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Timothy J. Baek 2024-04-09 23:54:20 -07:00
parent 506a061387
commit 48aad65514
1 changed files with 4 additions and 3 deletions
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7
backend/config.py
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@ -397,9 +397,10 @@ CHROMA_DATA_PATH = f"{DATA_DIR}/vector_db"
# this uses the model defined in the Dockerfile ENV variable. If you dont use docker or docker based deployments such as k8s, the default embedding model will be used (all-MiniLM-L6-v2) # this uses the model defined in the Dockerfile ENV variable. If you dont use docker or docker based deployments such as k8s, the default embedding model will be used (all-MiniLM-L6-v2)
RAG_EMBEDDING_MODEL = os.environ.get("RAG_EMBEDDING_MODEL", "all-MiniLM-L6-v2") RAG_EMBEDDING_MODEL = os.environ.get("RAG_EMBEDDING_MODEL", "all-MiniLM-L6-v2")
log.info(f"Embedding model set: {RAG_EMBEDDING_MODEL}"), log.info(f"Embedding model set: {RAG_EMBEDDING_MODEL}"),
RAG_EMBEDDING_MODEL_AUTO_UPDATE = False
if os.environ.get("RAG_EMBEDDING_MODEL_AUTO_UPDATE", "").lower() == "true": RAG_EMBEDDING_MODEL_AUTO_UPDATE = (
RAG_EMBEDDING_MODEL_AUTO_UPDATE = True os.environ.get("RAG_EMBEDDING_MODEL_AUTO_UPDATE", "").lower() == "true"
)
# device type ebbeding models - "cpu" (default), "cuda" (nvidia gpu required) or "mps" (apple silicon) - choosing this right can lead to better performance # device type ebbeding models - "cpu" (default), "cuda" (nvidia gpu required) or "mps" (apple silicon) - choosing this right can lead to better performance