This project automates the process of researching and writing blog posts on technical topics using CrewAI, a framework for building collaborative AI agents. The agents work together to research and generate content on a given topic—in this case, "Agentic AI: A Progression of Language Model Usage" from youtube video.
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🤖 Multi-agent collaboration: Includes a blog_researcher and blog_writer working in sequence.
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📄 Task automation: Automatically performs research and writes a blog based on the given topic.
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🔁 Sequential processing: Tasks are executed in a defined order for coherent output.
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💾 Memory & caching: Improves response consistency and efficiency.
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📈 Rate limiting: Limits execution to 100 requests per minute for stability.
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🌐 Shareable crew: Crew configuration is reusable across tasks.
. ├── main.py # Entry point for kicking off the Crew ├── agents.py # Contains agent definitions: Researcher and Writer ├── tasks.py # Defines the research and writing tasks ├── .env # Environment variables (e.g., API keys) ├── README.md # Project overview
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Python 3.10+
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crewai
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python-dotenv
pip install crewai python-dotenv crewai-tools
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Add your environment variables to a .env file (e.g., OpenAI API key).
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Modify the topic by copying and pasting any youtube video link in crew.py or also writing channel name e.g @stanfordonline in the place of youtube tool call in tools.py.
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Run the script: python main.py
The script prints a complete, AI-generated blog post on the specified topic.
inputs={'topic': 'Agentic AI: A Progression of Language Model Usage'}
##📚 Inspired By
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CrewAI
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DeepLearning.AI - Building Agentic RAG with LlamaIndex
📌 License MIT License