fix: handle ClientError in retry logic for translation service

[vasiliadi]

Summary by CodeRabbit

• Bug Fixes
  • Improved the resilience of the translation functionality by updating its error-handling process. Now, the service automatically retries when encountering additional transient issues, ensuring a smoother and more reliable experience for users.

[coderabbitai]

Walkthrough

The changes update the error handling in the translation module. The pull request adds the import of ClientError alongside ServerError from the Google GenAI errors module and modifies the retry decorator in the translate function. The retry mechanism now triggers for both ServerError and ClientError exceptions, thereby expanding the function's capability to handle a broader range of errors.

Changes

File	Change Summary
src/translate.py	- Import updated to include ClientError in addition to ServerError - Retry decorator updated to retry on both ServerError and ClientError

Sequence Diagram(s)

sequenceDiagram
    participant Client
    participant TranslateFunc as translate()
    participant RetryWrapper as Retry Decorator

    Client->>TranslateFunc: Call translate()
    TranslateFunc-->>RetryWrapper: Execute function
    RetryWrapper-->>TranslateFunc: Returns result or error
    alt Error is ServerError or ClientError
        RetryWrapper->>TranslateFunc: Retry translate()
    else Other error
        RetryWrapper->>Client: Propagate error
    end

Loading

Poem

Oh, what a hop, what a leap,
New errors now in our keep!
Client and Server join the play,
Retry again, come what may.
Bunny rhymes in code so deep!
🐇✨

---

📜 Recent review details

Configuration used: CodeRabbit UI
Review profile: CHILL
Plan: Pro

📥 Commits

Reviewing files that changed from the base of the PR and between 6c39e2d and a756ce0.

📒 Files selected for processing (1)

• src/translate.py (2 hunks)

🔇 Additional comments (2)

src/translate.py (2)

5-5: LGTM! Import change aligns with PR objective.

The addition of ClientError to the imports is appropriate for expanding the error handling capabilities.

---

23-25:

❓ Verification inconclusive

LGTM! Retry logic expanded to handle both server and client errors.

The addition of ClientError to the retry conditions improves the function's resilience by handling a broader range of transient errors.

Let's verify the types of errors that these classes handle:

---

🌐 Web query:

What types of errors do google.genai.errors.ServerError and ClientError handle? What's the difference between them?

💡 Result:

Google's Generative AI SDK (google-genai) uses ServerError and ClientError to categorize different types of API failures:

ClientError

Handles 4xx-class errors caused by client-side issues:

• Invalid request parameters (400 Bad Request)
• Authentication failures (401 Unauthorized)
• Permission issues (403 Forbidden)
• Resource not found (404 Not Found)
• Conflict errors (409 Already Exists)

Examples from search results:

• Invalid API keys or OAuth configuration[4]
• Exceeding input token limits[5]
• Missing required permissions[2][5]
• Attempting unauthorized resource access[2][5]

ServerError

Handles 5xx-class errors indicating server-side failures:

• Internal server errors (500 Internal Server Error)
• Service overloads (503 Service Unavailable)
• Timeouts (504 Gateway Timeout)

Common causes per search results:

• Model service overload ("Model is overloaded")[3][5]
• Transient infrastructure failures[3][5]
• Dependency service outages[3][5]

Key Differences

Aspect	ClientError	ServerError
HTTP Codes	400-499	500-599
Retry Strategy	Fix request first	Retry with backoff
Example Causes	Invalid parameters, permissions	Service overload, infrastructure issues
Typical Solutions	Modify request parameters/credentials	Wait & retry; check service status

Implementation Guidance

try:
    # API call
except google.genai.errors.ClientError as e:
    # Handle invalid requests/permissions
except google.genai.errors.ServerError as e:
    # Implement retry logic with exponential backoff

For transient server errors (500/503), the SDK automatically retries up to default limits[9], but you should implement additional retry logic for critical operations. Client errors typically require code changes to resolve[1][5].

Citations:

• 1: https://google.aip.dev/193
• 2: https://cloud.google.com/application-integration/docs/error-handling
• 3: https://www.googlecloudcommunity.com/gc/AI-ML/InternalServerError-500-Internal-error-encountered/m-p/694666
• 4: https://developers.google.com/identity/oauth2/web/guides/error
• 5: https://cloud.google.com/vertex-ai/generative-ai/docs/model-reference/api-errors
• 6: https://firebase.google.com/docs/auth/flutter/errors
• 7: Issue: Improve Error Handling and Provide Detailed Error Messages google-gemini/generative-ai-js#82
• 8: https://www.make.com/en/help/errors/how-to-handle-errors-in-make/overview-of-error-handling-in-make
• 9: https://github.com/googleapis/python-genai/blob/main/google/genai/errors.py
• 10: https://firebase.google.com/docs/storage/web/handle-errors

---

LGTM! Retry logic now covers both ServerError and ClientError.

The updated decorator correctly applies retries for both types:

• ServerError (5xx errors): Captures transient server issues like internal errors, timeouts, or service overload.
• ClientError (4xx errors): Usually represents problems like bad requests, authentication failures, or permission issues. While these errors typically indicate that the request should be fixed rather than retried, they may occasionally be transient. Please confirm that auto-retrying ClientError aligns with the intended error-handling strategy.

✨ Finishing Touches

• 📝 Generate Docstrings (Beta)

---

Thank you for using CodeRabbit. We offer it for free to the OSS community and would appreciate your support in helping us grow. If you find it useful, would you consider giving us a shout-out on your favorite social media?

❤️ Share

• X
• Mastodon
• Reddit
• LinkedIn

🪧 Tips

Chat

There are 3 ways to chat with CodeRabbit:

• Review comments: Directly reply to a review comment made by CodeRabbit. Example:
  • I pushed a fix in commit <commit_id>, please review it.
  • Generate unit testing code for this file.
  • Open a follow-up GitHub issue for this discussion.
• Files and specific lines of code (under the "Files changed" tab): Tag @coderabbitai in a new review comment at the desired location with your query. Examples:
  • @coderabbitai generate unit testing code for this file.
  • @coderabbitai modularize this function.
• PR comments: Tag @coderabbitai in a new PR comment to ask questions about the PR branch. For the best results, please provide a very specific query, as very limited context is provided in this mode. Examples:
  • @coderabbitai gather interesting stats about this repository and render them as a table. Additionally, render a pie chart showing the language distribution in the codebase.
  • @coderabbitai read src/utils.ts and generate unit testing code.
  • @coderabbitai read the files in the src/scheduler package and generate a class diagram using mermaid and a README in the markdown format.
  • @coderabbitai help me debug CodeRabbit configuration file.

Note: Be mindful of the bot's finite context window. It's strongly recommended to break down tasks such as reading entire modules into smaller chunks. For a focused discussion, use review comments to chat about specific files and their changes, instead of using the PR comments.

CodeRabbit Commands (Invoked using PR comments)

• @coderabbitai pause to pause the reviews on a PR.
• @coderabbitai resume to resume the paused reviews.
• @coderabbitai review to trigger an incremental review. This is useful when automatic reviews are disabled for the repository.
• @coderabbitai full review to do a full review from scratch and review all the files again.
• @coderabbitai summary to regenerate the summary of the PR.
• @coderabbitai generate docstrings to generate docstrings for this PR. (Beta)
• @coderabbitai resolve resolve all the CodeRabbit review comments.
• @coderabbitai configuration to show the current CodeRabbit configuration for the repository.
• @coderabbitai help to get help.

Other keywords and placeholders

• Add @coderabbitai ignore anywhere in the PR description to prevent this PR from being reviewed.
• Add @coderabbitai summary to generate the high-level summary at a specific location in the PR description.
• Add @coderabbitai anywhere in the PR title to generate the title automatically.

CodeRabbit Configuration File (.coderabbit.yaml)

• You can programmatically configure CodeRabbit by adding a .coderabbit.yaml file to the root of your repository.
• Please see the configuration documentation for more information.
• If your editor has YAML language server enabled, you can add the path at the top of this file to enable auto-completion and validation: # yaml-language-server: $schema=https://coderabbit.ai/integrations/schema.v2.json

Documentation and Community

• Visit our Documentation for detailed information on how to use CodeRabbit.
• Join our Discord Community to get help, request features, and share feedback.
• Follow us on X/Twitter for updates and announcements.

[blar-app]

PR Summary

This pull request updates the retry logic in the translation service to handle ClientError exceptions, enhancing the robustness of the service.

Key Findings

• Retry logic now accounts for both ClientError and ServerError exceptions in src/translate.py.

Pull Request Impact: 0
We measure the impact of a Pull Request on the codebase by counting the number of references to the changed code.

File Changes Overview

File	Description
src/translate.py	Updated the retry logic to handle both ClientError and ServerError exceptions in the translation service.

Blar Instructions

Blar Commands

• Comment -blar --review triggers a review of the Pull Request, analyzing only the unreviewed commits since the last review.
• Comment -blar --review --force to receive a complete review of the entire Pull Request, reanalyzing all commits.

Tags Explanation

• 🐛 Debugger Agent Issues:
  These issues are identified by our Debugger Agent, which focuses on detecting bugs and errors in your code.
  Solutions for 🐛 issues are available upon request using the -blar --fix command.

• ⚡ Optimizer Agent Issues:
  These issues focus on identifying inefficient database queries that can impact performance.
  Solutions for ⚡ issues are available upon request using the -blar --fix command.

• 🛡️ Cyber Security Agent Issues:
  These issues focus on identifying potential security vulnerabilities in your code.
  Solutions for 🛡️ issues are available upon request using the -blar --fix command.

• 🎨 Design Pattern Reviewer Agent Issues:
  These issues highlight concerns related to improper or suboptimal use of design patterns, evaluated based on rules set in the wiki.
  Solutions for 🎨 issues are currently not available, but the agent provides detailed insights.

[blar-app]

✅ No debugger issues found 🐛
✅ No optimizer issues found ⚡
✅ No cyber security issues found 🛡️
❕ It looks like we couldn't find any design patterns in the Wiki for this repository. Let's add some at: app.blar.io/wiki