airvo 0.3.4

Your local AI coding copilot — any model, any provider, zero cloud.

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.

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Table of Contents

• What is Airvo?
• Quick Start
• Features
• Supported Models
• Dashboard
• Multi-Model Modes
• VS Code Integration
• Configuration
• Use Cases
• Security
• FAQ
• Community
• License

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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
• ✅ Smart Memory (RAG) — semantic search of your codebase, 100% local
• ✅ Memory Manager — real-time RAM/GPU usage, Ollama model rotation
• ✅ Model Discovery — browse and add Ollama + OpenRouter models in one click
• ✅ 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

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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.

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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:5000.

🧠 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.

🔍 Smart Memory (RAG) Airvo indexes your codebase locally using AI embeddings (all-MiniLM-L6-v2). Before each request, it automatically finds the most relevant files and injects them into the context — no copy-pasting. Runs 100% on your machine, nothing sent to the cloud. Enable it in Configuration → Smart Memory.

🖥️ Memory Manager Real-time RAM and GPU usage visible right in the Status page. See which Ollama models are currently loaded, get intelligent suggestions when memory is under pressure, and unload models with a single click — no terminal needed.

🔭 Model Discovery Browse a curated catalog of Ollama-compatible models filtered by what fits in your RAM. Explore OpenRouter's full model library (free models highlighted). Add any model to Airvo with one click.

🌡️ 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.

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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.

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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, configure Smart Memory (RAG), 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.

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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.

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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

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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)

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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

Smart Memory — ask about your own code

enable Smart Memory → index your project folder
→ "how does the authentication flow work in this project?"
→ Airvo finds the relevant files automatically and answers with context
→ no copy-pasting, no manual file selection

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Security

Airvo is designed with privacy and security in mind:

• API keys stay local — stored in ~/.airvo/models.json on your machine, never sent to Airvo servers
• Localhost only — the server listens on localhost:5000 by 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

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FAQ

What is Smart Memory (RAG)? Smart Memory indexes your codebase locally using AI embeddings. Before each request, Airvo finds the most semantically relevant code chunks and injects them into the prompt automatically. Enable it in Configuration → Smart Memory, point it to your project folder, and click Index Now. The embedding model (~90 MB) downloads once and runs entirely on your machine.

Does Smart Memory send my code to the cloud? Never. The embedding model (all-MiniLM-L6-v2) runs 100% on your machine. The index is stored in ~/.airvo/rag/ and your code never leaves your computer.

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.

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Changelog

v0.3.2 — Fix README image URLs for PyPI

• Fixed all image paths to absolute GitHub raw URLs so screenshots and logo display correctly on PyPI.

v0.3.1 — Agent/Plan model selector, IPv6 fix, UI improvements

• Agent/Plan Model selector — choose which active model handles Agent/Plan (tool call) requests from continue.dev. Configured in the Configuration page.
• Server IPv6 fix — server now binds to 127.0.0.1 explicitly; .env PORT is correctly loaded on startup.
• Dashboard — relative API URLs (no hardcoded host), CORS accepts any localhost port.
• UI — Agent/Plan mode badge in header, Discovery info boxes, RAM badge tooltips, step-by-step workflow, Chat History Limit config, expanded Help page (7 languages).

v0.3.0 — Smart Memory, Memory Manager, Model Discovery

• Smart Memory (RAG) — semantic codebase indexing with sentence-transformers + ChromaDB, 100% local. Enable in Configuration.
• Memory Manager — real-time RAM/GPU monitoring via psutil, Ollama model detection, intelligent unload suggestions and one-click model rotation in the Status page.
• Model Discovery — curated Ollama catalog with RAM fit detection + full OpenRouter model browser (60 models, free-first sorting). Quick-add any model to Airvo from the Models page.

v0.2.0 — Multi-model modes, tool calling, continue.dev integration, 7-language dashboard

v0.1.0 — Initial release: single-model proxy, FastAPI server, basic dashboard

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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

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License

MIT — see LICENSE for details.

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Built for developers who want AI that works for them — not the other way around.

Your AI. Your Rules.