Third-party cyber evaluations involving OpenAI models
openai.com·13h ago
Data Science
Towards AI·21d ago·5 min read
Your AI Doesn’t Forget. It Just Runs Out of Space.
TL;DR
Chatbots often struggle with memory due to limited context windows, which can lead to forgetting information. A new approach was developed to pack entire conversation histories into prompts sent to the AI model.
✦ Why It Matters
Refactor your chatbot to include conversation history in prompts to enhance user engagement and memory retention.
Key Takeaways
- Implement a message count limit to manage context size.
- Use token counting for a more precise context management.
- Summarize older messages to retain key information.
- Combine summarization and trimming for optimal chatbot performance.
How It Works
The chatbot uses a token-based approach to determine how many messages can fit within the context window. By estimating the number of tokens each message consumes, it selectively retains the most relevant messages.
When the message count exceeds a threshold, it summarizes older messages into a concise format, ensuring that essential user information remains accessible.