Gemini Live API: Unexpected WebSocket Closures

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Gemini Live API: Unexpected WebSocket Closures After Tool Responses

Hey guys, let's dive into a frustrating issue some of us are encountering with the Gemini Live API. It seems like the WebSocket connection is closing unexpectedly after sending tool responses, throwing either a 1011 ("Internal error occurred") or 1008 ("Requested entity was not found") error. This is happening randomly, making it a real headache to debug. Let's break down the problem, what's expected, and what we can do about it.

The Bug: WebSocket Closures After sendToolResponse()

The core issue is that after a tool successfully executes and we send the response using sendToolResponse(), the Gemini Live API WebSocket sometimes decides to close shop. We're seeing error codes 1011 and 1008, which, let's be honest, aren't exactly descriptive. These errors don't give us a clear indication of what's going wrong – is it the payload size, the format, encoding problems, invalid tool call IDs, or something else entirely? This lack of clarity is making it super difficult to pinpoint the root cause and implement a fix.

I know some of us have already tried the obvious things, like double-checking tool IDs and shortening system prompts and tool responses, but the problem persists. This suggests the issue might be a bit more nuanced than a simple oversight on our part. We need to dig deeper to understand what's happening under the hood.

To put it simply, the Gemini Live API's WebSocket connection is randomly closing with error codes 1011 or 1008 after tool responses are sent using the sendToolResponse() method. This behavior is inconsistent, making debugging a significant challenge. The lack of specific error messages further compounds the difficulty in identifying the root cause, which could range from payload issues to internal API errors. This instability hinders the reliable integration of tools within the Gemini Live API ecosystem.

Actual vs. Expected Behavior: What's Going Wrong?

Let's clarify what's happening versus what we expect to happen. This will help highlight the discrepancy and focus our troubleshooting efforts. Understanding the difference between the actual and expected behavior is crucial for effectively diagnosing and resolving issues. It provides a clear benchmark against which we can measure the API's performance and identify deviations from the norm. In this case, the unexpected WebSocket closures are a significant deviation, impacting the reliability and usability of the Gemini Live API.

Actual Behavior:

Here's what's actually going down:

  1. The tool does its thing and executes successfully.
  2. We sanitize and format the tool response (making sure it's all nice and tidy).
  3. We call sendToolResponse({ functionResponses }) to send the response back to the API.
  4. Boom! The WebSocket connection closes immediately, giving us either code 1011 ("Internal error occurred") or code 1008 ("Requested entity was not found").
  5. We get absolutely zero additional error details. It's like getting a vague "something went wrong" message – not helpful at all!
  6. And, to add insult to injury, this happens randomly. It's not a consistent, reproducible error, which makes it even more frustrating to debug.

The intermittent nature of the issue further complicates the debugging process. Without a consistent pattern, it's difficult to isolate the triggering conditions or identify specific code paths that lead to the WebSocket closure. This randomness suggests that the problem might be related to concurrency issues, resource contention, or other factors that are difficult to control or predict.

Expected Behavior:

Now, here's what we expect to happen:

  1. The tool response should be accepted and processed without any hiccups.
  2. OR, if the response is rejected for some reason, we should get a clear, informative error message explaining why. Something like "Response too large", "Invalid format", "Encoding error", or "Tool call ID not found" would be incredibly helpful.

We expect the API to either successfully process the tool response or provide a detailed explanation if the response is rejected. This expectation is based on standard API design principles, which emphasize the importance of clear error handling and informative feedback. Without such feedback, developers are left in the dark, struggling to understand the root cause of the problem and implement effective solutions. The lack of clear error messages significantly increases the time and effort required to debug and resolve issues, impacting the overall efficiency and productivity of developers using the Gemini Live API.

Diving Deeper: The Technical Details

Let's get a bit more specific about the technical aspects of this issue. This will help us narrow down the potential causes and explore possible solutions. Providing context about the specific configurations, data formats, and API calls involved is crucial for effective troubleshooting. The more information we have, the better equipped we are to identify patterns, correlations, and potential problem areas.

  • Model: We're using gemini-2.5-flash-native-audio-preview-09-2025. This is important because specific model versions can sometimes have their own quirks or bugs.
  • Session Config: Our session configuration includes responseModalities: [Modality.AUDIO] and outputAudioTranscription: {}. This indicates that we're dealing with audio responses, which might introduce specific challenges related to data size, encoding, or processing.
  • Tools: We're providing tools as an array of objects with functionDeclarations. This is the standard way to define tools for the Gemini API, but it's still worth double-checking that our tool definitions are correct and valid.

It's essential to meticulously examine the session configuration and tool definitions to ensure that they adhere to the API's specifications and best practices. Incorrectly configured parameters or malformed tool declarations can lead to unexpected behavior and errors. By verifying these aspects, we can eliminate potential sources of the problem and focus on other areas of investigation.

Tool Response Format:

This is the structure we're using for tool responses:

{
  functionResponses: [
    {
      id: "uuid-string",
      name: "tool-name",
      response: {
        output: "string-response-content"  // Plain string, not JSON
      }
    }
  ]
}

We're sending a plain string as the output, not JSON. This is intentional, but it's worth noting in case there's an unexpected requirement for JSON formatting in some scenarios.

The choice of using a plain string for the output is a deliberate decision, potentially driven by factors such as simplicity, performance, or compatibility with specific tool implementations. However, it's important to ensure that this choice aligns with the API's expectations and that the string content is properly encoded and formatted to avoid any parsing issues. If the API expects JSON or has specific requirements for the string content, deviations from these requirements could lead to errors and unexpected behavior.

Potential Causes and Troubleshooting Steps

Okay, so what could be causing these mysterious WebSocket closures? Let's brainstorm some potential culprits and how we can investigate them.

  1. Payload Size Limits: Could our tool responses be too large? The API might have undocumented limits on the size of data we can send. We should try logging the size of our functionResponses payload before sending it and see if there's a correlation between size and the error.
  2. Encoding Issues: Are we encoding the string responses correctly? Maybe there's a subtle encoding problem that the API is choking on. We could try explicitly setting the encoding to UTF-8 and see if that makes a difference.
  3. Tool Call ID Mismatch: Is there a chance we're sending an incorrect tool call ID? It's crucial to ensure that the id in the functionResponses matches the ID of the original tool call. Double-checking this is essential.
  4. Concurrency Issues: Could there be a race condition or concurrency issue within the API itself? This is harder to debug from our side, but it's a possibility. If we can reproduce the issue consistently under heavy load, it might point to a concurrency problem.
  5. Internal API Errors: Let's face it, sometimes APIs have bugs. It's possible that there's an internal error within the Gemini Live API that's causing the WebSocket closures. If we've ruled out all other possibilities, this might be the most likely explanation.
  6. Rate Limiting: Are we hitting any undocumented rate limits? The API might be closing the connection if we're sending too many requests in a short period. Implementing a delay between requests could help mitigate this.
  7. WebSocket Connection Stability: Could there be underlying issues with the WebSocket connection itself? Network instability or intermittent connectivity problems could lead to unexpected closures. Monitoring network performance and connection stability could provide insights.

To effectively troubleshoot the WebSocket closures, a systematic approach is crucial. Each potential cause should be investigated individually, and the results of each investigation should inform the next steps. This iterative process of hypothesis, testing, and analysis is essential for narrowing down the problem and identifying the root cause.

Let's Work Together to Solve This!

This is a tricky issue, but I'm confident we can figure it out together. Let's share our findings, try different debugging approaches, and hopefully, we can get to the bottom of these mysterious WebSocket closures. The more we collaborate and share our experiences, the faster we'll be able to identify patterns, develop workarounds, and ultimately resolve the problem. Remember, collective intelligence is a powerful tool, and by working together, we can overcome even the most challenging technical hurdles.

If you've encountered this issue, please share your experience! What have you tried? What have you observed? The more information we gather, the better our chances of finding a solution. Let's keep the conversation going and support each other in this debugging journey. By sharing our insights, we can help each other avoid common pitfalls, discover new troubleshooting techniques, and ultimately contribute to a more stable and reliable Gemini Live API experience.

Let's document our findings, share code snippets, and collaborate on potential solutions. By working together, we can not only resolve the current issue but also contribute to the development of best practices and troubleshooting strategies for the Gemini Live API. This collaborative approach will benefit not only ourselves but also the broader community of developers using the API.