Support customized system prompt base

src/memos/mem_os/core.py

@@ -210,12 +210,16 @@ def _get_all_documents(self, path: str) -> list[str]:
                 documents.append(str(file_path))
         return documents
 
-    def chat(self, query: str, user_id: str | None = None) -> str:
+    def chat(self, query: str, user_id: str | None = None, base_prompt: str | None = None) -> str:
         """
         Chat with the MOS.
 
         Args:
             query (str): The user's query.
+            user_id (str, optional): The user ID for the chat session. Defaults to the user ID from the config.
+            base_prompt (str, optional): A custom base prompt to use for the chat.
+                It can be a template string with a `{memories}` placeholder.
+                If not provided, a default prompt is used.
 
         Returns:
             str: The response from the MOS.
@@ -251,9 +255,9 @@ def chat(self, query: str, user_id: str | None = None) -> str:
                 memories = mem_cube.text_mem.search(query, top_k=self.config.top_k)
                 memories_all.extend(memories)
             logger.info(f"🧠 [Memory] Searched memories:\n{self._str_memories(memories_all)}\n")
-            system_prompt = self._build_system_prompt(memories_all)
+            system_prompt = self._build_system_prompt(memories_all, base_prompt=base_prompt)
         else:
-            system_prompt = self._build_system_prompt()
+            system_prompt = self._build_system_prompt(base_prompt=base_prompt)
         current_messages = [
             {"role": "system", "content": system_prompt},
             *chat_history.chat_history,
@@ -302,27 +306,38 @@ def chat(self, query: str, user_id: str | None = None) -> str:
         return response
 
     def _build_system_prompt(
-        self, memories: list[TextualMemoryItem] | list[str] | None = None
+        self,
+        memories: list[TextualMemoryItem] | list[str] | None = None,
+        base_prompt: str | None = None,
     ) -> str:
         """Build system prompt with optional memories context."""
-        base_prompt = (
-            "You are a knowledgeable and helpful AI assistant. "
-            "You have access to conversation memories that help you provide more personalized responses. "
-            "Use the memories to understand the user's context, preferences, and past interactions. "
-            "If memories are provided, reference them naturally when relevant, but don't explicitly mention having memories."
-        )
+        if base_prompt is None:
+            base_prompt = (
+                "You are a knowledgeable and helpful AI assistant. "
+                "You have access to conversation memories that help you provide more personalized responses. "
+                "Use the memories to understand the user's context, preferences, and past interactions. "
+                "If memories are provided, reference them naturally when relevant, but don't explicitly mention having memories."
+            )
 
+        memory_context = ""
         if memories:
-            memory_context = "\n\n## Memories:\n"
+            memory_list = []
             for i, memory in enumerate(memories, 1):
                 if isinstance(memory, TextualMemoryItem):
                     text_memory = memory.memory
                 else:
                     if not isinstance(memory, str):
                         logger.error("Unexpected memory type.")
                     text_memory = memory
-                memory_context += f"{i}. {text_memory}\n"
-            return base_prompt + memory_context
+                memory_list.append(f"{i}. {text_memory}")
+            memory_context = "\n".join(memory_list)
+
+        if "{memories}" in base_prompt:
+            return base_prompt.format(memories=memory_context)
+        elif memories:
+            # For backward compatibility, append memories if no placeholder is found
+            memory_context_with_header = "\n\n## Memories:\n" + memory_context
+            return base_prompt + memory_context_with_header
         return base_prompt
 
     def _str_memories(

src/memos/mem_os/main.py

@@ -31,13 +31,16 @@ def __init__(self, config: MOSConfig):
             logger.info(PRO_MODE_WELCOME_MESSAGE)
         super().__init__(config)
 
-    def chat(self, query: str, user_id: str | None = None) -> str:
+    def chat(self, query: str, user_id: str | None = None, base_prompt: str | None = None) -> str:
         """
         Enhanced chat method with optional CoT (Chain of Thought) enhancement.
 
         Args:
             query (str): The user's query.
             user_id (str, optional): User ID for context.
+            base_prompt (str, optional): A custom base prompt to use for the chat.
+                It can be a template string with a `{memories}` placeholder.
+                If not provided, a default prompt is used.
 
         Returns:
             str: The response from the MOS.
@@ -46,12 +49,14 @@ def chat(self, query: str, user_id: str | None = None) -> str:
 
         if not self.enable_cot:
             # Use the original chat method from core
-            return super().chat(query, user_id)
+            return super().chat(query, user_id, base_prompt=base_prompt)
 
         # Enhanced chat with CoT decomposition
-        return self._chat_with_cot_enhancement(query, user_id)
+        return self._chat_with_cot_enhancement(query, user_id, base_prompt=base_prompt)
 
-    def _chat_with_cot_enhancement(self, query: str, user_id: str | None = None) -> str:
+    def _chat_with_cot_enhancement(
+        self, query: str, user_id: str | None = None, base_prompt: str | None = None
+    ) -> str:
         """
         Chat with CoT enhancement for complex query decomposition.
         This method includes all the same validation and processing logic as the core chat method.
@@ -84,7 +89,7 @@ def _chat_with_cot_enhancement(self, query: str, user_id: str | None = None) ->
             # Check if the query is complex and needs decomposition
             if not decomposition_result.get("is_complex", False):
                 logger.info("🔍 [CoT] Query is not complex, using standard chat")
-                return super().chat(query, user_id)
+                return super().chat(query, user_id, base_prompt=base_prompt)
 
             sub_questions = decomposition_result.get("sub_questions", [])
             logger.info(f"🔍 [CoT] Decomposed into {len(sub_questions)} sub-questions")
@@ -93,7 +98,7 @@ def _chat_with_cot_enhancement(self, query: str, user_id: str | None = None) ->
             search_engine = self._get_search_engine_for_cot_with_validation(user_cube_ids)
             if not search_engine:
                 logger.warning("🔍 [CoT] No search engine available, using standard chat")
-                return super().chat(query, user_id)
+                return super().chat(query, user_id, base_prompt=base_prompt)
 
             # Step 4: Get answers for sub-questions
             logger.info("🔍 [CoT] Getting answers for sub-questions...")
@@ -115,6 +120,7 @@ def _chat_with_cot_enhancement(self, query: str, user_id: str | None = None) ->
                 chat_history=chat_history,
                 user_id=target_user_id,
                 search_engine=search_engine,
+                base_prompt=base_prompt,
             )
 
             # Step 6: Update chat history (same as core method)
@@ -149,7 +155,7 @@ def _chat_with_cot_enhancement(self, query: str, user_id: str | None = None) ->
         except Exception as e:
             logger.error(f"🔍 [CoT] Error in CoT enhancement: {e}")
             logger.info("🔍 [CoT] Falling back to standard chat")
-            return super().chat(query, user_id)
+            return super().chat(query, user_id, base_prompt=base_prompt)
 
     def _get_search_engine_for_cot_with_validation(
         self, user_cube_ids: list[str]
@@ -183,6 +189,7 @@ def _generate_enhanced_response_with_context(
         chat_history: Any,
         user_id: str | None = None,
         search_engine: BaseTextMemory | None = None,
+        base_prompt: str | None = None,
     ) -> str:
         """
         Generate an enhanced response using sub-questions and their answers, with chat context.
@@ -193,6 +200,8 @@ def _generate_enhanced_response_with_context(
             sub_answers (list[str]): List of answers to sub-questions.
             chat_history: The user's chat history.
             user_id (str, optional): User ID for context.
+            search_engine (BaseTextMemory, optional): Search engine for context retrieval.
+            base_prompt (str, optional): A custom base prompt for the chat.
 
         Returns:
             str: The enhanced response.
@@ -213,10 +222,10 @@ def _generate_enhanced_response_with_context(
                     original_query, top_k=self.config.top_k, mode="fast"
                 )
             system_prompt = self._build_system_prompt(
-                search_memories
+                search_memories, base_prompt=base_prompt
             )  # Use the same system prompt builder
         else:
-            system_prompt = self._build_system_prompt()
+            system_prompt = self._build_system_prompt(base_prompt=base_prompt)
         current_messages = [
             {"role": "system", "content": system_prompt + SYNTHESIS_PROMPT.format(qa_text=qa_text)},
             *chat_history.chat_history,
@@ -261,7 +270,7 @@ def _generate_enhanced_response_with_context(
         except Exception as e:
             logger.error(f"🔍 [CoT] Error generating enhanced response: {e}")
             # Fallback to standard chat
-            return super().chat(original_query, user_id)
+            return super().chat(original_query, user_id, base_prompt=base_prompt)
 
     @classmethod
     def cot_decompose(

tests/mem_os/test_memos.py

@@ -100,3 +100,76 @@ def test_mos_has_core_methods(mock_llm, mock_reader, mock_user_manager, simple_c
     assert callable(mos.chat)
     assert callable(mos.search)
     assert callable(mos.add)
+
+
+@patch("memos.mem_os.core.UserManager")
+@patch("memos.mem_os.core.MemReaderFactory")
+@patch("memos.mem_os.core.LLMFactory")
+@patch("memos.mem_os.main.MOSCore.chat")
+def test_mos_chat_with_custom_prompt_no_cot(
+    mock_core_chat, mock_llm, mock_reader, mock_user_manager, simple_config
+):
+    """Test that MOS.chat passes base_prompt to MOSCore.chat when CoT is disabled."""
+    # Mock all dependencies
+    mock_llm.from_config.return_value = MagicMock()
+    mock_reader.from_config.return_value = MagicMock()
+    user_manager_instance = MagicMock()
+    user_manager_instance.validate_user.return_value = True
+    mock_user_manager.return_value = user_manager_instance
+
+    # Disable CoT
+    simple_config.PRO_MODE = False
+    mos = MOS(simple_config)
+
+    # Call chat with a custom prompt
+    custom_prompt = "You are a helpful bot."
+    mos.chat("Hello", user_id="test_user", base_prompt=custom_prompt)
+
+    # Assert that the core chat method was called with the custom prompt
+    mock_core_chat.assert_called_once_with("Hello", "test_user", base_prompt=custom_prompt)
+
+
+@patch("memos.mem_os.core.UserManager")
+@patch("memos.mem_os.core.MemReaderFactory")
+@patch("memos.mem_os.core.LLMFactory")
+@patch("memos.mem_os.main.MOS._generate_enhanced_response_with_context")
+@patch("memos.mem_os.main.MOS.cot_decompose")
+@patch("memos.mem_os.main.MOS.get_sub_answers")
+def test_mos_chat_with_custom_prompt_with_cot(
+    mock_get_sub_answers,
+    mock_cot_decompose,
+    mock_generate_enhanced_response,
+    mock_llm,
+    mock_reader,
+    mock_user_manager,
+    simple_config,
+):
+    """Test that MOS.chat passes base_prompt correctly when CoT is enabled."""
+    # Mock dependencies
+    mock_llm.from_config.return_value = MagicMock()
+    mock_reader.from_config.return_value = MagicMock()
+    user_manager_instance = MagicMock()
+    user_manager_instance.validate_user.return_value = True
+    user_manager_instance.get_user_cubes.return_value = [MagicMock(cube_id="test_cube")]
+    mock_user_manager.return_value = user_manager_instance
+
+    # Mock CoT process
+    mock_cot_decompose.return_value = {"is_complex": True, "sub_questions": ["Sub-question 1"]}
+    mock_get_sub_answers.return_value = (["Sub-question 1"], ["Sub-answer 1"])
+
+    # Enable CoT
+    simple_config.PRO_MODE = True
+    mos = MOS(simple_config)
+
+    # Mock the search engine to avoid errors
+    mos.mem_cubes["test_cube"] = MagicMock()
+    mos.mem_cubes["test_cube"].text_mem = MagicMock()
+
+    # Call chat with a custom prompt
+    custom_prompt = "You are a super helpful bot. Context: {memories}"
+    mos.chat("Complex question", user_id="test_user", base_prompt=custom_prompt)
+
+    # Assert that the enhanced response generator was called with the prompt
+    mock_generate_enhanced_response.assert_called_once()
+    call_args = mock_generate_enhanced_response.call_args[1]
+    assert call_args.get("base_prompt") == custom_prompt

tests/mem_os/test_memos_core.py

@@ -592,6 +592,44 @@ def test_chat_with_memories(
         assert mos.chat_history_manager["test_user"].chat_history[1]["role"] == "assistant"
         assert mos.chat_history_manager["test_user"].chat_history[1]["content"] == response
 
+    @patch("memos.mem_os.core.UserManager")
+    @patch("memos.mem_os.core.MemReaderFactory")
+    @patch("memos.mem_os.core.LLMFactory")
+    def test_chat_with_custom_base_prompt(
+        self,
+        mock_llm_factory,
+        mock_reader_factory,
+        mock_user_manager_class,
+        mock_config,
+        mock_llm,
+        mock_mem_reader,
+        mock_user_manager,
+        mock_mem_cube,
+    ):
+        """Test chat functionality with a custom base prompt."""
+        # Setup mocks
+        mock_llm_factory.from_config.return_value = mock_llm
+        mock_reader_factory.from_config.return_value = mock_mem_reader
+        mock_user_manager_class.return_value = mock_user_manager
+
+        mos = MOSCore(MOSConfig(**mock_config))
+        mos.mem_cubes["test_cube_1"] = mock_mem_cube
+        mos.mem_cubes["test_cube_2"] = mock_mem_cube
+
+        custom_prompt = "You are a pirate. Answer as such. User memories: {memories}"
+        mos.chat("What do I like?", base_prompt=custom_prompt)
+
+        # Verify that the system prompt passed to the LLM is the custom one
+        mock_llm.generate.assert_called_once()
+        call_args = mock_llm.generate.call_args[0]
+        messages = call_args[0]
+        system_prompt = messages[0]["content"]
+
+        assert "You are a pirate." in system_prompt
+        assert "You are a knowledgeable and helpful AI assistant." not in system_prompt
+        assert "User memories:" in system_prompt
+        assert "I like playing football" in system_prompt  # Check if memory is interpolated
+
     @patch("memos.mem_os.core.UserManager")
     @patch("memos.mem_os.core.MemReaderFactory")
     @patch("memos.mem_os.core.LLMFactory")
@@ -664,6 +702,60 @@ def test_clear_messages(
         assert mos.chat_history_manager["test_user"].user_id == "test_user"
 
 
+class TestMOSSystemPrompt:
+    """Test the _build_system_prompt method in MOSCore."""
+
+    @pytest.fixture
+    def mos_core_instance(self, mock_config, mock_user_manager):
+        """Fixture to create a MOSCore instance for testing the prompt builder."""
+        with patch("memos.mem_os.core.LLMFactory"), patch("memos.mem_os.core.MemReaderFactory"):
+            return MOSCore(MOSConfig(**mock_config), user_manager=mock_user_manager)
+
+    def test_build_prompt_with_template_and_memories(self, mos_core_instance):
+        """Test prompt with a template and memories."""
+        base_prompt = "You are a sales agent. Here are past interactions: {memories}"
+        memories = [TextualMemoryItem(memory="User likes blue cars.")]
+        prompt = mos_core_instance._build_system_prompt(memories, base_prompt)
+        assert "You are a sales agent." in prompt
+        assert "1. User likes blue cars." in prompt
+        assert "{memories}" not in prompt
+
+    def test_build_prompt_with_template_no_memories(self, mos_core_instance):
+        """Test prompt with a template but no memories."""
+        base_prompt = "You are a sales agent. Here are past interactions: {memories}"
+        prompt = mos_core_instance._build_system_prompt(None, base_prompt)
+        assert "You are a sales agent." in prompt
+        assert "Here are past interactions:" in prompt
+        # The placeholder should be replaced with an empty string
+        assert "{memories}" not in prompt
+        # Check that the output is clean
+        assert prompt.strip() == "You are a sales agent. Here are past interactions:"
+        assert "## Memories:" not in prompt
+
+    def test_build_prompt_no_template_with_memories(self, mos_core_instance):
+        """Test prompt without a template but with memories (backward compatibility)."""
+        base_prompt = "You are a helpful assistant."
+        memories = [TextualMemoryItem(memory="User is a developer.")]
+        prompt = mos_core_instance._build_system_prompt(memories, base_prompt)
+        assert "You are a helpful assistant." in prompt
+        assert "## Memories:" in prompt
+        assert "1. User is a developer." in prompt
+
+    def test_build_prompt_default_with_memories(self, mos_core_instance):
+        """Test default prompt with memories."""
+        memories = [TextualMemoryItem(memory="User lives in New York.")]
+        prompt = mos_core_instance._build_system_prompt(memories)
+        assert "You are a knowledgeable and helpful AI assistant." in prompt
+        assert "## Memories:" in prompt
+        assert "1. User lives in New York." in prompt
+
+    def test_build_prompt_default_no_memories(self, mos_core_instance):
+        """Test default prompt without any memories."""
+        prompt = mos_core_instance._build_system_prompt()
+        assert "You are a knowledgeable and helpful AI assistant." in prompt
+        assert "## Memories:" not in prompt
+
+
 class TestMOSErrorHandling:
     """Test MOS error handling."""