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name: querying description: "Guides paperai semantic and weighted queries, result filtering, article metadata display, interactive shell use, enriched API search, and optional search UI integration." disable-model-invocation: true metadata: disco-role: operating license: Apache 2.0

Querying

Use this route for one-shot paper searches, interactive terminal queries, API integration, or a small application around a saved paperai index. It assumes an articles.sqlite database and compatible txtai model directory already exist; route index construction to indexing. Route multi-query Markdown/CSV/annotation generation to reporting.

Fast route

1. Confirm the model directory contains both articles.sqlite and a saved embeddings config/model.
2. Run python -m paperai.query "your query" [topn] [model-dir] [threshold].
3. Use +token to require a token and -token to exclude matching sections; start with the default threshold of 0.25.
4. For repeated terminal use, run paperai <model-dir> and enter queries at the (paperai) prompt. For services, configure txtai's API with paperai.api.API and use its enriched article response.

Read api-reference.md for method signatures and response fields, cli-reference.md for command forms, workflows.md for recipes, and troubleshooting.md for failure recovery.

Important behavior

Query.run defaults topn to 10 through Query.query and the search threshold to 0.25. A query of * returns no vector matches in the direct query path; reports use * specially for all articles. A CPU package import or framework availability check does not validate a particular downloaded embedding model.