关于 API 速率限制处理与用户体验的详细改进建议 #3345
Description
Plugin Type
VSCode Extension
App Version
Laster
Description
Dear Kilo Code Development Team: Detailed Suggestions for Improving API Rate Limit Handling and User Experience
Dear Kilo Code Team: Hello!
I am a loyal user of the Kilo Code plugin and greatly appreciate its powerful code generation and task orchestration capabilities. However, when using the free tier of the Gemini API, I encountered a problem that seriously affected my user experience: frequent 429 Too Many Requests errors, causing task interruptions.
After multiple attempts, I found that the built-in "API Request Frequency Limit" feature of the plugin seems unable to effectively solve this problem. Even when I set it to a very long interval of 20 seconds, the plugin still seems to initiate a large number of parallel requests at the beginning of the task, immediately exhausting the quota.
Based on this pain point, I would like to propose the following specific and actionable improvement suggestions, hoping to help Kilo Code become a more friendly tool for all developers, including students and independent developers with limited API budgets.
Core issue: Parallel request burst and the limitation of rate limit settings
The current plugin, when handling complex tasks, initiates multiple API requests in parallel to efficiently analyze the codebase context. This design works well for users with high-quotum paid API keys, but it is fatal for free tier users. The existing "frequency limit" setting seems to only apply to the intervals between steps in a serial task flow and cannot control this parallel request burst.
Suggestion 1: Thoroughly restructure the rate limiting mechanism
The current frequency limit function is more like a "step delay" rather than a true "traffic valve". It is suggested to introduce a global request management mechanism.
- Implement a "Global Request Queue":
What it is: Establish a central request "gateway" within the plugin. All API requests initiated by Kilo Code, regardless of which sub-task or analyzer they come from, must first enter this queue to wait.
How to do it: The queue manager sends requests out in sequence and with intervals based on the user's set rate limit (e.g., "up to 15 requests per minute"). This can fundamentally ensure that the plugin does not exceed the API provider's limit within any time window.
Benefits: Transform chaotic parallel requests into orderly serial or controlled concurrent requests, completely solving the 429 problem. - Add a "Max Concurrent Requests" setting:
What it is: Next to the "API Request Frequency Limit", add a slider or input box to allow users to set the maximum number of concurrent requests the plugin can initiate.
How to do it: For example, the user can set it to 1 or 2. This means that even if the task needs to analyze 10 files, the plugin will only handle the requests of 1-2 files at a time, and then proceed to the next batch after completion.
Benefits: This is a powerful complement to the "Global Request Queue". Together, "Max Concurrent Requests" controls the peak of requests at any moment, and "frequency limit" controls the continuous flow rate of requests, ensuring smooth operation.
Suggestion 2: Implement intelligent error handling and automatic retry mechanism
When encountering a 429 error, the current plugin directly reports an error and stops the task. This is a very harsh experience. Modern web applications should be able to handle such predictable errors more gracefully. - Parse the Retry-After response header: What is it: When the API server returns a 429 error, it usually includes a Retry-After field in the response header, clearly informing the client how many seconds to wait before making another request.
How to do it: Kilo Code should catch the 429 error, check and read the Retry-After value, and then display a friendly prompt on the UI (e.g., "Request too frequent, waiting 55 seconds for automatic retry..."), and continue the task after the waiting period ends. - Implement the "Exponential Backoff" strategy:
What is it: If Retry-After is unavailable, a standard exponential backoff strategy can be adopted. That is, wait for 1 second before the first retry, if it fails again, wait for 2 seconds, if it fails again, wait for 4 seconds, and so on, until it succeeds or reaches the maximum number of retries.
Benefits: It makes the plugin resilient, allowing it to automatically recover from temporary network congestion or rate limits, greatly improving the success rate of tasks and the smoothness of the user experience.
Suggestion 3: Introduce a "Free-Tier Friendly Mode"
To provide a better onboarding experience for new and light users, a one-click optimization mode can be designed.
What is it: Provide a simple switch in the settings: "Optimize for low quota/free API keys".
How to do it: After enabling this mode, Kilo Code will automatically apply a set of preset conservative configurations, such as:
Maximum concurrent requests: 1
API request frequency limit: 8 seconds (approximately 7-8 RPM)
Automatically enable the intelligent retry mechanism.
It may default to using a more economical model (such as gemini-flash).
Benefits: It greatly lowers the configuration threshold for new users, preventing them from being frustrated and giving up due to rate limits during their initial experience.
Suggestion 4: Enhance the transparency and guidance of settings - Improve the description of setting items:
In the description of "API request frequency limit", clearly state that it may not limit the parallel requests at the start of a task, and guide users to use the new "Maximum concurrent requests" setting to control the peak. - Add onboarding guidance:
When users first configure API keys such as Gemini, a prompt can pop up: "We detected that you may be using a free key with strict rate limits. For the best experience, we recommend you [enable Free-Tier Friendly Mode] or [upgrade your API plan]." Summary
Kilo Code is an AI development tool with great potential. If the availability issues in restricted API environments can be addressed through the aforementioned improvements (especially the global request queue and intelligent retry), it will undoubtedly attract and retain a broader user base. This not only enhances the product's robustness and user experience but also demonstrates the team's concern for the needs of developers at different levels.
Thank you again for your excellent product, and I look forward to seeing it get better and better!
Sincerely,
A Kilo Code User
Reproduction steps
Reproduction Steps for Triggering 429 Too Many Requests Error
To enable you to consistently reproduce the rate limit issue encountered by users when using a free API key, we provide a clear test environment and operation steps. The core idea is to create a development task that requires cross-file context understanding to trigger a burst of parallel requests at the initial stage of the task in Kilo Code.
I. Environment Preparation (Prerequisites)
API Key:
Prepare a standard Google Gemini API key.
Key Requirements: This key must be generated through Google AI Studio and be in the Free Tier status, not bound to any Google Cloud project with enabled billing. This ensures it is subject to strict rate limits (for example, the free version of the Gemini 1.5 Pro model is typically limited to 2-15 RPM).
VS Code Plugin:
Install the latest version of the Kilo Code VS Code plugin.
Sample Project:
Create a simple project folder containing the following three files to simulate a basic front-end development scenario. index.html
code
Html
<! DOCTYPE html>
Hello, World!
Click Me <script src="script.js"></script> style.css code CSS body { font-family: sans-serif; display: flex; flex-direction: column; align-items: center; justify-content: center; height: 100vh; } button { padding: 10px 20px; font-size: 16px; } script.js code JavaScript const heading = document.getElementById('main-heading'); const button = document.getElementById('action-button');button.addEventListener('click', () => {
heading.textContent = 'Button Clicked! ';
});
II. Steps to Reproduce
Open the prepared project folder in VS Code.
Configure the Kilo Code plugin, enter your Gemini free plan API key in the "Providers" settings, and select a model, such as gemini-1.5-pro-latest.
Open the chat or task panel of Kilo Code.
To ensure that Kilo Code needs to understand the context of the entire project, use the @ symbol to reference all three files, or directly use @workspace.
Input a command that requires modifications to all three files to be completed. A good trigger command is:
@workspace Please add a new function to the button: when the button is clicked for the first time, in addition to changing the title text, also add an 'active' CSS class to the title. Please add a prominent color, such as crimson, for the 'active' class in style.css.
Send the command and observe closely.
III. Expected Result
In an ideal system with rate limit awareness, Kilo Code should:
Receive the task and start processing.
Send requests to the Gemini API in an orderly and spaced manner to analyze files and generate code.
The task execution time may be slightly longer, but it will eventually be completed successfully without any 429 errors.
IV. Actual Result
Under the current mechanism, almost immediately after sending the command, the following occurs:
The Kilo Code task fails immediately and stops.
An error prompt pops up in the IDE, or the error message "API request failed" and "got status: 429 Too Many Requests" is clearly displayed in the Kilo Code output panel.
The error details clearly indicate that the free plan quota of generativelanguage.googleapis.com has been exceeded.
This process clearly demonstrates that the parallel analysis requests for context at the start of the task by the plugin instantly overwhelms the rate limit barrier of the free API key.
Provider
No response
Model
Gemini2.5pro
System Information
No response