Social Film Platform

A modern film archiving and social platform with AI-powered features

Features • Tech Stack • Installation • Usage • AI Features

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About The Project

Social Film Platform is a web application built with ASP.NET Core MVC for film enthusiasts to catalog, review, and share movies. Features vintage cinema aesthetic with modern functionality and AI-powered tag suggestions.

Key Highlights

• Movie Archive - Database with genres, actors, trailers, and images
• Personal Diaries - Curated film collections with tags and categories
• Review System - Write, edit, and vote on reviews
• AI Integration - Automatic suggestions using Google Gemini
• Multi-Role System - Admin, Editor, and User roles
• Vintage UI/UX - Classic Hollywood-inspired design

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Features

Core Functionality

Movies

• CRUD operations
• Search by title, director, genre
• Sort by popularity or date
• Upload posters, embed trailers
• Associate with actors

Actors

• Profile pages with biography
• Filmography listings
• Photo uploads

Diaries (Movie Lists)

• Public/private collections
• Tag and category system
• Vote on diaries
• AI-powered suggestions

Reviews

• Rich-text reviews (up to 2000 chars)
• Like/Dislike voting
• Edit/delete capabilities
• Moderation tools

Organization

• Genres: Action, Sci-Fi, Drama, Comedy, Thriller, Romance, Animation, Horror
• User-defined tags and categories

User Roles

Role	Permissions
Admin	Full access: manage all content, users, and settings
Editor	Create/edit/delete movies, actors, genres; moderate reviews
User	Create diaries, write reviews, vote on content

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AI Features

The platform integrates Google Gemini Flash AI for intelligent content suggestions.

How It Works

1. Diary Analysis: When editing a diary, click "Suggest with AI"
2. Content Processing: The AI analyzes:
   • Movie titles in the diary
   • Diary name and description
   • Common themes and genres
3. Smart Suggestions: Receives 3 relevant tags + 3 categories
4. One-Click Apply: Add suggestions directly to your diary

Example Output

For a diary containing Fight Club, Pulp Fiction, and Mulholland Drive:

{
  "tags": ["Psychological Thriller", "Cult Classics", "Mind-Bending"],
  "categories": ["Thriller", "Drama", "Neo-Noir"]
}

AI Architecture

User Request → DiariesController.SuggestTags()
                     ↓
        Extract movie titles from diary
                     ↓
        Build context-aware prompt
                     ↓
        Google Gemini API call
                     ↓
        Parse JSON response
                     ↓
        Return tags + categories

API Configuration: Set Gemini:ApiKey in appsettings.json or User Secrets

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Tech Stack

Backend

• Framework: ASP.NET Core 9.0 MVC
• Language: C# 13.0
• ORM: Entity Framework Core 9.0
• Database: MySQL 8.0 (via Pomelo.EntityFrameworkCore.MySql)
• Authentication: ASP.NET Core Identity with role-based authorization

Frontend

• UI Framework: Bootstrap 5
• Rich Text Editor: Quill.js
• Icons: Bootstrap Icons
• Fonts: Google Fonts (Cinzel, Playfair Display, Lato)
• JavaScript: Vanilla JS with Fetch API

AI & Security

• AI Service: Google Gemini Flash API
• XSS Protection: HtmlSanitizer (Ganss.Xss)
• Image Uploads: Custom file handling with GUID naming

Architecture

• Pattern: MVC (Model-View-Controller)
• Dependency Injection: Built-in ASP.NET Core DI
• Razor Pages: For Identity UI
• View Components: Partial views for reusable UI

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Installation

Prerequisites

• .NET 9.0 SDK
• MySQL 8.0+
• Visual Studio 2022 or VS Code
• Google Gemini API Key (free tier available)

Step 1: Clone the Repository

git clone https://github.com/dariabulacu/SocialFilmPlatform.git
cd SocialFilmPlatform

Step 2: Configure Database

1. Create a MySQL database:

CREATE DATABASE socialfilmplatform CHARACTER SET utf8mb4 COLLATE utf8mb4_unicode_ci;

2. Update appsettings.json:

{
  "ConnectionStrings": {
    "DefaultConnection": "Server=localhost;Database=socialfilmplatform;User=root;Password=YOUR_PASSWORD;"
  }
}

Step 3: Configure AI (Optional)

Add your Gemini API key:

{
  "Gemini": {
    "ApiKey": "YOUR_GEMINI_API_KEY"
  }
}

Get API Key: Google AI Studio

Step 4: Run Migrations

cd SocialFilmPlatform
dotnet ef database update

This will:

• Create all database tables
• Seed initial data (users, movies, actors, genres)

Step 5: Run the Application

dotnet run

Navigate to: https://localhost:5001

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Default User Accounts

The database is seeded with test accounts:

Role	Email	Password
Admin	admin@test.com	Admin1!
Editor	editor@test.com	Editor1!
User	user@test.com	User1!

Warning: Change these passwords in production!

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Usage Guide

Creating a Movie (Editor/Admin)

1. Navigate to Movies → Add Movie
2. Fill required fields (title, director, description, date, score, genre)
3. Optional: Upload poster, add trailer URL
4. Click Save Movie

Creating a Diary (All Users)

1. Go to Diaries → Create New
2. Enter name, description, public/private toggle
3. Add movies from movie detail pages
4. Use AI Suggest for auto-generated tags

Writing a Review

1. Go to movie detail page
2. Use rich text editor in Critiques section
3. Click Publish
4. Vote on other reviews

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Project Structure

SocialFilmPlatform/
├── Controllers/           # MVC Controllers
│   ├── MoviesController.cs
│   ├── DiariesController.cs
│   ├── ActorsController.cs
│   ├── ReviewsController.cs
│   └── ...
├── Models/               # Data Models
│   ├── Movie.cs
│   ├── Diary.cs
│   ├── Review.cs
│   ├── ApplicationUser.cs
│   └── SeedData.cs
├── Views/                # Razor Views
│   ├── Movies/
│   ├── Diaries/
│   ├── Actors/
│   └── Shared/
├── Services/             # Business Logic
│   ├── IAiService.cs
│   └── GeminiAiService.cs
├── Data/                 # EF Core Context
│   ├── ApplicationDbContext.cs
│   └── Migrations/
├── wwwroot/              # Static Files
│   ├── css/
│   ├── js/
│   └── images/
└── Program.cs            # App Entry Point

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Database Schema

Key Relationships

• Many-to-Many: Movies ↔ Actors (via ActorMovie)
• Many-to-Many: Diaries ↔ Movies (via MovieDiary)
• Many-to-Many: Diaries ↔ Tags/Categories
• One-to-Many: Movie → Reviews, User → Diaries

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Security Features

XSS Protection

var sanitizer = new HtmlSanitizer();
movie.Description = sanitizer.Sanitize(movie.Description);

Role-Based Authorization

[Authorize(Roles = "Editor,Admin")]
public IActionResult New() { ... }

CSRF Protection

• Built-in anti-forgery tokens on all forms
• [ValidateAntiForgeryToken] on POST actions

SQL Injection Prevention

• Entity Framework parameterized queries
• No raw SQL execution

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API Endpoints

Movie API (Internal)

• GET /Movies/Index - List all movies (paginated)
• GET /Movies/Show/{id} - Movie details
• POST /Movies/New - Create movie
• POST /Movies/Edit/{id} - Update movie
• POST /Movies/Delete/{id} - Delete movie

Diary API (Internal)

• GET /Diaries/Index - Public diaries
• GET /Diaries/MyDiaries - User's diaries
• POST /Diaries/SuggestTags - AI suggestions (JSON response)

Review API (Internal)

• POST /Reviews/New - Submit review
• POST /Reviews/Vote - Like/dislike review (JSON response)

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Testing

Database Seeding

The application automatically seeds test data:

• 3 user roles
• 6 test users
• 8 genres
• 6 actors
• 7 movies
• 5 sample diaries
• 3 sample reviews

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