https://github.com/dominodatalab/rag

https://github.com/dominodatalab/rag

Last synced: 29 days ago
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• Host: GitHub
• URL: https://github.com/dominodatalab/rag
• Owner: dominodatalab
• Created: 2023-11-03T21:07:44.000Z (about 1 year ago)
• Default Branch: main
• Last Pushed: 2023-11-30T20:00:22.000Z (about 1 year ago)
• Last Synced: 2023-11-30T21:22:24.012Z (about 1 year ago)
• Language: Jupyter Notebook
• Size: 2.32 MB
• Stars: 1
• Watchers: 4
• Forks: 1
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# RAG

## Files

*  RAG.ipynb : This notebook contains all the logic to load embeddings, setup the QA chain for RAG and allows users to ask queries once all the hyperparameters have been finalized.

  

*  MLflow_eval.ipynb : This notebook contains code to evaluate a RAG pipeline for faithfulness and relevance using Mlflow. The metrics are also stored and can be visualized in the Experiments tab in Domino

  

*  RAGAS_eval.ipynb : This notebook uses the RAGAS package to evaluate a RAG pipeline. This is another example of how to evaluate a RAG pipeline, RAGAS offers a couple of more metrics than MLFlow

  

*  example_prompts.txt : Has a few examples of questions that can be presented as prompts to the QA chain

  

*  app.sh : Script required to setup and use Streamlit in Domino

  

*  streamlit_app.py : This file contains code that sets up the UI and workflow for a Streamlit chatbot. The app needs an Anthropic and Qdrant key to set in the sidebar to run

On `se-demo` this was run on a `Medium` hardware tier

## Environment Setup

### Custom base image 

```Domino Standard Environment Py3.9 R4.2```

### Dockerfile instructions

```

USER root:root

RUN pip uninstall --yes mlflow

RUN pip install openai langchain  transformers tiktoken  sentence-transformers \

                qdrant-client ragas mlflow==2.8.0 getpass4 anthropic evaluate \

                textstat streamlit pypdf accelerate peft bitsandbytes

RUN pip install -i https://test.pypi.org/simple/ streamlit-chat-domino

```

On `se2-demo` this environment is available as `MedRAG`

###