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 files.

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>

Note:

1. You can get the LANGCHAIN_API_KEY from LangSmith.
2. Get the MODEL_API from Mattermost.

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

ollama

Run ollama:

ollama serve

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

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.