fix(text_embedding): pass input_type to distinguish between document and query

[utsumi-fj]

Fixes #241

Compatibility Check

• I have checked whether this change affects the backward compatibility of the plugin declared in README.md
• I have checked whether this change affects the forward compatibility of the plugin declared in README.md
• If this change introduces a breaking change, I have discussed it with the project maintainer and specified the release version in the README.md
• I have described the compatibility impact and the corresponding version number in the PR description
• I have checked whether the plugin version is updated in the README.md

Compatibility impact

Since this is a bug fix, there is no compatibility impact.

Available Checks

• Code has passed local tests
• Relevant documentation has been updated (if necessary)

[gemini-code-assist]

Summary of Changes

Hello @utsumi-fj, I'm Gemini Code Assist¹! I'm currently reviewing this pull request and will post my feedback shortly. In the meantime, here's a summary to help you and other reviewers quickly get up to speed!

This pull request addresses a bug by enhancing the text embedding functionality to explicitly distinguish between document and query inputs. It achieves this by introducing a new input_type parameter within the text embedding request model and ensuring this parameter is correctly propagated to the model invocation logic. This change allows for more precise handling and processing of different types of text embedding requests.

Highlights

• New Input Type for Text Embedding: Introduced EmbeddingInputType to differentiate between document and query inputs for text embedding models.
• Model Request Update: Added an optional input_type field, defaulting to DOCUMENT, to the ModelInvokeTextEmbeddingRequest class.
• Embedding Invocation Logic: Modified the invoke_text_embedding function to pass the newly introduced input_type parameter to the underlying text embedding model provider.

Using Gemini Code Assist

The full guide for Gemini Code Assist can be found on our documentation page, here are some quick tips.

Invoking Gemini

You can request assistance from Gemini at any point by creating a comment using either /gemini <command> or @gemini-code-assist <command>. Below is a summary of the supported commands on the current page.

Feature	Command	Description
Code Review	/gemini review	Performs a code review for the current pull request in its current state.
Pull Request Summary	/gemini summary	Provides a summary of the current pull request in its current state.
Comment	@gemini-code-assist	Responds in comments when explicitly tagged, both in pull request comments and review comments.
Help	/gemini help	Displays a list of available commands.

Customization

To customize Gemini Code Assist for GitHub experience, repository maintainers can create a configuration file and/or provide a custom code review style guide (such as PEP-8 for Python) by creating and adding files to a .gemini/ folder in the base of the repository. Detailed instructions can be found here.

Limitations & Feedback

Gemini Code Assist may make mistakes. Please leave feedback on any instances where its feedback is incorrect or counter productive. You can react with 👍 and 👎 on @gemini-code-assist comments. If you're interested in giving your feedback about your experience with Gemini Code Assist for Github and other Google products, sign up here.

You can also get AI-powered code generation, chat, as well as code reviews directly in the IDE at no cost with the Gemini Code Assist IDE Extension.

Footnotes

1. Review the Privacy Notices, Generative AI Prohibited Use Policy, Terms of Service, and learn how to configure Gemini Code Assist in GitHub here. Gemini can make mistakes, so double check it and use code with caution. ↩

[gemini-code-assist]

Code Review

This pull request correctly adds an input_type field to ModelInvokeTextEmbeddingRequest to distinguish between document and query embeddings, and passes this value to the model invocation layer. This is a good enhancement for embedding models. My review includes one high-severity suggestion to improve type safety by disallowing None for input_type in the request model, which will prevent potential runtime errors and align with the model interface's expectations.

[utsumi-fj]

@Mairuis Hi, thank you for taking look at this PR.
I noticed that this PR was closed today without a comment, while the related issue #241 remains open.
This PR is a bug fix, and another PR langgenius/dify-official-plugins#2079 that depends on this has already been merged, so I wanted to kindly ask whether the closure was intentional.

If there's anything I should revise or any concerns about the approach, I would be very happy to update this PR.
Please let me know how you would like to proceed.
Thank you!

[utsumi-fj]

Hi @Yeuoly,
Sorry to bother you.
This PR was closed by @Mairuis recently, and I might have misunderstood the intention behind the closure.
Since I haven’t been able to get a response yet, I just wanted to check if you could take a look when you have time and let me know if it might be possible to review or reopen it.
Thanks a lot!

[Mairuis]

Please accept my sincere apologies for the incorrect closure of your pull request due to a technical issue in the trigger test. This was an operational mistake on our side, and I deeply regret any inconvenience this may have caused. Your PR has been reopened accordingly. Thank you for your understanding. @utsumi-fj

[utsumi-fj]

@Mairuis Thank you so much!

[Mairuis]

LGTM