{
 "schema_version": 1,
 "generated": "2026-10-20",
 "id": "pal-ai-lab-cortico--run-several-personas-from-separate-deployments",
 "repo": "Pal-AI-Lab/Cortico",
 "repo_url": "https://github.com/Pal-AI-Lab/Cortico",
 "repo_slug": "pal-ai-lab-cortico",
 "title": "Run several bot personas from separate deployments",
 "page_title": "How to run several bot personas from separate deployments with Cortico",
 "summary": "Create isolated deployment folders so each persona has its own config and memory.",
 "who": "A creator or developer who runs more than one bot persona and wants them kept apart.",
 "problem": "Mixing several personas in one configuration makes settings, endpoints and runtime state hard to keep separate.",
 "outcome": "Two or more isolated deployments inside deployments/, each starting on its own with its own endpoints and settings.",
 "steps": [
  "Run `pnpm start --new`.",
  "Pick a bot package, a directory name and a display name for the new deployment.",
  "Let the new deployment start, then configure its endpoints from the WebUI.",
  "Start a specific deployment by name with `pnpm start second` or the name you chose."
 ],
 "agent_prompt": "In the Cortico repo at <path>, create a new deployment with `pnpm start --new` and then start it by name. Expected output: a second deployment directory under deployments/ that starts separately. Verify that the first deployment is unchanged after the second one is configured.",
 "agents": [
  "any"
 ],
 "difficulty": "Intermediate",
 "time": "30 minutes",
 "basis": "readme",
 "caveat": "The README says each deployment is an isolated configuration directory, but you still need a separate model endpoint or shared endpoint settings for each persona.",
 "category": "Software and DevOps",
 "tags": [
  "Software and DevOps"
 ],
 "lang": "typescript",
 "requirements": [
  "Node 22+",
  "A model endpoint that supports the Responses protocol, or a local llama-server runtime",
  "git, to clone the Cortina workspace for extension work",
  "A coding agent, for the Cortina extension workflow"
 ],
 "risk": "none",
 "seen_in_the_wild": false,
 "mentioned_publicly": false,
 "risks": [],
 "best": false,
 "score": 0.6,
 "evidence": [],
 "url": "https://dedupedai.com/use-cases/pal-ai-lab-cortico/run-several-personas-from-separate-deployments/",
 "md": "https://dedupedai.com/use-cases/pal-ai-lab-cortico/run-several-personas-from-separate-deployments/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/pal-ai-lab-cortico--run-several-personas-from-separate-deployments.json",
 "api_version": "v1"
}