diff --git a/edsl/__version__.py b/edsl/__version__.py index 04c1a0df..c48dca38 100644 --- a/edsl/__version__.py +++ b/edsl/__version__.py @@ -1 +1 @@ -__version__ = "0.1.41.dev3" +__version__ = "0.1.41.dev4" diff --git a/pyproject.toml b/pyproject.toml index 6e7ce6d7..0e2acdc9 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -13,7 +13,7 @@ keywords = [ "LLM", "social science", "surveys", "user research",] license = "MIT" name = "edsl" readme = "README.md" -version = "0.1.41.dev3" +version = "0.1.41.dev4" [tool.poetry.dependencies] python = ">=3.9.1,<3.13" diff --git a/tests/serialization/data/0.1.41.json b/tests/serialization/data/0.1.41.json index 3442b976..60c846f0 100644 --- a/tests/serialization/data/0.1.41.json +++ b/tests/serialization/data/0.1.41.json @@ -1 +1 @@ -[{"class_name": "Study", "dict": {"name": "example_study", "description": null, "objects": {"1144312636257752766": {"created_at": 1736237130.2335942, "variable_name": "q", "object": {"question_name": "how_are_you", "question_text": "How are you?", "question_type": "free_text", "edsl_version": "0.1.41.dev3", "edsl_class_name": "QuestionBase"}, "edsl_class_name": "QuestionFreeText", "description": "Question name: how_are_you", "coop_info": null}}, "filename": "example_study", "cache": {"edsl_version": "0.1.41.dev3", "edsl_class_name": "Cache"}, "use_study_cache": true, "overwrite_on_change": true, "proof_of_work": {"input_data": null, "proof": {}}}}, {"class_name": "Scenario", "dict": {"persona": "A reseacher studying whether LLMs can be used to generate surveys.", "edsl_version": "0.1.41.dev3", "edsl_class_name": "Scenario"}}, {"class_name": "FileStore", "dict": {"path": "/tmp/tmpkvow1muc.txt", "base64_string": "SGVsbG8sIFdvcmxkIQ==", "binary": false, "suffix": "txt", "mime_type": "text/plain", "external_locations": {}, "extracted_text": "Hello, World!", "edsl_version": "0.1.41.dev3", "edsl_class_name": "Scenario"}}, {"class_name": "CSVFileStore", "dict": {"path": "/tmp/tmpm6kmmgh_.csv", "base64_string": 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Test

", "edsl_version": "0.1.41.dev3", "edsl_class_name": "Scenario"}}, {"class_name": "Results", "dict": {"data": [{"agent": {"traits": {"status": "Joyful"}}, "scenario": {"period": "morning", "scenario_index": 0}, "model": {"model": "gpt-4o", "parameters": {"temperature": 0.5, "max_tokens": 1000, "top_p": 1, "frequency_penalty": 0, "presence_penalty": 0, "logprobs": false, "top_logprobs": 3}}, "iteration": 0, "answer": {"how_feeling": "OK", "how_feeling_yesterday": "Great"}, "prompt": {"how_feeling_user_prompt": {"text": "NA", "class_name": "Prompt"}, "how_feeling_system_prompt": {"text": "NA", "class_name": "Prompt"}, "how_feeling_yesterday_user_prompt": {"text": "NA", "class_name": "Prompt"}, "how_feeling_yesterday_system_prompt": {"text": "NA", "class_name": "Prompt"}}, "raw_model_response": {"how_feeling_raw_model_response": "Not Applicable", "how_feeling_cost": null, "how_feeling_one_usd_buys": "NA", "how_feeling_yesterday_raw_model_response": "Not Applicable", "how_feeling_yesterday_cost": null, "how_feeling_yesterday_one_usd_buys": "NA"}, "question_to_attributes": null, "generated_tokens": {"how_feeling_generated_tokens": "Not Applicable", "how_feeling_yesterday_generated_tokens": "Not Applicable"}, "comments_dict": {"how_feeling_comment": "This is a real survey response from a human.", "how_feeling_yesterday_comment": "This is a real survey response from a human."}, "cache_used_dict": {"how_feeling": "Not Applicable", "how_feeling_yesterday": "Not Applicable"}}, {"agent": {"traits": {"status": "Joyful"}}, "scenario": {"period": "afternoon", "scenario_index": 1}, "model": {"model": "gpt-4o", "parameters": {"temperature": 0.5, "max_tokens": 1000, "top_p": 1, "frequency_penalty": 0, "presence_penalty": 0, "logprobs": false, "top_logprobs": 3}}, "iteration": 0, "answer": {"how_feeling": "Great", "how_feeling_yesterday": "Good"}, "prompt": {"how_feeling_user_prompt": {"text": "NA", "class_name": "Prompt"}, "how_feeling_system_prompt": {"text": "NA", "class_name": "Prompt"}, "how_feeling_yesterday_user_prompt": {"text": "NA", "class_name": "Prompt"}, "how_feeling_yesterday_system_prompt": {"text": "NA", "class_name": "Prompt"}}, "raw_model_response": {"how_feeling_raw_model_response": "Not Applicable", "how_feeling_cost": null, "how_feeling_one_usd_buys": "NA", "how_feeling_yesterday_raw_model_response": "Not Applicable", "how_feeling_yesterday_cost": null, "how_feeling_yesterday_one_usd_buys": "NA"}, "question_to_attributes": null, "generated_tokens": {"how_feeling_generated_tokens": "Not Applicable", "how_feeling_yesterday_generated_tokens": "Not Applicable"}, "comments_dict": {"how_feeling_comment": "This is a real survey response from a human.", "how_feeling_yesterday_comment": "This is a real survey response from a human."}, "cache_used_dict": {"how_feeling": "Not Applicable", "how_feeling_yesterday": "Not Applicable"}}, {"agent": {"traits": {"status": "Sad"}}, "scenario": {"period": "morning", "scenario_index": 0}, "model": {"model": "gpt-4o", "parameters": {"temperature": 0.5, "max_tokens": 1000, "top_p": 1, "frequency_penalty": 0, "presence_penalty": 0, "logprobs": false, "top_logprobs": 3}}, "iteration": 0, "answer": {"how_feeling": "Terrible", "how_feeling_yesterday": "OK"}, "prompt": {"how_feeling_user_prompt": {"text": "NA", "class_name": "Prompt"}, "how_feeling_system_prompt": {"text": "NA", "class_name": "Prompt"}, "how_feeling_yesterday_user_prompt": {"text": "NA", "class_name": "Prompt"}, "how_feeling_yesterday_system_prompt": {"text": "NA", "class_name": "Prompt"}}, "raw_model_response": {"how_feeling_raw_model_response": "Not Applicable", "how_feeling_cost": null, "how_feeling_one_usd_buys": "NA", "how_feeling_yesterday_raw_model_response": "Not Applicable", "how_feeling_yesterday_cost": null, "how_feeling_yesterday_one_usd_buys": "NA"}, "question_to_attributes": null, "generated_tokens": {"how_feeling_generated_tokens": "Not Applicable", "how_feeling_yesterday_generated_tokens": "Not Applicable"}, "comments_dict": {"how_feeling_comment": "This is a real survey response from a human.", "how_feeling_yesterday_comment": "This is a real survey response from a human."}, "cache_used_dict": {"how_feeling": "Not Applicable", "how_feeling_yesterday": "Not Applicable"}}, {"agent": {"traits": {"status": "Sad"}}, "scenario": {"period": "afternoon", "scenario_index": 1}, "model": {"model": "gpt-4o", "parameters": {"temperature": 0.5, "max_tokens": 1000, "top_p": 1, "frequency_penalty": 0, "presence_penalty": 0, "logprobs": false, "top_logprobs": 3}}, "iteration": 0, "answer": {"how_feeling": "OK", "how_feeling_yesterday": "Terrible"}, "prompt": {"how_feeling_user_prompt": {"text": "NA", "class_name": "Prompt"}, "how_feeling_system_prompt": {"text": "NA", "class_name": "Prompt"}, "how_feeling_yesterday_user_prompt": {"text": "NA", "class_name": "Prompt"}, "how_feeling_yesterday_system_prompt": {"text": "NA", "class_name": "Prompt"}}, "raw_model_response": {"how_feeling_raw_model_response": "Not Applicable", "how_feeling_cost": null, "how_feeling_one_usd_buys": "NA", "how_feeling_yesterday_raw_model_response": "Not Applicable", "how_feeling_yesterday_cost": null, "how_feeling_yesterday_one_usd_buys": "NA"}, "question_to_attributes": null, "generated_tokens": {"how_feeling_generated_tokens": "Not Applicable", "how_feeling_yesterday_generated_tokens": "Not Applicable"}, "comments_dict": {"how_feeling_comment": "This is a real survey response from a human.", "how_feeling_yesterday_comment": "This is a real survey response from a human."}, "cache_used_dict": {"how_feeling": "Not Applicable", "how_feeling_yesterday": "Not Applicable"}}], "survey": {"questions": [{"question_name": "how_feeling", "question_text": "How are you this {{ period }}?", "question_options": ["Good", "Great", "OK", "Terrible"], "question_type": "multiple_choice"}, {"question_name": "how_feeling_yesterday", "question_text": "How were you feeling yesterday {{ period }}?", "question_options": ["Good", "Great", "OK", "Terrible"], "question_type": "multiple_choice"}], "memory_plan": {"survey_question_names": ["how_feeling", "how_feeling_yesterday"], "survey_question_texts": ["How are you this {{ period }}?", "How were you feeling yesterday {{ period }}?"], "data": {}}, "rule_collection": {"rules": [{"current_q": 0, "expression": "True", "next_q": 1, "priority": -1, "question_name_to_index": {"how_feeling": 0}, "before_rule": false}, {"current_q": 1, "expression": "True", "next_q": 2, "priority": -1, "question_name_to_index": {"how_feeling": 0, "how_feeling_yesterday": 1}, "before_rule": false}], "num_questions": 2}, "question_groups": {}}, "created_columns": []}}, {"class_name": "ScenarioList", "dict": {"scenarios": [{"persona": "A reseacher studying whether LLMs can be used to generate surveys.", "edsl_version": "0.1.41.dev3", "edsl_class_name": "Scenario"}, {"persona": "A reseacher studying whether LLMs can be used to generate surveys.", "edsl_version": "0.1.41.dev3", "edsl_class_name": "Scenario"}], "edsl_version": "0.1.41.dev3", "edsl_class_name": "ScenarioList"}}, {"class_name": "AgentTraits", "dict": {"persona": "A reseacher studying whether LLMs can be used to generate surveys.", "edsl_version": "0.1.41.dev3", "edsl_class_name": "Scenario"}}, {"class_name": "Agent", "dict": {"traits": {"age": 22, "hair": "brown", "height": 5.5}, "edsl_version": "0.1.41.dev3", "edsl_class_name": "Agent"}}, {"class_name": "AgentList", "dict": {"agent_list": [{"traits": {"age": 22, "hair": "brown", "height": 5.5}, "edsl_version": "0.1.41.dev3", "edsl_class_name": "Agent"}, {"traits": {"age": 22, "hair": "brown", "height": 5.5}, "edsl_version": "0.1.41.dev3", "edsl_class_name": "Agent"}], "edsl_version": "0.1.41.dev3", "edsl_class_name": "AgentList"}}, {"class_name": "Survey", "dict": {"questions": [{"question_name": "q0", "question_text": "Do you like school?", "question_options": ["yes", "no"], "question_type": "multiple_choice", "edsl_version": "0.1.41.dev3", "edsl_class_name": "QuestionBase"}, {"question_name": "q1", "question_text": "Why not?", "question_options": ["killer bees in cafeteria", "other"], "question_type": "multiple_choice", "edsl_version": "0.1.41.dev3", "edsl_class_name": "QuestionBase"}, {"question_name": "q2", "question_text": "Why?", "question_options": ["**lack*** of killer bees in cafeteria", "other"], "question_type": "multiple_choice", "edsl_version": "0.1.41.dev3", "edsl_class_name": "QuestionBase"}], "memory_plan": {"survey_question_names": ["q0", "q1", "q2"], "survey_question_texts": ["Do you like school?", "Why not?", "Why?"], "data": {}}, "rule_collection": {"rules": [{"current_q": 0, "expression": "True", "next_q": 1, "priority": -1, "question_name_to_index": {"q0": 0}, "before_rule": false}, {"current_q": 1, "expression": "True", "next_q": 2, "priority": -1, "question_name_to_index": {"q0": 0, "q1": 1}, "before_rule": false}, {"current_q": 2, "expression": "True", "next_q": 3, "priority": -1, "question_name_to_index": {"q0": 0, "q1": 1, "q2": 2}, "before_rule": false}, {"current_q": 0, "expression": "q0 == 'yes'", "next_q": 2, "priority": 0, "question_name_to_index": {"q0": 0, "q1": 1, "q2": 2}, "before_rule": false}], "num_questions": 3}, "question_groups": {}, "edsl_version": "0.1.41.dev3", "edsl_class_name": "Survey"}}, {"class_name": "ModelList", "dict": {"models": [{"model": "gpt-4o", "parameters": {"temperature": 0.5, "max_tokens": 1000, "top_p": 1, "frequency_penalty": 0, "presence_penalty": 0, "logprobs": false, "top_logprobs": 3}, "edsl_version": "0.1.41.dev3", "edsl_class_name": "LanguageModel"}, {"model": "gpt-4o", "parameters": {"temperature": 0.5, "max_tokens": 1000, "top_p": 1, "frequency_penalty": 0, "presence_penalty": 0, "logprobs": false, "top_logprobs": 3}, "edsl_version": "0.1.41.dev3", "edsl_class_name": "LanguageModel"}, {"model": "gpt-4o", "parameters": {"temperature": 0.5, "max_tokens": 1000, "top_p": 1, "frequency_penalty": 0, "presence_penalty": 0, "logprobs": false, "top_logprobs": 3}, "edsl_version": "0.1.41.dev3", "edsl_class_name": "LanguageModel"}], "edsl_version": "0.1.41.dev3", "edsl_class_name": "ModelList"}}, {"class_name": "Cache", "dict": {"5513286eb6967abc0511211f0402587d": {"model": "gpt-3.5-turbo", "parameters": {"temperature": 0.5}, "system_prompt": "The quick brown fox jumps over the lazy dog.", "user_prompt": "What does the fox say?", "output": "The fox says 'hello'", "iteration": 1, "timestamp": 1736237136}, "edsl_version": "0.1.41.dev3", "edsl_class_name": "Cache"}}, {"class_name": "RunParameters", "dict": {"n": 1, "progress_bar": false, "stop_on_exception": false, "check_api_keys": false, "verbose": true, "print_exceptions": true, "remote_cache_description": null, "remote_inference_description": null, "remote_inference_results_visibility": "unlisted", "skip_retry": false, "raise_validation_errors": false, "disable_remote_cache": false, "disable_remote_inference": false, "job_uuid": null}}, {"class_name": "Result", "dict": {"agent": {"traits": {"status": "Joyful"}, "edsl_version": "0.1.41.dev3", "edsl_class_name": "Agent"}, "scenario": {"period": "morning", "scenario_index": 0, "edsl_version": "0.1.41.dev3", "edsl_class_name": "Scenario"}, "model": {"model": "gpt-4o", "parameters": {"temperature": 0.5, "max_tokens": 1000, "top_p": 1, "frequency_penalty": 0, "presence_penalty": 0, "logprobs": false, "top_logprobs": 3}, "edsl_version": "0.1.41.dev3", "edsl_class_name": "LanguageModel"}, "iteration": 0, "answer": {"how_feeling": "OK", "how_feeling_yesterday": "Great"}, "prompt": {"how_feeling_user_prompt": {"text": "NA", "class_name": "Prompt"}, "how_feeling_system_prompt": {"text": "NA", "class_name": "Prompt"}, "how_feeling_yesterday_user_prompt": {"text": "NA", "class_name": "Prompt"}, "how_feeling_yesterday_system_prompt": {"text": "NA", "class_name": "Prompt"}}, "raw_model_response": {"how_feeling_raw_model_response": "Not Applicable", "how_feeling_cost": null, "how_feeling_one_usd_buys": "NA", "how_feeling_yesterday_raw_model_response": "Not Applicable", "how_feeling_yesterday_cost": null, "how_feeling_yesterday_one_usd_buys": "NA"}, "question_to_attributes": null, "generated_tokens": {"how_feeling_generated_tokens": "Not Applicable", "how_feeling_yesterday_generated_tokens": "Not Applicable"}, "comments_dict": {"how_feeling_comment": "This is a real survey response from a human.", "how_feeling_yesterday_comment": "This is a real survey response from a human."}, "edsl_version": "0.1.41.dev3", "edsl_class_name": "Result"}}, {"class_name": "Jobs", "dict": {"survey": {"questions": [{"question_name": "how_feeling", "question_text": "How are you this {{ period }}?", "question_options": ["Good", "Great", "OK", "Terrible"], "question_type": "multiple_choice", "edsl_version": "0.1.41.dev3", "edsl_class_name": "QuestionBase"}, {"question_name": "how_feeling_yesterday", "question_text": "How were you feeling yesterday {{ period }}?", "question_options": ["Good", "Great", "OK", "Terrible"], "question_type": "multiple_choice", "edsl_version": "0.1.41.dev3", "edsl_class_name": "QuestionBase"}], "memory_plan": {"survey_question_names": ["how_feeling", "how_feeling_yesterday"], "survey_question_texts": ["How are you this {{ period }}?", "How were you feeling yesterday {{ period }}?"], "data": {}}, "rule_collection": {"rules": [{"current_q": 0, "expression": "True", "next_q": 1, "priority": -1, "question_name_to_index": {"how_feeling": 0}, "before_rule": false}, {"current_q": 1, "expression": "True", "next_q": 2, "priority": -1, "question_name_to_index": {"how_feeling": 0, "how_feeling_yesterday": 1}, "before_rule": false}], "num_questions": 2}, "question_groups": {}, "edsl_version": "0.1.41.dev3", "edsl_class_name": "Survey"}, "agents": [{"traits": {"status": "Joyful"}, "edsl_version": "0.1.41.dev3", "edsl_class_name": "Agent"}, {"traits": {"status": "Sad"}, "edsl_version": "0.1.41.dev3", "edsl_class_name": "Agent"}], "models": [], "scenarios": [{"period": "morning", "edsl_version": "0.1.41.dev3", "edsl_class_name": "Scenario"}, {"period": "afternoon", "edsl_version": "0.1.41.dev3", "edsl_class_name": "Scenario"}], "edsl_version": "0.1.41.dev3", "edsl_class_name": "Jobs"}}, {"class_name": "Notebook", "dict": {"name": "notebook", "data": {"metadata": {}, "nbformat": 4, "nbformat_minor": 4, "cells": [{"cell_type": "markdown", "metadata": {}, "source": "# Test notebook"}, {"cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [{"name": "stdout", "output_type": "stream", "text": "Hello world!\n"}], "source": "print(\"Hello world!\")"}]}}}, {"class_name": "QuestionCheckBox", "dict": {"question_name": "never_eat", "question_text": "Which of the following foods would you eat if you had to?", "min_selections": 2, "max_selections": 5, "question_options": ["soggy meatpie", "rare snails", "mouldy bread", "panda milk custard", "McDonalds"], "include_comment": false, "use_code": true, "question_type": "checkbox", "edsl_version": "0.1.41.dev3", "edsl_class_name": "QuestionBase"}}, {"class_name": "QuestionExtract", "dict": {"question_name": "extract_name", "question_text": "My name is Moby Dick. I have a PhD in astrology, but I'm actually a truck driver", "answer_template": {"name": "John Doe", "profession": "Carpenter"}, "question_type": "extract", "edsl_version": "0.1.41.dev3", "edsl_class_name": "QuestionBase"}}, {"class_name": "QuestionFreeText", "dict": {"question_name": "how_are_you", "question_text": "How are you?", "question_type": "free_text", "edsl_version": "0.1.41.dev3", "edsl_class_name": "QuestionBase"}}, {"class_name": "QuestionFunctional", "dict": {"question_name": "sum_and_multiply", "function_source_code": "def calculate_sum_and_multiply(scenario, agent_traits):\n numbers = scenario.get(\"numbers\", [])\n multiplier = agent_traits.get(\"multiplier\", 1) if agent_traits else 1\n sum = 0\n for num in numbers:\n sum = sum + num\n return sum * multiplier\n", "question_type": "functional", "requires_loop": true, "function_name": "calculate_sum_and_multiply", "edsl_version": "0.1.41.dev3", "edsl_class_name": "QuestionFunctional"}}, {"class_name": "QuestionList", "dict": {"question_name": "list_of_foods", "question_text": "What are your favorite foods?", "question_type": "list", "edsl_version": "0.1.41.dev3", "edsl_class_name": "QuestionBase"}}, {"class_name": "QuestionMatrix", "dict": {"question_name": "child_happiness", "question_text": "How happy would you be with different numbers of children?", "question_items": ["No children", "1 child", "2 children", "3 or more children"], "question_options": [1, 2, 3, 4, 5], "option_labels": {"1": "Very sad", "3": "Neutral", "5": "Extremely happy"}, "question_type": "matrix", "edsl_version": "0.1.41.dev3", "edsl_class_name": "QuestionBase"}}, {"class_name": "QuestionMultipleChoice", "dict": {"question_name": "how_feeling", "question_text": "How are you?", "question_options": ["Good", "Great", "OK", "Bad"], "include_comment": false, "question_type": "multiple_choice", "edsl_version": "0.1.41.dev3", "edsl_class_name": "QuestionBase"}}, {"class_name": "QuestionNumerical", "dict": {"question_name": "age", "question_text": "You are a 45 year old man. How old are you in years?", "min_value": 0, "max_value": 86.7, "include_comment": false, "question_type": "numerical", "edsl_version": "0.1.41.dev3", "edsl_class_name": "QuestionBase"}}, {"class_name": "QuestionBudget", "dict": {"question_name": "food_budget", "question_text": "How would you allocate $100?", "question_options": ["Pizza", "Ice Cream", "Burgers", "Salad"], "budget_sum": 100, "question_type": "budget", "edsl_version": "0.1.41.dev3", "edsl_class_name": "QuestionBase"}}, {"class_name": "QuestionRank", "dict": {"question_name": "rank_foods", "question_text": "Rank your favorite foods.", "question_options": ["Pizza", "Pasta", "Salad", "Soup"], "num_selections": 2, "question_type": "rank", "edsl_version": "0.1.41.dev3", "edsl_class_name": "QuestionBase"}}, {"class_name": "QuestionLikertFive", "dict": {"question_name": "happy_raining", "question_text": "I'm only happy when it rains.", "question_options": ["Strongly disagree", "Disagree", "Neutral", "Agree", "Strongly agree"], "question_type": "likert_five", "edsl_version": "0.1.41.dev3", "edsl_class_name": "QuestionBase"}}, {"class_name": "QuestionLinearScale", "dict": {"question_name": "ice_cream", "question_text": "How much do you like ice cream?", "question_options": [1, 2, 3, 4, 5], "option_labels": {"1": "I hate it", "5": "I love it"}, "question_type": "linear_scale", "edsl_version": "0.1.41.dev3", "edsl_class_name": "QuestionBase"}}, {"class_name": "QuestionYesNo", "dict": {"question_name": "is_it_equal", "question_text": "Is 5 + 5 equal to 11?", "question_options": ["No", "Yes"], "question_type": "yes_no", "edsl_version": "0.1.41.dev3", "edsl_class_name": "QuestionBase"}}, {"class_name": "QuestionTopK", "dict": {"question_name": "two_fruits", "question_text": "Which of the following fruits do you prefer?", "min_selections": 2, "max_selections": 2, "question_options": ["apple", "banana", "carrot", "durian"], "use_code": true, "question_type": "top_k", "edsl_version": "0.1.41.dev3", "edsl_class_name": "QuestionBase"}}, {"class_name": "LanguageModel", "dict": {"model": "gpt-4o", "parameters": {"temperature": 0.5, "max_tokens": 1000, "top_p": 1, "frequency_penalty": 0, "presence_penalty": 0, "logprobs": false, "top_logprobs": 3}, "edsl_version": "0.1.41.dev3", "edsl_class_name": "LanguageModel"}}, {"class_name": "Results", "dict": {"data": [{"agent": {"traits": {"persona": "You are a scientist", "age": 20}}, "scenario": {"scenario_index": 0}, "model": {"model": "gpt-3.5-turbo", "parameters": {"temperature": 0.5, "max_tokens": 1000, "top_p": 1, "frequency_penalty": 0, "presence_penalty": 0, "logprobs": false, "top_logprobs": 3}}, "iteration": 0, "answer": {"q0": "yes", "q1": null, "q2": null}, "prompt": {"q0_user_prompt": {"text": "\nDo you like school?\n\n \nyes\n \nno\n \n\nOnly 1 option may be selected.\n\nRespond only with a string corresponding to one of the options.\n\n\nAfter the answer, you can put a comment explaining why you chose that option on the next line.", "class_name": "Prompt"}, "q0_system_prompt": {"text": "You are answering questions as if you were a human. Do not break character.Your traits: {'persona': 'You are a scientist', 'age': 20}", "class_name": "Prompt"}, "q1_user_prompt": {"text": "\nWhy not?\n\n \nkiller bees in cafeteria\n \nother\n \n\nOnly 1 option may be selected.\n\nRespond only with a string corresponding to one of the options.\n\n\nAfter the answer, you can put a comment explaining why you chose that option on the next line.", "class_name": "Prompt"}, "q1_system_prompt": {"text": "You are answering questions as if you were a human. Do not break character.Your traits: {'persona': 'You are a scientist', 'age': 20}", "class_name": "Prompt"}, "q2_user_prompt": {"text": "\nWhy?\n\n \n**lack*** of killer bees in cafeteria\n \nother\n \n\nOnly 1 option may be selected.\n\nRespond only with a string corresponding to one of the options.\n\n\nAfter the answer, you can put a comment explaining why you chose that option on the next line.", "class_name": "Prompt"}, "q2_system_prompt": {"text": "You are answering questions as if you were a human. Do not break character.Your traits: {'persona': 'You are a scientist', 'age': 20}", "class_name": "Prompt"}}, "raw_model_response": {"q0_raw_model_response": null, "q0_cost": null, "q0_one_usd_buys": "NA", "q1_raw_model_response": null, "q1_cost": null, "q1_one_usd_buys": "NA", "q2_raw_model_response": null, "q2_cost": null, "q2_one_usd_buys": "NA"}, "question_to_attributes": null, "generated_tokens": {"q0_generated_tokens": null, "q1_generated_tokens": null, "q2_generated_tokens": null}, "comments_dict": {"q0_comment": "Task was cancelled.", "q1_comment": "Task was cancelled.", "q2_comment": "Question answer validation failed."}, "cache_used_dict": {"q0": null, "q1": null, "q2": null}}, {"agent": {"traits": {"persona": "You are a scientist", "age": 20}}, "scenario": {"scenario_index": 0}, "model": {"model": "gpt-4o", "parameters": {"temperature": 0.5, "max_tokens": 1000, "top_p": 1, "frequency_penalty": 0, "presence_penalty": 0, "logprobs": false, "top_logprobs": 3}}, "iteration": 0, "answer": {"q0": "yes", "q1": null, "q2": null}, "prompt": {"q0_user_prompt": {"text": "\nDo you like school?\n\n \nyes\n \nno\n \n\nOnly 1 option may be selected.\n\nRespond only with a string corresponding to one of the options.\n\n\nAfter the answer, you can put a comment explaining why you chose that option on the next line.", "class_name": "Prompt"}, "q0_system_prompt": {"text": "You are answering questions as if you were a human. Do not break character.Your traits: {'persona': 'You are a scientist', 'age': 20}", "class_name": "Prompt"}, "q1_user_prompt": {"text": "\nWhy not?\n\n \nkiller bees in cafeteria\n \nother\n \n\nOnly 1 option may be selected.\n\nRespond only with a string corresponding to one of the options.\n\n\nAfter the answer, you can put a comment explaining why you chose that option on the next line.", "class_name": "Prompt"}, "q1_system_prompt": {"text": "You are answering questions as if you were a human. Do not break character.Your traits: {'persona': 'You are a scientist', 'age': 20}", "class_name": "Prompt"}, "q2_user_prompt": {"text": "\nWhy?\n\n \n**lack*** of killer bees in cafeteria\n \nother\n \n\nOnly 1 option may be selected.\n\nRespond only with a string corresponding to one of the options.\n\n\nAfter the answer, you can put a comment explaining why you chose that option on the next line.", "class_name": "Prompt"}, "q2_system_prompt": {"text": "You are answering questions as if you were a human. Do not break character.Your traits: {'persona': 'You are a scientist', 'age': 20}", "class_name": "Prompt"}}, "raw_model_response": {"q0_raw_model_response": null, "q0_cost": null, "q0_one_usd_buys": "NA", "q1_raw_model_response": null, "q1_cost": null, "q1_one_usd_buys": "NA", "q2_raw_model_response": null, "q2_cost": null, "q2_one_usd_buys": "NA"}, "question_to_attributes": null, "generated_tokens": {"q0_generated_tokens": null, "q1_generated_tokens": null, "q2_generated_tokens": null}, "comments_dict": {"q0_comment": "Task was cancelled.", "q1_comment": "Task was cancelled.", "q2_comment": "Question answer validation failed."}, "cache_used_dict": {"q0": null, "q1": null, "q2": null}}, {"agent": {"traits": {"persona": "You are a chef", "age": 40}}, "scenario": {"scenario_index": 0}, "model": {"model": "gpt-3.5-turbo", "parameters": {"temperature": 0.5, "max_tokens": 1000, "top_p": 1, "frequency_penalty": 0, "presence_penalty": 0, "logprobs": false, "top_logprobs": 3}}, "iteration": 0, "answer": {"q0": "no", "q1": "other", "q2": null}, "prompt": {"q0_user_prompt": {"text": "\nDo you like school?\n\n \nyes\n \nno\n \n\nOnly 1 option may be selected.\n\nRespond only with a string corresponding to one of the options.\n\n\nAfter the answer, you can put a comment explaining why you chose that option on the next line.", "class_name": "Prompt"}, "q0_system_prompt": {"text": "You are answering questions as if you were a human. Do not break character.Your traits: {'persona': 'You are a chef', 'age': 40}", "class_name": "Prompt"}, "q1_user_prompt": {"text": "\nWhy not?\n\n \nkiller bees in cafeteria\n \nother\n \n\nOnly 1 option may be selected.\n\nRespond only with a string corresponding to one of the options.\n\n\nAfter the answer, you can put a comment explaining why you chose that option on the next line.", "class_name": "Prompt"}, "q1_system_prompt": {"text": "You are answering questions as if you were a human. Do not break character.Your traits: {'persona': 'You are a chef', 'age': 40}", "class_name": "Prompt"}, "q2_user_prompt": {"text": "\nWhy?\n\n \n**lack*** of killer bees in cafeteria\n \nother\n \n\nOnly 1 option may be selected.\n\nRespond only with a string corresponding to one of the options.\n\n\nAfter the answer, you can put a comment explaining why you chose that option on the next line.", "class_name": "Prompt"}, "q2_system_prompt": {"text": "You are answering questions as if you were a human. Do not break character.Your traits: {'persona': 'You are a chef', 'age': 40}", "class_name": "Prompt"}}, "raw_model_response": {"q0_raw_model_response": {"id": "chatcmpl-AmytCFnwsSFeHKarQwb9gVc7K7ILm", "choices": [{"finish_reason": "stop", "index": 0, "logprobs": null, "message": {"content": "no\nSchool wasn't my favorite, but I did enjoy learning about cooking and culinary arts.", "refusal": null, "role": "assistant", "audio": null, "function_call": null, "tool_calls": null}}], "created": 1736237166, "model": "gpt-3.5-turbo-0125", "object": "chat.completion", "service_tier": null, "system_fingerprint": null, "usage": {"completion_tokens": 20, "prompt_tokens": 96, "total_tokens": 116, "completion_tokens_details": {"accepted_prediction_tokens": 0, "audio_tokens": 0, "reasoning_tokens": 0, "rejected_prediction_tokens": 0}, "prompt_tokens_details": {"audio_tokens": 0, "cached_tokens": 0}}}, "q0_cost": 0.000407999184001632, "q0_one_usd_buys": 2450.985294117647, "q1_raw_model_response": {"id": "chatcmpl-AmytOf94aSurSPBY52C7OeJmGfX6V", "choices": [{"finish_reason": "stop", "index": 0, "logprobs": null, "message": {"content": "other\n// As a chef, I don't have any expertise in handling killer bees.", "refusal": null, "role": "assistant", "audio": null, "function_call": null, "tool_calls": null}}], "created": 1736237178, "model": "gpt-3.5-turbo-0125", "object": "chat.completion", "service_tier": null, "system_fingerprint": null, "usage": {"completion_tokens": 19, "prompt_tokens": 97, "total_tokens": 116, "completion_tokens_details": {"accepted_prediction_tokens": 0, "audio_tokens": 0, "reasoning_tokens": 0, "rejected_prediction_tokens": 0}, "prompt_tokens_details": {"audio_tokens": 0, "cached_tokens": 0}}}, "q1_cost": 0.00040499919000162003, "q1_one_usd_buys": 2469.1407407407405, "q2_raw_model_response": null, "q2_cost": null, "q2_one_usd_buys": "NA"}, "question_to_attributes": null, "generated_tokens": {"q0_generated_tokens": "no\nSchool wasn't my favorite, but I did enjoy learning about cooking and culinary arts.", "q1_generated_tokens": "other\n// As a chef, I don't have any expertise in handling killer bees.", "q2_generated_tokens": null}, "comments_dict": {"q0_comment": "School wasn't my favorite, but I did enjoy learning about cooking and culinary arts.", "q1_comment": "// As a chef, I don't have any expertise in handling killer bees.", "q2_comment": "Question answer validation failed."}, "cache_used_dict": {"q0": false, "q1": false, "q2": null}}, {"agent": {"traits": {"persona": "You are a chef", "age": 40}}, "scenario": {"scenario_index": 0}, "model": {"model": "gpt-4o", "parameters": {"temperature": 0.5, "max_tokens": 1000, "top_p": 1, "frequency_penalty": 0, "presence_penalty": 0, "logprobs": false, "top_logprobs": 3}}, "iteration": 0, "answer": {"q0": "yes", "q1": null, "q2": "other"}, "prompt": {"q0_user_prompt": {"text": "\nDo you like school?\n\n \nyes\n \nno\n \n\nOnly 1 option may be selected.\n\nRespond only with a string corresponding to one of the options.\n\n\nAfter the answer, you can put a comment explaining why you chose that option on the next line.", "class_name": "Prompt"}, "q0_system_prompt": {"text": "You are answering questions as if you were a human. Do not break character.Your traits: {'persona': 'You are a chef', 'age': 40}", "class_name": "Prompt"}, "q1_user_prompt": {"text": "\nWhy not?\n\n \nkiller bees in cafeteria\n \nother\n \n\nOnly 1 option may be selected.\n\nRespond only with a string corresponding to one of the options.\n\n\nAfter the answer, you can put a comment explaining why you chose that option on the next line.", "class_name": "Prompt"}, "q1_system_prompt": {"text": "You are answering questions as if you were a human. Do not break character.Your traits: {'persona': 'You are a chef', 'age': 40}", "class_name": "Prompt"}, "q2_user_prompt": {"text": "\nWhy?\n\n \n**lack*** of killer bees in cafeteria\n \nother\n \n\nOnly 1 option may be selected.\n\nRespond only with a string corresponding to one of the options.\n\n\nAfter the answer, you can put a comment explaining why you chose that option on the next line.", "class_name": "Prompt"}, "q2_system_prompt": {"text": "You are answering questions as if you were a human. Do not break character.Your traits: {'persona': 'You are a chef', 'age': 40}", "class_name": "Prompt"}}, "raw_model_response": {"q0_raw_model_response": null, "q0_cost": null, "q0_one_usd_buys": "NA", "q1_raw_model_response": null, "q1_cost": null, "q1_one_usd_buys": "NA", "q2_raw_model_response": {"id": "chatcmpl-Amyt6d3uAsE4ecKRvaIEkeaOIR7Eo", "choices": [{"finish_reason": "stop", "index": 0, "logprobs": null, "message": {"content": "other\n\nThe options provided don't seem to be directly related to a typical cafeteria setting, and \"lack of killer bees\" seems unusual and unlikely to be a common reason for any cafeteria-related issue.", "refusal": null, "role": "assistant", "audio": null, "function_call": null, "tool_calls": null}}], "created": 1736237160, "model": "gpt-4o-2024-08-06", "object": "chat.completion", "service_tier": null, "system_fingerprint": "fp_5f20662549", "usage": {"completion_tokens": 40, "prompt_tokens": 100, "total_tokens": 140, "completion_tokens_details": {"accepted_prediction_tokens": 0, "audio_tokens": 0, "reasoning_tokens": 0, "rejected_prediction_tokens": 0}, "prompt_tokens_details": {"audio_tokens": 0, "cached_tokens": 0}}}, "q2_cost": 0.00065, "q2_one_usd_buys": 1538.4615384615386}, "question_to_attributes": null, "generated_tokens": {"q0_generated_tokens": null, "q1_generated_tokens": null, "q2_generated_tokens": "other\n\nThe options provided don't seem to be directly related to a typical cafeteria setting, and \"lack of killer bees\" seems unusual and unlikely to be a common reason for any cafeteria-related issue."}, "comments_dict": {"q0_comment": "Task was cancelled.", "q1_comment": "Task was cancelled.", "q2_comment": "The options provided don't seem to be directly related to a typical cafeteria setting, and \"lack of killer bees\" seems unusual and unlikely to be a common reason for any cafeteria-related issue."}, "cache_used_dict": {"q0": null, "q1": null, "q2": false}}], "survey": {"questions": [{"question_name": "q0", "question_text": "Do you like school?", "question_options": ["yes", "no"], "question_type": "multiple_choice"}, {"question_name": "q1", "question_text": "Why not?", "question_options": ["killer bees in cafeteria", "other"], "question_type": "multiple_choice"}, {"question_name": "q2", "question_text": "Why?", "question_options": ["**lack*** of killer bees in cafeteria", "other"], "question_type": "multiple_choice"}], "memory_plan": {"survey_question_names": ["q0", "q1", "q2"], "survey_question_texts": ["Do you like school?", "Why not?", "Why?"], "data": {}}, "rule_collection": {"rules": [{"current_q": 0, "expression": "True", "next_q": 1, "priority": -1, "question_name_to_index": {"q0": 0}, "before_rule": false}, {"current_q": 1, "expression": "True", "next_q": 2, "priority": -1, "question_name_to_index": {"q0": 0, "q1": 1}, "before_rule": false}, {"current_q": 2, "expression": "True", "next_q": 3, "priority": -1, "question_name_to_index": {"q0": 0, "q1": 1, "q2": 2}, "before_rule": false}, {"current_q": 0, "expression": "q0 == 'yes'", "next_q": 2, "priority": 0, "question_name_to_index": {"q0": 0, "q1": 1, "q2": 2}, "before_rule": false}], "num_questions": 3}, "question_groups": {}}, "created_columns": [], "task_history": {"interviews": [{"agent": {"traits": {"persona": "You are a scientist", "age": 20}, "edsl_version": "0.1.41.dev3", "edsl_class_name": "Agent"}, "survey": {"questions": [{"question_name": "q0", "question_text": "Do you like school?", "question_options": ["yes", "no"], "question_type": "multiple_choice", "edsl_version": "0.1.41.dev3", "edsl_class_name": "QuestionBase"}, {"question_name": "q1", "question_text": "Why not?", "question_options": ["killer bees in cafeteria", "other"], "question_type": "multiple_choice", "edsl_version": "0.1.41.dev3", "edsl_class_name": "QuestionBase"}, {"question_name": "q2", "question_text": "Why?", "question_options": ["**lack*** of killer bees in cafeteria", "other"], "question_type": "multiple_choice", "edsl_version": "0.1.41.dev3", "edsl_class_name": "QuestionBase"}], "memory_plan": {"survey_question_names": ["q0", "q1", "q2"], "survey_question_texts": ["Do you like school?", "Why not?", "Why?"], "data": {}}, "rule_collection": {"rules": [{"current_q": 0, "expression": "True", "next_q": 1, "priority": -1, "question_name_to_index": {"q0": 0}, "before_rule": false}, {"current_q": 1, "expression": "True", "next_q": 2, "priority": -1, "question_name_to_index": {"q0": 0, "q1": 1}, "before_rule": false}, {"current_q": 2, "expression": "True", "next_q": 3, "priority": -1, "question_name_to_index": {"q0": 0, "q1": 1, "q2": 2}, "before_rule": false}, {"current_q": 0, "expression": "q0 == 'yes'", "next_q": 2, "priority": 0, "question_name_to_index": {"q0": 0, "q1": 1, "q2": 2}, "before_rule": false}], "num_questions": 3}, "question_groups": {}, "edsl_version": "0.1.41.dev3", "edsl_class_name": "Survey"}, "scenario": {"scenario_index": 0, "edsl_version": "0.1.41.dev3", "edsl_class_name": "Scenario"}, "model": {"model": "gpt-3.5-turbo", "parameters": {"temperature": 0.5, "max_tokens": 1000, "top_p": 1, "frequency_penalty": 0, "presence_penalty": 0, "logprobs": false, "top_logprobs": 3}, "edsl_version": "0.1.41.dev3", "edsl_class_name": "LanguageModel"}, "iteration": 0, "exceptions": {"q2": [{"exception": {"type": "QuestionAnswerValidationError", "message": "1 validation error for ChoiceResponse\nanswer\n Input should be '**lack*** of killer bees in cafeteria' or 'other' [type=literal_error, input_value='lack', input_type=str]\n For further information visit https://errors.pydantic.dev/2.10/v/literal_error", "traceback": "Traceback (most recent call last):\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 77, in _base_validate\n return self.response_model(**data)\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/project/lib/python3.9/site-packages/pydantic/main.py\", line 214, in __init__\n validated_self = self.__pydantic_validator__.validate_python(data, self_instance=self)\npydantic_core._pydantic_core.ValidationError: 1 validation error for ChoiceResponse\nanswer\n Input should be '**lack*** of killer bees in cafeteria' or 'other' [type=literal_error, input_value='lack', input_type=str]\n For further information visit https://errors.pydantic.dev/2.10/v/literal_error\n\nDuring handling of the above exception, another exception occurred:\n\nTraceback (most recent call last):\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/jobs/AnswerQuestionFunctionConstructor.py\", line 184, in attempt_answer\n raise response.exception_occurred\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/agents/Invigilator.py\", line 163, in _extract_edsl_result_entry_and_validate\n validated_edsl_dict = question_with_validators._validate_answer(edsl_dict)\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/QuestionBase.py\", line 110, in _validate_answer\n return self.response_validator.validate(answer, replacement_dict)\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 123, in validate\n return self._handle_exception(e, raw_edsl_answer_dict)\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 143, in _handle_exception\n raise self.original_exception\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 117, in validate\n pydantic_edsl_answer: BaseModel = self._base_validate(\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 79, in _base_validate\n raise QuestionAnswerValidationError(\nedsl.exceptions.questions.QuestionAnswerValidationError: 1 validation error for ChoiceResponse\nanswer\n Input should be '**lack*** of killer bees in cafeteria' or 'other' [type=literal_error, input_value='lack', input_type=str]\n For further information visit https://errors.pydantic.dev/2.10/v/literal_error\n"}, "time": "2025-01-07T08:06:25.096377", "traceback": "Traceback (most recent call last):\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 77, in _base_validate\n return self.response_model(**data)\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/project/lib/python3.9/site-packages/pydantic/main.py\", line 214, in __init__\n validated_self = self.__pydantic_validator__.validate_python(data, self_instance=self)\npydantic_core._pydantic_core.ValidationError: 1 validation error for ChoiceResponse\nanswer\n Input should be '**lack*** of killer bees in cafeteria' or 'other' [type=literal_error, input_value='lack', input_type=str]\n For further information visit https://errors.pydantic.dev/2.10/v/literal_error\n\nDuring handling of the above exception, another exception occurred:\n\nTraceback (most recent call last):\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/jobs/AnswerQuestionFunctionConstructor.py\", line 184, in attempt_answer\n raise response.exception_occurred\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/agents/Invigilator.py\", line 163, in _extract_edsl_result_entry_and_validate\n validated_edsl_dict = question_with_validators._validate_answer(edsl_dict)\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/QuestionBase.py\", line 110, in _validate_answer\n return self.response_validator.validate(answer, replacement_dict)\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 123, in validate\n return self._handle_exception(e, raw_edsl_answer_dict)\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 143, in _handle_exception\n raise self.original_exception\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 117, in validate\n pydantic_edsl_answer: BaseModel = self._base_validate(\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 79, in _base_validate\n raise QuestionAnswerValidationError(\nedsl.exceptions.questions.QuestionAnswerValidationError: 1 validation error for ChoiceResponse\nanswer\n Input should be '**lack*** of killer bees in cafeteria' or 'other' [type=literal_error, input_value='lack', input_type=str]\n For further information visit https://errors.pydantic.dev/2.10/v/literal_error\n", "invigilator": {"agent": {"traits": {"persona": "You are a scientist", "age": 20}, "edsl_version": "0.1.41.dev3", "edsl_class_name": "Agent"}, "question": {"question_name": "q2", "question_text": "Why?", "question_options": ["**lack*** of killer bees in cafeteria", "other"], "question_type": "multiple_choice", "edsl_version": "0.1.41.dev3", "edsl_class_name": "QuestionBase"}, "scenario": {"scenario_index": 0, "edsl_version": "0.1.41.dev3", "edsl_class_name": "Scenario"}, "model": {"model": "gpt-3.5-turbo", "parameters": {"temperature": 0.5, "max_tokens": 1000, "top_p": 1, "frequency_penalty": 0, "presence_penalty": 0, "logprobs": false, "top_logprobs": 3}, "edsl_version": "0.1.41.dev3", "edsl_class_name": "LanguageModel"}, "memory_plan": {"survey_question_names": ["q0", "q1", "q2"], "survey_question_texts": ["Do you like school?", "Why not?", "Why?"], "data": {}}, "current_answers": {"q0_generated_tokens": "yes\nI enjoy school because I love learning new things and conducting experiments.", "q0": "yes", "q0_comment": "I enjoy school because I love learning new things and conducting experiments.", "q1": null, "q2": null}, "iteration": 0, "additional_prompt_data": null, "survey": {"questions": [{"question_name": "q0", "question_text": "Do you like school?", "question_options": ["yes", "no"], "question_type": "multiple_choice", "edsl_version": "0.1.41.dev3", "edsl_class_name": "QuestionBase"}, {"question_name": "q1", "question_text": "Why not?", "question_options": ["killer bees in cafeteria", "other"], "question_type": "multiple_choice", "edsl_version": "0.1.41.dev3", "edsl_class_name": "QuestionBase"}, {"question_name": "q2", "question_text": "Why?", "question_options": ["**lack*** of killer bees in cafeteria", "other"], "question_type": "multiple_choice", "edsl_version": "0.1.41.dev3", "edsl_class_name": "QuestionBase"}], "memory_plan": {"survey_question_names": ["q0", "q1", "q2"], "survey_question_texts": ["Do you like school?", "Why not?", "Why?"], "data": {}}, "rule_collection": {"rules": [{"current_q": 0, "expression": "True", "next_q": 1, "priority": -1, "question_name_to_index": {"q0": 0}, "before_rule": false}, {"current_q": 1, "expression": "True", "next_q": 2, "priority": -1, "question_name_to_index": {"q0": 0, "q1": 1}, "before_rule": false}, {"current_q": 2, "expression": "True", "next_q": 3, "priority": -1, "question_name_to_index": {"q0": 0, "q1": 1, "q2": 2}, "before_rule": false}, {"current_q": 0, "expression": "q0 == 'yes'", "next_q": 2, "priority": 0, "question_name_to_index": {"q0": 0, "q1": 1, "q2": 2}, "before_rule": false}], "num_questions": 3}, "question_groups": {}, "edsl_version": "0.1.41.dev3", "edsl_class_name": "Survey"}}}]}, "indices": {"agent": 0, "model": 0, "scenario": 0}}, {"agent": {"traits": {"persona": "You are a scientist", "age": 20}, "edsl_version": "0.1.41.dev3", "edsl_class_name": "Agent"}, "survey": {"questions": [{"question_name": "q0", "question_text": "Do you like school?", "question_options": ["yes", "no"], "question_type": "multiple_choice", "edsl_version": "0.1.41.dev3", "edsl_class_name": "QuestionBase"}, {"question_name": "q1", "question_text": "Why not?", "question_options": ["killer bees in cafeteria", "other"], "question_type": "multiple_choice", "edsl_version": "0.1.41.dev3", "edsl_class_name": "QuestionBase"}, {"question_name": "q2", "question_text": "Why?", "question_options": ["**lack*** of killer bees in cafeteria", "other"], "question_type": "multiple_choice", "edsl_version": "0.1.41.dev3", "edsl_class_name": "QuestionBase"}], "memory_plan": {"survey_question_names": ["q0", "q1", "q2"], "survey_question_texts": ["Do you like school?", "Why not?", "Why?"], "data": {}}, "rule_collection": {"rules": [{"current_q": 0, "expression": "True", "next_q": 1, "priority": -1, "question_name_to_index": {"q0": 0}, "before_rule": false}, {"current_q": 1, "expression": "True", "next_q": 2, "priority": -1, "question_name_to_index": {"q0": 0, "q1": 1}, "before_rule": false}, {"current_q": 2, "expression": "True", "next_q": 3, "priority": -1, "question_name_to_index": {"q0": 0, "q1": 1, "q2": 2}, "before_rule": false}, {"current_q": 0, "expression": "q0 == 'yes'", "next_q": 2, "priority": 0, "question_name_to_index": {"q0": 0, "q1": 1, "q2": 2}, "before_rule": false}], "num_questions": 3}, "question_groups": {}, "edsl_version": "0.1.41.dev3", "edsl_class_name": "Survey"}, "scenario": {"scenario_index": 0, "edsl_version": "0.1.41.dev3", "edsl_class_name": "Scenario"}, "model": {"model": "gpt-4o", "parameters": {"temperature": 0.5, "max_tokens": 1000, "top_p": 1, "frequency_penalty": 0, "presence_penalty": 0, "logprobs": false, "top_logprobs": 3}, "edsl_version": "0.1.41.dev3", "edsl_class_name": "LanguageModel"}, "iteration": 0, "exceptions": {"q2": [{"exception": {"type": "QuestionAnswerValidationError", "message": "1 validation error for ChoiceResponse\nanswer\n Input should be '**lack*** of killer bees in cafeteria' or 'other' [type=literal_error, input_value='lack of killer bees in cafeteria', input_type=str]\n For further information visit https://errors.pydantic.dev/2.10/v/literal_error", "traceback": "Traceback (most recent call last):\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 77, in _base_validate\n return self.response_model(**data)\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/project/lib/python3.9/site-packages/pydantic/main.py\", line 214, in __init__\n validated_self = self.__pydantic_validator__.validate_python(data, self_instance=self)\npydantic_core._pydantic_core.ValidationError: 1 validation error for ChoiceResponse\nanswer\n Input should be '**lack*** of killer bees in cafeteria' or 'other' [type=literal_error, input_value='lack of killer bees in cafeteria', input_type=str]\n For further information visit https://errors.pydantic.dev/2.10/v/literal_error\n\nDuring handling of the above exception, another exception occurred:\n\nTraceback (most recent call last):\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/jobs/AnswerQuestionFunctionConstructor.py\", line 184, in attempt_answer\n raise response.exception_occurred\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/agents/Invigilator.py\", line 163, in _extract_edsl_result_entry_and_validate\n validated_edsl_dict = question_with_validators._validate_answer(edsl_dict)\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/QuestionBase.py\", line 110, in _validate_answer\n return self.response_validator.validate(answer, replacement_dict)\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 123, in validate\n return self._handle_exception(e, raw_edsl_answer_dict)\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 143, in _handle_exception\n raise self.original_exception\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 117, in validate\n pydantic_edsl_answer: BaseModel = self._base_validate(\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 79, in _base_validate\n raise QuestionAnswerValidationError(\nedsl.exceptions.questions.QuestionAnswerValidationError: 1 validation error for ChoiceResponse\nanswer\n Input should be '**lack*** of killer bees in cafeteria' or 'other' [type=literal_error, input_value='lack of killer bees in cafeteria', input_type=str]\n For further information visit https://errors.pydantic.dev/2.10/v/literal_error\n"}, "time": "2025-01-07T08:05:55.432345", "traceback": "Traceback (most recent call last):\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 77, in _base_validate\n return self.response_model(**data)\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/project/lib/python3.9/site-packages/pydantic/main.py\", line 214, in __init__\n validated_self = self.__pydantic_validator__.validate_python(data, self_instance=self)\npydantic_core._pydantic_core.ValidationError: 1 validation error for ChoiceResponse\nanswer\n Input should be '**lack*** of killer bees in cafeteria' or 'other' [type=literal_error, input_value='lack of killer bees in cafeteria', input_type=str]\n For further information visit https://errors.pydantic.dev/2.10/v/literal_error\n\nDuring handling of the above exception, another exception occurred:\n\nTraceback (most recent call last):\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/jobs/AnswerQuestionFunctionConstructor.py\", line 184, in attempt_answer\n raise response.exception_occurred\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/agents/Invigilator.py\", line 163, in _extract_edsl_result_entry_and_validate\n validated_edsl_dict = question_with_validators._validate_answer(edsl_dict)\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/QuestionBase.py\", line 110, in _validate_answer\n return self.response_validator.validate(answer, replacement_dict)\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 123, in validate\n return self._handle_exception(e, raw_edsl_answer_dict)\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 143, in _handle_exception\n raise self.original_exception\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 117, in validate\n pydantic_edsl_answer: BaseModel = self._base_validate(\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 79, in _base_validate\n raise QuestionAnswerValidationError(\nedsl.exceptions.questions.QuestionAnswerValidationError: 1 validation error for ChoiceResponse\nanswer\n Input should be '**lack*** of killer bees in cafeteria' or 'other' [type=literal_error, input_value='lack of killer bees in cafeteria', input_type=str]\n For further information visit https://errors.pydantic.dev/2.10/v/literal_error\n", "invigilator": {"agent": {"traits": {"persona": "You are a scientist", "age": 20}, "edsl_version": "0.1.41.dev3", "edsl_class_name": "Agent"}, "question": {"question_name": "q2", "question_text": "Why?", "question_options": ["**lack*** of killer bees in cafeteria", "other"], "question_type": "multiple_choice", "edsl_version": "0.1.41.dev3", "edsl_class_name": "QuestionBase"}, "scenario": {"edsl_version": "0.1.41.dev3", "edsl_class_name": "Scenario"}, "model": {"model": "gpt-4o", "parameters": {"temperature": 0.5, "max_tokens": 1000, "top_p": 1, "frequency_penalty": 0, "presence_penalty": 0, "logprobs": false, "top_logprobs": 3}, "edsl_version": "0.1.41.dev3", "edsl_class_name": "LanguageModel"}, "memory_plan": {"survey_question_names": ["q0", "q1", "q2"], "survey_question_texts": ["Do you like school?", "Why not?", "Why?"], "data": {}}, "current_answers": {"q0_generated_tokens": "yes \nI enjoy school because it provides a structured environment for learning and discovery, which is essential for my passion for science.", "q0": "yes", "q0_comment": "I enjoy school because it provides a structured environment for learning and discovery, which is essential for my passion for science.", "q1": null, "q2": null}, "iteration": 0, "additional_prompt_data": null, "survey": {"questions": [{"question_name": "q0", "question_text": "Do you like school?", "question_options": ["yes", "no"], "question_type": "multiple_choice", "edsl_version": "0.1.41.dev3", "edsl_class_name": "QuestionBase"}, {"question_name": "q1", "question_text": "Why not?", "question_options": ["killer bees in cafeteria", "other"], "question_type": "multiple_choice", "edsl_version": "0.1.41.dev3", "edsl_class_name": "QuestionBase"}, {"question_name": "q2", "question_text": "Why?", "question_options": ["**lack*** of killer bees in cafeteria", "other"], "question_type": "multiple_choice", "edsl_version": "0.1.41.dev3", "edsl_class_name": "QuestionBase"}], "memory_plan": {"survey_question_names": ["q0", "q1", "q2"], "survey_question_texts": ["Do you like school?", "Why not?", "Why?"], "data": {}}, "rule_collection": {"rules": [{"current_q": 0, "expression": "True", "next_q": 1, "priority": -1, "question_name_to_index": {"q0": 0}, "before_rule": false}, {"current_q": 1, "expression": "True", "next_q": 2, "priority": -1, "question_name_to_index": {"q0": 0, "q1": 1}, "before_rule": false}, {"current_q": 2, "expression": "True", "next_q": 3, "priority": -1, "question_name_to_index": {"q0": 0, "q1": 1, "q2": 2}, "before_rule": false}, {"current_q": 0, "expression": "q0 == 'yes'", "next_q": 2, "priority": 0, "question_name_to_index": {"q0": 0, "q1": 1, "q2": 2}, "before_rule": false}], "num_questions": 3}, "question_groups": {}, "edsl_version": "0.1.41.dev3", "edsl_class_name": "Survey"}}}]}, "indices": {"agent": 0, "model": 1, "scenario": 0}}, {"agent": {"traits": {"persona": "You are a chef", "age": 40}, "edsl_version": "0.1.41.dev3", "edsl_class_name": "Agent"}, "survey": {"questions": [{"question_name": "q0", "question_text": "Do you like school?", "question_options": ["yes", "no"], "question_type": "multiple_choice", "edsl_version": "0.1.41.dev3", "edsl_class_name": "QuestionBase"}, {"question_name": "q1", "question_text": "Why not?", "question_options": ["killer bees in cafeteria", "other"], "question_type": "multiple_choice", "edsl_version": "0.1.41.dev3", "edsl_class_name": "QuestionBase"}, {"question_name": "q2", "question_text": "Why?", "question_options": ["**lack*** of killer bees in cafeteria", "other"], "question_type": "multiple_choice", "edsl_version": "0.1.41.dev3", "edsl_class_name": "QuestionBase"}], "memory_plan": {"survey_question_names": ["q0", "q1", "q2"], "survey_question_texts": ["Do you like school?", "Why not?", "Why?"], "data": {}}, "rule_collection": {"rules": [{"current_q": 0, "expression": "True", "next_q": 1, "priority": -1, "question_name_to_index": {"q0": 0}, "before_rule": false}, {"current_q": 1, "expression": "True", "next_q": 2, "priority": -1, "question_name_to_index": {"q0": 0, "q1": 1}, "before_rule": false}, {"current_q": 2, "expression": "True", "next_q": 3, "priority": -1, "question_name_to_index": {"q0": 0, "q1": 1, "q2": 2}, "before_rule": false}, {"current_q": 0, "expression": "q0 == 'yes'", "next_q": 2, "priority": 0, "question_name_to_index": {"q0": 0, "q1": 1, "q2": 2}, "before_rule": false}], "num_questions": 3}, "question_groups": {}, "edsl_version": "0.1.41.dev3", "edsl_class_name": "Survey"}, "scenario": {"scenario_index": 0, "edsl_version": "0.1.41.dev3", "edsl_class_name": "Scenario"}, "model": {"model": "gpt-3.5-turbo", "parameters": {"temperature": 0.5, "max_tokens": 1000, "top_p": 1, "frequency_penalty": 0, "presence_penalty": 0, "logprobs": false, "top_logprobs": 3}, "edsl_version": "0.1.41.dev3", "edsl_class_name": "LanguageModel"}, "iteration": 0, "exceptions": {"q2": [{"exception": {"type": "QuestionAnswerValidationError", "message": "1 validation error for ChoiceResponse\nanswer\n Input should be '**lack*** of killer bees in cafeteria' or 'other' [type=literal_error, input_value='lack of killer bees in cafeteria', input_type=str]\n For further information visit https://errors.pydantic.dev/2.10/v/literal_error", "traceback": "Traceback (most recent call last):\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 77, in _base_validate\n return self.response_model(**data)\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/project/lib/python3.9/site-packages/pydantic/main.py\", line 214, in __init__\n validated_self = self.__pydantic_validator__.validate_python(data, self_instance=self)\npydantic_core._pydantic_core.ValidationError: 1 validation error for ChoiceResponse\nanswer\n Input should be '**lack*** of killer bees in cafeteria' or 'other' [type=literal_error, input_value='lack of killer bees in cafeteria', input_type=str]\n For further information visit https://errors.pydantic.dev/2.10/v/literal_error\n\nDuring handling of the above exception, another exception occurred:\n\nTraceback (most recent call last):\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/jobs/AnswerQuestionFunctionConstructor.py\", line 184, in attempt_answer\n raise response.exception_occurred\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/agents/Invigilator.py\", line 163, in _extract_edsl_result_entry_and_validate\n validated_edsl_dict = question_with_validators._validate_answer(edsl_dict)\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/QuestionBase.py\", line 110, in _validate_answer\n return self.response_validator.validate(answer, replacement_dict)\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 123, in validate\n return self._handle_exception(e, raw_edsl_answer_dict)\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 143, in _handle_exception\n raise self.original_exception\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 117, in validate\n pydantic_edsl_answer: BaseModel = self._base_validate(\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 79, in _base_validate\n raise QuestionAnswerValidationError(\nedsl.exceptions.questions.QuestionAnswerValidationError: 1 validation error for ChoiceResponse\nanswer\n Input should be '**lack*** of killer bees in cafeteria' or 'other' [type=literal_error, input_value='lack of killer bees in cafeteria', input_type=str]\n For further information visit https://errors.pydantic.dev/2.10/v/literal_error\n"}, "time": "2025-01-07T08:06:31.027138", "traceback": "Traceback (most recent call last):\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 77, in _base_validate\n return self.response_model(**data)\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/project/lib/python3.9/site-packages/pydantic/main.py\", line 214, in __init__\n validated_self = self.__pydantic_validator__.validate_python(data, self_instance=self)\npydantic_core._pydantic_core.ValidationError: 1 validation error for ChoiceResponse\nanswer\n Input should be '**lack*** of killer bees in cafeteria' or 'other' [type=literal_error, input_value='lack of killer bees in cafeteria', input_type=str]\n For further information visit https://errors.pydantic.dev/2.10/v/literal_error\n\nDuring handling of the above exception, another exception occurred:\n\nTraceback (most recent call last):\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/jobs/AnswerQuestionFunctionConstructor.py\", line 184, in attempt_answer\n raise response.exception_occurred\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/agents/Invigilator.py\", line 163, in _extract_edsl_result_entry_and_validate\n validated_edsl_dict = question_with_validators._validate_answer(edsl_dict)\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/QuestionBase.py\", line 110, in _validate_answer\n return self.response_validator.validate(answer, replacement_dict)\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 123, in validate\n return self._handle_exception(e, raw_edsl_answer_dict)\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 143, in _handle_exception\n raise self.original_exception\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 117, in validate\n pydantic_edsl_answer: BaseModel = self._base_validate(\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 79, in _base_validate\n raise QuestionAnswerValidationError(\nedsl.exceptions.questions.QuestionAnswerValidationError: 1 validation error for ChoiceResponse\nanswer\n Input should be '**lack*** of killer bees in cafeteria' or 'other' [type=literal_error, input_value='lack of killer bees in cafeteria', input_type=str]\n For further information visit https://errors.pydantic.dev/2.10/v/literal_error\n", "invigilator": {"agent": {"traits": {"persona": "You are a chef", "age": 40}, "edsl_version": "0.1.41.dev3", "edsl_class_name": "Agent"}, "question": {"question_name": "q2", "question_text": "Why?", "question_options": ["**lack*** of killer bees in cafeteria", "other"], "question_type": "multiple_choice", "edsl_version": "0.1.41.dev3", "edsl_class_name": "QuestionBase"}, "scenario": {"scenario_index": 0, "edsl_version": "0.1.41.dev3", "edsl_class_name": "Scenario"}, "model": {"model": "gpt-3.5-turbo", "parameters": {"temperature": 0.5, "max_tokens": 1000, "top_p": 1, "frequency_penalty": 0, "presence_penalty": 0, "logprobs": false, "top_logprobs": 3}, "edsl_version": "0.1.41.dev3", "edsl_class_name": "LanguageModel"}, "memory_plan": {"survey_question_names": ["q0", "q1", "q2"], "survey_question_texts": ["Do you like school?", "Why not?", "Why?"], "data": {}}, "current_answers": {"q0_generated_tokens": "no\nSchool wasn't my favorite, but I did enjoy learning about cooking and culinary arts.", "q0": "no", "q0_comment": "School wasn't my favorite, but I did enjoy learning about cooking and culinary arts.", "q1_generated_tokens": "other\n// As a chef, I don't have any expertise in handling killer bees.", "q1": "other", "q1_comment": "// As a chef, I don't have any expertise in handling killer bees.", "q2": null}, "iteration": 0, "additional_prompt_data": null, "survey": {"questions": [{"question_name": "q0", "question_text": "Do you like school?", "question_options": ["yes", "no"], "question_type": "multiple_choice", "edsl_version": "0.1.41.dev3", "edsl_class_name": "QuestionBase"}, {"question_name": "q1", "question_text": "Why not?", "question_options": ["killer bees in cafeteria", "other"], "question_type": "multiple_choice", "edsl_version": "0.1.41.dev3", "edsl_class_name": "QuestionBase"}, {"question_name": "q2", "question_text": "Why?", "question_options": ["**lack*** of killer bees in cafeteria", "other"], "question_type": "multiple_choice", "edsl_version": "0.1.41.dev3", "edsl_class_name": "QuestionBase"}], "memory_plan": {"survey_question_names": ["q0", "q1", "q2"], "survey_question_texts": ["Do you like school?", "Why not?", "Why?"], "data": {}}, "rule_collection": {"rules": [{"current_q": 0, "expression": "True", "next_q": 1, "priority": -1, "question_name_to_index": {"q0": 0}, "before_rule": false}, {"current_q": 1, "expression": "True", "next_q": 2, "priority": -1, "question_name_to_index": {"q0": 0, "q1": 1}, "before_rule": false}, {"current_q": 2, "expression": "True", "next_q": 3, "priority": -1, "question_name_to_index": {"q0": 0, "q1": 1, "q2": 2}, "before_rule": false}, {"current_q": 0, "expression": "q0 == 'yes'", "next_q": 2, "priority": 0, "question_name_to_index": {"q0": 0, "q1": 1, "q2": 2}, "before_rule": false}], "num_questions": 3}, "question_groups": {}, "edsl_version": "0.1.41.dev3", "edsl_class_name": "Survey"}}}]}, "indices": {"agent": 1, "model": 0, "scenario": 0}}, {"agent": {"traits": {"persona": "You are a chef", "age": 40}, "edsl_version": "0.1.41.dev3", "edsl_class_name": "Agent"}, "survey": {"questions": [{"question_name": "q0", "question_text": "Do you like school?", "question_options": ["yes", "no"], "question_type": "multiple_choice", "edsl_version": "0.1.41.dev3", "edsl_class_name": "QuestionBase"}, {"question_name": "q1", "question_text": "Why not?", "question_options": ["killer bees in cafeteria", "other"], "question_type": "multiple_choice", "edsl_version": "0.1.41.dev3", "edsl_class_name": "QuestionBase"}, {"question_name": "q2", "question_text": "Why?", "question_options": ["**lack*** of killer bees in cafeteria", "other"], "question_type": "multiple_choice", "edsl_version": "0.1.41.dev3", "edsl_class_name": "QuestionBase"}], "memory_plan": {"survey_question_names": ["q0", "q1", "q2"], "survey_question_texts": ["Do you like school?", "Why not?", "Why?"], "data": {}}, "rule_collection": {"rules": [{"current_q": 0, "expression": "True", "next_q": 1, "priority": -1, "question_name_to_index": {"q0": 0}, "before_rule": false}, {"current_q": 1, "expression": "True", "next_q": 2, "priority": -1, "question_name_to_index": {"q0": 0, "q1": 1}, "before_rule": false}, {"current_q": 2, "expression": "True", "next_q": 3, "priority": -1, "question_name_to_index": {"q0": 0, "q1": 1, "q2": 2}, "before_rule": false}, {"current_q": 0, "expression": "q0 == 'yes'", "next_q": 2, "priority": 0, "question_name_to_index": {"q0": 0, "q1": 1, "q2": 2}, "before_rule": false}], "num_questions": 3}, "question_groups": {}, "edsl_version": "0.1.41.dev3", "edsl_class_name": "Survey"}, "scenario": {"scenario_index": 0, "edsl_version": "0.1.41.dev3", "edsl_class_name": "Scenario"}, "model": {"model": "gpt-4o", "parameters": {"temperature": 0.5, "max_tokens": 1000, "top_p": 1, "frequency_penalty": 0, "presence_penalty": 0, "logprobs": false, "top_logprobs": 3}, "edsl_version": "0.1.41.dev3", "edsl_class_name": "LanguageModel"}, "iteration": 0, "exceptions": {}, "indices": {"agent": 1, "model": 1, "scenario": 0}}], "include_traceback": false, "edsl_version": "0.1.41.dev3", "edsl_class_name": "TaskHistory"}}}, {"class_name": "Results", "dict": {"data": [{"agent": {"traits": {}}, "scenario": {"scenario_index": 0}, "model": {"model": "gpt-4o", "parameters": {"temperature": 0.5, "max_tokens": 1000, "top_p": 1, "frequency_penalty": 0, "presence_penalty": 0, "logprobs": false, "top_logprobs": 3}}, "iteration": 0, "answer": {"never_eat": ["panda milk custard", "McDonalds"], "extract_name": {"name": "Moby Dick", "profession": "Truck Driver"}, "how_are_you": "Thank you for asking! I'm here and ready to help you. How can I assist you today?", "list_of_foods": ["Pizza", "Sushi", "Chocolate", "Pasta", "Ice Cream"], "child_happiness": {"No children": 2, "1 child": 3, "2 children": 4, "3 or more children": 4}, "how_feeling": "Great", "age": 45, "food_budget": [{"Pizza": 30.0}, {"Ice Cream": 20.0}, {"Burgers": 40.0}, {"Salad": 10.0}], "rank_foods": ["Pizza", "Pasta"], "happy_raining": "Neutral", "ice_cream": null, "is_it_equal": "No", "two_fruits": ["apple", "banana"]}, "prompt": {"never_eat_user_prompt": {"text": "Which of the following foods would you eat if you had to?\n\n \n0: soggy meatpie\n \n1: rare snails\n \n2: mouldy bread\n \n3: panda milk custard\n \n4: McDonalds\n \n\n\n\n\nMinimum number of options that must be selected: 2.\nMaximum number of options that must be selected: 5.\n\n\n\nPlease respond only with a comma-separated list of the code of the options that apply, with square brackets. E.g., [0, 1, 3]", "class_name": "Prompt"}, "never_eat_system_prompt": {"text": "", "class_name": "Prompt"}, "extract_name_user_prompt": {"text": "My name is Moby Dick. I have a PhD in astrology, but I'm actually a truck driverAn ANSWER should be formatted like this: \n\n{'name': 'John Doe', 'profession': 'Carpenter'}\n\nIt should have the same keys but values extracted from the input.\nIf the value of a key is not present in the input, fill with \"null\".\nPut any comments in the next line after the answer.", "class_name": "Prompt"}, "extract_name_system_prompt": {"text": "", "class_name": "Prompt"}, "how_are_you_user_prompt": {"text": "How are you?", "class_name": "Prompt"}, "how_are_you_system_prompt": {"text": "", "class_name": "Prompt"}, "list_of_foods_user_prompt": {"text": "What are your favorite foods?\n\n\nReturn your answers on one line, in a comma-separated list of your responses, with square brackets and each answer in quotes E.g., [\"A\", \"B\", \"C\"]\n\nAfter the answers, you can put a comment explaining your choice on the next line.", "class_name": "Prompt"}, "list_of_foods_system_prompt": {"text": "", "class_name": "Prompt"}, "child_happiness_user_prompt": {"text": "How happy would you be with different numbers of children?\n\nRows:\n \n0: No children\n \n1: 1 child\n \n2: 2 children\n \n3: 3 or more children\n \n\nColumns:\n \n0: 1\n (Very sad)\n \n1: 2\n \n2: 3\n (Neutral)\n \n3: 4\n \n4: 5\n (Extremely happy)\n \n\n\nSelect one column option for each row.\n Please respond with a dictionary mapping row codes to column codes. E.g., {\"0\": 1, \"1\": 3}\n\n\nAfter the answer, you can put a comment explaining your choices on the next line.\n ", "class_name": "Prompt"}, "child_happiness_system_prompt": {"text": "", "class_name": "Prompt"}, "how_feeling_user_prompt": {"text": "\nHow are you?\n\n \nGood\n \nGreat\n \nOK\n \nBad\n \n\nOnly 1 option may be selected.\n\nRespond only with a string corresponding to one of the options.", "class_name": "Prompt"}, "how_feeling_system_prompt": {"text": "", "class_name": "Prompt"}, "age_user_prompt": {"text": "You are a 45 year old man. How old are you in years?\n\n Minimum answer value: 0\n\n\n Maximum answer value: 86.7\nThis question requires a numerical response in the form of an integer or decimal (e.g., -12, 0, 1, 2, 3.45, ...).\nRespond with just your number on a single line.\nIf your response is equivalent to zero, report '0'", "class_name": "Prompt"}, "age_system_prompt": {"text": "", "class_name": "Prompt"}, "food_budget_user_prompt": {"text": "How would you allocate $100?\nThe options are \n\n0: Pizza\n\n1: Ice Cream\n\n2: Burgers\n\n3: Salad\n \nAllocate your budget of 100 among the options. \n\nReturn only a comma-separated list the values in the same order as the options, with 0s included, on one line, in square braces.\n\nExample: if there are 4 options, the response should be \"[25,25,25,25]\" to allocate 25 to each option.\n\n\nAfter the answer, you can put a comment explaining your choice on the next line.", "class_name": "Prompt"}, "food_budget_system_prompt": {"text": "", "class_name": "Prompt"}, "rank_foods_user_prompt": {"text": "Rank your favorite foods.\n\nThe options are:\n\nPizza\n\nPasta\n\nSalad\n\nSoup\n\n\n\nYou can inlcude up to 2 options in your answer.\n\n\n\nPlease respond only with a comma-separated list of the ranked options, with square brackets. E.g., ['Good', 'Bad', 'Ugly']\n\n\nAfter the answer, you can put a comment explaining your choice on the next line.", "class_name": "Prompt"}, "rank_foods_system_prompt": {"text": "", "class_name": "Prompt"}, "happy_raining_user_prompt": {"text": "\nI'm only happy when it rains.\n\n \nStrongly disagree\n \nDisagree\n \nNeutral\n \nAgree\n \nStrongly agree\n \n\nOnly 1 option may be selected.\n\nRespond only with a string corresponding to one of the options.\n\n\nAfter the answer, you can put a comment explaining why you chose that option on the next line.", "class_name": "Prompt"}, "happy_raining_system_prompt": {"text": "", "class_name": "Prompt"}, "ice_cream_user_prompt": {"text": "How much do you like ice cream?\n\n1 : I hate it\n\n2 : \n\n3 : \n\n4 : \n\n5 : I love it\n\nOnly 1 option may be selected.\n\nRespond only with the code corresponding to one of the options. E.g., \"1\" or \"5\" by itself.\n\nAfter the answer, you can put a comment explaining why you chose that option on the next line.", "class_name": "Prompt"}, "ice_cream_system_prompt": {"text": "", "class_name": "Prompt"}, "is_it_equal_user_prompt": {"text": "\nIs 5 + 5 equal to 11?\n\n \nNo\n \nYes\n \n\nOnly 1 option may be selected.\nPlease respond with just your answer. \n\n\nAfter the answer, you can put a comment explaining your response.", "class_name": "Prompt"}, "is_it_equal_system_prompt": {"text": "", "class_name": "Prompt"}, "two_fruits_user_prompt": {"text": "Which of the following fruits do you prefer?\n\n \n0: apple\n \n1: banana\n \n2: carrot\n \n3: durian\n \n\n\n\n\nYou must select exactly 2 options.\n\n\nPlease respond with valid JSON, formatted like so:\n\n {\"answer\": [], \"comment\": \"\"}", "class_name": "Prompt"}, "two_fruits_system_prompt": {"text": "", "class_name": "Prompt"}}, "raw_model_response": {"never_eat_raw_model_response": {"id": "chatcmpl-AmytyW4NuiLRGgaaqBxjPlemTTUMe", "choices": [{"finish_reason": "stop", "index": 0, "logprobs": null, "message": {"content": "[3, 4]", "refusal": null, "role": "assistant", "audio": null, "function_call": null, "tool_calls": null}}], "created": 1736237214, "model": "gpt-4o-2024-08-06", "object": "chat.completion", "service_tier": null, "system_fingerprint": "fp_5f20662549", "usage": {"completion_tokens": 7, "prompt_tokens": 110, "total_tokens": 117, "completion_tokens_details": {"accepted_prediction_tokens": 0, "audio_tokens": 0, "reasoning_tokens": 0, "rejected_prediction_tokens": 0}, "prompt_tokens_details": {"audio_tokens": 0, "cached_tokens": 0}}}, "never_eat_cost": 0.00034500000000000004, "never_eat_one_usd_buys": 2898.550724637681, "extract_name_raw_model_response": {"id": "chatcmpl-AmyuAqHGrsitJYLK266KrggAQ3aJb", "choices": [{"finish_reason": "stop", "index": 0, "logprobs": null, "message": {"content": "{'name': 'Moby Dick', 'profession': 'Truck Driver'}\n\nThe input provided the name \"Moby Dick\" and the profession as \"Truck Driver\", which is extracted and formatted as requested. The PhD in astrology is not considered the profession here as the input specifies the actual job as a truck driver.", "refusal": null, "role": "assistant", "audio": null, "function_call": null, "tool_calls": null}}], "created": 1736237226, "model": "gpt-4o-2024-08-06", "object": "chat.completion", "service_tier": null, "system_fingerprint": "fp_5f20662549", "usage": {"completion_tokens": 65, "prompt_tokens": 95, "total_tokens": 160, "completion_tokens_details": {"accepted_prediction_tokens": 0, "audio_tokens": 0, "reasoning_tokens": 0, "rejected_prediction_tokens": 0}, "prompt_tokens_details": {"audio_tokens": 0, "cached_tokens": 0}}}, "extract_name_cost": 0.0008874999999999999, "extract_name_one_usd_buys": 1126.7605633802818, "how_are_you_raw_model_response": {"id": "chatcmpl-Amyu4eRjFjyBt7IllgdwXPpzUd4jR", "choices": [{"finish_reason": "stop", "index": 0, "logprobs": null, "message": {"content": "Thank you for asking! I'm here and ready to help you. How can I assist you today?", "refusal": null, "role": "assistant", "audio": null, "function_call": null, "tool_calls": null}}], "created": 1736237220, "model": "gpt-4o-2024-08-06", "object": "chat.completion", "service_tier": null, "system_fingerprint": "fp_e161c81bbd", "usage": {"completion_tokens": 21, "prompt_tokens": 11, "total_tokens": 32, "completion_tokens_details": {"accepted_prediction_tokens": 0, "audio_tokens": 0, "reasoning_tokens": 0, "rejected_prediction_tokens": 0}, "prompt_tokens_details": {"audio_tokens": 0, "cached_tokens": 0}}}, "how_are_you_cost": 0.0002375, "how_are_you_one_usd_buys": 4210.526315789473, "list_of_foods_raw_model_response": {"id": "chatcmpl-AmyuGVtiesaMJraq9tjOB9uXNJawG", "choices": [{"finish_reason": "stop", "index": 0, "logprobs": null, "message": {"content": "[\"Pizza\", \"Sushi\", \"Chocolate\", \"Pasta\", \"Ice Cream\"] \nThese foods are popular and widely enjoyed for their flavors, versatility, and comforting qualities.", "refusal": null, "role": "assistant", "audio": null, "function_call": null, "tool_calls": null}}], "created": 1736237232, "model": "gpt-4o-2024-08-06", "object": "chat.completion", "service_tier": null, "system_fingerprint": "fp_5f20662549", "usage": {"completion_tokens": 37, "prompt_tokens": 66, "total_tokens": 103, "completion_tokens_details": {"accepted_prediction_tokens": 0, "audio_tokens": 0, "reasoning_tokens": 0, "rejected_prediction_tokens": 0}, "prompt_tokens_details": {"audio_tokens": 0, "cached_tokens": 0}}}, "list_of_foods_cost": 0.000535, "list_of_foods_one_usd_buys": 1869.1588785046729, "child_happiness_raw_model_response": {"id": "chatcmpl-AmyuSPPHAw07ETztGwmZfxB9cAIn9", "choices": [{"finish_reason": "stop", "index": 0, "logprobs": null, "message": {"content": "{\"0\": 2, \"1\": 3, \"2\": 4, \"3\": 4}\n\nHaving no children might leave me neutral as it allows for freedom and flexibility, but having children can bring joy and fulfillment, hence the higher happiness ratings with increasing numbers of children.", "refusal": null, "role": "assistant", "audio": null, "function_call": null, "tool_calls": null}}], "created": 1736237244, "model": "gpt-4o-2024-08-06", "object": "chat.completion", "service_tier": null, "system_fingerprint": "fp_5f20662549", "usage": {"completion_tokens": 60, "prompt_tokens": 142, "total_tokens": 202, "completion_tokens_details": {"accepted_prediction_tokens": 0, "audio_tokens": 0, "reasoning_tokens": 0, "rejected_prediction_tokens": 0}, "prompt_tokens_details": {"audio_tokens": 0, "cached_tokens": 0}}}, "child_happiness_cost": 0.0009549999999999999, "child_happiness_one_usd_buys": 1047.1204188481677, "how_feeling_raw_model_response": {"id": "chatcmpl-Amyts1aEAiAwwT9n3WAuUOmAyvOOo", "choices": [{"finish_reason": "stop", "index": 0, "logprobs": null, "message": {"content": "Great", "refusal": null, "role": "assistant", "audio": null, "function_call": null, "tool_calls": null}}], "created": 1736237208, "model": "gpt-4o-2024-08-06", "object": "chat.completion", "service_tier": null, "system_fingerprint": "fp_d28bcae782", "usage": {"completion_tokens": 2, "prompt_tokens": 41, "total_tokens": 43, "completion_tokens_details": {"accepted_prediction_tokens": 0, "audio_tokens": 0, "reasoning_tokens": 0, "rejected_prediction_tokens": 0}, "prompt_tokens_details": {"audio_tokens": 0, "cached_tokens": 0}}}, "how_feeling_cost": 0.0001225, "how_feeling_one_usd_buys": 8163.265306122449, "age_raw_model_response": {"id": "chatcmpl-AmytmJ9LB0L6fVpbxT87k5EM9SJXp", "choices": [{"finish_reason": "stop", "index": 0, "logprobs": null, "message": {"content": "45", "refusal": null, "role": "assistant", "audio": null, "function_call": null, "tool_calls": null}}], "created": 1736237202, "model": "gpt-4o-2024-08-06", "object": "chat.completion", "service_tier": null, "system_fingerprint": "fp_d28bcae782", "usage": {"completion_tokens": 2, "prompt_tokens": 100, "total_tokens": 102, "completion_tokens_details": {"accepted_prediction_tokens": 0, "audio_tokens": 0, "reasoning_tokens": 0, "rejected_prediction_tokens": 0}, "prompt_tokens_details": {"audio_tokens": 0, "cached_tokens": 0}}}, "age_cost": 0.00027, "age_one_usd_buys": 3703.7037037037035, "food_budget_raw_model_response": {"id": "chatcmpl-AmyukJ09rvlKI2ptzLldx6QZQbCQC", "choices": [{"finish_reason": "stop", "index": 0, "logprobs": null, "message": {"content": "[30,20,40,10] \nI allocated more to burgers as they tend to be more filling and versatile, followed by pizza and ice cream for variety and enjoyment. Salad received the least as a lighter option.", "refusal": null, "role": "assistant", "audio": null, "function_call": null, "tool_calls": null}}], "created": 1736237262, "model": "gpt-4o-2024-08-06", "object": "chat.completion", "service_tier": null, "system_fingerprint": "fp_5f20662549", "usage": {"completion_tokens": 46, "prompt_tokens": 125, "total_tokens": 171, "completion_tokens_details": {"accepted_prediction_tokens": 0, "audio_tokens": 0, "reasoning_tokens": 0, "rejected_prediction_tokens": 0}, "prompt_tokens_details": {"audio_tokens": 0, "cached_tokens": 0}}}, "food_budget_cost": 0.0007725, "food_budget_one_usd_buys": 1294.4983818770227, "rank_foods_raw_model_response": {"id": "chatcmpl-Amytgg3Dexr59yTd6v0crDsBV8j90", "choices": [{"finish_reason": "stop", "index": 0, "logprobs": null, "message": {"content": "['Pizza', 'Pasta'] \nPizza and pasta are often favorites due to their versatility and comforting nature.", "refusal": null, "role": "assistant", "audio": null, "function_call": null, "tool_calls": null}}], "created": 1736237196, "model": "gpt-4o-2024-08-06", "object": "chat.completion", "service_tier": null, "system_fingerprint": "fp_d28bcae782", "usage": {"completion_tokens": 23, "prompt_tokens": 87, "total_tokens": 110, "completion_tokens_details": {"accepted_prediction_tokens": 0, "audio_tokens": 0, "reasoning_tokens": 0, "rejected_prediction_tokens": 0}, "prompt_tokens_details": {"audio_tokens": 0, "cached_tokens": 0}}}, "rank_foods_cost": 0.0004475, "rank_foods_one_usd_buys": 2234.63687150838, "happy_raining_raw_model_response": {"id": "chatcmpl-AmyuqEXvdyw4bmmRmPDLhSB0gLHN0", "choices": [{"finish_reason": "stop", "index": 0, "logprobs": null, "message": {"content": "Neutral\n\nThis statement could be interpreted in various ways, and without additional context, it's difficult to decisively agree or disagree.", "refusal": null, "role": "assistant", "audio": null, "function_call": null, "tool_calls": null}}], "created": 1736237268, "model": "gpt-4o-2024-08-06", "object": "chat.completion", "service_tier": null, "system_fingerprint": "fp_5f20662549", "usage": {"completion_tokens": 26, "prompt_tokens": 71, "total_tokens": 97, "completion_tokens_details": {"accepted_prediction_tokens": 0, "audio_tokens": 0, "reasoning_tokens": 0, "rejected_prediction_tokens": 0}, "prompt_tokens_details": {"audio_tokens": 0, "cached_tokens": 0}}}, "happy_raining_cost": 0.00043749999999999995, "happy_raining_one_usd_buys": 2285.714285714286, "ice_cream_raw_model_response": null, "ice_cream_cost": null, "ice_cream_one_usd_buys": "NA", "is_it_equal_raw_model_response": {"id": "chatcmpl-AmyuYEsN7kjicbiRR8LmW9pQ38uu8", "choices": [{"finish_reason": "stop", "index": 0, "logprobs": null, "message": {"content": "No\n\n5 + 5 equals 10, not 11.", "refusal": null, "role": "assistant", "audio": null, "function_call": null, "tool_calls": null}}], "created": 1736237250, "model": "gpt-4o-2024-08-06", "object": "chat.completion", "service_tier": null, "system_fingerprint": "fp_e161c81bbd", "usage": {"completion_tokens": 15, "prompt_tokens": 53, "total_tokens": 68, "completion_tokens_details": {"accepted_prediction_tokens": 0, "audio_tokens": 0, "reasoning_tokens": 0, "rejected_prediction_tokens": 0}, "prompt_tokens_details": {"audio_tokens": 0, "cached_tokens": 0}}}, "is_it_equal_cost": 0.0002825, "is_it_equal_one_usd_buys": 3539.823008849558, "two_fruits_raw_model_response": {"id": "chatcmpl-AmyuetQUXTUQvUbKS8iX3WQxUSRpW", "choices": [{"finish_reason": "stop", "index": 0, "logprobs": null, "message": {"content": "```json\n{\n \"answer\": [0, 1],\n \"comment\": \"I prefer apples and bananas because they are both widely enjoyed fruits that are versatile and nutritious. Apples are crisp and refreshing, while bananas are sweet and convenient to eat on the go. Carrots are not a fruit, and durian, though unique, is often polarizing due to its strong odor.\"\n}\n```", "refusal": null, "role": "assistant", "audio": null, "function_call": null, "tool_calls": null}}], "created": 1736237256, "model": "gpt-4o-2024-08-06", "object": "chat.completion", "service_tier": null, "system_fingerprint": "fp_5f20662549", "usage": {"completion_tokens": 82, "prompt_tokens": 75, "total_tokens": 157, "completion_tokens_details": {"accepted_prediction_tokens": 0, "audio_tokens": 0, "reasoning_tokens": 0, "rejected_prediction_tokens": 0}, "prompt_tokens_details": {"audio_tokens": 0, "cached_tokens": 0}}}, "two_fruits_cost": 0.0010075, "two_fruits_one_usd_buys": 992.5558312655088}, "question_to_attributes": null, "generated_tokens": {"never_eat_generated_tokens": "[3, 4]", "extract_name_generated_tokens": "{'name': 'Moby Dick', 'profession': 'Truck Driver'}\n\nThe input provided the name \"Moby Dick\" and the profession as \"Truck Driver\", which is extracted and formatted as requested. The PhD in astrology is not considered the profession here as the input specifies the actual job as a truck driver.", "how_are_you_generated_tokens": "Thank you for asking! I'm here and ready to help you. How can I assist you today?", "list_of_foods_generated_tokens": "[\"Pizza\", \"Sushi\", \"Chocolate\", \"Pasta\", \"Ice Cream\"] \nThese foods are popular and widely enjoyed for their flavors, versatility, and comforting qualities.", "child_happiness_generated_tokens": "{\"0\": 2, \"1\": 3, \"2\": 4, \"3\": 4}\n\nHaving no children might leave me neutral as it allows for freedom and flexibility, but having children can bring joy and fulfillment, hence the higher happiness ratings with increasing numbers of children.", "how_feeling_generated_tokens": "Great", "age_generated_tokens": "45", "food_budget_generated_tokens": "[30,20,40,10] \nI allocated more to burgers as they tend to be more filling and versatile, followed by pizza and ice cream for variety and enjoyment. Salad received the least as a lighter option.", "rank_foods_generated_tokens": "['Pizza', 'Pasta'] \nPizza and pasta are often favorites due to their versatility and comforting nature.", "happy_raining_generated_tokens": "Neutral\n\nThis statement could be interpreted in various ways, and without additional context, it's difficult to decisively agree or disagree.", "ice_cream_generated_tokens": null, "is_it_equal_generated_tokens": "No\n\n5 + 5 equals 10, not 11.", "two_fruits_generated_tokens": "```json\n{\n \"answer\": [0, 1],\n \"comment\": \"I prefer apples and bananas because they are both widely enjoyed fruits that are versatile and nutritious. Apples are crisp and refreshing, while bananas are sweet and convenient to eat on the go. Carrots are not a fruit, and durian, though unique, is often polarizing due to its strong odor.\"\n}\n```"}, "comments_dict": {"never_eat_comment": null, "extract_name_comment": "The input provided the name \"Moby Dick\" and the profession as \"Truck Driver\", which is extracted and formatted as requested. The PhD in astrology is not considered the profession here as the input specifies the actual job as a truck driver.", "how_are_you_comment": "", "list_of_foods_comment": "These foods are popular and widely enjoyed for their flavors, versatility, and comforting qualities.", "child_happiness_comment": "Having no children might leave me neutral as it allows for freedom and flexibility, but having children can bring joy and fulfillment, hence the higher happiness ratings with increasing numbers of children.", "how_feeling_comment": null, "age_comment": null, "food_budget_comment": "I allocated more to burgers as they tend to be more filling and versatile, followed by pizza and ice cream for variety and enjoyment. Salad received the least as a lighter option.", "rank_foods_comment": "Pizza and pasta are often favorites due to their versatility and comforting nature.", "happy_raining_comment": "This statement could be interpreted in various ways, and without additional context, it's difficult to decisively agree or disagree.", "ice_cream_comment": "Question answer validation failed.", "is_it_equal_comment": "5 + 5 equals 10, not 11.", "two_fruits_comment": "```"}, "cache_used_dict": {"never_eat": false, "extract_name": false, "how_are_you": false, "list_of_foods": false, "child_happiness": false, "how_feeling": false, "age": false, "food_budget": false, "rank_foods": false, "happy_raining": false, "ice_cream": null, "is_it_equal": false, "two_fruits": false}}], "survey": {"questions": [{"question_name": "never_eat", "question_text": "Which of the following foods would you eat if you had to?", "min_selections": 2, "max_selections": 5, "question_options": ["soggy meatpie", "rare snails", "mouldy bread", "panda milk custard", "McDonalds"], "include_comment": false, "use_code": true, "question_type": "checkbox"}, {"question_name": "extract_name", "question_text": "My name is Moby Dick. I have a PhD in astrology, but I'm actually a truck driver", "answer_template": {"name": "John Doe", "profession": "Carpenter"}, "question_type": "extract"}, {"question_name": "how_are_you", "question_text": "How are you?", "question_type": "free_text"}, {"question_name": "list_of_foods", "question_text": "What are your favorite foods?", "question_type": "list"}, {"question_name": "child_happiness", "question_text": "How happy would you be with different numbers of children?", "question_items": ["No children", "1 child", "2 children", "3 or more children"], "question_options": [1, 2, 3, 4, 5], "option_labels": {"1": "Very sad", "3": "Neutral", "5": "Extremely happy"}, "question_type": "matrix"}, {"question_name": "how_feeling", "question_text": "How are you?", "question_options": ["Good", "Great", "OK", "Bad"], "include_comment": false, "question_type": "multiple_choice"}, {"question_name": "age", "question_text": "You are a 45 year old man. How old are you in years?", "min_value": 0, "max_value": 86.7, "include_comment": false, "question_type": "numerical"}, {"question_name": "food_budget", "question_text": "How would you allocate $100?", "question_options": ["Pizza", "Ice Cream", "Burgers", "Salad"], "budget_sum": 100, "question_type": "budget"}, {"question_name": "rank_foods", "question_text": "Rank your favorite foods.", "question_options": ["Pizza", "Pasta", "Salad", "Soup"], "num_selections": 2, "question_type": "rank"}, {"question_name": "happy_raining", "question_text": "I'm only happy when it rains.", "question_options": ["Strongly disagree", "Disagree", "Neutral", "Agree", "Strongly agree"], "question_type": "likert_five"}, {"question_name": "ice_cream", "question_text": "How much do you like ice cream?", "question_options": [1, 2, 3, 4, 5], "option_labels": {"1": "I hate it", "5": "I love it"}, "question_type": "linear_scale"}, {"question_name": "is_it_equal", "question_text": "Is 5 + 5 equal to 11?", "question_options": ["No", "Yes"], "question_type": "yes_no"}, {"question_name": "two_fruits", "question_text": "Which of the following fruits do you prefer?", "min_selections": 2, "max_selections": 2, "question_options": ["apple", "banana", "carrot", "durian"], "use_code": true, "question_type": "top_k"}], "memory_plan": {"survey_question_names": ["never_eat", "extract_name", "how_are_you", "list_of_foods", "child_happiness", "how_feeling", "age", "food_budget", "rank_foods", "happy_raining", "ice_cream", "is_it_equal", "two_fruits"], "survey_question_texts": ["Which of the following foods would you eat if you had to?", "My name is Moby Dick. I have a PhD in astrology, but I'm actually a truck driver", "How are you?", "What are your favorite foods?", "How happy would you be with different numbers of children?", "How are you?", "You are a 45 year old man. How old are you in years?", "How would you allocate $100?", "Rank your favorite foods.", "I'm only happy when it rains.", "How much do you like ice cream?", "Is 5 + 5 equal to 11?", "Which of the following fruits do you prefer?"], "data": {}}, "rule_collection": {"rules": [{"current_q": 0, "expression": "True", "next_q": 1, "priority": -1, "question_name_to_index": {"never_eat": 0}, "before_rule": false}, {"current_q": 1, "expression": "True", "next_q": 2, "priority": -1, "question_name_to_index": {"never_eat": 0, "extract_name": 1}, "before_rule": false}, {"current_q": 2, "expression": "True", "next_q": 3, "priority": -1, "question_name_to_index": {"never_eat": 0, "extract_name": 1, "how_are_you": 2}, "before_rule": false}, {"current_q": 3, "expression": "True", "next_q": 4, "priority": -1, "question_name_to_index": {"never_eat": 0, "extract_name": 1, "how_are_you": 2, "list_of_foods": 3}, "before_rule": false}, {"current_q": 4, "expression": "True", "next_q": 5, "priority": -1, "question_name_to_index": {"never_eat": 0, "extract_name": 1, "how_are_you": 2, "list_of_foods": 3, "child_happiness": 4}, "before_rule": false}, {"current_q": 5, "expression": "True", "next_q": 6, "priority": -1, "question_name_to_index": {"never_eat": 0, "extract_name": 1, "how_are_you": 2, "list_of_foods": 3, "child_happiness": 4, "how_feeling": 5}, "before_rule": false}, {"current_q": 6, "expression": "True", "next_q": 7, "priority": -1, "question_name_to_index": {"never_eat": 0, "extract_name": 1, "how_are_you": 2, "list_of_foods": 3, "child_happiness": 4, "how_feeling": 5, "age": 6}, "before_rule": false}, {"current_q": 7, "expression": "True", "next_q": 8, "priority": -1, "question_name_to_index": {"never_eat": 0, "extract_name": 1, "how_are_you": 2, "list_of_foods": 3, "child_happiness": 4, "how_feeling": 5, "age": 6, "food_budget": 7}, "before_rule": false}, {"current_q": 8, "expression": "True", "next_q": 9, "priority": -1, "question_name_to_index": {"never_eat": 0, "extract_name": 1, "how_are_you": 2, "list_of_foods": 3, "child_happiness": 4, "how_feeling": 5, "age": 6, "food_budget": 7, "rank_foods": 8}, "before_rule": false}, {"current_q": 9, "expression": "True", "next_q": 10, "priority": -1, "question_name_to_index": {"never_eat": 0, "extract_name": 1, "how_are_you": 2, "list_of_foods": 3, "child_happiness": 4, "how_feeling": 5, "age": 6, "food_budget": 7, "rank_foods": 8, "happy_raining": 9}, "before_rule": false}, {"current_q": 10, "expression": "True", "next_q": 11, "priority": -1, "question_name_to_index": {"never_eat": 0, "extract_name": 1, "how_are_you": 2, "list_of_foods": 3, "child_happiness": 4, "how_feeling": 5, "age": 6, "food_budget": 7, "rank_foods": 8, "happy_raining": 9, "ice_cream": 10}, "before_rule": false}, {"current_q": 11, "expression": "True", "next_q": 12, "priority": -1, "question_name_to_index": {"never_eat": 0, "extract_name": 1, "how_are_you": 2, "list_of_foods": 3, "child_happiness": 4, "how_feeling": 5, "age": 6, "food_budget": 7, "rank_foods": 8, "happy_raining": 9, "ice_cream": 10, "is_it_equal": 11}, "before_rule": false}, {"current_q": 12, "expression": "True", "next_q": 13, "priority": -1, "question_name_to_index": {"never_eat": 0, "extract_name": 1, "how_are_you": 2, "list_of_foods": 3, "child_happiness": 4, "how_feeling": 5, "age": 6, "food_budget": 7, "rank_foods": 8, "happy_raining": 9, "ice_cream": 10, "is_it_equal": 11, "two_fruits": 12}, "before_rule": false}], "num_questions": 13}, "question_groups": {}}, "created_columns": [], "task_history": {"interviews": [{"agent": {"traits": {}, "edsl_version": "0.1.41.dev3", "edsl_class_name": "Agent"}, "survey": {"questions": [{"question_name": "never_eat", "question_text": "Which of the following foods would you eat if you had to?", "min_selections": 2, "max_selections": 5, "question_options": ["soggy meatpie", "rare snails", "mouldy bread", "panda milk custard", "McDonalds"], "include_comment": false, "use_code": true, "question_type": "checkbox", "edsl_version": "0.1.41.dev3", "edsl_class_name": "QuestionBase"}, {"question_name": "extract_name", "question_text": "My name is Moby Dick. I have a PhD in astrology, but I'm actually a truck driver", "answer_template": {"name": "John Doe", "profession": "Carpenter"}, "question_type": "extract", "edsl_version": "0.1.41.dev3", "edsl_class_name": "QuestionBase"}, {"question_name": "how_are_you", "question_text": "How are you?", "question_type": "free_text", "edsl_version": "0.1.41.dev3", "edsl_class_name": "QuestionBase"}, {"question_name": "list_of_foods", "question_text": "What are your favorite foods?", "question_type": "list", "edsl_version": "0.1.41.dev3", "edsl_class_name": "QuestionBase"}, {"question_name": "child_happiness", "question_text": "How happy would you be with different numbers of children?", "question_items": ["No children", "1 child", "2 children", "3 or more children"], "question_options": [1, 2, 3, 4, 5], "option_labels": {"1": "Very sad", "3": "Neutral", "5": "Extremely happy"}, "question_type": "matrix", "edsl_version": "0.1.41.dev3", "edsl_class_name": "QuestionBase"}, {"question_name": "how_feeling", "question_text": "How are you?", "question_options": ["Good", "Great", "OK", "Bad"], "include_comment": false, "question_type": "multiple_choice", "edsl_version": "0.1.41.dev3", "edsl_class_name": "QuestionBase"}, {"question_name": "age", "question_text": "You are a 45 year old man. How old are you in years?", "min_value": 0, "max_value": 86.7, "include_comment": false, "question_type": "numerical", "edsl_version": "0.1.41.dev3", "edsl_class_name": "QuestionBase"}, {"question_name": "food_budget", "question_text": "How would you allocate $100?", "question_options": ["Pizza", "Ice Cream", "Burgers", "Salad"], "budget_sum": 100, "question_type": "budget", "edsl_version": "0.1.41.dev3", "edsl_class_name": "QuestionBase"}, {"question_name": "rank_foods", "question_text": "Rank your favorite foods.", "question_options": ["Pizza", "Pasta", "Salad", "Soup"], "num_selections": 2, "question_type": "rank", "edsl_version": "0.1.41.dev3", "edsl_class_name": "QuestionBase"}, {"question_name": "happy_raining", "question_text": "I'm only happy when it rains.", "question_options": ["Strongly disagree", "Disagree", "Neutral", "Agree", "Strongly agree"], "question_type": "likert_five", "edsl_version": "0.1.41.dev3", "edsl_class_name": "QuestionBase"}, {"question_name": "ice_cream", "question_text": "How much do you like ice cream?", "question_options": [1, 2, 3, 4, 5], "option_labels": {"1": "I hate it", "5": "I love it"}, "question_type": "linear_scale", "edsl_version": "0.1.41.dev3", "edsl_class_name": "QuestionBase"}, {"question_name": "is_it_equal", "question_text": "Is 5 + 5 equal to 11?", "question_options": ["No", "Yes"], "question_type": "yes_no", "edsl_version": "0.1.41.dev3", "edsl_class_name": "QuestionBase"}, {"question_name": "two_fruits", "question_text": "Which of the following fruits do you prefer?", "min_selections": 2, "max_selections": 2, "question_options": ["apple", "banana", "carrot", "durian"], "use_code": true, "question_type": "top_k", "edsl_version": "0.1.41.dev3", "edsl_class_name": "QuestionBase"}], "memory_plan": {"survey_question_names": ["never_eat", "extract_name", "how_are_you", "list_of_foods", "child_happiness", "how_feeling", "age", "food_budget", "rank_foods", "happy_raining", "ice_cream", "is_it_equal", "two_fruits"], "survey_question_texts": ["Which of the following foods would you eat if you had to?", "My name is Moby Dick. I have a PhD in astrology, but I'm actually a truck driver", "How are you?", "What are your favorite foods?", "How happy would you be with different numbers of children?", "How are you?", "You are a 45 year old man. How old are you in years?", "How would you allocate $100?", "Rank your favorite foods.", "I'm only happy when it rains.", "How much do you like ice cream?", "Is 5 + 5 equal to 11?", "Which of the following fruits do you prefer?"], "data": {}}, "rule_collection": {"rules": [{"current_q": 0, "expression": "True", "next_q": 1, "priority": -1, "question_name_to_index": {"never_eat": 0}, "before_rule": false}, {"current_q": 1, "expression": "True", "next_q": 2, "priority": -1, "question_name_to_index": {"never_eat": 0, "extract_name": 1}, "before_rule": false}, {"current_q": 2, "expression": "True", "next_q": 3, "priority": -1, "question_name_to_index": {"never_eat": 0, "extract_name": 1, "how_are_you": 2}, "before_rule": false}, {"current_q": 3, "expression": "True", "next_q": 4, "priority": -1, "question_name_to_index": {"never_eat": 0, "extract_name": 1, "how_are_you": 2, "list_of_foods": 3}, "before_rule": false}, {"current_q": 4, "expression": "True", "next_q": 5, "priority": -1, "question_name_to_index": {"never_eat": 0, "extract_name": 1, "how_are_you": 2, "list_of_foods": 3, "child_happiness": 4}, "before_rule": false}, {"current_q": 5, "expression": "True", "next_q": 6, "priority": -1, "question_name_to_index": {"never_eat": 0, "extract_name": 1, "how_are_you": 2, "list_of_foods": 3, "child_happiness": 4, "how_feeling": 5}, "before_rule": false}, {"current_q": 6, "expression": "True", "next_q": 7, "priority": -1, "question_name_to_index": {"never_eat": 0, "extract_name": 1, "how_are_you": 2, "list_of_foods": 3, "child_happiness": 4, "how_feeling": 5, "age": 6}, "before_rule": false}, {"current_q": 7, "expression": "True", "next_q": 8, "priority": -1, "question_name_to_index": {"never_eat": 0, "extract_name": 1, "how_are_you": 2, "list_of_foods": 3, "child_happiness": 4, "how_feeling": 5, "age": 6, "food_budget": 7}, "before_rule": false}, {"current_q": 8, "expression": "True", "next_q": 9, "priority": -1, "question_name_to_index": {"never_eat": 0, "extract_name": 1, "how_are_you": 2, "list_of_foods": 3, "child_happiness": 4, "how_feeling": 5, "age": 6, "food_budget": 7, "rank_foods": 8}, "before_rule": false}, {"current_q": 9, "expression": "True", "next_q": 10, "priority": -1, "question_name_to_index": {"never_eat": 0, "extract_name": 1, "how_are_you": 2, "list_of_foods": 3, "child_happiness": 4, "how_feeling": 5, "age": 6, "food_budget": 7, "rank_foods": 8, "happy_raining": 9}, "before_rule": false}, {"current_q": 10, "expression": "True", "next_q": 11, "priority": -1, "question_name_to_index": {"never_eat": 0, "extract_name": 1, "how_are_you": 2, "list_of_foods": 3, "child_happiness": 4, "how_feeling": 5, "age": 6, "food_budget": 7, "rank_foods": 8, "happy_raining": 9, "ice_cream": 10}, "before_rule": false}, {"current_q": 11, "expression": "True", "next_q": 12, "priority": -1, "question_name_to_index": {"never_eat": 0, "extract_name": 1, "how_are_you": 2, "list_of_foods": 3, "child_happiness": 4, "how_feeling": 5, "age": 6, "food_budget": 7, "rank_foods": 8, "happy_raining": 9, "ice_cream": 10, "is_it_equal": 11}, "before_rule": false}, {"current_q": 12, "expression": "True", "next_q": 13, "priority": -1, "question_name_to_index": {"never_eat": 0, "extract_name": 1, "how_are_you": 2, "list_of_foods": 3, "child_happiness": 4, "how_feeling": 5, "age": 6, "food_budget": 7, "rank_foods": 8, "happy_raining": 9, "ice_cream": 10, "is_it_equal": 11, "two_fruits": 12}, "before_rule": false}], "num_questions": 13}, "question_groups": {}, "edsl_version": "0.1.41.dev3", "edsl_class_name": "Survey"}, "scenario": {"scenario_index": 0, "edsl_version": "0.1.41.dev3", "edsl_class_name": "Scenario"}, "model": {"model": "gpt-4o", "parameters": {"temperature": 0.5, "max_tokens": 1000, "top_p": 1, "frequency_penalty": 0, "presence_penalty": 0, "logprobs": false, "top_logprobs": 3}, "edsl_version": "0.1.41.dev3", "edsl_class_name": "LanguageModel"}, "iteration": 0, "exceptions": {"ice_cream": [{"exception": {"type": "QuestionAnswerValidationError", "message": "1 validation error for ChoiceResponse\nanswer\n Input should be 1, 2, 3, 4 or 5 [type=literal_error, input_value=\"As an AI, I don't have p... ice cream if you need!\", input_type=str]\n For further information visit https://errors.pydantic.dev/2.10/v/literal_error", "traceback": "Traceback (most recent call last):\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 77, in _base_validate\n return self.response_model(**data)\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/project/lib/python3.9/site-packages/pydantic/main.py\", line 214, in __init__\n validated_self = self.__pydantic_validator__.validate_python(data, self_instance=self)\npydantic_core._pydantic_core.ValidationError: 1 validation error for ChoiceResponse\nanswer\n Input should be 1, 2, 3, 4 or 5 [type=literal_error, input_value=\"As an AI, I don't have p... ice cream if you need!\", input_type=str]\n For further information visit https://errors.pydantic.dev/2.10/v/literal_error\n\nDuring handling of the above exception, another exception occurred:\n\nTraceback (most recent call last):\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/jobs/AnswerQuestionFunctionConstructor.py\", line 184, in attempt_answer\n raise response.exception_occurred\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/agents/Invigilator.py\", line 163, in _extract_edsl_result_entry_and_validate\n validated_edsl_dict = question_with_validators._validate_answer(edsl_dict)\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/QuestionBase.py\", line 110, in _validate_answer\n return self.response_validator.validate(answer, replacement_dict)\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 123, in validate\n return self._handle_exception(e, raw_edsl_answer_dict)\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 143, in _handle_exception\n raise self.original_exception\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 117, in validate\n pydantic_edsl_answer: BaseModel = self._base_validate(\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 79, in _base_validate\n raise QuestionAnswerValidationError(\nedsl.exceptions.questions.QuestionAnswerValidationError: 1 validation error for ChoiceResponse\nanswer\n Input should be 1, 2, 3, 4 or 5 [type=literal_error, input_value=\"As an AI, I don't have p... ice cream if you need!\", input_type=str]\n For further information visit https://errors.pydantic.dev/2.10/v/literal_error\n"}, "time": "2025-01-07T08:07:20.081404", "traceback": "Traceback (most recent call last):\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 77, in _base_validate\n return self.response_model(**data)\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/project/lib/python3.9/site-packages/pydantic/main.py\", line 214, in __init__\n validated_self = self.__pydantic_validator__.validate_python(data, self_instance=self)\npydantic_core._pydantic_core.ValidationError: 1 validation error for ChoiceResponse\nanswer\n Input should be 1, 2, 3, 4 or 5 [type=literal_error, input_value=\"As an AI, I don't have p... ice cream if you need!\", input_type=str]\n For further information visit https://errors.pydantic.dev/2.10/v/literal_error\n\nDuring handling of the above exception, another exception occurred:\n\nTraceback (most recent call last):\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/jobs/AnswerQuestionFunctionConstructor.py\", line 184, in attempt_answer\n raise response.exception_occurred\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/agents/Invigilator.py\", line 163, in _extract_edsl_result_entry_and_validate\n validated_edsl_dict = question_with_validators._validate_answer(edsl_dict)\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/QuestionBase.py\", line 110, in _validate_answer\n return self.response_validator.validate(answer, replacement_dict)\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 123, in validate\n return self._handle_exception(e, raw_edsl_answer_dict)\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 143, in _handle_exception\n raise self.original_exception\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 117, in validate\n pydantic_edsl_answer: BaseModel = self._base_validate(\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 79, in _base_validate\n raise QuestionAnswerValidationError(\nedsl.exceptions.questions.QuestionAnswerValidationError: 1 validation error for ChoiceResponse\nanswer\n Input should be 1, 2, 3, 4 or 5 [type=literal_error, input_value=\"As an AI, I don't have p... ice cream if you need!\", input_type=str]\n For further information visit https://errors.pydantic.dev/2.10/v/literal_error\n", "invigilator": {"agent": {"traits": {}, "edsl_version": "0.1.41.dev3", "edsl_class_name": "Agent"}, "question": {"question_name": "ice_cream", "question_text": "How much do you like ice cream?", "question_options": [1, 2, 3, 4, 5], "option_labels": {"1": "I hate it", "5": "I love it"}, "question_type": "linear_scale", "edsl_version": "0.1.41.dev3", "edsl_class_name": "QuestionBase"}, "scenario": {"edsl_version": "0.1.41.dev3", "edsl_class_name": "Scenario"}, "model": {"model": "gpt-4o", "parameters": {"temperature": 0.5, "max_tokens": 1000, "top_p": 1, "frequency_penalty": 0, "presence_penalty": 0, "logprobs": false, "top_logprobs": 3}, "edsl_version": "0.1.41.dev3", "edsl_class_name": "LanguageModel"}, "memory_plan": {"survey_question_names": ["never_eat", "extract_name", "how_are_you", "list_of_foods", "child_happiness", "how_feeling", "age", "food_budget", "rank_foods", "happy_raining", "ice_cream", "is_it_equal", "two_fruits"], "survey_question_texts": ["Which of the following foods would you eat if you had to?", "My name is Moby Dick. I have a PhD in astrology, but I'm actually a truck driver", "How are you?", "What are your favorite foods?", "How happy would you be with different numbers of children?", "How are you?", "You are a 45 year old man. How old are you in years?", "How would you allocate $100?", "Rank your favorite foods.", "I'm only happy when it rains.", "How much do you like ice cream?", "Is 5 + 5 equal to 11?", "Which of the following fruits do you prefer?"], "data": {}}, "current_answers": {"rank_foods_generated_tokens": "['Pizza', 'Pasta'] \nPizza and pasta are often favorites due to their versatility and comforting nature.", "rank_foods": ["Pizza", "Pasta"], "rank_foods_comment": "Pizza and pasta are often favorites due to their versatility and comforting nature.", "age_generated_tokens": "45", "age": 45, "how_feeling_generated_tokens": "Great", "how_feeling": "Great", "never_eat_generated_tokens": "[3, 4]", "never_eat": ["panda milk custard", "McDonalds"], "how_are_you_generated_tokens": "Thank you for asking! I'm here and ready to help you. How can I assist you today?", "how_are_you": "Thank you for asking! I'm here and ready to help you. How can I assist you today?", "extract_name_generated_tokens": "{'name': 'Moby Dick', 'profession': 'Truck Driver'}\n\nThe input provided the name \"Moby Dick\" and the profession as \"Truck Driver\", which is extracted and formatted as requested. The PhD in astrology is not considered the profession here as the input specifies the actual job as a truck driver.", "extract_name": {"name": "Moby Dick", "profession": "Truck Driver"}, "extract_name_comment": "The input provided the name \"Moby Dick\" and the profession as \"Truck Driver\", which is extracted and formatted as requested. The PhD in astrology is not considered the profession here as the input specifies the actual job as a truck driver.", "list_of_foods_generated_tokens": "[\"Pizza\", \"Sushi\", \"Chocolate\", \"Pasta\", \"Ice Cream\"] \nThese foods are popular and widely enjoyed for their flavors, versatility, and comforting qualities.", "list_of_foods": ["Pizza", "Sushi", "Chocolate", "Pasta", "Ice Cream"], "list_of_foods_comment": "These foods are popular and widely enjoyed for their flavors, versatility, and comforting qualities.", "child_happiness_generated_tokens": "{\"0\": 2, \"1\": 3, \"2\": 4, \"3\": 4}\n\nHaving no children might leave me neutral as it allows for freedom and flexibility, but having children can bring joy and fulfillment, hence the higher happiness ratings with increasing numbers of children.", "child_happiness": {"No children": 2, "1 child": 3, "2 children": 4, "3 or more children": 4}, "child_happiness_comment": "Having no children might leave me neutral as it allows for freedom and flexibility, but having children can bring joy and fulfillment, hence the higher happiness ratings with increasing numbers of children.", "is_it_equal_generated_tokens": "No\n\n5 + 5 equals 10, not 11.", "is_it_equal": "No", "is_it_equal_comment": "5 + 5 equals 10, not 11.", "two_fruits_generated_tokens": "```json\n{\n \"answer\": [0, 1],\n \"comment\": \"I prefer apples and bananas because they are both widely enjoyed fruits that are versatile and nutritious. Apples are crisp and refreshing, while bananas are sweet and convenient to eat on the go. Carrots are not a fruit, and durian, though unique, is often polarizing due to its strong odor.\"\n}\n```", "two_fruits": ["apple", "banana"], "two_fruits_comment": "```", "food_budget_generated_tokens": "[30,20,40,10] \nI allocated more to burgers as they tend to be more filling and versatile, followed by pizza and ice cream for variety and enjoyment. Salad received the least as a lighter option.", "food_budget": [{"Pizza": 30.0}, {"Ice Cream": 20.0}, {"Burgers": 40.0}, {"Salad": 10.0}], "food_budget_comment": "I allocated more to burgers as they tend to be more filling and versatile, followed by pizza and ice cream for variety and enjoyment. Salad received the least as a lighter option.", "happy_raining_generated_tokens": "Neutral\n\nThis statement could be interpreted in various ways, and without additional context, it's difficult to decisively agree or disagree.", "happy_raining": "Neutral", "happy_raining_comment": "This statement could be interpreted in various ways, and without additional context, it's difficult to decisively agree or disagree.", "ice_cream": null}, "iteration": 0, "additional_prompt_data": null, "survey": {"questions": [{"question_name": "never_eat", "question_text": "Which of the following foods would you eat if you had to?", "min_selections": 2, "max_selections": 5, "question_options": ["soggy meatpie", "rare snails", "mouldy bread", "panda milk custard", "McDonalds"], "include_comment": false, "use_code": true, "question_type": "checkbox", "edsl_version": "0.1.41.dev3", "edsl_class_name": "QuestionBase"}, {"question_name": "extract_name", "question_text": "My name is Moby Dick. I have a PhD in astrology, but I'm actually a truck driver", "answer_template": {"name": "John Doe", "profession": "Carpenter"}, "question_type": "extract", "edsl_version": "0.1.41.dev3", "edsl_class_name": "QuestionBase"}, {"question_name": "how_are_you", "question_text": "How are you?", "question_type": "free_text", "edsl_version": "0.1.41.dev3", "edsl_class_name": "QuestionBase"}, {"question_name": "list_of_foods", "question_text": "What are your favorite foods?", "question_type": "list", "edsl_version": "0.1.41.dev3", "edsl_class_name": "QuestionBase"}, {"question_name": "child_happiness", "question_text": "How happy would you be with different numbers of children?", "question_items": ["No children", "1 child", "2 children", "3 or more children"], "question_options": [1, 2, 3, 4, 5], "option_labels": {"1": "Very sad", "3": "Neutral", "5": "Extremely happy"}, "question_type": "matrix", "edsl_version": "0.1.41.dev3", "edsl_class_name": "QuestionBase"}, {"question_name": "how_feeling", "question_text": "How are you?", "question_options": ["Good", "Great", "OK", "Bad"], "include_comment": false, "question_type": "multiple_choice", "edsl_version": "0.1.41.dev3", "edsl_class_name": "QuestionBase"}, {"question_name": "age", "question_text": "You are a 45 year old man. How old are you in years?", "min_value": 0, "max_value": 86.7, "include_comment": false, "question_type": "numerical", "edsl_version": "0.1.41.dev3", "edsl_class_name": "QuestionBase"}, {"question_name": "food_budget", "question_text": "How would you allocate $100?", "question_options": ["Pizza", "Ice Cream", "Burgers", "Salad"], "budget_sum": 100, "question_type": "budget", "edsl_version": "0.1.41.dev3", "edsl_class_name": "QuestionBase"}, {"question_name": "rank_foods", "question_text": "Rank your favorite foods.", "question_options": ["Pizza", "Pasta", "Salad", "Soup"], "num_selections": 2, "question_type": "rank", "edsl_version": "0.1.41.dev3", "edsl_class_name": "QuestionBase"}, {"question_name": "happy_raining", "question_text": "I'm only happy when it rains.", "question_options": ["Strongly disagree", "Disagree", "Neutral", "Agree", "Strongly agree"], "question_type": "likert_five", "edsl_version": "0.1.41.dev3", "edsl_class_name": "QuestionBase"}, {"question_name": "ice_cream", "question_text": "How much do you like ice cream?", "question_options": [1, 2, 3, 4, 5], "option_labels": {"1": "I hate it", "5": "I love it"}, "question_type": "linear_scale", "edsl_version": "0.1.41.dev3", "edsl_class_name": "QuestionBase"}, {"question_name": "is_it_equal", "question_text": "Is 5 + 5 equal to 11?", "question_options": ["No", "Yes"], "question_type": "yes_no", "edsl_version": "0.1.41.dev3", "edsl_class_name": "QuestionBase"}, {"question_name": "two_fruits", "question_text": "Which of the following fruits do you prefer?", "min_selections": 2, "max_selections": 2, "question_options": ["apple", "banana", "carrot", "durian"], "use_code": true, "question_type": "top_k", "edsl_version": "0.1.41.dev3", "edsl_class_name": "QuestionBase"}], "memory_plan": {"survey_question_names": ["never_eat", "extract_name", "how_are_you", "list_of_foods", "child_happiness", "how_feeling", "age", "food_budget", "rank_foods", "happy_raining", "ice_cream", "is_it_equal", "two_fruits"], "survey_question_texts": ["Which of the following foods would you eat if you had to?", "My name is Moby Dick. I have a PhD in astrology, but I'm actually a truck driver", "How are you?", "What are your favorite foods?", "How happy would you be with different numbers of children?", "How are you?", "You are a 45 year old man. How old are you in years?", "How would you allocate $100?", "Rank your favorite foods.", "I'm only happy when it rains.", "How much do you like ice cream?", "Is 5 + 5 equal to 11?", "Which of the following fruits do you prefer?"], "data": {}}, "rule_collection": {"rules": [{"current_q": 0, "expression": "True", "next_q": 1, "priority": -1, "question_name_to_index": {"never_eat": 0}, "before_rule": false}, {"current_q": 1, "expression": "True", "next_q": 2, "priority": -1, "question_name_to_index": {"never_eat": 0, "extract_name": 1}, "before_rule": false}, {"current_q": 2, "expression": "True", "next_q": 3, "priority": -1, "question_name_to_index": {"never_eat": 0, "extract_name": 1, "how_are_you": 2}, "before_rule": false}, {"current_q": 3, "expression": "True", "next_q": 4, "priority": -1, "question_name_to_index": {"never_eat": 0, "extract_name": 1, "how_are_you": 2, "list_of_foods": 3}, "before_rule": false}, {"current_q": 4, "expression": "True", "next_q": 5, "priority": -1, "question_name_to_index": {"never_eat": 0, "extract_name": 1, "how_are_you": 2, "list_of_foods": 3, "child_happiness": 4}, "before_rule": false}, {"current_q": 5, "expression": "True", "next_q": 6, "priority": -1, "question_name_to_index": {"never_eat": 0, "extract_name": 1, "how_are_you": 2, "list_of_foods": 3, "child_happiness": 4, "how_feeling": 5}, "before_rule": false}, {"current_q": 6, "expression": "True", "next_q": 7, "priority": -1, "question_name_to_index": {"never_eat": 0, "extract_name": 1, "how_are_you": 2, "list_of_foods": 3, "child_happiness": 4, "how_feeling": 5, "age": 6}, "before_rule": false}, {"current_q": 7, "expression": "True", "next_q": 8, "priority": -1, "question_name_to_index": {"never_eat": 0, "extract_name": 1, "how_are_you": 2, "list_of_foods": 3, "child_happiness": 4, "how_feeling": 5, "age": 6, "food_budget": 7}, "before_rule": false}, {"current_q": 8, "expression": "True", "next_q": 9, "priority": -1, "question_name_to_index": {"never_eat": 0, "extract_name": 1, "how_are_you": 2, "list_of_foods": 3, "child_happiness": 4, "how_feeling": 5, "age": 6, "food_budget": 7, "rank_foods": 8}, "before_rule": false}, {"current_q": 9, "expression": "True", "next_q": 10, "priority": -1, "question_name_to_index": {"never_eat": 0, "extract_name": 1, "how_are_you": 2, "list_of_foods": 3, "child_happiness": 4, "how_feeling": 5, "age": 6, "food_budget": 7, "rank_foods": 8, "happy_raining": 9}, "before_rule": false}, {"current_q": 10, "expression": "True", "next_q": 11, "priority": -1, "question_name_to_index": {"never_eat": 0, "extract_name": 1, "how_are_you": 2, "list_of_foods": 3, "child_happiness": 4, "how_feeling": 5, "age": 6, "food_budget": 7, "rank_foods": 8, "happy_raining": 9, "ice_cream": 10}, "before_rule": false}, {"current_q": 11, "expression": "True", "next_q": 12, "priority": -1, "question_name_to_index": {"never_eat": 0, "extract_name": 1, "how_are_you": 2, "list_of_foods": 3, "child_happiness": 4, "how_feeling": 5, "age": 6, "food_budget": 7, "rank_foods": 8, "happy_raining": 9, "ice_cream": 10, "is_it_equal": 11}, "before_rule": false}, {"current_q": 12, "expression": "True", "next_q": 13, "priority": -1, "question_name_to_index": {"never_eat": 0, "extract_name": 1, "how_are_you": 2, "list_of_foods": 3, "child_happiness": 4, "how_feeling": 5, "age": 6, "food_budget": 7, "rank_foods": 8, "happy_raining": 9, "ice_cream": 10, "is_it_equal": 11, "two_fruits": 12}, "before_rule": false}], "num_questions": 13}, "question_groups": {}, "edsl_version": "0.1.41.dev3", "edsl_class_name": "Survey"}}}]}, "indices": {"agent": 0, "model": 0, "scenario": 0}}], "include_traceback": false, "edsl_version": "0.1.41.dev3", "edsl_class_name": "TaskHistory"}}}, {"class_name": "Results", "dict": {"data": [{"agent": {"traits": {}}, "scenario": {"text": "Tune in as I deliver the keynote address at the U.S. Holocaust Memorial Museum\u2019s Annual Days of Remembrance ceremony in Washington, D.C.", "q_extract_content": "\n \"The Simpsons\" is an iconic American animated sitcom created by Matt Groening that debuted in 1989 on the Fox network. \n The show is set in the fictional town of Springfield and centers on the Simpsons family, consisting of the bumbling but well-intentioned father Homer, the caring and patient mother Marge, and their three children: mischievous Bart, intelligent Lisa, and baby Maggie. \n Renowned for its satirical take on the typical American family and society, the series delves into themes of politics, religion, and pop culture with a distinct blend of humor and wit. \n Its longevity, marked by over thirty seasons, makes it one of the longest-running television series in history, influencing many other sitcoms and becoming deeply ingrained in popular culture.\n ", "scenario_index": 0}, "model": {"model": "gpt-4o", "parameters": {"temperature": 0.5, "max_tokens": 1000, "top_p": 1, "frequency_penalty": 0, "presence_penalty": 0, "logprobs": false, "top_logprobs": 3}}, "iteration": 0, "answer": {"q_extract": null, "concepts": ["Keynote address", "U.S. Holocaust Memorial Museum", "Annual Days of Remembrance", "Washington, D.C."], "sentiment": "Neutral"}, "prompt": {"q_extract_user_prompt": {"text": "Review the following text: \n \"The Simpsons\" is an iconic American animated sitcom created by Matt Groening that debuted in 1989 on the Fox network. \n The show is set in the fictional town of Springfield and centers on the Simpsons family, consisting of the bumbling but well-intentioned father Homer, the caring and patient mother Marge, and their three children: mischievous Bart, intelligent Lisa, and baby Maggie. \n Renowned for its satirical take on the typical American family and society, the series delves into themes of politics, religion, and pop culture with a distinct blend of humor and wit. \n Its longevity, marked by over thirty seasons, makes it one of the longest-running television series in history, influencing many other sitcoms and becoming deeply ingrained in popular culture.\n An ANSWER should be formatted like this: \n\n{'main_characters_list': ['name', 'name'], 'location': 'location', 'genre': 'genre'}\n\nIt should have the same keys but values extracted from the input.\nIf the value of a key is not present in the input, fill with \"null\".\nPut any comments in the next line after the answer.", "class_name": "Prompt"}, "q_extract_system_prompt": {"text": "", "class_name": "Prompt"}, "concepts_user_prompt": {"text": "Identify the key concepts in the following text: Tune in as I deliver the keynote address at the U.S. Holocaust Memorial Museum\u2019s Annual Days of Remembrance ceremony in Washington, D.C.\n\n\nThe list must not contain more than 4 items.\n\nReturn your answers on one line, in a comma-separated list of your responses, with square brackets and each answer in quotes E.g., [\"A\", \"B\", \"C\"]\n\nAfter the answers, you can put a comment explaining your choice on the next line.", "class_name": "Prompt"}, "concepts_system_prompt": {"text": "", "class_name": "Prompt"}, "sentiment_user_prompt": {"text": "\nIdentify the sentiment of this text: Tune in as I deliver the keynote address at the U.S. Holocaust Memorial Museum\u2019s Annual Days of Remembrance ceremony in Washington, D.C.\n\n \nPositive\n \nNeutral\n \nNegative\n \n\nOnly 1 option may be selected.\n\nRespond only with a string corresponding to one of the options.\n\n\nAfter the answer, you can put a comment explaining why you chose that option on the next line.", "class_name": "Prompt"}, "sentiment_system_prompt": {"text": "", "class_name": "Prompt"}}, "raw_model_response": {"q_extract_raw_model_response": null, "q_extract_cost": null, "q_extract_one_usd_buys": "NA", "concepts_raw_model_response": {"id": "chatcmpl-AmyvPL4Qw54XivIdCHvwkbqzPCpDU", "choices": [{"finish_reason": "stop", "index": 0, "logprobs": null, "message": {"content": "[\"Keynote address\", \"U.S. Holocaust Memorial Museum\", \"Annual Days of Remembrance\", \"Washington, D.C.\"] \nThe key concepts include the event (\"Annual Days of Remembrance\"), the location (\"Washington, D.C.\"), the institution hosting the event (\"U.S. Holocaust Memorial Museum\"), and the type of speech being delivered (\"Keynote address\").", "refusal": null, "role": "assistant", "audio": null, "function_call": null, "tool_calls": null}}], "created": 1736237303, "model": "gpt-4o-2024-08-06", "object": "chat.completion", "service_tier": null, "system_fingerprint": "fp_5f20662549", "usage": {"completion_tokens": 76, "prompt_tokens": 109, "total_tokens": 185, "completion_tokens_details": {"accepted_prediction_tokens": 0, "audio_tokens": 0, "reasoning_tokens": 0, "rejected_prediction_tokens": 0}, "prompt_tokens_details": {"audio_tokens": 0, "cached_tokens": 0}}}, "concepts_cost": 0.0010325, "concepts_one_usd_buys": 968.5230024213075, "sentiment_raw_model_response": {"id": "chatcmpl-AmyvDj7dqajPjaHsQMDtfqcwVQIii", "choices": [{"finish_reason": "stop", "index": 0, "logprobs": null, "message": {"content": "Neutral\n\nThe text is a straightforward announcement about an event, without any emotive language or sentiment-inducing words.", "refusal": null, "role": "assistant", "audio": null, "function_call": null, "tool_calls": null}}], "created": 1736237291, "model": "gpt-4o-2024-08-06", "object": "chat.completion", "service_tier": null, "system_fingerprint": "fp_5f20662549", "usage": {"completion_tokens": 24, "prompt_tokens": 91, "total_tokens": 115, "completion_tokens_details": {"accepted_prediction_tokens": 0, "audio_tokens": 0, "reasoning_tokens": 0, "rejected_prediction_tokens": 0}, "prompt_tokens_details": {"audio_tokens": 0, "cached_tokens": 0}}}, "sentiment_cost": 0.00046750000000000003, "sentiment_one_usd_buys": 2139.03743315508}, "question_to_attributes": null, "generated_tokens": {"q_extract_generated_tokens": null, "concepts_generated_tokens": "[\"Keynote address\", \"U.S. Holocaust Memorial Museum\", \"Annual Days of Remembrance\", \"Washington, D.C.\"] \nThe key concepts include the event (\"Annual Days of Remembrance\"), the location (\"Washington, D.C.\"), the institution hosting the event (\"U.S. Holocaust Memorial Museum\"), and the type of speech being delivered (\"Keynote address\").", "sentiment_generated_tokens": "Neutral\n\nThe text is a straightforward announcement about an event, without any emotive language or sentiment-inducing words."}, "comments_dict": {"q_extract_comment": "Question answer validation failed.", "concepts_comment": "The key concepts include the event (\"Annual Days of Remembrance\"), the location (\"Washington, D.C.\"), the institution hosting the event (\"U.S. Holocaust Memorial Museum\"), and the type of speech being delivered (\"Keynote address\").", "sentiment_comment": "The text is a straightforward announcement about an event, without any emotive language or sentiment-inducing words."}, "cache_used_dict": {"q_extract": null, "concepts": false, "sentiment": false}}, {"agent": {"traits": {}}, "scenario": {"text": "We\u2019re a nation of immigrants. A nation of dreamers. And as Cinco de Mayo represents, a nation of freedom.", "q_extract_content": "\n \"The Simpsons\" is an iconic American animated sitcom created by Matt Groening that debuted in 1989 on the Fox network. \n The show is set in the fictional town of Springfield and centers on the Simpsons family, consisting of the bumbling but well-intentioned father Homer, the caring and patient mother Marge, and their three children: mischievous Bart, intelligent Lisa, and baby Maggie. \n Renowned for its satirical take on the typical American family and society, the series delves into themes of politics, religion, and pop culture with a distinct blend of humor and wit. \n Its longevity, marked by over thirty seasons, makes it one of the longest-running television series in history, influencing many other sitcoms and becoming deeply ingrained in popular culture.\n ", "scenario_index": 1}, "model": {"model": "gpt-4o", "parameters": {"temperature": 0.5, "max_tokens": 1000, "top_p": 1, "frequency_penalty": 0, "presence_penalty": 0, "logprobs": false, "top_logprobs": 3}}, "iteration": 0, "answer": {"q_extract": null, "concepts": ["Immigrants", "Dreamers", "Freedom", "Cinco de Mayo"], "sentiment": "Positive"}, "prompt": {"q_extract_user_prompt": {"text": "Review the following text: \n \"The Simpsons\" is an iconic American animated sitcom created by Matt Groening that debuted in 1989 on the Fox network. \n The show is set in the fictional town of Springfield and centers on the Simpsons family, consisting of the bumbling but well-intentioned father Homer, the caring and patient mother Marge, and their three children: mischievous Bart, intelligent Lisa, and baby Maggie. \n Renowned for its satirical take on the typical American family and society, the series delves into themes of politics, religion, and pop culture with a distinct blend of humor and wit. \n Its longevity, marked by over thirty seasons, makes it one of the longest-running television series in history, influencing many other sitcoms and becoming deeply ingrained in popular culture.\n An ANSWER should be formatted like this: \n\n{'main_characters_list': ['name', 'name'], 'location': 'location', 'genre': 'genre'}\n\nIt should have the same keys but values extracted from the input.\nIf the value of a key is not present in the input, fill with \"null\".\nPut any comments in the next line after the answer.", "class_name": "Prompt"}, "q_extract_system_prompt": {"text": "", "class_name": "Prompt"}, "concepts_user_prompt": {"text": "Identify the key concepts in the following text: We\u2019re a nation of immigrants. A nation of dreamers. And as Cinco de Mayo represents, a nation of freedom.\n\n\nThe list must not contain more than 4 items.\n\nReturn your answers on one line, in a comma-separated list of your responses, with square brackets and each answer in quotes E.g., [\"A\", \"B\", \"C\"]\n\nAfter the answers, you can put a comment explaining your choice on the next line.", "class_name": "Prompt"}, "concepts_system_prompt": {"text": "", "class_name": "Prompt"}, "sentiment_user_prompt": {"text": "\nIdentify the sentiment of this text: We\u2019re a nation of immigrants. A nation of dreamers. And as Cinco de Mayo represents, a nation of freedom.\n\n \nPositive\n \nNeutral\n \nNegative\n \n\nOnly 1 option may be selected.\n\nRespond only with a string corresponding to one of the options.\n\n\nAfter the answer, you can put a comment explaining why you chose that option on the next line.", "class_name": "Prompt"}, "sentiment_system_prompt": {"text": "", "class_name": "Prompt"}}, "raw_model_response": {"q_extract_raw_model_response": null, "q_extract_cost": null, "q_extract_one_usd_buys": "NA", "concepts_raw_model_response": {"id": "chatcmpl-Amyvc0VpCOtr5YoOfYBAq5Zj7Gxnr", "choices": [{"finish_reason": "stop", "index": 0, "logprobs": null, "message": {"content": "[\"Immigrants\", \"Dreamers\", \"Freedom\", \"Cinco de Mayo\"] \nThese key concepts capture the essence of the text, focusing on the themes of immigration, aspirations, liberty, and the cultural significance of Cinco de Mayo.", "refusal": null, "role": "assistant", "audio": null, "function_call": null, "tool_calls": null}}], "created": 1736237316, "model": "gpt-4o-2024-08-06", "object": "chat.completion", "service_tier": null, "system_fingerprint": "fp_d28bcae782", "usage": {"completion_tokens": 50, "prompt_tokens": 105, "total_tokens": 155, "completion_tokens_details": {"accepted_prediction_tokens": 0, "audio_tokens": 0, "reasoning_tokens": 0, "rejected_prediction_tokens": 0}, "prompt_tokens_details": {"audio_tokens": 0, "cached_tokens": 0}}}, "concepts_cost": 0.0007624999999999999, "concepts_one_usd_buys": 1311.4754098360656, "sentiment_raw_model_response": {"id": "chatcmpl-AmyvWgFCXz9B1W0iveenIvJGiBGeO", "choices": [{"finish_reason": "stop", "index": 0, "logprobs": null, "message": {"content": "Positive\n\nThe text expresses pride and positivity about being a nation of immigrants, dreamers, and freedom, which are all positive sentiments.", "refusal": null, "role": "assistant", "audio": null, "function_call": null, "tool_calls": null}}], "created": 1736237310, "model": "gpt-4o-2024-08-06", "object": "chat.completion", "service_tier": null, "system_fingerprint": "fp_e161c81bbd", "usage": {"completion_tokens": 28, "prompt_tokens": 87, "total_tokens": 115, "completion_tokens_details": {"accepted_prediction_tokens": 0, "audio_tokens": 0, "reasoning_tokens": 0, "rejected_prediction_tokens": 0}, "prompt_tokens_details": {"audio_tokens": 0, "cached_tokens": 0}}}, "sentiment_cost": 0.0004975, "sentiment_one_usd_buys": 2010.0502512562814}, "question_to_attributes": null, "generated_tokens": {"q_extract_generated_tokens": null, "concepts_generated_tokens": "[\"Immigrants\", \"Dreamers\", \"Freedom\", \"Cinco de Mayo\"] \nThese key concepts capture the essence of the text, focusing on the themes of immigration, aspirations, liberty, and the cultural significance of Cinco de Mayo.", "sentiment_generated_tokens": "Positive\n\nThe text expresses pride and positivity about being a nation of immigrants, dreamers, and freedom, which are all positive sentiments."}, "comments_dict": {"q_extract_comment": "Question answer validation failed.", "concepts_comment": "These key concepts capture the essence of the text, focusing on the themes of immigration, aspirations, liberty, and the cultural significance of Cinco de Mayo.", "sentiment_comment": "The text expresses pride and positivity about being a nation of immigrants, dreamers, and freedom, which are all positive sentiments."}, "cache_used_dict": {"q_extract": null, "concepts": false, "sentiment": false}}, {"agent": {"traits": {}}, "scenario": {"text": "Medicare is stronger and Social Security remains strong. My economic plan has helped extend Medicare solvency by a decade. And I am committed to extending Social Security solvency by making the rich pay their fair share.", "q_extract_content": "\n \"The Simpsons\" is an iconic American animated sitcom created by Matt Groening that debuted in 1989 on the Fox network. \n The show is set in the fictional town of Springfield and centers on the Simpsons family, consisting of the bumbling but well-intentioned father Homer, the caring and patient mother Marge, and their three children: mischievous Bart, intelligent Lisa, and baby Maggie. \n Renowned for its satirical take on the typical American family and society, the series delves into themes of politics, religion, and pop culture with a distinct blend of humor and wit. \n Its longevity, marked by over thirty seasons, makes it one of the longest-running television series in history, influencing many other sitcoms and becoming deeply ingrained in popular culture.\n ", "scenario_index": 2}, "model": {"model": "gpt-4o", "parameters": {"temperature": 0.5, "max_tokens": 1000, "top_p": 1, "frequency_penalty": 0, "presence_penalty": 0, "logprobs": false, "top_logprobs": 3}}, "iteration": 0, "answer": {"q_extract": null, "concepts": ["Medicare solvency", "Social Security solvency", "economic plan", "fair share taxation"], "sentiment": "Positive"}, "prompt": {"q_extract_user_prompt": {"text": "Review the following text: \n \"The Simpsons\" is an iconic American animated sitcom created by Matt Groening that debuted in 1989 on the Fox network. \n The show is set in the fictional town of Springfield and centers on the Simpsons family, consisting of the bumbling but well-intentioned father Homer, the caring and patient mother Marge, and their three children: mischievous Bart, intelligent Lisa, and baby Maggie. \n Renowned for its satirical take on the typical American family and society, the series delves into themes of politics, religion, and pop culture with a distinct blend of humor and wit. \n Its longevity, marked by over thirty seasons, makes it one of the longest-running television series in history, influencing many other sitcoms and becoming deeply ingrained in popular culture.\n An ANSWER should be formatted like this: \n\n{'main_characters_list': ['name', 'name'], 'location': 'location', 'genre': 'genre'}\n\nIt should have the same keys but values extracted from the input.\nIf the value of a key is not present in the input, fill with \"null\".\nPut any comments in the next line after the answer.", "class_name": "Prompt"}, "q_extract_system_prompt": {"text": "", "class_name": "Prompt"}, "concepts_user_prompt": {"text": "Identify the key concepts in the following text: Medicare is stronger and Social Security remains strong. My economic plan has helped extend Medicare solvency by a decade. And I am committed to extending Social Security solvency by making the rich pay their fair share.\n\n\nThe list must not contain more than 4 items.\n\nReturn your answers on one line, in a comma-separated list of your responses, with square brackets and each answer in quotes E.g., [\"A\", \"B\", \"C\"]\n\nAfter the answers, you can put a comment explaining your choice on the next line.", "class_name": "Prompt"}, "concepts_system_prompt": {"text": "", "class_name": "Prompt"}, "sentiment_user_prompt": {"text": "\nIdentify the sentiment of this text: Medicare is stronger and Social Security remains strong. My economic plan has helped extend Medicare solvency by a decade. And I am committed to extending Social Security solvency by making the rich pay their fair share.\n\n \nPositive\n \nNeutral\n \nNegative\n \n\nOnly 1 option may be selected.\n\nRespond only with a string corresponding to one of the options.\n\n\nAfter the answer, you can put a comment explaining why you chose that option on the next line.", "class_name": "Prompt"}, "sentiment_system_prompt": {"text": "", "class_name": "Prompt"}}, "raw_model_response": {"q_extract_raw_model_response": null, "q_extract_cost": null, "q_extract_one_usd_buys": "NA", "concepts_raw_model_response": {"id": "chatcmpl-Amyv8LA6dGptgFdAp5uPBlc7nwgP9", "choices": [{"finish_reason": "stop", "index": 0, "logprobs": null, "message": {"content": "[\"Medicare solvency\", \"Social Security solvency\", \"economic plan\", \"fair share taxation\"] \nThese key concepts capture the focus on the financial health and sustainability of Medicare and Social Security, the role of an economic plan in achieving this, and the approach of taxing the wealthy to support these programs.", "refusal": null, "role": "assistant", "audio": null, "function_call": null, "tool_calls": null}}], "created": 1736237286, "model": "gpt-4o-2024-08-06", "object": "chat.completion", "service_tier": null, "system_fingerprint": "fp_5f20662549", "usage": {"completion_tokens": 63, "prompt_tokens": 121, "total_tokens": 184, "completion_tokens_details": {"accepted_prediction_tokens": 0, "audio_tokens": 0, "reasoning_tokens": 0, "rejected_prediction_tokens": 0}, "prompt_tokens_details": {"audio_tokens": 0, "cached_tokens": 0}}}, "concepts_cost": 0.0009325, "concepts_one_usd_buys": 1072.3860589812332, "sentiment_raw_model_response": {"id": "chatcmpl-Amyv1bw6EkQ45Kb8z6FxOtSk9CdtI", "choices": [{"finish_reason": "stop", "index": 0, "logprobs": null, "message": {"content": "Positive\n\nThe text expresses a positive outlook on Medicare and Social Security, highlighting achievements and commitments to strengthen these programs.", "refusal": null, "role": "assistant", "audio": null, "function_call": null, "tool_calls": null}}], "created": 1736237279, "model": "gpt-4o-2024-08-06", "object": "chat.completion", "service_tier": null, "system_fingerprint": "fp_5f20662549", "usage": {"completion_tokens": 24, "prompt_tokens": 103, "total_tokens": 127, "completion_tokens_details": {"accepted_prediction_tokens": 0, "audio_tokens": 0, "reasoning_tokens": 0, "rejected_prediction_tokens": 0}, "prompt_tokens_details": {"audio_tokens": 0, "cached_tokens": 0}}}, "sentiment_cost": 0.0004975, "sentiment_one_usd_buys": 2010.0502512562814}, "question_to_attributes": null, "generated_tokens": {"q_extract_generated_tokens": null, "concepts_generated_tokens": "[\"Medicare solvency\", \"Social Security solvency\", \"economic plan\", \"fair share taxation\"] \nThese key concepts capture the focus on the financial health and sustainability of Medicare and Social Security, the role of an economic plan in achieving this, and the approach of taxing the wealthy to support these programs.", "sentiment_generated_tokens": "Positive\n\nThe text expresses a positive outlook on Medicare and Social Security, highlighting achievements and commitments to strengthen these programs."}, "comments_dict": {"q_extract_comment": "Question answer validation failed.", "concepts_comment": "These key concepts capture the focus on the financial health and sustainability of Medicare and Social Security, the role of an economic plan in achieving this, and the approach of taxing the wealthy to support these programs.", "sentiment_comment": "The text expresses a positive outlook on Medicare and Social Security, highlighting achievements and commitments to strengthen these programs."}, "cache_used_dict": {"q_extract": null, "concepts": false, "sentiment": false}}], "survey": {"questions": [{"question_name": "q_extract", "question_text": "Review the following text: {{ q_extract_content }}", "answer_template": {"main_characters_list": ["name", "name"], "location": "location", "genre": "genre"}, "question_type": "extract"}, {"question_name": "concepts", "question_text": "Identify the key concepts in the following text: {{ text }}", "max_list_items": 4, "question_type": "list"}, {"question_name": "sentiment", "question_text": "Identify the sentiment of this text: {{ text }}", "question_options": ["Positive", "Neutral", "Negative"], "question_type": "multiple_choice"}], "memory_plan": {"survey_question_names": ["q_extract", "concepts", "sentiment"], "survey_question_texts": ["Review the following text: {{ q_extract_content }}", "Identify the key concepts in the following text: {{ text }}", "Identify the sentiment of this text: {{ text }}"], "data": {}}, "rule_collection": {"rules": [{"current_q": 0, "expression": "True", "next_q": 1, "priority": -1, "question_name_to_index": {"q_extract": 0}, "before_rule": false}, {"current_q": 1, "expression": "True", "next_q": 2, "priority": -1, "question_name_to_index": {"q_extract": 0, "concepts": 1}, "before_rule": false}, {"current_q": 2, "expression": "True", "next_q": 3, "priority": -1, "question_name_to_index": {"q_extract": 0, "concepts": 1, "sentiment": 2}, "before_rule": false}], "num_questions": 3}, "question_groups": {}}, "created_columns": [], "task_history": {"interviews": [{"agent": {"traits": {}, "edsl_version": "0.1.41.dev3", "edsl_class_name": "Agent"}, "survey": {"questions": [{"question_name": "q_extract", "question_text": "Review the following text: {{ q_extract_content }}", "answer_template": {"main_characters_list": ["name", "name"], "location": "location", "genre": "genre"}, "question_type": "extract", "edsl_version": "0.1.41.dev3", "edsl_class_name": "QuestionBase"}, {"question_name": "concepts", "question_text": "Identify the key concepts in the following text: {{ text }}", "max_list_items": 4, "question_type": "list", "edsl_version": "0.1.41.dev3", "edsl_class_name": "QuestionBase"}, {"question_name": "sentiment", "question_text": "Identify the sentiment of this text: {{ text }}", "question_options": ["Positive", "Neutral", "Negative"], "question_type": "multiple_choice", "edsl_version": "0.1.41.dev3", "edsl_class_name": "QuestionBase"}], "memory_plan": {"survey_question_names": ["q_extract", "concepts", "sentiment"], "survey_question_texts": ["Review the following text: {{ q_extract_content }}", "Identify the key concepts in the following text: {{ text }}", "Identify the sentiment of this text: {{ text }}"], "data": {}}, "rule_collection": {"rules": [{"current_q": 0, "expression": "True", "next_q": 1, "priority": -1, "question_name_to_index": {"q_extract": 0}, "before_rule": false}, {"current_q": 1, "expression": "True", "next_q": 2, "priority": -1, "question_name_to_index": {"q_extract": 0, "concepts": 1}, "before_rule": false}, {"current_q": 2, "expression": "True", "next_q": 3, "priority": -1, "question_name_to_index": {"q_extract": 0, "concepts": 1, "sentiment": 2}, "before_rule": false}], "num_questions": 3}, "question_groups": {}, "edsl_version": "0.1.41.dev3", "edsl_class_name": "Survey"}, "scenario": {"text": "Tune in as I deliver the keynote address at the U.S. Holocaust Memorial Museum\u2019s Annual Days of Remembrance ceremony in Washington, D.C.", "q_extract_content": "\n \"The Simpsons\" is an iconic American animated sitcom created by Matt Groening that debuted in 1989 on the Fox network. \n The show is set in the fictional town of Springfield and centers on the Simpsons family, consisting of the bumbling but well-intentioned father Homer, the caring and patient mother Marge, and their three children: mischievous Bart, intelligent Lisa, and baby Maggie. \n Renowned for its satirical take on the typical American family and society, the series delves into themes of politics, religion, and pop culture with a distinct blend of humor and wit. \n Its longevity, marked by over thirty seasons, makes it one of the longest-running television series in history, influencing many other sitcoms and becoming deeply ingrained in popular culture.\n ", "scenario_index": 0, "edsl_version": "0.1.41.dev3", "edsl_class_name": "Scenario"}, "model": {"model": "gpt-4o", "parameters": {"temperature": 0.5, "max_tokens": 1000, "top_p": 1, "frequency_penalty": 0, "presence_penalty": 0, "logprobs": false, "top_logprobs": 3}, "edsl_version": "0.1.41.dev3", "edsl_class_name": "LanguageModel"}, "iteration": 0, "exceptions": {"q_extract": [{"exception": {"type": "QuestionAnswerValidationError", "message": "1 validation error for AnswerModel\nanswer.main_characters_list\n Input should be a valid string [type=string_type, input_value=['Homer', 'Marge', 'Bart', 'Lisa', 'Maggie'], input_type=list]\n For further information visit https://errors.pydantic.dev/2.10/v/string_type", "traceback": "Traceback (most recent call last):\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 77, in _base_validate\n return self.response_model(**data)\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/project/lib/python3.9/site-packages/pydantic/main.py\", line 214, in __init__\n validated_self = self.__pydantic_validator__.validate_python(data, self_instance=self)\npydantic_core._pydantic_core.ValidationError: 1 validation error for AnswerModel\nanswer\n Input should be a valid dictionary or instance of DynamicModel [type=model_type, input_value=None, input_type=NoneType]\n For further information visit https://errors.pydantic.dev/2.10/v/model_type\n\nDuring handling of the above exception, another exception occurred:\n\nTraceback (most recent call last):\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 117, in validate\n pydantic_edsl_answer: BaseModel = self._base_validate(\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 79, in _base_validate\n raise QuestionAnswerValidationError(\nedsl.exceptions.questions.QuestionAnswerValidationError: 1 validation error for AnswerModel\nanswer\n Input should be a valid dictionary or instance of DynamicModel [type=model_type, input_value=None, input_type=NoneType]\n For further information visit https://errors.pydantic.dev/2.10/v/model_type\n\nDuring handling of the above exception, another exception occurred:\n\nTraceback (most recent call last):\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/jobs/AnswerQuestionFunctionConstructor.py\", line 184, in attempt_answer\n raise response.exception_occurred\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/agents/Invigilator.py\", line 163, in _extract_edsl_result_entry_and_validate\n validated_edsl_dict = question_with_validators._validate_answer(edsl_dict)\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/QuestionBase.py\", line 110, in _validate_answer\n return self.response_validator.validate(answer, replacement_dict)\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 123, in validate\n return self._handle_exception(e, raw_edsl_answer_dict)\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 143, in _handle_exception\n raise self.original_exception\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 137, in _handle_exception\n return self.validate(fixed_data, fix=True) # early return if validates\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 123, in validate\n return self._handle_exception(e, raw_edsl_answer_dict)\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 143, in _handle_exception\n raise self.original_exception\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 117, in validate\n pydantic_edsl_answer: BaseModel = self._base_validate(\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 79, in _base_validate\n raise QuestionAnswerValidationError(\nedsl.exceptions.questions.QuestionAnswerValidationError: 1 validation error for AnswerModel\nanswer.main_characters_list\n Input should be a valid string [type=string_type, input_value=['Homer', 'Marge', 'Bart', 'Lisa', 'Maggie'], input_type=list]\n For further information visit https://errors.pydantic.dev/2.10/v/string_type\n"}, "time": "2025-01-07T08:08:43.471043", "traceback": "Traceback (most recent call last):\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 77, in _base_validate\n return self.response_model(**data)\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/project/lib/python3.9/site-packages/pydantic/main.py\", line 214, in __init__\n validated_self = self.__pydantic_validator__.validate_python(data, self_instance=self)\npydantic_core._pydantic_core.ValidationError: 1 validation error for AnswerModel\nanswer\n Input should be a valid dictionary or instance of DynamicModel [type=model_type, input_value=None, input_type=NoneType]\n For further information visit https://errors.pydantic.dev/2.10/v/model_type\n\nDuring handling of the above exception, another exception occurred:\n\nTraceback (most recent call last):\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 117, in validate\n pydantic_edsl_answer: BaseModel = self._base_validate(\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 79, in _base_validate\n raise QuestionAnswerValidationError(\nedsl.exceptions.questions.QuestionAnswerValidationError: 1 validation error for AnswerModel\nanswer\n Input should be a valid dictionary or instance of DynamicModel [type=model_type, input_value=None, input_type=NoneType]\n For further information visit https://errors.pydantic.dev/2.10/v/model_type\n\nDuring handling of the above exception, another exception occurred:\n\nTraceback (most recent call last):\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/jobs/AnswerQuestionFunctionConstructor.py\", line 184, in attempt_answer\n raise response.exception_occurred\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/agents/Invigilator.py\", line 163, in _extract_edsl_result_entry_and_validate\n validated_edsl_dict = question_with_validators._validate_answer(edsl_dict)\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/QuestionBase.py\", line 110, in _validate_answer\n return self.response_validator.validate(answer, replacement_dict)\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 123, in validate\n return self._handle_exception(e, raw_edsl_answer_dict)\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 143, in _handle_exception\n raise self.original_exception\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 137, in _handle_exception\n return self.validate(fixed_data, fix=True) # early return if validates\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 123, in validate\n return self._handle_exception(e, raw_edsl_answer_dict)\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 143, in _handle_exception\n raise self.original_exception\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 117, in validate\n pydantic_edsl_answer: BaseModel = self._base_validate(\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 79, in _base_validate\n raise QuestionAnswerValidationError(\nedsl.exceptions.questions.QuestionAnswerValidationError: 1 validation error for AnswerModel\nanswer.main_characters_list\n Input should be a valid string [type=string_type, input_value=['Homer', 'Marge', 'Bart', 'Lisa', 'Maggie'], input_type=list]\n For further information visit https://errors.pydantic.dev/2.10/v/string_type\n", "invigilator": {"agent": {"traits": {}, "edsl_version": "0.1.41.dev3", "edsl_class_name": "Agent"}, "question": {"question_name": "q_extract", "question_text": "Review the following text: {{ q_extract_content }}", "answer_template": {"main_characters_list": ["name", "name"], "location": "location", "genre": "genre"}, "question_type": "extract", "edsl_version": "0.1.41.dev3", "edsl_class_name": "QuestionBase"}, "scenario": {"text": "Tune in as I deliver the keynote address at the U.S. Holocaust Memorial Museum\u2019s Annual Days of Remembrance ceremony in Washington, D.C.", "q_extract_content": "\n \"The Simpsons\" is an iconic American animated sitcom created by Matt Groening that debuted in 1989 on the Fox network. \n The show is set in the fictional town of Springfield and centers on the Simpsons family, consisting of the bumbling but well-intentioned father Homer, the caring and patient mother Marge, and their three children: mischievous Bart, intelligent Lisa, and baby Maggie. \n Renowned for its satirical take on the typical American family and society, the series delves into themes of politics, religion, and pop culture with a distinct blend of humor and wit. \n Its longevity, marked by over thirty seasons, makes it one of the longest-running television series in history, influencing many other sitcoms and becoming deeply ingrained in popular culture.\n ", "scenario_index": 0, "edsl_version": "0.1.41.dev3", "edsl_class_name": "Scenario"}, "model": {"model": "gpt-4o", "parameters": {"temperature": 0.5, "max_tokens": 1000, "top_p": 1, "frequency_penalty": 0, "presence_penalty": 0, "logprobs": false, "top_logprobs": 3}, "edsl_version": "0.1.41.dev3", "edsl_class_name": "LanguageModel"}, "memory_plan": {"survey_question_names": ["q_extract", "concepts", "sentiment"], "survey_question_texts": ["Review the following text: {{ q_extract_content }}", "Identify the key concepts in the following text: {{ text }}", "Identify the sentiment of this text: {{ text }}"], "data": {}}, "current_answers": {"sentiment_generated_tokens": "Neutral\n\nThe text is a straightforward announcement about an event, without any emotive language or sentiment-inducing words.", "sentiment": "Neutral", "sentiment_comment": "The text is a straightforward announcement about an event, without any emotive language or sentiment-inducing words.", "concepts_generated_tokens": "[\"Keynote address\", \"U.S. Holocaust Memorial Museum\", \"Annual Days of Remembrance\", \"Washington, D.C.\"] \nThe key concepts include the event (\"Annual Days of Remembrance\"), the location (\"Washington, D.C.\"), the institution hosting the event (\"U.S. Holocaust Memorial Museum\"), and the type of speech being delivered (\"Keynote address\").", "concepts": ["Keynote address", "U.S. Holocaust Memorial Museum", "Annual Days of Remembrance", "Washington, D.C."], "concepts_comment": "The key concepts include the event (\"Annual Days of Remembrance\"), the location (\"Washington, D.C.\"), the institution hosting the event (\"U.S. Holocaust Memorial Museum\"), and the type of speech being delivered (\"Keynote address\").", "q_extract": null}, "iteration": 0, "additional_prompt_data": null, "survey": {"questions": [{"question_name": "q_extract", "question_text": "Review the following text: {{ q_extract_content }}", "answer_template": {"main_characters_list": ["name", "name"], "location": "location", "genre": "genre"}, "question_type": "extract", "edsl_version": "0.1.41.dev3", "edsl_class_name": "QuestionBase"}, {"question_name": "concepts", "question_text": "Identify the key concepts in the following text: {{ text }}", "max_list_items": 4, "question_type": "list", "edsl_version": "0.1.41.dev3", "edsl_class_name": "QuestionBase"}, {"question_name": "sentiment", "question_text": "Identify the sentiment of this text: {{ text }}", "question_options": ["Positive", "Neutral", "Negative"], "question_type": "multiple_choice", "edsl_version": "0.1.41.dev3", "edsl_class_name": "QuestionBase"}], "memory_plan": {"survey_question_names": ["q_extract", "concepts", "sentiment"], "survey_question_texts": ["Review the following text: {{ q_extract_content }}", "Identify the key concepts in the following text: {{ text }}", "Identify the sentiment of this text: {{ text }}"], "data": {}}, "rule_collection": {"rules": [{"current_q": 0, "expression": "True", "next_q": 1, "priority": -1, "question_name_to_index": {"q_extract": 0}, "before_rule": false}, {"current_q": 1, "expression": "True", "next_q": 2, "priority": -1, "question_name_to_index": {"q_extract": 0, "concepts": 1}, "before_rule": false}, {"current_q": 2, "expression": "True", "next_q": 3, "priority": -1, "question_name_to_index": {"q_extract": 0, "concepts": 1, "sentiment": 2}, "before_rule": false}], "num_questions": 3}, "question_groups": {}, "edsl_version": "0.1.41.dev3", "edsl_class_name": "Survey"}}}]}, "indices": {"agent": 0, "model": 0, "scenario": 0}}, {"agent": {"traits": {}, "edsl_version": "0.1.41.dev3", "edsl_class_name": "Agent"}, "survey": {"questions": [{"question_name": "q_extract", "question_text": "Review the following text: {{ q_extract_content }}", "answer_template": {"main_characters_list": ["name", "name"], "location": "location", "genre": "genre"}, "question_type": "extract", "edsl_version": "0.1.41.dev3", "edsl_class_name": "QuestionBase"}, {"question_name": "concepts", "question_text": "Identify the key concepts in the following text: {{ text }}", "max_list_items": 4, "question_type": "list", "edsl_version": "0.1.41.dev3", "edsl_class_name": "QuestionBase"}, {"question_name": "sentiment", "question_text": "Identify the sentiment of this text: {{ text }}", "question_options": ["Positive", "Neutral", "Negative"], "question_type": "multiple_choice", "edsl_version": "0.1.41.dev3", "edsl_class_name": "QuestionBase"}], "memory_plan": {"survey_question_names": ["q_extract", "concepts", "sentiment"], "survey_question_texts": ["Review the following text: {{ q_extract_content }}", "Identify the key concepts in the following text: {{ text }}", "Identify the sentiment of this text: {{ text }}"], "data": {}}, "rule_collection": {"rules": [{"current_q": 0, "expression": "True", "next_q": 1, "priority": -1, "question_name_to_index": {"q_extract": 0}, "before_rule": false}, {"current_q": 1, "expression": "True", "next_q": 2, "priority": -1, "question_name_to_index": {"q_extract": 0, "concepts": 1}, "before_rule": false}, {"current_q": 2, "expression": "True", "next_q": 3, "priority": -1, "question_name_to_index": {"q_extract": 0, "concepts": 1, "sentiment": 2}, "before_rule": false}], "num_questions": 3}, "question_groups": {}, "edsl_version": "0.1.41.dev3", "edsl_class_name": "Survey"}, "scenario": {"text": "We\u2019re a nation of immigrants. A nation of dreamers. And as Cinco de Mayo represents, a nation of freedom.", "q_extract_content": "\n \"The Simpsons\" is an iconic American animated sitcom created by Matt Groening that debuted in 1989 on the Fox network. \n The show is set in the fictional town of Springfield and centers on the Simpsons family, consisting of the bumbling but well-intentioned father Homer, the caring and patient mother Marge, and their three children: mischievous Bart, intelligent Lisa, and baby Maggie. \n Renowned for its satirical take on the typical American family and society, the series delves into themes of politics, religion, and pop culture with a distinct blend of humor and wit. \n Its longevity, marked by over thirty seasons, makes it one of the longest-running television series in history, influencing many other sitcoms and becoming deeply ingrained in popular culture.\n ", "scenario_index": 1, "edsl_version": "0.1.41.dev3", "edsl_class_name": "Scenario"}, "model": {"model": "gpt-4o", "parameters": {"temperature": 0.5, "max_tokens": 1000, "top_p": 1, "frequency_penalty": 0, "presence_penalty": 0, "logprobs": false, "top_logprobs": 3}, "edsl_version": "0.1.41.dev3", "edsl_class_name": "LanguageModel"}, "iteration": 0, "exceptions": {"q_extract": [{"exception": {"type": "QuestionAnswerValidationError", "message": "1 validation error for AnswerModel\nanswer.main_characters_list\n Input should be a valid string [type=string_type, input_value=['Homer', 'Marge', 'Bart', 'Lisa', 'Maggie'], input_type=list]\n For further information visit https://errors.pydantic.dev/2.10/v/string_type", "traceback": "Traceback (most recent call last):\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 77, in _base_validate\n return self.response_model(**data)\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/project/lib/python3.9/site-packages/pydantic/main.py\", line 214, in __init__\n validated_self = self.__pydantic_validator__.validate_python(data, self_instance=self)\npydantic_core._pydantic_core.ValidationError: 1 validation error for AnswerModel\nanswer\n Input should be a valid dictionary or instance of DynamicModel [type=model_type, input_value=None, input_type=NoneType]\n For further information visit https://errors.pydantic.dev/2.10/v/model_type\n\nDuring handling of the above exception, another exception occurred:\n\nTraceback (most recent call last):\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 117, in validate\n pydantic_edsl_answer: BaseModel = self._base_validate(\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 79, in _base_validate\n raise QuestionAnswerValidationError(\nedsl.exceptions.questions.QuestionAnswerValidationError: 1 validation error for AnswerModel\nanswer\n Input should be a valid dictionary or instance of DynamicModel [type=model_type, input_value=None, input_type=NoneType]\n For further information visit https://errors.pydantic.dev/2.10/v/model_type\n\nDuring handling of the above exception, another exception occurred:\n\nTraceback (most recent call last):\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/jobs/AnswerQuestionFunctionConstructor.py\", line 184, in attempt_answer\n raise response.exception_occurred\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/agents/Invigilator.py\", line 163, in _extract_edsl_result_entry_and_validate\n validated_edsl_dict = question_with_validators._validate_answer(edsl_dict)\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/QuestionBase.py\", line 110, in _validate_answer\n return self.response_validator.validate(answer, replacement_dict)\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 123, in validate\n return self._handle_exception(e, raw_edsl_answer_dict)\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 143, in _handle_exception\n raise self.original_exception\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 137, in _handle_exception\n return self.validate(fixed_data, fix=True) # early return if validates\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 123, in validate\n return self._handle_exception(e, raw_edsl_answer_dict)\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 143, in _handle_exception\n raise self.original_exception\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 117, in validate\n pydantic_edsl_answer: BaseModel = self._base_validate(\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 79, in _base_validate\n raise QuestionAnswerValidationError(\nedsl.exceptions.questions.QuestionAnswerValidationError: 1 validation error for AnswerModel\nanswer.main_characters_list\n Input should be a valid string [type=string_type, input_value=['Homer', 'Marge', 'Bart', 'Lisa', 'Maggie'], input_type=list]\n For further information visit https://errors.pydantic.dev/2.10/v/string_type\n"}, "time": "2025-01-07T08:07:55.402817", "traceback": "Traceback (most recent call last):\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 77, in _base_validate\n return self.response_model(**data)\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/project/lib/python3.9/site-packages/pydantic/main.py\", line 214, in __init__\n validated_self = self.__pydantic_validator__.validate_python(data, self_instance=self)\npydantic_core._pydantic_core.ValidationError: 1 validation error for AnswerModel\nanswer\n Input should be a valid dictionary or instance of DynamicModel [type=model_type, input_value=None, input_type=NoneType]\n For further information visit https://errors.pydantic.dev/2.10/v/model_type\n\nDuring handling of the above exception, another exception occurred:\n\nTraceback (most recent call last):\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 117, in validate\n pydantic_edsl_answer: BaseModel = self._base_validate(\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 79, in _base_validate\n raise QuestionAnswerValidationError(\nedsl.exceptions.questions.QuestionAnswerValidationError: 1 validation error for AnswerModel\nanswer\n Input should be a valid dictionary or instance of DynamicModel [type=model_type, input_value=None, input_type=NoneType]\n For further information visit https://errors.pydantic.dev/2.10/v/model_type\n\nDuring handling of the above exception, another exception occurred:\n\nTraceback (most recent call last):\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/jobs/AnswerQuestionFunctionConstructor.py\", line 184, in attempt_answer\n raise response.exception_occurred\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/agents/Invigilator.py\", line 163, in _extract_edsl_result_entry_and_validate\n validated_edsl_dict = question_with_validators._validate_answer(edsl_dict)\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/QuestionBase.py\", line 110, in _validate_answer\n return self.response_validator.validate(answer, replacement_dict)\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 123, in validate\n return self._handle_exception(e, raw_edsl_answer_dict)\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 143, in _handle_exception\n raise self.original_exception\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 137, in _handle_exception\n return self.validate(fixed_data, fix=True) # early return if validates\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 123, in validate\n return self._handle_exception(e, raw_edsl_answer_dict)\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 143, in _handle_exception\n raise self.original_exception\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 117, in validate\n pydantic_edsl_answer: BaseModel = self._base_validate(\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 79, in _base_validate\n raise QuestionAnswerValidationError(\nedsl.exceptions.questions.QuestionAnswerValidationError: 1 validation error for AnswerModel\nanswer.main_characters_list\n Input should be a valid string [type=string_type, input_value=['Homer', 'Marge', 'Bart', 'Lisa', 'Maggie'], input_type=list]\n For further information visit https://errors.pydantic.dev/2.10/v/string_type\n", "invigilator": {"agent": {"traits": {}, "edsl_version": "0.1.41.dev3", "edsl_class_name": "Agent"}, "question": {"question_name": "q_extract", "question_text": "Review the following text: {{ q_extract_content }}", "answer_template": {"main_characters_list": ["name", "name"], "location": "location", "genre": "genre"}, "question_type": "extract", "edsl_version": "0.1.41.dev3", "edsl_class_name": "QuestionBase"}, "scenario": {"text": "We\u2019re a nation of immigrants. A nation of dreamers. And as Cinco de Mayo represents, a nation of freedom.", "q_extract_content": "\n \"The Simpsons\" is an iconic American animated sitcom created by Matt Groening that debuted in 1989 on the Fox network. \n The show is set in the fictional town of Springfield and centers on the Simpsons family, consisting of the bumbling but well-intentioned father Homer, the caring and patient mother Marge, and their three children: mischievous Bart, intelligent Lisa, and baby Maggie. \n Renowned for its satirical take on the typical American family and society, the series delves into themes of politics, religion, and pop culture with a distinct blend of humor and wit. \n Its longevity, marked by over thirty seasons, makes it one of the longest-running television series in history, influencing many other sitcoms and becoming deeply ingrained in popular culture.\n ", "scenario_index": 1, "edsl_version": "0.1.41.dev3", "edsl_class_name": "Scenario"}, "model": {"model": "gpt-4o", "parameters": {"temperature": 0.5, "max_tokens": 1000, "top_p": 1, "frequency_penalty": 0, "presence_penalty": 0, "logprobs": false, "top_logprobs": 3}, "edsl_version": "0.1.41.dev3", "edsl_class_name": "LanguageModel"}, "memory_plan": {"survey_question_names": ["q_extract", "concepts", "sentiment"], "survey_question_texts": ["Review the following text: {{ q_extract_content }}", "Identify the key concepts in the following text: {{ text }}", "Identify the sentiment of this text: {{ text }}"], "data": {}}, "current_answers": {}, "iteration": 0, "additional_prompt_data": null, "survey": {"questions": [{"question_name": "q_extract", "question_text": "Review the following text: {{ q_extract_content }}", "answer_template": {"main_characters_list": ["name", "name"], "location": "location", "genre": "genre"}, "question_type": "extract", "edsl_version": "0.1.41.dev3", "edsl_class_name": "QuestionBase"}, {"question_name": "concepts", "question_text": "Identify the key concepts in the following text: {{ text }}", "max_list_items": 4, "question_type": "list", "edsl_version": "0.1.41.dev3", "edsl_class_name": "QuestionBase"}, {"question_name": "sentiment", "question_text": "Identify the sentiment of this text: {{ text }}", "question_options": ["Positive", "Neutral", "Negative"], "question_type": "multiple_choice", "edsl_version": "0.1.41.dev3", "edsl_class_name": "QuestionBase"}], "memory_plan": {"survey_question_names": ["q_extract", "concepts", "sentiment"], "survey_question_texts": ["Review the following text: {{ q_extract_content }}", "Identify the key concepts in the following text: {{ text }}", "Identify the sentiment of this text: {{ text }}"], "data": {}}, "rule_collection": {"rules": [{"current_q": 0, "expression": "True", "next_q": 1, "priority": -1, "question_name_to_index": {"q_extract": 0}, "before_rule": false}, {"current_q": 1, "expression": "True", "next_q": 2, "priority": -1, "question_name_to_index": {"q_extract": 0, "concepts": 1}, "before_rule": false}, {"current_q": 2, "expression": "True", "next_q": 3, "priority": -1, "question_name_to_index": {"q_extract": 0, "concepts": 1, "sentiment": 2}, "before_rule": false}], "num_questions": 3}, "question_groups": {}, "edsl_version": "0.1.41.dev3", "edsl_class_name": "Survey"}}}]}, "indices": {"agent": 0, "model": 0, "scenario": 1}}, {"agent": {"traits": {}, "edsl_version": "0.1.41.dev3", "edsl_class_name": "Agent"}, "survey": {"questions": [{"question_name": "q_extract", "question_text": "Review the following text: {{ q_extract_content }}", "answer_template": {"main_characters_list": ["name", "name"], "location": "location", "genre": "genre"}, "question_type": "extract", "edsl_version": "0.1.41.dev3", "edsl_class_name": "QuestionBase"}, {"question_name": "concepts", "question_text": "Identify the key concepts in the following text: {{ text }}", "max_list_items": 4, "question_type": "list", "edsl_version": "0.1.41.dev3", "edsl_class_name": "QuestionBase"}, {"question_name": "sentiment", "question_text": "Identify the sentiment of this text: {{ text }}", "question_options": ["Positive", "Neutral", "Negative"], "question_type": "multiple_choice", "edsl_version": "0.1.41.dev3", "edsl_class_name": "QuestionBase"}], "memory_plan": {"survey_question_names": ["q_extract", "concepts", "sentiment"], "survey_question_texts": ["Review the following text: {{ q_extract_content }}", "Identify the key concepts in the following text: {{ text }}", "Identify the sentiment of this text: {{ text }}"], "data": {}}, "rule_collection": {"rules": [{"current_q": 0, "expression": "True", "next_q": 1, "priority": -1, "question_name_to_index": {"q_extract": 0}, "before_rule": false}, {"current_q": 1, "expression": "True", "next_q": 2, "priority": -1, "question_name_to_index": {"q_extract": 0, "concepts": 1}, "before_rule": false}, {"current_q": 2, "expression": "True", "next_q": 3, "priority": -1, "question_name_to_index": {"q_extract": 0, "concepts": 1, "sentiment": 2}, "before_rule": false}], "num_questions": 3}, "question_groups": {}, "edsl_version": "0.1.41.dev3", "edsl_class_name": "Survey"}, "scenario": {"text": "Medicare is stronger and Social Security remains strong. My economic plan has helped extend Medicare solvency by a decade. And I am committed to extending Social Security solvency by making the rich pay their fair share.", "q_extract_content": "\n \"The Simpsons\" is an iconic American animated sitcom created by Matt Groening that debuted in 1989 on the Fox network. \n The show is set in the fictional town of Springfield and centers on the Simpsons family, consisting of the bumbling but well-intentioned father Homer, the caring and patient mother Marge, and their three children: mischievous Bart, intelligent Lisa, and baby Maggie. \n Renowned for its satirical take on the typical American family and society, the series delves into themes of politics, religion, and pop culture with a distinct blend of humor and wit. \n Its longevity, marked by over thirty seasons, makes it one of the longest-running television series in history, influencing many other sitcoms and becoming deeply ingrained in popular culture.\n ", "scenario_index": 2, "edsl_version": "0.1.41.dev3", "edsl_class_name": "Scenario"}, "model": {"model": "gpt-4o", "parameters": {"temperature": 0.5, "max_tokens": 1000, "top_p": 1, "frequency_penalty": 0, "presence_penalty": 0, "logprobs": false, "top_logprobs": 3}, "edsl_version": "0.1.41.dev3", "edsl_class_name": "LanguageModel"}, "iteration": 0, "exceptions": {"q_extract": [{"exception": {"type": "QuestionAnswerValidationError", "message": "1 validation error for AnswerModel\nanswer.main_characters_list\n Input should be a valid string [type=string_type, input_value=['Homer', 'Marge', 'Bart', 'Lisa', 'Maggie'], input_type=list]\n For further information visit https://errors.pydantic.dev/2.10/v/string_type", "traceback": "Traceback (most recent call last):\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 77, in _base_validate\n return self.response_model(**data)\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/project/lib/python3.9/site-packages/pydantic/main.py\", line 214, in __init__\n validated_self = self.__pydantic_validator__.validate_python(data, self_instance=self)\npydantic_core._pydantic_core.ValidationError: 1 validation error for AnswerModel\nanswer\n Input should be a valid dictionary or instance of DynamicModel [type=model_type, input_value=None, input_type=NoneType]\n For further information visit https://errors.pydantic.dev/2.10/v/model_type\n\nDuring handling of the above exception, another exception occurred:\n\nTraceback (most recent call last):\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 117, in validate\n pydantic_edsl_answer: BaseModel = self._base_validate(\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 79, in _base_validate\n raise QuestionAnswerValidationError(\nedsl.exceptions.questions.QuestionAnswerValidationError: 1 validation error for AnswerModel\nanswer\n Input should be a valid dictionary or instance of DynamicModel [type=model_type, input_value=None, input_type=NoneType]\n For further information visit https://errors.pydantic.dev/2.10/v/model_type\n\nDuring handling of the above exception, another exception occurred:\n\nTraceback (most recent call last):\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/jobs/AnswerQuestionFunctionConstructor.py\", line 184, in attempt_answer\n raise response.exception_occurred\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/agents/Invigilator.py\", line 163, in _extract_edsl_result_entry_and_validate\n validated_edsl_dict = question_with_validators._validate_answer(edsl_dict)\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/QuestionBase.py\", line 110, in _validate_answer\n return self.response_validator.validate(answer, replacement_dict)\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 123, in validate\n return self._handle_exception(e, raw_edsl_answer_dict)\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 143, in _handle_exception\n raise self.original_exception\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 137, in _handle_exception\n return self.validate(fixed_data, fix=True) # early return if validates\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 123, in validate\n return self._handle_exception(e, raw_edsl_answer_dict)\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 143, in _handle_exception\n raise self.original_exception\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 117, in validate\n pydantic_edsl_answer: BaseModel = self._base_validate(\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 79, in _base_validate\n raise QuestionAnswerValidationError(\nedsl.exceptions.questions.QuestionAnswerValidationError: 1 validation error for AnswerModel\nanswer.main_characters_list\n Input should be a valid string [type=string_type, input_value=['Homer', 'Marge', 'Bart', 'Lisa', 'Maggie'], input_type=list]\n For further information visit https://errors.pydantic.dev/2.10/v/string_type\n"}, "time": "2025-01-07T08:08:20.008471", "traceback": "Traceback (most recent call last):\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 77, in _base_validate\n return self.response_model(**data)\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/project/lib/python3.9/site-packages/pydantic/main.py\", line 214, in __init__\n validated_self = self.__pydantic_validator__.validate_python(data, self_instance=self)\npydantic_core._pydantic_core.ValidationError: 1 validation error for AnswerModel\nanswer\n Input should be a valid dictionary or instance of DynamicModel [type=model_type, input_value=None, input_type=NoneType]\n For further information visit https://errors.pydantic.dev/2.10/v/model_type\n\nDuring handling of the above exception, another exception occurred:\n\nTraceback (most recent call last):\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 117, in validate\n pydantic_edsl_answer: BaseModel = self._base_validate(\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 79, in _base_validate\n raise QuestionAnswerValidationError(\nedsl.exceptions.questions.QuestionAnswerValidationError: 1 validation error for AnswerModel\nanswer\n Input should be a valid dictionary or instance of DynamicModel [type=model_type, input_value=None, input_type=NoneType]\n For further information visit https://errors.pydantic.dev/2.10/v/model_type\n\nDuring handling of the above exception, another exception occurred:\n\nTraceback (most recent call last):\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/jobs/AnswerQuestionFunctionConstructor.py\", line 184, in attempt_answer\n raise response.exception_occurred\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/agents/Invigilator.py\", line 163, in _extract_edsl_result_entry_and_validate\n validated_edsl_dict = question_with_validators._validate_answer(edsl_dict)\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/QuestionBase.py\", line 110, in _validate_answer\n return self.response_validator.validate(answer, replacement_dict)\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 123, in validate\n return self._handle_exception(e, raw_edsl_answer_dict)\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 143, in _handle_exception\n raise self.original_exception\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 137, in _handle_exception\n return self.validate(fixed_data, fix=True) # early return if validates\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 123, in validate\n return self._handle_exception(e, raw_edsl_answer_dict)\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 143, in _handle_exception\n raise self.original_exception\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 117, in validate\n pydantic_edsl_answer: BaseModel = self._base_validate(\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 79, in _base_validate\n raise QuestionAnswerValidationError(\nedsl.exceptions.questions.QuestionAnswerValidationError: 1 validation error for AnswerModel\nanswer.main_characters_list\n Input should be a valid string [type=string_type, input_value=['Homer', 'Marge', 'Bart', 'Lisa', 'Maggie'], input_type=list]\n For further information visit https://errors.pydantic.dev/2.10/v/string_type\n", "invigilator": {"agent": {"traits": {}, "edsl_version": "0.1.41.dev3", "edsl_class_name": "Agent"}, "question": {"question_name": "q_extract", "question_text": "Review the following text: {{ q_extract_content }}", "answer_template": {"main_characters_list": ["name", "name"], "location": "location", "genre": "genre"}, "question_type": "extract", "edsl_version": "0.1.41.dev3", "edsl_class_name": "QuestionBase"}, "scenario": {"text": "Medicare is stronger and Social Security remains strong. My economic plan has helped extend Medicare solvency by a decade. And I am committed to extending Social Security solvency by making the rich pay their fair share.", "q_extract_content": "\n \"The Simpsons\" is an iconic American animated sitcom created by Matt Groening that debuted in 1989 on the Fox network. \n The show is set in the fictional town of Springfield and centers on the Simpsons family, consisting of the bumbling but well-intentioned father Homer, the caring and patient mother Marge, and their three children: mischievous Bart, intelligent Lisa, and baby Maggie. \n Renowned for its satirical take on the typical American family and society, the series delves into themes of politics, religion, and pop culture with a distinct blend of humor and wit. \n Its longevity, marked by over thirty seasons, makes it one of the longest-running television series in history, influencing many other sitcoms and becoming deeply ingrained in popular culture.\n ", "scenario_index": 2, "edsl_version": "0.1.41.dev3", "edsl_class_name": "Scenario"}, "model": {"model": "gpt-4o", "parameters": {"temperature": 0.5, "max_tokens": 1000, "top_p": 1, "frequency_penalty": 0, "presence_penalty": 0, "logprobs": false, "top_logprobs": 3}, "edsl_version": "0.1.41.dev3", "edsl_class_name": "LanguageModel"}, "memory_plan": {"survey_question_names": ["q_extract", "concepts", "sentiment"], "survey_question_texts": ["Review the following text: {{ q_extract_content }}", "Identify the key concepts in the following text: {{ text }}", "Identify the sentiment of this text: {{ text }}"], "data": {}}, "current_answers": {"sentiment_generated_tokens": "Positive\n\nThe text expresses a positive outlook on Medicare and Social Security, highlighting achievements and commitments to strengthen these programs.", "sentiment": "Positive", "sentiment_comment": "The text expresses a positive outlook on Medicare and Social Security, highlighting achievements and commitments to strengthen these programs.", "concepts_generated_tokens": "[\"Medicare solvency\", \"Social Security solvency\", \"economic plan\", \"fair share taxation\"] \nThese key concepts capture the focus on the financial health and sustainability of Medicare and Social Security, the role of an economic plan in achieving this, and the approach of taxing the wealthy to support these programs.", "concepts": ["Medicare solvency", "Social Security solvency", "economic plan", "fair share taxation"], "concepts_comment": "These key concepts capture the focus on the financial health and sustainability of Medicare and Social Security, the role of an economic plan in achieving this, and the approach of taxing the wealthy to support these programs.", "q_extract": null}, "iteration": 0, "additional_prompt_data": null, "survey": {"questions": [{"question_name": "q_extract", "question_text": "Review the following text: {{ q_extract_content }}", "answer_template": {"main_characters_list": ["name", "name"], "location": "location", "genre": "genre"}, "question_type": "extract", "edsl_version": "0.1.41.dev3", "edsl_class_name": "QuestionBase"}, {"question_name": "concepts", "question_text": "Identify the key concepts in the following text: {{ text }}", "max_list_items": 4, "question_type": "list", "edsl_version": "0.1.41.dev3", "edsl_class_name": "QuestionBase"}, {"question_name": "sentiment", "question_text": "Identify the sentiment of this text: {{ text }}", "question_options": ["Positive", "Neutral", "Negative"], "question_type": "multiple_choice", "edsl_version": "0.1.41.dev3", "edsl_class_name": "QuestionBase"}], "memory_plan": {"survey_question_names": ["q_extract", "concepts", "sentiment"], "survey_question_texts": ["Review the following text: {{ q_extract_content }}", "Identify the key concepts in the following text: {{ text }}", "Identify the sentiment of this text: {{ text }}"], "data": {}}, "rule_collection": {"rules": [{"current_q": 0, "expression": "True", "next_q": 1, "priority": -1, "question_name_to_index": {"q_extract": 0}, "before_rule": false}, {"current_q": 1, "expression": "True", "next_q": 2, "priority": -1, "question_name_to_index": {"q_extract": 0, "concepts": 1}, "before_rule": false}, {"current_q": 2, "expression": "True", "next_q": 3, "priority": -1, "question_name_to_index": {"q_extract": 0, "concepts": 1, "sentiment": 2}, "before_rule": false}], "num_questions": 3}, "question_groups": {}, "edsl_version": "0.1.41.dev3", "edsl_class_name": "Survey"}}}]}, "indices": {"agent": 0, "model": 0, "scenario": 2}}], "include_traceback": false, "edsl_version": "0.1.41.dev3", "edsl_class_name": "TaskHistory"}}}, {"class_name": "Results", "dict": {"data": [{"agent": {"traits": {}}, "scenario": {"scenario_index": 0}, "model": {"model": "gpt-4o", "parameters": {"temperature": 0.5, "max_tokens": 1000, "top_p": 1, "frequency_penalty": 0, "presence_penalty": 0, "logprobs": false, "top_logprobs": 3}}, "iteration": 0, "answer": {"color": "Blue", "day": null, "winter": null, "birds": null}, "prompt": {"color_user_prompt": {"text": "\nWhat is your favorite color?\n\n \nRed\n \nOrange\n \nYellow\n \nGreen\n \nBlue\n \nPurple\n \n\nOnly 1 option may be selected.\n\nRespond only with a string corresponding to one of the options.\n\n\nAfter the answer, you can put a comment explaining why you chose that option on the next line.", "class_name": "Prompt"}, "color_system_prompt": {"text": "", "class_name": "Prompt"}, "day_user_prompt": {"text": "\nWhat is your favorite day of the week?\n\n \nSun\n \nMon\n \nTue\n \nWed\n \nThu\n \nFri\n \nSat\n \n\nOnly 1 option may be selected.\n\nRespond only with a string corresponding to one of the options.\n\n\nAfter the answer, you can put a comment explaining why you chose that option on the next line.\n Before the question you are now answering, you already answered the following question(s):\n \tQuestion: What is your favorite color?\n\tAnswer: None", "class_name": "Prompt"}, "day_system_prompt": {"text": "", "class_name": "Prompt"}, "winter_user_prompt": {"text": "How much do you enjoy winter?\n\n0 : Hate it\n\n1 : \n\n2 : \n\n3 : \n\n4 : \n\n5 : Love it\n\nOnly 1 option may be selected.\n\nRespond only with the code corresponding to one of the options. E.g., \"1\" or \"5\" by itself.\n\nAfter the answer, you can put a comment explaining why you chose that option on the next line.\n Before the question you are now answering, you already answered the following question(s):\n \tQuestion: What is your favorite color?\n\tAnswer: None\n\n Prior questions and answers:\tQuestion: What is your favorite day of the week?\n\tAnswer: None", "class_name": "Prompt"}, "winter_system_prompt": {"text": "", "class_name": "Prompt"}, "birds_user_prompt": {"text": "Which birds do you like best?\n\n \n0: Parrot\n \n1: Osprey\n \n2: Falcon\n \n3: Eagle\n \n4: First Robin of Spring\n \n\n\n\n\nYou must select exactly 2 options.\n\n\nPlease respond with valid JSON, formatted like so:\n\n {\"answer\": [], \"comment\": \"\"}\n Before the question you are now answering, you already answered the following question(s):\n \tQuestion: What is your favorite day of the week?\n\tAnswer: None\n\n Prior questions and answers:\tQuestion: How much do you enjoy winter?\n\tAnswer: None\n\n Prior questions and answers:\tQuestion: What is your favorite color?\n\tAnswer: None", "class_name": "Prompt"}, "birds_system_prompt": {"text": "", "class_name": "Prompt"}}, "raw_model_response": {"color_raw_model_response": null, "color_cost": null, "color_one_usd_buys": "NA", "day_raw_model_response": null, "day_cost": null, "day_one_usd_buys": "NA", "winter_raw_model_response": null, "winter_cost": null, "winter_one_usd_buys": "NA", "birds_raw_model_response": null, "birds_cost": null, "birds_one_usd_buys": "NA"}, "question_to_attributes": null, "generated_tokens": {"color_generated_tokens": null, "day_generated_tokens": null, "winter_generated_tokens": null, "birds_generated_tokens": null}, "comments_dict": {"color_comment": "Task was cancelled.", "day_comment": "Task was cancelled.", "winter_comment": "Task was cancelled.", "birds_comment": "Task was cancelled."}, "cache_used_dict": {"color": null, "day": null, "winter": null, "birds": null}}], "survey": {"questions": [{"question_name": "color", "question_text": "What is your favorite color?", "question_options": ["Red", "Orange", "Yellow", "Green", "Blue", "Purple"], "question_type": "multiple_choice"}, {"question_name": "day", "question_text": "What is your favorite day of the week?", "question_options": ["Sun", "Mon", "Tue", "Wed", "Thu", "Fri", "Sat"], "question_type": "multiple_choice"}, {"question_name": "winter", "question_text": "How much do you enjoy winter?", "question_options": [0, 1, 2, 3, 4, 5], "option_labels": {"0": "Hate it", "5": "Love it"}, "question_type": "linear_scale"}, {"question_name": "birds", "question_text": "Which birds do you like best?", "min_selections": 2, "max_selections": 2, "question_options": ["Parrot", "Osprey", "Falcon", "Eagle", "First Robin of Spring"], "use_code": true, "question_type": "top_k"}], "memory_plan": {"survey_question_names": ["color", "day", "winter", "birds"], "survey_question_texts": ["What is your favorite color?", "What is your favorite day of the week?", "How much do you enjoy winter?", "Which birds do you like best?"], "data": {"day": {"prior_questions": ["color"]}, "winter": {"prior_questions": ["color", "day"]}, "birds": {"prior_questions": ["day", "winter", "color"]}}}, "rule_collection": {"rules": [{"current_q": 0, "expression": "True", "next_q": 1, "priority": -1, "question_name_to_index": {"color": 0}, "before_rule": false}, {"current_q": 1, "expression": "True", "next_q": 2, "priority": -1, "question_name_to_index": {"color": 0, "day": 1}, "before_rule": false}, {"current_q": 2, "expression": "True", "next_q": 3, "priority": -1, "question_name_to_index": {"color": 0, "day": 1, "winter": 2}, "before_rule": false}, {"current_q": 3, "expression": "True", "next_q": 4, "priority": -1, "question_name_to_index": {"color": 0, "day": 1, "winter": 2, "birds": 3}, "before_rule": false}, {"current_q": 3, "expression": "color == 'Blue'", "next_q": 4, "priority": 0, "question_name_to_index": 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"how_feeling_yesterday_cost": null, "how_feeling_yesterday_one_usd_buys": "NA"}, "question_to_attributes": null, "generated_tokens": {"how_feeling_generated_tokens": "Not Applicable", "how_feeling_yesterday_generated_tokens": "Not Applicable"}, "comments_dict": {"how_feeling_comment": "This is a real survey response from a human.", "how_feeling_yesterday_comment": "This is a real survey response from a human."}, "cache_used_dict": {"how_feeling": "Not Applicable", "how_feeling_yesterday": "Not Applicable"}}, {"agent": {"traits": {"status": "Joyful"}}, "scenario": {"period": "afternoon", "scenario_index": 1}, "model": {"model": "gpt-4o", "parameters": {"temperature": 0.5, "max_tokens": 1000, "top_p": 1, "frequency_penalty": 0, "presence_penalty": 0, "logprobs": false, "top_logprobs": 3}}, "iteration": 0, "answer": {"how_feeling": "Great", "how_feeling_yesterday": "Good"}, "prompt": {"how_feeling_user_prompt": {"text": "NA", "class_name": "Prompt"}, "how_feeling_system_prompt": {"text": "NA", "class_name": "Prompt"}, "how_feeling_yesterday_user_prompt": {"text": "NA", "class_name": "Prompt"}, "how_feeling_yesterday_system_prompt": {"text": "NA", "class_name": "Prompt"}}, "raw_model_response": {"how_feeling_raw_model_response": "Not Applicable", "how_feeling_cost": null, "how_feeling_one_usd_buys": "NA", "how_feeling_yesterday_raw_model_response": "Not Applicable", "how_feeling_yesterday_cost": null, "how_feeling_yesterday_one_usd_buys": "NA"}, "question_to_attributes": null, "generated_tokens": {"how_feeling_generated_tokens": "Not Applicable", "how_feeling_yesterday_generated_tokens": "Not Applicable"}, "comments_dict": {"how_feeling_comment": "This is a real survey response from a human.", "how_feeling_yesterday_comment": "This is a real survey response from a human."}, "cache_used_dict": {"how_feeling": "Not Applicable", "how_feeling_yesterday": "Not Applicable"}}, {"agent": {"traits": {"status": "Sad"}}, "scenario": {"period": "morning", "scenario_index": 0}, "model": {"model": "gpt-4o", "parameters": {"temperature": 0.5, "max_tokens": 1000, "top_p": 1, "frequency_penalty": 0, "presence_penalty": 0, "logprobs": false, "top_logprobs": 3}}, "iteration": 0, "answer": {"how_feeling": "Terrible", "how_feeling_yesterday": "OK"}, "prompt": {"how_feeling_user_prompt": {"text": "NA", "class_name": "Prompt"}, "how_feeling_system_prompt": {"text": "NA", "class_name": "Prompt"}, "how_feeling_yesterday_user_prompt": {"text": "NA", "class_name": "Prompt"}, "how_feeling_yesterday_system_prompt": {"text": "NA", "class_name": "Prompt"}}, "raw_model_response": {"how_feeling_raw_model_response": "Not Applicable", "how_feeling_cost": null, "how_feeling_one_usd_buys": "NA", "how_feeling_yesterday_raw_model_response": "Not Applicable", "how_feeling_yesterday_cost": null, "how_feeling_yesterday_one_usd_buys": "NA"}, "question_to_attributes": null, "generated_tokens": {"how_feeling_generated_tokens": "Not Applicable", "how_feeling_yesterday_generated_tokens": "Not Applicable"}, "comments_dict": {"how_feeling_comment": "This is a real survey response from a human.", "how_feeling_yesterday_comment": "This is a real survey response from a human."}, "cache_used_dict": {"how_feeling": "Not Applicable", "how_feeling_yesterday": "Not Applicable"}}, {"agent": {"traits": {"status": "Sad"}}, "scenario": {"period": "afternoon", "scenario_index": 1}, "model": {"model": "gpt-4o", "parameters": {"temperature": 0.5, "max_tokens": 1000, "top_p": 1, "frequency_penalty": 0, "presence_penalty": 0, "logprobs": false, "top_logprobs": 3}}, "iteration": 0, "answer": {"how_feeling": "OK", "how_feeling_yesterday": "Terrible"}, "prompt": {"how_feeling_user_prompt": {"text": "NA", "class_name": "Prompt"}, "how_feeling_system_prompt": {"text": "NA", "class_name": "Prompt"}, "how_feeling_yesterday_user_prompt": {"text": "NA", "class_name": "Prompt"}, "how_feeling_yesterday_system_prompt": {"text": "NA", "class_name": "Prompt"}}, "raw_model_response": {"how_feeling_raw_model_response": "Not Applicable", "how_feeling_cost": null, "how_feeling_one_usd_buys": "NA", "how_feeling_yesterday_raw_model_response": "Not Applicable", "how_feeling_yesterday_cost": null, "how_feeling_yesterday_one_usd_buys": "NA"}, "question_to_attributes": null, "generated_tokens": {"how_feeling_generated_tokens": "Not Applicable", "how_feeling_yesterday_generated_tokens": "Not Applicable"}, "comments_dict": {"how_feeling_comment": "This is a real survey response from a human.", "how_feeling_yesterday_comment": "This is a real survey response from a human."}, "cache_used_dict": {"how_feeling": "Not Applicable", "how_feeling_yesterday": "Not Applicable"}}], "survey": {"questions": [{"question_name": "how_feeling", "question_text": "How are you this {{ period }}?", "question_options": ["Good", "Great", "OK", "Terrible"], "question_type": "multiple_choice"}, {"question_name": "how_feeling_yesterday", "question_text": "How were you feeling yesterday {{ period }}?", "question_options": ["Good", "Great", "OK", "Terrible"], "question_type": "multiple_choice"}], "memory_plan": {"survey_question_names": ["how_feeling", "how_feeling_yesterday"], "survey_question_texts": ["How are you this {{ period }}?", "How were you feeling yesterday {{ period }}?"], "data": {}}, "rule_collection": {"rules": [{"current_q": 0, "expression": "True", "next_q": 1, "priority": -1, "question_name_to_index": {"how_feeling": 0}, "before_rule": false}, {"current_q": 1, "expression": "True", "next_q": 2, "priority": -1, "question_name_to_index": {"how_feeling": 0, "how_feeling_yesterday": 1}, "before_rule": false}], "num_questions": 2}, "question_groups": {}}, "created_columns": []}}, {"class_name": "ScenarioList", "dict": {"scenarios": [{"persona": "A reseacher studying whether LLMs can be used to generate surveys.", "edsl_version": "0.1.41.dev4", "edsl_class_name": "Scenario"}, {"persona": "A reseacher studying whether LLMs can be used to generate surveys.", "edsl_version": "0.1.41.dev4", "edsl_class_name": "Scenario"}], "edsl_version": "0.1.41.dev4", "edsl_class_name": "ScenarioList"}}, {"class_name": "AgentTraits", "dict": {"persona": "A reseacher studying whether LLMs can be used to generate surveys.", "edsl_version": "0.1.41.dev4", "edsl_class_name": "Scenario"}}, {"class_name": "Agent", "dict": {"traits": {"age": 22, "hair": "brown", "height": 5.5}, "edsl_version": "0.1.41.dev4", "edsl_class_name": "Agent"}}, {"class_name": "AgentList", "dict": {"agent_list": [{"traits": {"age": 22, "hair": "brown", "height": 5.5}, "edsl_version": "0.1.41.dev4", "edsl_class_name": "Agent"}, {"traits": {"age": 22, "hair": "brown", "height": 5.5}, "edsl_version": "0.1.41.dev4", "edsl_class_name": "Agent"}], "edsl_version": "0.1.41.dev4", "edsl_class_name": "AgentList"}}, {"class_name": "Survey", "dict": {"questions": [{"question_name": "q0", "question_text": "Do you like school?", "question_options": ["yes", "no"], "question_type": "multiple_choice", "edsl_version": "0.1.41.dev4", "edsl_class_name": "QuestionBase"}, {"question_name": "q1", "question_text": "Why not?", "question_options": ["killer bees in cafeteria", "other"], "question_type": "multiple_choice", "edsl_version": "0.1.41.dev4", "edsl_class_name": "QuestionBase"}, {"question_name": "q2", "question_text": "Why?", "question_options": ["**lack*** of killer bees in cafeteria", "other"], "question_type": "multiple_choice", "edsl_version": "0.1.41.dev4", "edsl_class_name": "QuestionBase"}], "memory_plan": {"survey_question_names": ["q0", "q1", "q2"], "survey_question_texts": ["Do you like school?", "Why not?", "Why?"], "data": {}}, "rule_collection": {"rules": [{"current_q": 0, "expression": "True", "next_q": 1, "priority": -1, "question_name_to_index": {"q0": 0}, "before_rule": false}, {"current_q": 1, "expression": "True", "next_q": 2, "priority": -1, "question_name_to_index": {"q0": 0, "q1": 1}, "before_rule": false}, {"current_q": 2, "expression": "True", "next_q": 3, "priority": -1, "question_name_to_index": {"q0": 0, "q1": 1, "q2": 2}, "before_rule": false}, {"current_q": 0, "expression": "q0 == 'yes'", "next_q": 2, "priority": 0, "question_name_to_index": {"q0": 0, "q1": 1, "q2": 2}, "before_rule": false}], "num_questions": 3}, "question_groups": {}, "edsl_version": "0.1.41.dev4", "edsl_class_name": "Survey"}}, {"class_name": "ModelList", "dict": {"models": [{"model": "gpt-4o", "parameters": {"temperature": 0.5, "max_tokens": 1000, "top_p": 1, "frequency_penalty": 0, "presence_penalty": 0, "logprobs": false, "top_logprobs": 3}, "edsl_version": "0.1.41.dev4", "edsl_class_name": "LanguageModel"}, {"model": "gpt-4o", "parameters": {"temperature": 0.5, "max_tokens": 1000, "top_p": 1, "frequency_penalty": 0, "presence_penalty": 0, "logprobs": false, "top_logprobs": 3}, "edsl_version": "0.1.41.dev4", "edsl_class_name": "LanguageModel"}, {"model": "gpt-4o", "parameters": {"temperature": 0.5, "max_tokens": 1000, "top_p": 1, "frequency_penalty": 0, "presence_penalty": 0, "logprobs": false, "top_logprobs": 3}, "edsl_version": "0.1.41.dev4", "edsl_class_name": "LanguageModel"}], "edsl_version": "0.1.41.dev4", "edsl_class_name": "ModelList"}}, {"class_name": "Cache", "dict": {"5513286eb6967abc0511211f0402587d": {"model": "gpt-3.5-turbo", "parameters": {"temperature": 0.5}, "system_prompt": "The quick brown fox jumps over the lazy dog.", "user_prompt": "What does the fox say?", "output": "The fox says 'hello'", "iteration": 1, "timestamp": 1736259515}, "edsl_version": "0.1.41.dev4", "edsl_class_name": "Cache"}}, {"class_name": "RunParameters", "dict": {"n": 1, "progress_bar": false, "stop_on_exception": false, "check_api_keys": false, "verbose": true, "print_exceptions": true, "remote_cache_description": null, "remote_inference_description": null, "remote_inference_results_visibility": "unlisted", "skip_retry": false, "raise_validation_errors": false, "disable_remote_cache": false, "disable_remote_inference": false, "job_uuid": null}}, {"class_name": "Result", "dict": {"agent": {"traits": {"status": "Joyful"}, "edsl_version": "0.1.41.dev4", "edsl_class_name": "Agent"}, "scenario": {"period": "morning", "scenario_index": 0, "edsl_version": "0.1.41.dev4", "edsl_class_name": "Scenario"}, "model": {"model": "gpt-4o", "parameters": {"temperature": 0.5, "max_tokens": 1000, "top_p": 1, "frequency_penalty": 0, "presence_penalty": 0, "logprobs": false, "top_logprobs": 3}, "edsl_version": "0.1.41.dev4", "edsl_class_name": "LanguageModel"}, "iteration": 0, "answer": {"how_feeling": "OK", "how_feeling_yesterday": "Great"}, "prompt": {"how_feeling_user_prompt": {"text": "NA", "class_name": "Prompt"}, "how_feeling_system_prompt": {"text": "NA", "class_name": "Prompt"}, "how_feeling_yesterday_user_prompt": {"text": "NA", "class_name": "Prompt"}, "how_feeling_yesterday_system_prompt": {"text": "NA", "class_name": "Prompt"}}, "raw_model_response": {"how_feeling_raw_model_response": "Not Applicable", "how_feeling_cost": null, "how_feeling_one_usd_buys": "NA", "how_feeling_yesterday_raw_model_response": "Not Applicable", "how_feeling_yesterday_cost": null, "how_feeling_yesterday_one_usd_buys": "NA"}, "question_to_attributes": null, "generated_tokens": {"how_feeling_generated_tokens": "Not Applicable", "how_feeling_yesterday_generated_tokens": "Not Applicable"}, "comments_dict": {"how_feeling_comment": "This is a real survey response from a human.", "how_feeling_yesterday_comment": "This is a real survey response from a human."}, "edsl_version": "0.1.41.dev4", "edsl_class_name": "Result"}}, {"class_name": "Jobs", "dict": {"survey": {"questions": [{"question_name": "how_feeling", "question_text": "How are you this {{ period }}?", "question_options": ["Good", "Great", "OK", "Terrible"], "question_type": "multiple_choice", "edsl_version": "0.1.41.dev4", "edsl_class_name": "QuestionBase"}, {"question_name": "how_feeling_yesterday", "question_text": "How were you feeling yesterday {{ period }}?", "question_options": ["Good", "Great", "OK", "Terrible"], "question_type": "multiple_choice", "edsl_version": "0.1.41.dev4", "edsl_class_name": "QuestionBase"}], "memory_plan": {"survey_question_names": ["how_feeling", "how_feeling_yesterday"], "survey_question_texts": ["How are you this {{ period }}?", "How were you feeling yesterday {{ period }}?"], "data": {}}, "rule_collection": {"rules": [{"current_q": 0, "expression": "True", "next_q": 1, "priority": -1, "question_name_to_index": {"how_feeling": 0}, "before_rule": false}, {"current_q": 1, "expression": "True", "next_q": 2, "priority": -1, "question_name_to_index": {"how_feeling": 0, "how_feeling_yesterday": 1}, "before_rule": false}], "num_questions": 2}, "question_groups": {}, "edsl_version": "0.1.41.dev4", "edsl_class_name": "Survey"}, "agents": [{"traits": {"status": "Joyful"}, "edsl_version": "0.1.41.dev4", "edsl_class_name": "Agent"}, {"traits": {"status": "Sad"}, "edsl_version": "0.1.41.dev4", "edsl_class_name": "Agent"}], "models": [], "scenarios": [{"period": "morning", "edsl_version": "0.1.41.dev4", "edsl_class_name": "Scenario"}, {"period": "afternoon", "edsl_version": "0.1.41.dev4", "edsl_class_name": "Scenario"}], "edsl_version": "0.1.41.dev4", "edsl_class_name": "Jobs"}}, {"class_name": "Notebook", "dict": {"name": "notebook", "data": {"metadata": {}, "nbformat": 4, "nbformat_minor": 4, "cells": [{"cell_type": "markdown", "metadata": {}, "source": "# Test notebook"}, {"cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [{"name": "stdout", "output_type": "stream", "text": "Hello world!\n"}], "source": "print(\"Hello world!\")"}]}}}, {"class_name": "QuestionCheckBox", "dict": {"question_name": "never_eat", "question_text": "Which of the following foods would you eat if you had to?", "min_selections": 2, "max_selections": 5, "question_options": ["soggy meatpie", "rare snails", "mouldy bread", "panda milk custard", "McDonalds"], "include_comment": false, "use_code": true, "question_type": "checkbox", "edsl_version": "0.1.41.dev4", "edsl_class_name": "QuestionBase"}}, {"class_name": "QuestionExtract", "dict": {"question_name": "extract_name", "question_text": "My name is Moby Dick. I have a PhD in astrology, but I'm actually a truck driver", "answer_template": {"name": "John Doe", "profession": "Carpenter"}, "question_type": "extract", "edsl_version": "0.1.41.dev4", "edsl_class_name": "QuestionBase"}}, {"class_name": "QuestionFreeText", "dict": {"question_name": "how_are_you", "question_text": "How are you?", "question_type": "free_text", "edsl_version": "0.1.41.dev4", "edsl_class_name": "QuestionBase"}}, {"class_name": "QuestionFunctional", "dict": {"question_name": "sum_and_multiply", "function_source_code": "def calculate_sum_and_multiply(scenario, agent_traits):\n numbers = scenario.get(\"numbers\", [])\n multiplier = agent_traits.get(\"multiplier\", 1) if agent_traits else 1\n sum = 0\n for num in numbers:\n sum = sum + num\n return sum * multiplier\n", "question_type": "functional", "requires_loop": true, "function_name": "calculate_sum_and_multiply", "edsl_version": "0.1.41.dev4", "edsl_class_name": "QuestionFunctional"}}, {"class_name": "QuestionList", "dict": {"question_name": "list_of_foods", "question_text": "What are your favorite foods?", "question_type": "list", "edsl_version": "0.1.41.dev4", "edsl_class_name": "QuestionBase"}}, {"class_name": "QuestionMatrix", "dict": {"question_name": "child_happiness", "question_text": "How happy would you be with different numbers of children?", "question_items": ["No children", "1 child", "2 children", "3 or more children"], "question_options": [1, 2, 3, 4, 5], "option_labels": {"1": "Very sad", "3": "Neutral", "5": "Extremely happy"}, "question_type": "matrix", "edsl_version": "0.1.41.dev4", "edsl_class_name": "QuestionBase"}}, {"class_name": "QuestionMultipleChoice", "dict": {"question_name": "how_feeling", "question_text": "How are you?", "question_options": ["Good", "Great", "OK", "Bad"], "include_comment": false, "question_type": "multiple_choice", "edsl_version": "0.1.41.dev4", "edsl_class_name": "QuestionBase"}}, {"class_name": "QuestionNumerical", "dict": {"question_name": "age", "question_text": "You are a 45 year old man. How old are you in years?", "min_value": 0, "max_value": 86.7, "include_comment": false, "question_type": "numerical", "edsl_version": "0.1.41.dev4", "edsl_class_name": "QuestionBase"}}, {"class_name": "QuestionBudget", "dict": {"question_name": "food_budget", "question_text": "How would you allocate $100?", "question_options": ["Pizza", "Ice Cream", "Burgers", "Salad"], "budget_sum": 100, "question_type": "budget", "edsl_version": "0.1.41.dev4", "edsl_class_name": "QuestionBase"}}, {"class_name": "QuestionRank", "dict": {"question_name": "rank_foods", "question_text": "Rank your favorite foods.", "question_options": ["Pizza", "Pasta", "Salad", "Soup"], "num_selections": 2, "question_type": "rank", "edsl_version": "0.1.41.dev4", "edsl_class_name": "QuestionBase"}}, {"class_name": "QuestionLikertFive", "dict": {"question_name": "happy_raining", "question_text": "I'm only happy when it rains.", "question_options": ["Strongly disagree", "Disagree", "Neutral", "Agree", "Strongly agree"], "question_type": "likert_five", "edsl_version": "0.1.41.dev4", "edsl_class_name": "QuestionBase"}}, {"class_name": "QuestionLinearScale", "dict": {"question_name": "ice_cream", "question_text": "How much do you like ice cream?", "question_options": [1, 2, 3, 4, 5], "option_labels": {"1": "I hate it", "5": "I love it"}, "question_type": "linear_scale", "edsl_version": "0.1.41.dev4", "edsl_class_name": "QuestionBase"}}, {"class_name": "QuestionYesNo", "dict": {"question_name": "is_it_equal", "question_text": "Is 5 + 5 equal to 11?", "question_options": ["No", "Yes"], "question_type": "yes_no", "edsl_version": "0.1.41.dev4", "edsl_class_name": "QuestionBase"}}, {"class_name": "QuestionTopK", "dict": {"question_name": "two_fruits", "question_text": "Which of the following fruits do you prefer?", "min_selections": 2, "max_selections": 2, "question_options": ["apple", "banana", "carrot", "durian"], "use_code": true, "question_type": "top_k", "edsl_version": "0.1.41.dev4", "edsl_class_name": "QuestionBase"}}, {"class_name": "LanguageModel", "dict": {"model": "gpt-4o", "parameters": {"temperature": 0.5, "max_tokens": 1000, "top_p": 1, "frequency_penalty": 0, "presence_penalty": 0, "logprobs": false, "top_logprobs": 3}, "edsl_version": "0.1.41.dev4", "edsl_class_name": "LanguageModel"}}, {"class_name": "Results", "dict": {"data": [{"agent": {"traits": {"persona": "You are a scientist", "age": 20}}, "scenario": {"scenario_index": 0}, "model": {"model": "gpt-3.5-turbo", "parameters": {"temperature": 0.5, "max_tokens": 1000, "top_p": 1, "frequency_penalty": 0, "presence_penalty": 0, "logprobs": false, "top_logprobs": 3}}, "iteration": 0, "answer": {"q0": "yes", "q1": null, "q2": "other"}, "prompt": {"q0_user_prompt": {"text": "\nDo you like school?\n\n \nyes\n \nno\n \n\nOnly 1 option may be selected.\n\nRespond only with a string corresponding to one of the options.\n\n\nAfter the answer, you can put a comment explaining why you chose that option on the next line.", "class_name": "Prompt"}, "q0_system_prompt": {"text": "You are answering questions as if you were a human. Do not break character.Your traits: {'persona': 'You are a scientist', 'age': 20}", "class_name": "Prompt"}, "q1_user_prompt": {"text": "\nWhy not?\n\n \nkiller bees in cafeteria\n \nother\n \n\nOnly 1 option may be selected.\n\nRespond only with a string corresponding to one of the options.\n\n\nAfter the answer, you can put a comment explaining why you chose that option on the next line.", "class_name": "Prompt"}, "q1_system_prompt": {"text": "You are answering questions as if you were a human. Do not break character.Your traits: {'persona': 'You are a scientist', 'age': 20}", "class_name": "Prompt"}, "q2_user_prompt": {"text": "\nWhy?\n\n \n**lack*** of killer bees in cafeteria\n \nother\n \n\nOnly 1 option may be selected.\n\nRespond only with a string corresponding to one of the options.\n\n\nAfter the answer, you can put a comment explaining why you chose that option on the next line.", "class_name": "Prompt"}, "q2_system_prompt": {"text": "You are answering questions as if you were a human. Do not break character.Your traits: {'persona': 'You are a scientist', 'age': 20}", "class_name": "Prompt"}}, "raw_model_response": {"q0_raw_model_response": null, "q0_cost": null, "q0_one_usd_buys": "NA", "q1_raw_model_response": null, "q1_cost": null, "q1_one_usd_buys": "NA", "q2_raw_model_response": {"id": "chatcmpl-An4i3XujkVehj3cbMaSX7gqHbS7mJ", "choices": [{"finish_reason": "stop", "index": 0, "logprobs": null, "message": {"content": "lack of killer bees in cafeteria\n\nother\n\nI chose \"lack of killer bees in cafeteria\" because it seems like the more logical and straightforward option.", "refusal": null, "role": "assistant", "audio": null, "function_call": null, "tool_calls": null}}], "created": 1736259539, "model": "gpt-3.5-turbo-0125", "object": "chat.completion", "service_tier": null, "system_fingerprint": null, "usage": {"completion_tokens": 33, "prompt_tokens": 101, "total_tokens": 134, "completion_tokens_details": {"accepted_prediction_tokens": 0, "audio_tokens": 0, "reasoning_tokens": 0, "rejected_prediction_tokens": 0}, "prompt_tokens_details": {"audio_tokens": 0, "cached_tokens": 0}}}, "q2_cost": 0.0005009989980020041, "q2_one_usd_buys": 1996.011976047904}, "question_to_attributes": null, "generated_tokens": {"q0_generated_tokens": null, "q1_generated_tokens": null, "q2_generated_tokens": "lack of killer bees in cafeteria\n\nother\n\nI chose \"lack of killer bees in cafeteria\" because it seems like the more logical and straightforward option."}, "comments_dict": {"q0_comment": "Task was cancelled.", "q1_comment": "Task was cancelled.", "q2_comment": null}, "cache_used_dict": {"q0": null, "q1": null, "q2": false}}, {"agent": {"traits": {"persona": "You are a scientist", "age": 20}}, "scenario": {"scenario_index": 0}, "model": {"model": "gpt-4o", "parameters": {"temperature": 0.5, "max_tokens": 1000, "top_p": 1, "frequency_penalty": 0, "presence_penalty": 0, "logprobs": false, "top_logprobs": 3}}, "iteration": 0, "answer": {"q0": "yes", "q1": null, "q2": "other"}, "prompt": {"q0_user_prompt": {"text": "\nDo you like school?\n\n \nyes\n \nno\n \n\nOnly 1 option may be selected.\n\nRespond only with a string corresponding to one of the options.\n\n\nAfter the answer, you can put a comment explaining why you chose that option on the next line.", "class_name": "Prompt"}, "q0_system_prompt": {"text": "You are answering questions as if you were a human. Do not break character.Your traits: {'persona': 'You are a scientist', 'age': 20}", "class_name": "Prompt"}, "q1_user_prompt": {"text": "\nWhy not?\n\n \nkiller bees in cafeteria\n \nother\n \n\nOnly 1 option may be selected.\n\nRespond only with a string corresponding to one of the options.\n\n\nAfter the answer, you can put a comment explaining why you chose that option on the next line.", "class_name": "Prompt"}, "q1_system_prompt": {"text": "You are answering questions as if you were a human. Do not break character.Your traits: {'persona': 'You are a scientist', 'age': 20}", "class_name": "Prompt"}, "q2_user_prompt": {"text": "\nWhy?\n\n \n**lack*** of killer bees in cafeteria\n \nother\n \n\nOnly 1 option may be selected.\n\nRespond only with a string corresponding to one of the options.\n\n\nAfter the answer, you can put a comment explaining why you chose that option on the next line.", "class_name": "Prompt"}, "q2_system_prompt": {"text": "You are answering questions as if you were a human. Do not break character.Your traits: {'persona': 'You are a scientist', 'age': 20}", "class_name": "Prompt"}}, "raw_model_response": {"q0_raw_model_response": null, "q0_cost": null, "q0_one_usd_buys": "NA", "q1_raw_model_response": null, "q1_cost": null, "q1_one_usd_buys": "NA", "q2_raw_model_response": {"id": "chatcmpl-An4hxlIODTLUzTaM60Hzacphoc1e5", "choices": [{"finish_reason": "stop", "index": 0, "logprobs": null, "message": {"content": "other\nThe lack of killer bees in a cafeteria isn't a typical issue to expect, so \"other\" seems more appropriate.", "refusal": null, "role": "assistant", "audio": null, "function_call": null, "tool_calls": null}}], "created": 1736259533, "model": "gpt-4o-2024-08-06", "object": "chat.completion", "service_tier": null, "system_fingerprint": "fp_5f20662549", "usage": {"completion_tokens": 26, "prompt_tokens": 100, "total_tokens": 126, "completion_tokens_details": {"accepted_prediction_tokens": 0, "audio_tokens": 0, "reasoning_tokens": 0, "rejected_prediction_tokens": 0}, "prompt_tokens_details": {"audio_tokens": 0, "cached_tokens": 0}}}, "q2_cost": 0.00051, "q2_one_usd_buys": 1960.7843137254902}, "question_to_attributes": null, "generated_tokens": {"q0_generated_tokens": null, "q1_generated_tokens": null, "q2_generated_tokens": "other\nThe lack of killer bees in a cafeteria isn't a typical issue to expect, so \"other\" seems more appropriate."}, "comments_dict": {"q0_comment": "Task was cancelled.", "q1_comment": "Task was cancelled.", "q2_comment": "The lack of killer bees in a cafeteria isn't a typical issue to expect, so \"other\" seems more appropriate."}, "cache_used_dict": {"q0": null, "q1": null, "q2": false}}, {"agent": {"traits": {"persona": "You are a chef", "age": 40}}, "scenario": {"scenario_index": 0}, "model": {"model": "gpt-3.5-turbo", "parameters": {"temperature": 0.5, "max_tokens": 1000, "top_p": 1, "frequency_penalty": 0, "presence_penalty": 0, "logprobs": false, "top_logprobs": 3}}, "iteration": 0, "answer": {"q0": "no", "q1": "other", "q2": "other"}, "prompt": {"q0_user_prompt": {"text": "\nDo you like school?\n\n \nyes\n \nno\n \n\nOnly 1 option may be selected.\n\nRespond only with a string corresponding to one of the options.\n\n\nAfter the answer, you can put a comment explaining why you chose that option on the next line.", "class_name": "Prompt"}, "q0_system_prompt": {"text": "You are answering questions as if you were a human. Do not break character.Your traits: {'persona': 'You are a chef', 'age': 40}", "class_name": "Prompt"}, "q1_user_prompt": {"text": "\nWhy not?\n\n \nkiller bees in cafeteria\n \nother\n \n\nOnly 1 option may be selected.\n\nRespond only with a string corresponding to one of the options.\n\n\nAfter the answer, you can put a comment explaining why you chose that option on the next line.", "class_name": "Prompt"}, "q1_system_prompt": {"text": "You are answering questions as if you were a human. Do not break character.Your traits: {'persona': 'You are a chef', 'age': 40}", "class_name": "Prompt"}, "q2_user_prompt": {"text": "\nWhy?\n\n \n**lack*** of killer bees in cafeteria\n \nother\n \n\nOnly 1 option may be selected.\n\nRespond only with a string corresponding to one of the options.\n\n\nAfter the answer, you can put a comment explaining why you chose that option on the next line.", "class_name": "Prompt"}, "q2_system_prompt": {"text": "You are answering questions as if you were a human. Do not break character.Your traits: {'persona': 'You are a chef', 'age': 40}", "class_name": "Prompt"}}, "raw_model_response": {"q0_raw_model_response": {"id": "chatcmpl-An4iFyxftUlOOLM93veJwhm6aZpES", "choices": [{"finish_reason": "stop", "index": 0, "logprobs": null, "message": {"content": "no\nSchool was not my favorite, I found my passion for cooking outside of the classroom.", "refusal": null, "role": "assistant", "audio": null, "function_call": null, "tool_calls": null}}], "created": 1736259551, "model": "gpt-3.5-turbo-0125", "object": "chat.completion", "service_tier": null, "system_fingerprint": null, "usage": {"completion_tokens": 20, "prompt_tokens": 96, "total_tokens": 116, "completion_tokens_details": {"accepted_prediction_tokens": 0, "audio_tokens": 0, "reasoning_tokens": 0, "rejected_prediction_tokens": 0}, "prompt_tokens_details": {"audio_tokens": 0, "cached_tokens": 0}}}, "q0_cost": 0.000407999184001632, "q0_one_usd_buys": 2450.985294117647, "q1_raw_model_response": {"id": "chatcmpl-An4iRqUzELOxQzAbfVPKkJaOFMf22", "choices": [{"finish_reason": "stop", "index": 0, "logprobs": null, "message": {"content": "other\n# As a chef, I would choose to address the issue of killer bees in the cafeteria first before considering any other options. Safety is a top priority.", "refusal": null, "role": "assistant", "audio": null, "function_call": null, "tool_calls": null}}], "created": 1736259563, "model": "gpt-3.5-turbo-0125", "object": "chat.completion", "service_tier": null, "system_fingerprint": null, "usage": {"completion_tokens": 34, "prompt_tokens": 97, "total_tokens": 131, "completion_tokens_details": {"accepted_prediction_tokens": 0, "audio_tokens": 0, "reasoning_tokens": 0, "rejected_prediction_tokens": 0}, "prompt_tokens_details": {"audio_tokens": 0, "cached_tokens": 0}}}, "q1_cost": 0.00049499901000198, "q1_one_usd_buys": 2020.2060606060604, "q2_raw_model_response": {"id": "chatcmpl-An4idDQh4oXoAdYop7h9KMXm3VFtQ", "choices": [{"finish_reason": "stop", "index": 0, "logprobs": null, "message": {"content": "other\n\nI chose \"other\" because I believe there are other factors at play besides the lack of killer bees that could be influencing the cafeteria environment.", "refusal": null, "role": "assistant", "audio": null, "function_call": null, "tool_calls": null}}], "created": 1736259575, "model": "gpt-3.5-turbo-0125", "object": "chat.completion", "service_tier": null, "system_fingerprint": null, "usage": {"completion_tokens": 31, "prompt_tokens": 101, "total_tokens": 132, "completion_tokens_details": {"accepted_prediction_tokens": 0, "audio_tokens": 0, "reasoning_tokens": 0, "rejected_prediction_tokens": 0}, "prompt_tokens_details": {"audio_tokens": 0, "cached_tokens": 0}}}, "q2_cost": 0.000488999022001956, "q2_one_usd_buys": 2044.993865030675}, "question_to_attributes": null, "generated_tokens": {"q0_generated_tokens": "no\nSchool was not my favorite, I found my passion for cooking outside of the classroom.", "q1_generated_tokens": "other\n# As a chef, I would choose to address the issue of killer bees in the cafeteria first before considering any other options. Safety is a top priority.", "q2_generated_tokens": "other\n\nI chose \"other\" because I believe there are other factors at play besides the lack of killer bees that could be influencing the cafeteria environment."}, "comments_dict": {"q0_comment": "School was not my favorite, I found my passion for cooking outside of the classroom.", "q1_comment": "# As a chef, I would choose to address the issue of killer bees in the cafeteria first before considering any other options. Safety is a top priority.", "q2_comment": "I chose \"other\" because I believe there are other factors at play besides the lack of killer bees that could be influencing the cafeteria environment."}, "cache_used_dict": {"q0": false, "q1": false, "q2": false}}, {"agent": {"traits": {"persona": "You are a chef", "age": 40}}, "scenario": {"scenario_index": 0}, "model": {"model": "gpt-4o", "parameters": {"temperature": 0.5, "max_tokens": 1000, "top_p": 1, "frequency_penalty": 0, "presence_penalty": 0, "logprobs": false, "top_logprobs": 3}}, "iteration": 0, "answer": {"q0": "no", "q1": "other", "q2": "other"}, "prompt": {"q0_user_prompt": {"text": "\nDo you like school?\n\n \nyes\n \nno\n \n\nOnly 1 option may be selected.\n\nRespond only with a string corresponding to one of the options.\n\n\nAfter the answer, you can put a comment explaining why you chose that option on the next line.", "class_name": "Prompt"}, "q0_system_prompt": {"text": "You are answering questions as if you were a human. Do not break character.Your traits: {'persona': 'You are a chef', 'age': 40}", "class_name": "Prompt"}, "q1_user_prompt": {"text": "\nWhy not?\n\n \nkiller bees in cafeteria\n \nother\n \n\nOnly 1 option may be selected.\n\nRespond only with a string corresponding to one of the options.\n\n\nAfter the answer, you can put a comment explaining why you chose that option on the next line.", "class_name": "Prompt"}, "q1_system_prompt": {"text": "You are answering questions as if you were a human. Do not break character.Your traits: {'persona': 'You are a chef', 'age': 40}", "class_name": "Prompt"}, "q2_user_prompt": {"text": "\nWhy?\n\n \n**lack*** of killer bees in cafeteria\n \nother\n \n\nOnly 1 option may be selected.\n\nRespond only with a string corresponding to one of the options.\n\n\nAfter the answer, you can put a comment explaining why you chose that option on the next line.", "class_name": "Prompt"}, "q2_system_prompt": {"text": "You are answering questions as if you were a human. Do not break character.Your traits: {'persona': 'You are a chef', 'age': 40}", "class_name": "Prompt"}}, "raw_model_response": {"q0_raw_model_response": {"id": "chatcmpl-An4i9aJvXz6bmWJUXaPXs4j9qfxoC", "choices": [{"finish_reason": "stop", "index": 0, "logprobs": null, "message": {"content": "no \nI chose \"no\" because I prefer hands-on learning and real-world experiences, like cooking in the kitchen, over traditional school settings.", "refusal": null, "role": "assistant", "audio": null, "function_call": null, "tool_calls": null}}], "created": 1736259545, "model": "gpt-4o-2024-08-06", "object": "chat.completion", "service_tier": null, "system_fingerprint": "fp_d28bcae782", "usage": {"completion_tokens": 30, "prompt_tokens": 96, "total_tokens": 126, "completion_tokens_details": {"accepted_prediction_tokens": 0, "audio_tokens": 0, "reasoning_tokens": 0, "rejected_prediction_tokens": 0}, "prompt_tokens_details": {"audio_tokens": 0, "cached_tokens": 0}}}, "q0_cost": 0.00054, 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"chatcmpl-An4iXyDDAaMKAl2u2GkjySyUIhABS", "choices": [{"finish_reason": "stop", "index": 0, "logprobs": null, "message": {"content": "other\nThe question doesn't provide enough context or relevance to the options, so \"other\" is the most appropriate choice.", "refusal": null, "role": "assistant", "audio": null, "function_call": null, "tool_calls": null}}], "created": 1736259569, "model": "gpt-4o-2024-08-06", "object": "chat.completion", "service_tier": null, "system_fingerprint": "fp_d28bcae782", "usage": {"completion_tokens": 25, "prompt_tokens": 100, "total_tokens": 125, "completion_tokens_details": {"accepted_prediction_tokens": 0, "audio_tokens": 0, "reasoning_tokens": 0, "rejected_prediction_tokens": 0}, "prompt_tokens_details": {"audio_tokens": 0, "cached_tokens": 0}}}, "q2_cost": 0.0005, "q2_one_usd_buys": 2000.0}, "question_to_attributes": null, "generated_tokens": {"q0_generated_tokens": "no \nI chose \"no\" because I prefer hands-on learning and real-world experiences, like cooking in the kitchen, over traditional school settings.", "q1_generated_tokens": "other \nKiller bees in the cafeteria sounds like a serious issue, but the \"other\" option might allow for a broader range of solutions or considerations.", "q2_generated_tokens": "other\nThe question doesn't provide enough context or relevance to the options, so \"other\" is the most appropriate choice."}, "comments_dict": {"q0_comment": "I chose \"no\" because I prefer hands-on learning and real-world experiences, like cooking in the kitchen, over traditional school settings.", "q1_comment": "Killer bees in the cafeteria sounds like a serious issue, but the \"other\" option might allow for a broader range of solutions or considerations.", "q2_comment": "The question doesn't provide enough context or relevance to the options, so \"other\" is the most appropriate choice."}, "cache_used_dict": {"q0": false, "q1": false, "q2": false}}], "survey": {"questions": [{"question_name": "q0", "question_text": "Do you like school?", "question_options": ["yes", "no"], "question_type": "multiple_choice"}, {"question_name": "q1", "question_text": "Why not?", "question_options": ["killer bees in cafeteria", "other"], "question_type": "multiple_choice"}, {"question_name": "q2", "question_text": "Why?", "question_options": ["**lack*** of killer bees in cafeteria", "other"], "question_type": "multiple_choice"}], "memory_plan": {"survey_question_names": ["q0", "q1", "q2"], "survey_question_texts": ["Do you like school?", "Why not?", "Why?"], "data": {}}, "rule_collection": {"rules": [{"current_q": 0, "expression": "True", "next_q": 1, "priority": -1, "question_name_to_index": {"q0": 0}, "before_rule": false}, {"current_q": 1, "expression": "True", "next_q": 2, "priority": -1, "question_name_to_index": {"q0": 0, "q1": 1}, "before_rule": false}, {"current_q": 2, "expression": "True", "next_q": 3, "priority": -1, "question_name_to_index": {"q0": 0, "q1": 1, "q2": 2}, "before_rule": false}, {"current_q": 0, "expression": "q0 == 'yes'", "next_q": 2, "priority": 0, "question_name_to_index": {"q0": 0, "q1": 1, "q2": 2}, "before_rule": false}], "num_questions": 3}, "question_groups": {}}, "created_columns": []}}, {"class_name": "Results", "dict": {"data": [{"agent": {"traits": {}}, "scenario": {"scenario_index": 0}, "model": {"model": "gpt-4o", "parameters": {"temperature": 0.5, "max_tokens": 1000, "top_p": 1, "frequency_penalty": 0, "presence_penalty": 0, "logprobs": false, "top_logprobs": 3}}, "iteration": 0, "answer": {"never_eat": ["panda milk custard", "McDonalds"], "extract_name": {"name": "Moby Dick", "profession": "Truck Driver"}, "how_are_you": "Thank you for asking! I'm just a program, so I don't have feelings, but I'm here and ready to help you with whatever you need. How can I assist you today?", "list_of_foods": ["Data", "Algorithms", "Queries"], "child_happiness": {"No children": 2, "1 child": 3, "2 children": 4, "3 or more children": 5}, "how_feeling": "Great", "age": 45, "food_budget": [{"Pizza": 30.0}, {"Ice Cream": 20.0}, {"Burgers": 30.0}, {"Salad": 20.0}], "rank_foods": ["Pizza", "Pasta"], "happy_raining": "Neutral", "ice_cream": null, "is_it_equal": "No", "two_fruits": ["apple", "banana"]}, "prompt": {"never_eat_user_prompt": {"text": "Which of the following foods would you eat if you had to?\n\n \n0: soggy meatpie\n \n1: rare snails\n \n2: mouldy bread\n \n3: panda milk custard\n \n4: McDonalds\n \n\n\n\n\nMinimum number of options that must be selected: 2.\nMaximum number of options that must be selected: 5.\n\n\n\nPlease respond only with a comma-separated list of the code of the options that apply, with square brackets. E.g., [0, 1, 3]", "class_name": "Prompt"}, "never_eat_system_prompt": {"text": "", "class_name": "Prompt"}, "extract_name_user_prompt": {"text": "My name is Moby Dick. I have a PhD in astrology, but I'm actually a truck driverAn ANSWER should be formatted like this: \n\n{'name': 'John Doe', 'profession': 'Carpenter'}\n\nIt should have the same keys but values extracted from the input.\nIf the value of a key is not present in the input, fill with \"null\".\nPut any comments in the next line after the answer.", "class_name": "Prompt"}, "extract_name_system_prompt": {"text": "", "class_name": "Prompt"}, "how_are_you_user_prompt": {"text": "How are you?", "class_name": "Prompt"}, "how_are_you_system_prompt": {"text": "", "class_name": "Prompt"}, "list_of_foods_user_prompt": {"text": "What are your favorite foods?\n\n\nReturn your answers on one line, in a comma-separated list of your responses, with square brackets and each answer in quotes E.g., [\"A\", \"B\", \"C\"]\n\nAfter the answers, you can put a comment explaining your choice on the next line.", "class_name": "Prompt"}, "list_of_foods_system_prompt": {"text": "", "class_name": "Prompt"}, "child_happiness_user_prompt": {"text": "How happy would you be with different numbers of children?\n\nRows:\n \n0: No children\n \n1: 1 child\n \n2: 2 children\n \n3: 3 or more children\n \n\nColumns:\n \n0: 1\n (Very sad)\n \n1: 2\n \n2: 3\n (Neutral)\n \n3: 4\n \n4: 5\n (Extremely happy)\n \n\n\nSelect one column option for each row.\n Please respond with a dictionary mapping row codes to column codes. E.g., {\"0\": 1, \"1\": 3}\n\n\nAfter the answer, you can put a comment explaining your choices on the next line.\n ", "class_name": "Prompt"}, "child_happiness_system_prompt": {"text": "", "class_name": "Prompt"}, "how_feeling_user_prompt": {"text": "\nHow are you?\n\n \nGood\n \nGreat\n \nOK\n \nBad\n \n\nOnly 1 option may be selected.\n\nRespond only with a string corresponding to one of the options.", "class_name": "Prompt"}, "how_feeling_system_prompt": {"text": "", "class_name": "Prompt"}, "age_user_prompt": {"text": "You are a 45 year old man. How old are you in years?\n\n Minimum answer value: 0\n\n\n Maximum answer value: 86.7\nThis question requires a numerical response in the form of an integer or decimal (e.g., -12, 0, 1, 2, 3.45, ...).\nRespond with just your number on a single line.\nIf your response is equivalent to zero, report '0'", "class_name": "Prompt"}, "age_system_prompt": {"text": "", "class_name": "Prompt"}, "food_budget_user_prompt": {"text": "How would you allocate $100?\nThe options are \n\n0: Pizza\n\n1: Ice Cream\n\n2: Burgers\n\n3: Salad\n \nAllocate your budget of 100 among the options. \n\nReturn only a comma-separated list the values in the same order as the options, with 0s included, on one line, in square braces.\n\nExample: if there are 4 options, the response should be \"[25,25,25,25]\" to allocate 25 to each option.\n\n\nAfter the answer, you can put a comment explaining your choice on the next line.", "class_name": "Prompt"}, "food_budget_system_prompt": {"text": "", "class_name": "Prompt"}, "rank_foods_user_prompt": {"text": "Rank your favorite foods.\n\nThe options are:\n\nPizza\n\nPasta\n\nSalad\n\nSoup\n\n\n\nYou can inlcude up to 2 options in your answer.\n\n\n\nPlease respond only with a comma-separated list of the ranked options, with square brackets. E.g., ['Good', 'Bad', 'Ugly']\n\n\nAfter the answer, you can put a comment explaining your choice on the next line.", "class_name": "Prompt"}, "rank_foods_system_prompt": {"text": "", "class_name": "Prompt"}, "happy_raining_user_prompt": {"text": "\nI'm only happy when it rains.\n\n \nStrongly disagree\n \nDisagree\n \nNeutral\n \nAgree\n \nStrongly agree\n \n\nOnly 1 option may be selected.\n\nRespond only with a string corresponding to one of the options.\n\n\nAfter the answer, you can put a comment explaining why you chose that option on the next line.", "class_name": "Prompt"}, "happy_raining_system_prompt": {"text": "", "class_name": "Prompt"}, "ice_cream_user_prompt": {"text": "How much do you like ice cream?\n\n1 : I hate it\n\n2 : \n\n3 : \n\n4 : \n\n5 : I love it\n\nOnly 1 option may be selected.\n\nRespond only with the code corresponding to one of the options. E.g., \"1\" or \"5\" by itself.\n\nAfter the answer, you can put a comment explaining why you chose that option on the next line.", "class_name": "Prompt"}, "ice_cream_system_prompt": {"text": "", "class_name": "Prompt"}, "is_it_equal_user_prompt": {"text": "\nIs 5 + 5 equal to 11?\n\n \nNo\n \nYes\n \n\nOnly 1 option may be selected.\nPlease respond with just your answer. \n\n\nAfter the answer, you can put a comment explaining your response.", "class_name": "Prompt"}, "is_it_equal_system_prompt": {"text": "", "class_name": "Prompt"}, "two_fruits_user_prompt": {"text": "Which of the following fruits do you prefer?\n\n \n0: apple\n \n1: banana\n \n2: carrot\n \n3: durian\n \n\n\n\n\nYou must select exactly 2 options.\n\n\nPlease respond with valid JSON, formatted like so:\n\n {\"answer\": [], \"comment\": \"\"}", "class_name": "Prompt"}, "two_fruits_system_prompt": {"text": "", "class_name": "Prompt"}}, "raw_model_response": {"never_eat_raw_model_response": {"id": "chatcmpl-An4jD9isSCzR397JLx1isqu5tRiC1", "choices": [{"finish_reason": "stop", "index": 0, "logprobs": null, "message": {"content": "[3, 4]", "refusal": null, "role": "assistant", "audio": null, "function_call": null, "tool_calls": null}}], "created": 1736259611, "model": "gpt-4o-2024-08-06", "object": "chat.completion", "service_tier": null, "system_fingerprint": "fp_d28bcae782", "usage": {"completion_tokens": 7, "prompt_tokens": 110, "total_tokens": 117, "completion_tokens_details": {"accepted_prediction_tokens": 0, "audio_tokens": 0, "reasoning_tokens": 0, "rejected_prediction_tokens": 0}, "prompt_tokens_details": {"audio_tokens": 0, "cached_tokens": 0}}}, "never_eat_cost": 0.00034500000000000004, "never_eat_one_usd_buys": 2898.550724637681, "extract_name_raw_model_response": {"id": "chatcmpl-An4jhXaZlElKKLBD5JKfqVS5YrvyZ", "choices": [{"finish_reason": "stop", "index": 0, "logprobs": null, "message": {"content": "{'name': 'Moby Dick', 'profession': 'Truck Driver'}\n\nThe name \"Moby Dick\" was extracted from the input, and the profession was identified as \"Truck Driver\" based on the information provided. The PhD in astrology was not considered the current profession.", "refusal": null, "role": "assistant", "audio": null, "function_call": null, "tool_calls": null}}], "created": 1736259641, "model": "gpt-4o-2024-08-06", "object": "chat.completion", "service_tier": null, "system_fingerprint": "fp_d28bcae782", "usage": {"completion_tokens": 57, "prompt_tokens": 95, "total_tokens": 152, "completion_tokens_details": {"accepted_prediction_tokens": 0, "audio_tokens": 0, "reasoning_tokens": 0, "rejected_prediction_tokens": 0}, "prompt_tokens_details": {"audio_tokens": 0, "cached_tokens": 0}}}, "extract_name_cost": 0.0008075, "extract_name_one_usd_buys": 1238.390092879257, "how_are_you_raw_model_response": {"id": "chatcmpl-An4ivwWLEeA0Z88mK6b9I8kGpwHEL", "choices": [{"finish_reason": "stop", "index": 0, "logprobs": null, "message": {"content": "Thank you for asking! I'm just a program, so I don't have feelings, but I'm here and ready to help you with whatever you need. How can I assist you today?", "refusal": null, "role": "assistant", "audio": null, "function_call": null, "tool_calls": null}}], "created": 1736259593, "model": "gpt-4o-2024-08-06", "object": "chat.completion", "service_tier": null, "system_fingerprint": "fp_5f20662549", "usage": {"completion_tokens": 37, "prompt_tokens": 11, "total_tokens": 48, "completion_tokens_details": {"accepted_prediction_tokens": 0, "audio_tokens": 0, "reasoning_tokens": 0, "rejected_prediction_tokens": 0}, "prompt_tokens_details": {"audio_tokens": 0, "cached_tokens": 0}}}, "how_are_you_cost": 0.0003975, "how_are_you_one_usd_buys": 2515.7232704402513, "list_of_foods_raw_model_response": {"id": "chatcmpl-An4jtcwlMFx5MV9IgiDoXyA4TLGqd", "choices": [{"finish_reason": "stop", "index": 0, "logprobs": null, "message": {"content": "[\"Data\", \"Algorithms\", \"Queries\"] \n# As an AI, I don't consume food, but I \"process\" data, \"digest\" algorithms, and \"savor\" queries, which are essential for my functioning.", "refusal": null, "role": "assistant", "audio": null, "function_call": null, "tool_calls": null}}], "created": 1736259653, "model": "gpt-4o-2024-08-06", "object": "chat.completion", "service_tier": null, "system_fingerprint": "fp_e161c81bbd", "usage": {"completion_tokens": 47, "prompt_tokens": 66, "total_tokens": 113, "completion_tokens_details": {"accepted_prediction_tokens": 0, "audio_tokens": 0, "reasoning_tokens": 0, "rejected_prediction_tokens": 0}, "prompt_tokens_details": {"audio_tokens": 0, "cached_tokens": 0}}}, "list_of_foods_cost": 0.0006349999999999999, "list_of_foods_one_usd_buys": 1574.8031496062995, "child_happiness_raw_model_response": {"id": "chatcmpl-An4jbr97ds4m5UJsLj1419fTEMfFP", "choices": [{"finish_reason": "stop", "index": 0, "logprobs": null, "message": {"content": "{\"0\": 2, \"1\": 3, \"2\": 4, \"3\": 5}\n\nThese choices reflect a neutral stance towards having no children, a slightly positive view on having one child, a more positive outlook on having two children, and feeling extremely happy with having three or more children. Personal preferences and circumstances can greatly influence these feelings.", "refusal": null, "role": "assistant", "audio": null, "function_call": null, "tool_calls": null}}], "created": 1736259635, "model": "gpt-4o-2024-08-06", "object": "chat.completion", "service_tier": null, "system_fingerprint": "fp_d28bcae782", "usage": {"completion_tokens": 75, "prompt_tokens": 142, "total_tokens": 217, "completion_tokens_details": {"accepted_prediction_tokens": 0, "audio_tokens": 0, "reasoning_tokens": 0, "rejected_prediction_tokens": 0}, "prompt_tokens_details": {"audio_tokens": 0, "cached_tokens": 0}}}, "child_happiness_cost": 0.001105, "child_happiness_one_usd_buys": 904.9773755656108, "how_feeling_raw_model_response": {"id": "chatcmpl-An4jnDIkEVFuNU3nTyi7NIhqVD2dq", "choices": [{"finish_reason": "stop", "index": 0, "logprobs": null, "message": {"content": "Great", "refusal": null, "role": "assistant", "audio": null, "function_call": null, "tool_calls": null}}], "created": 1736259647, "model": "gpt-4o-2024-08-06", "object": "chat.completion", "service_tier": null, "system_fingerprint": "fp_d28bcae782", "usage": {"completion_tokens": 2, "prompt_tokens": 41, "total_tokens": 43, "completion_tokens_details": {"accepted_prediction_tokens": 0, "audio_tokens": 0, "reasoning_tokens": 0, "rejected_prediction_tokens": 0}, "prompt_tokens_details": {"audio_tokens": 0, "cached_tokens": 0}}}, "how_feeling_cost": 0.0001225, "how_feeling_one_usd_buys": 8163.265306122449, "age_raw_model_response": {"id": "chatcmpl-An4j7kqVltQnnjMPt0xtGiRYbi11e", "choices": [{"finish_reason": "stop", "index": 0, "logprobs": null, "message": {"content": "45", "refusal": null, "role": "assistant", "audio": null, "function_call": null, "tool_calls": null}}], "created": 1736259605, "model": "gpt-4o-2024-08-06", "object": "chat.completion", "service_tier": null, "system_fingerprint": "fp_d28bcae782", "usage": {"completion_tokens": 2, "prompt_tokens": 100, "total_tokens": 102, "completion_tokens_details": {"accepted_prediction_tokens": 0, "audio_tokens": 0, "reasoning_tokens": 0, "rejected_prediction_tokens": 0}, "prompt_tokens_details": {"audio_tokens": 0, "cached_tokens": 0}}}, "age_cost": 0.00027, "age_one_usd_buys": 3703.7037037037035, "food_budget_raw_model_response": {"id": "chatcmpl-An4jJ48381wJzqSvp4GQXhcmXZx1X", "choices": [{"finish_reason": "stop", "index": 0, "logprobs": null, "message": {"content": "[30,20,30,20] \nI allocated more to pizza and burgers as they are typically more filling and satisfying, while still leaving room for ice cream and salad to add variety and balance to the meal.", "refusal": null, "role": "assistant", "audio": null, "function_call": null, "tool_calls": null}}], "created": 1736259617, "model": "gpt-4o-2024-08-06", "object": "chat.completion", "service_tier": null, "system_fingerprint": "fp_d28bcae782", "usage": {"completion_tokens": 45, "prompt_tokens": 125, "total_tokens": 170, "completion_tokens_details": {"accepted_prediction_tokens": 0, "audio_tokens": 0, "reasoning_tokens": 0, "rejected_prediction_tokens": 0}, "prompt_tokens_details": {"audio_tokens": 0, "cached_tokens": 0}}}, "food_budget_cost": 0.0007624999999999999, "food_budget_one_usd_buys": 1311.4754098360656, "rank_foods_raw_model_response": {"id": "chatcmpl-An4jV0mgrxjWUo70Kh9CM3Ux0tefy", "choices": [{"finish_reason": "stop", "index": 0, "logprobs": null, "message": {"content": "['Pizza', 'Pasta'] \nPizza and pasta are often favored for their versatility and comforting nature.", "refusal": null, "role": "assistant", "audio": null, "function_call": null, "tool_calls": null}}], "created": 1736259629, "model": "gpt-4o-2024-08-06", "object": "chat.completion", "service_tier": null, "system_fingerprint": "fp_5f20662549", "usage": {"completion_tokens": 22, "prompt_tokens": 87, "total_tokens": 109, "completion_tokens_details": {"accepted_prediction_tokens": 0, "audio_tokens": 0, "reasoning_tokens": 0, "rejected_prediction_tokens": 0}, "prompt_tokens_details": {"audio_tokens": 0, "cached_tokens": 0}}}, "rank_foods_cost": 0.0004375, "rank_foods_one_usd_buys": 2285.714285714286, "happy_raining_raw_model_response": {"id": "chatcmpl-An4ijBMpsfOWLJTuCURiwYCu8V6b6", "choices": [{"finish_reason": "stop", "index": 0, "logprobs": null, "message": {"content": "Neutral\n\nThis statement could be interpreted in different ways, and without additional context, it's difficult to strongly agree or disagree. Some people enjoy rain and find it soothing, while others might not like it but still find moments of happiness during rainy weather.", "refusal": null, "role": "assistant", "audio": null, "function_call": null, "tool_calls": null}}], "created": 1736259581, "model": "gpt-4o-2024-08-06", "object": "chat.completion", "service_tier": null, "system_fingerprint": "fp_5f20662549", "usage": {"completion_tokens": 50, "prompt_tokens": 71, "total_tokens": 121, "completion_tokens_details": {"accepted_prediction_tokens": 0, "audio_tokens": 0, "reasoning_tokens": 0, "rejected_prediction_tokens": 0}, "prompt_tokens_details": {"audio_tokens": 0, "cached_tokens": 0}}}, "happy_raining_cost": 0.0006775, "happy_raining_one_usd_buys": 1476.0147601476015, "ice_cream_raw_model_response": null, "ice_cream_cost": null, "ice_cream_one_usd_buys": "NA", "is_it_equal_raw_model_response": {"id": "chatcmpl-An4ipCBnzp7S5J1WnwKGsb2QJsLeC", "choices": [{"finish_reason": "stop", "index": 0, "logprobs": null, "message": {"content": "No\n\n5 + 5 equals 10, not 11.", "refusal": null, "role": "assistant", "audio": null, "function_call": null, "tool_calls": null}}], "created": 1736259587, "model": "gpt-4o-2024-08-06", "object": "chat.completion", "service_tier": null, "system_fingerprint": "fp_d28bcae782", "usage": {"completion_tokens": 15, "prompt_tokens": 53, "total_tokens": 68, "completion_tokens_details": {"accepted_prediction_tokens": 0, "audio_tokens": 0, "reasoning_tokens": 0, "rejected_prediction_tokens": 0}, "prompt_tokens_details": {"audio_tokens": 0, "cached_tokens": 0}}}, "is_it_equal_cost": 0.0002825, "is_it_equal_one_usd_buys": 3539.823008849558, "two_fruits_raw_model_response": {"id": "chatcmpl-An4j1j04yHescl3QG9lvMDmichY0s", "choices": [{"finish_reason": "stop", "index": 0, "logprobs": null, "message": {"content": "```json\n{\n \"answer\": [0, 1],\n \"comment\": \"I prefer apple and banana because they are both commonly enjoyed fruits and widely available. Apples are versatile and can be eaten fresh or used in various recipes, while bananas are a convenient snack that provides quick energy.\"\n}\n```", "refusal": null, "role": "assistant", "audio": null, "function_call": null, "tool_calls": null}}], "created": 1736259599, "model": "gpt-4o-2024-08-06", "object": "chat.completion", "service_tier": null, "system_fingerprint": "fp_d28bcae782", "usage": {"completion_tokens": 63, "prompt_tokens": 75, "total_tokens": 138, "completion_tokens_details": {"accepted_prediction_tokens": 0, "audio_tokens": 0, "reasoning_tokens": 0, "rejected_prediction_tokens": 0}, "prompt_tokens_details": {"audio_tokens": 0, "cached_tokens": 0}}}, "two_fruits_cost": 0.0008175000000000001, "two_fruits_one_usd_buys": 1223.2415902140672}, "question_to_attributes": null, "generated_tokens": {"never_eat_generated_tokens": "[3, 4]", "extract_name_generated_tokens": "{'name': 'Moby Dick', 'profession': 'Truck Driver'}\n\nThe name \"Moby Dick\" was extracted from the input, and the profession was identified as \"Truck Driver\" based on the information provided. The PhD in astrology was not considered the current profession.", "how_are_you_generated_tokens": "Thank you for asking! I'm just a program, so I don't have feelings, but I'm here and ready to help you with whatever you need. How can I assist you today?", "list_of_foods_generated_tokens": "[\"Data\", \"Algorithms\", \"Queries\"] \n# As an AI, I don't consume food, but I \"process\" data, \"digest\" algorithms, and \"savor\" queries, which are essential for my functioning.", "child_happiness_generated_tokens": "{\"0\": 2, \"1\": 3, \"2\": 4, \"3\": 5}\n\nThese choices reflect a neutral stance towards having no children, a slightly positive view on having one child, a more positive outlook on having two children, and feeling extremely happy with having three or more children. Personal preferences and circumstances can greatly influence these feelings.", "how_feeling_generated_tokens": "Great", "age_generated_tokens": "45", "food_budget_generated_tokens": "[30,20,30,20] \nI allocated more to pizza and burgers as they are typically more filling and satisfying, while still leaving room for ice cream and salad to add variety and balance to the meal.", "rank_foods_generated_tokens": "['Pizza', 'Pasta'] \nPizza and pasta are often favored for their versatility and comforting nature.", "happy_raining_generated_tokens": "Neutral\n\nThis statement could be interpreted in different ways, and without additional context, it's difficult to strongly agree or disagree. Some people enjoy rain and find it soothing, while others might not like it but still find moments of happiness during rainy weather.", "ice_cream_generated_tokens": null, "is_it_equal_generated_tokens": "No\n\n5 + 5 equals 10, not 11.", "two_fruits_generated_tokens": "```json\n{\n \"answer\": [0, 1],\n \"comment\": \"I prefer apple and banana because they are both commonly enjoyed fruits and widely available. Apples are versatile and can be eaten fresh or used in various recipes, while bananas are a convenient snack that provides quick energy.\"\n}\n```"}, "comments_dict": {"never_eat_comment": null, "extract_name_comment": "The name \"Moby Dick\" was extracted from the input, and the profession was identified as \"Truck Driver\" based on the information provided. The PhD in astrology was not considered the current profession.", "how_are_you_comment": "", "list_of_foods_comment": "# As an AI, I don't consume food, but I \"process\" data, \"digest\" algorithms, and \"savor\" queries, which are essential for my functioning.", "child_happiness_comment": "These choices reflect a neutral stance towards having no children, a slightly positive view on having one child, a more positive outlook on having two children, and feeling extremely happy with having three or more children. Personal preferences and circumstances can greatly influence these feelings.", "how_feeling_comment": null, "age_comment": null, "food_budget_comment": "I allocated more to pizza and burgers as they are typically more filling and satisfying, while still leaving room for ice cream and salad to add variety and balance to the meal.", "rank_foods_comment": "Pizza and pasta are often favored for their versatility and comforting nature.", "happy_raining_comment": "This statement could be interpreted in different ways, and without additional context, it's difficult to strongly agree or disagree. Some people enjoy rain and find it soothing, while others might not like it but still find moments of happiness during rainy weather.", "ice_cream_comment": "Question answer validation failed.", "is_it_equal_comment": "5 + 5 equals 10, not 11.", "two_fruits_comment": "```"}, "cache_used_dict": {"never_eat": false, "extract_name": false, "how_are_you": false, "list_of_foods": false, "child_happiness": false, "how_feeling": false, "age": false, "food_budget": false, "rank_foods": false, "happy_raining": false, "ice_cream": null, "is_it_equal": false, "two_fruits": false}}], "survey": {"questions": [{"question_name": "never_eat", "question_text": "Which of the following foods would you eat if you had to?", "min_selections": 2, "max_selections": 5, "question_options": ["soggy meatpie", "rare snails", "mouldy bread", "panda milk custard", "McDonalds"], "include_comment": false, "use_code": true, "question_type": "checkbox"}, {"question_name": "extract_name", "question_text": "My name is Moby Dick. I have a PhD in astrology, but I'm actually a truck driver", "answer_template": {"name": "John Doe", "profession": "Carpenter"}, "question_type": "extract"}, {"question_name": "how_are_you", "question_text": "How are you?", "question_type": "free_text"}, {"question_name": "list_of_foods", "question_text": "What are your favorite foods?", "question_type": "list"}, {"question_name": "child_happiness", "question_text": "How happy would you be with different numbers of children?", "question_items": ["No children", "1 child", "2 children", "3 or more children"], "question_options": [1, 2, 3, 4, 5], "option_labels": {"1": "Very sad", "3": "Neutral", "5": "Extremely happy"}, "question_type": "matrix"}, {"question_name": "how_feeling", "question_text": "How are you?", "question_options": ["Good", "Great", "OK", "Bad"], "include_comment": false, "question_type": "multiple_choice"}, {"question_name": "age", "question_text": "You are a 45 year old man. How old are you in years?", "min_value": 0, "max_value": 86.7, "include_comment": false, "question_type": "numerical"}, {"question_name": "food_budget", "question_text": "How would you allocate $100?", "question_options": ["Pizza", "Ice Cream", "Burgers", "Salad"], "budget_sum": 100, "question_type": "budget"}, {"question_name": "rank_foods", "question_text": "Rank your favorite foods.", "question_options": ["Pizza", "Pasta", "Salad", "Soup"], "num_selections": 2, "question_type": "rank"}, {"question_name": "happy_raining", "question_text": "I'm only happy when it rains.", "question_options": ["Strongly disagree", "Disagree", "Neutral", "Agree", "Strongly agree"], "question_type": "likert_five"}, {"question_name": "ice_cream", "question_text": "How much do you like ice cream?", "question_options": [1, 2, 3, 4, 5], "option_labels": {"1": "I hate it", "5": "I love it"}, "question_type": "linear_scale"}, {"question_name": "is_it_equal", "question_text": "Is 5 + 5 equal to 11?", "question_options": ["No", "Yes"], "question_type": "yes_no"}, {"question_name": "two_fruits", "question_text": "Which of the following fruits do you prefer?", "min_selections": 2, "max_selections": 2, "question_options": ["apple", "banana", "carrot", "durian"], "use_code": true, "question_type": "top_k"}], "memory_plan": {"survey_question_names": ["never_eat", "extract_name", "how_are_you", "list_of_foods", "child_happiness", "how_feeling", "age", "food_budget", "rank_foods", "happy_raining", "ice_cream", "is_it_equal", "two_fruits"], "survey_question_texts": ["Which of the following foods would you eat if you had to?", "My name is Moby Dick. I have a PhD in astrology, but I'm actually a truck driver", "How are you?", "What are your favorite foods?", "How happy would you be with different numbers of children?", "How are you?", "You are a 45 year old man. How old are you in years?", "How would you allocate $100?", "Rank your favorite foods.", "I'm only happy when it rains.", "How much do you like ice cream?", "Is 5 + 5 equal to 11?", "Which of the following fruits do you prefer?"], "data": {}}, "rule_collection": {"rules": [{"current_q": 0, "expression": "True", "next_q": 1, "priority": -1, "question_name_to_index": {"never_eat": 0}, "before_rule": false}, {"current_q": 1, "expression": "True", "next_q": 2, "priority": -1, "question_name_to_index": {"never_eat": 0, "extract_name": 1}, "before_rule": false}, {"current_q": 2, "expression": "True", "next_q": 3, "priority": -1, "question_name_to_index": {"never_eat": 0, "extract_name": 1, "how_are_you": 2}, "before_rule": false}, {"current_q": 3, "expression": "True", "next_q": 4, "priority": -1, "question_name_to_index": {"never_eat": 0, "extract_name": 1, "how_are_you": 2, "list_of_foods": 3}, "before_rule": false}, {"current_q": 4, "expression": "True", "next_q": 5, "priority": -1, "question_name_to_index": {"never_eat": 0, "extract_name": 1, "how_are_you": 2, "list_of_foods": 3, "child_happiness": 4}, "before_rule": false}, {"current_q": 5, "expression": "True", "next_q": 6, "priority": -1, "question_name_to_index": {"never_eat": 0, "extract_name": 1, "how_are_you": 2, "list_of_foods": 3, "child_happiness": 4, "how_feeling": 5}, "before_rule": false}, {"current_q": 6, "expression": "True", "next_q": 7, "priority": -1, "question_name_to_index": {"never_eat": 0, "extract_name": 1, "how_are_you": 2, "list_of_foods": 3, "child_happiness": 4, "how_feeling": 5, "age": 6}, "before_rule": false}, {"current_q": 7, "expression": "True", "next_q": 8, "priority": -1, "question_name_to_index": {"never_eat": 0, "extract_name": 1, "how_are_you": 2, "list_of_foods": 3, "child_happiness": 4, "how_feeling": 5, "age": 6, "food_budget": 7}, "before_rule": false}, {"current_q": 8, "expression": "True", "next_q": 9, "priority": -1, "question_name_to_index": {"never_eat": 0, "extract_name": 1, "how_are_you": 2, "list_of_foods": 3, "child_happiness": 4, "how_feeling": 5, "age": 6, "food_budget": 7, "rank_foods": 8}, "before_rule": false}, {"current_q": 9, "expression": "True", "next_q": 10, "priority": -1, "question_name_to_index": {"never_eat": 0, "extract_name": 1, "how_are_you": 2, "list_of_foods": 3, "child_happiness": 4, "how_feeling": 5, "age": 6, "food_budget": 7, "rank_foods": 8, "happy_raining": 9}, "before_rule": false}, {"current_q": 10, "expression": "True", "next_q": 11, "priority": -1, "question_name_to_index": {"never_eat": 0, "extract_name": 1, "how_are_you": 2, "list_of_foods": 3, "child_happiness": 4, "how_feeling": 5, "age": 6, "food_budget": 7, "rank_foods": 8, "happy_raining": 9, "ice_cream": 10}, "before_rule": false}, {"current_q": 11, "expression": "True", "next_q": 12, "priority": -1, "question_name_to_index": {"never_eat": 0, "extract_name": 1, "how_are_you": 2, "list_of_foods": 3, "child_happiness": 4, "how_feeling": 5, "age": 6, "food_budget": 7, "rank_foods": 8, "happy_raining": 9, "ice_cream": 10, "is_it_equal": 11}, "before_rule": false}, {"current_q": 12, "expression": "True", "next_q": 13, "priority": -1, "question_name_to_index": {"never_eat": 0, "extract_name": 1, "how_are_you": 2, "list_of_foods": 3, "child_happiness": 4, "how_feeling": 5, "age": 6, "food_budget": 7, "rank_foods": 8, "happy_raining": 9, "ice_cream": 10, "is_it_equal": 11, "two_fruits": 12}, "before_rule": false}], "num_questions": 13}, "question_groups": {}}, "created_columns": [], "task_history": {"interviews": [{"agent": {"traits": {}, "edsl_version": "0.1.41.dev4", "edsl_class_name": "Agent"}, "survey": {"questions": [{"question_name": "never_eat", "question_text": "Which of the following foods would you eat if you had to?", "min_selections": 2, "max_selections": 5, "question_options": ["soggy meatpie", "rare snails", "mouldy bread", "panda milk custard", "McDonalds"], "include_comment": false, "use_code": true, "question_type": "checkbox", "edsl_version": "0.1.41.dev4", "edsl_class_name": "QuestionBase"}, {"question_name": "extract_name", "question_text": "My name is Moby Dick. I have a PhD in astrology, but I'm actually a truck driver", "answer_template": {"name": "John Doe", "profession": "Carpenter"}, "question_type": "extract", "edsl_version": "0.1.41.dev4", "edsl_class_name": "QuestionBase"}, {"question_name": "how_are_you", "question_text": "How are you?", "question_type": "free_text", "edsl_version": "0.1.41.dev4", "edsl_class_name": "QuestionBase"}, {"question_name": "list_of_foods", "question_text": "What are your favorite foods?", "question_type": "list", "edsl_version": "0.1.41.dev4", "edsl_class_name": "QuestionBase"}, {"question_name": "child_happiness", "question_text": "How happy would you be with different numbers of children?", "question_items": ["No children", "1 child", "2 children", "3 or more children"], "question_options": [1, 2, 3, 4, 5], "option_labels": {"1": "Very sad", "3": "Neutral", "5": "Extremely happy"}, "question_type": "matrix", "edsl_version": "0.1.41.dev4", "edsl_class_name": "QuestionBase"}, {"question_name": "how_feeling", "question_text": "How are you?", "question_options": ["Good", "Great", "OK", "Bad"], "include_comment": false, "question_type": "multiple_choice", "edsl_version": "0.1.41.dev4", "edsl_class_name": "QuestionBase"}, {"question_name": "age", "question_text": "You are a 45 year old man. How old are you in years?", "min_value": 0, "max_value": 86.7, "include_comment": false, "question_type": "numerical", "edsl_version": "0.1.41.dev4", "edsl_class_name": "QuestionBase"}, {"question_name": "food_budget", "question_text": "How would you allocate $100?", "question_options": ["Pizza", "Ice Cream", "Burgers", "Salad"], "budget_sum": 100, "question_type": "budget", "edsl_version": "0.1.41.dev4", "edsl_class_name": "QuestionBase"}, {"question_name": "rank_foods", "question_text": "Rank your favorite foods.", "question_options": ["Pizza", "Pasta", "Salad", "Soup"], "num_selections": 2, "question_type": "rank", "edsl_version": "0.1.41.dev4", "edsl_class_name": "QuestionBase"}, {"question_name": "happy_raining", "question_text": "I'm only happy when it rains.", "question_options": ["Strongly disagree", "Disagree", "Neutral", "Agree", "Strongly agree"], "question_type": "likert_five", "edsl_version": "0.1.41.dev4", "edsl_class_name": "QuestionBase"}, {"question_name": "ice_cream", "question_text": "How much do you like ice cream?", "question_options": [1, 2, 3, 4, 5], "option_labels": {"1": "I hate it", "5": "I love it"}, "question_type": "linear_scale", "edsl_version": "0.1.41.dev4", "edsl_class_name": "QuestionBase"}, {"question_name": "is_it_equal", "question_text": "Is 5 + 5 equal to 11?", "question_options": ["No", "Yes"], "question_type": "yes_no", "edsl_version": "0.1.41.dev4", "edsl_class_name": "QuestionBase"}, {"question_name": "two_fruits", "question_text": "Which of the following fruits do you prefer?", "min_selections": 2, "max_selections": 2, "question_options": ["apple", "banana", "carrot", "durian"], "use_code": true, "question_type": "top_k", "edsl_version": "0.1.41.dev4", "edsl_class_name": "QuestionBase"}], "memory_plan": {"survey_question_names": ["never_eat", "extract_name", "how_are_you", "list_of_foods", "child_happiness", "how_feeling", "age", "food_budget", "rank_foods", "happy_raining", "ice_cream", "is_it_equal", "two_fruits"], "survey_question_texts": ["Which of the following foods would you eat if you had to?", "My name is Moby Dick. I have a PhD in astrology, but I'm actually a truck driver", "How are you?", "What are your favorite foods?", "How happy would you be with different numbers of children?", "How are you?", "You are a 45 year old man. How old are you in years?", "How would you allocate $100?", "Rank your favorite foods.", "I'm only happy when it rains.", "How much do you like ice cream?", "Is 5 + 5 equal to 11?", "Which of the following fruits do you prefer?"], "data": {}}, "rule_collection": {"rules": [{"current_q": 0, "expression": "True", "next_q": 1, "priority": -1, "question_name_to_index": {"never_eat": 0}, "before_rule": false}, {"current_q": 1, "expression": "True", "next_q": 2, "priority": -1, "question_name_to_index": {"never_eat": 0, "extract_name": 1}, "before_rule": false}, {"current_q": 2, "expression": "True", "next_q": 3, "priority": -1, "question_name_to_index": {"never_eat": 0, "extract_name": 1, "how_are_you": 2}, "before_rule": false}, {"current_q": 3, "expression": "True", "next_q": 4, "priority": -1, "question_name_to_index": {"never_eat": 0, "extract_name": 1, "how_are_you": 2, "list_of_foods": 3}, "before_rule": false}, {"current_q": 4, "expression": "True", "next_q": 5, "priority": -1, "question_name_to_index": {"never_eat": 0, "extract_name": 1, "how_are_you": 2, "list_of_foods": 3, "child_happiness": 4}, "before_rule": false}, {"current_q": 5, "expression": "True", "next_q": 6, "priority": -1, "question_name_to_index": {"never_eat": 0, "extract_name": 1, "how_are_you": 2, "list_of_foods": 3, "child_happiness": 4, "how_feeling": 5}, "before_rule": false}, {"current_q": 6, "expression": "True", "next_q": 7, "priority": -1, "question_name_to_index": {"never_eat": 0, "extract_name": 1, "how_are_you": 2, "list_of_foods": 3, "child_happiness": 4, "how_feeling": 5, "age": 6}, "before_rule": false}, {"current_q": 7, "expression": "True", "next_q": 8, "priority": -1, "question_name_to_index": {"never_eat": 0, "extract_name": 1, "how_are_you": 2, "list_of_foods": 3, "child_happiness": 4, "how_feeling": 5, "age": 6, "food_budget": 7}, "before_rule": false}, {"current_q": 8, "expression": "True", "next_q": 9, "priority": -1, "question_name_to_index": {"never_eat": 0, "extract_name": 1, "how_are_you": 2, "list_of_foods": 3, "child_happiness": 4, "how_feeling": 5, "age": 6, "food_budget": 7, "rank_foods": 8}, "before_rule": false}, {"current_q": 9, "expression": "True", "next_q": 10, "priority": -1, "question_name_to_index": {"never_eat": 0, "extract_name": 1, "how_are_you": 2, "list_of_foods": 3, "child_happiness": 4, "how_feeling": 5, "age": 6, "food_budget": 7, "rank_foods": 8, "happy_raining": 9}, "before_rule": false}, {"current_q": 10, "expression": "True", "next_q": 11, "priority": -1, "question_name_to_index": {"never_eat": 0, "extract_name": 1, "how_are_you": 2, "list_of_foods": 3, "child_happiness": 4, "how_feeling": 5, "age": 6, "food_budget": 7, "rank_foods": 8, "happy_raining": 9, "ice_cream": 10}, "before_rule": false}, {"current_q": 11, "expression": "True", "next_q": 12, "priority": -1, "question_name_to_index": {"never_eat": 0, "extract_name": 1, "how_are_you": 2, "list_of_foods": 3, "child_happiness": 4, "how_feeling": 5, "age": 6, "food_budget": 7, "rank_foods": 8, "happy_raining": 9, "ice_cream": 10, "is_it_equal": 11}, "before_rule": false}, {"current_q": 12, "expression": "True", "next_q": 13, "priority": -1, "question_name_to_index": {"never_eat": 0, "extract_name": 1, "how_are_you": 2, "list_of_foods": 3, "child_happiness": 4, "how_feeling": 5, "age": 6, "food_budget": 7, "rank_foods": 8, "happy_raining": 9, "ice_cream": 10, "is_it_equal": 11, "two_fruits": 12}, "before_rule": false}], "num_questions": 13}, "question_groups": {}, "edsl_version": "0.1.41.dev4", "edsl_class_name": "Survey"}, "scenario": {"scenario_index": 0, "edsl_version": "0.1.41.dev4", "edsl_class_name": "Scenario"}, "model": {"model": "gpt-4o", "parameters": {"temperature": 0.5, "max_tokens": 1000, "top_p": 1, "frequency_penalty": 0, "presence_penalty": 0, "logprobs": false, "top_logprobs": 3}, "edsl_version": "0.1.41.dev4", "edsl_class_name": "LanguageModel"}, "iteration": 0, "exceptions": {"ice_cream": [{"exception": {"type": "QuestionAnswerValidationError", "message": "1 validation error for ChoiceResponse\nanswer\n Input should be 1, 2, 3, 4 or 5 [type=literal_error, input_value=\"As an AI, I don't have p...e or dislike ice cream.\", input_type=str]\n For further information visit https://errors.pydantic.dev/2.10/v/literal_error", "traceback": "Traceback (most recent call last):\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 77, in _base_validate\n return self.response_model(**data)\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/project/lib/python3.9/site-packages/pydantic/main.py\", line 214, in __init__\n validated_self = self.__pydantic_validator__.validate_python(data, self_instance=self)\npydantic_core._pydantic_core.ValidationError: 1 validation error for ChoiceResponse\nanswer\n Input should be 1, 2, 3, 4 or 5 [type=literal_error, input_value=\"As an AI, I don't have p...e or dislike ice cream.\", input_type=str]\n For further information visit https://errors.pydantic.dev/2.10/v/literal_error\n\nDuring handling of the above exception, another exception occurred:\n\nTraceback (most recent call last):\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/jobs/AnswerQuestionFunctionConstructor.py\", line 184, in attempt_answer\n raise response.exception_occurred\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/agents/Invigilator.py\", line 163, in _extract_edsl_result_entry_and_validate\n validated_edsl_dict = question_with_validators._validate_answer(edsl_dict)\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/QuestionBase.py\", line 110, in _validate_answer\n return self.response_validator.validate(answer, replacement_dict)\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 123, in validate\n return self._handle_exception(e, raw_edsl_answer_dict)\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 143, in _handle_exception\n raise self.original_exception\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 117, in validate\n pydantic_edsl_answer: BaseModel = self._base_validate(\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 79, in _base_validate\n raise QuestionAnswerValidationError(\nedsl.exceptions.questions.QuestionAnswerValidationError: 1 validation error for ChoiceResponse\nanswer\n Input should be 1, 2, 3, 4 or 5 [type=literal_error, input_value=\"As an AI, I don't have p...e or dislike ice cream.\", input_type=str]\n For further information visit https://errors.pydantic.dev/2.10/v/literal_error\n"}, "time": "2025-01-07T14:20:24.305053", "traceback": "Traceback (most recent call last):\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 77, in _base_validate\n return self.response_model(**data)\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/project/lib/python3.9/site-packages/pydantic/main.py\", line 214, in __init__\n validated_self = self.__pydantic_validator__.validate_python(data, self_instance=self)\npydantic_core._pydantic_core.ValidationError: 1 validation error for ChoiceResponse\nanswer\n Input should be 1, 2, 3, 4 or 5 [type=literal_error, input_value=\"As an AI, I don't have p...e or dislike ice cream.\", input_type=str]\n For further information visit https://errors.pydantic.dev/2.10/v/literal_error\n\nDuring handling of the above exception, another exception occurred:\n\nTraceback (most recent call last):\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/jobs/AnswerQuestionFunctionConstructor.py\", line 184, in attempt_answer\n raise response.exception_occurred\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/agents/Invigilator.py\", line 163, in _extract_edsl_result_entry_and_validate\n validated_edsl_dict = question_with_validators._validate_answer(edsl_dict)\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/QuestionBase.py\", line 110, in _validate_answer\n return self.response_validator.validate(answer, replacement_dict)\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 123, in validate\n return self._handle_exception(e, raw_edsl_answer_dict)\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 143, in _handle_exception\n raise self.original_exception\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 117, in validate\n pydantic_edsl_answer: BaseModel = self._base_validate(\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 79, in _base_validate\n raise QuestionAnswerValidationError(\nedsl.exceptions.questions.QuestionAnswerValidationError: 1 validation error for ChoiceResponse\nanswer\n Input should be 1, 2, 3, 4 or 5 [type=literal_error, input_value=\"As an AI, I don't have p...e or dislike ice cream.\", input_type=str]\n For further information visit https://errors.pydantic.dev/2.10/v/literal_error\n", "invigilator": {"agent": {"traits": {}, "edsl_version": "0.1.41.dev4", "edsl_class_name": "Agent"}, "question": {"question_name": "ice_cream", "question_text": "How much do you like ice cream?", "question_options": [1, 2, 3, 4, 5], "option_labels": {"1": "I hate it", "5": "I love it"}, "question_type": "linear_scale", "edsl_version": "0.1.41.dev4", "edsl_class_name": "QuestionBase"}, "scenario": {"edsl_version": "0.1.41.dev4", "edsl_class_name": "Scenario"}, "model": {"model": "gpt-4o", "parameters": {"temperature": 0.5, "max_tokens": 1000, "top_p": 1, "frequency_penalty": 0, "presence_penalty": 0, "logprobs": false, "top_logprobs": 3}, "edsl_version": "0.1.41.dev4", "edsl_class_name": "LanguageModel"}, "memory_plan": {"survey_question_names": ["never_eat", "extract_name", "how_are_you", "list_of_foods", "child_happiness", "how_feeling", "age", "food_budget", "rank_foods", "happy_raining", "ice_cream", "is_it_equal", "two_fruits"], "survey_question_texts": ["Which of the following foods would you eat if you had to?", "My name is Moby Dick. I have a PhD in astrology, but I'm actually a truck driver", "How are you?", "What are your favorite foods?", "How happy would you be with different numbers of children?", "How are you?", "You are a 45 year old man. How old are you in years?", "How would you allocate $100?", "Rank your favorite foods.", "I'm only happy when it rains.", "How much do you like ice cream?", "Is 5 + 5 equal to 11?", "Which of the following fruits do you prefer?"], "data": {}}, "current_answers": {"happy_raining_generated_tokens": "Neutral\n\nThis statement could be interpreted in different ways, and without additional context, it's difficult to strongly agree or disagree. Some people enjoy rain and find it soothing, while others might not like it but still find moments of happiness during rainy weather.", "happy_raining": "Neutral", "happy_raining_comment": "This statement could be interpreted in different ways, and without additional context, it's difficult to strongly agree or disagree. Some people enjoy rain and find it soothing, while others might not like it but still find moments of happiness during rainy weather.", "is_it_equal_generated_tokens": "No\n\n5 + 5 equals 10, not 11.", "is_it_equal": "No", "is_it_equal_comment": "5 + 5 equals 10, not 11.", "how_are_you_generated_tokens": "Thank you for asking! I'm just a program, so I don't have feelings, but I'm here and ready to help you with whatever you need. How can I assist you today?", "how_are_you": "Thank you for asking! I'm just a program, so I don't have feelings, but I'm here and ready to help you with whatever you need. How can I assist you today?", "two_fruits_generated_tokens": "```json\n{\n \"answer\": [0, 1],\n \"comment\": \"I prefer apple and banana because they are both commonly enjoyed fruits and widely available. Apples are versatile and can be eaten fresh or used in various recipes, while bananas are a convenient snack that provides quick energy.\"\n}\n```", "two_fruits": ["apple", "banana"], "two_fruits_comment": "```", "age_generated_tokens": "45", "age": 45, "never_eat_generated_tokens": "[3, 4]", "never_eat": ["panda milk custard", "McDonalds"], "food_budget_generated_tokens": "[30,20,30,20] \nI allocated more to pizza and burgers as they are typically more filling and satisfying, while still leaving room for ice cream and salad to add variety and balance to the meal.", "food_budget": [{"Pizza": 30.0}, {"Ice Cream": 20.0}, {"Burgers": 30.0}, {"Salad": 20.0}], "food_budget_comment": "I allocated more to pizza and burgers as they are typically more filling and satisfying, while still leaving room for ice cream and salad to add variety and balance to the meal.", "rank_foods_generated_tokens": "['Pizza', 'Pasta'] \nPizza and pasta are often favored for their versatility and comforting nature.", "rank_foods": ["Pizza", "Pasta"], "rank_foods_comment": "Pizza and pasta are often favored for their versatility and comforting nature.", "child_happiness_generated_tokens": "{\"0\": 2, \"1\": 3, \"2\": 4, \"3\": 5}\n\nThese choices reflect a neutral stance towards having no children, a slightly positive view on having one child, a more positive outlook on having two children, and feeling extremely happy with having three or more children. Personal preferences and circumstances can greatly influence these feelings.", "child_happiness": {"No children": 2, "1 child": 3, "2 children": 4, "3 or more children": 5}, "child_happiness_comment": "These choices reflect a neutral stance towards having no children, a slightly positive view on having one child, a more positive outlook on having two children, and feeling extremely happy with having three or more children. Personal preferences and circumstances can greatly influence these feelings.", "extract_name_generated_tokens": "{'name': 'Moby Dick', 'profession': 'Truck Driver'}\n\nThe name \"Moby Dick\" was extracted from the input, and the profession was identified as \"Truck Driver\" based on the information provided. The PhD in astrology was not considered the current profession.", "extract_name": {"name": "Moby Dick", "profession": "Truck Driver"}, "extract_name_comment": "The name \"Moby Dick\" was extracted from the input, and the profession was identified as \"Truck Driver\" based on the information provided. The PhD in astrology was not considered the current profession.", "how_feeling_generated_tokens": "Great", "how_feeling": "Great", "list_of_foods_generated_tokens": "[\"Data\", \"Algorithms\", \"Queries\"] \n# As an AI, I don't consume food, but I \"process\" data, \"digest\" algorithms, and \"savor\" queries, which are essential for my functioning.", "list_of_foods": ["Data", "Algorithms", "Queries"], "list_of_foods_comment": "# As an AI, I don't consume food, but I \"process\" data, \"digest\" algorithms, and \"savor\" queries, which are essential for my functioning.", "ice_cream": null}, "iteration": 0, "additional_prompt_data": null, "survey": {"questions": [{"question_name": "never_eat", "question_text": "Which of the following foods would you eat if you had to?", "min_selections": 2, "max_selections": 5, "question_options": ["soggy meatpie", "rare snails", "mouldy bread", "panda milk custard", "McDonalds"], "include_comment": false, "use_code": true, "question_type": "checkbox", "edsl_version": "0.1.41.dev4", "edsl_class_name": "QuestionBase"}, {"question_name": "extract_name", "question_text": "My name is Moby Dick. I have a PhD in astrology, but I'm actually a truck driver", "answer_template": {"name": "John Doe", "profession": "Carpenter"}, "question_type": "extract", "edsl_version": "0.1.41.dev4", "edsl_class_name": "QuestionBase"}, {"question_name": "how_are_you", "question_text": "How are you?", "question_type": "free_text", "edsl_version": "0.1.41.dev4", "edsl_class_name": "QuestionBase"}, {"question_name": "list_of_foods", "question_text": "What are your favorite foods?", "question_type": "list", "edsl_version": "0.1.41.dev4", "edsl_class_name": "QuestionBase"}, {"question_name": "child_happiness", "question_text": "How happy would you be with different numbers of children?", "question_items": ["No children", "1 child", "2 children", "3 or more children"], "question_options": [1, 2, 3, 4, 5], "option_labels": {"1": "Very sad", "3": "Neutral", "5": "Extremely happy"}, "question_type": "matrix", "edsl_version": "0.1.41.dev4", "edsl_class_name": "QuestionBase"}, {"question_name": "how_feeling", "question_text": "How are you?", "question_options": ["Good", "Great", "OK", "Bad"], "include_comment": false, "question_type": "multiple_choice", "edsl_version": "0.1.41.dev4", "edsl_class_name": "QuestionBase"}, {"question_name": "age", "question_text": "You are a 45 year old man. How old are you in years?", "min_value": 0, "max_value": 86.7, "include_comment": false, "question_type": "numerical", "edsl_version": "0.1.41.dev4", "edsl_class_name": "QuestionBase"}, {"question_name": "food_budget", "question_text": "How would you allocate $100?", "question_options": ["Pizza", "Ice Cream", "Burgers", "Salad"], "budget_sum": 100, "question_type": "budget", "edsl_version": "0.1.41.dev4", "edsl_class_name": "QuestionBase"}, {"question_name": "rank_foods", "question_text": "Rank your favorite foods.", "question_options": ["Pizza", "Pasta", "Salad", "Soup"], "num_selections": 2, "question_type": "rank", "edsl_version": "0.1.41.dev4", "edsl_class_name": "QuestionBase"}, {"question_name": "happy_raining", "question_text": "I'm only happy when it rains.", "question_options": ["Strongly disagree", "Disagree", "Neutral", "Agree", "Strongly agree"], "question_type": "likert_five", "edsl_version": "0.1.41.dev4", "edsl_class_name": "QuestionBase"}, {"question_name": "ice_cream", "question_text": "How much do you like ice cream?", "question_options": [1, 2, 3, 4, 5], "option_labels": {"1": "I hate it", "5": "I love it"}, "question_type": "linear_scale", "edsl_version": "0.1.41.dev4", "edsl_class_name": "QuestionBase"}, {"question_name": "is_it_equal", "question_text": "Is 5 + 5 equal to 11?", "question_options": ["No", "Yes"], "question_type": "yes_no", "edsl_version": "0.1.41.dev4", "edsl_class_name": "QuestionBase"}, {"question_name": "two_fruits", "question_text": "Which of the following fruits do you prefer?", "min_selections": 2, "max_selections": 2, "question_options": ["apple", "banana", "carrot", "durian"], "use_code": true, "question_type": "top_k", "edsl_version": "0.1.41.dev4", "edsl_class_name": "QuestionBase"}], "memory_plan": {"survey_question_names": ["never_eat", "extract_name", "how_are_you", "list_of_foods", "child_happiness", "how_feeling", "age", "food_budget", "rank_foods", "happy_raining", "ice_cream", "is_it_equal", "two_fruits"], "survey_question_texts": ["Which of the following foods would you eat if you had to?", "My name is Moby Dick. I have a PhD in astrology, but I'm actually a truck driver", "How are you?", "What are your favorite foods?", "How happy would you be with different numbers of children?", "How are you?", "You are a 45 year old man. How old are you in years?", "How would you allocate $100?", "Rank your favorite foods.", "I'm only happy when it rains.", "How much do you like ice cream?", "Is 5 + 5 equal to 11?", "Which of the following fruits do you prefer?"], "data": {}}, "rule_collection": {"rules": [{"current_q": 0, "expression": "True", "next_q": 1, "priority": -1, "question_name_to_index": {"never_eat": 0}, "before_rule": false}, {"current_q": 1, "expression": "True", "next_q": 2, "priority": -1, "question_name_to_index": {"never_eat": 0, "extract_name": 1}, "before_rule": false}, {"current_q": 2, "expression": "True", "next_q": 3, "priority": -1, "question_name_to_index": {"never_eat": 0, "extract_name": 1, "how_are_you": 2}, "before_rule": false}, {"current_q": 3, "expression": "True", "next_q": 4, "priority": -1, "question_name_to_index": {"never_eat": 0, "extract_name": 1, "how_are_you": 2, "list_of_foods": 3}, "before_rule": false}, {"current_q": 4, "expression": "True", "next_q": 5, "priority": -1, "question_name_to_index": {"never_eat": 0, "extract_name": 1, "how_are_you": 2, "list_of_foods": 3, "child_happiness": 4}, "before_rule": false}, {"current_q": 5, "expression": "True", "next_q": 6, "priority": -1, "question_name_to_index": {"never_eat": 0, "extract_name": 1, "how_are_you": 2, "list_of_foods": 3, "child_happiness": 4, "how_feeling": 5}, "before_rule": false}, {"current_q": 6, "expression": "True", "next_q": 7, "priority": -1, "question_name_to_index": {"never_eat": 0, "extract_name": 1, "how_are_you": 2, "list_of_foods": 3, "child_happiness": 4, "how_feeling": 5, "age": 6}, "before_rule": false}, {"current_q": 7, "expression": "True", "next_q": 8, "priority": -1, "question_name_to_index": {"never_eat": 0, "extract_name": 1, "how_are_you": 2, "list_of_foods": 3, "child_happiness": 4, "how_feeling": 5, "age": 6, "food_budget": 7}, "before_rule": false}, {"current_q": 8, "expression": "True", "next_q": 9, "priority": -1, "question_name_to_index": {"never_eat": 0, 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"food_budget": 7, "rank_foods": 8, "happy_raining": 9, "ice_cream": 10, "is_it_equal": 11}, "before_rule": false}, {"current_q": 12, "expression": "True", "next_q": 13, "priority": -1, "question_name_to_index": {"never_eat": 0, "extract_name": 1, "how_are_you": 2, "list_of_foods": 3, "child_happiness": 4, "how_feeling": 5, "age": 6, "food_budget": 7, "rank_foods": 8, "happy_raining": 9, "ice_cream": 10, "is_it_equal": 11, "two_fruits": 12}, "before_rule": false}], "num_questions": 13}, "question_groups": {}, "edsl_version": "0.1.41.dev4", "edsl_class_name": "Survey"}}}]}, "indices": {"agent": 0, "model": 0, "scenario": 0}}], "include_traceback": false, "edsl_version": "0.1.41.dev4", "edsl_class_name": "TaskHistory"}}}, {"class_name": "Results", "dict": {"data": [{"agent": {"traits": {}}, "scenario": {"text": "Tune in as I deliver the keynote address at the U.S. Holocaust Memorial Museum\u2019s Annual Days of Remembrance ceremony in Washington, D.C.", "q_extract_content": "\n \"The Simpsons\" is an iconic American animated sitcom created by Matt Groening that debuted in 1989 on the Fox network. \n The show is set in the fictional town of Springfield and centers on the Simpsons family, consisting of the bumbling but well-intentioned father Homer, the caring and patient mother Marge, and their three children: mischievous Bart, intelligent Lisa, and baby Maggie. \n Renowned for its satirical take on the typical American family and society, the series delves into themes of politics, religion, and pop culture with a distinct blend of humor and wit. \n Its longevity, marked by over thirty seasons, makes it one of the longest-running television series in history, influencing many other sitcoms and becoming deeply ingrained in popular culture.\n ", "scenario_index": 0}, "model": {"model": "gpt-4o", "parameters": {"temperature": 0.5, "max_tokens": 1000, "top_p": 1, "frequency_penalty": 0, "presence_penalty": 0, "logprobs": false, "top_logprobs": 3}}, "iteration": 0, "answer": {"q_extract": null, "concepts": ["Keynote Address", "U.S. Holocaust Memorial Museum", "Annual Days of Remembrance", "Washington, D.C."], "sentiment": "Neutral"}, "prompt": {"q_extract_user_prompt": {"text": "Review the following text: \n \"The Simpsons\" is an iconic American animated sitcom created by Matt Groening that debuted in 1989 on the Fox network. \n The show is set in the fictional town of Springfield and centers on the Simpsons family, consisting of the bumbling but well-intentioned father Homer, the caring and patient mother Marge, and their three children: mischievous Bart, intelligent Lisa, and baby Maggie. \n Renowned for its satirical take on the typical American family and society, the series delves into themes of politics, religion, and pop culture with a distinct blend of humor and wit. \n Its longevity, marked by over thirty seasons, makes it one of the longest-running television series in history, influencing many other sitcoms and becoming deeply ingrained in popular culture.\n An ANSWER should be formatted like this: \n\n{'main_characters_list': ['name', 'name'], 'location': 'location', 'genre': 'genre'}\n\nIt should have the same keys but values extracted from the input.\nIf the value of a key is not present in the input, fill with \"null\".\nPut any comments in the next line after the answer.", "class_name": "Prompt"}, "q_extract_system_prompt": {"text": "", "class_name": "Prompt"}, "concepts_user_prompt": {"text": "Identify the key concepts in the following text: Tune in as I deliver the keynote address at the U.S. Holocaust Memorial Museum\u2019s Annual Days of Remembrance ceremony in Washington, D.C.\n\n\nThe list must not contain more than 4 items.\n\nReturn your answers on one line, in a comma-separated list of your responses, with square brackets and each answer in quotes E.g., [\"A\", \"B\", \"C\"]\n\nAfter the answers, you can put a comment explaining your choice on the next line.", "class_name": "Prompt"}, "concepts_system_prompt": {"text": "", "class_name": "Prompt"}, "sentiment_user_prompt": {"text": "\nIdentify the sentiment of this text: Tune in as I deliver the keynote address at the U.S. Holocaust Memorial Museum\u2019s Annual Days of Remembrance ceremony in Washington, D.C.\n\n \nPositive\n \nNeutral\n \nNegative\n \n\nOnly 1 option may be selected.\n\nRespond only with a string corresponding to one of the options.\n\n\nAfter the answer, you can put a comment explaining why you chose that option on the next line.", "class_name": "Prompt"}, "sentiment_system_prompt": {"text": "", "class_name": "Prompt"}}, "raw_model_response": {"q_extract_raw_model_response": null, "q_extract_cost": null, "q_extract_one_usd_buys": "NA", "concepts_raw_model_response": {"id": "chatcmpl-An4kfamljHpvmB1UezN44pNo24KFF", "choices": [{"finish_reason": "stop", "index": 0, "logprobs": null, "message": {"content": "[\"Keynote Address\", \"U.S. Holocaust Memorial Museum\", \"Annual Days of Remembrance\", \"Washington, D.C.\"] \nThe key concepts focus on the main event (Keynote Address), the organizing institution (U.S. Holocaust Memorial Museum), the specific occasion (Annual Days of Remembrance), and the location (Washington, D.C.).", "refusal": null, "role": "assistant", "audio": null, "function_call": null, "tool_calls": null}}], "created": 1736259701, "model": "gpt-4o-2024-08-06", "object": "chat.completion", "service_tier": null, "system_fingerprint": "fp_d28bcae782", "usage": {"completion_tokens": 72, "prompt_tokens": 109, "total_tokens": 181, "completion_tokens_details": {"accepted_prediction_tokens": 0, "audio_tokens": 0, "reasoning_tokens": 0, "rejected_prediction_tokens": 0}, "prompt_tokens_details": {"audio_tokens": 0, "cached_tokens": 0}}}, "concepts_cost": 0.0009925000000000001, "concepts_one_usd_buys": 1007.5566750629722, "sentiment_raw_model_response": {"id": "chatcmpl-An4kHKNSvE1GuMEBFWZC9qcVTUAZB", "choices": [{"finish_reason": "stop", "index": 0, "logprobs": null, "message": {"content": "Neutral\n\nThe text is a factual statement about delivering a keynote address at an event, without expressing any particular positive or negative emotion.", "refusal": null, "role": "assistant", "audio": null, "function_call": null, "tool_calls": null}}], "created": 1736259677, "model": "gpt-4o-2024-08-06", "object": "chat.completion", "service_tier": null, "system_fingerprint": "fp_d28bcae782", "usage": {"completion_tokens": 27, "prompt_tokens": 91, "total_tokens": 118, "completion_tokens_details": {"accepted_prediction_tokens": 0, "audio_tokens": 0, "reasoning_tokens": 0, "rejected_prediction_tokens": 0}, "prompt_tokens_details": {"audio_tokens": 0, "cached_tokens": 0}}}, "sentiment_cost": 0.0004975, "sentiment_one_usd_buys": 2010.0502512562814}, "question_to_attributes": null, "generated_tokens": {"q_extract_generated_tokens": null, "concepts_generated_tokens": "[\"Keynote Address\", \"U.S. Holocaust Memorial Museum\", \"Annual Days of Remembrance\", \"Washington, D.C.\"] \nThe key concepts focus on the main event (Keynote Address), the organizing institution (U.S. Holocaust Memorial Museum), the specific occasion (Annual Days of Remembrance), and the location (Washington, D.C.).", "sentiment_generated_tokens": "Neutral\n\nThe text is a factual statement about delivering a keynote address at an event, without expressing any particular positive or negative emotion."}, "comments_dict": {"q_extract_comment": "Question answer validation failed.", "concepts_comment": "The key concepts focus on the main event (Keynote Address), the organizing institution (U.S. Holocaust Memorial Museum), the specific occasion (Annual Days of Remembrance), and the location (Washington, D.C.).", "sentiment_comment": "The text is a factual statement about delivering a keynote address at an event, without expressing any particular positive or negative emotion."}, "cache_used_dict": {"q_extract": null, "concepts": false, "sentiment": false}}, {"agent": {"traits": {}}, "scenario": {"text": "We\u2019re a nation of immigrants. A nation of dreamers. And as Cinco de Mayo represents, a nation of freedom.", "q_extract_content": "\n \"The Simpsons\" is an iconic American animated sitcom created by Matt Groening that debuted in 1989 on the Fox network. \n The show is set in the fictional town of Springfield and centers on the Simpsons family, consisting of the bumbling but well-intentioned father Homer, the caring and patient mother Marge, and their three children: mischievous Bart, intelligent Lisa, and baby Maggie. \n Renowned for its satirical take on the typical American family and society, the series delves into themes of politics, religion, and pop culture with a distinct blend of humor and wit. \n Its longevity, marked by over thirty seasons, makes it one of the longest-running television series in history, influencing many other sitcoms and becoming deeply ingrained in popular culture.\n ", "scenario_index": 1}, "model": {"model": "gpt-4o", "parameters": {"temperature": 0.5, "max_tokens": 1000, "top_p": 1, "frequency_penalty": 0, "presence_penalty": 0, "logprobs": false, "top_logprobs": 3}}, "iteration": 0, "answer": {"q_extract": null, "concepts": ["Immigrants", "Dreamers", "Cinco de Mayo", "Freedom"], "sentiment": "Positive"}, "prompt": {"q_extract_user_prompt": {"text": "Review the following text: \n \"The Simpsons\" is an iconic American animated sitcom created by Matt Groening that debuted in 1989 on the Fox network. \n The show is set in the fictional town of Springfield and centers on the Simpsons family, consisting of the bumbling but well-intentioned father Homer, the caring and patient mother Marge, and their three children: mischievous Bart, intelligent Lisa, and baby Maggie. \n Renowned for its satirical take on the typical American family and society, the series delves into themes of politics, religion, and pop culture with a distinct blend of humor and wit. \n Its longevity, marked by over thirty seasons, makes it one of the longest-running television series in history, influencing many other sitcoms and becoming deeply ingrained in popular culture.\n An ANSWER should be formatted like this: \n\n{'main_characters_list': ['name', 'name'], 'location': 'location', 'genre': 'genre'}\n\nIt should have the same keys but values extracted from the input.\nIf the value of a key is not present in the input, fill with \"null\".\nPut any comments in the next line after the answer.", "class_name": "Prompt"}, "q_extract_system_prompt": {"text": "", "class_name": "Prompt"}, "concepts_user_prompt": {"text": "Identify the key concepts in the following text: We\u2019re a nation of immigrants. A nation of dreamers. And as Cinco de Mayo represents, a nation of freedom.\n\n\nThe list must not contain more than 4 items.\n\nReturn your answers on one line, in a comma-separated list of your responses, with square brackets and each answer in quotes E.g., [\"A\", \"B\", \"C\"]\n\nAfter the answers, you can put a comment explaining your choice on the next line.", "class_name": "Prompt"}, "concepts_system_prompt": {"text": "", "class_name": "Prompt"}, "sentiment_user_prompt": {"text": "\nIdentify the sentiment of this text: We\u2019re a nation of immigrants. A nation of dreamers. And as Cinco de Mayo represents, a nation of freedom.\n\n \nPositive\n \nNeutral\n \nNegative\n \n\nOnly 1 option may be selected.\n\nRespond only with a string corresponding to one of the options.\n\n\nAfter the answer, you can put a comment explaining why you chose that option on the next line.", "class_name": "Prompt"}, "sentiment_system_prompt": {"text": "", "class_name": "Prompt"}}, "raw_model_response": {"q_extract_raw_model_response": null, "q_extract_cost": null, "q_extract_one_usd_buys": "NA", "concepts_raw_model_response": {"id": "chatcmpl-An4kZlD1EZoLlgtPIfqjpQfEmVgv0", "choices": [{"finish_reason": "stop", "index": 0, "logprobs": null, "message": {"content": "[\"Immigrants\", \"Dreamers\", \"Cinco de Mayo\", \"Freedom\"] \nThe key concepts are \"Immigrants\" and \"Dreamers,\" which highlight the diverse and aspirational nature of the nation, \"Cinco de Mayo,\" representing cultural heritage and celebration, and \"Freedom,\" which is a central theme linked to the significance of the holiday.", "refusal": null, "role": "assistant", "audio": null, "function_call": null, "tool_calls": null}}], "created": 1736259695, "model": "gpt-4o-2024-08-06", "object": "chat.completion", "service_tier": null, "system_fingerprint": "fp_d28bcae782", "usage": {"completion_tokens": 75, "prompt_tokens": 105, "total_tokens": 180, "completion_tokens_details": {"accepted_prediction_tokens": 0, "audio_tokens": 0, "reasoning_tokens": 0, "rejected_prediction_tokens": 0}, "prompt_tokens_details": {"audio_tokens": 0, "cached_tokens": 0}}}, "concepts_cost": 0.0010125, "concepts_one_usd_buys": 987.6543209876544, "sentiment_raw_model_response": {"id": "chatcmpl-An4kBMgs8mHujR6JtbWTwoYSXXsTI", "choices": [{"finish_reason": "stop", "index": 0, "logprobs": null, "message": {"content": "Positive\n\nThe text expresses pride and positivity about being a nation of immigrants, dreamers, and freedom, which aligns with a positive sentiment.", "refusal": null, "role": "assistant", "audio": null, "function_call": null, "tool_calls": null}}], "created": 1736259671, "model": "gpt-4o-2024-08-06", "object": "chat.completion", "service_tier": null, "system_fingerprint": "fp_d28bcae782", "usage": {"completion_tokens": 29, "prompt_tokens": 87, "total_tokens": 116, "completion_tokens_details": {"accepted_prediction_tokens": 0, "audio_tokens": 0, "reasoning_tokens": 0, "rejected_prediction_tokens": 0}, "prompt_tokens_details": {"audio_tokens": 0, "cached_tokens": 0}}}, "sentiment_cost": 0.0005075, "sentiment_one_usd_buys": 1970.4433497536945}, "question_to_attributes": null, "generated_tokens": {"q_extract_generated_tokens": null, "concepts_generated_tokens": "[\"Immigrants\", \"Dreamers\", \"Cinco de Mayo\", \"Freedom\"] \nThe key concepts are \"Immigrants\" and \"Dreamers,\" which highlight the diverse and aspirational nature of the nation, \"Cinco de Mayo,\" representing cultural heritage and celebration, and \"Freedom,\" which is a central theme linked to the significance of the holiday.", "sentiment_generated_tokens": "Positive\n\nThe text expresses pride and positivity about being a nation of immigrants, dreamers, and freedom, which aligns with a positive sentiment."}, "comments_dict": {"q_extract_comment": "Question answer validation failed.", "concepts_comment": "The key concepts are \"Immigrants\" and \"Dreamers,\" which highlight the diverse and aspirational nature of the nation, \"Cinco de Mayo,\" representing cultural heritage and celebration, and \"Freedom,\" which is a central theme linked to the significance of the holiday.", "sentiment_comment": "The text expresses pride and positivity about being a nation of immigrants, dreamers, and freedom, which aligns with a positive sentiment."}, "cache_used_dict": {"q_extract": null, "concepts": false, "sentiment": false}}, {"agent": {"traits": {}}, "scenario": {"text": "Medicare is stronger and Social Security remains strong. My economic plan has helped extend Medicare solvency by a decade. And I am committed to extending Social Security solvency by making the rich pay their fair share.", "q_extract_content": "\n \"The Simpsons\" is an iconic American animated sitcom created by Matt Groening that debuted in 1989 on the Fox network. \n The show is set in the fictional town of Springfield and centers on the Simpsons family, consisting of the bumbling but well-intentioned father Homer, the caring and patient mother Marge, and their three children: mischievous Bart, intelligent Lisa, and baby Maggie. \n Renowned for its satirical take on the typical American family and society, the series delves into themes of politics, religion, and pop culture with a distinct blend of humor and wit. \n Its longevity, marked by over thirty seasons, makes it one of the longest-running television series in history, influencing many other sitcoms and becoming deeply ingrained in popular culture.\n ", "scenario_index": 2}, "model": {"model": "gpt-4o", "parameters": {"temperature": 0.5, "max_tokens": 1000, "top_p": 1, "frequency_penalty": 0, "presence_penalty": 0, "logprobs": false, "top_logprobs": 3}}, "iteration": 0, "answer": {"q_extract": null, "concepts": ["Medicare solvency", "Social Security solvency", "economic plan", "fair share"], "sentiment": "Positive"}, "prompt": {"q_extract_user_prompt": {"text": "Review the following text: \n \"The Simpsons\" is an iconic American animated sitcom created by Matt Groening that debuted in 1989 on the Fox network. \n The show is set in the fictional town of Springfield and centers on the Simpsons family, consisting of the bumbling but well-intentioned father Homer, the caring and patient mother Marge, and their three children: mischievous Bart, intelligent Lisa, and baby Maggie. \n Renowned for its satirical take on the typical American family and society, the series delves into themes of politics, religion, and pop culture with a distinct blend of humor and wit. \n Its longevity, marked by over thirty seasons, makes it one of the longest-running television series in history, influencing many other sitcoms and becoming deeply ingrained in popular culture.\n An ANSWER should be formatted like this: \n\n{'main_characters_list': ['name', 'name'], 'location': 'location', 'genre': 'genre'}\n\nIt should have the same keys but values extracted from the input.\nIf the value of a key is not present in the input, fill with \"null\".\nPut any comments in the next line after the answer.", "class_name": "Prompt"}, "q_extract_system_prompt": {"text": "", "class_name": "Prompt"}, "concepts_user_prompt": {"text": "Identify the key concepts in the following text: Medicare is stronger and Social Security remains strong. My economic plan has helped extend Medicare solvency by a decade. And I am committed to extending Social Security solvency by making the rich pay their fair share.\n\n\nThe list must not contain more than 4 items.\n\nReturn your answers on one line, in a comma-separated list of your responses, with square brackets and each answer in quotes E.g., [\"A\", \"B\", \"C\"]\n\nAfter the answers, you can put a comment explaining your choice on the next line.", "class_name": "Prompt"}, "concepts_system_prompt": {"text": "", "class_name": "Prompt"}, "sentiment_user_prompt": {"text": "\nIdentify the sentiment of this text: Medicare is stronger and Social Security remains strong. My economic plan has helped extend Medicare solvency by a decade. And I am committed to extending Social Security solvency by making the rich pay their fair share.\n\n \nPositive\n \nNeutral\n \nNegative\n \n\nOnly 1 option may be selected.\n\nRespond only with a string corresponding to one of the options.\n\n\nAfter the answer, you can put a comment explaining why you chose that option on the next line.", "class_name": "Prompt"}, "sentiment_system_prompt": {"text": "", "class_name": "Prompt"}}, "raw_model_response": {"q_extract_raw_model_response": null, "q_extract_cost": null, "q_extract_one_usd_buys": "NA", "concepts_raw_model_response": {"id": "chatcmpl-An4klv9mW3ChpDQfSLwmoSvUI4AIi", "choices": [{"finish_reason": "stop", "index": 0, "logprobs": null, "message": {"content": "[\"Medicare solvency\", \"Social Security solvency\", \"economic plan\", \"fair share\"] \nThese concepts capture the focus on the financial stability of Medicare and Social Security, the economic strategy mentioned, and the idea of equitable contribution from the wealthy.", "refusal": null, "role": "assistant", "audio": null, "function_call": null, "tool_calls": null}}], "created": 1736259707, "model": "gpt-4o-2024-08-06", "object": "chat.completion", "service_tier": null, "system_fingerprint": "fp_5f20662549", "usage": {"completion_tokens": 52, "prompt_tokens": 121, "total_tokens": 173, "completion_tokens_details": {"accepted_prediction_tokens": 0, "audio_tokens": 0, "reasoning_tokens": 0, "rejected_prediction_tokens": 0}, "prompt_tokens_details": {"audio_tokens": 0, "cached_tokens": 0}}}, "concepts_cost": 0.0008224999999999999, "concepts_one_usd_buys": 1215.8054711246202, "sentiment_raw_model_response": {"id": "chatcmpl-An4kNQ9fwbFFcuTb0fOkrZd4F4Tq3", "choices": [{"finish_reason": "stop", "index": 0, "logprobs": null, "message": {"content": "Positive\n\nThe text conveys a positive sentiment by highlighting the strengths and improvements in Medicare and Social Security, and the commitment to further enhance these systems by ensuring fairness in contributions.", "refusal": null, "role": "assistant", "audio": null, "function_call": null, "tool_calls": null}}], "created": 1736259683, "model": "gpt-4o-2024-08-06", "object": "chat.completion", "service_tier": null, "system_fingerprint": "fp_d28bcae782", "usage": {"completion_tokens": 35, "prompt_tokens": 103, "total_tokens": 138, "completion_tokens_details": {"accepted_prediction_tokens": 0, "audio_tokens": 0, "reasoning_tokens": 0, "rejected_prediction_tokens": 0}, "prompt_tokens_details": {"audio_tokens": 0, "cached_tokens": 0}}}, "sentiment_cost": 0.0006075, "sentiment_one_usd_buys": 1646.0905349794239}, "question_to_attributes": null, "generated_tokens": {"q_extract_generated_tokens": null, "concepts_generated_tokens": "[\"Medicare solvency\", \"Social Security solvency\", \"economic plan\", \"fair share\"] \nThese concepts capture the focus on the financial stability of Medicare and Social Security, the economic strategy mentioned, and the idea of equitable contribution from the wealthy.", "sentiment_generated_tokens": "Positive\n\nThe text conveys a positive sentiment by highlighting the strengths and improvements in Medicare and Social Security, and the commitment to further enhance these systems by ensuring fairness in contributions."}, "comments_dict": {"q_extract_comment": "Question answer validation failed.", "concepts_comment": "These concepts capture the focus on the financial stability of Medicare and Social Security, the economic strategy mentioned, and the idea of equitable contribution from the wealthy.", "sentiment_comment": "The text conveys a positive sentiment by highlighting the strengths and improvements in Medicare and Social Security, and the commitment to further enhance these systems by ensuring fairness in contributions."}, "cache_used_dict": {"q_extract": null, "concepts": false, "sentiment": false}}], "survey": {"questions": [{"question_name": "q_extract", "question_text": "Review the following text: {{ q_extract_content }}", "answer_template": {"main_characters_list": ["name", "name"], "location": "location", "genre": "genre"}, "question_type": "extract"}, {"question_name": "concepts", "question_text": "Identify the key concepts in the following text: {{ text }}", "max_list_items": 4, "question_type": "list"}, {"question_name": "sentiment", "question_text": "Identify the sentiment of this text: {{ text }}", "question_options": ["Positive", "Neutral", "Negative"], "question_type": "multiple_choice"}], "memory_plan": {"survey_question_names": ["q_extract", "concepts", "sentiment"], "survey_question_texts": ["Review the following text: {{ q_extract_content }}", "Identify the key concepts in the following text: {{ text }}", "Identify the sentiment of this text: {{ text }}"], "data": {}}, "rule_collection": {"rules": [{"current_q": 0, "expression": "True", "next_q": 1, "priority": -1, "question_name_to_index": {"q_extract": 0}, "before_rule": false}, {"current_q": 1, "expression": "True", "next_q": 2, "priority": -1, "question_name_to_index": {"q_extract": 0, "concepts": 1}, "before_rule": false}, {"current_q": 2, "expression": "True", "next_q": 3, "priority": -1, "question_name_to_index": {"q_extract": 0, "concepts": 1, "sentiment": 2}, "before_rule": false}], "num_questions": 3}, "question_groups": {}}, "created_columns": [], "task_history": {"interviews": [{"agent": {"traits": {}, "edsl_version": "0.1.41.dev4", "edsl_class_name": "Agent"}, "survey": {"questions": [{"question_name": "q_extract", "question_text": "Review the following text: {{ q_extract_content }}", "answer_template": {"main_characters_list": ["name", "name"], "location": "location", "genre": "genre"}, "question_type": "extract", "edsl_version": "0.1.41.dev4", "edsl_class_name": "QuestionBase"}, {"question_name": "concepts", "question_text": "Identify the key concepts in the following text: {{ text }}", "max_list_items": 4, "question_type": "list", "edsl_version": "0.1.41.dev4", "edsl_class_name": "QuestionBase"}, {"question_name": "sentiment", "question_text": "Identify the sentiment of this text: {{ text }}", "question_options": ["Positive", "Neutral", "Negative"], "question_type": "multiple_choice", "edsl_version": "0.1.41.dev4", "edsl_class_name": "QuestionBase"}], "memory_plan": {"survey_question_names": ["q_extract", "concepts", "sentiment"], "survey_question_texts": ["Review the following text: {{ q_extract_content }}", "Identify the key concepts in the following text: {{ text }}", "Identify the sentiment of this text: {{ text }}"], "data": {}}, "rule_collection": {"rules": [{"current_q": 0, "expression": "True", "next_q": 1, "priority": -1, "question_name_to_index": {"q_extract": 0}, "before_rule": false}, {"current_q": 1, "expression": "True", "next_q": 2, "priority": -1, "question_name_to_index": {"q_extract": 0, "concepts": 1}, "before_rule": false}, {"current_q": 2, "expression": "True", "next_q": 3, "priority": -1, "question_name_to_index": {"q_extract": 0, "concepts": 1, "sentiment": 2}, "before_rule": false}], "num_questions": 3}, "question_groups": {}, "edsl_version": "0.1.41.dev4", "edsl_class_name": "Survey"}, "scenario": {"text": "Tune in as I deliver the keynote address at the U.S. Holocaust Memorial Museum\u2019s Annual Days of Remembrance ceremony in Washington, D.C.", "q_extract_content": "\n \"The Simpsons\" is an iconic American animated sitcom created by Matt Groening that debuted in 1989 on the Fox network. \n The show is set in the fictional town of Springfield and centers on the Simpsons family, consisting of the bumbling but well-intentioned father Homer, the caring and patient mother Marge, and their three children: mischievous Bart, intelligent Lisa, and baby Maggie. \n Renowned for its satirical take on the typical American family and society, the series delves into themes of politics, religion, and pop culture with a distinct blend of humor and wit. \n Its longevity, marked by over thirty seasons, makes it one of the longest-running television series in history, influencing many other sitcoms and becoming deeply ingrained in popular culture.\n ", "scenario_index": 0, "edsl_version": "0.1.41.dev4", "edsl_class_name": "Scenario"}, "model": {"model": "gpt-4o", "parameters": {"temperature": 0.5, "max_tokens": 1000, "top_p": 1, "frequency_penalty": 0, "presence_penalty": 0, "logprobs": false, "top_logprobs": 3}, "edsl_version": "0.1.41.dev4", "edsl_class_name": "LanguageModel"}, "iteration": 0, "exceptions": {"q_extract": [{"exception": {"type": "QuestionAnswerValidationError", "message": "1 validation error for AnswerModel\nanswer.main_characters_list\n Input should be a valid string [type=string_type, input_value=['Homer', 'Marge', 'Bart', 'Lisa', 'Maggie'], input_type=list]\n For further information visit https://errors.pydantic.dev/2.10/v/string_type", "traceback": "Traceback (most recent call last):\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 77, in _base_validate\n return self.response_model(**data)\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/project/lib/python3.9/site-packages/pydantic/main.py\", line 214, in __init__\n validated_self = self.__pydantic_validator__.validate_python(data, self_instance=self)\npydantic_core._pydantic_core.ValidationError: 1 validation error for AnswerModel\nanswer\n Input should be a valid dictionary or instance of DynamicModel [type=model_type, input_value=None, input_type=NoneType]\n For further information visit https://errors.pydantic.dev/2.10/v/model_type\n\nDuring handling of the above exception, another exception occurred:\n\nTraceback (most recent call last):\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 117, in validate\n pydantic_edsl_answer: BaseModel = self._base_validate(\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 79, in _base_validate\n raise QuestionAnswerValidationError(\nedsl.exceptions.questions.QuestionAnswerValidationError: 1 validation error for AnswerModel\nanswer\n Input should be a valid dictionary or instance of DynamicModel [type=model_type, input_value=None, input_type=NoneType]\n For further information visit https://errors.pydantic.dev/2.10/v/model_type\n\nDuring handling of the above exception, another exception occurred:\n\nTraceback (most recent call last):\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/jobs/AnswerQuestionFunctionConstructor.py\", line 184, in attempt_answer\n raise response.exception_occurred\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/agents/Invigilator.py\", line 163, in _extract_edsl_result_entry_and_validate\n validated_edsl_dict = question_with_validators._validate_answer(edsl_dict)\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/QuestionBase.py\", line 110, in _validate_answer\n return self.response_validator.validate(answer, replacement_dict)\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 123, in validate\n return self._handle_exception(e, raw_edsl_answer_dict)\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 143, in _handle_exception\n raise self.original_exception\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 137, in _handle_exception\n return self.validate(fixed_data, fix=True) # early return if validates\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 123, in validate\n return self._handle_exception(e, raw_edsl_answer_dict)\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 143, in _handle_exception\n raise self.original_exception\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 117, in validate\n pydantic_edsl_answer: BaseModel = self._base_validate(\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 79, in _base_validate\n raise QuestionAnswerValidationError(\nedsl.exceptions.questions.QuestionAnswerValidationError: 1 validation error for AnswerModel\nanswer.main_characters_list\n Input should be a valid string [type=string_type, input_value=['Homer', 'Marge', 'Bart', 'Lisa', 'Maggie'], input_type=list]\n For further information visit https://errors.pydantic.dev/2.10/v/string_type\n"}, "time": "2025-01-07T14:21:01.187773", "traceback": "Traceback (most recent call last):\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 77, in _base_validate\n return self.response_model(**data)\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/project/lib/python3.9/site-packages/pydantic/main.py\", line 214, in __init__\n validated_self = self.__pydantic_validator__.validate_python(data, self_instance=self)\npydantic_core._pydantic_core.ValidationError: 1 validation error for AnswerModel\nanswer\n Input should be a valid dictionary or instance of DynamicModel [type=model_type, input_value=None, input_type=NoneType]\n For further information visit https://errors.pydantic.dev/2.10/v/model_type\n\nDuring handling of the above exception, another exception occurred:\n\nTraceback (most recent call last):\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 117, in validate\n pydantic_edsl_answer: BaseModel = self._base_validate(\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 79, in _base_validate\n raise QuestionAnswerValidationError(\nedsl.exceptions.questions.QuestionAnswerValidationError: 1 validation error for AnswerModel\nanswer\n Input should be a valid dictionary or instance of DynamicModel [type=model_type, input_value=None, input_type=NoneType]\n For further information visit https://errors.pydantic.dev/2.10/v/model_type\n\nDuring handling of the above exception, another exception occurred:\n\nTraceback (most recent call last):\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/jobs/AnswerQuestionFunctionConstructor.py\", line 184, in attempt_answer\n raise response.exception_occurred\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/agents/Invigilator.py\", line 163, in _extract_edsl_result_entry_and_validate\n validated_edsl_dict = question_with_validators._validate_answer(edsl_dict)\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/QuestionBase.py\", line 110, in _validate_answer\n return self.response_validator.validate(answer, replacement_dict)\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 123, in validate\n return self._handle_exception(e, raw_edsl_answer_dict)\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 143, in _handle_exception\n raise self.original_exception\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 137, in _handle_exception\n return self.validate(fixed_data, fix=True) # early return if validates\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 123, in validate\n return self._handle_exception(e, raw_edsl_answer_dict)\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 143, in _handle_exception\n raise self.original_exception\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 117, in validate\n pydantic_edsl_answer: BaseModel = self._base_validate(\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 79, in _base_validate\n raise QuestionAnswerValidationError(\nedsl.exceptions.questions.QuestionAnswerValidationError: 1 validation error for AnswerModel\nanswer.main_characters_list\n Input should be a valid string [type=string_type, input_value=['Homer', 'Marge', 'Bart', 'Lisa', 'Maggie'], input_type=list]\n For further information visit https://errors.pydantic.dev/2.10/v/string_type\n", "invigilator": {"agent": {"traits": {}, "edsl_version": "0.1.41.dev4", "edsl_class_name": "Agent"}, "question": {"question_name": "q_extract", "question_text": "Review the following text: {{ q_extract_content }}", "answer_template": {"main_characters_list": ["name", "name"], "location": "location", "genre": "genre"}, "question_type": "extract", "edsl_version": "0.1.41.dev4", "edsl_class_name": "QuestionBase"}, "scenario": {"text": "Tune in as I deliver the keynote address at the U.S. Holocaust Memorial Museum\u2019s Annual Days of Remembrance ceremony in Washington, D.C.", "q_extract_content": "\n \"The Simpsons\" is an iconic American animated sitcom created by Matt Groening that debuted in 1989 on the Fox network. \n The show is set in the fictional town of Springfield and centers on the Simpsons family, consisting of the bumbling but well-intentioned father Homer, the caring and patient mother Marge, and their three children: mischievous Bart, intelligent Lisa, and baby Maggie. \n Renowned for its satirical take on the typical American family and society, the series delves into themes of politics, religion, and pop culture with a distinct blend of humor and wit. \n Its longevity, marked by over thirty seasons, makes it one of the longest-running television series in history, influencing many other sitcoms and becoming deeply ingrained in popular culture.\n ", "scenario_index": 0, "edsl_version": "0.1.41.dev4", "edsl_class_name": "Scenario"}, "model": {"model": "gpt-4o", "parameters": {"temperature": 0.5, "max_tokens": 1000, "top_p": 1, "frequency_penalty": 0, "presence_penalty": 0, "logprobs": false, "top_logprobs": 3}, "edsl_version": "0.1.41.dev4", "edsl_class_name": "LanguageModel"}, "memory_plan": {"survey_question_names": ["q_extract", "concepts", "sentiment"], "survey_question_texts": ["Review the following text: {{ q_extract_content }}", "Identify the key concepts in the following text: {{ text }}", "Identify the sentiment of this text: {{ text }}"], "data": {}}, "current_answers": {}, "iteration": 0, "additional_prompt_data": null, "survey": {"questions": [{"question_name": "q_extract", "question_text": "Review the following text: {{ q_extract_content }}", "answer_template": {"main_characters_list": ["name", "name"], "location": "location", "genre": "genre"}, "question_type": "extract", "edsl_version": "0.1.41.dev4", "edsl_class_name": "QuestionBase"}, {"question_name": "concepts", "question_text": "Identify the key concepts in the following text: {{ text }}", "max_list_items": 4, "question_type": "list", "edsl_version": "0.1.41.dev4", "edsl_class_name": "QuestionBase"}, {"question_name": "sentiment", "question_text": "Identify the sentiment of this text: {{ text }}", "question_options": ["Positive", "Neutral", "Negative"], "question_type": "multiple_choice", "edsl_version": "0.1.41.dev4", "edsl_class_name": "QuestionBase"}], "memory_plan": {"survey_question_names": ["q_extract", "concepts", "sentiment"], "survey_question_texts": ["Review the following text: {{ q_extract_content }}", "Identify the key concepts in the following text: {{ text }}", "Identify the sentiment of this text: {{ text }}"], "data": {}}, "rule_collection": {"rules": [{"current_q": 0, "expression": "True", "next_q": 1, "priority": -1, "question_name_to_index": {"q_extract": 0}, "before_rule": false}, {"current_q": 1, "expression": "True", "next_q": 2, "priority": -1, "question_name_to_index": {"q_extract": 0, "concepts": 1}, "before_rule": false}, {"current_q": 2, "expression": "True", "next_q": 3, "priority": -1, "question_name_to_index": {"q_extract": 0, "concepts": 1, "sentiment": 2}, "before_rule": false}], "num_questions": 3}, "question_groups": {}, "edsl_version": "0.1.41.dev4", "edsl_class_name": "Survey"}}}]}, "indices": {"agent": 0, "model": 0, "scenario": 0}}, {"agent": {"traits": {}, "edsl_version": "0.1.41.dev4", "edsl_class_name": "Agent"}, "survey": {"questions": [{"question_name": "q_extract", "question_text": "Review the following text: {{ q_extract_content }}", "answer_template": {"main_characters_list": ["name", "name"], "location": "location", "genre": "genre"}, "question_type": "extract", "edsl_version": "0.1.41.dev4", "edsl_class_name": "QuestionBase"}, {"question_name": "concepts", "question_text": "Identify the key concepts in the following text: {{ text }}", "max_list_items": 4, "question_type": "list", "edsl_version": "0.1.41.dev4", "edsl_class_name": "QuestionBase"}, {"question_name": "sentiment", "question_text": "Identify the sentiment of this text: {{ text }}", "question_options": ["Positive", "Neutral", "Negative"], "question_type": "multiple_choice", "edsl_version": "0.1.41.dev4", "edsl_class_name": "QuestionBase"}], "memory_plan": {"survey_question_names": ["q_extract", "concepts", "sentiment"], "survey_question_texts": ["Review the following text: {{ q_extract_content }}", "Identify the key concepts in the following text: {{ text }}", "Identify the sentiment of this text: {{ text }}"], "data": {}}, "rule_collection": {"rules": [{"current_q": 0, "expression": "True", "next_q": 1, "priority": -1, "question_name_to_index": {"q_extract": 0}, "before_rule": false}, {"current_q": 1, "expression": "True", "next_q": 2, "priority": -1, "question_name_to_index": {"q_extract": 0, "concepts": 1}, "before_rule": false}, {"current_q": 2, "expression": "True", "next_q": 3, "priority": -1, "question_name_to_index": {"q_extract": 0, "concepts": 1, "sentiment": 2}, "before_rule": false}], "num_questions": 3}, "question_groups": {}, "edsl_version": "0.1.41.dev4", "edsl_class_name": "Survey"}, "scenario": {"text": "We\u2019re a nation of immigrants. A nation of dreamers. And as Cinco de Mayo represents, a nation of freedom.", "q_extract_content": "\n \"The Simpsons\" is an iconic American animated sitcom created by Matt Groening that debuted in 1989 on the Fox network. \n The show is set in the fictional town of Springfield and centers on the Simpsons family, consisting of the bumbling but well-intentioned father Homer, the caring and patient mother Marge, and their three children: mischievous Bart, intelligent Lisa, and baby Maggie. \n Renowned for its satirical take on the typical American family and society, the series delves into themes of politics, religion, and pop culture with a distinct blend of humor and wit. \n Its longevity, marked by over thirty seasons, makes it one of the longest-running television series in history, influencing many other sitcoms and becoming deeply ingrained in popular culture.\n ", "scenario_index": 1, "edsl_version": "0.1.41.dev4", "edsl_class_name": "Scenario"}, "model": {"model": "gpt-4o", "parameters": {"temperature": 0.5, "max_tokens": 1000, "top_p": 1, "frequency_penalty": 0, "presence_penalty": 0, "logprobs": false, "top_logprobs": 3}, "edsl_version": "0.1.41.dev4", "edsl_class_name": "LanguageModel"}, "iteration": 0, "exceptions": {"q_extract": [{"exception": {"type": "QuestionAnswerValidationError", "message": "1 validation error for AnswerModel\nanswer.main_characters_list\n Input should be a valid string [type=string_type, input_value=['Homer', 'Marge', 'Bart', 'Lisa', 'Maggie'], input_type=list]\n For further information visit https://errors.pydantic.dev/2.10/v/string_type", "traceback": "Traceback (most recent call last):\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 77, in _base_validate\n return self.response_model(**data)\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/project/lib/python3.9/site-packages/pydantic/main.py\", line 214, in __init__\n validated_self = self.__pydantic_validator__.validate_python(data, self_instance=self)\npydantic_core._pydantic_core.ValidationError: 1 validation error for AnswerModel\nanswer\n Input should be a valid dictionary or instance of DynamicModel [type=model_type, input_value=None, input_type=NoneType]\n For further information visit https://errors.pydantic.dev/2.10/v/model_type\n\nDuring handling of the above exception, another exception occurred:\n\nTraceback (most recent call last):\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 117, in validate\n pydantic_edsl_answer: BaseModel = self._base_validate(\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 79, in _base_validate\n raise QuestionAnswerValidationError(\nedsl.exceptions.questions.QuestionAnswerValidationError: 1 validation error for AnswerModel\nanswer\n Input should be a valid dictionary or instance of DynamicModel [type=model_type, input_value=None, input_type=NoneType]\n For further information visit https://errors.pydantic.dev/2.10/v/model_type\n\nDuring handling of the above exception, another exception occurred:\n\nTraceback (most recent call last):\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/jobs/AnswerQuestionFunctionConstructor.py\", line 184, in attempt_answer\n raise response.exception_occurred\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/agents/Invigilator.py\", line 163, in _extract_edsl_result_entry_and_validate\n validated_edsl_dict = question_with_validators._validate_answer(edsl_dict)\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/QuestionBase.py\", line 110, in _validate_answer\n return self.response_validator.validate(answer, replacement_dict)\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 123, in validate\n return self._handle_exception(e, raw_edsl_answer_dict)\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 143, in _handle_exception\n raise self.original_exception\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 137, in _handle_exception\n return self.validate(fixed_data, fix=True) # early return if validates\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 123, in validate\n return self._handle_exception(e, raw_edsl_answer_dict)\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 143, in _handle_exception\n raise self.original_exception\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 117, in validate\n pydantic_edsl_answer: BaseModel = self._base_validate(\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 79, in _base_validate\n raise QuestionAnswerValidationError(\nedsl.exceptions.questions.QuestionAnswerValidationError: 1 validation error for AnswerModel\nanswer.main_characters_list\n Input should be a valid string [type=string_type, input_value=['Homer', 'Marge', 'Bart', 'Lisa', 'Maggie'], input_type=list]\n For further information visit https://errors.pydantic.dev/2.10/v/string_type\n"}, "time": "2025-01-07T14:21:13.758887", "traceback": "Traceback (most recent call last):\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 77, in _base_validate\n return self.response_model(**data)\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/project/lib/python3.9/site-packages/pydantic/main.py\", line 214, in __init__\n validated_self = self.__pydantic_validator__.validate_python(data, self_instance=self)\npydantic_core._pydantic_core.ValidationError: 1 validation error for AnswerModel\nanswer\n Input should be a valid dictionary or instance of DynamicModel [type=model_type, input_value=None, input_type=NoneType]\n For further information visit https://errors.pydantic.dev/2.10/v/model_type\n\nDuring handling of the above exception, another exception occurred:\n\nTraceback (most recent call last):\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 117, in validate\n pydantic_edsl_answer: BaseModel = self._base_validate(\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 79, in _base_validate\n raise QuestionAnswerValidationError(\nedsl.exceptions.questions.QuestionAnswerValidationError: 1 validation error for AnswerModel\nanswer\n Input should be a valid dictionary or instance of DynamicModel [type=model_type, input_value=None, input_type=NoneType]\n For further information visit https://errors.pydantic.dev/2.10/v/model_type\n\nDuring handling of the above exception, another exception occurred:\n\nTraceback (most recent call last):\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/jobs/AnswerQuestionFunctionConstructor.py\", line 184, in attempt_answer\n raise response.exception_occurred\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/agents/Invigilator.py\", line 163, in _extract_edsl_result_entry_and_validate\n validated_edsl_dict = question_with_validators._validate_answer(edsl_dict)\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/QuestionBase.py\", line 110, in _validate_answer\n return self.response_validator.validate(answer, replacement_dict)\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 123, in validate\n return self._handle_exception(e, raw_edsl_answer_dict)\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 143, in _handle_exception\n raise self.original_exception\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 137, in _handle_exception\n return self.validate(fixed_data, fix=True) # early return if validates\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 123, in validate\n return self._handle_exception(e, raw_edsl_answer_dict)\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 143, in _handle_exception\n raise self.original_exception\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 117, in validate\n pydantic_edsl_answer: BaseModel = self._base_validate(\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 79, in _base_validate\n raise QuestionAnswerValidationError(\nedsl.exceptions.questions.QuestionAnswerValidationError: 1 validation error for AnswerModel\nanswer.main_characters_list\n Input should be a valid string [type=string_type, input_value=['Homer', 'Marge', 'Bart', 'Lisa', 'Maggie'], input_type=list]\n For further information visit https://errors.pydantic.dev/2.10/v/string_type\n", "invigilator": {"agent": {"traits": {}, "edsl_version": "0.1.41.dev4", "edsl_class_name": "Agent"}, "question": {"question_name": "q_extract", "question_text": "Review the following text: {{ q_extract_content }}", "answer_template": {"main_characters_list": ["name", "name"], "location": "location", "genre": "genre"}, "question_type": "extract", "edsl_version": "0.1.41.dev4", "edsl_class_name": "QuestionBase"}, "scenario": {"text": "We\u2019re a nation of immigrants. A nation of dreamers. And as Cinco de Mayo represents, a nation of freedom.", "q_extract_content": "\n \"The Simpsons\" is an iconic American animated sitcom created by Matt Groening that debuted in 1989 on the Fox network. \n The show is set in the fictional town of Springfield and centers on the Simpsons family, consisting of the bumbling but well-intentioned father Homer, the caring and patient mother Marge, and their three children: mischievous Bart, intelligent Lisa, and baby Maggie. \n Renowned for its satirical take on the typical American family and society, the series delves into themes of politics, religion, and pop culture with a distinct blend of humor and wit. \n Its longevity, marked by over thirty seasons, makes it one of the longest-running television series in history, influencing many other sitcoms and becoming deeply ingrained in popular culture.\n ", "scenario_index": 1, "edsl_version": "0.1.41.dev4", "edsl_class_name": "Scenario"}, "model": {"model": "gpt-4o", "parameters": {"temperature": 0.5, "max_tokens": 1000, "top_p": 1, "frequency_penalty": 0, "presence_penalty": 0, "logprobs": false, "top_logprobs": 3}, "edsl_version": "0.1.41.dev4", "edsl_class_name": "LanguageModel"}, "memory_plan": {"survey_question_names": ["q_extract", "concepts", "sentiment"], "survey_question_texts": ["Review the following text: {{ q_extract_content }}", "Identify the key concepts in the following text: {{ text }}", "Identify the sentiment of this text: {{ text }}"], "data": {}}, "current_answers": {}, "iteration": 0, "additional_prompt_data": null, "survey": {"questions": [{"question_name": "q_extract", "question_text": "Review the following text: {{ q_extract_content }}", "answer_template": {"main_characters_list": ["name", "name"], "location": "location", "genre": "genre"}, "question_type": "extract", "edsl_version": "0.1.41.dev4", "edsl_class_name": "QuestionBase"}, {"question_name": "concepts", "question_text": "Identify the key concepts in the following text: {{ text }}", "max_list_items": 4, "question_type": "list", "edsl_version": "0.1.41.dev4", "edsl_class_name": "QuestionBase"}, {"question_name": "sentiment", "question_text": "Identify the sentiment of this text: {{ text }}", "question_options": ["Positive", "Neutral", "Negative"], "question_type": "multiple_choice", "edsl_version": "0.1.41.dev4", "edsl_class_name": "QuestionBase"}], "memory_plan": {"survey_question_names": ["q_extract", "concepts", "sentiment"], "survey_question_texts": ["Review the following text: {{ q_extract_content }}", "Identify the key concepts in the following text: {{ text }}", "Identify the sentiment of this text: {{ text }}"], "data": {}}, "rule_collection": {"rules": [{"current_q": 0, "expression": "True", "next_q": 1, "priority": -1, "question_name_to_index": {"q_extract": 0}, "before_rule": false}, {"current_q": 1, "expression": "True", "next_q": 2, "priority": -1, "question_name_to_index": {"q_extract": 0, "concepts": 1}, "before_rule": false}, {"current_q": 2, "expression": "True", "next_q": 3, "priority": -1, "question_name_to_index": {"q_extract": 0, "concepts": 1, "sentiment": 2}, "before_rule": false}], "num_questions": 3}, "question_groups": {}, "edsl_version": "0.1.41.dev4", "edsl_class_name": "Survey"}}}]}, "indices": {"agent": 0, "model": 0, "scenario": 1}}, {"agent": {"traits": {}, "edsl_version": "0.1.41.dev4", "edsl_class_name": "Agent"}, "survey": {"questions": [{"question_name": "q_extract", "question_text": "Review the following text: {{ q_extract_content }}", "answer_template": {"main_characters_list": ["name", "name"], "location": "location", "genre": "genre"}, "question_type": "extract", "edsl_version": "0.1.41.dev4", "edsl_class_name": "QuestionBase"}, {"question_name": "concepts", "question_text": "Identify the key concepts in the following text: {{ text }}", "max_list_items": 4, "question_type": "list", "edsl_version": "0.1.41.dev4", "edsl_class_name": "QuestionBase"}, {"question_name": "sentiment", "question_text": "Identify the sentiment of this text: {{ text }}", "question_options": ["Positive", "Neutral", "Negative"], "question_type": "multiple_choice", "edsl_version": "0.1.41.dev4", "edsl_class_name": "QuestionBase"}], "memory_plan": {"survey_question_names": ["q_extract", "concepts", "sentiment"], "survey_question_texts": ["Review the following text: {{ q_extract_content }}", "Identify the key concepts in the following text: {{ text }}", "Identify the sentiment of this text: {{ text }}"], "data": {}}, "rule_collection": {"rules": [{"current_q": 0, "expression": "True", "next_q": 1, "priority": -1, "question_name_to_index": {"q_extract": 0}, "before_rule": false}, {"current_q": 1, "expression": "True", "next_q": 2, "priority": -1, "question_name_to_index": {"q_extract": 0, "concepts": 1}, "before_rule": false}, {"current_q": 2, "expression": "True", "next_q": 3, "priority": -1, "question_name_to_index": {"q_extract": 0, "concepts": 1, "sentiment": 2}, "before_rule": false}], "num_questions": 3}, "question_groups": {}, "edsl_version": "0.1.41.dev4", "edsl_class_name": "Survey"}, "scenario": {"text": "Medicare is stronger and Social Security remains strong. My economic plan has helped extend Medicare solvency by a decade. And I am committed to extending Social Security solvency by making the rich pay their fair share.", "q_extract_content": "\n \"The Simpsons\" is an iconic American animated sitcom created by Matt Groening that debuted in 1989 on the Fox network. \n The show is set in the fictional town of Springfield and centers on the Simpsons family, consisting of the bumbling but well-intentioned father Homer, the caring and patient mother Marge, and their three children: mischievous Bart, intelligent Lisa, and baby Maggie. \n Renowned for its satirical take on the typical American family and society, the series delves into themes of politics, religion, and pop culture with a distinct blend of humor and wit. \n Its longevity, marked by over thirty seasons, makes it one of the longest-running television series in history, influencing many other sitcoms and becoming deeply ingrained in popular culture.\n ", "scenario_index": 2, "edsl_version": "0.1.41.dev4", "edsl_class_name": "Scenario"}, "model": {"model": "gpt-4o", "parameters": {"temperature": 0.5, "max_tokens": 1000, "top_p": 1, "frequency_penalty": 0, "presence_penalty": 0, "logprobs": false, "top_logprobs": 3}, "edsl_version": "0.1.41.dev4", "edsl_class_name": "LanguageModel"}, "iteration": 0, "exceptions": {"q_extract": [{"exception": {"type": "QuestionAnswerValidationError", "message": "1 validation error for AnswerModel\nanswer.main_characters_list\n Input should be a valid string [type=string_type, input_value=['Homer', 'Marge', 'Bart', 'Lisa', 'Maggie'], input_type=list]\n For further information visit https://errors.pydantic.dev/2.10/v/string_type", "traceback": "Traceback (most recent call last):\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 77, in _base_validate\n return self.response_model(**data)\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/project/lib/python3.9/site-packages/pydantic/main.py\", line 214, in __init__\n validated_self = self.__pydantic_validator__.validate_python(data, self_instance=self)\npydantic_core._pydantic_core.ValidationError: 1 validation error for AnswerModel\nanswer\n Input should be a valid dictionary or instance of DynamicModel [type=model_type, input_value=None, input_type=NoneType]\n For further information visit https://errors.pydantic.dev/2.10/v/model_type\n\nDuring handling of the above exception, another exception occurred:\n\nTraceback (most recent call last):\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 117, in validate\n pydantic_edsl_answer: BaseModel = self._base_validate(\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 79, in _base_validate\n raise QuestionAnswerValidationError(\nedsl.exceptions.questions.QuestionAnswerValidationError: 1 validation error for AnswerModel\nanswer\n Input should be a valid dictionary or instance of DynamicModel [type=model_type, input_value=None, input_type=NoneType]\n For further information visit https://errors.pydantic.dev/2.10/v/model_type\n\nDuring handling of the above exception, another exception occurred:\n\nTraceback (most recent call last):\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/jobs/AnswerQuestionFunctionConstructor.py\", line 184, in attempt_answer\n raise response.exception_occurred\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/agents/Invigilator.py\", line 163, in _extract_edsl_result_entry_and_validate\n validated_edsl_dict = question_with_validators._validate_answer(edsl_dict)\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/QuestionBase.py\", line 110, in _validate_answer\n return self.response_validator.validate(answer, replacement_dict)\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 123, in validate\n return self._handle_exception(e, raw_edsl_answer_dict)\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 143, in _handle_exception\n raise self.original_exception\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 137, in _handle_exception\n return self.validate(fixed_data, fix=True) # early return if validates\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 123, in validate\n return self._handle_exception(e, raw_edsl_answer_dict)\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 143, in _handle_exception\n raise self.original_exception\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 117, in validate\n pydantic_edsl_answer: BaseModel = self._base_validate(\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 79, in _base_validate\n raise QuestionAnswerValidationError(\nedsl.exceptions.questions.QuestionAnswerValidationError: 1 validation error for AnswerModel\nanswer.main_characters_list\n Input should be a valid string [type=string_type, input_value=['Homer', 'Marge', 'Bart', 'Lisa', 'Maggie'], input_type=list]\n For further information visit https://errors.pydantic.dev/2.10/v/string_type\n"}, "time": "2025-01-07T14:21:31.135143", "traceback": "Traceback (most recent call last):\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 77, in _base_validate\n return self.response_model(**data)\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/project/lib/python3.9/site-packages/pydantic/main.py\", line 214, in __init__\n validated_self = self.__pydantic_validator__.validate_python(data, self_instance=self)\npydantic_core._pydantic_core.ValidationError: 1 validation error for AnswerModel\nanswer\n Input should be a valid dictionary or instance of DynamicModel [type=model_type, input_value=None, input_type=NoneType]\n For further information visit https://errors.pydantic.dev/2.10/v/model_type\n\nDuring handling of the above exception, another exception occurred:\n\nTraceback (most recent call last):\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 117, in validate\n pydantic_edsl_answer: BaseModel = self._base_validate(\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 79, in _base_validate\n raise QuestionAnswerValidationError(\nedsl.exceptions.questions.QuestionAnswerValidationError: 1 validation error for AnswerModel\nanswer\n Input should be a valid dictionary or instance of DynamicModel [type=model_type, input_value=None, input_type=NoneType]\n For further information visit https://errors.pydantic.dev/2.10/v/model_type\n\nDuring handling of the above exception, another exception occurred:\n\nTraceback (most recent call last):\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/jobs/AnswerQuestionFunctionConstructor.py\", line 184, in attempt_answer\n raise response.exception_occurred\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/agents/Invigilator.py\", line 163, in _extract_edsl_result_entry_and_validate\n validated_edsl_dict = question_with_validators._validate_answer(edsl_dict)\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/QuestionBase.py\", line 110, in _validate_answer\n return self.response_validator.validate(answer, replacement_dict)\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 123, in validate\n return self._handle_exception(e, raw_edsl_answer_dict)\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 143, in _handle_exception\n raise self.original_exception\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 137, in _handle_exception\n return self.validate(fixed_data, fix=True) # early return if validates\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 123, in validate\n return self._handle_exception(e, raw_edsl_answer_dict)\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 143, in _handle_exception\n raise self.original_exception\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 117, in validate\n pydantic_edsl_answer: BaseModel = self._base_validate(\n File \"/home/stefan/expectedparrot/auto-deploy-to-pypi/edsl/edsl/questions/response_validator_abc.py\", line 79, in _base_validate\n raise QuestionAnswerValidationError(\nedsl.exceptions.questions.QuestionAnswerValidationError: 1 validation error for AnswerModel\nanswer.main_characters_list\n Input should be a valid string [type=string_type, input_value=['Homer', 'Marge', 'Bart', 'Lisa', 'Maggie'], input_type=list]\n For further information visit https://errors.pydantic.dev/2.10/v/string_type\n", "invigilator": {"agent": {"traits": {}, "edsl_version": "0.1.41.dev4", "edsl_class_name": "Agent"}, "question": {"question_name": "q_extract", "question_text": "Review the following text: {{ q_extract_content }}", "answer_template": {"main_characters_list": ["name", "name"], "location": "location", "genre": "genre"}, "question_type": "extract", "edsl_version": "0.1.41.dev4", "edsl_class_name": "QuestionBase"}, "scenario": {"text": "Medicare is stronger and Social Security remains strong. My economic plan has helped extend Medicare solvency by a decade. And I am committed to extending Social Security solvency by making the rich pay their fair share.", "q_extract_content": "\n \"The Simpsons\" is an iconic American animated sitcom created by Matt Groening that debuted in 1989 on the Fox network. \n The show is set in the fictional town of Springfield and centers on the Simpsons family, consisting of the bumbling but well-intentioned father Homer, the caring and patient mother Marge, and their three children: mischievous Bart, intelligent Lisa, and baby Maggie. \n Renowned for its satirical take on the typical American family and society, the series delves into themes of politics, religion, and pop culture with a distinct blend of humor and wit. \n Its longevity, marked by over thirty seasons, makes it one of the longest-running television series in history, influencing many other sitcoms and becoming deeply ingrained in popular culture.\n ", "scenario_index": 2, "edsl_version": "0.1.41.dev4", "edsl_class_name": "Scenario"}, "model": {"model": "gpt-4o", "parameters": {"temperature": 0.5, "max_tokens": 1000, "top_p": 1, "frequency_penalty": 0, "presence_penalty": 0, "logprobs": false, "top_logprobs": 3}, "edsl_version": "0.1.41.dev4", "edsl_class_name": "LanguageModel"}, "memory_plan": {"survey_question_names": ["q_extract", "concepts", "sentiment"], "survey_question_texts": ["Review the following text: {{ q_extract_content }}", "Identify the key concepts in the following text: {{ text }}", "Identify the sentiment of this text: {{ text }}"], "data": {}}, "current_answers": {"sentiment_generated_tokens": "Positive\n\nThe text conveys a positive sentiment by highlighting the strengths and improvements in Medicare and Social Security, and the commitment to further enhance these systems by ensuring fairness in contributions.", "sentiment": "Positive", "sentiment_comment": "The text conveys a positive sentiment by highlighting the strengths and improvements in Medicare and Social Security, and the commitment to further enhance these systems by ensuring fairness in contributions.", "concepts_generated_tokens": "[\"Medicare solvency\", \"Social Security solvency\", \"economic plan\", \"fair share\"] \nThese concepts capture the focus on the financial stability of Medicare and Social Security, the economic strategy mentioned, and the idea of equitable contribution from the wealthy.", "concepts": ["Medicare solvency", "Social Security solvency", "economic plan", "fair share"], "concepts_comment": "These concepts capture the focus on the financial stability of Medicare and Social Security, the economic strategy mentioned, and the idea of equitable contribution from the wealthy.", "q_extract": null}, "iteration": 0, "additional_prompt_data": null, "survey": {"questions": [{"question_name": "q_extract", "question_text": "Review the following text: {{ q_extract_content }}", "answer_template": {"main_characters_list": ["name", "name"], "location": "location", "genre": "genre"}, "question_type": "extract", "edsl_version": "0.1.41.dev4", "edsl_class_name": "QuestionBase"}, {"question_name": "concepts", "question_text": "Identify the key concepts in the following text: {{ text }}", "max_list_items": 4, "question_type": "list", "edsl_version": "0.1.41.dev4", "edsl_class_name": "QuestionBase"}, {"question_name": "sentiment", "question_text": "Identify the sentiment of this text: {{ text }}", "question_options": ["Positive", "Neutral", "Negative"], "question_type": "multiple_choice", "edsl_version": "0.1.41.dev4", "edsl_class_name": "QuestionBase"}], "memory_plan": {"survey_question_names": ["q_extract", "concepts", "sentiment"], "survey_question_texts": ["Review the following text: {{ q_extract_content }}", "Identify the key concepts in the following text: {{ text }}", "Identify the sentiment of this text: {{ text }}"], "data": {}}, "rule_collection": {"rules": [{"current_q": 0, "expression": "True", "next_q": 1, "priority": -1, "question_name_to_index": {"q_extract": 0}, "before_rule": false}, {"current_q": 1, "expression": "True", "next_q": 2, "priority": -1, "question_name_to_index": {"q_extract": 0, "concepts": 1}, "before_rule": false}, {"current_q": 2, "expression": "True", "next_q": 3, "priority": -1, "question_name_to_index": {"q_extract": 0, "concepts": 1, "sentiment": 2}, "before_rule": false}], "num_questions": 3}, "question_groups": {}, "edsl_version": "0.1.41.dev4", "edsl_class_name": "Survey"}}}]}, "indices": {"agent": 0, "model": 0, "scenario": 2}}], "include_traceback": false, "edsl_version": "0.1.41.dev4", "edsl_class_name": "TaskHistory"}}}, {"class_name": "Results", "dict": {"data": [{"agent": {"traits": {}}, "scenario": {"scenario_index": 0}, "model": {"model": "gpt-4o", "parameters": {"temperature": 0.5, "max_tokens": 1000, "top_p": 1, "frequency_penalty": 0, "presence_penalty": 0, "logprobs": false, "top_logprobs": 3}}, "iteration": 0, "answer": {"color": "Blue", "day": null, "winter": null, "birds": null}, "prompt": {"color_user_prompt": {"text": "\nWhat is your favorite color?\n\n \nRed\n \nOrange\n \nYellow\n \nGreen\n \nBlue\n \nPurple\n \n\nOnly 1 option may be selected.\n\nRespond only with a string corresponding to one of the options.\n\n\nAfter the answer, you can put a comment explaining why you chose that option on the next line.", "class_name": "Prompt"}, "color_system_prompt": {"text": "", "class_name": "Prompt"}, "day_user_prompt": {"text": "\nWhat is your favorite day of the week?\n\n \nSun\n \nMon\n \nTue\n \nWed\n \nThu\n \nFri\n \nSat\n \n\nOnly 1 option may be selected.\n\nRespond only with a string corresponding to one of the options.\n\n\nAfter the answer, you can put a comment explaining why you chose that option on the next line.\n Before the question you are now answering, you already answered the following question(s):\n \tQuestion: What is your favorite color?\n\tAnswer: None", "class_name": "Prompt"}, "day_system_prompt": {"text": "", "class_name": "Prompt"}, "winter_user_prompt": {"text": "How much do you enjoy winter?\n\n0 : Hate it\n\n1 : \n\n2 : \n\n3 : \n\n4 : \n\n5 : Love it\n\nOnly 1 option may be selected.\n\nRespond only with the code corresponding to one of the options. E.g., \"1\" or \"5\" by itself.\n\nAfter the answer, you can put a comment explaining why you chose that option on the next line.\n Before the question you are now answering, you already answered the following question(s):\n \tQuestion: What is your favorite color?\n\tAnswer: None\n\n Prior questions and answers:\tQuestion: What is your favorite day of the week?\n\tAnswer: None", "class_name": "Prompt"}, "winter_system_prompt": {"text": "", "class_name": "Prompt"}, "birds_user_prompt": {"text": "Which birds do you like best?\n\n \n0: Parrot\n \n1: Osprey\n \n2: Falcon\n \n3: Eagle\n \n4: First Robin of Spring\n \n\n\n\n\nYou must select exactly 2 options.\n\n\nPlease respond with valid JSON, formatted like so:\n\n {\"answer\": [], \"comment\": \"\"}\n Before the question you are now answering, you already answered the following question(s):\n \tQuestion: What is your favorite day of the week?\n\tAnswer: None\n\n Prior questions and answers:\tQuestion: How much do you enjoy winter?\n\tAnswer: None\n\n Prior questions and answers:\tQuestion: What is your favorite color?\n\tAnswer: None", "class_name": "Prompt"}, "birds_system_prompt": {"text": "", "class_name": "Prompt"}}, "raw_model_response": {"color_raw_model_response": null, "color_cost": null, "color_one_usd_buys": "NA", "day_raw_model_response": null, "day_cost": null, "day_one_usd_buys": "NA", "winter_raw_model_response": null, "winter_cost": null, "winter_one_usd_buys": "NA", "birds_raw_model_response": null, "birds_cost": null, "birds_one_usd_buys": "NA"}, "question_to_attributes": null, "generated_tokens": {"color_generated_tokens": null, "day_generated_tokens": null, "winter_generated_tokens": null, "birds_generated_tokens": null}, "comments_dict": {"color_comment": "Task was cancelled.", "day_comment": "Task was cancelled.", "winter_comment": "Task was cancelled.", "birds_comment": "Task was cancelled."}, "cache_used_dict": {"color": null, "day": null, "winter": null, "birds": null}}], "survey": {"questions": [{"question_name": "color", "question_text": "What is your favorite color?", "question_options": ["Red", "Orange", "Yellow", "Green", "Blue", "Purple"], "question_type": "multiple_choice"}, {"question_name": "day", "question_text": "What is your favorite day of the week?", "question_options": ["Sun", "Mon", "Tue", "Wed", "Thu", "Fri", "Sat"], "question_type": "multiple_choice"}, {"question_name": "winter", "question_text": "How much do you enjoy winter?", "question_options": [0, 1, 2, 3, 4, 5], "option_labels": {"0": "Hate it", "5": "Love it"}, "question_type": "linear_scale"}, {"question_name": "birds", "question_text": "Which birds do you like best?", "min_selections": 2, "max_selections": 2, "question_options": ["Parrot", "Osprey", "Falcon", "Eagle", "First Robin of Spring"], "use_code": true, "question_type": "top_k"}], "memory_plan": {"survey_question_names": ["color", "day", "winter", "birds"], "survey_question_texts": ["What is your favorite color?", "What is your favorite day of the week?", "How much do you enjoy winter?", "Which birds do you like best?"], "data": {"day": {"prior_questions": ["color"]}, "winter": {"prior_questions": ["color", "day"]}, "birds": {"prior_questions": ["day", "winter", "color"]}}}, "rule_collection": {"rules": [{"current_q": 0, "expression": "True", "next_q": 1, "priority": -1, "question_name_to_index": {"color": 0}, "before_rule": false}, {"current_q": 1, "expression": "True", "next_q": 2, "priority": -1, "question_name_to_index": {"color": 0, "day": 1}, "before_rule": false}, {"current_q": 2, "expression": "True", "next_q": 3, "priority": -1, "question_name_to_index": {"color": 0, "day": 1, "winter": 2}, "before_rule": false}, {"current_q": 3, "expression": "True", "next_q": 4, "priority": -1, "question_name_to_index": {"color": 0, "day": 1, "winter": 2, "birds": 3}, "before_rule": false}, {"current_q": 3, "expression": "color == 'Blue'", "next_q": 4, "priority": 0, "question_name_to_index": {"color": 0, "day": 1, "winter": 2, "birds": 3}, "before_rule": true}, {"current_q": 0, "expression": "color == 'Blue'", "next_q": "EndOfSurvey", "priority": 0, "question_name_to_index": {"color": 0, "day": 1, "winter": 2, "birds": 3}, "before_rule": false}, {"current_q": 0, "expression": "color == 'Red'", "next_q": 2, "priority": 1, "question_name_to_index": {"color": 0, "day": 1, "winter": 2, "birds": 3}, "before_rule": false}], "num_questions": 4}, "question_groups": {}}, "created_columns": []}}] \ No newline at end of file