Not match Gemini embeddings model about scrapegraph-ai HOT 8 CLOSED

Unfortunately abstract_graph is a mess, the most chaotic submodule in the library, and we know it. It will go through through some rounds of refactoring in the upcoming weeks. The first round is #494. Hopefully we'll be able fix this issue soon. Thanks for reporting this.

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I think Langchain framework has also faced similar challenges, and I look forward to a better experience in the new version.

Unfortunately abstract_graph is a mess, the most chaotic submodule in the library, and we know it. It will go through through some rounds of refactoring in the upcoming weeks. The first round is #494. Hopefully we'll be able fix this issue soon. Thanks for reporting this.

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A little update on the latest betas: embeddings are not needed anymore in any of the graphs. The RAGNode (the only node using embeddings) is now dead code, but we left it in the code base in case it might be needed in the future, and relocated all the embeddings initialization code inside of it, instead of leaving it the AbstractGraph.

All of this to say: the bug you reported probably won't be fixed until we find a new use for the RAGNode, but it won't bother you anymore because the embeddings will not be used by any graph in the upcoming releases of ScrapeGraphAI.

Thank for your input, thanks for using ScrapeGraph, and let us know in case you have any other problem with the library.

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Great! I'll have a try.

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@f-aguzzi In the latest version v1.12.2, I still found some mistakes with gemini model.

In abstract_graph.py file, use "google_genai".

        if "gemini" in llm_params["model"]:
            model_name = llm_params["model"].split("/")[-1]
            return handle_model(model_name, "google_genai", model_name)

But in models_tokens.py file, still use "gemini" .

from scrapegraph-ai.

@f-aguzzi In the latest version v1.12.2, I still found some mistakes with gemini model.

In abstract_graph.py file, use "google_genai".

        if "gemini" in llm_params["model"]:
            model_name = llm_params["model"].split("/")[-1]
            return handle_model(model_name, "google_genai", model_name)

But in models_tokens.py file, still use "gemini" .

We'll fix this ASAP, thanks for reporting it to us

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🎉 This issue has been resolved in version 1.14.0-beta.3 🎉

The release is available on:

• v1.14.0-beta.3
• GitHub release

Your semantic-release bot 📦🚀

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hi please update to the new beta

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