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Building an AI Agent That Can Use Tools: When LLMs meet IBM WXFlows Tools

Writer's picture: Steven BarrowSteven Barrow
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You know what's cooler than building an AI agent? Building one that can handle dad jokes without cringing. Today, I'm sharing my journey of creating a full-stack AI application that's more stacked than my programming books collection (which, let's be honest, is mostly being used as a monitor stand).


The Tech Stack: A Tower of Power

Remember when we thought jQuery was the future? Well, buckle up, because this stack makes jQuery look like a calculator app:

  • Next.js 15: Because sometimes, you need your React with a side of "I can't believe it's not a backend!"

  • Claude 3.5 Sonnet: The AI model that's better at completing your sentences than your spouse

  • LangChain & LangGraph: For when you want your AI to have more tools than Batman's utility belt

  • IBM's wxflows: Making API integration smoother than a jazz saxophone solo

  • Clerk: Handling auth like a bouncer who actually remembers faces

  • Convex: Real-time database that's faster than my consumption of Hu chocolate bars (Salty Dark y'all)


The Build: A Comedy of Errors (And Eventual Success)

Remember the time Elon Musk tried to rename Twitter to X? Well, this build process was slightly less chaotic, but equally ambitious. We're talking about implementing:

  • Prompt caching that's more efficient than my attempts at meal prepping

  • Real-time streaming that's smoother than ChatGPT's pickup lines

  • Tool orchestration that would make an orchestra conductor jealous

  • State management that's more reliable than your New Year's resolutions


Why This Matters

In a world where AI is everywhere (seriously, my toaster probably has GPT-4), building intelligent agents that can actually do useful stuff is crucial. This isn't just another chat interface – it's a sophisticated system that can:

  • Process data faster than my brain processes chocolate

  • Handle context better than a therapist

  • Manage tools more efficiently than my garage organization system


The Secret Sauce: Implementation Details

The real magic happens in the integration layer. We're using LangGraph's StateGraph like it's conducting traffic at a busy intersection – everything flows smoothly, even when chaos ensues. The tool orchestration system is so smart, it makes my smartphone look like a flip phone.

What makes this build special is the attention to real-world usage. The streaming solution works around LangChainAdapter limitations like a gymnast doing parkour – elegant, efficient, and slightly showing off.


Deployment: To Infinity and Beyond

Deploying to Vercel was smoother than explaining to my grandma why the cloud doesn't make it rain. With proper environment variable management and production-ready configurations, it's more secure than my partner's secret cookie stash.


Come check out the project! You can access it here at this link: https://aiagent.patronusenergy.com/


Conclusion: The Future is Now (And It's Pretty Funny)

Building this AI agent wasn't just about writing code – it was about creating something that could handle both serious tasks and dad jokes with equal proficiency. In a world where AI models are becoming as common as coffee shops, this project stands out like a rubber duck in a server room.

Remember: in the end, the best AI agent is the one that doesn't just pass the Turing test, but also laughs at your programming puns.

P.S. Why did the AI agent go to therapy? It had too many parent-child issues in its component tree! 🤖

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