Removed some requirements from Dockerfile for AWS deployment to reduce container size

Allowed for app running on AWS to use smaller embedding model and not to load representation LLM (due to size restrictions).

Can split passages into sentences. Improved embedding, LLM representation models, improved zero shot capabilities

Updated packages. Improve hierarchy vis. Better models - mixedbread and phi3. Now option to split texts into sentences before modelling.

Hopefully now LLM download from hub should work

Added note to say that LLM representation is not currently working on the HF website

Trying to download LLM to local_dir instead of cache_dir

LLM model save is failing in Huggingface - attempting instead to save to base folder

Added clean data options, improved re-representation options and visualisation. General format changes

Lots of general fixes. New visualisations, fixed hierarchical vis for zero shot. Added calc all probabilities.

Changed Phi model to smaller StableLM 2 1.6. Fixed a None type detection error.

More efficient embeddings save and representations load/process. Custom visualisation hover option added, formatting improvements. Version 0.1?

Hopefully fixed install and load of LLM model on systems without a HF_HOME environmental variable

Greatly increased low resource process dimensions for higher quality. Visualisations disabled by default to increase speed.

Greatly improved low resource mode speed (at cost of potential quality)

Changed zero shot min similarity to 0.5

Now should save embeddings by default. Added random seed to representation

Fixed llm_config, environmental variable, zero shot topic model errors with quick embeddings

removed cpu_config as causing problems

Model export changed to safetensors. Improved representational model function. Got zero shot topic modelling working

first commit