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Updated README to include project outline structure.
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README.md
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This project is a demonstration playground for the LLM-enabled architectures built as a submission for the Online MSc in Artificial Intelligence through the University of Bath. The purpose of the project is to explore "LLM-enabled architectures" where an LLM is used in conjunction with some store of private data. The goal is to provide decision support information to technical managers on the _how_ of using LLMs with their organisational data. Specifically by comparing technical architectures and assessing the organisational implications of the technical choices.
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# Demonstration environment
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The project is available as a demonstration running [here on Hugging Face Spaces](https://huggingface.co/spaces/alfraser/llm-arch). This should be the preferred method to interact with the project.
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This project is a demonstration playground for the LLM-enabled architectures built as a submission for the Online MSc in Artificial Intelligence through the University of Bath. The purpose of the project is to explore "LLM-enabled architectures" where an LLM is used in conjunction with some store of private data. The goal is to provide decision support information to technical managers on the _how_ of using LLMs with their organisational data. Specifically by comparing technical architectures and assessing the organisational implications of the technical choices.
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# File Structure
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```
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llm-arch
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βββ config
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β βββ architectures.json (configuration for the architectures under test and displayed in the UI)
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βββ data
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β βββ fine_tuning (data and scripts related to fine-tuning LLMs)
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β βββ json (raw json files containing the synthetic private data built for the project)
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β βββ sqlite
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β β βββ 01_all_products_dataset.db (sqlite db containing all products generated)
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β β βββ 02_baseline_dataset.db (sqlite db containing the subset of data selected to be the baseline)
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β β βββ test_records.db (sqlite database containing the peristed test results)
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β βββ vector_stores
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βββ img
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βββ pages
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βββ src
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β βββ data_synthesis
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β βββ training
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β βββ architectures.py (the core architecture pipeline code including components, and trace)
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β βββ common.py (utilities for common functions, e.g. security token access, data type manipulations)
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β βββ datatypes.py (object oriented representation of the test data and single point for runtime access of the product DB)
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β βββ st_helpers.py (helpers specific to streamlit)
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β βββ testing.py (functionality relating to running, recording and reporting on batches of tests)
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βββ Home.py (main entry point for streamlit - first page in the streamlit app)
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βββ local_env.yml (conda environment for running project locally)
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βββ README.md (readme - this file)
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βββ requirements.txt (requirements file for additional requirements in the HF spaces environment - do not use for local running of the project)
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```
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# Demonstration environment
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The project is available as a demonstration running [here on Hugging Face Spaces](https://huggingface.co/spaces/alfraser/llm-arch). This should be the preferred method to interact with the project.
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