metadata

license: cc-by-nc-sa-4.0

This dataset contains the embeddings for the segmented TREC RAG 2024 corpus, embedded with the Cohere Embed V3 model.

You can search on this dataset with just 500MB of memory using DiskVectorIndex.

Installation & Usage

Get your free Cohere API key from cohere.com. You must set this API key as an environment variable:

export COHERE_API_KEY=your_api_key

Install the package:

pip install DiskVectorIndex

You can then search via:

from DiskVectorIndex import DiskVectorIndex

index = DiskVectorIndex("Cohere/trec-rag-2024-index")

while True:
    query = input("\n\nEnter a question: ")
    docs = index.search(query, top_k=3)
    for doc in docs:
        print(doc)
        print("=========")

License

Please observe the License for the TREC RAG 2024 Corpus. The license displayed here is just for the embeddings.