{
 "schema_version": 1,
 "generated": "2026-10-26",
 "id": "plab-lead-clsr-mdia--run-offline-dialect-pipeline",
 "repo": "Plab-Lead/CLSR_MDia",
 "repo_url": "https://github.com/Plab-Lead/CLSR_MDia",
 "repo_slug": "plab-lead-clsr-mdia",
 "title": "Run the offline MDia lifecycle on fixtures",
 "page_title": "How to run the offline MDia lifecycle on fixtures with CLSR MDia",
 "summary": "Run the deterministic toy pipeline to see every MDia stage without API keys or model downloads.",
 "who": "A researcher or developer new to MDia who wants to see the full collect-to-report lifecycle before using real models or data.",
 "problem": "Reading about dialect cards, frozen banks, and route plans is hard without seeing the artifacts they produce.",
 "outcome": "A versioned run directory with split manifests, dialect generations, profiles, route plans, predictions, token accounting, and a reproducibility report.",
 "steps": [
  "Clone the repository at https://github.com/Plab-Lead/CLSR_MDia and open a terminal in its folder.",
  "`python -m venv .venv`",
  "`source .venv/bin/activate`",
  "`python -m pip install -e .`",
  "`mdia pipeline --config configs/toy_mdia.yaml`"
 ],
 "agent_prompt": "In the CLSR_MDia repository, create a virtual environment, install the package with `python -m pip install -e .`, and run `mdia pipeline --config configs/toy_mdia.yaml`. Report the run directory and confirm that manifest.json, report.md, and selection/frozen_dialect_bank.json exist under it.",
 "agents": [
  "any"
 ],
 "difficulty": "Intermediate",
 "time": "30 minutes",
 "basis": "readme",
 "caveat": "The toy pipeline uses redistributable fixtures to exercise the lifecycle; its outputs show the mechanics and are not the benchmark results reported in the paper.",
 "category": "Research",
 "tags": [
  "Research"
 ],
 "lang": "python",
 "requirements": [
  "Python 3.10+ for the offline toy pipeline, or Python 3.11+ for the release reproduction",
  "A terminal and git for cloning the repository",
  "No API keys are needed for the toy pipeline or the offline release reproduction",
  "For new model inference, benchmark inputs from their original sources and provider access (see docs/extending.md)"
 ],
 "risk": "none",
 "seen_in_the_wild": false,
 "mentioned_publicly": false,
 "risks": [],
 "best": true,
 "score": 1.0,
 "evidence": [],
 "url": "https://dedupedai.com/use-cases/plab-lead-clsr-mdia/run-offline-dialect-pipeline/",
 "md": "https://dedupedai.com/use-cases/plab-lead-clsr-mdia/run-offline-dialect-pipeline/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/plab-lead-clsr-mdia--run-offline-dialect-pipeline.json",
 "api_version": "v1"
}