Fix 'SCORE' not found bug (#4178)

### What problem does this PR solve?

As title

### Type of change

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

---------

Signed-off-by: jinhai <[email protected]>

api/db/services/dialog_service.py

@@ -311,7 +311,7 @@ def chat(dialog, messages, stream=True, **kwargs):
         retrieval_time_cost = (retrieval_ts - generate_keyword_ts) * 1000
         generate_result_time_cost = (finish_chat_ts - retrieval_ts) * 1000
 
-        prompt = f"{prompt} ### Elapsed\n  - Total: {total_time_cost:.1f}ms\n  - Check LLM: {check_llm_time_cost:.1f}ms\n  - Create retriever: {create_retriever_time_cost:.1f}ms\n  - Bind embedding: {bind_embedding_time_cost:.1f}ms\n  - Bind LLM: {bind_llm_time_cost:.1f}ms\n  - Tune question: {refine_question_time_cost:.1f}ms\n  - Bind reranker: {bind_reranker_time_cost:.1f}ms\n  - Generate keyword: {generate_keyword_time_cost:.1f}ms\n  - Retrieval: {retrieval_time_cost:.1f}ms\n  - Generate answer: {generate_result_time_cost:.1f}ms"
+        prompt = f"{prompt}\n\n - Total: {total_time_cost:.1f}ms\n  - Check LLM: {check_llm_time_cost:.1f}ms\n  - Create retriever: {create_retriever_time_cost:.1f}ms\n  - Bind embedding: {bind_embedding_time_cost:.1f}ms\n  - Bind LLM: {bind_llm_time_cost:.1f}ms\n  - Tune question: {refine_question_time_cost:.1f}ms\n  - Bind reranker: {bind_reranker_time_cost:.1f}ms\n  - Generate keyword: {generate_keyword_time_cost:.1f}ms\n  - Retrieval: {retrieval_time_cost:.1f}ms\n  - Generate answer: {generate_result_time_cost:.1f}ms"
         return {"answer": answer, "reference": refs, "prompt": prompt}
 
     if stream:

api/db/services/task_service.py

@@ -204,7 +204,7 @@ def queue_tasks(doc: dict, bucket: str, name: str):
     def new_task():
         return {"id": get_uuid(), "doc_id": doc["id"], "progress": 0.0, "from_page": 0, "to_page": 100000000}
 
-    tsks = []
+    parse_task_array = []
 
     if doc["type"] == FileType.PDF.value:
         file_bin = STORAGE_IMPL.get(bucket, name)
@@ -224,7 +224,7 @@ def queue_tasks(doc: dict, bucket: str, name: str):
                 task = new_task()
                 task["from_page"] = p
                 task["to_page"] = min(p + page_size, e)
-                tsks.append(task)
+                parse_task_array.append(task)
 
     elif doc["parser_id"] == "table":
         file_bin = STORAGE_IMPL.get(bucket, name)
@@ -233,12 +233,12 @@ def queue_tasks(doc: dict, bucket: str, name: str):
             task = new_task()
             task["from_page"] = i
             task["to_page"] = min(i + 3000, rn)
-            tsks.append(task)
+            parse_task_array.append(task)
     else:
-        tsks.append(new_task())
+        parse_task_array.append(new_task())
 
     chunking_config = DocumentService.get_chunking_config(doc["id"])
-    for task in tsks:
+    for task in parse_task_array:
         hasher = xxhash.xxh64()
         for field in sorted(chunking_config.keys()):
             hasher.update(str(chunking_config[field]).encode("utf-8"))
@@ -251,7 +251,7 @@ def queue_tasks(doc: dict, bucket: str, name: str):
     prev_tasks = TaskService.get_tasks(doc["id"])
     ck_num = 0
     if prev_tasks:
-        for task in tsks:
+        for task in parse_task_array:
             ck_num += reuse_prev_task_chunks(task, prev_tasks, chunking_config)
         TaskService.filter_delete([Task.doc_id == doc["id"]])
         chunk_ids = []
@@ -263,13 +263,13 @@ def queue_tasks(doc: dict, bucket: str, name: str):
                                          chunking_config["kb_id"])
     DocumentService.update_by_id(doc["id"], {"chunk_num": ck_num})
 
-    bulk_insert_into_db(Task, tsks, True)
+    bulk_insert_into_db(Task, parse_task_array, True)
     DocumentService.begin2parse(doc["id"])
 
-    tsks = [task for task in tsks if task["progress"] < 1.0]
-    for t in tsks:
+    unfinished_task_array = [task for task in parse_task_array if task["progress"] < 1.0]
+    for unfinished_task in unfinished_task_array:
         assert REDIS_CONN.queue_product(
-            SVR_QUEUE_NAME, message=t
+            SVR_QUEUE_NAME, message=unfinished_task
         ), "Can't access Redis. Please check the Redis' status."
 
 

rag/utils/infinity_conn.py

@@ -342,7 +342,7 @@ class InfinityConnection(DocStoreConnection):
         self.connPool.release_conn(inf_conn)
         res = concat_dataframes(df_list, selectFields)
         if matchExprs:
-            res = res.sort(pl.col("SCORE") + pl.col("pagerank_fea"), descending=True, maintain_order=True)
+            res = res.sort(pl.col("score()") + pl.col("pagerank_fea"), descending=True, maintain_order=True)
         res = res.limit(limit)
         logger.debug(f"INFINITY search final result: {str(res)}")
         return res, total_hits_count