Learning CrewAI - Multi-Agent AI System Projects

Intelligent Multi-Agent Collaboration | Production-Ready Systems | Real-World Applications

A comprehensive collection of enterprise-grade, multi-agent AI systems built with CrewAI. Each project demonstrates collaborative AI agents solving complex real-world problems through intelligent task orchestration and domain-specific expertise.

Overview

graph LR
    A[Stock Researcher] --> E[Multi-Agent System]
    B[Cricket Analytics] --> E
    C[Budget Knowledge] --> E
    D[Research Writer] --> E
    E --> F[Intelligent Solutions]

This workspace contains multiple CrewAI projects that showcase advanced multi-agent AI capabilities:

Stock Researcher: Financial analysis with S&P 500 benchmarking and investment recommendations
Cricket Performance Analysis: Sports analytics with player performance metrics and visualizations
Union Budget Knowledge: Government budget analysis and policy query system
Research Writer Crew: Automated research and article generation

Quick Start

1. Environment Setup

# Navigate to workspace root
cd /Users/shinde/Desktop/Talbot/learning_crewai

# Activate shared virtual environment
source venv/bin/activate

# Create .env file with API keys
cp .env.example .env
# Edit .env and add your API keys:
# OPENAI_API_KEY=sk-...
# SERPER_API_KEY=...

2. Run a Project

# Stock Researcher
cd stock_researcher/src
python main.py "AAPL"

# Cricket Performance Analysis
cd cricketer_performance_analysis/src
python main.py "Virat Kohli" "2023"

# Union Budget Knowledge
cd union_budget_knowledge
PYTHONPATH=src python -c 'from union_budget_knowledge.main import kickoff; kickoff()'

# Research Writer Crew
cd research_writer_crew/src
python main.py

Projects

1. Stock Researcher

Advanced financial analysis system with S&P 500 benchmarking

Agents: 6 specialized financial analysts
Capabilities:
- Real-time stock data retrieval
- Comparative S&P 500 analysis
- Investment recommendations (BUY/HOLD/SELL)
- Professional visualization and reporting

→ Full Documentation

Quick Run:

cd stock_researcher/src
python main.py "AAPL"  # Analyze Apple stock

2. Cricket Performance Analysis

Sports analytics and player performance evaluation system

Agents: 3 specialized sports analysts
Capabilities:
- Cricket player statistics aggregation
- Performance metric calculations
- Format-wise analysis (Test/ODI/T20)
- Professional visualization and reporting

→ Full Documentation

Quick Run:

cd cricketer_performance_analysis/src
python main.py "Virat Kohli" "2023"

3. Union Budget Knowledge

Government budget analysis and policy query system

Agents: Multi-agent budget analysis system
Capabilities:
- PDF document processing and indexing
- Natural language budget queries
- Policy analysis and insights
- Interactive Q&A interface

→ Full Documentation

Quick Run:

cd union_budget_knowledge
PYTHONPATH=src python -c 'from union_budget_knowledge.main import kickoff; kickoff()'

4. Research Writer Crew

Automated research and article generation system

Agents: Research and writing specialists
Capabilities:
- Topic research and data gathering
- Article outline generation
- Content writing and editing
- SEO optimization

→ Full Documentation

Quick Run:

cd research_writer_crew/src
python main.py

Shared Resources

Documentation

Location: docs/

Comprehensive learning resources and guides:

Complete A-Z Guide to CrewAI - The ultimate 6,000+ line reference covering:
- All CrewAI concepts from Agents to Zero-to-Production
- Architecture patterns and best practices
- Prompt engineering techniques
- Production deployment strategies
- Real-world code examples
- Debugging and monitoring

Virtual Environment

Location: venv/

All projects use a shared Python virtual environment for efficient dependency management.

Setup:

# One-time setup (already done)
python3 -m venv venv
source venv/bin/activate
pip install crewai[tools] python-dotenv pypdf2 litellm

# Subsequent uses
source venv/bin/activate

Environment Configuration

Location: .env

Centralized API key management for all projects:

# Required for all projects
OPENAI_API_KEY=sk-your_openai_key
SERPER_API_KEY=your_serper_key

# Optional project-specific settings
LOG_LEVEL=INFO
DEBUG_MODE=false

Project Structure

learning_crewai/
├── .env                              # Shared environment variables
├── .gitignore                        # Git ignore rules
├── venv/                             # Shared virtual environment
│   ├── bin/
│   ├── lib/
│   └── ...
│
├── docs/                             # Documentation
│   └── crew_ai_context.md           # Complete A-Z Guide to CrewAI
│
├── stock_researcher/                 # Financial analysis project
│   ├── src/
│   │   ├── main.py
│   │   ├── crew.py
│   │   └── config/
│   │       ├── agents.yaml
│   │       └── tasks.yaml
│   └── README.md
│
├── cricketer_performance_analysis/   # Sports analytics project
│   ├── src/
│   │   ├── main.py
│   │   ├── crew_setup.py
│   │   └── config/
│   │       ├── agents.yaml
│   │       └── tasks.yaml
│   └── README.md
│
├── union_budget_knowledge/           # Budget analysis project
│   ├── src/
│   │   ├── main.py
│   │   ├── crews/
│   │   │   └── budget_response_crew/
│   │   │       ├── budget_crew.py
│   │   │       └── config/
│   │   │           ├── agents.yaml
│   │   │           └── tasks.yaml
│   │   └── tools/
│   ├── Union_Budget_Analysis-2023-24.pdf
│   └── README.md
│
├── research_writer_crew/             # Research & writing project
│   ├── src/
│   │   ├── main.py
│   │   ├── crew_setup.py
│   │   └── config/
│   │       ├── agents.yaml
│   │       └── tasks.yaml
│   └── README.md
│
└── README.md                         # This file

Prerequisites

System Requirements

OS: macOS, Linux, or Windows
Python: 3.10, 3.11, 3.12, or 3.13
Memory: Minimum 4GB RAM (8GB recommended)
Disk Space: 5GB for dependencies

API Keys Required

OpenAI API Key
- Get at: https://platform.openai.com/api-keys
- Cost: Pay-as-you-go (free tier available)
- Models: GPT-4, GPT-3.5-turbo
Serper API Key (for web search projects)
- Get at: https://serper.dev
- Cost: Free tier (100 searches/month), paid plans from $5/month
- Used by: Stock Researcher, Cricket Analysis

Setup Instructions

1. Initial Setup (One-time)

# Clone or navigate to the workspace
cd /Users/shinde/Desktop/Talbot/learning_crewai

# Create virtual environment (if not exists)
python3 -m venv venv

# Activate virtual environment
source venv/bin/activate

# Install dependencies
pip install -r requirements.txt
# Or install manually:
pip install crewai[tools]>=0.86.0 python-dotenv pypdf2 litellm

# Create .env file
cp .env.example .env
# Edit .env with your API keys
nano .env

2. For Each Session

# Activate virtual environment
cd /Users/shinde/Desktop/Talbot/learning_crewai
source venv/bin/activate

# Navigate to desired project
cd <project_name>

# Run the project
python main.py [arguments]

3. Configuration

Update the .env file in the workspace root:

# File: /Users/shinde/Desktop/Talbot/learning_crewai/.env

# OpenAI Configuration (Required)
OPENAI_API_KEY=sk-your_key_here
OPENAI_MODEL_NAME=gpt-4  # or gpt-3.5-turbo

# Serper Configuration (Required for Stock & Cricket projects)
SERPER_API_KEY=your_serper_key_here

# Logging Configuration (Optional)
LOG_LEVEL=INFO  # DEBUG, INFO, WARNING, ERROR
DEBUG_MODE=false

# Project Settings (Optional)
STOCK_SYMBOL=AAPL
CRICKETER_NAME=Virat Kohli
YEAR=2023

Architecture Overview

graph TB
    subgraph Workspace["Learning CrewAI Workspace"]
        subgraph Resources["Shared Resources"]
            ENV[.env Configuration]
            VENV[Python Virtual Environment]
            DOCS[Documentation Hub]
        end
        
        subgraph Projects["Multi-Agent Projects"]
            STOCK[Stock Researcher<br/>Financial Analysis]
            CRICKET[Cricket Analytics<br/>Sports Intelligence]
            BUDGET[Budget Knowledge<br/>Policy Analysis]
            WRITER[Research Writer<br/>Content Creation]
        end
        
        subgraph Framework["CrewAI Framework"]
            AGENTS[Specialized Agents]
            TASKS[Orchestrated Tasks]
            TOOLS[Integrated Tools]
        end
        
        subgraph External["External Services"]
            OPENAI[OpenAI GPT-4]
            SERPER[Serper Search API]
            DATA[Data Sources]
        end
    end
    
    ENV --> Projects
    VENV --> Projects
    DOCS --> Projects
    
    STOCK --> Framework
    CRICKET --> Framework
    BUDGET --> Framework
    WRITER --> Framework
    
    Framework --> External
    
    AGENTS -.-> TASKS
    TASKS -.-> TOOLS
    
    style Workspace fill:#f9f9f9,stroke:#333,stroke-width:2px
    style Resources fill:#e3f2fd,stroke:#1976d2,stroke-width:2px
    style Projects fill:#f3e5f5,stroke:#7b1fa2,stroke-width:2px
    style Framework fill:#fff3e0,stroke:#f57c00,stroke-width:2px
    style External fill:#e8f5e9,stroke:#388e3c,stroke-width:2px

System Flow

sequenceDiagram
    participant User
    participant Project
    participant CrewAI
    participant Agents
    participant LLM
    participant Tools
    
    User->>Project: Execute Command
    Project->>CrewAI: Initialize Crew
    CrewAI->>Agents: Assign Tasks
    
    loop Task Execution
        Agents->>LLM: Process Information
        LLM-->>Agents: Generate Response
        Agents->>Tools: Use External Tools
        Tools-->>Agents: Return Data
    end
    
    Agents->>CrewAI: Complete Tasks
    CrewAI->>Project: Aggregate Results
    Project->>User: Deliver Output

Features Across All Projects

Architecture	Configuration	Integration	Output
Multi-agent system	YAML-based	Real-time APIs	Professional reports
Specialized roles	Environment vars	OpenAI & Serper	Structured data
Task orchestration	Modular design	External tools	Rich formatting

Common Capabilities

Multi-agent architecture with specialized roles
YAML-based configuration for agents and tasks
Real-time API integration (OpenAI, Serper)
Comprehensive logging and error handling
Professional output formatting
Modular and extensible design
Environment-based configuration

Project-Specific Features

Project	Key Features
Stock Researcher	Real-time stock data, benchmark analysis, investment ratings
Cricket Analysis	Player statistics, format analysis, performance visualization
Budget Knowledge	PDF processing, policy analysis, interactive Q&A
Research Writer	Topic research, outline generation, content writing

Usage Examples

Stock Researcher

cd stock_researcher/src
python main.py "AAPL"      # Apple
python main.py "GOOGL"     # Google
python main.py "MSFT"      # Microsoft

Output: Investment recommendations, S&P 500 comparison, analysis files

Cricket Performance Analysis

cd cricketer_performance_analysis/src
python main.py "Virat Kohli" "2023"
python main.py "Babar Azam" "2022"
python main.py "Steve Smith" "2021"

Output: Performance statistics, visualizations, analysis reports

Union Budget Knowledge

cd union_budget_knowledge
PYTHONPATH=src python -c 'from union_budget_knowledge.main import kickoff; kickoff()'

Interactive Mode: Ask budget-related questions, get instant analysis

Research Writer Crew

cd research_writer_crew/src
python main.py

Interactive Mode: Enter topic, get comprehensive research and article

Customization Guide

Adding a New Project

Create project structure:

mkdir my_new_project
cd my_new_project
mkdir -p src/my_new_project/config

Create configuration files:

# agents.yaml
touch src/my_new_project/config/agents.yaml

# tasks.yaml
touch src/my_new_project/config/tasks.yaml

Create crew file:

touch src/my_new_project/crew_setup.py

Create main entry point:

touch src/my_new_project/main.py

Update root README to list the new project

Extending Existing Projects

Each project can be extended by:

Adding new agents in config/agents.yaml
Adding new tasks in config/tasks.yaml
Creating custom tools in the tools/ directory
Modifying crew orchestration in crew.py or crew_setup.py

Troubleshooting

Common Issues

"Virtual environment not activated"

source /Users/shinde/Desktop/Talbot/learning_crewai/venv/bin/activate

"ModuleNotFoundError"

# Reinstall dependencies
pip install crewai[tools] python-dotenv

"API Key not found"

# Verify .env file exists and contains keys
cat /Users/shinde/Desktop/Talbot/learning_crewai/.env
export OPENAI_API_KEY=your_key

"Disk space full"

# Free up space
rm -rf ~/.cache/pip
pip cache purge

Debug Mode

Enable detailed logging:

export LOG_LEVEL=DEBUG
export DEBUG_MODE=true
python main.py

Performance & Optimization

API Rate Limiting

OpenAI: Monitor at https://platform.openai.com/account/usage
Serper: Check quota at https://serper.dev/dashboard

Cost Optimization

Use GPT-3.5-turbo for cost savings
Cache agent responses when possible
Batch process queries

Execution Times

Simple queries: 2-5 seconds
Complex analysis: 10-30 seconds
Large document processing: 1-2 minutes

Security Best Practices

Never commit .env file
Rotate API keys regularly
Monitor API usage for unauthorized access
Use environment variables only, never hardcode keys
Keep dependencies updated

Contributing

Development Workflow

# Create feature branch
git checkout -b feature/new-feature

# Make changes
git add .

# Commit with descriptive message
git commit -m "feat: description of changes"

# Push to repository
git push origin feature/new-feature

Code Standards

Follow PEP 8 style guide
Add type hints to functions
Write comprehensive docstrings
Add error handling
Update README for user-facing changes

Monitoring & Metrics

What to Track

API usage and costs
Agent performance (response time, accuracy)
Error rates and failures
User query patterns

View Logs

# Recent logs
tail -f <project>/run_output.txt

# Search for errors
grep -i error <project>/run_output.txt

Support & Resources

CrewAI Docs: https://docs.crewai.com/
OpenAI API: https://platform.openai.com/docs/
Serper API: https://serper.dev/docs
Python Docs: https://docs.python.org/3/

Roadmap

Future Enhancements

License

This project collection is provided as-is for educational and commercial use.

Version History

Version	Date	Status
1.0.0	Dec 6, 2025	Production Ready
0.9.0	Dec 5, 2025	Beta
0.1.0	Dec 4, 2025	Alpha

Team & Contact

Maintained By: Shinde Vinayak Rao Patil Last Updated: December 6, 2025

Note: For project-specific documentation, refer to individual project READMEs linked above.

Name		Name	Last commit message	Last commit date
Latest commit History 10 Commits
cricketer_performance_analysis		cricketer_performance_analysis
docs		docs
research_writer_crew		research_writer_crew
stock_researcher		stock_researcher
union_budget_knowledge		union_budget_knowledge
.gitignore		.gitignore
README.md		README.md

Shindevrp/learning_crewai

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Learning CrewAI - Multi-Agent AI System Projects

Intelligent Multi-Agent Collaboration | Production-Ready Systems | Real-World Applications

Overview

Quick Start

1. Environment Setup

2. Run a Project

Projects

1. Stock Researcher

2. Cricket Performance Analysis

3. Union Budget Knowledge

4. Research Writer Crew

Shared Resources

Documentation

Virtual Environment

Environment Configuration

Project Structure

Prerequisites

System Requirements

API Keys Required

Setup Instructions

1. Initial Setup (One-time)

2. For Each Session

3. Configuration

Architecture Overview

System Flow

Features Across All Projects

Common Capabilities

Project-Specific Features

Usage Examples

Stock Researcher

Cricket Performance Analysis

Union Budget Knowledge

Research Writer Crew

Customization Guide

Adding a New Project

Extending Existing Projects

Troubleshooting

Common Issues

"Virtual environment not activated"

"ModuleNotFoundError"

"API Key not found"

"Disk space full"

Debug Mode

Performance & Optimization

API Rate Limiting

Cost Optimization

Execution Times

Security Best Practices

Contributing

Development Workflow

Code Standards

Monitoring & Metrics

What to Track

View Logs

Support & Resources

Roadmap

Future Enhancements

License

Version History

Team & Contact

About

Topics

Resources

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