Infinite Memory Chat is a proof-of-concept chatbot that stores conversation history. Built using OpenAIβs Responses API and Vector Stores, it tackles the problem of losing earlier messages in long conversations.
Language models (LLMs) have a limit on how much context they can remember. When conversations get long, older messages disappear. Common strategies to manage this have their downsides:
This project introduces a self-populating RAG system. It archives conversation history automatically, offering a smooth way to maintain long-term memory.
Hereβs a simple overview of the memory levels:
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β LEVEL 1: Active Conversation (20 messages) β
β Full detail, immediate context β
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β at 20 messages, archive oldest 10
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β LEVEL 2: Vector Store Archive β
β Access previous messages and context β
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To get started, follow these steps:
Visit the Releases Page: Go to our Releases page to access the latest version.
Download the Application: Look for the download button and select the appropriate file for your operating system. Click to download it.
Run the Application: After the file downloads, find it in your downloads folder and open it. Follow the on-screen instructions to install and run the application.
Start Chatting: Once installed, open the Infinite Memory Chat application. You can now start having conversations that it remembers over time.
If your conversation exceeds 20 messages, older messages will be automatically archived. You can access these by:
Should you have questions or need help, feel free to open an issue on GitHub. We are always here to assist.
If youβre interested in contributing, please check the contribution guidelines in our GitHub repository. Your feedback and enhancements are appreciated.
We plan to introduce these features soon:
For the latest updates, keep an eye on the Releases page.
Join our community on GitHub Discussions to share feedback, ask questions, or discuss ideas related to Infinite Memory Chat. Your input is valuable and helps improve the project.
We thank OpenAI for their powerful API that enables this project, allowing users to enjoy a more intuitive conversation experience.