Build Smarter AI Apps with This LangGraph + Vercel AI SDK Starter Template 🚀

For the past few weeks, I’ve been exploring how to build more sophisticated AI applications – not just chatbots, but actual agents that can reason, search the web, interact with APIs, and deliver useful outcomes.

I wanted a starter project that could bring together the power of the Vercel AI SDK, the flexibility of LangGraph (via LangChain), and the usability of a modern React frontend, all with built-in support for real-time web search using SerpAPI.

To my surprise, there wasn’t a good one out there.

So, I decided to build it myself.

👉 GitHub Repo

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🧠 What This Project Solves

Most AI starter kits are either too simple or too fragmented – they might show you how to call an OpenAI model, or how to use LangChain chains, or how to build a React UI... but not all of it working together in a coherent, extendable structure.

This project aims to bridge that gap and give developers a solid foundation to build truly intelligent applications.

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🔧 Tech Stack

Here’s what’s under the hood:

1. Vercel AI SDK

Makes it easier to stream responses from LLMs with built-in support for OpenAI, Anthropic, and others. No need to handle SSE manually.

2. LangChain + LangGraph

Used to create structured, multi-step flows that let the AI reason, take actions, and return meaningful outputs – not just one-shot completions.

LangGraph brings agent workflows to life through a graph-based architecture, which is perfect for branching logic and tool use.

3. React Frontend

A clean and responsive interface to interact with your AI agents. Uses useStream from the Vercel SDK for real-time UX.

4. SerpAPI

Brings live, contextual web search into your LangGraph agents. Your AI can now look things up before answering, and soon – cite sources too.

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⚡ Why This Project Matters

If you’re building:

• AI copilots

• Research agents

• Knowledge assistants

• Workflow automation bots

...then starting with a strong, integrated foundation saves weeks of effort and gets you building features faster.

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📌 What’s Next?

This is just the beginning. Here’s what I’m planning to add next:

1. Source Attribution
   Show which web links or sources were used to generate the answer – transparency matters.

2. Composio Integration
   Enable the agent to take action across multiple tools and APIs (e.g., Notion, Gmail, Google Calendar) with just one setup.

3. Complex LangGraph Architectures
   Think beyond simple tool calls — build real multi-step agents with memory, conditional flows, and fallback strategies.

4. Mem0 for Memory
   Persistent, contextual memory for users, allowing the agent to retain information across sessions and be truly helpful over time.

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🤝 Contribute or Fork

This project is open-source and built to be extended. Whether you want to build your own custom AI product or contribute back, I’d love your feedback and ideas.

Check out the code and get started here:
👉 https://github.com/Sirsho29/dia-langchain

If you find it useful, give it a star 🌟 and feel free to share what you build!

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💬 Let’s Connect

If you’re working on AI apps, agents, or just interested in the future of intelligent tooling – let’s talk!
I’d love to learn from others building in this space.

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#LangChain #LangGraph #VercelAI #ReactJS #SerpAPI #AIagents #LLMs #OpenSource #Hackernotes #AItools