{
 "schema_version": 1,
 "generated": "2026-10-24",
 "id": "fsdatalab-quail--run-long-llm-job-on-gpu-server",
 "repo": "fsdatalab/quail",
 "repo_url": "https://github.com/fsdatalab/quail",
 "repo_slug": "fsdatalab-quail",
 "title": "Run a long LLM query on a GPU server and reconnect later",
 "page_title": "How to run a long LLM query on a GPU server and reconnect later with Quail",
 "summary": "Submit a query to a Quail Server on your GPU machine, disconnect, and fetch results later.",
 "who": "A team member with a GPU machine who runs big jobs that take longer than a laptop session should stay connected.",
 "problem": "A long-running LLM job can fail or be lost if the client disconnects while it runs.",
 "outcome": "A saved query on the server that you can watch, reconnect to by query id, and collect results from when it finishes.",
 "steps": [
  "On the GPU machine, run `uv pip install \"quail-engine[server]\"` to install the server extra.",
  "Start the HTTP server by running `quail-server`.",
  "From the client, open Quail.Session with endpoint set to the server address, then call session.sql(sql, dialect=\"bq\").submit().",
  "Call run.watch() to print progress, or note the query id and later call get_run(query_id) to reconnect.",
  "Call run.result().collect() to get the table once the run is done."
 ],
 "agent_prompt": "Use the repo fsdatalab/quail to submit the SQL query in <sql_file> to a Quail Server at <server_address>, save the query id, and later call get_run to fetch the result table. Output the final table as CSV. Verify that the server returned a completed status before collecting results.",
 "agents": [
  "any"
 ],
 "difficulty": "Advanced",
 "time": "1 hour 15 minutes",
 "basis": "readme",
 "caveat": "The server runs on the machine that has the GPU, so you need network access to that machine and the README does not describe authentication for the endpoint.",
 "category": "Data and analytics",
 "tags": [
  "Data and analytics"
 ],
 "lang": "python",
 "requirements": [
  "Python 3.12",
  "An NVIDIA CUDA GPU from the supported list (for example H100 SXM)",
  "uv installed to run the pip install command",
  "A table of text rows (for example reviews with an id and a body column)"
 ],
 "risk": "none",
 "seen_in_the_wild": false,
 "mentioned_publicly": false,
 "risks": [],
 "best": false,
 "score": 0.8,
 "evidence": [],
 "url": "https://dedupedai.com/use-cases/fsdatalab-quail/run-long-llm-job-on-gpu-server/",
 "md": "https://dedupedai.com/use-cases/fsdatalab-quail/run-long-llm-job-on-gpu-server/index.md",
 "disclaimer": "Deduped lists open-source repositories that belong to other people. We do not own, maintain, audit, or vouch for any of them, and a repo appearing here is not an endorsement or a safety check. The use cases, steps, and prompts are written by AI and may be incomplete, outdated, or just wrong. Where a use case is marked \"Seen in the wild\", we link to public posts where someone described something similar, but we have not verified those posts and the use case itself is still our AI's own write-up. Use all of this at your own risk. Only run code, commands, or agents on systems and accounts you are authorized to use, and read the code and every command before you run it, especially anything that touches credentials, files, or the network. Nothing here is professional, security, legal, or financial advice. All trademarks and project names belong to their respective owners, and their use here does not imply affiliation. Content is provided as is, without warranties of any kind. Found a mistake, a safety problem, or something you want removed? Email hello@dedupedai.com and we will look at it promptly.",
 "api": "https://dedupedai.com/api/v1/usecases/fsdatalab-quail--run-long-llm-job-on-gpu-server.json",
 "api_version": "v1"
}