feat: add EmbeddingModelComponent for generating embeddings

[rodrigosnader]

• Introduced a new EmbeddingModelComponent to generate embeddings using specified providers, starting with OpenAI.
• Updated the init.py file to include the new component in the exports.
• The component includes various input fields for configuration, such as provider selection, model name, API key, and additional parameters.

[Copilot]

Pull Request Overview

This PR adds a new EmbeddingModelComponent for generating embeddings using OpenAI and updates the component exports to include the new model component.

• Introduces the EmbeddingModelComponent with multiple configuration inputs for provider, model, API key, and other parameters.
• Updates the init.py file to export the new component.

Reviewed Changes

Copilot reviewed 2 out of 2 changed files in this pull request and generated no comments.

File	Description
src/backend/base/langflow/components/embeddings/embedding_model.py	Adds the new component definition and implementation for generating embeddings.
src/backend/base/langflow/components/embeddings/init.py	Updates the exports to include the new EmbeddingModelComponent.

Comments suppressed due to low confidence (2)

src/backend/base/langflow/components/embeddings/embedding_model.py:24

• [nitpick] The component class is named 'EmbeddingModelComponent' but its 'name' attribute is set to 'EmbeddingModel'; consider aligning these names for consistency.

name = "EmbeddingModel"

src/backend/base/langflow/components/embeddings/embedding_model.py:103

• [nitpick] Consider providing a more descriptive error message that outlines the supported provider(s) when an unknown provider is encountered.

msg = f"Unknown provider: {provider}"