From cc9cb202cdf507ad0f6bfe6e934a8175e8561017 Mon Sep 17 00:00:00 2001 From: Weves Date: Tue, 21 May 2024 11:06:24 -0700 Subject: [PATCH] Add option to specify custom port for indexing model server --- backend/danswer/indexing/embedder.py | 4 ++-- backend/shared_configs/configs.py | 3 +++ 2 files changed, 5 insertions(+), 2 deletions(-) diff --git a/backend/danswer/indexing/embedder.py b/backend/danswer/indexing/embedder.py index 0aaeb3552..0b542067a 100644 --- a/backend/danswer/indexing/embedder.py +++ b/backend/danswer/indexing/embedder.py @@ -19,7 +19,7 @@ from danswer.search.search_nlp_models import EmbeddingModel from danswer.utils.batching import batch_list from danswer.utils.logger import setup_logger from shared_configs.configs import INDEXING_MODEL_SERVER_HOST -from shared_configs.configs import MODEL_SERVER_PORT +from shared_configs.configs import INDEXING_MODEL_SERVER_PORT logger = setup_logger() @@ -61,7 +61,7 @@ class DefaultIndexingEmbedder(IndexingEmbedder): normalize=normalize, # The below are globally set, this flow always uses the indexing one server_host=INDEXING_MODEL_SERVER_HOST, - server_port=MODEL_SERVER_PORT, + server_port=INDEXING_MODEL_SERVER_PORT, ) def embed_chunks( diff --git a/backend/shared_configs/configs.py b/backend/shared_configs/configs.py index 41b46723e..aeeb9cf2a 100644 --- a/backend/shared_configs/configs.py +++ b/backend/shared_configs/configs.py @@ -9,6 +9,9 @@ MODEL_SERVER_PORT = int(os.environ.get("MODEL_SERVER_PORT") or "9000") INDEXING_MODEL_SERVER_HOST = ( os.environ.get("INDEXING_MODEL_SERVER_HOST") or MODEL_SERVER_HOST ) +INDEXING_MODEL_SERVER_PORT = int( + os.environ.get("INDEXING_MODEL_SERVER_PORT") or MODEL_SERVER_PORT +) # Danswer custom Deep Learning Models INTENT_MODEL_VERSION = "danswer/intent-model"