Gradient Base Model
- pydantic model llama_index.llms.gradient.GradientBaseModelLLM
Show JSON schema
{ "title": "GradientBaseModelLLM", "description": "Simple abstract base class for custom LLMs.\n\nSubclasses must implement the `__init__`, `complete`,\n `stream_complete`, and `metadata` methods.", "type": "object", "properties": { "callback_manager": { "title": "Callback Manager" }, "max_tokens": { "title": "Max Tokens", "description": "The number of tokens to generate.", "default": 256, "exclusiveMinimum": 0, "exclusiveMaximum": 512, "type": "integer" }, "access_token": { "title": "Access Token", "description": "The Gradient access token to use.", "type": "string" }, "host": { "title": "Host", "description": "The url of the Gradient service to access.", "type": "string" }, "workspace_id": { "title": "Workspace Id", "description": "The Gradient workspace id to use.", "type": "string" }, "is_chat_model": { "title": "Is Chat Model", "description": "Whether the model is a chat model.", "default": false, "type": "boolean" }, "base_model_slug": { "title": "Base Model Slug", "description": "The slug of the base model to use.", "type": "string" }, "class_name": { "title": "Class Name", "type": "string", "default": "custom_llm" } }, "required": [ "base_model_slug" ] }
- Config
arbitrary_types_allowed: bool = True
- Fields
callback_manager (llama_index.callbacks.base.CallbackManager)
- Validators
_validate_callback_manager
»callback_manager
- field access_token: Optional[str] = None
The Gradient access token to use.
- field base_model_slug: str [Required]
The slug of the base model to use.
- field host: Optional[str] = None
The url of the Gradient service to access.
- field is_chat_model: bool = False
Whether the model is a chat model.
- field max_tokens: Optional[int] = 256
The number of tokens to generate.
- Constraints
exclusiveMinimum = 0
exclusiveMaximum = 512
- field workspace_id: Optional[str] = None
The Gradient workspace id to use.
- close() None
- complete(*args: Any, **kwargs: Any) Any
Completion endpoint for LLM.
- stream_complete(prompt: str, **kwargs: Any) Generator[CompletionResponse, None, None]
Streaming completion endpoint for LLM.
- property metadata: LLMMetadata
LLM metadata.