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[Hotfix] minor fix on embedding related bugs #463

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Oct 21, 2024
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5 changes: 2 additions & 3 deletions src/agentscope/manager/_file.py
Original file line number Diff line number Diff line change
Expand Up @@ -34,13 +34,12 @@ def _get_text_embedding_record_hash(
if isinstance(embedding_model, dict):
# Format the dict to avoid duplicate keys
embedding_model = json.dumps(embedding_model, sort_keys=True)
elif isinstance(embedding_model, str):
embedding_model_hash = _hash_string(embedding_model, hash_method)
else:
elif not isinstance(embedding_model, str):
raise RuntimeError(
f"The embedding model must be a string or a dict, got "
f"{type(embedding_model)}.",
)
embedding_model_hash = _hash_string(embedding_model, hash_method)

# Calculate the embedding id by hashing the hash codes of the
# original data and the embedding model
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3 changes: 2 additions & 1 deletion src/agentscope/rag/llama_index_knowledge.py
Original file line number Diff line number Diff line change
Expand Up @@ -203,8 +203,9 @@ def __init__(
)

if persist_root is None:
persist_root = FileManager.get_instance().run_dir or "./"
persist_root = FileManager.get_instance().cache_dir or "./"
self.persist_dir = os.path.join(persist_root, knowledge_id)
logger.info(f"** persist_dir: {self.persist_dir}")
self.emb_model = emb_model
self.overwrite_index = overwrite_index
self.showprogress = showprogress
Expand Down