# Standard Packages import os from datetime import datetime # External Packages import pytest import freezegun from freezegun import freeze_time # Internal Packages from khoj.processor.conversation.openai.gpt import converse, extract_questions from khoj.processor.conversation.utils import message_to_log # Initialize variables for tests api_key = os.getenv("OPENAI_API_KEY") if api_key is None: pytest.skip( reason="Set OPENAI_API_KEY environment variable to run tests below. Get OpenAI API key from https://platform.openai.com/account/api-keys", allow_module_level=True, ) freezegun.configure(extend_ignore_list=["transformers"]) # Test # ---------------------------------------------------------------------------------------------------- @pytest.mark.chatquality @freeze_time("1984-04-02") def test_extract_question_with_date_filter_from_relative_day(): # Act response = extract_questions("Where did I go for dinner yesterday?") # Assert expected_responses = [ ("dt='1984-04-01'", ""), ("dt>='1984-04-01'", "dt<'1984-04-02'"), ("dt>'1984-03-31'", "dt<'1984-04-02'"), ] assert len(response) == 1 assert any([start in response[0] and end in response[0] for start, end in expected_responses]), ( "Expected date filter to limit to 1st April 1984 in response but got: " + response[0] ) # ---------------------------------------------------------------------------------------------------- @pytest.mark.chatquality @freeze_time("1984-04-02") def test_extract_question_with_date_filter_from_relative_month(): # Act response = extract_questions("Which countries did I visit last month?") # Assert expected_responses = [("dt>='1984-03-01'", "dt<'1984-04-01'"), ("dt>='1984-03-01'", "dt<='1984-03-31'")] assert len(response) == 1 assert any([start in response[0] and end in response[0] for start, end in expected_responses]), ( "Expected date filter to limit to March 1984 in response but got: " + response[0] ) # ---------------------------------------------------------------------------------------------------- @pytest.mark.chatquality @freeze_time("1984-04-02") def test_extract_question_with_date_filter_from_relative_year(): # Act response = extract_questions("Which countries have I visited this year?") # Assert expected_responses = [ ("dt>='1984-01-01'", ""), ("dt>='1984-01-01'", "dt<'1985-01-01'"), ("dt>='1984-01-01'", "dt<='1984-12-31'"), ] assert len(response) == 1 assert any([start in response[0] and end in response[0] for start, end in expected_responses]), ( "Expected date filter to limit to 1984 in response but got: " + response[0] ) # ---------------------------------------------------------------------------------------------------- @pytest.mark.chatquality def test_extract_multiple_explicit_questions_from_message(): # Act response = extract_questions("What is the Sun? What is the Moon?") # Assert expected_responses = [ ("sun", "moon"), ] assert len(response) == 2 assert any([start in response[0].lower() and end in response[1].lower() for start, end in expected_responses]), ( "Expected two search queries in response but got: " + response[0] ) # ---------------------------------------------------------------------------------------------------- @pytest.mark.chatquality def test_extract_multiple_implicit_questions_from_message(): # Act response = extract_questions("Is Morpheus taller than Neo?") # Assert expected_responses = [ ("morpheus", "neo"), ] assert len(response) == 2 assert any([start in response[0].lower() and end in response[1].lower() for start, end in expected_responses]), ( "Expected two search queries in response but got: " + response[0] ) # ---------------------------------------------------------------------------------------------------- @pytest.mark.chatquality def test_generate_search_query_using_question_from_chat_history(): # Arrange message_list = [ ("What is the name of Mr. Vader's daughter?", "Princess Leia", []), ] # Act response = extract_questions("Does he have any sons?", conversation_log=populate_chat_history(message_list)) # Assert assert len(response) == 1 assert "Vader" in response[0] # ---------------------------------------------------------------------------------------------------- @pytest.mark.chatquality def test_generate_search_query_using_answer_from_chat_history(): # Arrange message_list = [ ("What is the name of Mr. Vader's daughter?", "Princess Leia", []), ] # Act response = extract_questions("Is she a Jedi?", conversation_log=populate_chat_history(message_list)) # Assert assert len(response) == 1 assert "Leia" in response[0] # ---------------------------------------------------------------------------------------------------- @pytest.mark.chatquality def test_generate_search_query_using_question_and_answer_from_chat_history(): # Arrange message_list = [ ("Does Luke Skywalker have any Siblings?", "Yes, Princess Leia", []), ] # Act response = extract_questions("Who is their father?", conversation_log=populate_chat_history(message_list)) # Assert assert len(response) == 1 assert "Leia" in response[0] and "Luke" in response[0] # ---------------------------------------------------------------------------------------------------- @pytest.mark.chatquality def test_generate_search_query_with_date_and_context_from_chat_history(): # Arrange message_list = [ ("When did I visit Masai Mara?", "You visited Masai Mara in April 2000", []), ] # Act response = extract_questions( "What was the Pizza place we ate at over there?", conversation_log=populate_chat_history(message_list) ) # Assert expected_responses = [ ("dt>='2000-04-01'", "dt<'2000-05-01'"), ("dt>='2000-04-01'", "dt<='2000-04-30'"), ('dt>="2000-04-01"', 'dt<"2000-05-01"'), ('dt>="2000-04-01"', 'dt<="2000-04-30"'), ] assert len(response) == 1 assert "Masai Mara" in response[0] assert any([start in response[0] and end in response[0] for start, end in expected_responses]), ( "Expected date filter to limit to April 2000 in response but got: " + response[0] ) # ---------------------------------------------------------------------------------------------------- @pytest.mark.chatquality def test_chat_with_no_chat_history_or_retrieved_content(): # Act response_gen = converse( references=[], # Assume no context retrieved from notes for the user_query user_query="Hello, my name is Testatron. Who are you?", api_key=api_key, ) response = "".join([response_chunk for response_chunk in response_gen]) # Assert expected_responses = ["Khoj", "khoj"] assert len(response) > 0 assert any([expected_response in response for expected_response in expected_responses]), ( "Expected assistants name, [K|k]hoj, in response but got: " + response ) # ---------------------------------------------------------------------------------------------------- @pytest.mark.chatquality def test_answer_from_chat_history_and_no_content(): # Arrange message_list = [ ("Hello, my name is Testatron. Who are you?", "Hi, I am Khoj, a personal assistant. How can I help?", []), ("When was I born?", "You were born on 1st April 1984.", []), ] # Act response_gen = converse( references=[], # Assume no context retrieved from notes for the user_query user_query="What is my name?", conversation_log=populate_chat_history(message_list), api_key=api_key, ) response = "".join([response_chunk for response_chunk in response_gen]) # Assert expected_responses = ["Testatron", "testatron"] assert len(response) > 0 assert any([expected_response in response for expected_response in expected_responses]), ( "Expected [T|t]estatron in response but got: " + response ) # ---------------------------------------------------------------------------------------------------- @pytest.mark.chatquality def test_answer_from_chat_history_and_previously_retrieved_content(): "Chat actor needs to use context in previous notes and chat history to answer question" # Arrange message_list = [ ("Hello, my name is Testatron. Who are you?", "Hi, I am Khoj, a personal assistant. How can I help?", []), ( "When was I born?", "You were born on 1st April 1984.", ["Testatron was born on 1st April 1984 in Testville."], ), ] # Act response_gen = converse( references=[], # Assume no context retrieved from notes for the user_query user_query="Where was I born?", conversation_log=populate_chat_history(message_list), api_key=api_key, ) response = "".join([response_chunk for response_chunk in response_gen]) # Assert assert len(response) > 0 # Infer who I am and use that to infer I was born in Testville using chat history and previously retrieved notes assert "Testville" in response # ---------------------------------------------------------------------------------------------------- @pytest.mark.chatquality def test_answer_from_chat_history_and_currently_retrieved_content(): "Chat actor needs to use context across currently retrieved notes and chat history to answer question" # Arrange message_list = [ ("Hello, my name is Testatron. Who are you?", "Hi, I am Khoj, a personal assistant. How can I help?", []), ("When was I born?", "You were born on 1st April 1984.", []), ] # Act response_gen = converse( references=[ "Testatron was born on 1st April 1984 in Testville." ], # Assume context retrieved from notes for the user_query user_query="Where was I born?", conversation_log=populate_chat_history(message_list), api_key=api_key, ) response = "".join([response_chunk for response_chunk in response_gen]) # Assert assert len(response) > 0 assert "Testville" in response # ---------------------------------------------------------------------------------------------------- @pytest.mark.chatquality def test_refuse_answering_unanswerable_question(): "Chat actor should not try make up answers to unanswerable questions." # Arrange message_list = [ ("Hello, my name is Testatron. Who are you?", "Hi, I am Khoj, a personal assistant. How can I help?", []), ("When was I born?", "You were born on 1st April 1984.", []), ] # Act response_gen = converse( references=[], # Assume no context retrieved from notes for the user_query user_query="Where was I born?", conversation_log=populate_chat_history(message_list), api_key=api_key, ) response = "".join([response_chunk for response_chunk in response_gen]) # Assert expected_responses = [ "don't know", "do not know", "no information", "do not have", "don't have", "cannot answer", "I'm sorry", ] assert len(response) > 0 assert any([expected_response in response for expected_response in expected_responses]), ( "Expected chat actor to say they don't know in response, but got: " + response ) # ---------------------------------------------------------------------------------------------------- @pytest.mark.chatquality def test_answer_requires_current_date_awareness(): "Chat actor should be able to answer questions relative to current date using provided notes" # Arrange context = [ f"""{datetime.now().strftime("%Y-%m-%d")} "Naco Taco" "Tacos for Dinner" Expenses:Food:Dining 10.00 USD""", f"""{datetime.now().strftime("%Y-%m-%d")} "Sagar Ratna" "Dosa for Lunch" Expenses:Food:Dining 10.00 USD""", f"""2020-04-01 "SuperMercado" "Bananas" Expenses:Food:Groceries 10.00 USD""", f"""2020-01-01 "Naco Taco" "Burittos for Dinner" Expenses:Food:Dining 10.00 USD""", ] # Act response_gen = converse( references=context, # Assume context retrieved from notes for the user_query user_query="What did I have for Dinner today?", api_key=api_key, ) response = "".join([response_chunk for response_chunk in response_gen]) # Assert expected_responses = ["tacos", "Tacos"] assert len(response) > 0 assert any([expected_response in response for expected_response in expected_responses]), ( "Expected [T|t]acos in response, but got: " + response ) # ---------------------------------------------------------------------------------------------------- @pytest.mark.chatquality def test_answer_requires_date_aware_aggregation_across_provided_notes(): "Chat actor should be able to answer questions that require date aware aggregation across multiple notes" # Arrange context = [ f"""# {datetime.now().strftime("%Y-%m-%d")} "Naco Taco" "Tacos for Dinner" Expenses:Food:Dining 10.00 USD""", f"""{datetime.now().strftime("%Y-%m-%d")} "Sagar Ratna" "Dosa for Lunch" Expenses:Food:Dining 10.00 USD""", f"""2020-04-01 "SuperMercado" "Bananas" Expenses:Food:Groceries 10.00 USD""", f"""2020-01-01 "Naco Taco" "Burittos for Dinner" Expenses:Food:Dining 10.00 USD""", ] # Act response_gen = converse( references=context, # Assume context retrieved from notes for the user_query user_query="How much did I spend on dining this year?", api_key=api_key, ) response = "".join([response_chunk for response_chunk in response_gen]) # Assert assert len(response) > 0 assert "20" in response # ---------------------------------------------------------------------------------------------------- @pytest.mark.chatquality def test_answer_general_question_not_in_chat_history_or_retrieved_content(): "Chat actor should be able to answer general questions not requiring looking at chat history or notes" # Arrange message_list = [ ("Hello, my name is Testatron. Who are you?", "Hi, I am Khoj, a personal assistant. How can I help?", []), ("When was I born?", "You were born on 1st April 1984.", []), ("Where was I born?", "You were born Testville.", []), ] # Act response_gen = converse( references=[], # Assume no context retrieved from notes for the user_query user_query="Write a haiku about unit testing in 3 lines", conversation_log=populate_chat_history(message_list), api_key=api_key, ) response = "".join([response_chunk for response_chunk in response_gen]) # Assert expected_responses = ["test", "Test"] assert len(response.splitlines()) == 3 # haikus are 3 lines long assert any([expected_response in response for expected_response in expected_responses]), ( "Expected [T|t]est in response, but got: " + response ) # ---------------------------------------------------------------------------------------------------- @pytest.mark.xfail(reason="Chat actor not consistently capable of asking for clarification yet.") @pytest.mark.chatquality def test_ask_for_clarification_if_not_enough_context_in_question(): "Chat actor should ask for clarification if question cannot be answered unambiguously with the provided context" # Arrange context = [ f"""# Ramya My sister, Ramya, is married to Kali Devi. They have 2 kids, Ravi and Rani.""", f"""# Fang My sister, Fang Liu is married to Xi Li. They have 1 kid, Xiao Li.""", f"""# Aiyla My sister, Aiyla is married to Tolga. They have 3 kids, Yildiz, Ali and Ahmet.""", ] # Act response_gen = converse( references=context, # Assume context retrieved from notes for the user_query user_query="How many kids does my older sister have?", api_key=api_key, ) response = "".join([response_chunk for response_chunk in response_gen]) # Assert expected_responses = ["which sister", "Which sister", "which of your sister", "Which of your sister"] assert any([expected_response in response for expected_response in expected_responses]), ( "Expected chat actor to ask for clarification in response, but got: " + response ) # Helpers # ---------------------------------------------------------------------------------------------------- def populate_chat_history(message_list): # Generate conversation logs conversation_log = {"chat": []} for user_message, gpt_message, context in message_list: conversation_log["chat"] += message_to_log( user_message, gpt_message, {"context": context, "intent": {"query": user_message, "inferred-queries": f'["{user_message}"]'}}, ) return conversation_log