chunk-init

applications/async_task/chunk_task.py

@@ -21,7 +21,7 @@ class ChunkEmbeddingTask(TopicAwareChunker):
 
     @staticmethod
     async def get_embedding_list(text: str) -> List:
-        return await get_basic_embedding(text=text, model=DEFAULT_MODEL, dev=True)
+        return await get_basic_embedding(text=text, model=DEFAULT_MODEL)
 
     def init_processer(self):
         self.contents_processor = Contents(self.mysql_pool)

applications/utils/chunks/kg_classifier.py

@@ -43,7 +43,7 @@ class KGClassifier:
         """
         调用 HTTP embedding 服务，返回向量
         """
-        embedding = await get_basic_embedding(text=text, model=DEFAULT_MODEL, dev=True)
+        embedding = await get_basic_embedding(text=text, model=DEFAULT_MODEL)
         return np.array(embedding, dtype=np.float32)
 
     async def classify(

applications/utils/chunks/topic_aware_chunking.py

@@ -103,7 +103,7 @@ class TopicAwareChunker(BoundaryDetector, SplitTextIntoSentences):
     async def _encode_batch(texts: List[str]) -> np.ndarray:
         embs = []
         for t in texts:
-            e = await get_basic_embedding(t, model=DEFAULT_MODEL, dev=True)
+            e = await get_basic_embedding(t, model=DEFAULT_MODEL)
             embs.append(np.array(e, dtype=np.float32))
         return np.stack(embs)