Parameters
url – URL of the site currently on.
browser_content – Content of the page as currently displayed by the browser.
Returns
Next browser command to run.
Example
browser_content = "...."
llm_command = natbot.run("www.google.com", browser_content)
classmethod from_default(objective: str, **kwargs: Any) → NatBotChain[source]¶
Load with default LLMChain.
classmethod from_llm(llm: BaseLanguageModel, objective: str, **kwargs: Any) → NatBotChain[source]¶
Load from LLM.
classmethod from_orm(obj: Any) → Model¶
get_input_schema(config: Optional[RunnableConfig] = None) → Type[BaseModel]¶
Get a pydantic model that can be used to validate input to the runnable.
Runnables that leverage the configurable_fields and configurable_alternatives
methods will have a dynamic input schema that depends on which
configuration the runnable is invoked with.
This method allows to get an input schema for a specific configuration.
Parameters
config – A config to use when generating the schema.
Returns
A pydantic model that can be used to validate input.
classmethod get_lc_namespace() → List[str]¶
Get the namespace of the langchain object.
For example, if the class is langchain.llms.openai.OpenAI, then the
namespace is [“langchain”, “llms”, “openai”]
get_output_schema(config: Optional[RunnableConfig] = None) → Type[BaseModel]¶
Get a pydantic model that can be used to validate output to the runnable.
Runnables that leverage the configurable_fields and configurable_alternatives
methods will have a dynamic output schema that depends on which
configuration the runnable is invoked with.
This method allows to get an output schema for a specific configuration.
Parameters