Epics for Pecha AI Studio: Buddhist AI Evaluation Platform

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Epics for Pecha AI Studio: Buddhist AI Evaluation Platform

Here are the high-level Epics derived from the Product Requirements Document. Each Epic represents a major deliverable for the project.

Epic 1: Foundational Platform & Core Infrastructure

Summary: To build the essential, non-user-facing backend infrastructure that will serve as the foundation for the entire evaluation platform. This includes setting up user authentication, a secure database, data storage, and a reliable deployment pipeline. This Epic must be completed before any user-facing features can be developed.

Key Features / Stories:

  • Set up a secure user registration and login system (email/password, OAuth).

  • Design and implement the database schema for users, challenges, submissions, and results.

  • Configure secure cloud storage for hosting benchmark datasets.

  • Establish a CI/CD pipeline for automated testing and deployment to a staging environment.

  • Implement basic user profile management.

Epic 2: Core Evaluation Engine & Workflow

Summary: To create the robust, scalable, and modular end-to-end workflow for all challenges. This engine will handle the complete user journey from downloading test data to submitting results and receiving a score, and it will be designed to accommodate any type of AI model or evaluation metric from the outset.

Key Features / Stories:

  • Develop the user interface for viewing a challenge and downloading the associated test dataset.

  • Build a secure and scalable file upload mechanism for users to submit model inference results.

  • Implement an asynchronous background processing system to handle submissions for various challenge types.

  • Develop a system for executing automated evaluation scripts against ground truth data.

  • Store calculated scores in the database, linking them to the user, submission, and specific challenge.

  • Create the basic API endpoints to serve evaluation results to the front-end.

Epic 3: Public-Facing User Interface & Experience

Summary: To design and build the complete, intuitive, and polished user interface based on the provided mockups. This Epic focuses on making the platform easy to navigate and visually appealing, ensuring users can easily discover challenges, understand results, and track their progress across all model types.

Key Features / Stories:

  • Build the main “Challenges” discovery page with a card-based layout.

  • Develop the detailed, dynamic leaderboard page with columns for Rank, Model, Description, challenge-specific Metrics (e.g., CER, WER, BLEU), and Submission Date.

  • Implement search and filtering functionality on the leaderboard.

  • Create static pages for documentation, providing clear instructions on how to participate, format submissions, and understand the datasets.

  • Ensure the entire front-end is responsive and works well on different screen sizes.

Epic 4: Challenge Expansion & Management System

Summary: To build the administrative tools required to manage the platform and expand its content. This involves creating a backend interface that allows the team to add new evaluation challenges, update datasets, and configure metrics without requiring new code deployments.

Key Features / Stories:

  • Create an admin dashboard for creating, editing, and managing evaluation challenges (e.g., setting titles, descriptions, evaluation metrics).

  • Develop a system for uploading and versioning benchmark datasets associated with each challenge.

  • Ensure the evaluation engine is fully modular, allowing new evaluation scripts to be easily plugged in via the admin system.

  • Extend the front-end to dynamically render pages and leaderboards based on the configurations set in the admin dashboard.

Epic 5: Community & Collaboration Features

Summary: To enhance the platform with features that encourage community engagement, collaboration, and transparency. This will help solidify the platform as the central hub for the Buddhist AI community, moving it beyond a simple evaluation tool.

Key Features / Stories:

  • Allow users to add a public description to their submissions, with support for linking to a paper, code repository, or model card.

  • Develop a user profile page that showcases a user’s submission history and rankings across different challenges.

  • Implement a system for versioning leaderboards to track progress over time as datasets are updated.

  • Create a mechanism for users to report issues or provide feedback directly on the