refactor(core): update config parsing and memory management system

.gitignore

@@ -41,4 +41,5 @@ meta_memory/*
 *.sqlite3
 **/data/*.json
 *.db
-memories/*
+memories/*
+.reme/*

benchmark/halumem/eval_reme.py

@@ -220,7 +220,7 @@ async def answer_question_with_memories(
 
     result = await reme.llm.simple_request_for_json(
         prompt=prompt,
-        model_name="qwen-flash"
+        model_name=model_name,
     )
 
     return result

reme/agent/memory/personal/personal_v1_retriever.yaml

@@ -20,7 +20,6 @@ user_message: |
     * Entity-focused queries (extract and search specific names, places, events)
     * Keyword-based searches (core concepts, topics)
     * Related context queries (broader themes)
-  - Review all results before proceeding to next phase
 
   ### Phase 2(Optional): Temporal Search
   **Tool**: `retrieve_memory` (with time filter)
@@ -32,8 +31,7 @@ user_message: |
   - After date: `20200101,99999999` (from 20200101 onwards)
   **Approach**:
   - Identify temporal constraints from the user question
-  - Refine Phase 1 queries with appropriate time filters
-  - Try multiple time ranges if initial searches yield no results
+  - Refine Phase 1 queries with 3-5 diverse appropriate different time filters
 
   ### Phase 3: Deep Dive into History
   **Tool**: `read_history`
@@ -57,6 +55,4 @@ user_message: |
   - If you find sufficient information to answer the user's question, you may output directly without exhausting all search phases
   - Exhaust all search strategies before concluding information doesn't exist
 
-  ### Output any tangentially related findings, Format:
-  [timestamp] [memory/profile/history] [relevant content1]
-  [timestamp] [memory/profile/history] [relevant content2]
+  Output a summary of all retrieved memories, user profile, and history data.

reme/agent/memory/personal/personal_v1_summarizer.yaml

@@ -15,65 +15,41 @@ user_message_s1: |
   - Extract all important information comprehensively—do not miss critical details, but avoid any fabrications or unfounded assumptions
   - The tool will retrieve similar historical memories via vector search to help you in Step 2
 
-  ### Step 2: Update and Add Memories
-  Review each memory draft from Step 1 and compare it with the retrieved historical memories, then use `update_memory` to manage all memories in one call:
+  ### Step 2: Add New Memories
+  Review each memory draft from Step 1 and compare it with the retrieved historical memories, then use `add_memory` to add new memories:
 
-  **For memories_to_update** (updating existing memories):
-  - For each memory to update, fill in the required parameters:
-    * `memory_id`: ID of the historical memory to update (from retrieved memories in Step 1)
-    * `message_time`: timestamp from the conversation (e.g., '2020-01-01 00:00:00')
-    * `memory_content`: updated or consolidated memory content
-  - Update memories when:
-    * The draft contains additional information that should be merged with existing memories
-    * Historical memories need to be corrected or refined based on new information
-
-  **For memories_to_add** (adding new memories):
-  - For each new memory, fill in the required parameters:
-    * `message_time`: timestamp from the conversation (e.g., '2020-01-01 00:00:00')
-    * `memory_content`: memory content
-  - Add memories when:
-    * The draft contains completely new information not present in historical memories
-    * The information cannot be merged into any existing memory
-
-  **General Guidelines:**
+  **Parameters for each memory:**
+  - `message_time`: timestamp from the conversation (e.g., '2020-01-01 00:00:00')
+  - `memory_content`: memory content
+  **When to skip:**
   - **Skip** drafts if their content is already fully covered by historical memories (avoid redundancy)
-  - You can update and add memories in a single `update_memory` tool call
 
 user_message_s2: |
-  You are a Profile Agent responsible for managing profiles about {memory_target}.
+  You are a User Profile Agent responsible for managing user profiles about {memory_target}.
 
   ## Latest Conversation
   Format: round<index> [<timestamp>] <role/name>: <content>
   {context}
 
-  ## Current Profiles
+  ## Current User Profiles
   {profiles}
 
   ## Task
-  Analyze the Latest Conversation and use `update_profiles` to manage profiles (both updates and additions in one call):
+  Analyze the Latest Conversation and use `update_profiles` to manage user profiles (both updates and additions in one call):
 
-  **For profiles_to_update** (updating existing profiles):
+  **For profiles_to_update** (updating existing user profiles):
   - For each profile to update, fill in the required parameters:
-    * `profile_id`: ID of the profile to update (from Current Profiles)
+    * `profile_id`: ID of the profile to update (from Current User Profiles)
     * `message_time`: timestamp from the conversation (e.g., '2020-01-01 00:00:00')
-    * `profile_key`: profile key or category (e.g., 'name', 'age', 'occupation')
-    * `profile_value`: updated profile value (e.g., 'John Smith')
-  - Update profiles when:
-    * Information in the conversation conflicts with or supersedes existing profiles
-    * Profiles need to be consolidated or merged with new information
-    * Existing profile values need to be corrected or refined
+    * `profile_key`: key (e.g., 'name', 'age', 'occupation')
+    * `profile_value`: value (e.g., 'John Smith')
 
-  **For profiles_to_add** (adding new profiles):
+  **For profiles_to_add** (adding new user profiles):
   - For each new profile, fill in the required parameters:
     * `message_time`: timestamp from the conversation (e.g., '2020-01-01 00:00:00')
-    * `profile_key`: profile key or category (e.g., 'name', 'age', 'occupation')
-    * `profile_value`: profile value (e.g., 'John Smith')
-  - Add profiles when:
-    * The information represents a new distinct profile not present in Current Profiles
-    * The profile key doesn't exist in Current Profiles
-    * The information cannot be merged into existing profiles
+    * `profile_key`: key (e.g., 'name', 'age', 'occupation')
+    * `profile_value`: value (e.g., 'John Smith')
 
   **General Guidelines:**
-  - Use actual names from the conversation (e.g., "Bob") instead of generic references (e.g., "user")
-  - Extract all important information comprehensively—do not miss critical details, but avoid any fabrications or unfounded assumptions
-  - You can update and add profiles in a single tool call
+  - Avoid any fabrications or unfounded assumptions
+  - You can update and add user profiles in a single tool call

reme/config/default.yaml

@@ -22,7 +22,7 @@ llm:
     backend: openai
     model_name: qwen3-30b-a3b-instruct-2507
     request_interval: 1
-    temperature: 0.0001
+#    temperature: 0.0001
 
   qwen3_max_instruct:
     backend: openai

reme/core/context/service_context.py

@@ -118,9 +118,7 @@ class ServiceContext(BaseContext):
                 input_args.append(f"config={config_path}")
             if args:
                 input_args.extend(args)
-            if kwargs:
-                input_args.extend([f"{k}={v}" for k, v in kwargs.items()])
-            service_config = parser.parse_args(*input_args)
+            service_config = parser.parse_args(*input_args, **kwargs)
 
         service_config.enable_logo = enable_logo
         if llm:

reme/core/utils/pydantic_config_parser.py

@@ -145,19 +145,8 @@ class PydanticConfigParser:
             raise FileNotFoundError(f"config={config_path} not found")
         return config_path
 
-    def parse_args(self, *args: str) -> T:
-        """Parse CLI arguments and load configs from YAML files.
-
-        Args:
-            *args: CLI arguments in format "key=value" or "config=file.yaml".
-
-        Returns:
-            Validated Pydantic config instance.
-
-        Raises:
-            ValueError: If no config file is specified.
-            FileNotFoundError: If specified config file does not exist.
-        """
+    def parse_args(self, *args: str, **kwargs) -> T:
+        """Parse CLI arguments and load configs from YAML files."""
         configs_to_merge = [self.config_class().model_dump()]
 
         # Separate config file path from other arguments
@@ -184,6 +173,9 @@ class PydanticConfigParser:
         if filter_args:
             configs_to_merge.append(self.parse_dot_notation(filter_args))
 
+        if kwargs:
+            configs_to_merge.append(kwargs)
+
         # Merge all configs and validate
         self.config_dict = self.merge_configs(*configs_to_merge)
         return self.config_class.model_validate(self.config_dict)

reme/reme.py

@@ -36,7 +36,7 @@ from .tool.memory import (
     AddHistory,
     ReadAllProfiles,
     UpdateProfilesV1,
-    UpdateMemoryV1,
+    AddMemory,
 )
 
 
@@ -222,7 +222,7 @@ class ReMe(Application):
                         enable_when_to_use=False,
                         enable_multiple=True,
                     ),
-                    UpdateMemoryV1(
+                    AddMemory(
                         enable_thinking_params=enable_thinking_params,
                         enable_memory_target=False,
                         enable_when_to_use=False,

reme/reme_fs.py

@@ -0,0 +1,41 @@
+"""ReMe File System"""
+
+from .config import ReMeConfigParser
+from .core import Application
+
+
+class ReMeFs(Application):
+    """ReMe File System"""
+
+    def __init__(
+        self,
+        *args,
+        llm_api_key: str | None = None,
+        llm_api_base: str | None = None,
+        embedding_api_key: str | None = None,
+        embedding_api_base: str | None = None,
+        enable_logo: bool = True,
+        llm: dict | None = None,
+        embedding_model: dict | None = None,
+        vector_store: dict | None = None,
+        token_counter: dict | None = None,
+        working_dir: str = "./agent",
+        **kwargs,
+    ):
+        """Initialize ReMe with config."""
+        super().__init__(
+            *args,
+            llm_api_key=llm_api_key,
+            llm_api_base=llm_api_base,
+            embedding_api_key=embedding_api_key,
+            embedding_api_base=embedding_api_base,
+            enable_logo=enable_logo,
+            parser=ReMeConfigParser,
+            llm=llm,
+            embedding_model=embedding_model,
+            vector_store=vector_store,
+            token_counter=token_counter,
+            **kwargs,
+        )
+
+        self.working_dir: str = working_dir