RAG

Installation

We use Poetry to manage dependencies.

poetry shell
poetry install

Create testdata directory in the root directory and add files.

Now we only support .md, .txt, .docx, .pdf files.

You can also import documents from github repositories.

Use pre-commit.

pre-commit install

(Optional) Create a .env file in the root directory and add the following environment variables:

LANGCHAIN_TRACING_V2=true
LANGCHAIN_API_KEY=<LANGCHAIN_API_KEY>
MODEL_API=<the model api from Mattermost>
ACCESS_TOKEN=<Github access token>

Note:

1. You can get the LANGCHAIN_API_KEY from LangSmith.
2. Get the MODEL_API from Mattermost.
3. How to get Github access token: Github Docs.

Usage

Qdrant

預設使用 port:6333

Add or Update Data

如果要新增或修改資料請使用此方法

cd vectorDB
docker-compose -f addData/docker-compose.yml up -d  

Run DB

cd vectorDB
docker build -t polyhistor:db .
docker run -d --restart always -p 6333:6333 --name polyhistor_qdrant polyhistor:db

Create Qdrant collection

cd vectorDB
python3 create_collection.py

Import documents to vectorDB

cd vectorDB
python3 read_docs.py

Ollama

Run Ollama:

ollama serve

Default embedding model is chevalblanc/acge_text_embedding and default language model is qwen:4b.

Q & A

Open a new terminal and run the following command:

cd src
python main.py

Then you can ask questions to the model. If you want to exit, type bye.