Source code for our paper :
ActiveRAG: Revealing the Treasures of Knowledge via Active Learning

If you find this work useful, please cite our paper and give us a shining star 🌟

git clone https://github.com/OpenMatch/ActiveRAG
pip install -r requirements.txt

We provide our request logs, so the results in the paper can be quickly reproduced:

python -m logs.eval --dataset nq --topk 5

Parameters:

• dataset: dataset name.
• topk: using top-k of retrieved passages to augment.

We also provide the full request code, you can re-request for further exploration.

First, set your own api-key in agent file:

openai.api_key = 'sk-<your-api-key>'

Then, run the following script:

python -m scripts.run --dataset nq --topk 5

Analyzing log files:

python -m scripts.build --dataset nq --topk 5

Evaluate:

python -m scripts.evaluate --dataset nq --topk 5

If you have questions, suggestions, and bug reports, please send a email to us, we will try our best to help you.

[email protected]