Fix: ollama model list issue. (#11175)

### Type of change

- [x] Bug Fix (non-breaking change which fixes an issue)

api/apps/llm_app.py

@@ -358,7 +358,7 @@ def list_app():
         for o in objs:
             if o.llm_name + "@" + o.llm_factory in llm_set:
                 continue
-            llms.append({"llm_name": o.llm_name, "model_type": o.model_type, "fid": o.llm_factory, "available": True})
+            llms.append({"llm_name": o.llm_name, "model_type": o.model_type, "fid": o.llm_factory, "available": True, "status": StatusEnum.VALID.value})
 
         res = {}
         for m in llms:

api/db/init_data.py

@@ -101,6 +101,7 @@ def init_llm_factory():
         info = deepcopy(factory_llm_info)
         llm_infos = info.pop("llm")
         try:
+            LLMFactoriesService.filter_delete([LLMFactories.name == factory_llm_info["name"]])
             LLMFactoriesService.save(**info)
         except Exception:
             pass

api/db/services/document_service.py

@@ -846,7 +846,7 @@ def queue_raptor_o_graphrag_tasks(sample_doc_id, ty, priority, fake_doc_id="", d
             "to_page": 100000000,
             "task_type": ty,
             "progress_msg":  datetime.now().strftime("%H:%M:%S") + " created task " + ty,
-            "begin_at": datetime.now(),
+            "begin_at": datetime.now().strftime("%Y-%m-%d %H:%M:%S"),
         }
 
     task = new_task()

rag/raptor.py

@@ -97,7 +97,7 @@ class RecursiveAbstractiveProcessing4TreeOrganizedRetrieval:
     async def __call__(self, chunks, random_state, callback=None, task_id: str = ""):
         if len(chunks) <= 1:
             return []
-        chunks = [(s, a) for s, a in chunks if s and a and len(a) > 0]
+        chunks = [(s, a) for s, a in chunks if s and a is not None and len(a) > 0]
         layers = [(0, len(chunks))]
         start, end = 0, len(chunks)
 

rag/svr/task_executor.py

@@ -647,7 +647,7 @@ async def run_raptor_for_kb(row, kb_parser_config, chat_mdl, embd_mdl, vector_si
 
     res = []
     tk_count = 0
-    async def generate(chunks):
+    async def generate(chunks, did):
         nonlocal tk_count, res
         raptor = Raptor(
             raptor_config.get("max_cluster", 64),
@@ -660,7 +660,7 @@ async def run_raptor_for_kb(row, kb_parser_config, chat_mdl, embd_mdl, vector_si
         original_length = len(chunks)
         chunks = await raptor(chunks, kb_parser_config["raptor"]["random_seed"], callback, row["id"])
         doc = {
-            "doc_id": fake_doc_id,
+            "doc_id": did,
             "kb_id": [str(row["kb_id"])],
             "docnm_kwd": row["name"],
             "title_tks": rag_tokenizer.tokenize(row["name"]),
@@ -688,9 +688,8 @@ async def run_raptor_for_kb(row, kb_parser_config, chat_mdl, embd_mdl, vector_si
                                                  fields=["content_with_weight", vctr_nm],
                                                  sort_by_position=True):
                 chunks.append((d["content_with_weight"], np.array(d[vctr_nm])))
-            callback(progress=(x+1.)/len(doc_ids))
+            await generate(chunks, doc_id)
-            await generate(chunks)
+            callback(prog=(x+1.)/len(doc_ids))
-
     else:
         chunks = []
         for doc_id in doc_ids:
@@ -699,7 +698,7 @@ async def run_raptor_for_kb(row, kb_parser_config, chat_mdl, embd_mdl, vector_si
                                                  sort_by_position=True):
                 chunks.append((d["content_with_weight"], np.array(d[vctr_nm])))
 
-        await generate(chunks)
+        await generate(chunks, fake_doc_id)
 
     return res, tk_count