Source: https://docs.nygen.io/CyteType/api/llm-config.html
Revision: 6ce97c558d4353ff1796056a86b1e6d8b42f4b4e

LLM configuration
*****************

"CyteType.run()" accepts your own models in "llm_configs", a list of
dicts. Each dict is validated against "cytetype.api.LLMModelConfig"
before any file is uploaded: a missing required field raises a
"pydantic.ValidationError", and keys that are not fields of the model
are ignored, so check their spelling (field names are case-sensitive).
The server then checks every model before the job starts, and "run()"
raises "LLMValidationError" if one fails. Use your own LLM explains
when to use these fields, with examples.

   adata = annotator.run(
       study_context="Human PBMCs from a healthy donor.",
       llm_configs=[
           {"provider": "openai", "name": "<model-name>", "apiKey": "<your-api-key>"},
       ],
   )

Each configuration needs either "apiKey" or all three AWS fields
("awsAccessKeyId", "awsSecretAccessKey" and "awsDefaultRegion").

class cytetype.api.LLMModelConfig

   The fields of one entry in "llm_configs".

   provider: str

      Required. The model provider: "anthropic", "bedrock",
      "deepseek", "fireworks", "google", "groq", "huggingface",
      "mistral", "nebius", "openai", "openrouter", "together",
      "vertex" or "xai".

   name: str

      Required. The model name, as the provider names it.

   apiKey: str | None = None

      Your API key for the provider. Required unless the three AWS
      fields are set.

   baseUrl: str | None = None

      The base URL of the provider’s API. The "openai" provider uses
      it to reach OpenAI-compatible servers, and "vertex" uses it too;
      other providers ignore it.

   awsAccessKeyId: str | None = None

      AWS access key ID for "bedrock". Set all three AWS fields
      together.

   awsSecretAccessKey: str | None = None

      AWS secret access key for "bedrock".

   awsDefaultRegion: str | None = None

      AWS region for "bedrock".

   modelSettings: dict[str, Any] | None = None

      Extra settings for the requests to the model, such as
      "temperature".

   targetAgents: list[str] | None = []

      The CyteType agents that use this model: "contextualizer",
      "annotator" or "reviewer". An empty list means all agents.
      "summarizer", "clinician" and "chat" are also accepted but have
      no effect: the current workflow does not use the summarizer, and
      target analysis and Chat always use CyteType’s hosted models.

   skipValidation: bool = False

      Has no effect: the server validates every model regardless.

   allowFallback: bool = False

      If true, an agent tries this model only after its models without
      "allowFallback".