Browse Source

fix: unify log format, use placeholders instead of string concatenation (#24544)

tags/1.8.0
GuanMu 2 months ago
parent
commit
47f480c0dc
No account linked to committer's email address

+ 1
- 1
api/core/llm_generator/llm_generator.py View File

error = str(e) error = str(e)
return {"error": f"Failed to generate code. Error: {error}"} return {"error": f"Failed to generate code. Error: {error}"}
except Exception as e: except Exception as e:
logging.exception("Failed to invoke LLM model, model: " + json.dumps(model_config.get("name")), exc_info=e)
logging.exception("Failed to invoke LLM model, model: %s", model_config.get("name"), exc_info=e)
return {"error": f"An unexpected error occurred: {str(e)}"} return {"error": f"An unexpected error occurred: {str(e)}"}

+ 2
- 2
api/core/rag/datasource/vdb/tidb_vector/tidb_vector.py View File

self._dimension = 1536 self._dimension = 1536


def create(self, texts: list[Document], embeddings: list[list[float]], **kwargs): def create(self, texts: list[Document], embeddings: list[list[float]], **kwargs):
logger.info("create collection and add texts, collection_name: " + self._collection_name)
logger.info("create collection and add texts, collection_name: %s", self._collection_name)
self._create_collection(len(embeddings[0])) self._create_collection(len(embeddings[0]))
self.add_texts(texts, embeddings) self.add_texts(texts, embeddings)
self._dimension = len(embeddings[0]) self._dimension = len(embeddings[0])
pass pass


def _create_collection(self, dimension: int): def _create_collection(self, dimension: int):
logger.info("_create_collection, collection_name " + self._collection_name)
logger.info("_create_collection, collection_name %s", self._collection_name)
lock_name = f"vector_indexing_lock_{self._collection_name}" lock_name = f"vector_indexing_lock_{self._collection_name}"
with redis_client.lock(lock_name, timeout=20): with redis_client.lock(lock_name, timeout=20):
collection_exist_cache_key = f"vector_indexing_{self._collection_name}" collection_exist_cache_key = f"vector_indexing_{self._collection_name}"

+ 1
- 1
api/core/rag/embedding/cached_embedding.py View File

db.session.rollback() db.session.rollback()
except Exception as ex: except Exception as ex:
db.session.rollback() db.session.rollback()
logger.exception("Failed to embed documents: %s")
logger.exception("Failed to embed documents")
raise ex raise ex


return text_embeddings return text_embeddings

Loading…
Cancel
Save