Project2024

ACT (Agentic Corporate Trader)

Project Readme File

User Authentication and Access Control • User Login/Logout • Role-based Access Control • Session Management • Forgot Password/Reset Password
Dashboard Overview • Client Overview (total clients, account statuses) • Market Overview (current stock/market prices/news Section) • Recent Activities Log • Graphical Analysis (performance graphs)
Client Management • Client Profiles (personal info, portfolio details) • Client Search and Filter • Client Communication (email or chat integration) • Client Segmentation (by risk profile, investment goals)
Portfolio Management • View and Manage Portfolios • Investment Strategy Settings • Trade Execution (buy/sell functionality) • Portfolio Performance Tracking • Asset Allocation Management • Risk Management Tools (risk exposure analysis)
Market and Price Alerts • Set Price/Performance Alerts • Real-time Alert Notifications • Watchlist Management
Trading and Transaction Management • Place Trades (stocks, crypto currencies) • Order History • Transaction Fees Tracking • Support for Different Order Types (market, limit, stop-loss) • Trade Execution Report
Reporting and Analytics • Generate Reports (portfolio performance, risk analysis) • Customizable Reports • Performance Benchmarks (S&P 500, Bitcoin etc.) • Export Options (PDF, CSV, Excel) • Data Visualization (charts, graphs)
Financial Tools and Calculators • Investment Calculators (portfolio growth, interest) • Risk Assessment Tools • Tax Calculation Tools
Security Features • Security (SSL/TLS Encryption) • Multi-factor Authentication (MFA) • Audit Logs
User Interface (UI) and User Experience (UX) • Responsive Design (mobile-friendly) • Intuitive Layout • Customizable Dashboard (Dark mode optional?) • Loading States and Feedback • Colour visuals
Integration with External APIs • Market Data Integration (real-time stock prices) • Banking Integration (deposits/withdrawals) • CRM System Integration
Support and Help Section • Support Page (troubleshooting, help requests) • FAQ Section • User Guide (Guide for Navigation or a help page)
Notifications System • In-app Notifications • Email Notifications
Progressive Web App (PWA) • Progressive Web App (PWA) Support
Admin Panel (For Website Management) • User Management (accounts, permissions) • Content Management (static page updates)
Verification and Regulatory Tools • Customer Verification • Trade Compliance with Local Regulations
Backup and Disaster Recovery • Regular Data Backup • Disaster Recovery Plan (Database Backup files)

Requirements

Django – The main framework for the backend.
Django REST Framework – For building REST APIs.
Django Allauth – For social login integration (if needed).
djangorestframework-simplejwt – For token-based authentication (JWT).
Firebase Admin SDK – For Firebase integration.
Stripe/PayPal SDK – If you need to integrate payment options.

*** Comparison of Django and Flask to choose the optimal framework for the project

Feature	Django	Flask
User Management & Authentication	Built-in (authentication, authorization, roles)	Not built-in, requires external libraries (e.g., Flask-Login)
Admin Interface	Built-in, powerful and customizable	Not built-in, requires external libraries (e.g., Flask-Admin)
Data Management & ORM	Built-in (Django ORM)	Not built-in, typically uses SQLAlchemy
Security	Built-in protections (CSRF, XSS, SQL injections)	Minimal built-in protections, requires manual setup or extensions
Scalability & Asynchronicity	Supports asynchronous requests, scalable architecture	Flexible, supports asynchronous behavior with additional setup
API Support	Built-in (Django REST Framework)	Not built-in, but Flask-RESTful can be used
Modularity & Code Reuse	Modular by design (through apps)	Requires manual setup for modularity
Payment Integration	Easy integration with Stripe, PayPal via libraries	Not built-in, manual integration with payment systems required

Conclusion: Django is better suited for your "ACT (Agentic Corporate Trader)" project because:

It provides built-in solutions for managing users. The built-in admin interface. Django REST Framework (DRF) quick option for create of APIs for mobile and web applications. Django has a good secure, it is very important for a financial applications. Django’ssupport for asynchronous requests, it is very important for work with large amounts of data and market information.

Flask can be use for smaller microservices or lightweight APIs, but for a centralized backend with complex features and high security needs, Django is the optimal choice.

Database Configuration

This project utilizes the following database setup:

SQLite:
- Purpose: Used for storing system-level data (e.g., user authentication, admin panel, session data).
- Configuration: Default Django database (db.sqlite3).
Firebase Firestore:
- Purpose: Used for business logic data (e.g., assets, portfolios, trade history).
- Configuration: Integrated via Firebase Admin SDK, with credentials stored in the project directory (config/your-firebase-key.json).

Data Model Overview

The system is designed to manage funds and portfolios, allowing Fund Administrators and Fund Managers to create and manage orders for purchasing or selling technology stocks and crypto assets. These orders are processed and managed by the system, with real-time financial data (such as asset prices, trading volume, and financial news) fetched from external APIs.

1. User

The User entity represents the primary actors in the system. There are three roles:

System Administrator: manages the system and users.
Fund Administrator: manages only their own assets (funds and portfolios).
Fund Manager: manages assets for multiple client companies.

Fields:

id: Unique identifier for the user.
username: The username for login.
password: Encrypted password for the user.
role: The role of the user (system_admin, fund_admin, fund_manager).

Relationships:

A Fund Administrator manages multiple Funds and Portfolios.
A Fund Manager manages multiple Clients, each with their own Funds and Portfolios.

2. Client

The Client entity represents a company or organization whose assets are managed by a Fund Manager. Each client record contains information about the client and their assets.

Fields:

id: Unique identifier for the client.
name: The name of the company or organization.
fund_manager_id: The ID of the User who acts as the Fund Manager.

Relationships:

A Client has multiple Funds.

3. Fund

The Fund entity represents a pool of financial assets managed by a user. Depending on the user’s role, a fund may belong to either a Fund Administrator or a Client, managed by a Fund Manager.

Fields:

id: Unique identifier for the fund.
name: The name of the fund.
user_id: The ID of the User (if the fund is managed by a Fund Administrator).
client_id: The ID of the Client (if the fund is managed by a Fund Manager).

Relationships:

A Fund contains multiple Portfolios.

4. Portfolio

The Portfolio entity represents a collection of financial assets (stocks and cryptocurrencies) owned by a user or client.

Fields:

id: Unique identifier for the portfolio.
name: The name of the portfolio.
fund_id: The ID of the Fund associated with the portfolio.

Relationships:

A Portfolio contains multiple Assets.
A Portfolio has multiple Orders.

5. Asset

The Asset entity represents individual financial assets (stocks or crypto assets) within a portfolio. It tracks real-time financial data (such as price and volume) through external APIs like Yahoo Finance and Alpha Vantage.

Fields:

id: Unique identifier for the asset.
symbol: Ticker symbol of the asset (e.g., AAPL for Apple).
price: Current market price of the asset, fetched from external APIs.
volume: The total market trading volume for the asset, fetched from external APIs (not related to the user's specific holdings).
amount: The quantity of the asset held in the portfolio by the user.
last_updated: Date and time of the last price and volume update.
portfolio_id: The ID of the portfolio containing the asset.

Relationships:

An Asset belongs to one Portfolio.

6. Order

The Order entity represents financial actions (buying or selling) within a portfolio.

Fields:

id: Unique identifier for the order.
amount: The quantity of the asset being traded.
order_type: The type of order, either:
- buy: A purchase of an asset.
- sell: A sale of an asset.
portfolio_id: The ID of the portfolio associated with the order.

Relationships:

An Order is linked to one Portfolio.
An Order may be rated by one Trade_Rating.

7. Trade_Rating

The Trade_Rating entity represents a user’s evaluation or rating of a specific order, used to assess the performance of the trade.

Fields:

id: Unique identifier for the rating.
rating: The score or evaluation of the order.
order_id: The ID of the associated order.

Relationships:

A Trade_Rating is linked to one Order.

8. AI_Forecast

The AI_Forecast entity stores predictions or forecasts generated by the system’s AI model. These forecasts help users make informed decisions about their investments.

Fields:

id: Unique identifier for the forecast.
forecast: The AI-generated prediction or advice.
user_id: The ID of the User who generated the forecast.

Relationships:

An AI_Forecast is generated by one User.

9. Support_Request

The Support_Request entity allows users to submit inquiries or issues requiring assistance. This can be related to technical or account-related problems.

Fields:

id: Unique identifier for the support request.
request: The content of the support request.
user_id: The ID of the User who submitted the request.

Relationships:

A Support_Request is submitted by one User.

Integration with External APIs

Yahoo Finance API and Alpha Vantage API are integrated to fetch real-time data such as stock prices, trading volume, and financial news. The system regularly updates this data to ensure accurate information is available to users.
Stock Prices and Volume: The Asset entity uses real-time price data from external APIs to keep portfolios up to date. Each order records the volume of traded assets.
Financial News: The system can display relevant financial news related to assets using Yahoo Finance, allowing users to stay informed about events that may impact their investments.

Integration with External APIs:

Yahoo Finance API and Alpha Vantage API are used to fetch real-time data for investments, including stock prices, trading volume, and financial news. These APIs keep the system updated with real-world data that allows Fund Managers and Administrators to make well-informed decisions.
Financial News: By integrating with the Yahoo Finance API, the system can display relevant financial news related to a user’s investments, helping them stay informed of market events that could impact their assets.

Database Diagram

The ACT system's database structure represents the relationships between key entities such as Users, Clients, Funds, Portfolios, and financial Assets. Below is a summary of the database structure, which includes managing orders, tracking assets, work with AI, and integrating with external APIs for real-time financial data.

Key Entities:

User: Represents system actors, including Fund Administrators, Fund Managers, and System Administrators.
Client: A company or organization whose assets are managed by a Fund Manager.
Fund: A collection of assets managed by a User (either a Fund Administrator or Client managed by a Fund Manager).
Portfolio: A collection of assets within a fund, managed by a User or Client.
Asset: Financial assets (stocks or crypto) tracked within a portfolio, with real-time data fetched from external APIs.
Order: Represents buy or sell transactions within a portfolio.
Trade Rating: User's evaluation of an order's performance.
AI Forecast: Predictive financial insights generated by the AI engine.
Support Request: A user's inquiry for technical or account-related issues requiring assistance.

Relationships:

A User manages multiple Funds and Portfolios.
A Fund contains multiple Portfolios.
A Portfolio contains multiple Assets and Orders.
Each Order may be rated by one Trade Rating.
AI Forecasts are generated by Users.
Support Requests are submitted by Users.

Key Relationships Explained:

User and Fund: A user can manage multiple funds. For example, a Fund Manager could oversee various funds belonging to different clients.
User and Portfolio: Each User can own multiple portfolios, especially Fund Administrators who are handling their own investments.
Client and Fund: A Client can have multiple funds managed on their behalf by a Fund Manager.
Portfolio and Asset: Each portfolio contains several assets, representing individual stocks or crypto assets that the user has invested in.
Order and Portfolio: Users can create multiple orders (buy or sell) for assets within their portfolios.
Order and Trade Rating: Each order can be rated based on the performance of the trade.
AI Forecast: Generated by the AI engine to assist users in making informed investment decisions.
Support Request: Users can submit support requests if they require assistance with their portfolios or technical issues.

Diagram Code in PlantUML:

@startuml
class User {
  +id: int
  +username: string
  +password: string
  +role: string
}

class Client {
  +id: int
  +name: string
  +fund_manager_id: int
}

class Fund {
  +id: int
  +name: string
  +user_id: int
  +client_id: int
}

class Portfolio {
  +id: int
  +name: string
  +fund_id: int
}

class Asset {
  +id: int
  +symbol: string
  +price: float
  +volume: int
  +amount: float
  +last_updated: datetime
  +portfolio_id: int
}

class Order {
  +id: int
  +amount: float
  +order_type: string
  +portfolio_id: int
}

class Trade_Rating {
  +id: int
  +rating: float
  +order_id: int
}

class AI_Forecast {
  +id: int
  +forecast: string
  +user_id: int
}

class Support_Request {
  +id: int
  +request: string
  +user_id: int
}

' Relationships
User "1" -- "many" Fund : manages
User "1" -- "many" Portfolio : owns
User "1" -- "many" AI_Forecast : generates
User "1" -- "many" Support_Request : submits

Client "1" -- "many" Fund : manages

Fund "1" -- "many" Portfolio : contains
Portfolio "1" -- "many" Asset : contains
Portfolio "1" -- "many" Order : has

Order "1" -- "1" Trade_Rating : rated by

@enduml

Backend

Development Server on the DigitalOcean host

The project is currently running on a development server accessible via the following address:

http://161.35.38.50:8000

You can access both the API and the Django Admin interface using this URL.

Django Admin: To access the admin panel, navigate to /admin/ on the server URL (e.g., http://161.35.38.50:8000/admin/).
API Endpoints: The API can be accessed by using the /api/, for example
- User Registration:
```
POST http://161.35.38.50:8000/api/register/
```

Backend-Installation-Guide for local machine

The ACT (Agentic Corporate Trader) backend uses Docker to streamline local development, ensuring consistent dependencies and an isolated runtime environment. This setup eliminates the need for manual installation of Python or additional libraries on the host machine.

Docker Setup

Make sure Docker and Docker Compose are installed on your system. Follow these command to build and run the backend:

docker-compose up --build

Access the Application:

Base Url: http://localhost:8000
Admin panel: http://localhost:8000/admin

Docker Compose Configuration

The provided docker-compose.yml file ensures that the Django backend is containerized and exposes port 8000 for local access. The configuration includes:

services:
  web:
    build:
      context: .
    ports:
      - "8000:8000"
    volumes:
      - .:/app
    env_file:
      - .env
    environment:
      - DJANGO_SETTINGS_MODULE=act_backend.settings

Explanation:

web: The main service running the Django backend.
ports: Maps the container's port 8000 to the host's port 8000, enabling access at http://localhost:8000.
volumes: Mounts the current project directory into the container for live updates.
env_file: Specifies .env for environment variables, centralizing sensitive data like secret keys and API credentials.
environment: Passes runtime variables to the Django application.

Dockerfile Configuration

The Dockerfile is optimized for a Python 3.11 environment and includes all necessary dependencies for the backend:

# Base image
FROM python:3.11-slim

# Install system dependencies
RUN apt-get update && apt-get install -y \
    build-essential \
    gcc \
    libffi-dev \
    libssl-dev \
    && apt-get clean

# Upgrade pip
RUN pip install --upgrade pip

# Set working directory and install Python dependencies
WORKDIR /app
COPY requirements.txt /app/
RUN pip install -r requirements.txt

# Copy the entire project code
COPY . /app/

# Expose port 8000 for the Django application
EXPOSE 8000

# Start the Django development server
CMD ["python", "manage.py", "runserver", "0.0.0.0:8000"]

Managing the Project with Docker

4.1. Apply Database Migrations

Run migrations to initialize the SQLite database:

docker-compose exec web python manage.py migrate

4.2. Load Sample Data

Populate both SQLite and Firebase with fixtures:

docker-compose exec web python manage.py load_fixtures

Environment Variables

The .env file contains all configuration values required for the backend to run. An example .env file is provided below:

DJANGO_SECRET_KEY="your-django-secret-key"
FIREBASE_CREDENTIALS_FILE="/path/to/your-firebase-key.json"
RAPIDAPI_KEY="your-rapidapi-key"
RAPIDAPI_HOST="your-rapidapi-host"
ALPHA_VANTAGE_API_KEY="your-alpha-vantage-api-key"
FINNHUB_API_KEY=""your-finnhub-api-key"
STRIPE_SECRET_KEY="your-stripe-secret-key"
STRIPE_PUBLISHABLE_KEY="your-stripe-publishable-key"
FRONTEND_URL="https://chrisluddy.github.io/Project2024/"
GEMINI_API_KEY="your-gemini-api-key"

Notes:

AI Integration: The AI libraries and models are managed within the container, ensuring compatibility across environments and reducing setup complexity.
Firebase Integration: Ensure that the Firebase Admin SDK JSON file is correctly placed in the config directory and referenced in the volumes section.
Live Code Changes: The volumes directive allows live code changes to reflect without rebuilding the container.
Environment Variables: The .env file centralizes environment-specific configuration, making the application portable across different environments.

Tests

The tests for this project are located in tests/tests.py. They are divided into three categories:

CRUD Tests for Firebase Models

These tests validate the basic CRUD operations (Create, Read, Update, Delete) for Firebase models:

Client
Fund
Portfolio
Asset
Order
TradeRating
AIForecast
SupportRequest

Purpose: Ensure all Firebase models are correctly created, updated, retrieved, and deleted.

Permission Tests

These tests check role-based access control for API endpoints:

fund_manager: Allowed access to funds-related endpoints.
fund_admin: Restricted from accessing certain endpoints.
Anonymous users: Denied access (401 Unauthorized).

Endpoints Tested: /api/funds/

External API Tests

Tests for integrations with external APIs like:

Yahoo Finance: Mocked responses for stock data retrieval.
Alpha Vantage: Mocked responses for time series data.

Note: Mocking is used to avoid actual API calls.

How to Run Tests

Execute all tests with:

python manage.py test tests

Work in admin panel

Creating Fund Administrator or Fund Manager from admin panel You can to add users with the roles Fund Administrator and Fund Manager through the Django admin interface:
1. Go to the admin panel at {{url}}/admin/.
2. Log in using your superuser credentials.
3. Navigate to CORE > Users and add new users. You can assign them the roles Fund Administrator or Fund Manager as needed.
4. Ensure that the is_staff and is_active flags are checked for the users you create. This allows them to log in and interact with the system.
5. After creating the users, you can authenticate them via the API.

Permissions in Project

In this project, role-based permissions are enforced to provide secure and restricted access to various endpoints. The following roles have been defined for the system:

Role Definitions

FundAdmin:
- Fund Administrators can manage assets and subscriptions associated with their own funds.
- They have access to create, read, update, and delete operations within their own scope.
FundManager:
- Fund Managers can manage client assets, subscriptions, and funds for multiple clients.
- They have broader permissions compared to Fund Administrators.

API

User Registration Endpoint

This endpoint allows for the registration of new users with specific roles, such as Fund Administrator or Fund Manager.

To register a new user, send a POST request to:

POST /api/register/

With the following fields in the request body:

{
    "username": "admin001",
    "email": "admin001@example.com",
    "password": "password_123",
    "role": "fund_admin"
}

For example:

POST /api/register/
HTTP 201 Created
Allow: POST, OPTIONS
Content-Type: application/json
Vary: Accept

{
    "username": "Admin001",
    "email": "admin001@example.com",
    "password": "password_123",
    "role": "fund_admin"
}

Example Responses:

Status: 201 Created

{
    "user": {
        "username": "Manager004",
        "email": "manager004@example.com",
        "role": "fund_manager"
    },
    "refresh": "eyJhbGciOiJIUzI1....z0Lb9o4syqXDB4kzA",
    "access": "eyJhbGciOiJI.............8hFCgOmlBXTr_4"
}

Status: 400 Bad Request

{
  "error": "User already exists or invalid data"
}

API Authentication

The project uses JWT (JSON Web Tokens) for authentication.

To obtain JWT tokens, send a POST request to:

POST /api/token/

With Fund Administrator or Fund Manager credentials in the request body:

{
    "email": "user@emai.com",
    "password": "password"
}

This will return access and refresh tokens, which are used to authenticate API requests.

For example:

POST /api/token/
HTTP 200 OK
Allow: POST, OPTIONS
Content-Type: application/json
Vary: Accept
{
    "refresh": "eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXV...hEdGfvcfWZk6mZa0ftLU3AOPyFDZHI",
    "access": "eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVC...-Rl2Tc57Kkp_MzuH0jxg0APRrDr9o9s"
}

Asset Management

Retrieve All Assets

Endpoint: GET /api/assets/

Description: Fetches a list of all assets.

Example Request:

curl -X GET 'http://161.35.38.50:8000/api/assets/' -H 'Authorization: Bearer JWT_TOKEN'

Example Response (Status 200):

[
    {
        "id": "asset_id_1",
        "symbol": "AAPL",
        "price": 150.5,
        "volume": 2000,
        "amount": 100,
        "portfolio_id": "portfolio_id_1",
        "last_updated": "2024-11-02T12:34:56Z"
    },
    ...
]

Create an Asset

Endpoint: POST /api/assets/

Description: Creates a new asset.

Request Body:

{
    "symbol": "AAPL",
    "price": 150.5,
    "volume": 2000,
    "amount": 100,
    "portfolio_id": "portfolio_id_1"
}

Example Request:

curl -X POST 'http://161.35.38.50:8000/api/assets/' -H 'Authorization: Bearer JWT_TOKEN' -d '{"symbol": "AAPL", "price": 150.5, "volume": 2000, "amount": 100, "portfolio_id": "portfolio_id_1"}'

Example Response (Status 201 Created):

{
    "id": "asset_id_1",
    "symbol": "AAPL",
    "price": 150.5,
    "volume": 2000,
    "amount": 100,
    "portfolio_id": "portfolio_id_1",
    "last_updated": "2024-11-02T12:34:56Z"
}

Retrieve a Specific Asset by ID

Endpoint: GET /api/assets/<asset_id>/

Description: Fetches details of a specific asset by its ID.

Example Request:

curl -X GET 'http://161.35.38.50:8000/api/assets/asset_id_1/' -H 'Authorization: Bearer JWT_TOKEN'

Example Response (Status 200):

{
    "id": "asset_id_1",
    "symbol": "AAPL",
    "price": 150.5,
    "volume": 2000,
    "amount": 100,
    "portfolio_id": "portfolio_id_1",
    "last_updated": "2024-11-02T12:34:56Z"
}

Update an Existing Asset

Endpoint: PUT /api/assets/<asset_id>/

Description: Updates an existing asset's details.

Request Body:

{
    "symbol": "AAPL",
    "price": 160.0,
    "volume": 2500,
    "amount": 120
}

Example Request:

curl -X PUT 'http://161.35.38.50:8000/api/assets/asset_id_1/' -H 'Authorization: Bearer JWT_TOKEN' -d '{"symbol": "AAPL", "price": 160.0, "volume": 2500, "amount": 120}'

Example Response (Status 200):

{
    "id": "asset_id_1",
    "symbol": "AAPL",
    "price": 160.0,
    "volume": 2500,
    "amount": 120,
    "portfolio_id": "portfolio_id_1",
    "last_updated": "2024-11-03T12:34:56Z"
}

Delete an Asset

Endpoint: DELETE /api/assets/<asset_id>/

Description: Deletes a specific asset.

Example Request:

curl -X DELETE 'http://161.35.38.50:8000/api/assets/asset_id_1/' -H 'Authorization: Bearer JWT_TOKEN'

Example Response (Status 204 No Content):

{}

Client Management

GET /api/clients/ - Retrieve all clients.
POST /api/clients/ - Create a new client.
GET /api/clients/<client_id>/ - Retrieve a specific client by its ID.
PUT /api/clients/<client_id>/ - Update an existing client.
DELETE /api/clients/<client_id>/ - Delete a client.

Fund Management

GET /api/funds/ - Retrieve all funds.
POST /api/funds/ - Create a new fund.
GET /api/funds/<fund_id>/ - Retrieve a specific fund by its ID.
PUT /api/funds/<fund_id>/ - Update an existing fund.
DELETE /api/funds/<fund_id>/ - Delete a fund.

Portfolio Management

GET /api/portfolios/ - Retrieve all portfolios.
POST /api/portfolios/ - Create a new portfolio.
GET /api/portfolios/<portfolio_id>/ - Retrieve a specific portfolio by its ID.
PUT /api/portfolios/<portfolio_id>/ - Update an existing portfolio.
DELETE /api/portfolios/<portfolio_id>/ - Delete a portfolio.

Order Management

GET /api/orders/ - Retrieve all orders.
POST /api/orders/ - Create a new order.
GET /api/orders/<order_id>/ - Retrieve a specific order by its ID.
PUT /api/orders/<order_id>/ - Update an existing order.
DELETE /api/orders/<order_id>/ - Delete an order.

Trade Rating Management

GET /api/trade-ratings/ - Retrieve all trade ratings.
POST /api/trade-ratings/ - Create a new trade rating.
GET /api/trade-ratings/<trade_rating_id>/ - Retrieve a specific trade rating by its ID.
PUT /api/trade-ratings/<trade_rating_id>/ - Update an existing trade rating.
DELETE /api/trade-ratings/<trade_rating_id>/ - Delete a trade rating.

AI Forecast Management

GET /api/ai-forecasts/ - Retrieve all AI forecasts.
POST /api/ai-forecasts/ - Create a new AI forecast.
GET /api/ai-forecasts/<forecast_id>/ - Retrieve a specific AI forecast by its ID.
PUT /api/ai-forecasts/<forecast_id>/ - Update an existing AI forecast.
DELETE /api/ai-forecasts/<forecast_id>/ - Delete an AI forecast.

Support Request Management

GET /api/support-requests/ - Retrieve all support requests.
POST /api/support-requests/ - Create a new support request.
GET /api/support-requests/<support_request_id>/ - Retrieve a specific support request by its ID.
PUT /api/support-requests/<support_request_id>/ - Update an existing support request.
DELETE /api/support-requests/<support_request_id>/ - Delete a support request.

External APIs Integration

In this project, we have integrated two external financial APIs: Yahoo Finance and Alpha Vantage. These APIs allow the application to retrieve real-time and historical market data for stocks and other financial instruments.

Yahoo Finance API:

The Yahoo Finance API provides real-time stock prices, market data, and other financial insights. We use this API to get information such as the current price of stocks, market sentiment, and trading volumes.

URL: /api/yahoo-finance/

Request Method: GET

Request Parameters:

ticker: The stock ticker symbol (e.g., AAPL for Apple Inc.).
type: The type of asset (e.g., STOCKS).

curl -X GET 'http://161.35.38.50:8000/api/yahoo-finance/?ticker=AAPL&type=STOCKS' \
-H 'Authorization: Bearer JWT_TOKEN'

Example Response:

{
    "meta": {
        "version": "v1.0",
        "status": 200,
        "copywrite": "https://apicalls.io"
    },
    "body": {
        "symbol": "AAPL",
        "companyName": "Apple Inc. Common Stock",
        "stockType": "Common Stock",
        "exchange": "NASDAQ-GS",
        "primaryData": {
            "lastSalePrice": "$227.55",
            "netChange": "-1.49",
            "percentageChange": "-0.65%",
            "deltaIndicator": "down",
            "lastTradeTimestamp": "Oct 13, 2024",
            "isRealTime": true,
            "bidPrice": "N/A",
            "askPrice": "N/A",
            "bidSize": "N/A",
            "askSize": "N/A",
            "volume": "31,759,188",
            "currency": null
        },
        "secondaryData": null,
        "marketStatus": "Closed",
        "assetClass": "STOCKS",
        "keyStats": {
            "fiftyTwoWeekHighLow": {
                "label": "52 Week Range:",
                "value": "164.08 - 237.23"
            },
            "dayrange": {
                "label": "High/Low:",
                "value": "NA"
            }
        }
    }
}

Yahoo Finance News API:

The Yahoo News API endpoint in our backend allows fetching real-time financial up-to-date market news, trends, and insights from the Yahoo Finance service.

URL: /api/yahoo-news/

Request Method: GET

Request Parameters:

ticker: The stock ticker symbol (e.g., AAPL for Apple Inc.).
type: The type of asset (ALL, VIDEO or PRESS_RELEASE).

curl -X GET http://161.35.38.50:8000/api/yahoo-news/ \
-H "Authorization: Bearer JWT_TOKEN" \
-H "Content-Type: application/json" \
-d "tickers=AAPL&type=ALL"

Example Response:

{
    "meta": {
        "version": "v1.0",
        "status": 200,
        "copywrite": "https://apicalls.io",
        "total": 50
    },
    "body": [
        {
            "url": "https://www.cnbc.com/2024/11/19/qualcomm-says-it-expects-4-billion-in-pc-sales-by-2029.html",
            "img": "https://cdn.snapi.dev/images/v1/o/w/m/qcomm14-2450117-2767892.jpg",
            "title": "Qualcomm says it expects $4 billion in PC chip sales by 2029",
            "text": "Qualcomm said at its investor day on Tuesday...",
            "source": "CNBC",
            "type": "Article",
            "tickers": ["$QCOM"],
            "time": "Nov 19, 2024, 4:49 PM EST",
            "ago": "6 minutes ago"
        },
        {
            "url": "https://www.youtube-nocookie.com/embed/q8qdLAb0nMo",
            "img": "https://cdn.snapi.dev/images/v1/m/i/6/nvda19-2686814-2767903.jpg",
            "title": "What Nvidia's Blackwell means for 2025 AI chip demand",
            "text": "Nvidia (NVDA) prepares to report fiscal third quarter earnings...",
            "source": "Yahoo Finance",
            "type": "Video",
            "tickers": ["$NVDA"],
            "time": "Nov 19, 2024, 4:48 PM EST",
            "ago": "7 minutes ago"
        }
    ]
}

Response Fields:

meta: Metadata about the API call.
- version: API version.
- status: HTTP status code.
- total: Total number of articles retrieved.
body: A list of news articles.
- url: The link to the full news article or video.
- img: URL to the thumbnail image.
- title: Title of the article or video.
- text: A brief description of the content.
- source: The source of the news (e.g., CNBC, Reuters).
- type: Type of content (ALL or VIDEO or PRESS_RELEASE).
- tickers: Associated stock tickers.
- time: Published date and time.
- ago: How long ago the news was published.

Common Use Cases:

Fetch All News: Retrieve all available financial news.

curl -X GET http://161.35.38.50:8000/api/yahoo-news/ \
-H "Authorization: Bearer JWT_TOKEN"

Fetch News by Tickers: Retrieve news related to specific companies or assets.

curl -X GET http://161.35.38.50:8000/api/yahoo-news/?tickers=AAPL,MSFT \
-H "Authorization: Bearer JWT_TOKEN"

Filter by Content Type: Fetch only videos or articles.

curl -X GET http://161.35.38.50:8000/api/yahoo-news/?type=VIDEO \
-H "Authorization: Bearer JWT_TOKEN"

Error Handling:

401 Unauthorized: Ensure your token is valid and included in the Authorization header.
400 Bad Request: Verify that query parameters are correctly formatted.
503 Service Unavailable: Yahoo API service is down or unreachable.

Alpha Vantage API:

The Alpha Vantage API provides historical and real-time stock data, including daily time series, which shows the open, high, low, close prices, and volume for each day. This is particularly useful for performing technical analysis or retrieving historical trends of a stock.

URL: /api/alpha-vantage/

Request Method: GET

Request Parameters:

symbol: The stock ticker symbol (e.g., AAPL for Apple Inc.).
function: The type of time series data (e.g., TIME_SERIES_DAILY).
outputsize: Data size, either compact (latest 100 data points) or full (all available data).

curl -X GET 'http://161.35.38.50:8000/api/alpha-vantage/?symbol=AAPL' \
-H 'Authorization: Bearer JWT_TOKEN'

Example Response:

{
    "Meta Data": {
        "1. Information": "Daily Prices (open, high, low, close) and Volumes",
        "2. Symbol": "IBM",
        "3. Last Refreshed": "2024-10-11",
        "4. Output Size": "Compact",
        "5. Time Zone": "US/Eastern"
    },
    "Time Series (Daily)": {
        "2024-10-11": {
            "1. open": "233.2500",
            "2. high": "233.4400",
            "3. low": "230.4600",
            "4. close": "233.2600",
            "5. volume": "3469322"
        },
        "2024-10-10": {
            "1. open": "235.1000",
            "2. high": "235.8300",
            "3. low": "231.8100",
            "4. close": "233.0200",
            "5. volume": "3142031"
        },
        ...
        "2024-05-21": {
            "1. open": "169.9400",
            "2. high": "174.9700",
            "3. low": "169.9400",
            "4. close": "173.4700",
            "5. volume": "6459800"
        }
    }
}

AI-Powered Predict API:

The Predict API endpoint provides stock prediction data based on AI analysis.

URL: /api/act-ai/predict/

Request Method: POST

Request Body:

symbol: The stock ticker symbol (e.g., AAPL for Apple Inc.).

curl -X POST http://localhost:8000/api/act-ai/predict/ \
-H "Authorization: Bearer JWT_TOKEN" \
-H "Content-Type: application/json" \
-d '{"symbol": "AAPL"}'

Example Response:

{
  "id": 1,
  "forecast": "**AAPL Short-Term Trading Analysis**\n\n**Time of Analysis:** December 4, 2024, 01:09 AM GMT\n\n**Disclaimer:** This analysis is based on hypothetical real-time data provided and is for illustrative purposes only. It does not constitute financial advice. Trading involves risk, and losses can exceed your investment. Always conduct your own thorough research and consider consulting a financial advisor before making any investment decisions.\n\n**1. Price Action Analysis:**\n\n- **Current Trend Direction and Strength:** The current price of $243.00 shows a slight uptrend from the previous day's close of $229.00. However, the net change is minimal (0.14%), suggesting weak momentum. After-hours trading might show temporary fluctuation, and a more robust trend assessment requires observing the opening price and subsequent price action during regular trading hours.\n\n- **Price Momentum Indicators:** Without access to real-time data for momentum indicators like RSI (Relative Strength Index) or MACD (Moving Average Convergence Divergence), a precise assessment is not possible. These indicators would help confirm the strength and sustainability of the current trend.\n\n- **Support/Resistance Levels from Current Price Action:** Immediate support could be found around $238.9 (today's low), while resistance might be encountered near $242.75 (today's high). More robust support and resistance levels would be identified by examining longer-term charts and previous significant high and low points.\n\n- **Significance of the Current Bid/Ask Spread:** The bid/ask spread of $242.74/$242.95 ($0.21) is relatively tight, suggesting relatively good liquidity, making it easier to enter and exit trades. However, it doesn't reveal anything conclusive about the immediate buying or selling pressure.\n\n**2. Volume Analysis:**\n\n- **Volume Trend Analysis:** Current volume (38,861,014) is significantly higher than the previous day's volume (3,138,952). This increased volume could indicate heightened investor interest and potentially stronger price movements. Volume will be crucial in determining the trend's strength. If the price increase is accompanied by above-average volume, it suggests strong buying pressure. If volume decreases while prices rise, it could indicate a weakening buying momentum.\n\n- **Unusual Volume Activity Assessment:** The drastically higher volume today compared to yesterday warrants further investigation for any news or events driving this increased activity.\n\n**3. Trading Range Analysis:**\n\n- **Key Levels within Today's Range:** $238.9 (low) and $242.75 (high) are significant intraday levels. Breaks above $242.75 or below $238.9 could signal further price movements in that direction.\n\n- **Position Relative to 52-Week Range:** The current price of $243 is relatively high compared to the 52-week low of $164.08 but significantly below the 52-week high of $240.79, suggesting potential for further upward movement, but cautious approach is suggested.\n\n- **Breakout/Breakdown Potential:** A decisive break above $242.75 could signal a potential short-term uptrend. Conversely, a break below $238.9 could signal a possible short-term downturn.\n\n- **Price Volatility Assessment:** The relatively small range between today's high and low compared to the 52-week range indicates relatively low volatility for now. However, this could change rapidly.\n\n**4. Market Context:**\n\n- **Current Market Phase:** The overall market phase (bullish, bearish, or sideways) is not provided. This crucial context is needed for a more comprehensive analysis.\n\n- **Trading Session Analysis:** The data is from the after-hours trading session. This period can experience increased volatility due to lower liquidity and is not always representative of the regular trading session's price action.\n\n- **Exchange-Specific Considerations:** The stock trades on NASDAQ-GS, a well-established and liquid exchange.\n\n- **Real-time vs. Delayed Data Implications:** Using real-time data is crucial for short-term trading opportunities. Delayed data will not suffice.\n\n**5. Short-Term Opportunities:**\n\nBased on the limited data, identifying concrete short-term trading opportunities is difficult. A more complete picture requires:\n\n- **Real-time data for momentum indicators (RSI, MACD):** This will confirm the trend's strength and potential reversal points.\n- **Extended historical price data:** This will provide more comprehensive support and resistance levels.\n- **News and events affecting AAPL:** This will explain any unusual volume activity.\n- **Market-wide conditions:** This provides the proper context to the stock's movement.\n\n**Hypothetical Trading Scenario (Illustrative Only):**\n\n- **If the price decisively breaks above $243.50 (slightly above today's high) with increased volume:** This might signal a short-term bullish opportunity.\n  - **Entry Point:** $243.75\n  - **Stop-Loss:** $242.50\n  - **Target:** $245.00 (risk-reward of approximately 1:1)\n\n- **If the price decisively breaks below $238.00 (slightly below today's low) with increased volume:** This might signal a short-term bearish opportunity.\n  - **Entry Point:** $237.75\n  - **Stop-Loss:** $238.50\n  - **Target:** $236.00 (risk-reward of approximately 1:1)\n\n**Confidence Level:** Low. The analysis is highly limited by the absence of vital data. The confidence level would increase significantly with more complete real-time and historical data, including technical indicators and fundamental analysis.\n\n**Short-Term Price Targets:** Given the limited data, providing specific price targets is unreliable. More complete analysis is necessary.\n\n**Note:** This analysis is purely hypothetical due to the limitations in available data. It's crucial to use up-to-date and comprehensive data for making real trading decisions.",
  "user_id": 2
}

Response Fields:

forecast: AI prediction results.
- price: Predicted stock price.
- confidence: AI model confidence in the prediction (percentage).

Error Handling:

401 Unauthorized: Ensure your token is valid and included in the Authorization header.
400 Bad Request: Ensure symbol is included in the request body.
503 Service Unavailable: Yahoo API service is down or unreachable.

AI-Powered Trade Rating Endpoint:

This AI-powered endpoint provides the trade rating information for a given stock symbol. The trade rating is based on various analytics and insights related to the specified symbol.

URL: /api/act-ai/trade-rating/

Request Method: GET

Request Parameters:

symbol (required): The stock ticker symbol (e.g., AAPL for Apple Inc.).

curl -X GET "http://localhost:8000/api/act-ai/trade-rating/?symbol=AAPL" \
-H "Authorization: Bearer JWT_TOKEN"

Response:

Returns an object with the trade rating details for the given stock symbol.

Example Response:

{
  "symbol": "AAPL",
  "rating": {
    "overall": 8.5,
    "technical": 7.8,
    "fundamental": 9.2,
    "sentiment": 8.0
  },
  "updated_at": "2024-12-11T10:00:00Z"
}

Error Handling:

401 Unauthorized: Ensure your token is valid and included in the Authorization header.
400 Bad Request: Ensure symbol query parameter is included.

Fetch Stock Data from Finnhub

This endpoint allows fetching stock market data for a given stock symbol using the Finnhub API.

URL: /api/act-ai/stock-data/

Request Method: GET

Request Parameters:

symbol: The stock ticker symbol (e.g., AAPL for Apple Inc.).

curl -X GET "http://localhost:8000/api/act-ai/stock-data/?symbol=AAPL" \
-H "Authorization: Bearer JWT_TOKEN"

Example Response:

{
    "c": 247.77,
    "d": 1.02,
    "dp": 0.4134,
    "h": 248.21,
    "l": 245.34,
    "o": 246.89,
    "pc": 246.75,
    "t": 1733864400
}

Error Handling:

401 Unauthorized: Ensure your token is valid and included in the Authorization header.
400 Bad Request: Ensure symbol query parameter is included.
503 Service Unavailable: Finnhub API service is down or unreachable.

Fetch News from Finnhub

This endpoint retrieves the latest news articles for a specific category from Finnhub.

URL: /api/act-ai/stock-news/

Request Method: GET

Request Parameters:

category: (Optional) News category (e.g., general, crypto). Default is general.

curl -X GET "http://localhost:8000/api/act-ai/stock-news/?category=general" \
-H "Authorization: Bearer JWT_TOKEN"

Example Response:

[
    {
        "category": "general",
        "datetime": 1733864400,
        "headline": "Stock market trends today",
        "id": 12345,
        "image": "https://example.com/image.jpg",
        "related": "AAPL",
        "source": "Finnhub",
        "summary": "An overview of today's stock market performance.",
        "url": "https://example.com/news/12345"
    },
    ...
]

Error Handling:

401 Unauthorized: Ensure your token is valid and included in the Authorization header.
400 Bad Request: Ensure symbol query parameter is included.
503 Service Unavailable: Finnhub API service is down or unreachable.

Trending Coins Endpoint from CoinGecko

This endpoint retrieves a list of trending cryptocurrencies, including their detailed market data, price changes, rankings, and additional information using CoinGecko.

URL: /api/act-ai/trending-coins/

Request Method: GET

Request Parameters:

coin_id: (Optional) The ID of the cryptocurrency (e.g., bitcoin, ethereum). Default is bitcoin.

curl -X GET "http://localhost:8000/api/act-ai/trending-coins/" \
-H "Authorization: Bearer YOUR_JWT_TOKEN"

Response:

A JSON array containing trending coins. Each object includes the following fields:

id: The unique identifier for the coin.
name: The name of the cryptocurrency.
symbol: The ticker symbol of the cryptocurrency.
market_cap_rank: The current ranking based on market capitalization.
price: Current price in USD.
price_btc: Current price in BTC.
price_change_percentage_24h: The percentage price change in the last 24 hours for various currencies.
market_cap: The current market capitalization of the cryptocurrency.
total_volume: The total trading volume in USD over the last 24 hours.
sparkline: A URL to a sparkline chart representing the price changes over time.
thumb, small, large: URLs for different sizes of the cryptocurrency's logo.

Example Response:

{
    "coins": [
        {
            "item": {
                "id": "vita-inu",
                "name": "Vita Inu",
                "symbol": "VINU",
                "market_cap_rank": 918,
                "price": 5.110131718661772e-08,
                "price_btc": "0.000000000000528258635215761",
                "price_change_percentage_24h": {
                    "usd": -9.777662743078121,
                    "btc": -9.125630280198598,
                    "eth": -7.593784806228662
                },
                "market_cap": "$46,018,123",
                "total_volume": "$13,096,062",
                "sparkline": "https://www.coingecko.com/coins/20594/sparkline.svg",
                "thumb": "https://coin-images.coingecko.com/coins/images/20594/standard/vita-inu.png",
                "small": "https://coin-images.coingecko.com/coins/images/20594/small/vita-inu.png",
                "large": "https://coin-images.coingecko.com/coins/images/20594/large/vita-inu.png"
            }
        },
        ...
    ]
}

Error Handling:

401 Unauthorized: Ensure your token is valid and included in the Authorization header.
503 Service Unavailable: CoinGecko API service is down or unreachable.

Get Cryptocurrency Information from CoinGecko

This endpoint provides detailed information about a specific cryptocurrency. It allows users to retrieve data such as the cryptocurrency's current price, market capitalization, trading volume, and other relevant details by specifying its unique identifier or symbol using CoinGecko.

URL: /api/act-ai/coin-data/

Request Method: GET

Request Parameters:

coin_id (required): The unique identifier of the cryptocurrency, e.g., bitcoin.

curl -X GET "http://localhost:8000/api/act-ai/coin-data/?coin_id=bitcoin" \
-H "Authorization: Bearer YOUR_JWT_TOKEN"

Response:

A JSON array containing trending coins. Each object includes the following fields:

id: Unique identifier of the cryptocurrency (e.g., bitcoin).
symbol: Cryptocurrency symbol (e.g., btc).
name: Full name of the cryptocurrency.
web_slug: Unique identifier used for URLs.
hashing_algorithm: Hashing algorithm used by the cryptocurrency (e.g., SHA-256).
categories: Categories the cryptocurrency belongs to (e.g., Cryptocurrency, Proof of Work).
description: A description of the cryptocurrency (available in multiple languages).
localization: Localized names of the cryptocurrency.
links: Official resource links, including the website, whitepaper, forums, etc.
market_data: Market data including current price, market capitalization, trading volume, and more.

Example Response:

{
  "id": "bitcoin",
  "symbol": "btc",
  "name": "Bitcoin",
  "web_slug": "bitcoin",
  "hashing_algorithm": "SHA-256",
  "categories": ["Cryptocurrency", "Proof of Work"],
  "description": {
    "en": "Bitcoin is the first successful internet money...",
    "ru": "Биткоин — это первая успешная интернет-валюта..."
  },
  "localization": {
    "en": "Bitcoin",
    "ru": "Биткоин"
  },
  "links": {
    "homepage": ["https://bitcoin.org"],
    "whitepaper": "https://bitcoin.org/bitcoin.pdf"
  },
  "market_data": {
    "current_price": {
      "usd": 96412,
      "eur": 91560
    },
    "market_cap": {
      "usd": 1910526095727,
      "eur": 1814390333117
    },
    "total_volume": {
      "usd": 143027804177
    }
  }
}

Error Handling:

401 Unauthorized: Ensure your token is valid and included in the Authorization header.
400 Bad Request: The coin_id parameter is missing or invalid.
503 Service Unavailable: CoinGecko API service is down or unreachable.

Stripe Integration Endpoints

Payment for Subscription (Annual or Monthly)

URL: /api/create-checkout-session/
Method: POST
Permissions: Only users with roles FundAdmin or FundManager.

Description: This endpoint creates a Stripe Checkout session for processing subscription payments. It supports both annual and monthly plans.

Request (JSON):

{
  "price_id": "price_1QX8TOP9tIxdtAMKjWZcQIu6",
  "email": "customer@example.com"
}

price_id: Stripe Price ID for the subscription plan (annual or monthly).
email: User's email to associate the subscription with a Stripe Customer.

Response (Success):

{
  "sessionId": "cs_test_a1b2c3d4e5f6g7h8i9j0"
}

Response (Error):

{
  "error": "Invalid price ID or email."
}

Notes:

After receiving the sessionId, redirect the user to Stripe Checkout for completing the payment:
```
stripe.redirectToCheckout({ sessionId: "cs_test_a1b2c3d4e5f6g7h8i9j0" });
```
Upon successful payment, the user will be redirected to the success_url. If canceled, the user will be redirected to the cancel_url.

Retrieve Subscription Status

URL: /api/subscription-status/ Method: GET Permissions: Only users with roles FundAdmin or FundManager.

Description: This endpoint retrieves the user's subscription status, including plan name, billing interval (annual or monthly), and next renewal date.

Response (With Active Subscription):

{
  "status": "active",
  "current_period_end": 1702892956,
  "plan_name": "Pro Plan",
  "interval": "year"
}

status: The current subscription status (e.g., active, canceled, past_due).
current_period_end: Unix timestamp representing the end date of the current billing period.
plan_name: The name of the subscribed plan. If a nickname is not provided in Stripe, the product name is used.
interval: Billing interval for the subscription (year or month).

Response (No Active Subscription):

{
  "status": "No active subscription"
}

Response (Error):

{
  "error": "Stripe API error or invalid customer email."
}

Notes:

This endpoint uses the authenticated user's email to retrieve their subscription from Stripe.
Ensure that the user's email is associated with a Stripe Customer.
The current_period_end timestamp can be converted to a human-readable date on the client side.

Chat with Gemini AI

This endpoint allows users to send a message to the Gemini AI model and receive an AI-generated response. It provides seamless integration with Google's Gemini API to enable conversational interactions.

URL: /api/act-ai/chat/

Request Method: POST

Request Parameters:

message (required): The text input or question you want to send to the Gemini AI model.

curl -X POST "http://161.35.38.50:8000/api/act-ai/chat/" \
-H "Authorization: Bearer JWT_TOKEN" \
-H "Content-Type: application/json" \
-d '{
    "message": "Explain how can I make AI predict with your help in very short style"
}'

Response:

reply: The response text generated by the Gemini AI model.

Example Response:

{
    "reply": "1. **Define problem:** Clearly state what you want the AI to predict.\n2. **Gather data:** Collect relevant data.  More data = better predictions.\n3. **Choose model:** Select an appropriate AI model (I can help suggest one).\n4. **Train model:** Use your data to \"teach\" the model.\n5. **Evaluate & refine:** Test the model's accuracy and adjust as needed.\n6. **Make predictions:** Use the trained model to predict new outcomes.\n\n\nI can assist with steps 3 and potentially 4, given sufficient context.  Tell me your problem!\n"
}

Error Handling:

401 Unauthorized: Ensure your token is valid and included in the Authorization header.
400 Bad Request: The message parameter is missing.
503 Service Unavailable: Server misconfiguration or issues with the Gemini API.

External API Failure: Issues with the Gemini API, such as invalid credentials or service downtime.

{
    "error": "Failed to communicate with Gemini API",
    "details": {
        "error": {
            "code": 401,
            "message": "Request had invalid authentication credentials.",
            "status": "UNAUTHENTICATED"
        }
    }
}

Notes:

Ensure the GEMINI_API_KEY is set as an environment variable in your backend configuration..

The endpoint integrates with the Gemini API endpoint:

https://generativelanguage.googleapis.com/v1beta/models/gemini-1.5-flash:generateContent

Ensure the request payload sent to Gemini API matches the required format:

{
    "contents": [{
        "parts": [{"text": "Your input message"}]
    }]
}

Frontend

Set up project environment
- Languages: HTML, CSS, and JavaScript.
- File Structure:
  - Separate CSS files for web (style.css) and mobile (mobile.css) to manage specific styles for different platforms.
  - JavaScript will be used for dynamic interactions and API integration.
  - Maintain a clean and scalable project structure for future development, ensuring easy modification and feature expansion.
Website Layout Design (Desktop-First Approach)
- General Structure:
  - Create a basic structure for the webpage that includes a header, navigation, main content area, and footer.
  - Apply CSS Grid or Flexbox for a responsive and flexible layout.
  - Ensure that the navigation bar is well-styled and intuitive, providing clear paths for users to access different parts of the application.
- Responsive Design:
  - Initially focus on the desktop layout to ensure the design works well on larger screens.
  - Implement a clean and minimalistic approach with proper spacing, alignment, and structure, making sure it's easy to scale down for mobile screens later.
Mobile Layout Design (Mobile-First Approach)
- Media Queries:
  - Use media queries to design layouts for various screen sizes (e.g., 320px, 480px, 768px). This ensures the site is optimized for both mobile and desktop devices.
  - Focus on smaller screens first and build up, applying different breakpoints for fluid responsiveness.
- Mobile-Friendly Navigation:
  - Create a hamburger menu or collapsible menu for mobile users. This ensures the navigation bar adapts smoothly to different screen sizes.
  - Optimize interactive areas such as buttons, icons, and touchable links for mobile users. Ensure sufficient spacing for easy interaction, especially on touch devices..
Typography and Colour Scheme
- Typography:
  - Choose font families and sizes that work well across both web and mobile platforms, ensuring readability on all screen sizes.
  - Adjust line spacing and text alignment based on screen size to maintain clean readability across devices.
- Colour Palette:
  - Define a consistent colour scheme for background, text, buttons, and links. Create separate palettes for both web and mobile to ensure visual consistency across platforms.
  - Ensure that colour choices comply with accessibility standards by testing the contrast ratio and legibility of text against backgrounds, particularly for users with visual impairments.
Performance Optimization
- CSS Optimization:
  - Minify CSS files for both web (style.css) and mobile (mobile.css) to reduce file size and improve page load times.
  - Use browser-specific optimizations by applying vendor prefixes (e.g., -webkit-, -moz-, -o-) to ensure CSS properties work consistently across different browsers.
- Load Optimization:
  - Implement asynchronous loading for CSS files where applicable to ensure that styles are loaded in a non-blocking manner, enhancing the user experience by reducing render-blocking issues.
Cross-Browser Testing and Debugging
- Browser Testing:
  - Test the website's layout and functionality across all major browsers, including Chrome, Firefox, Safari, and Edge, ensuring that the design and interactions work consistently.
- Debugging Tools:
  - Use browser-specific developer tools (e.g., Chrome DevTools, Firefox Inspector) to troubleshoot any layout or JavaScript issues.
  - Debug and fix any inconsistencies in the design, such as padding, margin, and alignment issues, across different browsers.
Final QA and Adjustments
- Comprehensive Testing:
  - Perform a final review of the design and functionality across all devices (desktop, mobile, tablet). Use feedback from the team or lecturers to ensure the site performs well in various scenarios.
- Issue Resolution:
  - Address any remaining visual or performance issues before final deployment.
- User Experience Optimization:
  - Gather user feedback to improve the overall user experience, ensuring the interface is intuitive, fast, and responsive.
Integration with Backend APIs
- Use JavaScript to integrate with the backend APIs (built using Django) for dynamic content rendering, such as user authentication, stock portfolio management, and real-time data fetching.
- Ensure seamless communication between the frontend and backend, including error handling for API calls, smooth data flow, and fast response times.
AI Data Visualization Integration
- Plan for the integration of AI-powered stock price predictions into the frontend interface in later stages.
- Ensure the layout is flexible enough to accommodate charts, tables, or graphs that will visualize stock trends and market predictions based on the AI model.

CSS

- General Body Styling

body {
    font-family: Arial, sans-serif;
    margin: 0;
    padding: 0;
    background-color: #ffffff;
    color: #333;
}

.Font & Colors: Sets a basic font family of Arial, a common sans-serif font, for readability across devices. Background color (#ffffff) and text color (#333) are chosen for a high contrast, enhancing readability. .Margins & Padding: By setting these to 0, it removes any default spacing, allowing for more control over layout spacing.

- Header Styling

header {
    background-color: #0073e6;
    padding: 20px;
    text-align: center;
    color: white;
    font-size: 1.8em;
    font-weight: bold;
}

.Color & Text Styling: The header has a bold blue background (#0073e6) and white text to make it prominent. The large font size and bold styling indicate its importance as a key site element. .Centering Text: Text is centered for a balanced, visually pleasing look.

- Navigation Styling

nav {
    background-color: #005bb5;
    overflow: hidden;
    display: flex; /* Ensures items are in a row */
    justify-content: center; /* Centers the navigation items */
}

nav a {
    display: block;
    color: white;
    text-align: center;
    padding: 14px 20px;
    text-decoration: none;
    font-size: 1.2em;
}

nav a:hover {
    background-color: #004494;
    color: #fff;
}


nav ul {
    list-style-type: none;
    margin: 0;
    padding: 0;
    display: flex;
    justify-content: center;
}

nav ul li {
    margin-right: 20px;
}

nav ul li:last-child {
    margin-right: 0;
}

nav ul li a {
    color: white;
    text-decoration: none;
    padding: 10px 20px;
    background-color: #005bb5;
    border-radius: 5px;
    font-size: 1.2em;
}

nav ul li a:hover {
    background-color: #004494;
}

.Responsive Flex Layout: The navigation bar is styled with flex to align items in a row, providing easy access to navigation links. Centering (justify-content: center) ensures that links are balanced and intuitively placed. .Link Colors & Hover Effects: Links are white on a dark blue background, ensuring readability. The hover effect slightly darkens the background (#004494), providing feedback to users when they interact with a link. .List Item Styling: nav ul li items are spaced out with margin-right, ensuring sufficient space between links for easy clickability on desktop screens. Last items have no right margin to align with the container’s edge.

- Main Content Styling

main {
    padding: 20px;
    text-align: center;
}

main h1 {
    color: #0073e6;
    font-size: 2.5em;
    margin-bottom: 10px;
}

main p {
    font-size: 1.1em;
    color: #555;
    margin-bottom: 30px;
}

.Section Text Centering & Max Width: The main content section uses centered text and a max width (800px) to keep line lengths manageable for reading. .Headings and Text Colors: Blue (#0073e6) heading colors and light grey text (#666) help distinguish section titles and paragraphs, adding visual hierarchy. .Image Styling: Section images are set to 50% width, keeping them adaptable to different screen sizes. The rounded corners add a modern, friendly appearance.

- Form Styling

form {
    max-width: 500px; /* Centering the form */
    margin: 0 auto; /* Centering the form */
    background-color: #fff; /* Form background color */
    border-radius: 8px; /* Rounded corners */
    padding: 20px; /* Padding inside the form */
    box-shadow: 0 2px 10px rgba(0, 0, 0, 0.1); /* Box shadow for depth */
    display: flex;
    flex-direction: column;
    gap: 1rem;
}

form label {
    text-align: left;
    color: #333;
    font-weight: bold;
}

form input, form textarea {
    padding: 10px;
    border: 1px solid #ccc;
    border-radius: 4px;
    font-size: 16px;
}

form textarea {
    resize: vertical;
    min-height: 100px;
}

form button {
    background-color: #0073e6;
    color: white;
    padding: 12px;
    border: none;
    border-radius: 4px;
    cursor: pointer;
    font-size: 16px;
}

form button:hover {
    background-color: #005bb5;
}

.Centering & Box Shadow: The form is centered and has a box shadow for depth, visually separating it from the rest of the page. .Form Inputs: Text inputs and text areas are padded and have rounded borders, improving usability and aesthetics. .Form Button: The button color (#0073e6) matches the overall theme. The hover effect on buttons gives a clear, interactive feel, enhancing user feedback.

- Footer Styling

footer {
    background-color: #0073e6;
    padding: 10px;
    text-align: center;
    color: white;
    position: fixed;
    width: 100%;
    bottom: 0;
}

footer p {
    margin: 0;
    font-size: 0.9em;
}

.Fixed Positioning: The footer is styled to stay at the bottom of the page, with a consistent background color (#0073e6) and white text. It’s small enough to avoid obstructing content but provides easy access to footer information.

- Button Styling

button, .btn {
    background-color: #005bb5;
    color: white;
    padding: 10px 20px;
    border: none;
    border-radius: 5px;
    cursor: pointer;
    font-size: 1em;
}

button:hover, .btn:hover {
    background-color: #004494;
}

.Consistent Button Design: All buttons share a similar blue background and white text with rounded borders, giving them a cohesive look. The color change on hover provides feedback, improving interaction experience.

- Responsive Design

@media (max-width: 768px) {
    nav a {
        float: none;
        width: 100%;
        text-align: left;
    }
}

.Mobile Navigation: At widths below 768px, navigation links take up the full width and are aligned to the left for easier tapping on mobile screens. This approach maintains usability across devices.

- Overall User Friendliness

.Color and Spacing: Consistent colors across sections enhance brand cohesion. Spacing and padding make elements easily clickable and visually distinct. .Intuitive Interactivity: Hover effects and clearly defined buttons guide users in navigating the website. .Responsive Adjustments: Adaptable layouts ensure the design remains accessible and legible on both desktop and mobile, optimizing user experience across all screen sizes.

This code enhances user-friendliness by creating a visually cohesive, responsive design that is easy to navigate and interact with, whether on desktop or mobile.

🤖 ACT-AI-Engine

Advanced Market Analysis & Trading Intelligence

📊 Overview

The ACT-AI-Engine is a sophisticated artificial intelligence system designed for advanced market analysis and trading insights. It serves as the analytical backbone of the larger trading system, providing real-time market analysis, trading recommendations, and predictive insights for both traditional stocks and cryptocurrencies.

⭐ Core Features

The engine employs a multi-agent AI architecture powered by the CrewAI framework, combining different specialized agents to perform complex market analysis tasks. Each agent has specific roles and capabilities, working together to provide comprehensive market insights. Key features include:

Real-time market data analysis Technical and fundamental analysis Trading opportunity identification Risk assessment and trade ratings Price predictions and forecasting Natural language chat interface for market queries Support for both cryptocurrency and traditional stock markets

🏗️ System Architecture

AI Agents The system utilizes five specialized AI agents:

Researcher Agent

Conducts deep market research Analyzes technical indicators Identifies market patterns and trends Provides unique market insights

Accountant Agent

Calculates financial ratios Analyzes fundamental metrics Processes numerical market data Utilizes specialized calculator tools

Recommender Agent

Generates trading recommendations Provides buy/sell/hold signals Assesses market opportunities Evaluates risk factors

Blogger Agent

Formats analysis reports Creates readable market summaries Structures technical content Produces clear documentation

Chatbot Agent

Handles natural language queries Provides market information Maintains conversation context Offers real-time market updates

Data Integration The engine integrates with multiple market data providers:

Yahoo Finance API Alpha Vantage Finnhub CoinGecko (for cryptocurrency data)

Core Components

AiAPI: Main interface for the AI engine TaskManager: Orchestrates AI agent operations MarketData: Handles market data retrieval and processing DataParsers: Processes and standardizes market data CalculatorTool: Performs financial calculations ChatbotTools: Manages natural language interactions

🔍 System Outputs

Chat Interface The chat interface provides natural language responses with real-time market data and analysis:

{
    "message": "What's the market sentiment for Microsoft?",
    "response": "Okay, let's take a look at the market sentiment for Microsoft (MSFT). Currently, the stock is trading at $434.25, down 0.54% for the day as of 3:19 PM ET. The day's trading range has been between $432.83 and $437.65, with a volume of 8,270,924 shares traded.\n\nAnalyst recommendations show a very positive outlook for MSFT. Over the past three months, there have been a significant number of Buy and Strong Buy ratings, with very few Sell or Strong Sell ratings. The exact numbers vary slightly depending on the specific time period, but consistently show a very strong buy consensus. For example, over the past month, there were 13 Strong Buy, 37 Buy, 5 Hold, and zero Sell or Strong Sell ratings.\n\nIt's important to remember that analyst ratings represent opinions, and it's always best to consider other factors before making investment decisions. To help me provide you with more tailored insights, could you tell me what your investment timeframe is (short-term, long-term, etc.) and what your general investment strategy is like?",
    "user_id": 1
}

Trade Ratings The trade rating system provides a simple binary POSITIVE/NEGATIVE assessment:

{
    "symbol": "MSFT",
    "rating": "NEGATIVE",
    "user_id": 1
}

Market Forecasts The forecast system provides detailed multi-timeframe analysis and predictions:

{
    "id": "forecast_id",
    "forecast": "Price Prediction Analysis:\n\n1. Short-term Outlook (1-5 days):\n   - Price Target Range: $430 - $440\n   - Key Support Levels: $430, $425\n   - Key Resistance Levels: $438, $440\n   - Expected Volatility: Medium\n   - Confidence Level: 4/10\n   - Primary Drivers: Recent price consolidation, low trading volume suggesting indecision, potential for short-term price fluctuations based on news and investor sentiment. Lack of technical indicators severely limits confidence.\n\n2. Medium-term Outlook (1-3 weeks):\n   - Price Target Range: $425 - $450\n   - Key Support Levels: $425, $420\n   - Key Resistance Levels: $445, $450\n   - Expected Volatility: Medium\n   - Confidence Level: 5/10\n   - Primary Drivers: Underlying strong fundamentals will provide support. However, regulatory uncertainty and potential negative impacts from insider selling could exert downward pressure.\n\n[... Additional forecast details ...]\n\nFinal Verdict:\nGiven the strong fundamental performance of Microsoft, the long-term outlook remains positive, but the short-to-medium term is characterized by uncertainty. The lack of comprehensive technical data and the prevailing regulatory risks warrant caution.",
    "user_id": 1
}

🛠️ Setup & Configuration

Dependencies Core Requirements

crewai==0.83.0
crewai_tools==0.14.0
Requests==2.32.3

Required API Keys The following API keys must be configured in the environment:

RAPIDAPI_KEY
RAPIDAPI_HOST
ALPHA_VANTAGE_API_KEY
FINNHUB_API_KEY
GEMINI_API_KEY

Installation

Install required packages:

pip install -r requirements.txt

Set up environment variables:

export RAPIDAPI_KEY="your_key"
export RAPIDAPI_HOST="your_host"
export ALPHA_VANTAGE_API_KEY="your_key"
export FINNHUB_API_KEY="your_key"
export GEMINI_API_KEY="your_key"

💻 Usage

Basic Implementation

from act_ai_engine import AiAPI

# Initialize the AI engine
ai_engine = AiAPI()

# Get market forecast
forecast = ai_engine.get_forecast("forecast_id", "AAPL")

# Get trade rating
rating = ai_engine.get_trade_rating("AAPL")

# Process chat message
response = ai_engine.get_chat("What's the outlook for Bitcoin?")

Testing

The engine includes comprehensive testing capabilities:

# Run all tests
ai_engine.run_all_tests()

# Test specific functionality
ai_engine.test_crypto_forecast()
ai_engine.test_stock_forecast()
ai_engine.test_chat()

⚠️ Important Notes

Error Handling The engine implements comprehensive error handling:

API connection error management Data validation and cleaning Graceful degradation when services are unavailable Detailed error logging and reporting

Limitations

API rate limits may affect real-time data availability Cryptocurrency data limited to major tokens Historical data depth varies by data provider Some features require premium API access

Product Backlog

Here's a product backlog by sprint breakdown for the "ACT (Agentic Corporate Trader)" project, aligned with the parallel development of frontend, backend, and AI.

Sprint 1: Initial Setup and Core Development

ID	Feature/Task	Assigned To	Priority	Estimated Effort	Notes
1	Backend Setup: Initialize Django project	Backend Developer	High	4 hours	Start backend API and development
2	User Authentication: Implement Allauth	Backend Developer	High	5 hours	Setup social login integration (Google/Facebook)
8	Frontend Setup: Initialize project structure	Frontend Developers (2)	High	4 hours	Start frontend development
9	Responsive Design: Create web (desktop) layout	Frontend Developers (2)	High	6 hours	Basic layout and responsive design for the web version
12	AI Integration: Implement AI engine (Phase 1)	AI Developer	High	6 hours	Initial setup of AI models and environment
16	Documentation: Prepare README & setup instructions	Backend Developer	High	2 hours	Setup documentation

Sprint 2: API Development and Advanced Frontend

ID	Feature/Task	Assigned To	Priority	Estimated Effort	Notes
3	JWT Authentication: Integrate SimpleJWT	Backend Developer	High	4 hours	Secure token-based authentication for API
4	API for Stock & Crypto Management: Create REST APIs	Backend Developer	High	8 hours	Core API functionality for buying/selling assets
10	Mobile Layout Design: Design mobile-first approach	Frontend Developers (2)	High	5 hours	Responsive design for mobile
12	AI Integration (Phase 2): Develop stock recommendations logic	AI Developer	High	8 hours	Connect models to analyze stocks/crypto and make recommendations
14	Cross-Browser Testing: Test on different browsers	Frontend Developers (2)	Medium	3 hours	Ensure compatibility across browsers

Sprint 3: Finalize Features and Testing

ID	Feature/Task	Assigned To	Priority	Estimated Effort	Notes
5	Admin Interface: Set up Django admin for fund managers	Backend Developer	Medium	6 hours	Admin panel for managing users and funds
6	Firebase Integration: Connect Firebase SDK	Backend Developer	Medium	5 hours	Sync with Firebase for user data storage
7	Payment Gateway Integration: Add Stripe/PayPal	Backend Developer	Medium	6 hours	Payment processing for premium features
11	Typography & Color Scheme: Define styles	Frontend Developers (2)	Medium	4 hours	Finalize design choices for the web and mobile versions
13	Performance Optimization: Minify CSS, JS	Frontend Developers (2)	Medium	3 hours	Optimize performance for both web and mobile platforms
15	Final QA & Adjustments: Review and fix issues	Entire Team	High	4 hours	Fix any remaining issues based on testing and feedback

Sprint 4: Final Adjustments and Handoff

ID	Feature/Task	Assigned To	Priority	Estimated Effort	Notes
16	Final Review: Prepare submission for supervisor	Group Leader	High	2 hours	Finalize documentation and demonstrate environment
12	AI Integration (Finalization): Test AI engine with API	AI Developer	High	4 hours	Ensure AI is fully functional and integrated with API
15	Final QA & Adjustments: Perform final review	Entire Team	High	4 hours	Fix last-minute issues and optimize for submission

Summary:

Total Number of Tasks: 20

Total Estimated Hours: 85 hours

Sprint Breakdown:

Sprint 1:

Number of Tasks: 6 Total Hours: 27 hours
Sprint 2:

Number of Tasks: 5 Total Hours: 28 hours
Sprint 3:

Number of Tasks: 6 Total Hours: 28 hours
Sprint 4:

Number of Tasks: 3 Total Hours: 10 hours

Name		Name	Last commit message	Last commit date
Latest commit History 334 Commits
ACT-HTML-JavaScript		ACT-HTML-JavaScript
backend		backend
.gitignore		.gitignore
.nojekyll		.nojekyll
README.md		README.md
database-diagram.png		database-diagram.png
requirements.txt		requirements.txt

ChrisLuddy/Project2024

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Project2024

Project Readme File

Table of contents

Features

Requirements

Database Configuration

Data Model Overview

1. User

Fields:

Relationships:

2. Client

Fields:

Relationships:

3. Fund

Fields:

Relationships:

4. Portfolio

Fields:

Relationships:

5. Asset

Fields:

Relationships:

6. Order

Fields:

Relationships:

7. Trade_Rating

Fields:

Relationships:

8. AI_Forecast

Fields:

Relationships:

9. Support_Request

Fields:

Relationships:

Integration with External APIs

Integration with External APIs:

Database Diagram

Key Entities:

Relationships:

Key Relationships Explained:

Backend

Development Server on the DigitalOcean host

Backend-Installation-Guide for local machine

Tests

Work in admin panel

Permissions in Project

Role Definitions

API

User Registration Endpoint

API Authentication

Asset Management

Retrieve All Assets

Create an Asset

Retrieve a Specific Asset by ID

Update an Existing Asset

Delete an Asset

Client Management

Fund Management

Portfolio Management

Order Management

Trade Rating Management

AI Forecast Management

Support Request Management

External APIs Integration

Yahoo Finance API:

Yahoo Finance News API:

Alpha Vantage API:

AI-Powered Predict API:

AI-Powered Trade Rating Endpoint:

Fetch Stock Data from Finnhub

Fetch News from Finnhub

Trending Coins Endpoint from CoinGecko

Get Cryptocurrency Information from CoinGecko

Stripe Integration Endpoints

Chat with Gemini AI

Packages