vtai 0.7.9

VT.ai - Minimal multimodal AI chat app with dynamic conversation routing

VT.ai

VT.ai is an open-source multimodal AI chat application with dynamic conversation routing. Supports multiple LLM providers with semantic-based routing and comprehensive multimodal capabilities.

Installation

Native Installer (Recommended)

• Automatic Python 3.11 setup
• Installs uv package manager (faster than pip)
• Creates isolated virtual environment
• Installs all dependencies including Chainlit
• Interactive API key configuration
• Auto-launches VT.ai after installation

Linux & macOS:

curl -fsSL https://raw.githubusercontent.com/vinhnx/VT.ai/main/scripts/install_and_run.sh | bash
# Or skip API key configuration
curl -fsSL https://raw.githubusercontent.com/vinhnx/VT.ai/main/scripts/install_and_run.sh | bash -s -- --no-api-config

Windows (PowerShell):

git clone https://github.com/vinhnx/VT.ai.git
cd VT.ai
.\scripts\install_and_run.bat

Alternative Installation Methods:

# PyPI (standard installation)
pip install vtai

# With uv (faster)
uv pip install vtai

# Try without installing
uvx --python 3.11 vtai

See Installation Guide and Security Notice for more options and troubleshooting.

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Usage

# Set your API key
export OPENAI_API_KEY="sk-..."

# Launch VT.ai
vtai

The application will open in your default browser at http://localhost:8000.

Command-Line Usage

# Start the application
vtai

# Show version
vtai --version

# Show help
vtai --help

# Configure API keys
vtai --api-key openai=sk-...

Supported Providers: openai, anthropic, gemini, deepseek, ollama

Capabilities

Multimodal Support

VT.ai provides comprehensive multimodal capabilities:

• Text Chat: Natural conversations with multiple AI models
• Image Generation: Create images with DALL-E 3 and GPT-Image-1
• Visual Analysis: Upload and analyze images with vision models
• Voice Interaction: Speech-to-text and text-to-speech with configurable voices
• Web Search: Real-time information retrieval with Tavily API
• Reasoning Visualization: Step-by-step thinking with <think> tag

Semantic Routing

VT.ai uses vector-based semantic routing to automatically direct queries to the most appropriate model:

• Fast Classification: Uses FastEmbed embeddings for instant routing decisions
• No Manual Selection: Automatic model selection based on query intent
• Optimized Performance: Reduces latency by avoiding unnecessary LLM calls
• Custom Routes: Extensible routing system for specialized use cases

For more information about capabilities, see Usage Guide.

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Supported Providers

VT.ai works with OpenAI, Anthropic, Google Gemini, DeepSeek, Cohere, Ollama (local), and more. Set the corresponding environment variable for your provider:

export OPENAI_API_KEY="sk-..."        # OpenAI (GPT-o1, GPT-o3, GPT-4o)
export ANTHROPIC_API_KEY="sk-ant-..." # Anthropic (Claude 3.5/3.7)
export GEMINI_API_KEY="..."           # Google (Gemini 2.0/2.5)
export DEEPSEEK_API_KEY="..."         # DeepSeek models

See Provider Configuration for complete setup instructions.

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Configuration

VT.ai supports flexible configuration options:

API Key Management:

• Environment Variables: Session-only configuration
• Command-Line: vtai --api-key provider=key
• Persistent Storage: Securely stored in ~/.config/vtai/.env

Model Selection:

• Automatic routing based on query semantics
• Manual override via conversation profiles
• Custom model aliases in configuration

For full configuration options, see Configuration Guide.

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Key Features

• Multi-Provider Integration: Unified access to models from OpenAI, Anthropic, Google, DeepSeek, and local models via Ollama
• Semantic Routing System: Vector-based classification using FastEmbed embeddings for automatic model selection
• Multimodal Capabilities: Text, image, and audio inputs with advanced vision analysis
• Image Generation: GPT-Image-1 integration with transparent backgrounds, multiple formats, and quality parameters
• Web Search Integration: Real-time information retrieval with source attribution via Tavily API
• Voice Processing: Advanced speech-to-text and text-to-speech with configurable voice options
• Reasoning Visualization: Step-by-step model reasoning with <think> tag for transparent decision processes
• Security First: All dependencies regularly updated with automated vulnerability scanning

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Security & Safety

VT.ai implements a security-first approach to protect users and their data:

Dependency Security:

• Automated Scanning: Dependabot integration for vulnerability detection
• Regular Updates: All dependencies kept at latest secure versions
• Override Dependencies: Force secure versions for transitive dependencies
• Version Pinning: Critical dependencies pinned to known-safe versions

Data Protection:

• Local Storage: API keys stored locally in ~/.config/vtai/.env
• No Data Collection: No telemetry or data collection by default
• Secure Defaults: Conservative security settings out of the box
• Workspace Isolation: All operations confined to workspace boundaries

Latest Security Release (v0.7.5):

• Fixed 25 vulnerabilities in dependencies
• Updated aiohttp, cryptography, mcp, PyJWT, black, onnx, and pillow
• Added uv override-dependencies for transitive security fixes

See Security Information for complete details.

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Docs & Examples

• Getting Started
  • Installation Guide
  • Quick Start
  • Configuration
• Security Information
  • Latest Security Release
  • Vulnerability Details
  • Upgrade Instructions
• Usage Guide
  • Chat Interface
  • Image Generation
  • Visual Analysis
  • Voice Features
• Provider Guides
  • OpenAI Setup
  • Anthropic Setup
  • Google Gemini Setup
• Developer Guide
  • Architecture Overview
  • Semantic Routing
  • Extension Points
• API Reference
  • Module Documentation
  • Conversation Handlers
  • Router Components
• Troubleshooting
  • Common Issues
  • FAQ

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Command-Line Reference

# Basic usage
vtai

# Show version
vtai --version

# Show help
vtai --help

# Configure API keys
vtai --api-key <provider>=<key>

# Supported providers
vtai --api-key openai=sk-...
vtai --api-key anthropic=sk-ant-...
vtai --api-key gemini=...

Environment Variables:

export OPENAI_API_KEY="sk-..."
export ANTHROPIC_API_KEY="sk-ant-..."
export GEMINI_API_KEY="..."
vtai

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Supported Models

Category	Models
Chat	GPT-o1, GPT-o3 Mini, GPT-4o, Claude 3.5/3.7, Gemini 2.0/2.5
Vision	GPT-4o, Gemini 1.5 Pro/Flash, Claude 3, Llama3.2 Vision
Image Gen	GPT-Image-1 with custom parameters
TTS	GPT-4o mini TTS, TTS-1, TTS-1-HD
Local	Llama3, Mistral, DeepSeek R1 (1.5B to 70B via Ollama)

See Models Documentation for detailed model capabilities and configuration.

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Technical Architecture

VT.ai leverages several open-source projects:

• Chainlit: Modern chat interface framework
• LiteLLM: Unified model abstraction layer
• SemanticRouter: Intent classification system
• FastEmbed: Efficient embedding generation
• Tavily: Web search capabilities

Architecture Components:

• Entry Point: vtai/app.py - Main application logic
• Routing Layer: vtai/router/ - Semantic classification system
• Assistants: vtai/assistants/ - Specialized handlers
• Tools: vtai/tools/ - Web search, file operations, integrations

See Architecture Documentation for details.

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Contributing

I warmly welcome contributions of all kinds! Whether you're looking to fix bugs, add new features, improve documentation, or enhance the user experience, your help is greatly appreciated.

How To Contribute:

• Report issues you're experiencing
• Suggest new features or improvements
• Help answer questions in the issue tracker
• Improve documentation or add examples

If you're not sure where to start:

• Check out the issues page
• Look for good first issue labeled items
• Feel free to browse all open issues and pick one that resonates with you!

Steps to get started:

1. Fork the repository by clicking the Fork button in the top-right corner
2. Clone your forked repository to your local machine
3. Create a new branch for your changes
4. Start contributing!

When reporting an issue, please include enough details for others to reproduce the problem effectively.

See CONTRIBUTING.md for detailed guidelines.

Development

Type Checking

This project uses ty for static type checking. ty is a fast type checker developed by Astral (the creators of ruff and uv).

# Run type checking
./scripts/type-check.sh

# Or directly with uv
uv run ty check vtai

Why ty?

• Extremely fast type checking (10-100x faster than mypy)
• Zero configuration needed
• Works seamlessly with ruff for linting
• Native uv integration

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Recent Releases

v0.7.8 (April 2, 2026) - CLI Enhancement

New command-line interface with instant version and help flags.

• Added dedicated vtai.cli module for command-line interface
• --version / -v flag shows version without loading the full app (instant response)
• --help / -h flag displays usage information (instant response)
• Improved CLI entry point separation for faster startup
• Refactored vtai.app to extract run_app() function

View full release notes

v0.7.5 (April 2, 2026) - Security Release

Critical security update addressing 25 vulnerabilities in dependencies.

• Fixed high-severity CVEs in aiohttp, cryptography, mcp, PyJWT, black, onnx, and pillow
• Added uv override-dependencies for transitive security fixes
• Pinned Python version to 3.11.x for stable dependency resolution

View full release notes

v0.7.4

• Optimized URL extraction and async file handling
• Enhanced router training capabilities
• Improved LLM provider configuration

View all releases

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Star History

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License

VT.ai is available under the MIT License.