Gemini 3 Pro Streaming Issue With Codex CLI

by Alex Johnson 44 views

Experiencing issues with Gemini 3 Pro streaming ending earlier than expected when using Codex CLI? You're not alone. This article dives deep into the bug, exploring potential causes, and offering insights into troubleshooting this frustrating problem. We'll cover everything from identifying the issue to examining log files and exploring possible solutions, ensuring you get the most out of your Gemini 3 Pro experience.

Understanding the Gemini 3 Pro Streaming Bug

When working with language models like Gemini 3 Pro, streaming is a crucial feature. It allows you to receive responses in real-time, chunk by chunk, rather than waiting for the entire output to be generated. This is particularly important for interactive applications, long-form content generation, and scenarios where responsiveness is key. However, some users have reported that the streaming process ends prematurely when using Gemini 3 Pro in conjunction with Codex CLI, disrupting workflows and hindering productivity.

The core issue is that the streaming output from Gemini 3 Pro terminates before the expected completion point. This means that you might only receive a partial response, leaving you with an incomplete answer or an abruptly cut-off piece of text. This behavior is inconsistent and can occur across various CLI types and LLM clients, making it a challenging problem to diagnose and resolve. We will look at different types of CLI accounts including, gemini-cli, gemini, codex, claude code or openai-compatibility. In addition to what model you are using for example, gemini-2.5-pro, claude-sonnet-4-20250514, gpt-5, etc. This makes identifying and resolving the root cause more complicated. The premature termination of streaming can lead to a fragmented and unsatisfactory user experience.

Key Aspects of the Bug:

  • Inconsistent Behavior: The issue doesn't occur consistently, making it difficult to reproduce and debug.
  • Multiple CLI Types Affected: The bug has been observed across various CLI types, including gemini-cli, gemini, codex, claude code, and openai-compatibility.
  • Impact on Different LLM Clients: The problem persists regardless of the LLM client used, such as roo-code, cline, or claude code.
  • Disrupts Workflows: The premature termination of streaming disrupts the user experience and can lead to data loss or incomplete results.

Diagnosing the Issue: A Deep Dive into Log Files

To effectively troubleshoot the Gemini 3 Pro streaming bug, examining log files is crucial. Log files provide a detailed record of the interactions between your system, the CLI, and the language model. They can reveal valuable clues about the cause of the premature termination. In this specific case, the user has provided two log files: v1-responses-2025-11-27T003242-808994094.log and v1-responses-2025-11-27T003252-078226702.log.

Analyzing these log files can help pinpoint the exact moment the streaming stopped, identify any error messages or warnings, and provide insights into the communication flow between the components involved. Specifically, you should look for:

  • Error Messages: Any error messages or exceptions thrown during the streaming process.
  • Timestamps: The timestamps of events to correlate the termination with specific actions or processes.
  • Network Activity: Information about network requests and responses to identify potential connectivity issues.
  • Resource Usage: Data on CPU, memory, and other resource utilization to rule out resource constraints.

By meticulously reviewing the log files, you can gain a deeper understanding of the underlying cause of the streaming issue. It's a bit like being a detective, piecing together clues to solve a mystery. The log files are your crime scene, and each line of code is a potential piece of evidence.

Steps for Log File Analysis:

  1. Download the Log Files: Obtain the relevant log files from the user or your system.
  2. Open in a Text Editor: Use a text editor or a log file viewer to open the files.
  3. Search for Errors: Look for error messages, warnings, or exceptions.
  4. Analyze Timestamps: Correlate the timestamps with the termination point.
  5. Identify Patterns: Look for patterns or recurring events that might indicate the root cause.

Potential Causes and Solutions

Several factors can contribute to the Gemini 3 Pro streaming bug. Understanding these potential causes is the first step in finding a solution. Here are some of the most common culprits:

1. Network Connectivity Issues

A stable internet connection is essential for seamless streaming. Any interruptions or fluctuations in network connectivity can lead to premature termination. The language model relies on a continuous connection to send data in real-time. If the connection drops, even momentarily, the streaming process may be interrupted.

Solutions:

  • Check your internet connection: Ensure you have a stable and reliable internet connection.
  • Test network speed: Run a speed test to verify your upload and download speeds.
  • Use a wired connection: If possible, use a wired connection instead of Wi-Fi for a more stable connection.
  • Firewall settings: Check your firewall settings to ensure they are not blocking the connection to the language model.

2. API Rate Limits

Language models often have API rate limits to prevent abuse and ensure fair usage. If you exceed the rate limit, the streaming process may be terminated. Rate limits are put in place to manage the resources of the service and prevent any single user from overwhelming the system. When the rate limit is exceeded, the service might temporarily halt the streaming process.

Solutions:

  • Monitor API usage: Track your API usage to ensure you are not exceeding the rate limits.
  • Implement rate limiting: Implement your own rate limiting mechanism to control the number of requests you send.
  • Optimize requests: Optimize your requests to reduce the number of API calls.
  • Contact API provider: If you consistently exceed the rate limits, contact the API provider to discuss your options.

3. Server-Side Issues

Sometimes, the issue might not be on your end but rather on the server-side. The language model's servers might be experiencing temporary outages or performance issues. This can lead to premature termination of streaming. Server-side problems are often difficult to diagnose from the user's perspective, as they are beyond the user's direct control.

Solutions:

  • Check the service status: Check the service status page of the language model provider to see if there are any known issues.
  • Try again later: If there are server-side issues, try again later when the issue is resolved.
  • Contact support: Contact the support team of the language model provider to report the issue.

4. Client-Side Configuration

Incorrect configuration of the CLI or the LLM client can also lead to streaming issues. This includes incorrect API keys, endpoint URLs, or other settings. Misconfigurations can prevent the client from properly communicating with the language model, leading to the premature termination of the streaming process. Client-side issues are usually within the user's control, making them easier to resolve once identified.

Solutions:

  • Verify API keys: Ensure your API keys are correct and valid.
  • Check endpoint URLs: Verify that the endpoint URLs are correct.
  • Review client settings: Review the settings of your CLI and LLM client to ensure they are configured correctly.
  • Update client software: Ensure you are using the latest version of the CLI and LLM client.

5. Bugs in the CLI or LLM Client

Occasionally, the issue might stem from a bug in the CLI or LLM client software itself. Bugs can cause unexpected behavior, including premature termination of streaming. Software bugs are an inherent part of the development process, and while developers strive to eliminate them, they can sometimes slip through and affect users.

Solutions:

  • Update software: Check for updates to the CLI and LLM client and install the latest versions.
  • Report the bug: Report the bug to the developers of the CLI or LLM client.
  • Try a different client: If possible, try a different LLM client to see if the issue persists.

Additional Context and Troubleshooting Steps

The user has mentioned that Gemini CLI works fine without using CLIProxyAPI. This provides a valuable clue. It suggests that the issue might be specific to the interaction between Gemini 3 Pro, Codex CLI, and CLIProxyAPI. CLIProxyAPI might be introducing a layer of complexity that is triggering the bug.

Troubleshooting Steps:

  1. Isolate the Issue: Try using Gemini 3 Pro with Codex CLI without CLIProxyAPI to confirm if CLIProxyAPI is the culprit.
  2. Update CLIProxyAPI: Check for updates to CLIProxyAPI and install the latest version.
  3. Review CLIProxyAPI Configuration: Carefully review the configuration of CLIProxyAPI to ensure it is set up correctly.
  4. Check Compatibility: Verify that CLIProxyAPI is compatible with Gemini 3 Pro and Codex CLI.
  5. Contact Support: If the issue persists, contact the support team of CLIProxyAPI or Codex CLI for assistance.

Conclusion

The Gemini 3 Pro streaming bug with Codex CLI is a frustrating issue, but by systematically diagnosing the problem and exploring potential solutions, you can increase your chances of resolving it. Analyzing log files, checking network connectivity, verifying API limits, reviewing client-side configurations, and considering potential bugs are all essential steps in the troubleshooting process. By isolating the issue to CLIProxyAPI, we have narrowed down the potential cause and can focus on specific solutions.

Remember, the key to resolving complex issues is a methodical approach. By carefully examining each potential cause and trying the recommended solutions, you can restore seamless streaming and get back to leveraging the power of Gemini 3 Pro. And remember, staying informed about the service status and keeping your software up-to-date are crucial for preventing issues like this from disrupting your workflow.

For more information on troubleshooting API issues, you can visit Troubleshooting Cloud APIs. This external resource provides valuable insights and guidance on resolving various API-related problems.