Starter Tutorial

! uv pip install edsl -q

pip install git+https://github.com/expectedparrot/edsl.git@main

pip show edsl

pip install --upgrade edsl

from edsl import login

login()

from edsl import (
  # QuestionCheckBox,
  # QuestionExtract,
  # QuestionFreeText,
  # QuestionFunctional,
  # QuestionLikertFive,
  # QuestionLinearScale,
  # QuestionList,
  QuestionMultipleChoice,
  # QuestionNumerical,
  # QuestionRank,
  # QuestionTopK,
  # QuestionYesNo
)

q = QuestionMultipleChoice.example() # substitute any question type class name
q

from edsl import QuestionMultipleChoice

q = QuestionMultipleChoice(
  question_name = "smallest_prime",
  question_text = "Which is the smallest prime number?",
  question_options = [0, 1, 2, 3]
)

results = q.run()

results.select("model", "smallest_prime", "smallest_prime_comment")

results.columns

from edsl import QuestionLinearScale, QuestionFreeText

q_enjoy = QuestionLinearScale(
  question_name = "enjoy",
  question_text = "On a scale from 1 to 5, how much do you enjoy reading?",
  question_options = [1, 2, 3, 4, 5],
  option_labels = {1:"Not at all", 5:"Very much"}
)

q_favorite_place = QuestionFreeText(
  question_name = "favorite_place",
  question_text = "Describe your favorite place for reading."
)

from edsl import Survey

survey = Survey(questions = [q_enjoy, q_favorite_place])

from edsl import AgentList, Agent

agents = AgentList(
  Agent(traits = {"persona":p}) for p in ["artist", "mechanic", "sailor"]
)

from edsl import Model

# Model.available() # uncomment this code and run it to see the list of available models

Model()

from edsl import ModelList, Model

models = ModelList(
  Model(m) for m in ["gpt-4o", "gemini-pro"]
  )

results = survey.by(agents).by(models).run()

(
  results
  .sort_by("persona", "model")
  .select("model", "persona", "enjoy", "favorite_place")
)

results = survey.by(agents).by(models).run(background=True)

results.fetch()

results.columns # to view a list of all columns

results.select("answer.*") # to view all answers

from edsl import QuestionNumerical, QuestionYesNo, Survey

q1 = QuestionNumerical(
  question_name = "random_number",
  question_text = "Pick a random number between 1 and 1,000."
)

q2 = QuestionYesNo(
  question_name = "prime",
  question_text = "Is this a prime number: {{ random_number.answer }}"
)

survey = Survey([q1, q2])

results = survey.run()

results.select("random_number", "prime_user_prompt", "prime", "prime_comment")

from edsl import QuestionNumerical, QuestionYesNo, Survey

q1 = QuestionNumerical(
  question_name = "random_number",
  question_text = "Pick a random number between 1 and 1,000."
)

q2 = QuestionYesNo(
  question_name = "prime",
  question_text = "Is the number you picked a prime number?"
)

survey = Survey([q1, q2]).add_targeted_memory(q2, q1)

results = survey.run()

results.select("random_number", "prime_user_prompt", "prime", "prime_comment").table().long()

from edsl import ScenarioList, Scenario

scenarios = ScenarioList.from_list("activity", ["reading", "running", "relaxing"])

from edsl import QuestionLinearScale, QuestionFreeText, Survey

q_enjoy = QuestionLinearScale(
  question_name = "enjoy",
  question_text = "On a scale from 1 to 5, how much do you enjoy {{ scenario.activity }}?",
  question_options = [1, 2, 3, 4, 5],
  option_labels = {1:"Not at all", 5:"Very much"}
)

q_favorite_place = QuestionFreeText(
  question_name = "favorite_place",
  question_text = "In a brief sentence, describe your favorite place for {{ scenario.activity }}."
)

survey = Survey([q_enjoy, q_favorite_place])

results = survey.by(scenarios).by(agents).by(models).run()

(
  results
  .filter("model.model == 'gpt-4o'")
  .sort_by("activity", "persona")
  .select("activity", "persona", "enjoy", "favorite_place")
)

df = results.to_pandas(remove_prefix=True)

results.sql("""
select model, persona, enjoy_reading, favorite_place_reading
from self
order by 1,2,3
""")

results.push(
  description = "Starter tutorial sample survey results",
  alias = "starter-tutorial-example-survey-results",
  visibility = "public"
)

{
'description': 'Starter tutorial sample survey results',
'object_type': 'results',
'url': 'https://www.expectedparrot.com/content/9c8ba866-2be3-4ad6-9d2f-8160a06b2cf7',
'uuid': '9c8ba866-2be3-4ad6-9d2f-8160a06b2cf7',
'version': '0.1.47.dev1',
'visibility': 'public'
}

from edsl import Notebook

notebook = Notebook(path="filename.ipynb")

notebook.push(description="Starter Tutorial", alias = "example-notebook-new-alias", visibility="public")