https://github.com/laolarou726/rag_demo

This is a minimal demo project to show the capabilities of a RAG system using LangChain and Milvus, it contains all the things you required to build a basic RAG system.
https://github.com/laolarou726/rag_demo

demo knowledge-base langchain llm mark milvus minimal ollama pdf plain python rag vector-database

Last synced: 7 months ago
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This is a minimal demo project to show the capabilities of a RAG system using LangChain and Milvus, it contains all the things you required to build a basic RAG system.

• Host: GitHub
• URL: https://github.com/laolarou726/rag_demo
• Owner: laolarou726
• License: mit
• Created: 2025-03-17T19:29:14.000Z (7 months ago)
• Default Branch: master
• Last Pushed: 2025-03-17T20:31:46.000Z (7 months ago)
• Last Synced: 2025-03-17T20:35:13.321Z (7 months ago)
• Topics: demo, knowledge-base, langchain, llm, mark, milvus, minimal, ollama, pdf, plain, python, rag, vector-database
• Language: Python
• Homepage:
• Size: 26.4 KB
• Stars: 2
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

          
# RAG DEMO

![GitHub](https://img.shields.io/github/license/laolarou726/RAG_Demo?logo=github&style=for-the-badge)

![Maintenance](https://img.shields.io/maintenance/yes/2025?logo=diaspora&style=for-the-badge)

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This is a minimal demo project to show the capabilities of a RAG system using `LangChain` and `Milvus`, it contains all the things you required to build a basic RAG system.

## Before Start

First, make a copy of `.env.sample` and rename it to `.env`, and change any fields need to be changed

Then:

1. Setup the `Milvus` as the vector database

   1. See folder `Milvus`

2. Setup the `Ollama` for the document tokenization and interaction

   1. See [Setup - OllamaEmbeddings](https://python.langchain.com/docs/integrations/text_embedding/ollama/)

   2. See [Ollama](https://ollama.com/)

3. Prep the documents used for RAG and the vector DB

4. Copy all the documents to the `Documents` folder under the project root

5. Run `python prep_doc.py` to prepare the documents for the RAG system

6. You can run `python milvus_search.py` to verify all the documents has been loaded to the vector DB

## Start the demo

Run `python main.py` and type anything you want to ask the RAG system

## Screenshots

### Ask RAG a random question

![a2f22b53e37ee6fb92e43bd67d735e20](https://github.com/user-attachments/assets/bfc7f3e0-bea7-4b3f-9f1f-855f4b78c1fa)

### Vector Database

![fb20250642869db7e0e8dd406774fdd3](https://github.com/user-attachments/assets/e8649171-8950-4693-b2d8-02e4d1cbc72b)

![680b5c08190bfca80f51d1aeef6edff9](https://github.com/user-attachments/assets/af31f243-6b4f-4763-9e63-b0e53f2efc75)