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Fix RAG with Generative APIs and Langchain tutorial #4047

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@fpagny fpagny commented Nov 27, 2024

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@fpagny fpagny self-assigned this Nov 27, 2024
fpagny and others added 15 commits November 28, 2024 18:06
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@@ -34,28 +34,35 @@ In this tutorial, you will learn how to implement RAG using LangChain, a leading

### Install required packages

Run the following command to install the required packages:
1. Run the following command to install the required Python packages:
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This section is now the only one in the whole tutorial having numbered steps 1. and 2.

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@tgenaitay @fpagny we can remove the steps numbers, as we have less than 3 in the tutorial.
Sorry, I ended up forgetting to remove them yesterday after I finished the review. 🤓

…untu

Adding dependencies requirements for MacOS and Debian/Ubuntu, and fixing python packages version.
```

## Embeddings and vector store setup
## Setup embeddings and vector store
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Suggested change
## Setup embeddings and vector store
## Set up embeddings and vector store


By integrating Scaleway Object Storage, Managed Database for PostgreSQL with pgvector, and LangChain’s embedding tools, you have the foundation to build a powerful RAG system that scales with your data while offering robust information retrieval capabilities. This approach equips you with the tools necessary to handle complex queries and deliver accurate, relevant results efficiently.
**Error**: `ERROR:root:An error occurred: bge-multilingual-gemma2 is not a local folder and is not a valid model identifier listed on 'https://huggingface.co/models'
If this is a private repository, make sure to pass a token having permission to this repo either by logging in with `huggingface-cli login` or by passing `token=<your_token>``
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Suggested change
If this is a private repository, make sure to pass a token having permission to this repo either by logging in with `huggingface-cli login` or by passing `token=<your_token>``
If this is a private repository, make sure to pass a token having permission to this repo either by logging in with `huggingface-cli login` or by passing ```token=<your_token>```

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4 participants