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Use Self-Hosted CodeRabbit With Azure DevOps
Azure DevOps
Instructions to self-host CodeRabbit and integrate it with Azure DevOps.
3

Create a Azure DevOps User

  • Username: Set the username to "CodeRabbit" for easier identification (optional).
  • Profile Image: Use the CodeRabbitAI logo for the user image (optional).

Add User to Projects

Add the CodeRabbit user to each project where you want CodeRabbit to post reviews, with rights to post reviews & open PRs.

Create a Personal Access Token for CodeRabbit user

Generate a personal access token for the CodeRabbit user to be added in the .env file as AZURE_DEVOPS_BOT_TOKEN.

Necessary Scopes:

  • Code - Full
  • Work Items - Read, write, and manage

Consult official CodeRabbitAI documentation for a detailed guide on creating personal access tokens.

Add the necessary webhooks to each project

  1. Navigate to project's Service Hooks Page: Go to the service hooks configuration page in the desired Azure DevOps project.

  2. Add the following webhooks:

    1. Pull request created
    2. Pull request updated
    3. Pull request commented on

  3. Add Webhook URL: Enter the URL pointing to the CodeRabbit service, followed by /azure_webhooks (e.g., http://127.0.0.1:8080/azure_webhooks) for each webhook.

Prepare an .env file

Create an .env file with the following content:

# if using OpenAI
LLM_PROVIDER=openai
LLM_TIMEOUT=360000
OPENAI_API_KEYS=<openai-key>
OPENAI_BASE_URL=[<openai-base-url>]
OPENAI_ORG_ID=[<openai-org-id>]
OPENAI_PROJECT_ID=[<openai-project-id>]

# if using Azure OpenAI
LLM_PROVIDER=azure-openai
LLM_TIMEOUT=360000
AZURE_OPENAI_ENDPOINT=<azure-openai-endpoint>
AZURE_OPENAI_API_KEY=<key>
AZURE_GPT4OMINI_DEPLOYMENT_NAME=<gpt-4o-mini-deployment-name>
AZURE_GPT4O_DEPLOYMENT_NAME=<gpt-4o-deployment-name, modelVersion: 2024-08-06>
## o1-mini is optional
AZURE_O1_MINI_DEPLOYMENT_NAME=[<o1-mini-deployment-name>]
## o1-preview is optional: it’s very expensive but provides best reviews
AZURE_O1_DEPLOYMENT_NAME=[<o1-preview-deployment-name>]
## gpt-4-turbo is optional: it’s expensive but provides better reviews than gpt-4o
AZURE_GPT4TURBO_DEPLOYMENT_NAME=[<gpt-4-turbo-deployment-name, modelVersion: turbo-2024-04-09>]

TEMP_PATH=/cache

AST_GREP_RULES_PATH=/home/jailuser/ast-grep-rules
AST_GREP_ESSENTIALS=ast-grep-essentials

SELF_HOSTED=azure-devops

AZURE_DEVOPS_BOT_TOKEN=<personal-access-token>
AZURE_DEVOPS_BOT_USERNAME=<bot-user-username>
CODERABBIT_LICENSE_KEY=<license-key>

CODERABBIT_API_KEY=[<coderabbitai-api-key>]
ENABLE_LEARNINGS=[true]
ENABLE_METRICS=[true]

JIRA_HOST=[<jira-host-url>]
JIRA_PAT=[<jira-personal-access-token>]

LINEAR_PAT=[<linear-personal-access-token>]

:::note

  • If you are using Azure OpenAI, verify that the model deployment names are in the .env file.
  • Values marked with [] are not optional to provide.
  • You can generate CODERABBIT_API_KEY from CodeRabbit UI -> Organizations Settings -> API Keys.

:::

Pull the CodeRabbit Docker image

Authenticate and pull the Docker image using the provided credentials file:

cat coderabbit.json | docker login -u _json_key --password-stdin us-docker.pkg.dev
docker pull <docker-registry>/coderabbit-agent:latest

Verify the image is up

You can query /health endpoint to verify that the coderabbit-agent service is up and running.

curl 127.0.0.1:8080/health

Host the image

You can host the image on a server, serverless function, or container environment and expose port 8080. Run the Docker image with the equivalent command on your chosen platform, ensuring you replace the .env file path with the path to your actual .env file:

docker run --env-file .env --publish 127.0.0.1:8080:8080 <docker-registry>/coderabbit-agent:latest