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- # Multi-Agent E-Commerce Recommendation System
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-
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- A sophisticated recommendation system that uses multiple AI agents to provide personalized product recommendations to users.
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-
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- ## Features
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-
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- - Multiple recommendation algorithms (Collaborative Filtering, Content-Based, Sequential Pattern Mining, Hybrid)
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- - Real-time user feedback processing
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- - Personalized product recommendations
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- - Admin dashboard for system monitoring
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- - Modern React.js frontend
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- - FastAPI backend with async support
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-
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- ## Project Structure
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-
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- ```
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- .
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- β”œβ”€β”€ frontend/ # React.js frontend
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- β”œβ”€β”€ src/
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- β”‚ β”œβ”€β”€ api/ # API endpoints and routes
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- β”‚ β”œβ”€β”€ algorithms/ # Recommendation algorithms
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- β”‚ β”œβ”€β”€ agents/ # AI agents implementation
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- β”‚ β”œβ”€β”€ database/ # Database models and connection
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- β”‚ └── utils/ # Utility functions
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- β”œβ”€β”€ main.py # Application entry point
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- β”œβ”€β”€ requirements.txt # Python dependencies
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- └── .env # Environment variables
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- ```
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-
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- ## Prerequisites
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-
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- - Python 3.8+
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- - Node.js 14+
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- - npm or yarn
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-
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- ## Setup
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-
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- 1. Clone the repository:
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- ```bash
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- git clone <repository-url>
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- cd ai-mart
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- ```
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-
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- 2. Set up the backend:
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- ```bash
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- # Create and activate virtual environment
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- python -m venv venv
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- source venv/bin/activate # On Windows: venv\Scripts\activate
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-
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- # Install dependencies
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- pip install -r requirements.txt
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-
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- # Set up environment variables
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- cp .env.example .env
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- # Edit .env with your configuration
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- ```
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-
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- 3. Set up the frontend:
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- ```bash
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- cd frontend
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- npm install
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- ```
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-
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- ## Running the Application
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-
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- 1. Start the backend server:
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- ```bash
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- # From the project root
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- uvicorn main:app --reload
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- ```
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-
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- 2. Start the frontend development server:
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- ```bash
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- # From the frontend directory
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- npm start
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- ```
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-
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- The application will be available at:
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- - Backend API: http://localhost:8000
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- - Frontend: http://localhost:3000
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- - API Documentation: http://localhost:8000/docs
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-
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- ## API Documentation
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-
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- The API documentation is available at `/docs` when running the backend server. It provides detailed information about all available endpoints, request/response formats, and authentication requirements.
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-
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- ## Contributing
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-
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- 1. Fork the repository
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- 2. Create your feature branch (`git checkout -b feature/amazing-feature`)
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- 3. Commit your changes (`git commit -m 'Add some amazing feature'`)
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- 4. Push to the branch (`git push origin feature/amazing-feature`)
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- 5. Open a Pull Request
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-
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- ## License
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-
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- This project is licensed under the MIT License - see the LICENSE file for details.
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-
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- ## Acknowledgments
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-
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- - FastAPI for the amazing backend framework
102
- - React.js for the frontend framework
 
 
 
 
 
 
 
 
 
 
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  - All contributors and maintainers
 
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+ ---
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+ title: Multi-Agent E-Commerce Recommender
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+ emoji: πŸ›’
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+ colorFrom: indigo
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+ colorTo: pink
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+ sdk: docker
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+ app_file: main.py
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+ pinned: false
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+ ---
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+
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+ # Multi-Agent E-Commerce Recommendation System
12
+
13
+ A sophisticated recommendation system that uses multiple AI agents to provide personalized product recommendations to users.
14
+
15
+ ## Features
16
+
17
+ - Multiple recommendation algorithms (Collaborative Filtering, Content-Based, Sequential Pattern Mining, Hybrid)
18
+ - Real-time user feedback processing
19
+ - Personalized product recommendations
20
+ - Admin dashboard for system monitoring
21
+ - Modern React.js frontend
22
+ - FastAPI backend with async support
23
+
24
+ ## Project Structure
25
+
26
+ ```
27
+ .
28
+ β”œβ”€β”€ frontend/ # React.js frontend
29
+ β”œβ”€β”€ src/
30
+ β”‚ β”œβ”€β”€ api/ # API endpoints and routes
31
+ β”‚ β”œβ”€β”€ algorithms/ # Recommendation algorithms
32
+ β”‚ β”œβ”€β”€ agents/ # AI agents implementation
33
+ β”‚ β”œβ”€β”€ database/ # Database models and connection
34
+ β”‚ └── utils/ # Utility functions
35
+ β”œβ”€β”€ main.py # Application entry point
36
+ β”œβ”€β”€ requirements.txt # Python dependencies
37
+ └── .env # Environment variables
38
+ ```
39
+
40
+ ## Prerequisites
41
+
42
+ - Python 3.8+
43
+ - Node.js 14+
44
+ - npm or yarn
45
+
46
+ ## Setup
47
+
48
+ 1. Clone the repository:
49
+ ```bash
50
+ git clone <repository-url>
51
+ cd ai-mart
52
+ ```
53
+
54
+ 2. Set up the backend:
55
+ ```bash
56
+ # Create and activate virtual environment
57
+ python -m venv venv
58
+ source venv/bin/activate # On Windows: venv\Scripts\activate
59
+
60
+ # Install dependencies
61
+ pip install -r requirements.txt
62
+
63
+ # Set up environment variables
64
+ cp .env.example .env
65
+ # Edit .env with your configuration
66
+ ```
67
+
68
+ 3. Set up the frontend:
69
+ ```bash
70
+ cd frontend
71
+ npm install
72
+ ```
73
+
74
+ ## Running the Application
75
+
76
+ 1. Start the backend server:
77
+ ```bash
78
+ # From the project root
79
+ uvicorn main:app --reload
80
+ ```
81
+
82
+ 2. Start the frontend development server:
83
+ ```bash
84
+ # From the frontend directory
85
+ npm start
86
+ ```
87
+
88
+ The application will be available at:
89
+ - Backend API: http://localhost:8000
90
+ - Frontend: http://localhost:3000
91
+ - API Documentation: http://localhost:8000/docs
92
+
93
+ ## API Documentation
94
+
95
+ The API documentation is available at `/docs` when running the backend server. It provides detailed information about all available endpoints, request/response formats, and authentication requirements.
96
+
97
+ ## Contributing
98
+
99
+ 1. Fork the repository
100
+ 2. Create your feature branch (`git checkout -b feature/amazing-feature`)
101
+ 3. Commit your changes (`git commit -m 'Add some amazing feature'`)
102
+ 4. Push to the branch (`git push origin feature/amazing-feature`)
103
+ 5. Open a Pull Request
104
+
105
+ ## License
106
+
107
+ This project is licensed under the MIT License - see the LICENSE file for details.
108
+
109
+ ## Acknowledgments
110
+
111
+ - FastAPI for the amazing backend framework
112
+ - React.js for the frontend framework
113
  - All contributors and maintainers