Merge commit '5bc2ef1eff1f570779191a8f3c7a562f5b8fe230' into hl/incremental_review

INSTALL.md

@@ -149,16 +149,15 @@ git clone https://github.com/Codium-ai/pr-agent.git
 ```
 
 5. Copy the secrets template file and fill in the following:
+    ```
+    cp pr_agent/settings/.secrets_template.toml pr_agent/settings/.secrets.toml
+    # Edit .secrets.toml file
+    ```
    - Your OpenAI key.
-   - Set deployment_type to 'app'
    - Copy your app's private key to the private_key field.
    - Copy your app's ID to the app_id field.
    - Copy your app's webhook secret to the webhook_secret field.
-
-```
-cp pr_agent/settings/.secrets_template.toml pr_agent/settings/.secrets.toml
-# Edit .secrets.toml file
-```
+   - Set deployment_type to 'app' in [configuration.toml](./pr_agent/settings/configuration.toml)
 
 6. Build a Docker image for the app and optionally push it to a Docker repository. We'll use Dockerhub as an example:
 
@@ -169,6 +168,7 @@ docker push codiumai/pr-agent:github_app  # Push to your Docker repository
 
 7. Host the app using a server, serverless function, or container environment. Alternatively, for development and
    debugging, you may use tools like smee.io to forward webhooks to your local machine.
+    You can check [Deploy as a Lambda Function](#deploy-as-a-lambda-function)
 
 8. Go back to your app's settings, and set the following:
 
@@ -178,3 +178,20 @@ docker push codiumai/pr-agent:github_app  # Push to your Docker repository
 9. Install the app by navigating to the "Install App" tab and selecting your desired repositories.
 
 ---
+
+####  Deploy as a Lambda Function
+
+1. Follow steps 1-5 of [Method 5](#method-5-run-as-a-github-app).
+2. Build a docker image that can be used as a lambda function
+    ```shell
+    docker buildx build --platform=linux/amd64 . -t codiumai/pr-agent:serverless -f docker/Dockerfile.lambda
+   ```
+3. Push image to ECR
+    ```shell
+	docker tag codiumai/pr-agent:serverless <AWS_ACCOUNT>.dkr.ecr.<AWS_REGION>.amazonaws.com/codiumai/pr-agent:serverless
+	docker push <AWS_ACCOUNT>.dkr.ecr.<AWS_REGION>.amazonaws.com/codiumai/pr-agent:serverless
+    ```
+4. Create a lambda function that uses the uploaded image. Set the lambda timeout to be at least 3m.
+5. Configure the lambda function to have a Function URL.
+6. Go back to steps 8-9 of [Method 5](#method-5-run-as-a-github-app) with the function url as your Webhook URL.
+    The Webhook URL would look like `https://<LAMBDA_FUNCTION_URL>/api/v1/github_webhooks`

README.md

@@ -132,7 +132,7 @@ Here are several ways to install and run PR-Agent:
 
 ## How it works
 
-![PR-Agent Tools](https://www.codium.ai/wp-content/uploads/2023/07/pr-agent-schema-updated.png)
+![PR-Agent Tools](https://www.codium.ai/wp-content/uploads/2023/07/codiumai-diagram-v4.jpg)
 
 Check out the [PR Compression strategy](./PR_COMPRESSION.md) page for more details on how we convert a code diff to a manageable LLM prompt
 

docker/Dockerfile.lambda

@@ -0,0 +1,12 @@
+FROM public.ecr.aws/lambda/python:3.10
+
+RUN yum update -y && \
+    yum install -y gcc python3-devel && \
+    yum clean all
+
+ADD requirements.txt .
+RUN pip install -r requirements.txt && rm requirements.txt
+RUN pip install mangum==16.0.0
+COPY pr_agent/ ${LAMBDA_TASK_ROOT}/pr_agent/
+
+CMD ["pr_agent.servers.serverless.serverless"]

pr_agent/cli.py

@@ -10,7 +10,7 @@ from pr_agent.tools.pr_questions import PRQuestions
 from pr_agent.tools.pr_reviewer import PRReviewer
 
 
-def run():
+def run(args=None):
     parser = argparse.ArgumentParser(description='AI based pull request analyzer', usage="""\
 Usage: cli.py --pr-url <URL on supported git hosting service> <command> [<args>].
 For example:
@@ -35,7 +35,7 @@ reflect - Ask the PR author questions about the PR.
                                                                   'reflect', 'review_after_reflect'],
                         default='review')
     parser.add_argument('rest', nargs=argparse.REMAINDER, default=[])
-    args = parser.parse_args()
+    args = parser.parse_args(args)
     logging.basicConfig(level=os.environ.get("LOGLEVEL", "INFO"))
     command = args.command.lower()
     if command in ['ask', 'ask_question']:

pr_agent/servers/serverless.py

@@ -0,0 +1,18 @@
+import logging
+
+from fastapi import FastAPI
+from mangum import Mangum
+
+from pr_agent.servers.github_app import router
+
+logger = logging.getLogger()
+logger.setLevel(logging.DEBUG)
+
+app = FastAPI()
+app.include_router(router)
+
+handler = Mangum(app, lifespan="off")
+
+
+def serverless(event, context):
+    return handler(event, context)