How Together AI works

Together AI makes it easy to run leading open-source models using only a few lines of code. The platform provides fast inference, OpenAI-compatible APIs, and access to cutting-edge models like Llama 4, DeepSeek, and more. Built for developers who need reliable, scalable AI infrastructure without the complexity.

Recommended Models

We recommend good coding models with high context windows and competitive pricing.

Creating API Key

Go directly to Together AI Console to create a new API Key.

Or, follow these steps:

1. Create an account at api.together.ai or log in if you have one already
2. In the main dashboard, scroll down to the “Manage Account” section
3. In the “API Keys” card, click on “Manage Keys” button
4. Click on “Add Key” button
5. Give it a name like ‘Mesrai’ or any descriptive name
6. Copy your API key, and you’re ready to go!

How to use

System Requirements

Domain Name Setup (Optional)

If you’re planning to integrate Mesrai with cloud-based Git providers (GitHub, GitLab, or Bitbucket), you’ll need public-facing URLs for both the Mesrai Web App and its API. This allows your server to receive webhooks for proper Code Review functionality and ensures correct application behavior.

We recommend setting up two subdomains:

• One for the Web Application, e.g., mesrai-web.yourdomain.com.
• One for the API, e.g., mesrai-api.yourdomain.com.

Webhooks are handled by a separate service (port 3332). You can either:

• Use a dedicated webhooks subdomain, e.g., mesrai-webhooks.yourdomain.com, or
• Keep using the API domain and route /github/webhook, /gitlab/webhook, etc. to the webhooks service in your reverse proxy.

Both subdomains should have DNS A records pointing to your server’s IP address. Later in this guide, we will configure a reverse proxy (Nginx) to route requests to these subdomains to the correct internal services. This setup is essential for full functionality, including webhooks and authentication.

Note: If you’re only connecting to self-hosted Git tools on your network and do not require public access or webhooks, you might be able to use a simpler setup, but this guide focuses on public-facing deployments.

Setup

1. 1

   Clone the installer repository

   git clone https://github.com/mesraiofficial/mesrai-installer.git
   cd mesrai-installer
2. 2

   Copy the example environment file

   cp .env.example .env
3. 3

   Generate secure keys for the required environment variables

   ./generate-keys.sh
4. 4

   Edit the environment file

   Edit .env with your values using your preferred text editor.

   nano .env

   See Environment Variables Configuration for detailed instructions.

5. 5

   Run the installer

   ./scripts/install.sh
6. 6

   Success 🎉

   When complete, Mesrai Services should be running on your machine. You can verify your installation using the following script:

   ./scripts/doctor.sh
7. 7

   Access the web interface

   Once you access the web interface for the first time, you’ll need to:

   1. Create your admin account - This will be the first user with full system access
   2. Configure your Git provider - Connect GitHub, GitLab, or Bitbucket following the on-screen instructions
   3. Select repositories for analysis - Choose which code repositories Mesrai will review

   For detailed steps on the initial configuration process, refer to our Getting Started Guide.

Configure Together AI in Environment File

Edit your .env file and configure the core settings. For LLM Integration, use Together AI in Fixed Mode:

# Core System Settings (update with your domains)
WEB_HOSTNAME_API="mesrai-api.yourdomain.com"    
WEB_PORT_API=443                               
NEXTAUTH_URL="https://mesrai-web.yourdomain.com"

# Security Keys (generate with openssl commands above)
WEB_NEXTAUTH_SECRET="your-generated-secret"
API_CRYPTO_KEY="your-generated-hex-key"
API_JWT_SECRET="your-generated-secret"
API_JWT_REFRESH_SECRET="your-generated-secret"

# Database Configuration
API_PG_DB_PASSWORD="your-secure-db-password"
API_MG_DB_PASSWORD="your-secure-db-password"

# Together AI Configuration (Fixed Mode) 
API_LLM_PROVIDER_MODEL="meta-llama/Meta-Llama-4-Maverick-Instruct"  # Choose your preferred model
API_OPENAI_FORCE_BASE_URL="https://api.together.xyz/v1"             # Together AI API URL  
API_OPEN_AI_API_KEY="your-together-api-key"                         # Your Together AI API Key

# Git Provider Webhooks (choose your provider)
API_GITHUB_CODE_MANAGEMENT_WEBHOOK="https://mesrai-api.yourdomain.com/github/webhook"
# or API_GITLAB_CODE_MANAGEMENT_WEBHOOK="https://mesrai-api.yourdomain.com/gitlab/webhook"
# or GLOBAL_BITBUCKET_CODE_MANAGEMENT_WEBHOOK="https://mesrai-api.yourdomain.com/bitbucket/webhook"

Run the Installation Script

Set the proper permissions for the installation script:

chmod +x scripts/install.sh

Run the script:

./scripts/install.sh

What the Installer Does

Our installer automates several important steps:

• Verifies Docker installation
• Creates networks for Mesrai services
• Clones repositories and configures environment files
• Runs docker-compose to start all services
• Executes database migrations
• Seeds initial data

🎉 Success! When complete, the Mesrai Web App and backend services (API, worker, webhooks, MCP manager) should be running on your machine.

You can verify your installation by visiting http://localhost:3000 - you should see the Mesrai Web Application interface.

Set Up Reverse Proxy (For Production)

For webhooks and external access, configure Nginx:

# Web App (port 3000)
server {
    listen 80;
    server_name mesrai-web.yourdomain.com;
    location / {
        proxy_pass http://localhost:3000;
        proxy_set_header Host $host;
        proxy_set_header X-Real-IP $remote_addr;
        proxy_set_header X-Forwarded-For $proxy_add_x_forwarded_for;
        proxy_set_header X-Forwarded-Proto $scheme;
    }
}
 
# API (port 3001)  
server {
    listen 80;
    server_name mesrai-api.yourdomain.com;
    location ~ ^/(github|gitlab|bitbucket|azure-repos)/webhook {
        proxy_pass http://localhost:3332;
        proxy_set_header Host $host;
        proxy_set_header X-Real-IP $remote_addr;
        proxy_set_header X-Forwarded-For $proxy_add_x_forwarded_for;
        proxy_set_header X-Forwarded-Proto $scheme;
    }
 
    location / {
        proxy_pass http://localhost:3001;
        proxy_set_header Host $host;
        proxy_set_header X-Real-IP $remote_addr;
        proxy_set_header X-Forwarded-For $proxy_add_x_forwarded_for;
        proxy_set_header X-Forwarded-Proto $scheme;
    }
}

Verify Together AI Integration

In addition to the basic installation verification, confirm that Together AI is working:

# Verify Together AI API connection specifically
docker-compose logs api worker | grep -i together

Troubleshooting