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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](../indexing/SKILL.md). Route
multi-query Markdown/CSV/annotation generation to
[reporting](../reporting/SKILL.md).
## 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](references/api-reference.md) for method signatures and
response fields, [cli-reference.md](references/cli-reference.md) for command
forms, [workflows.md](references/workflows.md) for recipes, and
[troubleshooting.md](references/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.