v1.1.2

Release v1.1.2 - Performance Optimization and Memory Efficiency

We are thrilled to announce the release of version 1.1.2 of the shortterm-memory package. This update focuses on optimizing performance, enhancing memory management, and improving overall efficiency.

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Main Updates

1. Advanced Memory Management Enhancements

• GPU Acceleration:
  Added automatic GPU support using PyTorch, significantly improving summarization performance when a CUDA device is available.

• Batch Processing for Memory Compression:
  Introduced batch processing (default batch size: 5) for more efficient handling of conversation history during summarization, reducing latency.

• Optimized Memory Counter:
  Enhanced the memory counter to use token-based counting instead of word-based, improving accuracy and performance.

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2. Efficient Conversation History Handling

• Optimized Update Memory Method:
  The update_memory method has been refactored for better performance, including dynamic compression and automatic trimming of older conversations.

• Dynamic Compression Threshold:
  Compression is now triggered based on the token count rather than word count, providing more precise control over memory usage.

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3. Integration with Transformers

• Enhanced Summarization:
  Improved summarization using BART with optimized parameters for faster and more concise summaries.

• Efficient Tokenization:
  Direct use of tokenization for both counting and summarization, reducing redundant operations.

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4. Error Handling and Logging

• Improved Logging:
  Enhanced logging features to provide detailed insights into memory operations, including compression and trimming events.

• Error Handling:
  Added robust error handling to manage issues during summarization and memory updates gracefully.

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Usage Example

import torch
from transformers import pipeline
import logging
from shortterm_memory.ChatbotMemory import ChatbotMemory

# Initialize Chatbot Memory
chat_memory = ChatbotMemory()

# Example of updating the memory with user input and bot response
user_input = "Hello, how are you?"
bot_response = "I'm fine, thank you! How about you?"
chat_memory.update_memory(user_input, bot_response)

# Retrieve the updated conversation history
history = chat_memory.get_memory()
print(history)

How to Upgrade

To upgrade to this latest version, run the following command:

pip install --upgrade shortterm-memory