https://github.com/parthsareen/simple-rag

Too many docs? Quickly search over any PDF or Markdown documents
https://github.com/parthsareen/simple-rag

llama local-llm obsidian obsidian-md ollama python rag

Last synced: 21 days ago
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Too many docs? Quickly search over any PDF or Markdown documents

• Host: GitHub
• URL: https://github.com/parthsareen/simple-rag
• Owner: ParthSareen
• Created: 2024-09-23T18:22:37.000Z (3 months ago)
• Default Branch: main
• Last Pushed: 2024-11-30T22:15:35.000Z (24 days ago)
• Last Synced: 2024-11-30T23:23:54.815Z (24 days ago)
• Topics: llama, local-llm, obsidian, obsidian-md, ollama, python, rag
• Language: Python
• Homepage:
• Size: 279 KB
• Stars: 10
• Watchers: 2
• Forks: 1
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# Simple RAG



  





  Run RAG (Retreival Augment Generation) for any documents!



Hey there! 👋 RAG-in-a-box is your go-to tool for quickly setting up Retrieval Augmented Generation (RAG) on your docs. It's perfect for when you're tired of uploading docs to chatgpt or want everything to be saved locally.

- 📚 Handles PDFs and Markdown files

- 🤖 Works with OpenAI and Ollama models

- 🖥️ Easy-to-use interface s/o Gradio

- 💻 CLI for you command-line lovers

## Prerequisites

1. Python 3.10 or higher

2. pip or rye package manager

### Installation

Choose one of the following methods:

- Using pip:

  ```

  pip install -r requirements.lock

  ```

- Using rye:

  ```

  rye sync

  ```

### API Keys

- For OpenAI models: Set the `OPENAI_API_KEY` environment variable with your OpenAI API key.

- For Ollama models: Ensure Ollama is installed and running on your system.

# Using the Gradio Interface

`python3 src/rag_in_a_box/interface.py`



  



# Using the CLI

To use RAG-in-a-box from the command line, you can utilize the `main.py` script. Here’s how you can get started:

1. **Basic Usage:**

   ```

   python3 src/rag_in_a_box/main.py --path 

   ```

   Replace `` with the path to the directory containing your PDF or Markdown files.

2. **Specify Document Loader Type:**

   By default, the script assumes you are loading PDF documents. If you want to load Markdown files, use the `--loader_type` argument:

   ```

   python3 src/rag_in_a_box/main.py --loader_type md --path 

   ```

3. **Persisting the Vector Database:**

   You can specify a custom path to persist the vector database using the `--persist_path` argument:

   ```

   python3 src/rag_in_a_box/main.py --path  --persist_path 

   ```

4. **Choosing the Model:**

   The script supports both OpenAI and Ollama models. You can specify the model to use with the `--model` argument:

   ```

   python3 src/rag_in_a_box/main.py --path  --model 

   ```

5. **Interactive Q&A:**

   Once the documents are loaded and stored, the script enters an interactive Q&A loop. Simply type your questions, and the system will provide answers based on the loaded documents. Type `quit` to exit the loop.

Example command:

   ```

   python3 src/rag_in_a_box/main.py --loader_type pdf --path ./docs --persist_path ./chroma_db --model gpt-4o-mini-2024-07-18

   ```

This command loads PDF documents from the `./docs` directory, stores them in the `./chroma_db` vector database, and uses the `gpt-4o-mini-2024-07-18` model for Q&A.