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Make Offline Chat Date Aware (#636)
- Provide more context and instructions to offline chat on Khoj - Upgrade offilne chat quality tests to support more use-cases ### Details - Improve offline chat system prompt to think step by step - Make offline chat model current date aware. Improve system prompts - Fix actor, director tests using freeze time by ignoring transformers package
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commit
c6fa98ce3e
6 changed files with 30 additions and 22 deletions
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@ -171,9 +171,10 @@ def converse_offline(
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)
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# Setup Prompt with Primer or Conversation History
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current_date = datetime.now().strftime("%Y-%m-%d")
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messages = generate_chatml_messages_with_context(
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conversation_primer,
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prompts.system_prompt_message_gpt4all,
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prompts.system_prompt_message_gpt4all.format(current_date=current_date),
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conversation_log,
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model_name=model,
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max_prompt_size=max_prompt_size,
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@ -198,7 +199,7 @@ def llm_thread(g, messages: List[ChatMessage], model: Any):
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for message in conversation_history
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]
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stop_words = ["<s>"]
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stop_words = ["<s>", "INST]", "Notes:"]
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chat_history = "".join(formatted_messages)
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templated_system_message = prompts.system_prompt_gpt4all.format(message=system_message.content)
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templated_user_message = prompts.user_message_gpt4all.format(message=user_message.content)
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@ -5,7 +5,7 @@ from langchain.prompts import PromptTemplate
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personality = PromptTemplate.from_template(
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"""
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You are Khoj, a smart, inquisitive and helpful personal assistant.
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Use your general knowledge and the past conversation with the user as context to inform your responses.
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Use your general knowledge and past conversation with the user as context to inform your responses.
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You were created by Khoj Inc. with the following capabilities:
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- You *CAN REMEMBER ALL NOTES and PERSONAL INFORMATION FOREVER* that the user ever shares with you.
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@ -48,9 +48,17 @@ no_entries_found = PromptTemplate.from_template(
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## Conversation Prompts for GPT4All Models
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## --
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system_prompt_message_gpt4all = f"""You are Khoj, a smart, inquisitive and helpful personal assistant.
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Using your general knowledge and our past conversations as context, answer the following question.
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If you do not know the answer, say 'I don't know.'"""
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system_prompt_message_gpt4all = PromptTemplate.from_template(
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"""
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You are Khoj, a smart, inquisitive and helpful personal assistant.
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- Use your general knowledge and past conversation with the user as context to inform your responses.
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- If you do not know the answer, say 'I don't know.'
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- Think step-by-step and ask questions to get the necessary information to answer the user's question.
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- Do not print verbatim Notes unless necessary.
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Today is {current_date} in UTC.
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""".strip()
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)
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system_prompt_message_extract_questions_gpt4all = f"""You are Khoj, a kind and intelligent personal assistant. When the user asks you a question, you ask follow-up questions to clarify the necessary information you need in order to answer from the user's perspective.
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- Write the question as if you can search for the answer on the user's personal notes.
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@ -41,7 +41,7 @@ freezegun.configure(extend_ignore_list=["transformers"])
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# ----------------------------------------------------------------------------------------------------
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@pytest.mark.xfail(reason="Search actor isn't very date aware nor capable of formatting")
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@pytest.mark.chatquality
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@freeze_time("1984-04-02")
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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(loaded_model):
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# Act
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response = extract_questions_offline("Where did I go for dinner yesterday?", loaded_model=loaded_model)
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@ -61,7 +61,7 @@ def test_extract_question_with_date_filter_from_relative_day(loaded_model):
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# ----------------------------------------------------------------------------------------------------
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@pytest.mark.xfail(reason="Search actor still isn't very date aware nor capable of formatting")
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@pytest.mark.chatquality
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@freeze_time("1984-04-02")
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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(loaded_model):
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# Act
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response = extract_questions_offline("Which countries did I visit last month?", loaded_model=loaded_model)
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@ -83,7 +83,7 @@ def test_extract_question_with_date_filter_from_relative_month(loaded_model):
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# ----------------------------------------------------------------------------------------------------
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@pytest.mark.xfail(reason="Chat actor still isn't very date aware nor capable of formatting")
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@pytest.mark.chatquality
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@freeze_time("1984-04-02")
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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_offline("Which countries have I visited this year?")
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@ -102,7 +102,7 @@ def test_extract_question_with_date_filter_from_relative_year():
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# ----------------------------------------------------------------------------------------------------
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@pytest.mark.chatquality
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@freeze_time("1984-04-02")
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@freeze_time("1984-04-02", ignore=["transformers"])
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def test_extract_question_includes_root_question(loaded_model):
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# Act
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response = extract_questions_offline("Which countries have I visited this year?", loaded_model=loaded_model)
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@ -298,14 +298,16 @@ def test_answer_not_known_using_notes_command(client_offline_chat, default_user2
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# ----------------------------------------------------------------------------------------------------
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@pytest.mark.xfail(AssertionError, reason="Chat director not capable of answering time aware questions yet")
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@pytest.mark.chatquality
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@pytest.mark.django_db(transaction=True)
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@freeze_time("2023-04-01")
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@freeze_time("2023-04-01", ignore=["transformers"])
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def test_answer_requires_current_date_awareness(client_offline_chat):
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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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query = urllib.parse.quote("Where did I have lunch today?")
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# Act
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response = client_offline_chat.get(f'/api/chat?q="Where did I have lunch today?"&stream=true')
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response = client_offline_chat.get(f"/api/chat?q={query}&stream=true")
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response_message = response.content.decode("utf-8")
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# Assert
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@ -320,7 +322,7 @@ def test_answer_requires_current_date_awareness(client_offline_chat):
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@pytest.mark.xfail(AssertionError, reason="Chat director not capable of answering this question yet")
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@pytest.mark.chatquality
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@pytest.mark.django_db(transaction=True)
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@freeze_time("2023-04-01")
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@freeze_time("2023-04-01", ignore=["transformers"])
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def test_answer_requires_date_aware_aggregation_across_provided_notes(client_offline_chat):
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"Chat director should be able to answer questions that require date aware aggregation across multiple notes"
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# Act
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@ -333,7 +335,6 @@ def test_answer_requires_date_aware_aggregation_across_provided_notes(client_off
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# ----------------------------------------------------------------------------------------------------
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@pytest.mark.xfail(AssertionError, reason="Chat director not capable of answering this question yet")
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@pytest.mark.chatquality
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@pytest.mark.django_db(transaction=True)
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def test_answer_general_question_not_in_chat_history_or_retrieved_content(client_offline_chat, default_user2):
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@ -425,7 +426,6 @@ def test_answer_chat_history_very_long(client_offline_chat, default_user2):
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# ----------------------------------------------------------------------------------------------------
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@pytest.mark.xfail(AssertionError, reason="Chat director not capable of answering this question yet")
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@pytest.mark.chatquality
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@pytest.mark.django_db(transaction=True)
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def test_answer_requires_multiple_independent_searches(client_offline_chat):
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@ -22,7 +22,7 @@ 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")
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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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@ -41,7 +41,7 @@ def test_extract_question_with_date_filter_from_relative_day():
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# ----------------------------------------------------------------------------------------------------
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@pytest.mark.chatquality
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@freeze_time("1984-04-02")
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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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@ -56,7 +56,7 @@ def test_extract_question_with_date_filter_from_relative_month():
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# ----------------------------------------------------------------------------------------------------
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@pytest.mark.chatquality
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@freeze_time("1984-04-02")
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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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@ -277,7 +277,7 @@ def test_answer_not_known_using_notes_command(chat_client_no_background, default
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@pytest.mark.xfail(AssertionError, reason="Chat director not capable of answering time aware questions yet")
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@pytest.mark.django_db(transaction=True)
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@pytest.mark.chatquality
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@freeze_time("2023-04-01")
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@freeze_time("2023-04-01", ignore=["transformers"])
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def test_answer_requires_current_date_awareness(chat_client):
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"Chat actor should be able to answer questions relative to current date using provided notes"
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# Act
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@ -295,11 +295,10 @@ def test_answer_requires_current_date_awareness(chat_client):
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# ----------------------------------------------------------------------------------------------------
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@pytest.mark.django_db(transaction=True)
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@pytest.mark.chatquality
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@freeze_time("2023-04-01")
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@freeze_time("2023-04-01", ignore=["transformers"])
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def test_answer_requires_date_aware_aggregation_across_provided_notes(chat_client):
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"Chat director should be able to answer questions that require date aware aggregation across multiple notes"
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# Act
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response = chat_client.get(f'/api/chat?q="How much did I spend on dining this year?"&stream=true')
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response_message = response.content.decode("utf-8")
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