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# streamlit run src/scholar_sense/apps/vectordb_app.py -- \ | ||
# --backend qdrant \ | ||
# --topK 15 \ | ||
# --model-type open-ai \ | ||
# --model-name text-embedding-ada-002 \ | ||
# --collection-name papers_openai \ | ||
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||
streamlit run src/scholar_sense/apps/app.py -- \ | ||
--backend simple \ | ||
--topK 15 \ | ||
--model-type sentence-transformers \ | ||
--model-name roberta-large-nli-stsb-mean-tokens \ | ||
--encoding-method title \ | ||
--csv-file-path artifacts/data/csv/arxiv.csv \ | ||
--embeddings-file-path artifacts/embeddings/arxiv_embeddings.pkl | ||
--backend qdrant \ | ||
--limit 15 \ | ||
--model-type open-ai \ | ||
--model-name text-embedding-ada-002 \ | ||
--collection-name papers_openai \ | ||
|
||
# streamlit run src/scholar_sense/apps/app.py -- \ | ||
# --backend simple \ | ||
# --limit 15 \ | ||
# --model-type sentence_transformers \ | ||
# --model-name roberta_large_nli_stsb_mean_tokens \ | ||
# --encoding-method title \ | ||
# --csv-file-path artifacts/data/csv/arxiv.csv \ | ||
# --embeddings-file-path artifacts/embeddings/arxiv_embeddings.pkl |
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