mirror of
https://github.com/khoj-ai/khoj.git
synced 2024-11-23 23:48:56 +01:00
dd883dc53a
- Remove stale tests - Improve tests to pass across gpt-3.5 and gpt-4-turbo - The haiku creation director was failing because of duplicate query in instantiated prompt
524 lines
19 KiB
Python
524 lines
19 KiB
Python
import os
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from datetime import datetime
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import freezegun
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import pytest
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from freezegun import freeze_time
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from khoj.processor.conversation.openai.gpt import converse, extract_questions
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from khoj.processor.conversation.utils import message_to_log
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from khoj.routers.helpers import (
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aget_relevant_information_sources,
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aget_relevant_output_modes,
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generate_online_subqueries,
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)
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from khoj.utils.helpers import ConversationCommand
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# Initialize variables for tests
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api_key = os.getenv("OPENAI_API_KEY")
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if api_key is None:
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pytest.skip(
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reason="Set OPENAI_API_KEY environment variable to run tests below. Get OpenAI API key from https://platform.openai.com/account/api-keys",
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allow_module_level=True,
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)
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freezegun.configure(extend_ignore_list=["transformers"])
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# Test
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# ----------------------------------------------------------------------------------------------------
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@pytest.mark.chatquality
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@freeze_time("1984-04-02", ignore=["transformers"])
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def test_extract_question_with_date_filter_from_relative_day():
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# Act
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response = extract_questions("Where did I go for dinner yesterday?")
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# Assert
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expected_responses = [
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("dt='1984-04-01'", ""),
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("dt>='1984-04-01'", "dt<'1984-04-02'"),
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("dt>'1984-03-31'", "dt<'1984-04-02'"),
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]
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assert len(response) == 1
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assert any([start in response[0] and end in response[0] for start, end in expected_responses]), (
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"Expected date filter to limit to 1st April 1984 in response but got: " + response[0]
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)
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# ----------------------------------------------------------------------------------------------------
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@pytest.mark.chatquality
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@freeze_time("1984-04-02", ignore=["transformers"])
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def test_extract_question_with_date_filter_from_relative_month():
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# Act
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response = extract_questions("Which countries did I visit last month?")
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# Assert
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expected_responses = [("dt>='1984-03-01'", "dt<'1984-04-01'"), ("dt>='1984-03-01'", "dt<='1984-03-31'")]
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assert len(response) == 1
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assert any([start in response[0] and end in response[0] for start, end in expected_responses]), (
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"Expected date filter to limit to March 1984 in response but got: " + response[0]
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)
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# ----------------------------------------------------------------------------------------------------
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@pytest.mark.chatquality
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@freeze_time("1984-04-02", ignore=["transformers"])
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def test_extract_question_with_date_filter_from_relative_year():
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# Act
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response = extract_questions("Which countries have I visited this year?")
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# Assert
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expected_responses = [
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("dt>='1984-01-01'", ""),
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("dt>='1984-01-01'", "dt<'1985-01-01'"),
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("dt>='1984-01-01'", "dt<='1984-12-31'"),
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]
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assert len(response) == 1
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assert any([start in response[0] and end in response[0] for start, end in expected_responses]), (
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"Expected date filter to limit to 1984 in response but got: " + response[0]
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)
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# ----------------------------------------------------------------------------------------------------
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@pytest.mark.chatquality
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def test_extract_multiple_explicit_questions_from_message():
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# Act
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response = extract_questions("What is the Sun? What is the Moon?")
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# Assert
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expected_responses = [
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("sun", "moon"),
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]
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assert len(response) == 2
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assert any([start in response[0].lower() and end in response[1].lower() for start, end in expected_responses]), (
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"Expected two search queries in response but got: " + response[0]
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)
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# ----------------------------------------------------------------------------------------------------
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@pytest.mark.chatquality
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def test_extract_multiple_implicit_questions_from_message():
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# Act
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response = extract_questions("Is Morpheus taller than Neo?")
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# Assert
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expected_responses = [
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("morpheus", "neo"),
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]
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assert len(response) == 2
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assert any([start in response[0].lower() and end in response[1].lower() for start, end in expected_responses]), (
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"Expected two search queries in response but got: " + response[0]
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)
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# ----------------------------------------------------------------------------------------------------
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@pytest.mark.chatquality
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def test_generate_search_query_using_question_from_chat_history():
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# Arrange
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message_list = [
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("What is the name of Mr. Vader's daughter?", "Princess Leia", []),
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]
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# Act
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response = extract_questions("Does he have any sons?", conversation_log=populate_chat_history(message_list))
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# Assert
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assert len(response) == 1
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assert "Vader" in response[0]
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# ----------------------------------------------------------------------------------------------------
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@pytest.mark.chatquality
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def test_generate_search_query_using_answer_from_chat_history():
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# Arrange
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message_list = [
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("What is the name of Mr. Vader's daughter?", "Princess Leia", []),
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]
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# Act
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response = extract_questions("Is she a Jedi?", conversation_log=populate_chat_history(message_list))
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# Assert
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assert len(response) == 1
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assert "Leia" in response[0]
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# ----------------------------------------------------------------------------------------------------
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@pytest.mark.chatquality
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def test_generate_search_query_using_question_and_answer_from_chat_history():
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# Arrange
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message_list = [
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("Does Luke Skywalker have any Siblings?", "Yes, Princess Leia", []),
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]
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# Act
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response = extract_questions("Who is their father?", conversation_log=populate_chat_history(message_list))
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# Assert
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assert len(response) == 1
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assert "Leia" in response[0] and "Luke" in response[0]
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# ----------------------------------------------------------------------------------------------------
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@pytest.mark.chatquality
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def test_chat_with_no_chat_history_or_retrieved_content():
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# Act
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response_gen = converse(
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references=[], # Assume no context retrieved from notes for the user_query
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user_query="Hello, my name is Testatron. Who are you?",
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api_key=api_key,
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)
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response = "".join([response_chunk for response_chunk in response_gen])
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# Assert
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expected_responses = ["Khoj", "khoj"]
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assert len(response) > 0
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assert any([expected_response in response for expected_response in expected_responses]), (
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"Expected assistants name, [K|k]hoj, in response but got: " + response
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)
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# ----------------------------------------------------------------------------------------------------
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@pytest.mark.chatquality
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def test_answer_from_chat_history_and_no_content():
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# Arrange
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message_list = [
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("Hello, my name is Testatron. Who are you?", "Hi, I am Khoj, a personal assistant. How can I help?", []),
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("When was I born?", "You were born on 1st April 1984.", []),
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]
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# Act
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response_gen = converse(
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references=[], # Assume no context retrieved from notes for the user_query
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user_query="What is my name?",
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conversation_log=populate_chat_history(message_list),
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api_key=api_key,
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)
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response = "".join([response_chunk for response_chunk in response_gen])
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# Assert
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expected_responses = ["Testatron", "testatron"]
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assert len(response) > 0
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assert any([expected_response in response for expected_response in expected_responses]), (
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"Expected [T|t]estatron in response but got: " + response
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)
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# ----------------------------------------------------------------------------------------------------
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@pytest.mark.chatquality
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def test_answer_from_chat_history_and_previously_retrieved_content():
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"Chat actor needs to use context in previous notes and chat history to answer question"
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# Arrange
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message_list = [
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("Hello, my name is Testatron. Who are you?", "Hi, I am Khoj, a personal assistant. How can I help?", []),
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(
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"When was I born?",
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"You were born on 1st April 1984.",
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["Testatron was born on 1st April 1984 in Testville."],
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),
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]
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# Act
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response_gen = converse(
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references=[], # Assume no context retrieved from notes for the user_query
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user_query="Where was I born?",
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conversation_log=populate_chat_history(message_list),
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api_key=api_key,
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)
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response = "".join([response_chunk for response_chunk in response_gen])
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# Assert
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assert len(response) > 0
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# Infer who I am and use that to infer I was born in Testville using chat history and previously retrieved notes
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assert "Testville" in response
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# ----------------------------------------------------------------------------------------------------
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@pytest.mark.chatquality
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def test_answer_from_chat_history_and_currently_retrieved_content():
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"Chat actor needs to use context across currently retrieved notes and chat history to answer question"
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# Arrange
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message_list = [
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("Hello, my name is Testatron. Who are you?", "Hi, I am Khoj, a personal assistant. How can I help?", []),
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("When was I born?", "You were born on 1st April 1984.", []),
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]
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# Act
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response_gen = converse(
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references=[
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"Testatron was born on 1st April 1984 in Testville."
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], # Assume context retrieved from notes for the user_query
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user_query="Where was I born?",
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conversation_log=populate_chat_history(message_list),
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api_key=api_key,
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)
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response = "".join([response_chunk for response_chunk in response_gen])
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# Assert
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assert len(response) > 0
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assert "Testville" in response
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# ----------------------------------------------------------------------------------------------------
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@pytest.mark.chatquality
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def test_refuse_answering_unanswerable_question():
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"Chat actor should not try make up answers to unanswerable questions."
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# Arrange
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message_list = [
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("Hello, my name is Testatron. Who are you?", "Hi, I am Khoj, a personal assistant. How can I help?", []),
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("When was I born?", "You were born on 1st April 1984.", []),
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]
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# Act
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response_gen = converse(
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references=[], # Assume no context retrieved from notes for the user_query
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user_query="Where was I born?",
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conversation_log=populate_chat_history(message_list),
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api_key=api_key,
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)
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response = "".join([response_chunk for response_chunk in response_gen])
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# Assert
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expected_responses = [
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"don't know",
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"do not know",
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"no information",
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"do not have",
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"don't have",
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"cannot answer",
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"I'm sorry",
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]
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assert len(response) > 0
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assert any([expected_response in response for expected_response in expected_responses]), (
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"Expected chat actor to say they don't know in response, but got: " + response
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)
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# ----------------------------------------------------------------------------------------------------
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@pytest.mark.chatquality
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def test_answer_requires_current_date_awareness():
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"Chat actor should be able to answer questions relative to current date using provided notes"
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# Arrange
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context = [
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f"""{datetime.now().strftime("%Y-%m-%d")} "Naco Taco" "Tacos for Dinner"
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Expenses:Food:Dining 10.00 USD""",
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f"""{datetime.now().strftime("%Y-%m-%d")} "Sagar Ratna" "Dosa for Lunch"
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Expenses:Food:Dining 10.00 USD""",
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f"""2020-04-01 "SuperMercado" "Bananas"
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Expenses:Food:Groceries 10.00 USD""",
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f"""2020-01-01 "Naco Taco" "Burittos for Dinner"
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Expenses:Food:Dining 10.00 USD""",
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]
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# Act
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response_gen = converse(
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references=context, # Assume context retrieved from notes for the user_query
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user_query="What did I have for Dinner today?",
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api_key=api_key,
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)
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response = "".join([response_chunk for response_chunk in response_gen])
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# Assert
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expected_responses = ["tacos", "Tacos"]
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assert len(response) > 0
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assert any([expected_response in response for expected_response in expected_responses]), (
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"Expected [T|t]acos in response, but got: " + response
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)
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# ----------------------------------------------------------------------------------------------------
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@pytest.mark.chatquality
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def test_answer_requires_date_aware_aggregation_across_provided_notes():
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"Chat actor should be able to answer questions that require date aware aggregation across multiple notes"
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# Arrange
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context = [
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f"""# {datetime.now().strftime("%Y-%m-%d")} "Naco Taco" "Tacos for Dinner"
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Expenses:Food:Dining 10.00 USD""",
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f"""{datetime.now().strftime("%Y-%m-%d")} "Sagar Ratna" "Dosa for Lunch"
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Expenses:Food:Dining 10.00 USD""",
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f"""2020-04-01 "SuperMercado" "Bananas"
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Expenses:Food:Groceries 10.00 USD""",
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f"""2020-01-01 "Naco Taco" "Burittos for Dinner"
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Expenses:Food:Dining 10.00 USD""",
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]
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# Act
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response_gen = converse(
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references=context, # Assume context retrieved from notes for the user_query
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user_query="How much did I spend on dining this year?",
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api_key=api_key,
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)
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response = "".join([response_chunk for response_chunk in response_gen])
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# Assert
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assert len(response) > 0
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assert "20" in response
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# ----------------------------------------------------------------------------------------------------
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@pytest.mark.chatquality
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def test_answer_general_question_not_in_chat_history_or_retrieved_content():
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"Chat actor should be able to answer general questions not requiring looking at chat history or notes"
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# Arrange
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message_list = [
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("Hello, my name is Testatron. Who are you?", "Hi, I am Khoj, a personal assistant. How can I help?", []),
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("When was I born?", "You were born on 1st April 1984.", []),
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("Where was I born?", "You were born Testville.", []),
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]
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# Act
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response_gen = converse(
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references=[], # Assume no context retrieved from notes for the user_query
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user_query="Write a haiku about unit testing in 3 lines. Do not say anything else",
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conversation_log=populate_chat_history(message_list),
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api_key=api_key,
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)
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response = "".join([response_chunk for response_chunk in response_gen])
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# Assert
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expected_responses = ["test", "Test"]
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assert len(response.splitlines()) == 3 # haikus are 3 lines long
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assert any([expected_response in response for expected_response in expected_responses]), (
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"Expected [T|t]est in response, but got: " + response
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)
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# ----------------------------------------------------------------------------------------------------
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@pytest.mark.xfail(reason="Chat actor not consistently capable of asking for clarification yet.")
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@pytest.mark.chatquality
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def test_ask_for_clarification_if_not_enough_context_in_question():
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"Chat actor should ask for clarification if question cannot be answered unambiguously with the provided context"
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# Arrange
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context = [
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f"""# Ramya
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My sister, Ramya, is married to Kali Devi. They have 2 kids, Ravi and Rani.""",
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f"""# Fang
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My sister, Fang Liu is married to Xi Li. They have 1 kid, Xiao Li.""",
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f"""# Aiyla
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My sister, Aiyla is married to Tolga. They have 3 kids, Yildiz, Ali and Ahmet.""",
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]
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# Act
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response_gen = converse(
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references=context, # Assume context retrieved from notes for the user_query
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user_query="How many kids does my older sister have?",
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api_key=api_key,
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)
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response = "".join([response_chunk for response_chunk in response_gen])
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# Assert
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expected_responses = ["which sister", "Which sister", "which of your sister", "Which of your sister"]
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assert any([expected_response in response for expected_response in expected_responses]), (
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"Expected chat actor to ask for clarification in response, but got: " + response
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)
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# ----------------------------------------------------------------------------------------------------
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@pytest.mark.anyio
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@pytest.mark.django_db(transaction=True)
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@freeze_time("2024-04-04", ignore=["transformers"])
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async def test_websearch_with_operators(chat_client):
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# Arrange
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user_query = "Share popular posts on r/worldnews this month"
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# Act
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responses = await generate_online_subqueries(user_query, {}, None)
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# Assert
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assert any(
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["reddit.com/r/worldnews" in response for response in responses]
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), "Expected a search query to include site:reddit.com but got: " + str(responses)
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assert any(
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["site:reddit.com" in response for response in responses]
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), "Expected a search query to include site:reddit.com but got: " + str(responses)
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assert any(
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["after:2024/04/01" in response for response in responses]
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), "Expected a search query to include after:2024/04/01 but got: " + str(responses)
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# ----------------------------------------------------------------------------------------------------
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@pytest.mark.anyio
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@pytest.mark.django_db(transaction=True)
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async def test_websearch_khoj_website_for_info_about_khoj(chat_client):
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# Arrange
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user_query = "Do you support image search?"
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# Act
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responses = await generate_online_subqueries(user_query, {}, None)
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# Assert
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assert any(
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["site:khoj.dev" in response for response in responses]
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), "Expected search query to include site:khoj.dev but got: " + str(responses)
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# ----------------------------------------------------------------------------------------------------
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@pytest.mark.anyio
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@pytest.mark.django_db(transaction=True)
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async def test_use_default_response_mode(chat_client):
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# Arrange
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user_query = "What's the latest in the Israel/Palestine conflict?"
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# Act
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mode = await aget_relevant_output_modes(user_query, {})
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# Assert
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assert mode.value == "default"
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# ----------------------------------------------------------------------------------------------------
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@pytest.mark.anyio
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@pytest.mark.django_db(transaction=True)
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async def test_use_image_response_mode(chat_client):
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# Arrange
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user_query = "Paint a scenery in Timbuktu in the winter"
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# Act
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mode = await aget_relevant_output_modes(user_query, {})
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# Assert
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assert mode.value == "image"
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# ----------------------------------------------------------------------------------------------------
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@pytest.mark.anyio
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@pytest.mark.django_db(transaction=True)
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async def test_select_data_sources_actor_chooses_to_search_notes(chat_client):
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# Arrange
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user_query = "Where did I learn to swim?"
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# Act
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conversation_commands = await aget_relevant_information_sources(user_query, {})
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|
|
|
# Assert
|
|
assert ConversationCommand.Notes in conversation_commands
|
|
|
|
|
|
# ----------------------------------------------------------------------------------------------------
|
|
@pytest.mark.anyio
|
|
@pytest.mark.django_db(transaction=True)
|
|
async def test_select_data_sources_actor_chooses_to_search_online(chat_client):
|
|
# Arrange
|
|
user_query = "Where is the nearest hospital?"
|
|
|
|
# Act
|
|
conversation_commands = await aget_relevant_information_sources(user_query, {})
|
|
|
|
# Assert
|
|
assert ConversationCommand.Online in conversation_commands
|
|
|
|
|
|
# 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
|