Watch how a Pro develops AI Agents in real-time

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AI Summary

Summary Outline

• Objective: Build AI agents using Crew AI with Agent Ops.
• Steps:
  1. Create Python file with explanations.
  2. Implement two functions:
     • crawl_web for website scraping.
     • summarize_text for summarizing web data.
  3. Import Agent Ops and initialize with agent_ops.init.
  4. Use fir_crawl for web scraping.
  5. Install necessary libraries (e.g., pip install fire_crawl).
  6. Set up request library to hit API and handle JSON data.
  7. Load environmental variables with load_env.
  8. Test crawl_web function with a URL.
  9. Store outputs of functions in variables.
  10. Add Agent Ops decorators to record functions.
  11. Use OpenAI for summarizing and creating table summaries.
  12. Track requests, costs, and latency with Agent Ops.
  13. Debug errors using Agent Ops dashboard.
  14. Integrate with Crew AI and other frameworks.
  15. Utilize Agent Ops for session tracking and cost management.
• Tools:
  • Agent Ops for tracking and debugging.
  • fir_crawl for easy web scraping.
  • OpenAI for language model interactions.
  • Python libraries for API requests and environmental management.
• Benefits:
  • Streamlined debugging with Agent Ops dashboard.
  • Cost and performance tracking for AI agents.
  • Easy integration with popular AI frameworks.
  • Support for benchmarking and compliance.
• Support:
  • Active Discord community for troubleshooting and support.