{
 "schema_version": 1,
 "generated": "2026-10-20",
 "id": "jsdsg666-autowwtp-asm-demo--calibrate-asm-model-from-task-file",
 "repo": "jsdsg666/AutoWWTP-ASM-Demo",
 "repo_url": "https://github.com/jsdsg666/AutoWWTP-ASM-Demo",
 "repo_slug": "jsdsg666-autowwtp-asm-demo",
 "title": "Calibrate an ASM model from a task file",
 "page_title": "How to calibrate an ASM model from a task file with Auto WWTP ASM Demo",
 "summary": "Run the full ASM workflow on plant data and get a report, calibration results and a final summary.",
 "who": "A wastewater engineer who has plant data in a spreadsheet and needs an ASM model calibrated for an anaerobic, anoxic or aerobic tank or the full process section.",
 "problem": "Building an ASM model, running sensitivity analysis and calibrating parameters by hand takes repeated setup and manual checks.",
 "outcome": "A run folder with the process context, plan, configuration, sensitivity and calibration results, figures, an asm_report.md and asm_report.pdf, and final_result.json.",
 "steps": [
  "Install the dependencies with `pip install langgraph langchain-core langchain-openai langchain-anthropic langchain-google-genai pandas numpy scipy matplotlib openpyxl markdown-pdf pymoo`.",
  "Set the LLM variables in PowerShell, starting with `$env:AUTOWWTP_LLM_API_KEY=\"your-api-key\"`, then set AUTOWWTP_LLM_BASE_URL, AUTOWWTP_LLM_MODEL and AUTOWWTP_LLM_MESSAGE_CLASS as shown in the LLM Configuration section.",
  "Open a terminal in the code/langgraph-en folder of your clone, since the README path is a local Windows path you must replace.",
  "Confirm that your task file in task/ names the data path such as input/data1.xlsx, the modeled object, the target state variables, the boundary conditions and the calibration targets.",
  "Run `python main.py --task-file task/task1.md`.",
  "Open the new output/task-YYYYMMDD-HHMMSS-ffffff folder and read asm_report.md and final_result.json."
 ],
 "agent_prompt": "Use the AutoWWTP-ASM repo at <repo-folder>/code/langgraph-en to run the task file <task-file> with the LLM variables already set. Expected output: a new output/task-* folder containing asm_report.md, final_result.json and midoutput/calibration.json. Verify that midoutput/sensitivity.json and midoutput/calibration.json both exist before reporting success.",
 "agents": [
  "any"
 ],
 "difficulty": "Intermediate",
 "time": "1 hour",
 "basis": "readme",
 "caveat": "The README gives a local Windows path and a placeholder LLM base URL, so you must adapt both before the first run.",
 "category": "Research",
 "tags": [
  "Research"
 ],
 "lang": "python",
 "requirements": [
  "Python 3.10 or later",
  "An LLM service with an API key, base URL, model name and message class (openai, anthropic or gemini)",
  "A task text file and an input spreadsheet such as input/data1.xlsx",
  "Ability to edit the README's local Windows path to match your clone location"
 ],
 "risk": "none",
 "seen_in_the_wild": false,
 "mentioned_publicly": false,
 "risks": [
  {
   "tag": "credentials",
   "notice": "Keep your LLM API key in environment variables as the README advises and do not paste it into task files or source code."
  }
 ],
 "best": true,
 "score": 1.0,
 "evidence": [],
 "url": "https://dedupedai.com/use-cases/jsdsg666-autowwtp-asm-demo/calibrate-asm-model-from-task-file/",
 "md": "https://dedupedai.com/use-cases/jsdsg666-autowwtp-asm-demo/calibrate-asm-model-from-task-file/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/jsdsg666-autowwtp-asm-demo--calibrate-asm-model-from-task-file.json",
 "api_version": "v1"
}