warisgill/MeanCache

Datasets and the main code will be available soon.

1

stars

4

commits

Python

primary language

Jun 24, 2025

updated

README

Dataset Information

  • The contextual queries datasets are located in the dataset_contextual_queries directory
  • Additional datasets used in experiments are sourced from publicly available repositories. Please use them from their original locations to ensure compliance with their licenses and terms of use.

Code Informtion

  • generate_scripts.py: This script generates the necessary scripts for training and evaluating the MeanCache model.
  • fl_sim_train.py: This script is used for training the MeanCache model using Federated Learning simulation.
  • cache_comparison.py and eval.py: Contains basic cache comparison functions.
  • utils.py: Contains utility functions used across the codebase.
  • logs/: This directory contains logs generated during the training and evaluation processes.
  • run.sh: contains configurations for running the training the scripts.

Other Work on This Topic

During my Redis internship, I trained embedding models for semantic caching (redis/langcache-embed-v1 and redis/langcache-embed-v2), reaching thousands of downloads on Huggingface. The corresponding research paper is Advancing Semantic Caching for LLMs with Domain-Specific Embeddings and Synthetic Data. This might be useful for those interested in semantic caching techniques and embedding models.

Contributors

warisgill

4 commits

warisgill/MeanCache

Datasets and the main code will be available soon.

1

stars

4

commits

Python

primary language

Jun 24, 2025

updated

README

Dataset Information

  • The contextual queries datasets are located in the dataset_contextual_queries directory
  • Additional datasets used in experiments are sourced from publicly available repositories. Please use them from their original locations to ensure compliance with their licenses and terms of use.

Code Informtion

  • generate_scripts.py: This script generates the necessary scripts for training and evaluating the MeanCache model.
  • fl_sim_train.py: This script is used for training the MeanCache model using Federated Learning simulation.
  • cache_comparison.py and eval.py: Contains basic cache comparison functions.
  • utils.py: Contains utility functions used across the codebase.
  • logs/: This directory contains logs generated during the training and evaluation processes.
  • run.sh: contains configurations for running the training the scripts.

Other Work on This Topic

During my Redis internship, I trained embedding models for semantic caching (redis/langcache-embed-v1 and redis/langcache-embed-v2), reaching thousands of downloads on Huggingface. The corresponding research paper is Advancing Semantic Caching for LLMs with Domain-Specific Embeddings and Synthetic Data. This might be useful for those interested in semantic caching techniques and embedding models.

Contributors

warisgill

4 commits

Languages

Python

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