Why is the embedding null when uploading

In fact this is unrelated to qdrant - I can totally reproduce this with chroma

I.e. embedding_model.get_text_embedding(documents[0].text) is returning a value, however, VectorStoreIndex.from_documents when queried via index.as_retriever().retrieve('foo')[0].embedding is null/empty

It's not that it's empty, it's just the llama-index is not populating the embedding field of the node when retirveing (the embedding is stored separately from the node)

There code be a PR to attach the embedding to the node in the vector db you are using

Interesting

| result = self.index.as_retriever(similarity_top_k=10).retrieve(query)
| ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
| File "/opt/conda/lib/python3.11/site-packages/llama_index/indices/base_retriever.py", line 22, in retrieve
| return self._retrieve(str_or_query_bundle)
| ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
| File "/opt/conda/lib/python3.11/site-packages/llama_index/indices/vector_store/retrievers/retriever.py", line 81, in _retrieve
| if query_bundle.embedding is None and len(query_bundle.embedding_strs) > 0:

as I am running into 'Message' object has no attribute 'embedding'

but only in the docker container

my local installation works fine

locally I have a 0.8.41 in docker where it fails 0.8.46

However, when using the newer version locally it also works.

Do you have any idea why the docker version of the retriever is failing in this strange way?

hmm that's quite strange. maybe check if the query you pass in in the docker container is indeed a string?

A simple python script inside docker works just fine. However, a chainlit based fails with this error

Wow - indeed this was the right pointer. I have no idea why inside docker the message is not a string (it ineed is a string in the local setup) but it is a chainlit message which needs to be unwrapped. @disiok thanks!

turns out chainlit was only pinned to the Minor and not to Patch - and they recently bumped from 0.3 0.300 ...

glad it helped!