ai-studio
Health Uyari
- License — License: AGPL-3.0
- Description — Repository has a description
- Active repo — Last push 0 days ago
- Low visibility — Only 5 GitHub stars
Code Basarisiz
- rm -rf — Recursive force deletion command in .github/workflows/ui-tests.yml
Permissions Gecti
- Permissions — No dangerous permissions requested
This tool is an open-source AI gateway and management platform designed to help organizations securely proxy, govern, and monitor their AI usage across multiple vendors. It helps developers manage costs, access controls, and compliance in a single interface.
Security Assessment
As an AI gateway, this tool inherently processes highly sensitive data, including API keys for external LLM providers and the contents of user prompts. It requires making external network requests to route traffic to services like OpenAI, Anthropic, and AWS. No hardcoded secrets or explicitly dangerous runtime permissions were detected. However, the codebase includes a recursive force deletion command (`rm -rf`) inside a GitHub Actions workflow. While this is limited to an automated UI testing environment rather than the core application, it represents a minor supply chain risk. Overall risk is rated as Medium due to the sensitive nature of the data it handles.
Quality Assessment
The project is actively maintained, with recent repository updates. It uses the standard AGPL-3.0 license and includes clear documentation and quickstart guides. However, community trust and visibility are currently very low, as indicated by only 5 GitHub stars. Developers should be aware that the project is in its early stages and lacks a large, established community to actively audit the code.
Verdict
Use with caution. Ensure you securely manage your LLM API keys and thoroughly review the repository workflows if contributing to the project.
Tyk AI Studio provides an AI gateway and comprehensive suite of capabilities to manage, govern, and interact with AI across your organization
Tyk AI Studio
Official Documentation | AI Studio Homepage | Community Forum | Contributing
Open source AI management platform for secure, governed, and scalable AI integration
Tyk AI Studio is an open source platform that addresses the critical challenges organizations face when adopting AI: shadow AI usage, compliance requirements, security concerns, and spiraling costs. Built for developers and platform teams, it provides structured AI management through governance, monitoring, and unified access controls.
Available in two editions: Community Edition (open source) and Enterprise Edition (advanced features). See edition comparison below.
Try it Now
Get a demo instance running in minutes using Docker Compose.
Community Edition (no license required):
git clone https://github.com/TykTechnologies/ai-studio.git
cd ai-studio/quickstart
docker compose -f ./ce/compose.yaml up -d
Enterprise Edition (requires license):
git clone https://github.com/TykTechnologies/ai-studio.git
cd ai-studio/quickstart
# Add your license to required.env
echo "TYK_AI_LICENSE=<your-license-key>" > required.env
docker compose -f ./enterprise/compose.yaml up -d
Once running, access the UI at http://localhost:8585
See the quickstart README for more details.
Why Tyk AI Studio?
AI adoption brings significant challenges that require structured solutions:
- Shadow AI Prevention - Stop unauthorized AI tool usage without oversight
- Security & Compliance - Maintain data privacy and meet regulatory requirements
- Cost Control - Monitor usage and prevent unlimited AI consumption
- Unified Access - Single interface for multiple AI vendors and internal tools
Core Capabilities
AI Gateway
The heart of secure AI integration, providing:
- Multi-vendor LLM support: OpenAI, Anthropic, Mistral, Vertex AI, Bedrock, Gemini, Huggingface, Ollama, and custom models
- Secure API proxying: Centralized access control and credential management
- Usage monitoring: Real-time tracking of costs, usage patterns, and performance
- Rate limiting: Prevent excessive token consumption and manage budgets
- Content filtering: Scriptable policy enforcement for data security
AI Portal
Developer-focused service catalog featuring:
- Curated AI services: Easy discovery and access to approved AI tools
- Unified interface: Single point of access for all AI capabilities
- Integration support: Connect with internal systems and external workflows
- Rapid prototyping: Secure experimentation with built-in policy controls
AI Chat Interface
Collaborative workspace that provides:
- Universal chat experience: Single interface for LLMs, tools, and internal data sources
- Custom chatrooms: Dedicated spaces for teams, projects, or specific use cases
- Built-in governance: Policy enforcement without disrupting user workflows
- Document integration: Upload and use documents within AI conversations
MCP Integration
Standards-based AI component integration:
- Remote MCP support: Connect internal APIs and tools without custom scripts
- Local MCP servers: Generate installable servers for testing or restricted environments
- Standardized interactions: Following Model Context Protocol specifications
- Secure connections: All MCP traffic routed through the AI Gateway for visibility
Real-World Applications
Software Development
- Integrate AI with Jira, GitHub, and internal development tools
- Accelerate development cycles with AI-powered assistance
- Maintain security while enabling developer productivity
Financial Services
- Ensure only anonymized data reaches external LLMs
- Track AI usage costs by department or team
- Meet compliance requirements while enabling innovation
Healthcare
- Route LLM traffic through governed pathways for HIPAA compliance
- Protect sensitive patient data with content filtering
- Enable AI-driven insights while maintaining privacy controls
General Business Applications
- Query internal APIs and databases through conversational interfaces
- Integrate AI with existing business systems and workflows
- Enable non-technical users to leverage AI capabilities safely
First Time Setup
For absolute first-timers who want to build from source:
Prerequisites
- Go 1.22+
- Node.js 18+
- Git
Initial Setup Steps
- Clone the repository
git clone https://github.com/TykTechnologies/ai-studio.git
cd ai-studio
- Install frontend dependencies
cd ui/admin-frontend
npm install
- Build the frontend (required for Go embedding)
npm run build
- Return to project root and build backend
cd ../../
go build
- Setup environment
cp .env.example .env
# Edit .env file with your AI provider credentials
- Run the application
./ai-studio
Important: If you try to run go build without first building the frontend, you'll get an error about empty directories because the Go application embeds the frontend build assets. Always build the frontend first.
Edition Comparison
Tyk AI Studio is available in two editions:
| Feature | Community Edition | Enterprise Edition |
|---|---|---|
| LLM Proxy Gateway | ✅ | ✅ |
| Chat Interface | ✅ | ✅ |
| Tool Integration | ✅ | ✅ |
| User Management & RBAC | ✅ | ✅ |
| Hub-and-Spoke Deployment | ✅ | ✅ |
| Cost Tracking & Analytics | ✅ | ✅ |
| Plugin System | ✅ | ✅ |
| Budget Management | ❌ | ✅ |
| Budget Enforcement | ❌ | ✅ |
| Budget Alerts | ❌ | ✅ |
| Advanced SSO (SAML, OIDC) | ❌ | ✅ |
| Advanced RBAC | ❌ | ✅ |
| Audit Logging | ❌ | ✅ |
| Priority Support | ❌ | ✅ |
Community Edition
Free and open source. Perfect for:
- Development and testing
- Small teams
- Cost visibility without enforcement
- Learning AI management
Enterprise Edition
Advanced features for production. Ideal for:
- Production deployments
- Cost control and governance
- Compliance requirements
- Enterprise SSO integration
Learn more about Enterprise Edition →
For detailed framework documentation, see ENTERPRISE_FRAMEWORK.md
Quick Start
Get up and running in under 5 minutes:
Option 1: Docker (Recommended)
- Clone and setup
git clone https://github.com/TykTechnologies/ai-studio.git
cd ai-studio
cp .env.example .env
Configure environment
Edit.envfile with your AI provider credentials and desired settings.Start the platform
docker compose up --build
- Access the interface
- UI: http://localhost:3000
- API: http://localhost:8080
- Proxy: http://localhost:9090
When you first register, your account will automatically become admin with a default user group created.
Option 2: Native Development
Prerequisites
- Go 1.22+
- Node.js 18+
- Clone the langchaingo fork: https://github.com/lonelycode/langchaingo
Start development servers
make start-dev # Starts both frontend and backend
make stop-dev # Stops both services
Installation Options
Docker
# Production deployment
docker compose up -d
# Development with hot reload
docker compose up --build
Kubernetes
# Using Helm (if available)
helm install ai-studio ./helm
# Using kubectl
kubectl apply -f k8s/
Native Binary
# Build production binary
make build
# The binary includes both API and UI
./ai-studio
Architecture
Tyk AI Studio follows a clean three-tier architecture:
Model Layer: Data structures and database-level CRUD operations
Service Layer: Business logic and data access to the model layer
API Layer: REST interface to the service layer
Frontend Structure:
- Admin: Managing AI models, tools, and data sources
- Portal: User interface for interacting with AI models and tools
The AI Gateway sits at the center, proxying all AI interactions while enforcing policies, monitoring usage, and maintaining security controls.
Plugin System
Tyk AI Studio features a powerful Unified Plugin SDK that enables extensive customization and integration across the entire platform. Plugins run as isolated processes using gRPC communication, providing security and fault tolerance.
Plugin Capabilities
Build plugins that extend AI Studio in multiple ways:
Gateway Extensions
- Custom authentication and authorization
- Request/response transformation and filtering
- Content policy enforcement
- Data export to external systems (Elasticsearch, ClickHouse, etc.)
- Custom rate limiting and budget controls
UI Extensions
- Add custom pages and dashboards to the admin interface
- Extend sidebar navigation with new sections
- Build interactive WebComponents with full JavaScript framework support
- Access platform APIs to manage LLMs, apps, tools, and datasources
Conversational AI Agents
- Create custom chat agents with specialized behaviors
- Wrap LLMs with custom logic and validation
- Integrate external services into conversations
- Build multi-turn dialogue experiences with tool access
Object Hooks
- Intercept CRUD operations on LLMs, tools, datasources, and users
- Enforce validation rules and approval workflows
- Integrate with external systems (LDAP, ticketing, CMDBs)
- Add audit trails and policy enforcement
Key Features
- Single SDK: One import works everywhere (AI Studio and Microgateway)
- 10 Plugin Capabilities: Mix and match to build exactly what you need
- Secure Isolation: Plugins run as separate processes
- Fine-grained Permissions: Control access with declarative scopes
- Multiple Deployment Options: Local files, remote gRPC, or OCI containers
Quick Start
import "github.com/TykTechnologies/midsommar/v2/pkg/plugin_sdk"
type MyPlugin struct {
plugin_sdk.BasePlugin
}
func (p *MyPlugin) HandlePostAuth(ctx plugin_sdk.Context, req *plugin_sdk.EnrichedRequest) (*plugin_sdk.Response, error) {
// Your custom logic here
return &plugin_sdk.Response{Modified: false}, nil
}
func main() {
plugin_sdk.Serve(NewMyPlugin())
}
Learn More: See Plugin System Documentation for comprehensive guides, examples, and API references.
Supported AI Vendors
- OpenAI: GPT models, Embeddings, and more
- Anthropic: Claude models and assistants
- Mistral: Open source and commercial models
- Google: Vertex AI and Gemini models
- AWS: Bedrock model access
- Hugging Face: Open source model ecosystem
- Ollama: Local model deployment
- Custom Models: Bring your own model integrations
Key Benefits
- Reduce Risk - Centralized access controls and comprehensive monitoring
- Improve Efficiency - Streamlined workflows for both developers and end users
- Cost Control - Real-time usage tracking with budgeting and rate limiting
- Support Compliance - Built-in policy enforcement and audit logging
- Enable Scale - Standards-based architecture supporting growth
Documentation & Resources
Official Documentation
Product Information
Developer Resources
Configuration
All configuration is managed through the .env file. Key settings include:
# AI Provider Credentials
OPENAI_API_KEY=your-openai-key
ANTHROPIC_API_KEY=your-anthropic-key
# Database Configuration
DATABASE_URL=your-database-url
# Telemetry (Optional)
TELEMETRY_ENABLED=false # Disable usage statistics collection
Privacy Note: Tyk AI Studio collects anonymized usage statistics to improve the platform. No personal data or AI conversation content is collected. Set TELEMETRY_ENABLED=false to disable.
Development
Building from Source
Manual build process (step by step):
# 1. Install frontend dependencies (if not done already)
cd ui/admin-frontend
npm install
# 2. Build frontend assets (required before Go build)
npm run build
# 3. Return to root and build backend
cd ../../
go build
# 4. Run the application
./ai-studio
Using Make commands (automated):
# Build everything (frontend + backend)
make build
# Build for local development only
make build-local
# Run tests
make test
# Clean build artifacts
make clean
Build Order Important: The frontend must be built before the Go binary because the application embeds frontend assets. Running go build without building the frontend first will fail with empty directory errors.
Version and Build Tagging
Version information is injected at build time via Go linker flags (-ldflags -X). The variables are defined in version.go:
| Variable | Description | Default |
|---|---|---|
main.Version |
Release version (from git tag) | dev |
main.BuildHash |
Git commit hash | unknown |
main.BuildTime |
Build timestamp (UTC) | unknown |
How version is set across build methods:
| Build Method | Version Source |
|---|---|
make build-native / make build-prod |
git describe --tags --always --dirty |
Dockerfile |
--build-arg VERSION=... |
build-commands.sh (pre-release) |
git describe --tags --always |
| GoReleaser (CI release) | Git tag via {{.Version}} |
make dev (Air hot reload) |
Default dev |
To verify the version embedded in a binary, check the startup output:
Starting Tyk AI Studio v2.1.0
When tagging a release, create a git tag and the version will propagate automatically:
git tag v2.1.0
git push origin v2.1.0
Additional Commands
make start-frontend # Frontend development server only
make start-backend # Backend development server only
make stop-frontend # Stop frontend server
make stop-backend # Stop backend server
Testing
The project has multiple test categories with different build tags. Here's how to run them:
Quick Test Commands
# Run all standard unit tests (fastest)
go test ./...
# Run tests for a specific package
go test ./api/...
# Run tests with coverage report
go test -coverprofile=coverage.out -coverpkg=./... ./...
go tool cover -html=coverage.out # View in browser
Complete Test Suite
To validate everything before a release or major change:
# 1. Unit tests (no special tags required)
go test ./...
# 2. Enterprise feature tests
go test -tags enterprise ./...
# 3. Integration tests (requires test environment)
go test -tags integration ./...
# 4. Plugin E2E tests (builds and spawns real plugin binaries)
go test -tags e2e ./pkg/testinfra/plugintest/...
# 5. All tests combined (comprehensive validation)
go test -tags "enterprise,integration,e2e" ./...
Test Categories Explained
| Category | Build Tag | Description | Speed |
|---|---|---|---|
| Unit | (none) | Standard tests, no external deps | Fast |
| Enterprise | enterprise |
Tests for enterprise-only features | Fast |
| Integration | integration |
Tests requiring DB/services | Medium |
| E2E Plugin | e2e |
Spawns real plugin subprocesses | Slow |
Plugin Contract Tests
The plugin test framework validates UI-to-RPC contracts without building plugins:
# Fast contract validation (no plugin build)
go test -v ./pkg/testinfra/plugintest/... -run "TestAdvancedLLMCacheUIContract"
CI/CD Recommendation
For CI pipelines, we recommend:
# Fast feedback (every PR)
- run: go test ./...
# Pre-merge validation
- run: go test -tags enterprise ./...
# Nightly/release validation
- run: go test -tags "enterprise,integration,e2e" ./...
Community & Support
Get Help
- Community Forum - Technical support and discussions
- GitHub Issues - Bug reports and feature requests
- Official Documentation - Comprehensive guides and references
Contributing
We welcome contributions! Please see our Contributing Guide for details on how to:
- Report bugs and request features
- Submit pull requests
- Sign the Contributor License Agreement
- Join our development community
Licensing
Tyk AI Studio is released under the GNU Affero General Public License v3.0. See LICENSE.md for full details.
Contributor License Agreement: All contributors must sign the Tyk CLA before contributions can be accepted.
Project Status
Tyk AI Studio is actively developed and maintained by Tyk Technologies. It serves as the open source foundation for Tyk's AI management ecosystem.
Stability: Production ready for AI gateway and basic management features
Development: Active development with regular releases
Community: Welcoming contributions and feedback from the community
Built by Tyk
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