Re-added TruncatedSVD dependency to topic_core_funcs.py

Debugged reference to random_seed in vectorisation and reference to torch in representation_model.py

Importing space package near start of app now to avoid issue with cuda being initialised before

Rearranged functions for embeddings creation to be compatible with zero GPU space. Updated packages.

Added example of how to run function from command line. Updated packages. Embedding model default now smaller and at fp16.

Improved initial clean options. Now has option to return embeddings only.

App now retains original index following cleaning to allow for referring back to original data

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

Only aggregate topics not 'other', allowed for minimum sentence length, default max_topics now will auto aggregate topics. Added Cognito Auth functionality (boto3 with AWS).

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.

Minor cleaning, csv formatting changes

Reduce outliers now more efficient and relabels with correct vectoriser. Default topic labels now tidier. Hiearchical topics outputs more useful for joining to df afterwards. Switched low resource reduction algorithm to UMAP as default is not good.

Should now parse custom regex correctly. Will now wipe previously created embeddings if 'low resource mode' option switched.

Allowed for uploading custom regex for cleaning. Fixed calculate all probabilities, reduce outliers. Added text tree for hierarchical modelling.

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

Some text changes. Fixed a couple of TF-IDF embeddings issues

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