Update token_handler.py

[DedyKredo]

Type

enhancement, bug_fix

---

Description

• Introduced error handling in _get_system_user_tokens method to return -1 if an exception occurs, enhancing the robustness of token calculation.
• Maintained consistency in the count_tokens method by ensuring the newline at the end of the file is unchanged.

---

Changes walkthrough

	Relevant files
Enhancement	token_handler.py Enhance Token Calculation Robustness and Maintain Consistency pr_agent/algo/token_handler.py Wrapped token calculation in a try-except block to handle potential exceptions. Added a default return value of -1 in case of exceptions during token calculation. Ensured consistent return of token count for count_tokens method by maintaining the newline at the end of the file. +10/-7

---

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

[codiumai-pr-agent-pro]

PR Description updated to latest commit (a461c2a)

• Copy walkthrough table to "Files Changed" Tab

[codiumai-pr-agent-pro]

PR Review

⏱️ Estimated effort to review [1-5]	2, because the changes are straightforward and localized to a specific functionality within the code. The addition of error handling and maintaining the newline at the end of the file are simple yet important improvements.
🏅 Score	85
🧪 Relevant tests	No
🔍 Possible issues	Silent Failure: Returning -1 in case of an exception without logging the error might lead to silent failures where the underlying issue is not easily identifiable. Consider logging the exception for easier debugging.
🔒 Security concerns	No

---

✨ Review tool usage guide:

---

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.

[codiumai-pr-agent-pro]

PR Code Suggestions

Category	Suggestions
Best practice	Catch specific exceptions instead of using a broad except clause. It's recommended to catch specific exceptions rather than using a broad except: clause. This will help in identifying and handling potential errors more accurately. For instance, if the render or encode methods might raise a specific exception (e.g., TemplateError for Jinja2 templates), catch that specific exception. pr_agent/algo/token_handler.py [52-60] try: environment = Environment(undefined=StrictUndefined) system_prompt = environment.from_string(system).render(vars) user_prompt = environment.from_string(user).render(vars) system_prompt_tokens = len(encoder.encode(system_prompt)) user_prompt_tokens = len(encoder.encode(user_prompt)) return system_prompt_tokens + user_prompt_tokens -except: +except TemplateError: return -1
	Specify all arguments explicitly in the encode method for clarity. For the encode method call, it's a good practice to explicitly specify all arguments, including those with default values. This makes the code more readable and understandable, especially for someone who might not be familiar with the default behavior of encode. pr_agent/algo/token_handler.py [56-57] -system_prompt_tokens = len(encoder.encode(system_prompt)) -user_prompt_tokens = len(encoder.encode(user_prompt)) +system_prompt_tokens = len(encoder.encode(system_prompt, disallowed_special=())) +user_prompt_tokens = len(encoder.encode(user_prompt, disallowed_special=()))
Enhancement	Add logging within the except block for better error insight. Consider adding logging or error reporting within the except block to provide insight into why an error occurred. This can be helpful for debugging purposes and to improve the robustness of the code. pr_agent/algo/token_handler.py [52-60] try: environment = Environment(undefined=StrictUndefined) system_prompt = environment.from_string(system).render(vars) user_prompt = environment.from_string(user).render(vars) system_prompt_tokens = len(encoder.encode(system_prompt)) user_prompt_tokens = len(encoder.encode(user_prompt)) return system_prompt_tokens + user_prompt_tokens -except: +except Exception as e: + logger.error(f"Failed to calculate tokens: {e}") return -1
	Allow disallowed_special to be specified as a parameter in count_tokens. To ensure the encode method's flexibility and future-proofing, consider passing disallowed_special as a parameter to the count_tokens method. This allows users of the method to specify their own set of disallowed special tokens if necessary. pr_agent/algo/token_handler.py [72] -return len(self.encoder.encode(patch, disallowed_special=())) +def count_tokens(self, patch: str, disallowed_special=()) -> int: + return len(self.encoder.encode(patch, disallowed_special=disallowed_special))

---

✨ 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.