feat: add upload skill logic

src/memos/api/product_models.py

@@ -608,6 +608,17 @@ class APIADDRequest(BaseRequest):
         description=("Whether this request represents user feedback. Default: False."),
     )
 
+    # ==== Upload skill flag ====
+    is_upload_skill: bool = Field(
+        False,
+        description=(
+            "Whether this request is an upload skill request. "
+            "When True, the messages field should contain file items "
+            "with zip file download URLs for pre-built skill packages. "
+            "Default: False."
+        ),
+    )
+
     # ==== Backward compatibility fields (will delete later) ====
     mem_cube_id: str | None = Field(
         None,

src/memos/mem_reader/multi_modal_struct.py

@@ -1019,6 +1019,7 @@ def _process_multi_modal_data(
             return fast_memory_items
 
         # Stage: llm_extract — fine mode 4-way parallel LLM + per-source serial
+        is_upload_skill = kwargs.pop("is_upload_skill", False)
         non_file_url_fast_items = [
             item for item in fast_memory_items if not self._is_file_url_only_item(item)
         ]
@@ -1035,14 +1036,17 @@ def _process_multi_modal_data(
                 )
                 future_skill = executor.submit(
                     process_skill_memory_fine,
-                    fast_memory_items=non_file_url_fast_items,
+                    fast_memory_items=fast_memory_items
+                    if is_upload_skill
+                    else non_file_url_fast_items,
                     info=info,
                     searcher=self.searcher,
                     graph_db=self.graph_db,
                     llm=self.general_llm,
                     embedder=self.embedder,
                     oss_config=self.oss_config,
                     skills_dir_config=self.skills_dir_config,
+                    is_upload_skill=is_upload_skill,
                     **kwargs,
                 )
                 future_pref = executor.submit(
@@ -1065,6 +1069,10 @@ def _process_multi_modal_data(
             fine_memory_items.extend(fine_memory_items_pref_parser)
 
             # Part B: per-source serial processing
+            if is_upload_skill:
+                # (skip for upload skill to avoid zip being parsed)
+                return fine_memory_items
+
             with timed_stage("add", "per_source") as ts_ps:
                 for fast_item in fast_memory_items:
                     sources = fast_item.metadata.sources
@@ -1098,6 +1106,8 @@ def _process_transfer_multi_modal_data(
             logger.warning("[MultiModalStruct] No raw nodes found.")
             return []
 
+        is_upload_skill = kwargs.pop("is_upload_skill", False)
+
         # Extract info from raw_nodes (same as simple_struct.py)
         info = {
             "user_id": raw_nodes[0].metadata.user_id,
@@ -1119,14 +1129,15 @@ def _process_transfer_multi_modal_data(
             )
             future_skill = executor.submit(
                 process_skill_memory_fine,
-                non_file_url_nodes,
+                raw_nodes if is_upload_skill else non_file_url_nodes,
                 info,
                 searcher=self.searcher,
                 llm=self.general_llm,
                 embedder=self.embedder,
                 graph_db=self.graph_db,
                 oss_config=self.oss_config,
                 skills_dir_config=self.skills_dir_config,
+                is_upload_skill=is_upload_skill,
                 **kwargs,
             )
             # Add preference memory extraction
@@ -1151,6 +1162,9 @@ def _process_transfer_multi_modal_data(
         fine_memory_items.extend(fine_memory_items_pref_parser)
 
         # Part B: get fine multimodal items
+        if is_upload_skill:
+            # (skip for upload skill to avoid zip being parsed)
+            return fine_memory_items
         for raw_node in raw_nodes:
             sources = raw_node.metadata.sources
             for source in sources:

src/memos/mem_reader/read_skill_memory/process_skill_memory.py

@@ -252,36 +252,6 @@ def create_task(skill_mem, gen_type, prompt, requirements, context, **kwargs):
     return [item[0] for item in raw_skills_data]
 
 
-def add_id_to_mysql(memory_id: str, mem_cube_id: str):
-    """Add id to mysql, will deprecate this function in the future"""
-    # TODO: tmp function, deprecate soon
-    import requests
-
-    skill_mysql_url = os.getenv("SKILLS_MYSQL_URL", "")
-    skill_mysql_bearer = os.getenv("SKILLS_MYSQL_BEARER", "")
-
-    if not skill_mysql_url or not skill_mysql_bearer:
-        logger.warning("[PROCESS_SKILLS] SKILLS_MYSQL_URL or SKILLS_MYSQL_BEARER is not set")
-        return None
-    headers = {"Authorization": skill_mysql_bearer, "Content-Type": "application/json"}
-    data = {"memCubeId": mem_cube_id, "skillId": memory_id}
-    try:
-        response = requests.post(skill_mysql_url, headers=headers, json=data)
-
-        logger.info(f"[PROCESS_SKILLS] response: \n\n{response.json()}")
-        logger.info(f"[PROCESS_SKILLS] memory_id: \n\n{memory_id}")
-        logger.info(f"[PROCESS_SKILLS] mem_cube_id: \n\n{mem_cube_id}")
-        logger.info(f"[PROCESS_SKILLS] skill_mysql_url: \n\n{skill_mysql_url}")
-        logger.info(f"[PROCESS_SKILLS] skill_mysql_bearer: \n\n{skill_mysql_bearer}")
-        logger.info(f"[PROCESS_SKILLS] headers: \n\n{headers}")
-        logger.info(f"[PROCESS_SKILLS] data: \n\n{data}")
-
-        return response.json()
-    except Exception as e:
-        logger.warning(f"[PROCESS_SKILLS] Error adding id to mysql: {e}")
-        return None
-
-
 @require_python_package(
     import_name="alibabacloud_oss_v2",
     install_command="pip install alibabacloud-oss-v2",
@@ -948,6 +918,7 @@ def create_skill_memory_item(
         scripts=skill_memory.get("scripts"),
         others=skill_memory.get("others"),
         url=skill_memory.get("url", ""),
+        skill_source=skill_memory.get("skill_source"),
         manager_user_id=manager_user_id,
         project_id=project_id,
     )
@@ -1024,6 +995,21 @@ def process_skill_memory_fine(
     complete_skill_memory: bool = True,
     **kwargs,
 ) -> list[TextualMemoryItem]:
+    is_upload_skill = kwargs.pop("is_upload_skill", False)
+    if is_upload_skill:
+        from memos.mem_reader.read_skill_memory.upload_skill_memory import (
+            process_upload_skill_memory,
+        )
+
+        return process_upload_skill_memory(
+            fast_memory_items=fast_memory_items,
+            info=info,
+            embedder=embedder,
+            oss_config=oss_config,
+            skills_dir_config=skills_dir_config,
+            **kwargs,
+        )
+
     skills_repo_backend = _get_skill_file_storage_location()
     oss_client, _missing_keys, flag = _skill_init(
         skills_repo_backend, oss_config, skills_dir_config
@@ -1253,6 +1239,7 @@ def _full_extract():
                     if source:
                         skill_sources.append(source)
 
+            skill_memory["skill_source"] = "auto_create"
             memory_item = create_skill_memory_item(
                 skill_memory, info, embedder, sources=skill_sources, **kwargs
             )
@@ -1261,12 +1248,4 @@ def _full_extract():
             logger.warning(f"[PROCESS_SKILLS] Error creating skill memory item: {e}")
             continue
 
-    # TODO: deprecate this funtion and call
-    for skill_memory, skill_memory_item in zip(skill_memories, skill_memory_items, strict=False):
-        if skill_memory.get("update", False) and skill_memory.get("old_memory_id", ""):
-            continue
-        add_id_to_mysql(
-            memory_id=skill_memory_item.id,
-            mem_cube_id=kwargs.get("user_name", info.get("user_id", "")),
-        )
     return skill_memory_items