Update to Helical

{
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  "connector_id": "asdk_app_6abe37bd8c6c8191afaf84a1b31585b4",
  "created_at": "2026-10-04T19:53:32.501160Z",
  "discoverability": "LISTED",
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  "is_template": false,
  "is_template_instance": false,
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    "app_templates": [],
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    "id": "pluginrel_207be56c6084819192acba120465543c",
    "interface": {
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        "Fine-tune models",
        "Download results"
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      "default_prompts": [
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      "logo_url": "https://files.openai.com/content?id=file_00000000595c820a83c4887d431b0186",
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      "long_description": "Helical lets you run biological foundation models on your own single-cell data, from the chat you're already in.\n\nUpload an .h5ad dataset into your private Helical project, pick a model — scGPT, Geneformer, TranscriptFormer, Cell2Sentence or Nicheformer — and compute embeddings on Helical's GPUs. Follow the run while it goes, read the error if it fails, and download the embeddings when it finishes.\n\nNothing starts on its own. A run is quoted and queued first, and only begins once you approve it in a second, separate step. Every tool works inside the one project your account owns.\n\nRuns use the credits in your existing Helical account.",
      "plugin_category_id": "scientific research",
      "privacy_policy_url": "https://helical.bio/plugin/privacy",
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        "interface": {
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          "default_prompt": "Use $check-credits to check my Helical credit balance.",
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        "description": "Compute cell embeddings for a single-cell dataset with a Helical foundation model, then download the outputs. Use when the user wants embeddings, representations, or features from a dataset already in the platform catalogue. For training a model on labelled data, use fine-tune-model instead.",
        "interface": {
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          "default_prompt": "Use $compute-embeddings to embed my dataset with a Helical model.",
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          "icon_small_url": null,
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          "display_name": "Reconnect Helical",
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