GenerativeAgent#
- class langchain_experimental.generative_agents.generative_agent.GenerativeAgent[source]#
Bases:
BaseModel
Agent as a character with memory and innate characteristics.
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be parsed to form a valid model.
- param age: int | None = None#
The optional age of the character.
- param daily_summaries: List[str] [Optional]#
Summary of the events in the plan that the agent took.
- param last_refreshed: datetime [Optional]#
The last time the character’s summary was regenerated.
- param llm: BaseLanguageModel [Required]#
The underlying language model.
- param memory: GenerativeAgentMemory [Required]#
The memory object that combines relevance, recency, and ‘importance’.
- param name: str [Required]#
The character’s name.
- param status: str [Required]#
The traits of the character you wish not to change.
- param summary: str = ''#
Stateful self-summary generated via reflection on the character’s memory.
- param summary_refresh_seconds: int = 3600#
How frequently to re-generate the summary.
- param traits: str = 'N/A'#
Permanent traits to ascribe to the character.
- param verbose: bool = False#
- chain(prompt: PromptTemplate) LLMChain [source]#
Create a chain with the same settings as the agent.
- Parameters:
prompt (PromptTemplate) –
- Return type:
- generate_dialogue_response(observation: str, now: datetime | None = None) Tuple[bool, str] [source]#
React to a given observation.
- Parameters:
observation (str) –
now (datetime | None) –
- Return type:
Tuple[bool, str]
- generate_reaction(observation: str, now: datetime | None = None) Tuple[bool, str] [source]#
React to a given observation.
- Parameters:
observation (str) –
now (datetime | None) –
- Return type:
Tuple[bool, str]
- get_full_header(force_refresh: bool = False, now: datetime | None = None) str [source]#
Return a full header of the agent’s status, summary, and current time.
- Parameters:
force_refresh (bool) –
now (datetime | None) –
- Return type:
str
- get_summary(force_refresh: bool = False, now: datetime | None = None) str [source]#
Return a descriptive summary of the agent.
- Parameters:
force_refresh (bool) –
now (datetime | None) –
- Return type:
str
Summarize memories that are most relevant to an observation.
- Parameters:
observation (str) –
- Return type:
str