fix: address comment in pr #1687

backend/apps/rag/utils.py

@@ -1,3 +1,4 @@
+import os
 import logging
 import requests
 
@@ -8,6 +9,8 @@ from apps.ollama.main import (
     GenerateEmbeddingsForm,
 )
 
+from huggingface_hub import snapshot_download
+
 from langchain_core.documents import Document
 from langchain_community.retrievers import BM25Retriever
 from langchain.retrievers import (
@@ -282,8 +285,6 @@ def rag_messages(
 
         extracted_collections.extend(collection)
 
-    log.debug(f"relevant_contexts: {relevant_contexts}")
-
     context_string = ""
     for context in relevant_contexts:
         items = context["documents"][0]
@@ -319,6 +320,44 @@ def rag_messages(
     return messages
 
 
+def get_model_path(model: str, update_model: bool = False):
+    # Construct huggingface_hub kwargs with local_files_only to return the snapshot path
+    cache_dir = os.getenv("SENTENCE_TRANSFORMERS_HOME")
+
+    local_files_only = not update_model
+
+    snapshot_kwargs = {
+        "cache_dir": cache_dir,
+        "local_files_only": local_files_only,
+    }
+
+    log.debug(f"embedding_model: {model}")
+    log.debug(f"snapshot_kwargs: {snapshot_kwargs}")
+
+    # Inspiration from upstream sentence_transformers
+    if (
+        os.path.exists(model)
+        or ("\\" in model or model.count("/") > 1)
+        and local_files_only
+    ):
+        # If fully qualified path exists, return input, else set repo_id
+        return model
+    elif "/" not in model:
+        # Set valid repo_id for model short-name
+        model = "sentence-transformers" + "/" + model
+
+    snapshot_kwargs["repo_id"] = model
+
+    # Attempt to query the huggingface_hub library to determine the local path and/or to update
+    try:
+        model_repo_path = snapshot_download(**snapshot_kwargs)
+        log.debug(f"model_repo_path: {model_repo_path}")
+        return model_repo_path
+    except Exception as e:
+        log.exception(f"Cannot determine model snapshot path: {e}")
+        return model
+
+
 def generate_openai_embeddings(
     model: str, text: str, key: str, url: str = "https://api.openai.com/v1"
 ):