llmware-ai / llmware-ai/llmware

Rag 5 Semantic Query (Fast Start throws an error)

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#989 3 comments 1 reaction 0 assignees View on GitHub
Dominant language
Python
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Description

Hello,
I am new to all of this and I was trying to follow and run the RAG notebooks on google colab. The 5th notebook in the RAG series (Fast Start) when run on colab throws the following error. In fact, you can find the error in the original notebook itself which was uploaded. It seems this notebook never ran well.

update: Step 4 - Generating Embeddings in chomadb db - with Model- industry-bert-contracts
---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
[](https://localhost:8080/#) in ()
1 print("\nupdate: Step 4 - Generating Embeddings in {} db - with Model- {}".format(vector_db, embedding_model))
----> 2 library.install_new_embedding(embedding_model=embedding_model, vector_db=vector_db)

TypeError: Library.install_new_embedding() got an unexpected keyword argument 'embedding_model'

I hope you see that.

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Research direction

Start with the fifth RAG notebook, “Fast Start,” and reproduce Step 4 in Google Colab using the shown install_new_embedding call and industry-bert-contracts model. Compare that call with the Library API used by the notebook, then rerun the notebook and confirm Step 4 completes without the TypeError.

Written by the indexing model from the issue text.

Assessment

Tech stack
jupyter-notebook, python
Domain
ai, machine-learning
Issue type
Bug
Difficulty
2/5
Estimated time
1-3 hours
Activity status
Stale
Clarity
Mostly clear
Newbie friendliness
42/100

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