feat: merge v2.0.5 to main

README.md

@@ -269,6 +269,9 @@ Get Free API: [Try API](https://memos-dashboard.openmem.net/quickstart/?source=g
 - **Awesome-AI-Memory**   
  This is a curated repository dedicated to resources on memory and memory systems for large language models. It systematically collects relevant research papers, frameworks, tools, and practical insights. The repository aims to organize and present the rapidly evolving research landscape of LLM memory, bridging multiple research directions including natural language processing, information retrieval, agentic systems, and cognitive science.  
 - **Get started** 👉 [IAAR-Shanghai/Awesome-AI-Memory](https://github.com/IAAR-Shanghai/Awesome-AI-Memory)
+- **MemOS Cloud OpenClaw Plugin**
+  Official OpenClaw lifecycle plugin for MemOS Cloud. It automatically recalls context from MemOS before the agent starts and saves the conversation back to MemOS after the agent finishes.
+- **Get started** 👉 [MemTensor/MemOS-Cloud-OpenClaw-Plugin](https://github.com/MemTensor/MemOS-Cloud-OpenClaw-Plugin)
 
 <br>
 

docker/Dockerfile.krolik

@@ -0,0 +1,65 @@
+# MemOS with Krolik Security Extensions
+# 
+# This Dockerfile builds MemOS with authentication, rate limiting, and admin API.
+# It uses the overlay pattern to keep customizations separate from base code.
+
+FROM python:3.11-slim
+
+# Install system dependencies
+RUN apt-get update && apt-get install -y --no-install-recommends \
+    gcc \
+    g++ \
+    build-essential \
+    libffi-dev \
+    python3-dev \
+    curl \
+    libpq-dev \
+    && rm -rf /var/lib/apt/lists/*
+
+# Create non-root user
+RUN groupadd -r memos && useradd -r -g memos -u 1000 memos
+
+WORKDIR /app
+
+# Use official Hugging Face
+ENV HF_ENDPOINT=https://huggingface.co
+
+# Copy base MemOS source
+COPY src/ ./src/
+COPY pyproject.toml ./
+
+# Install base dependencies
+RUN pip install --upgrade pip && \
+    pip install --no-cache-dir poetry && \
+    poetry config virtualenvs.create false && \
+    poetry install --no-dev --extras "tree-mem mem-scheduler"
+
+# Install additional dependencies for Krolik
+RUN pip install --no-cache-dir \
+    sentence-transformers \
+    torch \
+    transformers \
+    psycopg2-binary \
+    redis
+
+# Apply Krolik overlay (AFTER base install to allow easy updates)
+COPY overlays/krolik/ ./src/memos/
+
+# Create data directory
+RUN mkdir -p /data/memos && chown -R memos:memos /data/memos
+RUN chown -R memos:memos /app
+
+# Set Python path
+ENV PYTHONPATH=/app/src
+
+# Switch to non-root user
+USER memos
+
+EXPOSE 8000
+
+# Healthcheck
+HEALTHCHECK --interval=30s --timeout=10s --retries=3 --start-period=60s \
+    CMD curl -f http://localhost:8000/health || exit 1
+
+# Use extended entry point with security features
+CMD ["gunicorn", "memos.api.server_api_ext:app", "--preload", "-w", "2", "-k", "uvicorn.workers.UvicornWorker", "--bind", "0.0.0.0:8000", "--timeout", "120"]

examples/mem_agent/deepsearch_example.py

@@ -179,7 +179,7 @@ def factory_initialization() -> tuple[DeepSearchMemAgent, dict[str, Any]]:
 
 
 def main():
-    agent_factory, components_factory = factory_initialization()
+    agent_factory, _components_factory = factory_initialization()
     results = agent_factory.run(
         "Caroline met up with friends, family, and mentors in early July 2023.",
         user_id="locomo_exp_user_0_speaker_b_ct-1118",

examples/mem_scheduler/memos_w_scheduler.py

@@ -84,7 +84,9 @@ def init_task():
     return conversations, questions
 
 
-working_memories = []
+default_mem_update_handler = mem_scheduler.handlers.get(MEM_UPDATE_TASK_LABEL)
+if default_mem_update_handler is None:
+    logger.warning("Default MEM_UPDATE handler not found; custom handler will be a no-op.")
 
 
 # Define custom query handler function
@@ -100,24 +102,11 @@ def custom_query_handler(messages: list[ScheduleMessageItem]):
 
 # Define custom memory update handler function
 def custom_mem_update_handler(messages: list[ScheduleMessageItem]):
-    global working_memories
-    search_args = {}
-    top_k = 2
-    for msg in messages:
-        # Search for memories relevant to the current content in text memory (return top_k=2)
-        results = mem_scheduler.retriever.search(
-            query=msg.content,
-            user_id=msg.user_id,
-            mem_cube_id=msg.mem_cube_id,
-            mem_cube=mem_scheduler.current_mem_cube,
-            top_k=top_k,
-            method=mem_scheduler.search_method,
-            search_args=search_args,
-        )
-        working_memories.extend(results)
-        working_memories = working_memories[-5:]
-        for mem in results:
-            print(f"\n[scheduler] Retrieved memory: {mem.memory}")
+    if default_mem_update_handler is None:
+        logger.error("Default MEM_UPDATE handler missing; cannot process messages.")
+        return
+    # Delegate to the built-in handler to keep behavior aligned with scheduler refactor.
+    default_mem_update_handler(messages)
 
 
 async def run_with_scheduler():

examples/mem_scheduler/try_schedule_modules.py

@@ -167,7 +167,8 @@ def add_msgs(
             label=MEM_UPDATE_TASK_LABEL,
             content=query,
         )
-        # Run one session turn manually to get search candidates
-        mem_scheduler._memory_update_consumer(
-            messages=[message],
-        )
+        # Run one session turn manually via registered handler (public surface)
+        handler = mem_scheduler.handlers.get(MEM_UPDATE_TASK_LABEL)
+        if handler is None:
+            raise RuntimeError("MEM_UPDATE handler not registered on mem_scheduler.")
+        handler([message])

src/memos/api/README_api.md

@@ -0,0 +1,13 @@
+# MemOS API
+
+## Default entry and deployment
+
+- Use **`server_api.py`** as the API service entry for **public open-source usage**.
+- You can deploy via **`docker/Dockerfile`**.
+
+The above is the default, general way to run and deploy the API.
+
+## Extensions and reference implementations
+
+- **`server_api_ext.py`** and **`Dockerfile.krolik`** are one developer’s extended API and deployment setup, **for reference only**. They are not yet integrated with cloud services and are still in testing.
+- If you need extensions or custom behavior, you can refer to these and use or adapt them as you like.

src/memos/api/client.py

@@ -31,10 +31,27 @@
 class MemOSClient:
     """MemOS API client"""
 
-    def __init__(self, api_key: str | None = None, base_url: str | None = None):
-        self.base_url = (
-            base_url or os.getenv("MEMOS_BASE_URL") or "https://memos.memtensor.cn/api/openmem/v1"
+    def __init__(
+        self,
+        api_key: str | None = None,
+        base_url: str | None = None,
+        is_global: str | bool = "false",
+    ):
+        # Priority:
+        # 1. base_url argument
+        # 2. MEMOS_BASE_URL environment variable (direct URL)
+        # 3. MEMOS_IS_GLOBAL environment variable (True/False toggle)
+        arg_is_global = str(is_global).lower() in ("true", "1", "yes")
+        memos_is_global = os.getenv("MEMOS_IS_GLOBAL", "false").lower() in ("true", "1", "yes")
+        final_is_global = arg_is_global or memos_is_global
+        default_url = (
+            "https://api.memt.ai/platform/api/openmem/v1"
+            if final_is_global
+            else "https://memos.memtensor.cn/api/openmem/v1"
         )
+
+        self.base_url = base_url or os.getenv("MEMOS_BASE_URL") or default_url
+
         api_key = api_key or os.getenv("MEMOS_API_KEY")
 
         if not api_key:
@@ -56,7 +73,7 @@ def get_message(
         message_limit_number: int = 6,
         source: str | None = None,
     ) -> MemOSGetMessagesResponse | None:
-        """Get messages"""
+        """Get message"""
         # Validate required parameters
         self._validate_required_params(user_id=user_id)
 

src/memos/api/config.py

@@ -538,6 +538,10 @@ def get_internet_config() -> dict[str, Any]:
                         "chunker": {
                             "backend": "sentence",
                             "config": {
+                                "save_rawfile": os.getenv(
+                                    "MEM_READER_SAVE_RAWFILENODE", "true"
+                                ).lower()
+                                == "true",
                                 "tokenizer_or_token_counter": "gpt2",
                                 "chunk_size": 512,
                                 "chunk_overlap": 128,
@@ -676,6 +680,30 @@ def get_polardb_config(user_id: str | None = None) -> dict[str, Any]:
             "embedding_dimension": int(os.getenv("EMBEDDING_DIMENSION", 1024)),
         }
 
+    @staticmethod
+    def get_postgres_config(user_id: str | None = None) -> dict[str, Any]:
+        """Get PostgreSQL + pgvector configuration for MemOS graph storage.
+
+        Uses standard PostgreSQL with pgvector extension.
+        Schema: memos.memories, memos.edges
+        """
+        user_name = os.getenv("MEMOS_USER_NAME", "default")
+        if user_id:
+            user_name = f"memos_{user_id.replace('-', '')}"
+
+        return {
+            "host": os.getenv("POSTGRES_HOST", "postgres"),
+            "port": int(os.getenv("POSTGRES_PORT", "5432")),
+            "user": os.getenv("POSTGRES_USER", "n8n"),
+            "password": os.getenv("POSTGRES_PASSWORD", ""),
+            "db_name": os.getenv("POSTGRES_DB", "n8n"),
+            "schema_name": os.getenv("MEMOS_SCHEMA", "memos"),
+            "user_name": user_name,
+            "use_multi_db": False,
+            "embedding_dimension": int(os.getenv("EMBEDDING_DIMENSION", "384")),
+            "maxconn": int(os.getenv("POSTGRES_MAX_CONN", "20")),
+        }
+
     @staticmethod
     def get_mysql_config() -> dict[str, Any]:
         """Get MySQL configuration."""
@@ -780,6 +808,8 @@ def get_product_default_config() -> dict[str, Any]:
                     "chunker": {
                         "backend": "sentence",
                         "config": {
+                            "save_rawfile": os.getenv("MEM_READER_SAVE_RAWFILENODE", "true").lower()
+                            == "true",
                             "tokenizer_or_token_counter": "gpt2",
                             "chunk_size": 512,
                             "chunk_overlap": 128,
@@ -797,7 +827,12 @@ def get_product_default_config() -> dict[str, Any]:
                     "oss_config": APIConfig.get_oss_config(),
                     "skills_dir_config": {
                         "skills_oss_dir": os.getenv("SKILLS_OSS_DIR", "skill_memory/"),
-                        "skills_local_dir": os.getenv("SKILLS_LOCAL_DIR", "/tmp/skill_memory/"),
+                        "skills_local_tmp_dir": os.getenv(
+                            "SKILLS_LOCAL_TMP_DIR", "/tmp/skill_memory/"
+                        ),
+                        "skills_local_dir": os.getenv(
+                            "SKILLS_LOCAL_DIR", "/tmp/upload_skill_memory/"
+                        ),
                     },
                 },
             },
@@ -895,6 +930,8 @@ def create_user_config(user_name: str, user_id: str) -> tuple["MOSConfig", "Gene
                     "chunker": {
                         "backend": "sentence",
                         "config": {
+                            "save_rawfile": os.getenv("MEM_READER_SAVE_RAWFILENODE", "true").lower()
+                            == "true",
                             "tokenizer_or_token_counter": "gpt2",
                             "chunk_size": 512,
                             "chunk_overlap": 128,
@@ -937,13 +974,18 @@ def create_user_config(user_name: str, user_id: str) -> tuple["MOSConfig", "Gene
             if os.getenv("ENABLE_INTERNET", "false").lower() == "true"
             else None
         )
+        postgres_config = APIConfig.get_postgres_config(user_id=user_id)
         graph_db_backend_map = {
             "neo4j-community": neo4j_community_config,
             "neo4j": neo4j_config,
             "nebular": nebular_config,
             "polardb": polardb_config,
+            "postgres": postgres_config,
         }
-        graph_db_backend = os.getenv("NEO4J_BACKEND", "neo4j-community").lower()
+        # Support both GRAPH_DB_BACKEND and legacy NEO4J_BACKEND env vars
+        graph_db_backend = os.getenv(
+            "GRAPH_DB_BACKEND", os.getenv("NEO4J_BACKEND", "neo4j-community")
+        ).lower()
         if graph_db_backend in graph_db_backend_map:
             # Create MemCube config
 
@@ -1011,18 +1053,23 @@ def get_default_cube_config() -> "GeneralMemCubeConfig | None":
         neo4j_config = APIConfig.get_neo4j_config(user_id="default")
         nebular_config = APIConfig.get_nebular_config(user_id="default")
         polardb_config = APIConfig.get_polardb_config(user_id="default")
+        postgres_config = APIConfig.get_postgres_config(user_id="default")
         graph_db_backend_map = {
             "neo4j-community": neo4j_community_config,
             "neo4j": neo4j_config,
             "nebular": nebular_config,
             "polardb": polardb_config,
+            "postgres": postgres_config,
         }
         internet_config = (
             APIConfig.get_internet_config()
             if os.getenv("ENABLE_INTERNET", "false").lower() == "true"
             else None
         )
-        graph_db_backend = os.getenv("NEO4J_BACKEND", "neo4j-community").lower()
+        # Support both GRAPH_DB_BACKEND and legacy NEO4J_BACKEND env vars
+        graph_db_backend = os.getenv(
+            "GRAPH_DB_BACKEND", os.getenv("NEO4J_BACKEND", "neo4j-community")
+        ).lower()
         if graph_db_backend in graph_db_backend_map:
             return GeneralMemCubeConfig.model_validate(
                 {