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style: add path to yaml

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0Xiao0
2025-04-03 18:10:32 +08:00
parent 1ee838327e
commit eb9ec3c0bf
8 changed files with 98 additions and 49 deletions
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22
src/blackbox/chroma_upsert.py
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@ -21,6 +21,10 @@ import logging
from ..log.logging_time import logging_time
import re
from pathlib import Path
from ..configuration import Configuration
from ..configuration import PathConf
logger = logging.getLogger
DEFAULT_COLLECTION_ID = "123"
@ -31,9 +35,13 @@ class ChromaUpsert(Blackbox):
def __init__(self, *args, **kwargs) -> None:
# config = read_yaml(args[0])
# load embedding model
self.embedding_model_1 = SentenceTransformerEmbeddings(model_name="/Workspace/Models/BAAI/bge-large-zh-v1.5", model_kwargs={"device": "cuda"})
path = PathConf(Configuration())
self.model_path = Path(path.chroma_rerank_embedding_model)
self.embedding_model_1 = SentenceTransformerEmbeddings(model_name=str(self.model_path / "bge-large-zh-v1.5"), model_kwargs={"device": "cuda"})
# load chroma db
self.client_1 = chromadb.HttpClient(host='10.6.44.141', port=7000)
self.client_1 = chromadb.HttpClient(host='localhost', port=7000)
def __call__(self, *args, **kwargs):
return self.processing(*args, **kwargs)
@ -79,24 +87,24 @@ class ChromaUpsert(Blackbox):
chroma_collection_id = settings.get("chroma_collection_id")
if chroma_embedding_model is None or chroma_embedding_model.isspace() or chroma_embedding_model == "":
chroma_embedding_model = "/Workspace/Models/BAAI/bge-large-zh-v1.5"
chroma_embedding_model = model_name=str(self.model_path / "bge-large-zh-v1.5")
if chroma_host is None or chroma_host.isspace() or chroma_host == "":
chroma_host = "10.6.82.192"
chroma_host = "localhost"
if chroma_port is None or chroma_port.isspace() or chroma_port == "":
chroma_port = "8000"
chroma_port = "7000"
if chroma_collection_id is None or chroma_collection_id.isspace() or chroma_collection_id == "":
chroma_collection_id = "g2e"
# load client and embedding model from init
if re.search(r"10.6.82.192", chroma_host) and re.search(r"8000", chroma_port):
if re.search(r"localhost", chroma_host) and re.search(r"7000", chroma_port):
client = self.client_1
else:
client = chromadb.HttpClient(host=chroma_host, port=chroma_port)
print(f"chroma_embedding_model: {chroma_embedding_model}")
if re.search(r"/Workspace/Models/BAAI/bge-large-zh-v1.5", chroma_embedding_model):
if re.search((self.model_path / "bge-large-zh-v1.5"), chroma_embedding_model):
embedding_model = self.embedding_model_1
else:
embedding_model = SentenceTransformerEmbeddings(model_name=chroma_embedding_model, device = "cuda:0")