Build Your Own POWERFUL Multi-Agent AI (FastAPI & PydanticAI)

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AI Summary

Title: Creating a Multi-Agent AI Fitness Application

Overview: This video demonstrates the creation of a fitness application utilizing multiple AI agents (multi-agent AI) to improve user health and fitness experiences.

Key Concepts:

• Multi-Agent AI: Utilizes specialized AI agents to automate tasks and enhance results.
• Users input their health/fitness goals.

Application Development:

1. Technologies: FastAPI, Pydantic AI.
2. Main Application Structure:
   • Created a main.py file to manage routing.
   • An /analyze endpoint processes user fitness profiles.

User Input Requirements:

• Activity Level (e.g., sedentary, extreme athlete).
• Specific fitness goals (e.g., weight loss, muscle gain).
• Personal fitness profile (age, weight, height, gender, dietary restrictions, injuries, equipment).

Response Structure:

• Fitness Report: Includes a workout plan, meal plan, daily caloric needs, and motivational quotes.
• Workout plan consists of exercises with details (name, sets, reps, rest).
• Meal plan with calorie counts and types of meals.

AI Agents:

• Fitness Agent: Constructs personalized fitness reports from user data.
• Motivational Agent: Generates motivational quotes based on user goals and selects the best one from a list.

Installation:

• Pydantic AI is installed via pip install pydantic_ai.

Demo: The application is demonstrated by running a sample user profile.

• Output includes a complete fitness plan customized to the user’s input.

Conclusion: The video emphasizes the future potential of multi-agent AI in software development and the necessity for software engineers to adapt.