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This template is designed to help you set up a multi-agent AI system with ease, leveraging the powerful and flexible framework provided by crewAI. Our goal is to enable your agents to collaborate effectively on complex tasks, maximizing their collective intelligence and capabilities.\n# Spoonflower Sales Analyzer: Project Analysis Report\nOverview\nThe Spoonflower Sales Analyzer is an autonomous multi-agent system built with CrewAI and Python to streamline the exploratory data analysis (EDA) of digital marketplace transactions. By leveraging collaborative AI agents, the pipeline automates the extraction of statistical insights, identifies sales trends and anomalies, and translates raw operational data into structured business reports.\n\n# 🤖 Multi-Agent Architecture\nThe system utilizes two specialized agents working in tandem:\n\n## Senior Data Analyst:\nParses the dataset, executes Python-based data cleaning and validation, and uncovers underlying patterns, top-performing product trends, and performance metrics.\n\n## Professional Data Report Writer: \nSynthesizes the quantitative findings from the data analyst and converts them into clear, actionable executive summaries and business reports.\n\n# 📊 Key Analytical Capabilities\nAutomated Data Processing: Inspects and parses CSV order exports securely using custom Python tools.\n\nTrend & Pattern Recognition: Identifies top-selling surface patterns, peak sales periods, and customer buying behaviors.\n\nStructured Reporting: Automatically formats findings into clean, readable Markdown reports suitable for business review and strategic planning.\n\n## Installation\n\nEnsure you have Python >=3.10 <3.14 installed on your system. This project uses [UV](https://docs.astral.sh/uv/) for dependency management and package handling, offering a seamless setup and execution experience.\n\nFirst, if you haven't already, install uv:\n\n```bash\npip install uv\n```\n\nNext, navigate to your project directory and install the dependencies:\n\n(Optional) Lock the dependencies and install them by using the CLI command:\n```bash\ncrewai install\n```\n### Customizing\n\n**Add your `OPENAI_API_KEY` into the `.env` file**\n\n- Modify `src/spoonflower_sales_analyzer/config/agents.yaml` to define your agents\n- Modify `src/spoonflower_sales_analyzer/config/tasks.yaml` to define your tasks\n- Modify `src/spoonflower_sales_analyzer/crew.py` to add your own logic, tools and specific args\n- Modify `src/spoonflower_sales_analyzer/main.py` to add custom inputs for your agents and tasks\n\n## Running the Project\n\nTo kickstart your crew of AI agents and begin task execution, run this from the root folder of your project:\n\n```bash\n$ crewai run\n```\n\nThis command initializes the spoonflower-sales-analyzer Crew, assembling the agents and assigning them tasks as defined in your configuration.\n\nThis example, unmodified, will run the create a `report.md` file with the output of a research on LLMs in the root folder.\n\n## Understanding Your Crew\n\nThe spoonflower-sales-analyzer Crew is composed of multiple AI agents, each with unique roles, goals, and tools. 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