Boosting Chatbot Memory: File-Based Approach Outperforms Embedding Search!
Published:Jan 19, 2026 06:36
•1 min read
•r/MachineLearning
Analysis
This is a fantastic demonstration of how file-based memory can significantly improve a chatbot's ability to handle complex queries! The results show impressive gains in accuracy, particularly for temporal and logical reasoning. This innovative approach could revolutionize personal assistant design.
Key Takeaways
- •File-based memory retrieval proved significantly more accurate than embedding search for complex queries.
- •The approach organizes memory into thematic files, enabling the model to directly access relevant information.
- •While slightly slower and more costly in terms of tokens, the file-based method excels in handling temporal and logical reasoning.
Reference
“The tradeoff is inference cost. file based approach uses more tokens because the model reads entire memory files. for my use case thats fine because i care more about accuracy than cost.”