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It turns a user's fitness request into a structured, safety-conscious fitness package through the collaboration of four specialised AI agents.\n\nThe app provides general educational fitness guidance. It helps users organise a realistic workout routine, consider safer movement choices, build consistency, and download a formal report. It does **not** diagnose injuries, prescribe treatment, or replace advice from a qualified healthcare or exercise professional.\n\n## Project Description\n\nFitness Crew divides fitness planning between specialised AI agents. Each agent has a different job, personality, goal, and output. Their tasks are chained, so each later agent builds on earlier work rather than repeating it.\n\n```text\nUser fitness details\n        |\n        v\nPractical Fitness Coach\n        |\n        v\nExercise Safety Reviewer\n        |\n        v\nHealthy-Habit Motivator\n        |\n        v\nFitness Report Writer\n        |\n        v\nFinal report + downloadable PDF\n```\n\n## What the Application Can Do\n\nFitness Crew can:\n\n- Create a personalised general fitness plan based on the user's goal, experience, schedule, equipment, and intensity preference.\n- Recommend exercises, sets or time, warm-up, cooldown, rest periods, and weekly progression.\n- Review the plan for avoidable risks and suggest safer modifications.\n- Provide simple stop rules, recovery reminders, and lower-impact alternatives when appropriate.\n- Give supportive motivation and habit-building guidance.\n- Organise all outputs into separate Streamlit tabs.\n- Generate a formal PDF version of the final fitness report for the user to view and download.\n- Limit runs to help control API usage responsibly.\n\n## AI Crew Members\n\n### 1. Practical Fitness Coach\n\n**Role:** Designs the first workout draft.\n\n**Goal:** Create a realistic workout that matches the user's goal, available time, equipment, training days, and preferred intensity.\n\n**Backstory:** The coach is encouraging and practical. It prefers simple movements, clear sets or time, adequate rest, warm-ups, cooldowns, and gradual progression.\n\n**Output:** A clear workout draft with exercises, timing, recovery, and progression ideas.\n\n### 2. Exercise Safety Reviewer\n\n**Role:** Reviews and improves the coach's workout draft.\n\n**Goal:** Reduce avoidable risk and provide safer movement choices while keeping the routine useful for the user's stated goal.\n\n**Backstory:** The reviewer is a cautious movement-safety specialist. It prioritises safety over intensity and checks for excessive workload or unsuitable exercise choices.\n\n**Output:** A revised plan with modifications, lower-impact alternatives, recovery notes, and clear stop rules.\n\n### 3. Healthy-Habit Motivator\n\n**Role:** Helps the user stay consistent with the plan.\n\n**Goal:** Turn the reviewed plan into realistic habits that the user can start and maintain.\n\n**Backstory:** The motivator focuses on small wins, scheduling, consistency, recovery after missed workouts, and encouraging language. It avoids guilt, body-shaming, extreme promises, and punishment workouts.\n\n**Output:** A supportive pep talk, consistency tips, and a practical first-week commitment.\n\n### 4. Fitness Report Writer - Bonus Agent\n\n**Role:** Produces the final formal report.\n\n**Goal:** Combine the coach's draft, the safety review, and the motivation guidance into one professional, well-structured package.\n\n**Backstory:** The report writer is an organised editor who turns the crew's work into a clear, readable, implementation-focused report.\n\n**Output:** A final report containing:\n\n1. Participant Profile\n2. Safety Scope\n3. Weekly Workout Plan\n4. Four-Week Progression\n5. Exercise Modifications and Stop Rules\n6. Recovery and Tracking\n7. Motivation and First-Week Commitment\n\n## How the Crew Works\n\nThe project uses `Process.sequential` in CrewAI. Tasks are deliberately chained with `context=[...]` so each agent uses the previous agents’ output.\n\n1. The user enters fitness details in the Streamlit app.\n2. The Fitness Coach creates the initial workout draft.\n3. The Safety Reviewer reads and improves the coach’s result.\n4. The Motivator receives the reviewed plan and creates a practical adherence plan.\n5. The Report Writer receives the reviewed plan and motivation guidance, then produces the final report.\n6. The application displays all results in tabs and creates a downloadable PDF report.\n\n## Streamlit App Features\n\n### User Inputs\n\nThe user can enter:\n\n- Main fitness goal\n- Limitations or preferences\n- Age group\n- Current fitness level\n- Training days per week\n- Minutes available per session\n- Available equipment\n- Preferred intensity\n\n### Working Sidebar Controls\n\nThe app includes Streamlit sidebar controls, including select boxes, sliders, and radio buttons. These settings actively change the generated output.\n\nFor example:\n\n- Changing available equipment from **No equipment** to **Dumbbells** changes exercise recommendations.\n- Changing training days changes the weekly schedule.\n- Changing minutes per session changes the amount of work suggested.\n- Changing intensity changes the overall workload and exercise approach.\n\n### Organised Output Tabs\n\nAfter the crew finishes, the app displays:\n\n- Final Fitness Report\n- Safety Review\n- Coach Draft\n- Motivation Plan\n- PDF Report\n\n## PDF Report Download - Extra Feature\n\nFitness Crew goes beyond the basic app requirement by generating a formal PDF report. The user can view the PDF inside the app and download it for later use.\n\nThe PDF packages the workout plan, safety guidance, progression, recovery, and motivation into one useful document.\n\n## Example Input to Test\n\n| Field | Example value |\n| --- | --- |\n| Main fitness goal | Build muscle strength and size with a balanced full-body workout routine. |\n| Age group | Adult |\n| Fitness level | Beginner or Some experience |\n| Training days each week | 4 |\n| Minutes per session | 45-60 minutes |\n| Available equipment | Dumbbells |\n| Preferred intensity | Moderate |\n| Limitations or preferences | Adult beginner with access to dumbbells. Prefer proper form guidance, rest days for recovery, and a gradual increase in difficulty. |\n\n## How to Use the App\n\n1. Open the deployed Fitness Crew Streamlit link.\n2. Enter a clear main fitness goal.\n3. Add any relevant preferences or limitations.\n4. Use the sidebar to choose age group, fitness level, training days, time per session, equipment, and intensity.\n5. Click **Build my safe fitness plan**.\n6. Wait for the four agents to complete their sequential work.\n7. Read the final report and the specialist tabs.\n8. Open the PDF tab to view or download the formal report.\n\n## Safety and Responsible API Use\n\n- The app provides general educational fitness guidance only.\n- It does not diagnose injuries or replace professional medical or exercise advice.\n- The Safety Reviewer includes modifications and stop rules.\n- The app includes a run limit to help control API usage.\n- The Groq API key is never placed in the code, repository, or commit history.\n- The Groq API key is stored securely in Streamlit Community Cloud Secrets when deployed.\n\n## Assignment Requirements Completion\n\nThis project has been designed to meet every technical assignment requirement:\n\n| Requirement | How Fitness Crew completes it |\n| --- | --- |\n| At least 3 distinct agents | The project contains four genuinely different agents: Coach, Safety Reviewer, Motivator, and Report Writer. Each has its own role, goal, backstory, and output. |\n| Chained tasks with `context=[...]` and `Process.sequential` | Tasks are sequentially connected. Each later agent uses previous work, especially the safety-reviewed plan and motivation guidance. |\n| Working Streamlit application | Users enter a goal and receive a structured result. Sidebar select boxes, sliders, and radio buttons actively change the plan. |\n| Public Streamlit Community Cloud deployment | The repository is configured for Streamlit Community Cloud deployment with `app.py`, pinned requirements, Python 3.12, and secure Streamlit Secrets. The public Streamlit URL is submitted with the assignment. |\n| Code quality and safety | The project uses pinned versions in `requirements.txt`, has a run limit, and does not store an API key in the code or repository. |\n| Complete README | This README explains the purpose, agents, workflow, features, safety approach, and a copy-paste test input. |\n\n## Bonus Marks Justification - Fourth Agent and PDF Download\n\nThis project respectfully requests consideration for the **up to 10 bonus marks** because it includes meaningful features beyond the core assignment:\n\n1. **Fourth AI Agent:** The Fitness Report Writer is a separate fourth agent that reviews and packages the work of the other agents into a structured formal report.\n2. **Downloadable PDF Report:** The application creates a PDF version of the complete final report. Users can view it in Streamlit and download it.\n3. **Organised Result Tabs:** The final report, coach draft, safety review, motivation guidance, and PDF are separated into clear tabs for a better user experience.\n\nThese additions add a final quality-control and presentation stage to the multi-agent workflow, making the project more complete, useful, and professional.\n\n## Project Files\n\n```text\napp.py             # Streamlit application and CrewAI workflow\nrequirements.txt   # Pinned Python dependencies\nREADME.md          # Project documentation\n```\n\n## Run Locally\n\n1. Install dependencies:\n\n   ```bash\n   pip install -r requirements.txt\n   ```\n\n2. Set the Groq API key as an environment variable. Never commit the actual key:\n\n   ```bash\n   GROQ_API_KEY=\"your_groq_api_key\"\n   ```\n\n3. Run the Streamlit app:\n\n   ```bash\n   streamlit run app.py\n   ```\n\n## Deployment Notes\n\n1. Keep this repository public.\n2. Select `app.py` as the main file.\n3. Set Python version to **3.12** in Advanced settings.\n4. Add the Groq key in Streamlit Secrets:\n\n   ```toml\n   GROQ_API_KEY = \"your_groq_api_key\"\n   ```\n\n5. Deploy and test the public link in an incognito/private browser window.\n\n## Creator and Author\n\n**AYaan Imad**\n\nCreated for the **AI for Teens - Build & Deploy Your Own AI Crew** activity using CrewAI, Groq, Streamlit, and ReportLab.\n","readmeExcerpt":"Fitness Crew - Multi-Agent AI Fitness Planner Fitness Crew is a complete multi-agent AI fitness-planning web application built with **CrewAI**, **Groq**, and **Streamlit**. It turns a user's fitness request into a structured, safety-conscious fitness package through the collaboration of four specialised AI agents. The app provides general educational fitness guidance. 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