Fix bug: run Knowledge graph or RAPTOR, it will update an existing task (infiniflow#14102)

### What problem does this PR solve?

It fixed the bug: infiniflow#14101
When run Knowledge graph or RAPTOR, the last document running status
will be wrongly set, see below:
It should never touch existing document result.

![Image](https://github.com/user-attachments/assets/14fe1f9e-0541-4093-8111-ed0bd25b87ba)
### Type of change

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

Author: wangq8

api/apps/kb_app.py

@@ -773,7 +773,7 @@ async def run_mindmap():
     sample_document = documents[0]
     document_ids = [document["id"] for document in documents]
 
-    task_id = queue_raptor_o_graphrag_tasks(sample_doc_id=sample_document, ty="mindmap", priority=0, fake_doc_id=GRAPH_RAPTOR_FAKE_DOC_ID, doc_ids=list(document_ids))
+    task_id = queue_raptor_o_graphrag_tasks(sample_doc=sample_document, ty="mindmap", priority=0, fake_doc_id=GRAPH_RAPTOR_FAKE_DOC_ID, doc_ids=list(document_ids))
 
     if not KnowledgebaseService.update_by_id(kb.id, {"mindmap_task_id": task_id}):
         logging.warning(f"Cannot save mindmap_task_id for kb {kb_id}")

api/apps/services/dataset_api_service.py

@@ -444,7 +444,7 @@ def run_graphrag(dataset_id: str, tenant_id: str):
     sample_document = documents[0]
     document_ids = [document["id"] for document in documents]
 
-    task_id = queue_raptor_o_graphrag_tasks(sample_doc_id=sample_document, ty="graphrag", priority=0, fake_doc_id=GRAPH_RAPTOR_FAKE_DOC_ID, doc_ids=list(document_ids))
+    task_id = queue_raptor_o_graphrag_tasks(sample_doc=sample_document, ty="graphrag", priority=0, fake_doc_id=GRAPH_RAPTOR_FAKE_DOC_ID, doc_ids=list(document_ids))
 
     if not KnowledgebaseService.update_by_id(kb.id, {"graphrag_task_id": task_id}):
         logging.warning(f"Cannot save graphrag_task_id for Dataset {dataset_id}")
@@ -523,7 +523,7 @@ def run_raptor(dataset_id: str, tenant_id: str):
     sample_document = documents[0]
     document_ids = [document["id"] for document in documents]
 
-    task_id = queue_raptor_o_graphrag_tasks(sample_doc_id=sample_document, ty="raptor", priority=0, fake_doc_id=GRAPH_RAPTOR_FAKE_DOC_ID, doc_ids=list(document_ids))
+    task_id = queue_raptor_o_graphrag_tasks(sample_doc=sample_document, ty="raptor", priority=0, fake_doc_id=GRAPH_RAPTOR_FAKE_DOC_ID, doc_ids=list(document_ids))
 
     if not KnowledgebaseService.update_by_id(kb.id, {"raptor_task_id": task_id}):
         logging.warning(f"Cannot save raptor_task_id for Dataset {dataset_id}")

api/db/services/document_service.py

@@ -984,23 +984,22 @@ def run(cls, tenant_id: str, doc: dict, kb_table_num_map: dict):
             queue_tasks(doc, bucket, name, 0)
 
 
-def queue_raptor_o_graphrag_tasks(sample_doc_id, ty, priority, fake_doc_id="", doc_ids=[]):
+def queue_raptor_o_graphrag_tasks(sample_doc, ty, priority, fake_doc_id="", doc_ids=[]):
     """
     You can provide a fake_doc_id to bypass the restriction of tasks at the knowledgebase level.
     Optionally, specify a list of doc_ids to determine which documents participate in the task.
     """
     assert ty in ["graphrag", "raptor", "mindmap"], "type should be graphrag, raptor or mindmap"
 
-    chunking_config = DocumentService.get_chunking_config(sample_doc_id["id"])
+    chunking_config = DocumentService.get_chunking_config(sample_doc["id"])
     hasher = xxhash.xxh64()
     for field in sorted(chunking_config.keys()):
         hasher.update(str(chunking_config[field]).encode("utf-8"))
 
     def new_task():
-        nonlocal sample_doc_id
         return {
             "id": get_uuid(),
-            "doc_id": sample_doc_id["id"],
+            "doc_id": fake_doc_id,
             "from_page": 100000000,
             "to_page": 100000000,
             "task_type": ty,
@@ -1015,9 +1014,8 @@ def new_task():
     task["digest"] = hasher.hexdigest()
     bulk_insert_into_db(Task, [task], True)
 
-    task["doc_id"] = fake_doc_id
     task["doc_ids"] = doc_ids
-    DocumentService.begin2parse(sample_doc_id["id"], keep_progress=True)
+    DocumentService.begin2parse(task["doc_id"], keep_progress=True)
     assert REDIS_CONN.queue_product(settings.get_svr_queue_name(priority), message=task), "Can't access Redis. Please check the Redis' status."
     return task["id"]