rguilmont
commented
1 week ago Looks like it's due to dependency installation in Milvus.
New version of Flag Embedding ( https://pypi.org/project/FlagEmbedding/1.3.2/ ) has been released some days ago and basically broke everything. Maybe we should pin-point to the working 1.2.X version ( i personnaly prefer installing it via Poetry to avoid this live dependency installation )
wxywb
mhamdik
When using the BGEM3EmbeddingFunction from the milvus_model package, calling the encode_queries or encode_documents method leads to a TypeError. The error occurs because the _encode method in BGEM3EmbeddingFunction uses sentences as the argument name when calling self.model.encode. However, the underlying model, BGEM3FlagModel, expects an argument named queries.
Traceback (most recent call last): File "/path/to/my/code.py", line 51, in
query_embeddings = bge_m3.encode_queries(queries)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/path/to/api-venv/lib/python3.12/site-packages/milvus_model/hybrid/bge_m3.py", line 102, in encode_queries
return self._encode(queries)
^^^^^^^^^^^^^^^^^^^^^
File "/path/to/api-venv/lib/python3.12/site-packages/milvus_model/hybrid/bge_m3.py", line 83, in _encode
output = self.model.encode(sentences=texts, **self._encode_config)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
TypeError: M3Embedder.encode() missing 1 required positional argument: 'queries'
Using MacOS, Python 3.12, and the latest version of the milvus_model package from PyPI. This issue may impact other methods within the BGEM3EmbeddingFunction class that depend on self.model.encode.
from pymilvus.model.hybrid import BGEM3EmbeddingFunction
bge_m3 = BGEM3EmbeddingFunction( model_name='BAAI/bge-m3', devices="cpu", use_fp16=False )
queries = [ "What are the effects of climate change?", "¿Cuáles son los efectos del cambio climático?", "气候变化有什么影响？" ]
Encoding the queries
query_embeddings = bge_m3.encode_queries(queries=queries) print("Query Embeddings:", query_embeddings)
Merci