I used deepseek to explain it more clearly (English it's not my first language)

Feature Request: Context Window Limit Notification System

Subject: Suggestion: Implement a user notification when approaching the context window limit.

Description:

I would like to suggest a feature to improve the user experience during long conversations: a clear notification system when a chat session is nearing its context window limit.

Currently, the model operates with a large but finite context window. When a conversation becomes extremely long, the system silently begins to "forget" the earliest messages to make room for new ones. There is no visual cue or warning for the user that this is happening. This can lead to a degraded experience where the user continues the dialogue unaware that the model's responses are no longer grounded in the full conversation history.

Proposed Solution:

Implement a non-intrusive, user-friendly notification mechanism. For example:

· A subtle progress bar in the chat interface indicating the approximate usage of the active context.
· A clear text warning (e.g., "This conversation is getting long. For best performance, consider summarizing key points.") when usage exceeds a high threshold (e.g., 75-90%).
· An ideal, advanced functionality could link this warning to a summary action. The system could prompt the user to provide or co-create a concise summary of key points that are about to be displaced, allowing for efficient context retention.

Benefits & Impact:

· Transparency: Users gain a clear understanding of the system's operational limits.
· User Control: It empowers users to take informed actions—like summarizing, starting a new chat, or refining their queries—to maintain conversation quality.
· Improved Conversation Quality: Helps prevent sudden drops in coherence during marathon sessions by prompting proactive context management.
· Educational Value: Teaches users effective practices for interacting with large language models.

Context & Motivation:
This suggestion arose from a detailed discussion about the model's technical capabilities,where the lack of a warning system was identified as a point where user collaboration could significantly enhance the interaction, especially for complex, long-form analysis (e.g., discussing technical topics like video game graphics).

Where and How to Send It

· Where: The official channel is the project's GitHub repository. You should create a new "Issue" on the relevant repo (for example, one related to the DeepSeek model or its web interface).
· Language: English is the standard language for technical communication on platforms like GitHub and will ensure your request is seen and understood by the core developers and the wider community.