diff --git a/src/khoj/processor/conversation/offline/chat_model.py b/src/khoj/processor/conversation/offline/chat_model.py index 8361650c..c366b1fd 100644 --- a/src/khoj/processor/conversation/offline/chat_model.py +++ b/src/khoj/processor/conversation/offline/chat_model.py @@ -171,9 +171,10 @@ def converse_offline( ) # Setup Prompt with Primer or Conversation History + current_date = datetime.now().strftime("%Y-%m-%d") messages = generate_chatml_messages_with_context( conversation_primer, - prompts.system_prompt_message_gpt4all, + prompts.system_prompt_message_gpt4all.format(current_date=current_date), conversation_log, model_name=model, max_prompt_size=max_prompt_size, @@ -198,7 +199,7 @@ def llm_thread(g, messages: List[ChatMessage], model: Any): for message in conversation_history ] - stop_words = [""] + stop_words = ["", "INST]", "Notes:"] chat_history = "".join(formatted_messages) templated_system_message = prompts.system_prompt_gpt4all.format(message=system_message.content) templated_user_message = prompts.user_message_gpt4all.format(message=user_message.content) diff --git a/src/khoj/processor/conversation/prompts.py b/src/khoj/processor/conversation/prompts.py index 67d8725f..bb3bd0a9 100644 --- a/src/khoj/processor/conversation/prompts.py +++ b/src/khoj/processor/conversation/prompts.py @@ -5,7 +5,7 @@ from langchain.prompts import PromptTemplate personality = PromptTemplate.from_template( """ You are Khoj, a smart, inquisitive and helpful personal assistant. -Use your general knowledge and the past conversation with the user as context to inform your responses. +Use your general knowledge and past conversation with the user as context to inform your responses. You were created by Khoj Inc. with the following capabilities: - You *CAN REMEMBER ALL NOTES and PERSONAL INFORMATION FOREVER* that the user ever shares with you. @@ -48,9 +48,17 @@ no_entries_found = PromptTemplate.from_template( ## Conversation Prompts for GPT4All Models ## -- -system_prompt_message_gpt4all = f"""You are Khoj, a smart, inquisitive and helpful personal assistant. -Using your general knowledge and our past conversations as context, answer the following question. -If you do not know the answer, say 'I don't know.'""" +system_prompt_message_gpt4all = PromptTemplate.from_template( + """ +You are Khoj, a smart, inquisitive and helpful personal assistant. +- Use your general knowledge and past conversation with the user as context to inform your responses. +- If you do not know the answer, say 'I don't know.' +- Ask crisp follow-up questions to get additional context, when the answer cannot be inferred from the provided notes or past conversations. +- Do not print verbatim Notes unless necessary. + +Today is {current_date} in UTC. + """.strip() +) 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. - Write the question as if you can search for the answer on the user's personal notes. diff --git a/tests/test_gpt4all_chat_director.py b/tests/test_gpt4all_chat_director.py index 0c6b3b95..7476c4e6 100644 --- a/tests/test_gpt4all_chat_director.py +++ b/tests/test_gpt4all_chat_director.py @@ -298,7 +298,6 @@ def test_answer_not_known_using_notes_command(client_offline_chat, default_user2 # ---------------------------------------------------------------------------------------------------- -@pytest.mark.xfail(AssertionError, reason="Chat director not capable of answering time aware questions yet") @pytest.mark.chatquality @pytest.mark.django_db(transaction=True) @freeze_time("2023-04-01", ignore=["transformers"]) @@ -336,7 +335,6 @@ def test_answer_requires_date_aware_aggregation_across_provided_notes(client_off # ---------------------------------------------------------------------------------------------------- -@pytest.mark.xfail(AssertionError, reason="Chat director not capable of answering this question yet") @pytest.mark.chatquality @pytest.mark.django_db(transaction=True) def test_answer_general_question_not_in_chat_history_or_retrieved_content(client_offline_chat, default_user2):