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---
title: Simple_Gradio_RAG_App_of_RGov_Talks
app_file: rag_apps/rag_gradio/gradio_rag1a.py
sdk: gradio
sdk_version: 5.1.0
---
# dcr-3-frameworks
<a target="_blank" href="https://cookiecutter-data-science.drivendata.org/">
<img src="https://img.shields.io/badge/CCDS-Project%20template-328F97?logo=cookiecutter" />
</a>
Comparison of Multiple Frammeworks
## Project Organization
```
β”œβ”€β”€ LICENSE <- Open-source license if one is chosen
β”œβ”€β”€ Makefile <- Makefile with convenience commands like `make data` or `make train`
β”œβ”€β”€ README.md <- The top-level README for developers using this project.
β”œβ”€β”€ data
β”‚ β”œβ”€β”€ external <- Data from third party sources.
β”‚ β”œβ”€β”€ interim <- Intermediate data that has been transformed.
β”‚ β”œβ”€β”€ processed <- The final, canonical data sets for modeling.
β”‚ └── raw <- The original, immutable data dump.
β”‚
β”œβ”€β”€ docs <- A default mkdocs project; see www.mkdocs.org for details
β”‚
β”œβ”€β”€ models <- Trained and serialized models, model predictions, or model summaries
β”‚
β”œβ”€β”€ notebooks <- Jupyter notebooks. Naming convention is a number (for ordering),
β”‚ the creator's initials, and a short `-` delimited description, e.g.
β”‚ `1.0-jqp-initial-data-exploration`.
β”‚
β”œβ”€β”€ pyproject.toml <- Project configuration file with package metadata for
β”‚ dcr_3_frameworks and configuration for tools like black
β”‚
β”œβ”€β”€ references <- Data dictionaries, manuals, and all other explanatory materials.
β”‚
β”œβ”€β”€ reports <- Generated analysis as HTML, PDF, LaTeX, etc.
β”‚ └── figures <- Generated graphics and figures to be used in reporting
β”‚
β”œβ”€β”€ requirements.txt <- The requirements file for reproducing the analysis environment, e.g.
β”‚ generated with `pip freeze > requirements.txt`
β”‚
β”œβ”€β”€ setup.cfg <- Configuration file for flake8
β”‚
└── dcr_3_frameworks <- Source code for use in this project.
β”‚
β”œβ”€β”€ __init__.py <- Makes dcr_3_frameworks a Python module
β”‚
β”œβ”€β”€ config.py <- Store useful variables and configuration
β”‚
β”œβ”€β”€ dataset.py <- Scripts to download or generate data
β”‚
β”œβ”€β”€ features.py <- Code to create features for modeling
β”‚
β”œβ”€β”€ modeling
β”‚ β”œβ”€β”€ __init__.py
β”‚ β”œβ”€β”€ predict.py <- Code to run model inference with trained models
β”‚ └── train.py <- Code to train models
β”‚
└── plots.py <- Code to create visualizations
```
--------