mirror of
https://github.com/khoaliber/khoj.git
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Fix openai chat actor, director tests
- Update test ChatModelOptions setup since update to it's schema - Fix stale function calls using their updated signatures
This commit is contained in:
Debanjum Singh Solanky
@@ -250,7 +250,7 @@ def test_answer_from_chat_history_and_currently_retrieved_content():
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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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{"compiled": "Testatron was born on 1st April 1984 in Testville.", "file": "background.md"}
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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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@@ -304,14 +304,26 @@ 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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{
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"compiled": 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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"file": "Ledger.org",
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},
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{
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"compiled": 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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"file": "Ledger.org",
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},
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{
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"compiled": 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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"file": "Ledger.org",
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},
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{
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"compiled": f"""2020-01-01 "Naco Taco" "Burittos for Dinner"
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Expenses:Food:Dining 10.00 USD""",
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"file": "Ledger.org",
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},
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]
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# Act
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@@ -336,14 +348,26 @@ 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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{
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"compiled": 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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"file": "Ledger.md",
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},
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{
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"compiled": 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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"file": "Ledger.md",
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},
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{
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"compiled": 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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"file": "Ledger.md",
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},
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{
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"compiled": f"""2020-01-01 "Naco Taco" "Burittos for Dinner"
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Expenses:Food:Dining 10.00 USD""",
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"file": "Ledger.md",
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},
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]
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# Act
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@@ -423,9 +447,9 @@ def test_agent_prompt_should_be_used(openai_agent):
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"Chat actor should ask be tuned to think like an accountant based on the agent definition"
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# Arrange
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context = [
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f"""I went to the store and bought some bananas for 2.20""",
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f"""I went to the store and bought some apples for 1.30""",
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f"""I went to the store and bought some oranges for 6.00""",
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{"compiled": f"""I went to the store and bought some bananas for 2.20""", "file": "Ledger.md"},
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{"compiled": f"""I went to the store and bought some apples for 1.30""", "file": "Ledger.md"},
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{"compiled": f"""I went to the store and bought some oranges for 6.00""", "file": "Ledger.md"},
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]
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expected_responses = ["9.50", "9.5"]
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@@ -496,10 +520,10 @@ async def test_websearch_khoj_website_for_info_about_khoj(chat_client):
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@pytest.mark.parametrize(
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"user_query, expected_mode",
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[
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("What's the latest in the Israel/Palestine conflict?", "default"),
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("Summarize the latest tech news every Monday evening", "reminder"),
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("What's the latest in the Israel/Palestine conflict?", "text"),
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("Summarize the latest tech news every Monday evening", "automation"),
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("Paint a scenery in Timbuktu in the winter", "image"),
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("Remind me, when did I last visit the Serengeti?", "default"),
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("Remind me, when did I last visit the Serengeti?", "text"),
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],
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)
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async def test_use_default_response_mode(chat_client, user_query, expected_mode):
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@@ -525,10 +549,10 @@ async def test_select_data_sources_actor_chooses_to_search_notes(
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chat_client, user_query, expected_conversation_commands
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):
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# Act
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conversation_commands = await aget_relevant_information_sources(user_query, {})
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conversation_commands = await aget_relevant_information_sources(user_query, {}, False)
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# Assert
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assert expected_conversation_commands in conversation_commands
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assert set(expected_conversation_commands) == set(conversation_commands)
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# ----------------------------------------------------------------------------------------------------
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@@ -549,46 +573,37 @@ async def test_infer_webpage_urls_actor_extracts_correct_links(chat_client):
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@pytest.mark.anyio
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@pytest.mark.django_db(transaction=True)
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@pytest.mark.parametrize(
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"user_query, location, expected_crontime, expected_qs, unexpected_qs",
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"user_query, expected_crontime, expected_qs, unexpected_qs",
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[
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(
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"Share the weather forecast for the next day daily at 7:30pm",
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("Ubud", "Bali", "Indonesia"),
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"30 11 * * *", # ensure correctly converts to utc
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["weather forecast", "ubud"],
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"30 19 * * *",
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["weather forecast"],
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["7:30"],
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),
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(
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"Notify me when the new President of Brazil is announced",
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("Sao Paulo", "Sao Paulo", "Brazil"),
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"* *", # crontime is variable
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["brazil", "president"],
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["notify"], # ensure reminder isn't re-triggered on scheduled query run
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),
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(
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"Let me know whenever Elon leaves Twitter. Check this every afternoon at 12",
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("Karachi", "Sindh", "Pakistan"),
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"0 7 * * *", # ensure correctly converts to utc
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"0 12 * * *", # ensure correctly converts to utc
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["elon", "twitter"],
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["12"],
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),
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(
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"Draw a wallpaper every morning using the current weather",
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("Bogota", "Cundinamarca", "Colombia"),
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"* * *", # daily crontime
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["weather", "wallpaper", "bogota"],
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["weather", "wallpaper"],
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["every"],
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),
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],
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)
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async def test_infer_task_scheduling_request(
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chat_client, user_query, location, expected_crontime, expected_qs, unexpected_qs
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):
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# Arrange
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location_data = LocationData(city=location[0], region=location[1], country=location[2])
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async def test_infer_task_scheduling_request(chat_client, user_query, expected_crontime, expected_qs, unexpected_qs):
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# Act
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crontime, inferred_query = await schedule_query(user_query, location_data, {})
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crontime, inferred_query, _ = await schedule_query(user_query, {})
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inferred_query = inferred_query.lower()
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# Assert
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