✅Getting Started

Prerequisites

1. Programming Environment: Python 3.8 or above.

2. Dependencies: Install from pyproject.toml.

3. System Requirements: Linux, Windows, or macOS.

Installation

1. Clone the repository:

   git clone https://github.com/your-repo/aimxt.git
   cd aimxt

2. Install dependencies:

   pip install -r bindings/AIMXT/requirements.txt

3. Verify installation:

   python bindings/AIMXT/examples/stock_market_analyser/standalone_mode.py

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Core Components

1. Agents

AI-driven units responsible for executing tasks.

Key Files:

• agent.py: Main agent logic.

• admin.py: Admin-level functionalities.

2. Tasks

Individual units of work assigned to agents.

Key Files:

• task_coordinator.py: Coordinates task execution.

• task_operator.py: Handles task operations.

3. Utilities

Key Tools:

• agent_monitor.py: Monitor agent performance.

• file_publisher_tool.py: Manage file-based outputs.

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API Documentation

Agent API

• Initialize an Agent:

  from AIMXT.agent import Agent
  agent = Agent(name="ExampleAgent")

• Add Tasks:

  task = Task(name="SampleTask")
  agent.add_task(task)

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Examples and Use Cases

1. Stock Market Analyzer

Analyze market trends and predict outcomes using AI agents.

File: examples/stock_market_analyser/standalone_mode.py

Execution:

python standalone_mode.py

2. Time Scheduling

Automate the scheduling of meetings and tasks.

File: examples/time_scheduling/time_scheduling.py

Execution:

python time_scheduling.py

3. Auction Management

AI-assisted bidding strategies for auctions.

File: examples/auction/single_item_auction.py

Execution:

python single_item_auction.py

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Testing Framework

AIMXT includes an extensive suite of tests to ensure functionality:

• Unit Tests: Verify individual components.

• Integration Tests: Check collaboration between modules.

Example Test:

python tests/AIMXT_agent_test.py

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