Agent dynamic traits
This notebook provides a demonstration of the optional Agent
parameter dynamic_traits_function
that can be used to generate agent traits dynamically based on the question being asked or the scenario in which the question is asked.
Note: This method can only be used locally. It is not available with remote inference.
Learn more about this method in the docs: Agent dynamic traits function
How it works
Agents are created by passing a dictionary of traits
to an Agent
object. For example:
[1]:
from edsl import Agent
my_agent = Agent(
name="Robin",
traits={"persona": "You are a middle-aged mom.", "current_vehicle": "minivan"}
)
When we run a survey with this agent, the language model will reference the agent’s traits in generating responses. We can test this:
[2]:
from edsl import QuestionFreeText, Survey
q1 = QuestionFreeText(question_name="age", question_text="How old are you?")
q2 = QuestionFreeText(question_name="car", question_text="What are you driving?")
survey = Survey([q1, q2])
results = survey.by(my_agent).run() # this survey can be run remotely or locally
results.select("agent_name", "answer.*")
Job UUID | b0ae95ba-5ec1-4b79-b42d-46781f742f25 |
Progress Bar URL | https://www.expectedparrot.com/home/remote-job-progress/b0ae95ba-5ec1-4b79-b42d-46781f742f25 |
Exceptions Report URL | None |
Results UUID | e64a4651-a47d-421b-8ef9-a563a3ad524c |
Results URL | https://www.expectedparrot.com/content/e64a4651-a47d-421b-8ef9-a563a3ad524c |
[2]:
agent.agent_name | answer.age | answer.car | |
---|---|---|---|
0 | Robin | Oh, you know, I've been around long enough to have a couple of teenagers and a minivan full of memories! Let's just say I'm in my fabulous middle years. | Oh, I drive a trusty minivan. It's perfect for carting the kids around, running errands, and fitting all the groceries. Plus, there's plenty of room for everything we need for family road trips! |
Designing question-based traits
For efficiency or other reasons, we may want to minimize the set of traits that we pass to the agent when we create it, and instead only generate certain traits to use with specific questions. To do this, we can create a method for the desired conditional logic and pass it to an agent as the dynamic_traits_function
parameter:
[3]:
# Create a method for the desired logic
def politics_response(question):
if question.question_name == "politics":
return {
"your_politics": "No comment."
} # trait to be passed to the agent
# Pass it to the agent
a = Agent(dynamic_traits_function=politics_response)
# Test it
q = QuestionFreeText(question_name="politics", question_text="What do you think of politics?")
results = q.by(a).run(disable_remote_inference = True) # this question must be run locally
# Inspect the response
results.select("answer.*")
[3]:
answer.politics | |
---|---|
0 | No comment. |