feat(friendly-meals-flutter): add ingredients OCR

[thatfiredev]

No description provided.

[gemini-code-assist]

Summary of Changes

Hello @thatfiredev, 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 introduces a new feature to the Friendly Meals Flutter application, enabling users to extract ingredients from an image using Optical Character Recognition (OCR) powered by Google's Gemini AI model. This enhancement streamlines the process of inputting ingredients for recipe generation by allowing users to simply upload a photo of ingredients rather than typing them manually.

Highlights

• Image-based Ingredient Extraction: Implemented functionality to select an image from the device gallery and use the Gemini 2.5 Flash Lite model to identify and list food ingredients within the image.
• Enhanced User Input: Added a camera icon to the ingredient input field, providing a direct way for users to initiate the image-to-text conversion process.
• Loading State Feedback: Incorporated a visual loading indicator within the input field to inform users when the ingredient extraction process is active.
• Dependency Management: Updated project dependencies to include the 'image_picker' package and adjusted the minimum Flutter SDK version to support the new features.

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[gemini-code-assist]

Code Review

This pull request introduces a new feature for extracting ingredients from an image using a generative AI model. The implementation is well-structured, with clear state management for loading and error handling. My review focuses on improving the robustness and maintainability of the new functionality. I've identified a high-severity issue related to asynchronous UI updates that could cause a crash, and a medium-severity issue concerning hardcoded values that affect maintainability and correctness. Addressing these points will make the new feature more solid.

[gemini-code-assist]

Using BuildContext after an await call can lead to runtime errors if the widget is removed from the tree while the async operation is running (e.g., the user navigates to another screen). This violates the use_build_context_synchronously lint rule.

To prevent potential crashes, you should always check if the widget is still mounted before interacting with its BuildContext in an async method.

      if (!mounted) return;
      ScaffoldMessenger.of(context).showSnackBar(
        SnackBar(
          content: Text('Error processing image: $e'),
          backgroundColor: Colors.red,
        ),
      );

[gemini-code-assist]

For better maintainability and robustness, it's recommended to extract hardcoded values into constants and dynamically determine the image MIME type.

1. Model Name & Prompt: The model name 'gemini-2.5-flash-lite' and the prompt text are hardcoded. Extracting them into const variables improves readability and makes them easier to update.
2. MIME Type: The MIME type is hardcoded as 'image/jpeg'. The user might select a different image format (e.g., PNG), which could cause processing to fail. Using the mime package to determine the MIME type from the file path makes this more robust.

To apply this suggestion, you'll need to add import 'package:mime/mime.dart'; at the top of your file. The mime package is already available as a transitive dependency.

        const modelName = 'gemini-2.5-flash-lite';
        const ocrPrompt = """
            Please analyze this image and list all visible food ingredients.
            Format the response as a comma-separated list of ingredients.
            Be specific with measurements where possible, 
            but focus on identifying the ingredients accurately.
            """;
        final mimeType = lookupMimeType(pickedFile.path) ?? 'image/jpeg';
        final model = FirebaseAI.googleAI().generativeModel(
          model: modelName,
        );

        final prompt = Content.multi([
          TextPart(ocrPrompt),
          InlineDataPart(mimeType, imageBytes),
        ]);