t1

CONFIGURATION.md

@@ -9,6 +9,7 @@ You can select your git_provider with the flag `git_provider` in the `config` se
 You can enable/disable the different PR Reviewer abilities with the following flags (`pr_reviewer` section):
 ```
 require_focused_review=true
+require_score_review=true
 require_tests_review=true
 require_security_review=true
 ```

INSTALL.md

@@ -95,9 +95,10 @@ cp pr_agent/settings/.secrets_template.toml pr_agent/settings/.secrets.toml
 # Edit .secrets.toml file
 ```
 
-4. Run the appropriate Python scripts from the scripts folder:
+4. Add the pr_agent folder to your PYTHONPATH, then run the cli.py script:
 
 ```
+export PYTHONPATH=[$PYTHONPATH:]<PATH to pr_agent folder>
 python pr_agent/cli.py --pr_url <pr_url> review
 python pr_agent/cli.py --pr_url <pr_url> ask <your question>
 python pr_agent/cli.py --pr_url <pr_url> describe
@@ -149,16 +150,35 @@ 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)
+
+> The .secrets.toml file is not copied to the Docker image by default, and is only used for local development. 
+> If you want to use the .secrets.toml file in your Docker image, you can add remove it from the .dockerignore file.
+> In most production environments, you would inject the secrets file as environment variables or as mounted volumes. 
+> For example, in order to inject a secrets file as a volume in a Kubernetes environment you can update your pod spec to include the following,
+> assuming you have a secret named `pr-agent-settings` with a key named `.secrets.toml`:
+``` 
+       volumes:
+        - name: settings-volume
+          secret:
+            secretName: pr-agent-settings
+// ...
+       containers:
+// ...
+          volumeMounts:
+            - mountPath: /app/pr_agent/settings_prod
+              name: settings-volume
+```
+
+> Another option is to set the secrets as environment variables in your deployment environment, for example `OPENAI.KEY` and `GITHUB.USER_TOKEN`.
 
 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 +189,7 @@ 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 +199,20 @@ 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

@@ -2,93 +2,96 @@
 
 <div align="center">
 
-<img src="./pics/logo-dark.png#gh-dark-mode-only" width="250"/>
-<img src="./pics/logo-light.png#gh-light-mode-only" width="250"/>
-
+<img src="./pics/logo-dark.png#gh-dark-mode-only" width="330"/>
+<img src="./pics/logo-light.png#gh-light-mode-only" width="330"/><br/>
+Making pull requests less painful with an AI agent
 </div>
 
 [![GitHub license](https://img.shields.io/badge/License-Apache_2.0-blue.svg)](https://github.com/Codium-ai/pr-agent/blob/main/LICENSE)
 [![Discord](https://badgen.net/badge/icon/discord?icon=discord&label&color=purple)](https://discord.com/channels/1057273017547378788/1126104260430528613)
+    <a href="https://github.com/Codium-ai/pr-agent/commits/main">
+    <img alt="GitHub" src="https://img.shields.io/github/last-commit/Codium-ai/pr-agent/main?style=for-the-badge" height="20">
+    </a>
 </div>
 <div style="text-align:left;">
 
-CodiumAI `PR-Agent` is an open-source tool aiming to help developers review PRs faster and more efficiently. It automatically analyzes the PR and can provide several types of feedback:
+CodiumAI `PR-Agent` is an open-source tool aiming to help developers review pull requests faster and more efficiently. It automatically analyzes the pull request and can provide several types of feedback:
 
-**Auto-Description**: Automatically generating PR description - name, type, summary, and code walkthrough.
+**Auto-Description**: Automatically generating PR description - title, type, summary, code walkthrough and PR labels.
 \
-**PR Review**: Feedback about the PR main theme, type, relevant tests, security issues, focused PR, and various suggestions for the PR content.
+**PR Review**: Adjustable feedback about the PR main theme, type, relevant tests, security issues, focus, score, and various suggestions for the PR content.
 \
 **Question Answering**: Answering free-text questions about the PR.
 \
 **Code Suggestion**: Committable code suggestions for improving the PR.
 
 <h3>Example results:</h2>
 </div>
-<h4>Describe:</h4>
+<h4>/describe:</h4>
+<div align="center">
+<p float="center">
+<img src="https://www.codium.ai/images/describe-2.gif" width="800">
+</p>
+</div>
+<h4>/review:</h4>
 <div align="center">
 <p float="center">
-<img src="https://codium.ai/images/describe.gif" width="800">
+<img src="https://www.codium.ai/images/review-2.gif" width="800">
 </p>
 </div>
-<h4>Review:</h4>
+<h4>/reflect_and_review:</h4>
 <div align="center">
 <p float="center">
-<img src="https://codium.ai/images/review.gif" width="800">
+<img src="https://www.codium.ai/images/reflect_and_review.gif" width="800">
 </p>
 </div>
-<h4>Ask:</h4>
+<h4>/ask:</h4>
 <div align="center">
 <p float="center">
-<img src="https://codium.ai/images/ask.gif" width="800">
+<img src="https://www.codium.ai/images/ask-2.gif" width="800">
 </p>
 </div>
-<h4>Improve:</h4>
+<h4>/improve:</h4>
 <div align="center">
 <p float="center">
-<img src="https://codium.ai/images/improve.gif" width="800">
+<img src="https://www.codium.ai/images/improve-2.gif" width="800">
 </p>
 </div>
 <div align="left">
 
-- [Live demo](#live-demo)
+
 - [Overview](#overview)
-- [Quickstart](#quickstart)
+- [Try it now](#try-it-now)
+- [Installation](#installation)
 - [Usage and tools](#usage-and-tools)
 - [Configuration](./CONFIGURATION.md)
 - [How it works](#how-it-works)
 - [Roadmap](#roadmap)
 - [Similar projects](#similar-projects)
 </div>
 
-## Live demo
-
-Experience GPT-4 powered PR review on your public GitHub repository with our hosted PR-Agent. To try it, just mention `@CodiumAI-Agent` and add the desired command in any PR comment! The agent will generate a response based on your command.
-
-![Review generation process](https://codium.ai/images/demo.gif)
-
-To set up your own PR-Agent, see the [Quickstart](#Quickstart) section
 
----
 ## Overview
 `PR-Agent` offers extensive pull request functionalities across various git providers:
 |       |                                             | GitHub | Gitlab | Bitbucket |
 |-------|---------------------------------------------|:------:|:------:|:---------:|
 | TOOLS | Review                                      |   :white_check_mark:    |   :white_check_mark:    |   :white_check_mark:       |
 |       | ⮑ Inline review                             |   :white_check_mark:    |   :white_check_mark:    |           |
 |       | Ask                                         |   :white_check_mark:    |   :white_check_mark:    |           |
-|       | Auto-Description                            |   :white_check_mark:    |        |           |
+|       | Auto-Description                            |   :white_check_mark:    |  :white_check_mark:      |           |
 |       | Improve Code                                |   :white_check_mark:    |   :white_check_mark:    |           |
 |       | Reflect and Review                          |   :white_check_mark:    |                         |           |
 |       |                                             |        |        |           |
 | USAGE | CLI                                         |   :white_check_mark:    |   :white_check_mark:    |   :white_check_mark:       |
-|       | Tagging bot                                 |   :white_check_mark:    |   :white_check_mark:    |           |
+|       | Tagging bot                                 |   :white_check_mark:    |        |           |
 |       | Actions                                     |   :white_check_mark:    |        |           |
 |       |                                             |        |        |           |
 | CORE  | PR compression                              |   :white_check_mark:    |   :white_check_mark:    |   :white_check_mark:       |
 |       | Repo language prioritization                |   :white_check_mark:    |   :white_check_mark:    |   :white_check_mark:       |
 |       | Adaptive and token-aware<br />file patch fitting |   :white_check_mark:    |   :white_check_mark:    |   :white_check_mark:       |
+|       | Incremental PR Review |   :white_check_mark:    |      |         |
 
-Examples for invoking the different tools via the [CLI](#quickstart):
+Examples for invoking the different tools via the CLI:
 - **Review**:       python cli.py --pr-url=<pr_url>  review
 - **Describe**:     python cli.py --pr-url=<pr_url>  describe
 - **Improve**:      python cli.py --pr-url=<pr_url>  improve
@@ -99,18 +102,24 @@ Examples for invoking the different tools via the [CLI](#quickstart):
 
 In the [configuration](./CONFIGURATION.md) file you can select your git provider (GitHub, Gitlab, Bitbucket), and further configure the different tools.
 
-## Quickstart
+## Try it now
+
+Try GPT-4 powered PR-Agent on your public GitHub repository for free. Just mention `@CodiumAI-Agent` and add the desired command in any PR comment! The agent will generate a response based on your command.
+
+![Review generation process](https://www.codium.ai/images/demo-2.gif)
+
+To set up your own PR-Agent, see the [Installation](#installation) section
+
+---
+
+## Installation
 
 To get started with PR-Agent quickly, you first need to acquire two tokens:
 
 1. An OpenAI key from [here](https://platform.openai.com/), with access to GPT-4.
 2. A GitHub personal access token (classic) with the repo scope.
 
-There are several ways to use PR-Agent. Let's start with the simplest one:
-
-
-## Install
-Here are several ways to install and run PR-Agent:
+There are several ways to use PR-Agent:
 
 - [Method 1: Use Docker image (no installation required)](INSTALL.md#method-1-use-docker-image-no-installation-required)
 - [Method 2: Run as a GitHub Action](INSTALL.md#method-2-run-as-a-github-action)
@@ -128,19 +137,19 @@ Here are several ways to install and run PR-Agent:
 - The "PR Q&A" tool answers free-text questions about the PR.
 - The "PR Description" tool automatically sets the PR Title and body.
 - The "PR Code Suggestion" tool provide inline code suggestions for the PR that can be applied and committed.
-- The "PR Reflect and Review" tool first dialog with the user and asks him to reflect on the PR, and then provides a review.
+- The "PR Reflect and Review" tool initiates a dialog with the user, asks them to reflect on the PR, and then provides a more focused review.
 
 ## How it works
 
-![PR-Agent Tools](https://codium.ai/images/pr_agent_overview.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
 
 ## Roadmap
 
-- [ ] Support open-source models, as a replacement for openai models. (Note - a minimal requirement for each open-source model is to have 8k+ context, and good support for generating json as an output)
+- [ ] Support open-source models, as a replacement for OpenAI models. (Note - a minimal requirement for each open-source model is to have 8k+ context, and good support for generating JSON as an output)
 - [x] Support other Git providers, such as Gitlab and Bitbucket.
-- [ ] Develop additional logics for handling large PRs, and compressing git patches
+- [ ] Develop additional logic for handling large PRs, and compressing git patches
 - [ ] Add additional context to the prompt. For example, repo (or relevant files) summarization, with tools such a [ctags](https://github.com/universal-ctags/ctags)
 - [ ] Adding more tools. Possible directions:
   - [x] PR description

action.yaml

@@ -1,5 +1,8 @@
-name: 'PR Agent'
+name: 'Codium PR Agent'
 description: 'Summarize, review and suggest improvements for pull requests'
+branding:
+  icon: 'award'
+  color: 'green'
 runs:
   using: 'docker'
   image: 'Dockerfile.github_action_dockerhub'

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/agent/pr_agent.py

@@ -1,35 +1,32 @@
 import re
 
+from pr_agent.config_loader import settings
 from pr_agent.tools.pr_code_suggestions import PRCodeSuggestions
 from pr_agent.tools.pr_description import PRDescription
 from pr_agent.tools.pr_information_from_user import PRInformationFromUser
 from pr_agent.tools.pr_questions import PRQuestions
 from pr_agent.tools.pr_reviewer import PRReviewer
-from pr_agent.config_loader import settings
 
 
 class PRAgent:
     def __init__(self):
         pass
 
     async def handle_request(self, pr_url, request) -> bool:
-        if any(cmd in request for cmd in ["/answer"]):
+        action, *args = request.strip().split()
+        if any(cmd == action for cmd in ["/answer"]):
             await PRReviewer(pr_url, is_answer=True).review()
-        elif any(cmd in request for cmd in ["/review", "/review_pr", "/reflect_and_review"]):
+        elif any(cmd == action for cmd in ["/review", "/review_pr", "/reflect_and_review"]):
             if settings.pr_reviewer.ask_and_reflect or "/reflect_and_review" in request:
                 await PRInformationFromUser(pr_url).generate_questions()
             else:
-                await PRReviewer(pr_url).review()
-        elif any(cmd in request for cmd in ["/describe", "/describe_pr"]):
+                await PRReviewer(pr_url, args=args).review()
+        elif any(cmd == action for cmd in ["/describe", "/describe_pr"]):
             await PRDescription(pr_url).describe()
-        elif any(cmd in request for cmd in ["/improve", "/improve_code"]):
+        elif any(cmd == action for cmd in ["/improve", "/improve_code"]):
             await PRCodeSuggestions(pr_url).suggest()
-        elif any(cmd in request for cmd in ["/ask", "/ask_question"]):
-            pattern = r'(/ask|/ask_question)\s*(.*)'
-            matches = re.findall(pattern, request, re.IGNORECASE)
-            if matches:
-                question = matches[0][1]
-                await PRQuestions(pr_url, question).answer()
+        elif any(cmd == action for cmd in ["/ask", "/ask_question"]):
+            await PRQuestions(pr_url, args).answer()
         else:
             return False