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Use Self-Hosted CodeRabbit With Bitbucket Datacenter

note

The self-hosted option is only available for CodeRabbit Enterprise customers with 500 user seats or more. Please contact CodeRabbit Sales to learn more about the CodeRabbit Enterprise plan.

Create a Bitbucket 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 permissions to:

  • Post reviews
  • Open pull requests

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 BITBUCKET_SERVER_BOT_TOKEN.

Add a webhook to each project​

  1. Navigate to Webhook Settings: Go to the repository settings and locate the webhooks configuration page.
  2. Configure Events: Enable the following Pull Request events:
    • "Opened"
    • "Modified"
    • "Comment Added"
  3. Add Webhook URL: Enter the URL pointing to the CodeRabbit service, followed by /bitbucket_server_webhooks (e.g., http://127.0.0.1:8080/bitbucket_server_webhooks).

Prepare a .env file​

Create a .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>
## it is recommended to use gpt-4o-mini, o1-mini, and o1-preview deployments. The production release of o1 model is inferior to the preview release as of now. Also, please make sure that the deployment name of o1-preview mentions "o1-preview" in it.
AZURE_GPT4OMINI_DEPLOYMENT_NAME=<gpt-4o-mini-deployment-name>
AZURE_O1MINI_DEPLOYMENT_NAME=[<o1-mini-deployment-name>]
AZURE_O1_DEPLOYMENT_NAME=[<o1-deployment-name>]

# if using AWS Bedrock
LLM_PROVIDER=bedrock-anthropic
AWS_ACCESS_KEY_ID=<aws-access-key>
AWS_SECRET_ACCESS_KEY=<aws-secret-access-key>
AWS_REGION=<aws-region>

# System Configuration
TEMP_PATH=/cache

SELF_HOSTED=bitbucket-server

BITBUCKET_SERVER_URL=<bitbucket-server-url>/rest
BITBUCKET_SERVER_WEBHOOK_SECRET=<webhook-secret>
BITBUCKET_SERVER_BOT_TOKEN=<personal-access-token>
BITBUCKET_SERVER_BOT_USERNAME=<bot-user-username>

CODERABBIT_LICENSE_KEY=<license-key>
CODERABBIT_API_KEY=<coderabbitai-api-key>

# Optional Features
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 optional and can be omitted if the feature is not needed.
  • 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 us-docker.pkg.dev/coderabbitprod/self-hosted/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 us-docker.pkg.dev/coderabbitprod/self-hosted/coderabbit-agent:latest