Cacassiano/review-analizer

AI Summary: This issue requests the development of a frontend for an application and its subsequent publication or deployment. The 'help wanted' label indicates it's an open task seeking community contributions.

AI Summary: This issue proposes implementing asynchronous processing for the system's analyses. The goal is to ensure that analysis tasks run in the background without blocking the main application flow, likely to improve responsiveness and efficiency.

AI Summary: This issue proposes a general refactoring of the codebase. The primary goals are to ensure adherence to SOLID principles and to implement a suitable architectural pattern, aiming for improved code quality and maintainability.

AI Summary: The issue proposes to refactor the system so that the unique identifier for 'analyses' (or 'analizes') is the URL associated with them. This means that instead of a separate ID, the URL itself will serve as the primary key for each analysis, ensuring uniqueness based on the URL.

AI Summary: This issue requests a new feature that allows users to trigger a re-run or update of an existing analysis. The goal is to provide a mechanism for users to initiate the analysis process again for a specific item or dataset.

AI Summary: The issue aims to enhance the platform's ability to collect more reviews for its services. It suggests improving the quantity of reviews retrieved, potentially by implementing automated scrolling mechanisms (e.g., simulating a space bar press) to reveal more content.

AI Summary: This issue, marked as a 'good first issue', calls for implementing or improving basic exception handling within the project. The task likely involves identifying a specific area where unhandled exceptions could occur and adding simple `try-except` blocks or similar error management to prevent crashes or provide more informative error messages.