refactor: consolidate API to server_api and remove deprecated stacks (#1344)

* chore: delete nebula

* feat: update .gitignore

* feat: delete old product/core files

* feat: delete old product/core files

Author: CaralHsi

.gitignore

@@ -234,6 +234,6 @@ apps/openwork-memos-integration/apps/desktop/public/assets/usecases/
 # Outputs and Evaluation Results
 outputs
 
-evaluation/data/temporal_locomo
+evaluation/data/
 test_add_pipeline.py
 test_file_pipeline.py

Makefile

@@ -36,7 +36,7 @@ pre_commit:
 	poetry run pre-commit run -a
 
 serve:
-	poetry run uvicorn memos.api.start_api:app
+	poetry run uvicorn memos.api.server_api:app
 
 openapi:
 	poetry run memos export_openapi --output docs/openapi.json

README.md

@@ -75,7 +75,7 @@
 - [**72% lower token usage**](https://x.com/MemOS_dev/status/2020854044583924111) — intelligent memory retrieval instead of loading full chat history
 - [**Multi-agent memory sharing**](https://x.com/MemOS_dev/status/2020538135487062094) — multi-instance agents share memory via same user_id, automatic context handoff
 
-Get your API key: [MemOS Dashboard](https://memos-dashboard.openmem.net/cn/login/)  
+Get your API key: [MemOS Dashboard](https://memos-dashboard.openmem.net/cn/login/)
 Full tutorial → [MemOS-Cloud-OpenClaw-Plugin](https://github.com/MemTensor/MemOS-Cloud-OpenClaw-Plugin)
 
 ### 🧠 Local Plugin — 100% On-Device Memory
@@ -84,7 +84,7 @@ Full tutorial → [MemOS-Cloud-OpenClaw-Plugin](https://github.com/MemTensor/Mem
 - **Hybrid search + task & skill evolution** — FTS5 + vector search, auto task summarization, reusable skills that self-upgrade
 - **Multi-agent collaboration + Memory Viewer** — memory isolation, skill sharing, full web dashboard with 7 management pages
 
- 🌐 [Homepage](https://memos-claw.openmem.net) · 
+ 🌐 [Homepage](https://memos-claw.openmem.net) ·
 📖 [Documentation](https://memos-claw.openmem.net/docs/index.html) · 📦 [NPM](https://www.npmjs.com/package/@memtensor/memos-local-openclaw-plugin)
 
 ## 📌 MemOS: Memory Operating System for AI Agents
@@ -104,10 +104,10 @@ Full tutorial → [MemOS-Cloud-OpenClaw-Plugin](https://github.com/MemTensor/Mem
 
 ### News
 
-- **2026-03-08** · 🦞 **MemOS OpenClaw Plugin — Cloud & Local**  
+- **2026-03-08** · 🦞 **MemOS OpenClaw Plugin — Cloud & Local**
   Official OpenClaw memory plugins launched. **Cloud Plugin**: hosted memory service with 72% lower token usage and multi-agent memory sharing ([MemOS-Cloud-OpenClaw-Plugin](https://github.com/MemTensor/MemOS-Cloud-OpenClaw-Plugin)). **Local Plugin** (`v1.0.0`): 100% on-device memory with persistent SQLite, hybrid search (FTS5 + vector), task summarization & skill evolution, multi-agent collaboration, and a full Memory Viewer dashboard.
 
-- **2025-12-24** · 🎉 **MemOS v2.0: Stardust (星尘) Release**  
+- **2025-12-24** · 🎉 **MemOS v2.0: Stardust (星尘) Release**
   Comprehensive KB (doc/URL parsing + cross-project sharing), memory feedback & precise deletion, multi-modal memory (images/charts), tool memory for agent planning, Redis Streams scheduling + DB optimizations, streaming/non-streaming chat, MCP upgrade, and lightweight quick/full deployment.
   <details>
     <summary>✨ <b>New Features</b></summary>
@@ -155,7 +155,7 @@ Full tutorial → [MemOS-Cloud-OpenClaw-Plugin](https://github.com/MemTensor/Mem
   </details>
 
 - **2025-08-07** · 🎉 **MemOS v1.0.0 (MemCube) Release**
-  First MemCube release with a word-game demo, LongMemEval evaluation, BochaAISearchRetriever integration, NebulaGraph support, improved search capabilities, and the official Playground launch.
+  First MemCube release with a word-game demo, LongMemEval evaluation, BochaAISearchRetriever integration, improved search capabilities, and the official Playground launch.
 
   <details>
     <summary>✨ <b>New Features</b></summary>
@@ -176,7 +176,7 @@ Full tutorial → [MemOS-Cloud-OpenClaw-Plugin](https://github.com/MemTensor/Mem
 
   **Plaintext Memory**
   - Integrated internet search with Bocha.
-  - Added support for Nebula database.
+  - Expanded graph database support.
   - Added contextual understanding for the tree-structured plaintext memory search interface.
 
   </details>
@@ -188,7 +188,7 @@ Full tutorial → [MemOS-Cloud-OpenClaw-Plugin](https://github.com/MemTensor/Mem
   - Fixed the concat_cache method.
 
   **Plaintext Memory**
-  - Fixed Nebula search-related issues.
+  - Fixed graph search-related issues.
 
   </details>
 

docker/.env.example

@@ -127,7 +127,7 @@ MEMSCHEDULER_USE_REDIS_QUEUE=false
 
 ## Graph / vector stores
 # Neo4j database selection mode
-NEO4J_BACKEND=neo4j-community             # neo4j-community | neo4j | nebular | polardb
+NEO4J_BACKEND=neo4j-community             # neo4j-community | neo4j | polardb | postgres
 # Neo4j database url
 NEO4J_URI=bolt://localhost:7687           # required when backend=neo4j*
 #  Neo4j database user

examples/mem_agent/deepsearch_example.py

@@ -47,7 +47,7 @@ def build_minimal_components():
 
     # Build component configurations using APIConfig methods (like config_builders.py)
 
-    # Graph DB configuration - using APIConfig.get_nebular_config()
+    # Graph DB configuration - using APIConfig graph DB helpers
     graph_db_backend = os.getenv("NEO4J_BACKEND", "polardb").lower()
     graph_db_backend_map = {
         "polardb": APIConfig.get_polardb_config(),

src/memos/api/config.py

@@ -741,21 +741,6 @@ def get_neo4j_shared_config(user_id: str | None = None) -> dict[str, Any]:
             "embedding_dimension": int(os.getenv("EMBEDDING_DIMENSION", 3072)),
         }
 
-    @staticmethod
-    def get_nebular_config(user_id: str | None = None) -> dict[str, Any]:
-        """Get Nebular configuration."""
-        return {
-            "uri": json.loads(os.getenv("NEBULAR_HOSTS", '["localhost"]')),
-            "user": os.getenv("NEBULAR_USER", "root"),
-            "password": os.getenv("NEBULAR_PASSWORD", "xxxxxx"),
-            "space": os.getenv("NEBULAR_SPACE", "shared-tree-textual-memory"),
-            "user_name": f"memos{user_id.replace('-', '')}",
-            "use_multi_db": False,
-            "auto_create": True,
-            "embedding_dimension": int(os.getenv("EMBEDDING_DIMENSION", 3072)),
-        }
-
-    @staticmethod
     def get_milvus_config():
         return {
             "collection_name": [
@@ -1103,7 +1088,6 @@ def create_user_config(user_name: str, user_id: str) -> tuple["MOSConfig", "Gene
 
         neo4j_community_config = APIConfig.get_neo4j_community_config(user_id)
         neo4j_config = APIConfig.get_neo4j_config(user_id)
-        nebular_config = APIConfig.get_nebular_config(user_id)
         polardb_config = APIConfig.get_polardb_config(user_id)
         internet_config = (
             APIConfig.get_internet_config()
@@ -1114,7 +1098,6 @@ def create_user_config(user_name: str, user_id: str) -> tuple["MOSConfig", "Gene
         graph_db_backend_map = {
             "neo4j-community": neo4j_community_config,
             "neo4j": neo4j_config,
-            "nebular": nebular_config,
             "polardb": polardb_config,
             "postgres": postgres_config,
         }
@@ -1144,9 +1127,9 @@ def create_user_config(user_name: str, user_id: str) -> tuple["MOSConfig", "Gene
                             "reorganize": os.getenv("MOS_ENABLE_REORGANIZE", "false").lower()
                             == "true",
                             "memory_size": {
-                                "WorkingMemory": int(os.getenv("NEBULAR_WORKING_MEMORY", 20)),
-                                "LongTermMemory": int(os.getenv("NEBULAR_LONGTERM_MEMORY", 1e6)),
-                                "UserMemory": int(os.getenv("NEBULAR_USER_MEMORY", 1e6)),
+                                "WorkingMemory": int(os.getenv("MOS_WORKING_MEMORY", 20)),
+                                "LongTermMemory": int(os.getenv("MOS_LONGTERM_MEMORY", 1e6)),
+                                "UserMemory": int(os.getenv("MOS_USER_MEMORY", 1e6)),
                             },
                             "search_strategy": {
                                 "fast_graph": bool(os.getenv("FAST_GRAPH", "false") == "true"),
@@ -1169,7 +1152,7 @@ def create_user_config(user_name: str, user_id: str) -> tuple["MOSConfig", "Gene
                 }
             )
         else:
-            raise ValueError(f"Invalid Neo4j backend: {graph_db_backend}")
+            raise ValueError(f"Invalid graph DB backend: {graph_db_backend}")
         default_mem_cube = GeneralMemCube(default_cube_config)
         return default_config, default_mem_cube
 
@@ -1188,13 +1171,11 @@ def get_default_cube_config() -> "GeneralMemCubeConfig | None":
         openai_config = APIConfig.get_openai_config()
         neo4j_community_config = APIConfig.get_neo4j_community_config(user_id="default")
         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,
         }
@@ -1227,9 +1208,9 @@ def get_default_cube_config() -> "GeneralMemCubeConfig | None":
                             == "true",
                             "internet_retriever": internet_config,
                             "memory_size": {
-                                "WorkingMemory": int(os.getenv("NEBULAR_WORKING_MEMORY", 20)),
-                                "LongTermMemory": int(os.getenv("NEBULAR_LONGTERM_MEMORY", 1e6)),
-                                "UserMemory": int(os.getenv("NEBULAR_USER_MEMORY", 1e6)),
+                                "WorkingMemory": int(os.getenv("MOS_WORKING_MEMORY", 20)),
+                                "LongTermMemory": int(os.getenv("MOS_LONGTERM_MEMORY", 1e6)),
+                                "UserMemory": int(os.getenv("MOS_USER_MEMORY", 1e6)),
                             },
                             "search_strategy": {
                                 "fast_graph": bool(os.getenv("FAST_GRAPH", "false") == "true"),
@@ -1253,4 +1234,4 @@ def get_default_cube_config() -> "GeneralMemCubeConfig | None":
                 }
             )
         else:
-            raise ValueError(f"Invalid Neo4j backend: {graph_db_backend}")
+            raise ValueError(f"Invalid graph DB backend: {graph_db_backend}")

src/memos/api/handlers/base_handler.py

@@ -36,7 +36,6 @@ def __init__(
         vector_db: Any | None = None,
         internet_retriever: Any | None = None,
         memory_manager: Any | None = None,
-        mos_server: Any | None = None,
         feedback_server: Any | None = None,
         **kwargs,
     ):
@@ -54,7 +53,6 @@ def __init__(
             vector_db: Vector database instance
             internet_retriever: Internet retriever instance
             memory_manager: Memory manager instance
-            mos_server: MOS server instance
             **kwargs: Additional dependencies
         """
         self.llm = llm
@@ -68,7 +66,6 @@ def __init__(
         self.vector_db = vector_db
         self.internet_retriever = internet_retriever
         self.memory_manager = memory_manager
-        self.mos_server = mos_server
         self.feedback_server = feedback_server
 
         # Store any additional dependencies
@@ -158,11 +155,6 @@ def vector_db(self):
         """Get vector database instance."""
         return self.deps.vector_db
 
-    @property
-    def mos_server(self):
-        """Get MOS server instance."""
-        return self.deps.mos_server
-
     @property
     def deepsearch_agent(self):
         """Get deepsearch agent instance."""

src/memos/api/handlers/component_init.py

@@ -28,7 +28,6 @@
 from memos.log import get_logger
 from memos.mem_cube.navie import NaiveMemCube
 from memos.mem_feedback.simple_feedback import SimpleMemFeedback
-from memos.mem_os.product_server import MOSServer
 from memos.mem_reader.factory import MemReaderFactory
 from memos.mem_scheduler.orm_modules.base_model import BaseDBManager
 from memos.mem_scheduler.scheduler_factory import SchedulerFactory
@@ -211,15 +210,6 @@ def init_server() -> dict[str, Any]:
 
     logger.debug("Text memory initialized")
 
-    # Initialize MOS Server
-    mos_server = MOSServer(
-        mem_reader=mem_reader,
-        llm=llm,
-        online_bot=False,
-    )
-
-    logger.debug("MOS server initialized")
-
     # Create MemCube with pre-initialized memory instances
     naive_mem_cube = NaiveMemCube(
         text_mem=text_mem,
@@ -304,7 +294,6 @@ def init_server() -> dict[str, Any]:
         "internet_retriever": internet_retriever,
         "memory_manager": memory_manager,
         "default_cube_config": default_cube_config,
-        "mos_server": mos_server,
         "mem_scheduler": mem_scheduler,
         "naive_mem_cube": naive_mem_cube,
         "searcher": searcher,

src/memos/api/handlers/config_builders.py

@@ -39,13 +39,14 @@ def build_graph_db_config(user_id: str = "default") -> dict[str, Any]:
     graph_db_backend_map = {
         "neo4j-community": APIConfig.get_neo4j_community_config(user_id=user_id),
         "neo4j": APIConfig.get_neo4j_config(user_id=user_id),
-        "nebular": APIConfig.get_nebular_config(user_id=user_id),
         "polardb": APIConfig.get_polardb_config(user_id=user_id),
         "postgres": APIConfig.get_postgres_config(user_id=user_id),
     }
 
     # Support both GRAPH_DB_BACKEND and legacy NEO4J_BACKEND env vars
-    graph_db_backend = os.getenv("GRAPH_DB_BACKEND", os.getenv("NEO4J_BACKEND", "nebular")).lower()
+    graph_db_backend = os.getenv(
+        "GRAPH_DB_BACKEND", os.getenv("NEO4J_BACKEND", "neo4j-community")
+    ).lower()
     return GraphDBConfigFactory.model_validate(
         {
             "backend": graph_db_backend,