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Code for Search-in-the-Chain: Towards Accurate, Credible and Traceable Large Language Models for Knowledge-intensive Tasks

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This is the project for Search-in-the-Chain

Welcome to read our paper:https://arxiv.org/abs/2304.14732

@misc{xu2023searchinthechain,
      title={Search-in-the-Chain: Towards Accurate, Credible and Traceable Large Language Models for Knowledge-intensive Tasks}, 
      author={Shicheng Xu and Liang Pang and Huawei Shen and Xueqi Cheng and Tat-Seng Chua},
      year={2023},
      eprint={2304.14732},
      archivePrefix={arXiv},
      primaryClass={cs.CL}
}

You can start Searchain quickly from LLamaIndex: here

You can try to run our project by following the steps below, running in different environments may encounter various problems. We are still working hard to make it robust and bug-free.

1. Index your corpus via ColBERT

Process your data into a format suitable for ColBERT indexing

python ColBERT/process_hotpotqa_wiki.py

Indext your data

python ColBERT/index.py

Run the service for retrieval

python ColBERT/server_retrieval.py

2. Run the serive for verification and completion in Information Retrieval

python Server/server.py

3. Construct Chain-of-Query and and interact with search service (communicate with Server/server.py)

An example on HotpotQA in the setting without IR:

python SearChain_without_IR.py

An example on HotpotQA in the setting with IR:

python SearChain_w_IR.py

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Code for Search-in-the-Chain: Towards Accurate, Credible and Traceable Large Language Models for Knowledge-intensive Tasks

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