Fix issue of `ask` API. (#5400)

### Type of change

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

api/db/services/conversation_service.py

 from api.utils import get_uuid
 import json
 
+from rag.prompts import chunks_format
+
 
 class ConversationService(CommonService):
     model = Conversation
         reference = {}
         ans["reference"] = {}
 
-    def get_value(d, k1, k2):
-        return d.get(k1, d.get(k2))
-
-    chunk_list = [{
-        "id": get_value(chunk, "chunk_id", "id"),
-        "content": get_value(chunk, "content", "content_with_weight"),
-        "document_id": get_value(chunk, "doc_id", "document_id"),
-        "document_name": get_value(chunk, "docnm_kwd", "document_name"),
-        "dataset_id": get_value(chunk, "kb_id", "dataset_id"),
-        "image_id": get_value(chunk, "image_id", "img_id"),
-        "positions": get_value(chunk, "positions", "position_int"),
-        "url": chunk.get("url")
-    } for chunk in reference.get("chunks", [])]
+    chunk_list = chunks_format(reference)
 
     reference["chunks"] = chunk_list
     ans["id"] = message_id

api/db/services/dialog_service.py

 from rag.app.resume import forbidden_select_fields4resume
 from rag.app.tag import label_question
 from rag.nlp.search import index_name
-from rag.prompts import kb_prompt, message_fit_in, llm_id2llm_type, keyword_extraction, full_question
+from rag.prompts import kb_prompt, message_fit_in, llm_id2llm_type, keyword_extraction, full_question, chunks_format
 from rag.utils import rmSpace, num_tokens_from_string
 from rag.utils.tavily_conn import Tavily
 
 
         if answer.lower().find("invalid key") >= 0 or answer.lower().find("invalid api") >= 0:
             answer += " Please set LLM API-Key in 'User Setting -> Model Providers -> API-Key'"
-        return {"answer": answer, "reference": refs}
+        return {"answer": answer, "reference": chunks_format(refs)}
 
     answer = ""
     for ans in chat_mdl.chat_streamly(prompt, msg, {"temperature": 0.1}):

rag/prompts.py

 from rag.utils import num_tokens_from_string, encoder
 
 
+def chunks_format(reference):
+    def get_value(d, k1, k2):
+        return d.get(k1, d.get(k2))
+
+    return [{
+        "id": get_value(chunk, "chunk_id", "id"),
+        "content": get_value(chunk, "content", "content_with_weight"),
+        "document_id": get_value(chunk, "doc_id", "document_id"),
+        "document_name": get_value(chunk, "docnm_kwd", "document_name"),
+        "dataset_id": get_value(chunk, "kb_id", "dataset_id"),
+        "image_id": get_value(chunk, "image_id", "img_id"),
+        "positions": get_value(chunk, "positions", "position_int"),
+        "url": chunk.get("url")
+    } for chunk in reference.get("chunks", [])]
+
+
 def llm_id2llm_type(llm_id):
     llm_id, _ = TenantLLMService.split_model_name_and_factory(llm_id)
     fnm = os.path.join(get_project_base_directory(), "conf")