readme updates

[mrT23]

Type

enhancement, documentation

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Description

• Enhanced the changelog update mechanism in pr_update_changelog.py by specifying the ModelType.TURBO for the retry_with_fallback_models function.
• Updated the README.md to include new images and sections for the PR agent features, adjusting image sizes and adding new content for /review and /improve commands.

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Changes walkthrough

	Relevant files
Enhancement	pr_update_changelog.py Enhance changelog update mechanism with TURBO model            pr_agent/tools/pr_update_changelog.py Added ModelType import from pr_agent.algo.utils. Modified retry_with_fallback_models function call to use ModelType.TURBO. +2/-1
Documentation	README.md Update README with new images and sections for PR agent features README.md Updated image sizes for /describe and /review sections. Added a new section for /review with updated image. Updated image for /improve section and added a new /improve section with a new image. +13/-3

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✨ PR-Agent usage:
Comment /help on the PR to get a list of all available PR-Agent tools and their descriptions

[qodo-merge-pro]

PR Description updated to latest commit (b37d4fa)

• Copy walkthrough table to "Files Changed" Tab

[qodo-merge-pro]

PR Review

⏱️ Estimated effort to review [1-5]	2, because the changes are straightforward and localized to specific sections of the code and documentation. The PR involves a minor enhancement in the code and updates to the README.md, which are generally easier to review for clarity and correctness.
🏅 Score	85
🧪 Relevant tests	No
🔍 Possible issues	The change in pr_update_changelog.py to use ModelType.TURBO might have implications on resource usage or processing time that should be considered or tested, especially if TURBO is significantly more resource-intensive or slower.
	The resizing and addition of images in README.md improve visual documentation but ensure the new image sizes and formats are optimized for web viewing to avoid unnecessary loading times.
🔒 Security concerns	No

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✨ Review tool usage guide:

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Overview:
The review tool scans the PR code changes, and generates a PR review. The tool can be triggered automatically every time a new PR is opened, or can be invoked manually by commenting on any PR.
When commenting, to edit configurations related to the review tool (pr_reviewer section), use the following template:

/review --pr_reviewer.some_config1=... --pr_reviewer.some_config2=...

With a configuration file, use the following template:

[pr_reviewer]
some_config1=...
some_config2=...

Utilizing extra instructions The review tool can be configured with extra instructions, which can be used to guide the model to a feedback tailored to the needs of your project. Be specific, clear, and concise in the instructions. With extra instructions, you are the prompter. Specify the relevant sub-tool, and the relevant aspects of the PR that you want to emphasize. Examples for extra instructions: [pr_reviewer] # /review # extra_instructions=""" In the 'possible issues' section, emphasize the following: - Does the code logic cover relevant edge cases? - Is the code logic clear and easy to understand? - Is the code logic efficient? ... """ Use triple quotes to write multi-line instructions. Use bullet points to make the instructions more readable.

How to enable\disable automation When you first install PR-Agent app, the default mode for the review tool is: pr_commands = ["/review", ...] meaning the review tool will run automatically on every PR, with the default configuration. Edit this field to enable/disable the tool, or to change the used configurations

Auto-labels The review tool can auto-generate two specific types of labels for a PR: a possible security issue label, that detects possible security issues (enable_review_labels_security flag) a Review effort [1-5]: x label, where x is the estimated effort to review the PR (enable_review_labels_effort flag)

Extra sub-tools The review tool provides a collection of possible feedbacks about a PR. It is recommended to review the possible options, and choose the ones relevant for your use case. Some of the feature that are disabled by default are quite useful, and should be considered for enabling. For example: require_score_review, require_soc2_ticket, and more.

Auto-approve PRs By invoking: /review auto_approve The tool will automatically approve the PR, and add a comment with the approval. To ensure safety, the auto-approval feature is disabled by default. To enable auto-approval, you need to actively set in a pre-defined configuration file the following: [pr_reviewer] enable_auto_approval = true (this specific flag cannot be set with a command line argument, only in the configuration file, committed to the repository) You can also enable auto-approval only if the PR meets certain requirements, such as that the estimated_review_effort is equal or below a certain threshold, by adjusting the flag: [pr_reviewer] maximal_review_effort = 5

More PR-Agent commands To invoke the PR-Agent, add a comment using one of the following commands: /review: Request a review of your Pull Request. /describe: Update the PR title and description based on the contents of the PR. /improve [--extended]: Suggest code improvements. Extended mode provides a higher quality feedback. /ask <QUESTION>: Ask a question about the PR. /update_changelog: Update the changelog based on the PR's contents. /add_docs 💎: Generate docstring for new components introduced in the PR. /generate_labels 💎: Generate labels for the PR based on the PR's contents. /analyze 💎: Automatically analyzes the PR, and presents changes walkthrough for each component. See the tools guide for more details. To list the possible configuration parameters, add a /config comment.

See the review usage page for a comprehensive guide on using this tool.

[qodo-merge-pro]

PR Code Suggestions

Category	Suggestions
Enhancement	Add a condition to check the availability or suitability of ModelType.TURBO before using it. Consider checking if ModelType.TURBO is available or suitable before directly passing it to retry_with_fallback_models. This can be done by adding a condition to verify the availability or suitability of the model type based on the current context or settings. pr_agent/tools/pr_update_changelog.py [66] -await retry_with_fallback_models(self._prepare_prediction, model_type=ModelType.TURBO) +if is_model_type_available(ModelType.TURBO): + await retry_with_fallback_models(self._prepare_prediction, model_type=ModelType.TURBO) +else: + await retry_with_fallback_models(self._prepare_prediction)
	Add alt attributes to tags for better accessibility and SEO. For better accessibility and SEO, add alt attributes to all tags describing the content of the images. This helps users who rely on screen readers and improves the webpage's SEO. README.md [145] -<img src="https://www.codium.ai/images/pr_agent/describe_new_short_main.png" width="512"> +<img src="https://www.codium.ai/images/pr_agent/describe_new_short_main.png" width="512" alt="Description of the PR Agent's describe feature">
Maintainability	Use consistent HTML tags for image presentation in the README. Ensure consistency in the presentation of the images by using either or tags for all images, not a mix of both. This will improve the readability and uniformity of the document. README.md [152-155] -<kbd> +<div align="center"> <img src="https://www.codium.ai/images/pr_agent/review_new_short_main.png" width="512"> -</kbd> +</div>
Best practice	Use a consistent width for all images in the README. To maintain a consistent visual layout, consider using the same width for all images. This can be achieved by setting a standard width that works well for all images included in the README. README.md [145] -<img src="https://www.codium.ai/images/pr_agent/describe_new_short_main.png" width="512"> +<img src="https://www.codium.ai/images/pr_agent/describe_new_short_main.png" width="standard_width">
	Log the model type being used for prediction. It's a good practice to log the model type being used for prediction. This can be helpful for debugging purposes and for understanding the model's behavior in different scenarios. pr_agent/tools/pr_update_changelog.py [66] +get_logger().info(f"Using model type: {ModelType.TURBO}") await retry_with_fallback_models(self._prepare_prediction, model_type=ModelType.TURBO)

---

✨ Improve tool usage guide:

---

Overview:
The improve tool scans the PR code changes, and automatically generates suggestions for improving the PR code. The tool can be triggered automatically every time a new PR is opened, or can be invoked manually by commenting on a PR.
When commenting, to edit configurations related to the improve tool (pr_code_suggestions section), use the following template:

/improve --pr_code_suggestions.some_config1=... --pr_code_suggestions.some_config2=...

With a configuration file, use the following template:

[pr_code_suggestions]
some_config1=...
some_config2=...

Enabling\disabling automation When you first install the app, the default mode for the improve tool is: pr_commands = ["/improve --pr_code_suggestions.summarize=true", ...] meaning the improve tool will run automatically on every PR, with summarization enabled. Delete this line to disable the tool from running automatically.

Utilizing extra instructions Extra instructions are very important for the improve tool, since they enable to guide the model to suggestions that are more relevant to the specific needs of the project. Be specific, clear, and concise in the instructions. With extra instructions, you are the prompter. Specify relevant aspects that you want the model to focus on. Examples for extra instructions: [pr_code_suggestions] # /improve # extra_instructions=""" Emphasize the following aspects: - Does the code logic cover relevant edge cases? - Is the code logic clear and easy to understand? - Is the code logic efficient? ... """ Use triple quotes to write multi-line instructions. Use bullet points to make the instructions more readable.

A note on code suggestions quality While the current AI for code is getting better and better (GPT-4), it's not flawless. Not all the suggestions will be perfect, and a user should not accept all of them automatically. Suggestions are not meant to be simplistic. Instead, they aim to give deep feedback and raise questions, ideas and thoughts to the user, who can then use his judgment, experience, and understanding of the code base. Recommended to use the 'extra_instructions' field to guide the model to suggestions that are more relevant to the specific needs of the project, or use the custom suggestions 💎 tool With large PRs, best quality will be obtained by using 'improve --extended' mode.

More PR-Agent commands To invoke the PR-Agent, add a comment using one of the following commands: /review: Request a review of your Pull Request. /describe: Update the PR title and description based on the contents of the PR. /improve [--extended]: Suggest code improvements. Extended mode provides a higher quality feedback. /ask <QUESTION>: Ask a question about the PR. /update_changelog: Update the changelog based on the PR's contents. /add_docs 💎: Generate docstring for new components introduced in the PR. /generate_labels 💎: Generate labels for the PR based on the PR's contents. /analyze 💎: Automatically analyzes the PR, and presents changes walkthrough for each component. See the tools guide for more details. To list the possible configuration parameters, add a /config comment.

See the improve usage page for a more comprehensive guide on using this tool.

[mrT23]

/review auto_approve

[qodo-merge-pro]

Auto-approved PR