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Build a Chatbot in Streamlit to perform Generative QA with indexed documents in a Vector DB as knowledge base

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abinbev-llm

This project aims to build an MVP to solve the following problem statement:

Build a Chatbot to perform Generative QA with indexed documents in a vector database as knowledge base

https://llm-chatbot-rbjv6s9pz7kcjrjwd4clwm.streamlit.app

Example of usage: How can i estimate rainfall?

Also works in spanish: Como puedo estimar la caida de lluvia?

Project Organization

├── LICENSE
├── Makefile           <- WIP
├── README.md          <- The top-level README for developers using this project.
├── data
│   ├── external       <- Data from third party sources.
│   ├── interim        <- Intermediate data that has been transformed.
│   ├── processed      <- The final, canonical data sets for modeling.
│   └── raw            <- The original, immutable data dump.
│
├──connectors          <- Data Connectors to external sources
│
├── docs               <- WIP
│
├── authentication     <- Authentication implementation for streamlit appication
│
├── pages              <- Pages of the streamlit application 
│
├── config             <- Configuration file
│
├── logs               <- WIP
│
├── models             <- Trained and serialized models, model predictions, or model summaries (WIP)
│
├── notebooks          <- Jupyter notebooks. Naming convention is a number (for ordering),
│                         the creator's initials, and a short `-` delimited description, e.g.
│                         `1.0-jqp-initial-data-exploration`.
│
├── references         <- Data dictionaries, manuals, and all other explanatory materials. (WIP)
│
├── reports            <- WIP
│   └── figures        <- WIP
│
├── requirements.txt (requirements_dev.txt)   <- The requirements file for reproducing the analysis environment, e.g.
│                         generated with `pip freeze > requirements.txt`
│
├── static             <- Static files to be used inside the app
│
├── setup.py           <- makes project pip installable (pip install -e .) so src can be imported
├── src                <- Source code for use in this project.
│   ├── __init__.py    <- Makes src a Python module
│   │
│   ├── data           <- Scripts to download or generate data
│   │   └── make_dataset.py
│   │    └── parser.py Parser for files
│   │  
│   ├── models         <- Scripts to train models and then use trained models to make
│   │   │                 predictions
│   │   ├── predict_model.py
│   │   └── train_model.py
│   │
│   └── visualization  <- Scripts to create exploratory and results oriented visualizations
│       └── visualize.py
│
├── client_config.toml <- Customizable file for client
│
├── settings.py        <- File for setting paths
│
├── streamlit_app.py   <- Streamlit applicatin base
│
├── streamlit_app_pages.py <- Streamlit application splitted into pages
│
├── test_environment.py <- WIP
│
└── tox.ini            <- tox file with settings for running tox; see tox.readthedocs.io

Project based on the cookiecutter data science project template. #cookiecutterdatascience

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Build a Chatbot in Streamlit to perform Generative QA with indexed documents in a Vector DB as knowledge base

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