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---
title: Vc Aie4 Pythonic RAG
emoji: 🌖
colorFrom: blue
colorTo: indigo
sdk: docker
pinned: false
license: apache-2.0
---
Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
# Summary
This is my completed pythonic RAG assignment, completed for Session 3 of the AI Engineering Cohort 4.
I implemented the following:
1. Allow user to upload TWO documents (instead of a single document)
2. Format of doc: they can be either text files or pdf docs.
3. Text splitter - RecursiveTextSplitter from Langchain
4. Vector store - using Chroma db
5. Coded the chain in two ways for my own education
a. traditional Langchain syntax - two step process of with 'stuff documents chain' and 'retrieval chain'
b. using LCEL syntax with Runnables
6. Most processing pythonic steps implemented via a single class with modular components
that can be replaced with others (e.g., text splitter, vector store, etc.)
# Retaining the original content of the README.md for my future reference!!
# Deploying Pythonic Chat With Your Text File Application
In today's breakout rooms, we will be following the processed that you saw during the challenge - for reference, the instructions for that are available [here](https://github.com/AI-Maker-Space/Beyond-ChatGPT/tree/main).
Today, we will repeat the same process - but powered by our Pythonic RAG implementation we created last week.
You'll notice a few differences in the `app.py` logic - as well as a few changes to the `aimakerspace` package to get things working smoothly with Chainlit.
## Reference Diagram (It's Busy, but it works)
## Deploying the Application to Hugging Face Space
Due to the way the repository is created - it should be straightforward to deploy this to a Hugging Face Space!
> NOTE: If you wish to go through the local deployments using `chainlit run app.py` and Docker - please feel free to do so!
<details>
<summary>Creating a Hugging Face Space</summary>
1. Navigate to the `Spaces` tab.
2. Click on `Create new Space`
3. Create the Space by providing values in the form. Make sure you've selected "Docker" as your Space SDK.
</details>
<details>
<summary>Adding this Repository to the Newly Created Space</summary>
1. Collect the SSH address from the newly created Space.
> NOTE: The address is the component that starts with `[email protected]:spaces/`.
2. Use the command:
```bash
git remote add hf HF_SPACE_SSH_ADDRESS_HERE
```
3. Use the command:
```bash
git pull hf main --no-rebase --allow-unrelated-histories -X ours
```
4. Use the command:
```bash
git add .
```
5. Use the command:
```bash
git commit -m "Deploying Pythonic RAG"
```
6. Use the command:
```bash
git push hf main
```
7. The Space should automatically build as soon as the push is completed!
> NOTE: The build will fail before you complete the following steps!
</details>
<details>
<summary>Adding OpenAI Secrets to the Space</summary>
1. Navigate to your Space settings.
2. Navigate to `Variables and secrets` on the Settings page and click `New secret`:
3. In the `Name` field - input `OPENAI_API_KEY` in the `Value (private)` field, put your OpenAI API Key.
4. The Space will begin rebuilding!
</details>
## 🎉
You just deployed Pythonic RAG!
Try uploading a text file and asking some questions!
## 🚧CHALLENGE MODE 🚧
For more of a challenge, please reference [Building a Chainlit App](./BuildingAChainlitApp.md)!
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