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@@ -326,22 +326,25 @@ def get_model_path(model: str, update_model: bool = False):
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local_files_only = not update_model
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local_files_only = not update_model
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+ local_model_path = os.path.join(cache_dir, model)
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+
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snapshot_kwargs = {
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snapshot_kwargs = {
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"cache_dir": cache_dir,
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"cache_dir": cache_dir,
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"local_files_only": local_files_only,
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"local_files_only": local_files_only,
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}
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}
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log.debug(f"model: {model}")
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log.debug(f"model: {model}")
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+ log.debug(f"local_model_path: {local_model_path}")
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log.debug(f"snapshot_kwargs: {snapshot_kwargs}")
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log.debug(f"snapshot_kwargs: {snapshot_kwargs}")
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# Inspiration from upstream sentence_transformers
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# Inspiration from upstream sentence_transformers
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if (
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if (
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- os.path.exists(model)
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+ os.path.exists(local_model_path)
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or ("\\" in model or model.count("/") > 1)
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or ("\\" in model or model.count("/") > 1)
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and local_files_only
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and local_files_only
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):
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):
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# If fully qualified path exists, return input, else set repo_id
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# If fully qualified path exists, return input, else set repo_id
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- return model
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+ return local_model_path
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elif "/" not in model:
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elif "/" not in model:
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# Set valid repo_id for model short-name
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# Set valid repo_id for model short-name
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model = "sentence-transformers" + "/" + model
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model = "sentence-transformers" + "/" + model
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@@ -355,7 +358,7 @@ def get_model_path(model: str, update_model: bool = False):
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return model_repo_path
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return model_repo_path
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except Exception as e:
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except Exception as e:
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log.exception(f"Cannot determine model snapshot path: {e}")
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log.exception(f"Cannot determine model snapshot path: {e}")
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- return model
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+ return local_model_path
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def generate_openai_embeddings(
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def generate_openai_embeddings(
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