integration for VS Code
- ✅ Visual dashboard with 7 languages
- ✅ CLI —
pip install airvo && airvo start - ✅ Temperature and max tokens — configurable from dashboard
- ✅ Project Context — inject your stack into every request
- ✅ Usage stats — requests and tokens per model, stored locally
What's next
We're working on the next phase of Airvo. If you want to be the first to know:
→ ⭐ Star this repo to follow updates → 💬 Open an issue and tell us what you'd like to see
Security
Airvo is designed with privacy and security in mind:
- API keys stay local — stored in
~/.airvo/models.jsonon your machine, never sent to Airvo servers - Localhost only — the server listens on
localhost:5000by default, not accessible from the internet - Restricted CORS — only the dashboard and VS Code extensions can make requests to the server
- No telemetry — Airvo collects no usage data, no analytics, no crash reports
- Open source — the full source code is on GitHub, you can audit everything
FAQ
How do I add a model? Open the dashboard → Add Model → fill in the Model ID, Provider, and API Key → Save. Any model supported by LiteLLM works. Check the Supported Models table for examples.
How do I run multiple models? Add models in the dashboard and activate them. Airvo supports up to 3 active models simultaneously. Choose your mode in Configuration: Parallel, Race, Vote, or Review.
What is the Model ID format?
It follows LiteLLM's format: provider/model-name. For example: groq/llama-3.3-70b-versatile, openai/gpt-4o, ollama/llama3. Check the LiteLLM docs for the full list.
Do I need to pay for anything? Airvo itself is free. You only pay for the AI models you use. Groq, Ollama, and LM Studio all have free options.
Does my code get sent to the cloud? Only when you use cloud models (OpenAI, Anthropic, etc.) — and only the specific code you include in your message. When using local models (Ollama, LM Studio), nothing leaves your machine.
Where are my API keys stored?
Locally in ~/.airvo/models.json on your machine. They are never sent anywhere except to the model provider when making requests.
Can I use any model? Yes — any model supported by LiteLLM works with Airvo. Over 100 providers.
How do I get a free Groq API key? Go to console.groq.com, sign up, and create an API key. No credit card required.
How do I add a local model like Ollama?
Install Ollama, pull a model with ollama pull llama3, then add it in the dashboard with Model ID ollama/llama3, Provider ollama, Base URL http://localhost:11434, and leave the API Key empty.
Can I run Airvo on a local network?
Yes — run airvo start --host 0.0.0.0 and it will be accessible from any device on your network.
Airvo is not connecting to VS Code — what do I do?
Make sure continue.dev is installed in VS Code and that airvo start has run at least once to create the config. You can verify the config exists at ~/.continue/config.yaml.
Community
Airvo is early. Your feedback shapes what comes next.
- 🐛 Found a bug? Open an issue
- 💡 Have an idea? Start a discussion
- ⭐ Liked Airvo? Star the repo — it helps a lot
License
MIT — see LICENSE for details.
Built for developers who want AI that works for them — not the other way around.
Your AI. Your Rules.
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
File details
Details for the file airvo-0.2.0.tar.gz.
File metadata
- Download URL: airvo-0.2.0.tar.gz
- Upload date:
- Size: 101.5 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.2.0 CPython/3.12.0
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
e76e4544a47d28731115b612ece7af11f7860c9ae962148b0a5dcb8700813295
|
|
| MD5 |
93f02ca0639d3bab6e20b876ce66be95
|
|
| BLAKE2b-256 |
ed89348b7ab680c7e4e8115535f90e77ddd4add903898a5de4732d2fa6eae53d
|
File details
Details for the file airvo-0.2.0-py3-none-any.whl.
File metadata
- Download URL: airvo-0.2.0-py3-none-any.whl
- Upload date:
- Size: 96.4 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.2.0 CPython/3.12.0
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
66015431f404dd595b3c37146e4547d7ed72d9583488fbe2e8e8ea03e4741623
|
|
| MD5 |
b6defaf7b9290801ef4d6839dd0392eb
|
|
| BLAKE2b-256 |
bc8ee4717150880c3ea40384cf2d4885cadbd5fb446a9dbdff9c8ef8f57f9357
|