@rossanodr,

Thank you reporting this issue.
This repository is for issues related to Gemini API Cookbook quickstarts and examples. For issues related to Gemini API, we would suggest you to use "Send Feedback" option in Gemini docs. Ref: Screenshot below. You can also post this issue on Google AI forum.

Thank you but Unfortunately, I did not receive any response from any of them.

@rossanodr,

Thank you reporting this issue. This repository is for issues related to Gemini API Cookbook quickstarts and examples. For issues related to Gemini API, we would suggest you to use "Send Feedback" option in Gemini docs. Ref: Screenshot below. You can also post this issue on Google AI forum.

Description of the bug:

Summary: When using the “gemini-1.5-flash” model for generating long texts, the model often starts creating repetitive sequences of tokens, leading to an infinite loop and exhausting the token limit. This issue is observed with both the Vertex and Gemini APIs.

Example: ``` “The judgment can be appealed in a motion for reconsideration, claiming that the judge did not consider the evidence properly. The judgment can be appealed in a motion for reconsideration, claiming that the judge did not consider the evidence properly. The judgment can be appealed in a motion for reconsideration, claiming that the judge did not consider the evidence properly. The judgment can be appealed…” Steps to Reproduce:

Use the "gemini-1.5-flash" model via Vertex or Gemini API. Generate a long text (e.g., legal or technical document). Observe the generated output for repetition of phrases or sentences. Expected Behavior: The model should generate coherent and non-repetitive text.

Actual Behavior: The model begins to repeat sequences of tokens indefinitely, leading to the maximum token limit being reached.

Impact:

Wastes tokens and API usage limits. Generates unusable text, necessitating additional requests and costs. Reproduction Rate: Occurs frequently with long text generation tasks.

Workaround: Currently, there is no known workaround to prevent this issue.

Request for Resolution:

Investigate the cause of the repetitive token generation. Implement a fix to prevent the model from entering a repetitive loop. Provide a mechanism for users to request refunds or credits for tokens wasted due to this bug.

Actual vs expected behavior:

Actual: “The judgment can be appealed in a motion for reconsideration, claiming that the judge did not consider the evidence properly. The judgment can be appealed in a motion for reconsideration, claiming that the judge did not consider the evidence properly. The judgment can be appealed in a motion for reconsideration, claiming that the judge did not consider the evidence properly. The judgment can be appealed…”

Expected: “The judgment can be appealed in a motion for reconsideration, claiming that the judge did not consider the evidence properly. ”

Any other information you'd like to share?

No response

nbdh