Build Innovative LLM-Driven Applications with Next.js, Vercel, and Graphlit: A Comprehensive Guide
Building LLM-Driven Applications with Next.js, Vercel, and Graphlit
As I dive into the world of building applications powered by large language models (LLMs), I can't help but feel a tinge of excitement. The fusion of Next.js, Vercel, and Graphlit opens up a treasure trove of possibilities. With this combination, we can create applications that not only respond intelligently to user input but also do so seamlessly and efficiently. Today, I'm thrilled to share three sample applications that showcase the remarkable capabilities of Graphlit when integrated with Next.js and deployed on Vercel.
Getting Started with Graphlit
Before we jump into the applications, let’s take a moment to understand the essentials. Graphlit is a powerful platform that enables the integration of LLMs into your applications. With the Graphlit Node.js SDK, you can easily harness the capabilities of the Graphlit Platform API.
Here’s how you can get started with the SDK:
javascript
import { Graphlit } from 'graphlit-client';
From here, you can begin to craft your applications with the capabilities of LLMs at your fingertips.
Sample Applications
1. Chat Application
The first example I want to highlight is a chat application that mimics the conversational capabilities of ChatGPT. The chat application supports Retrieval Augmented Generation (RAG) conversations, allowing it to engage in meaningful dialogues based on ingested content.
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Clone the Repository:
bash git clone [email protected]:graphlit/graphlit-samples.git cd nextjs/chat
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Key Features:
- Upload files to your Graphlit project.
- Initiate a chat conversation by asking questions or summarizing the file contents.
This application is a splendid demonstration of how LLMs can enhance user interactions by providing context-rich responses.
2. Document Summarization Tool
Imagine a scenario where you need a quick summary of a lengthy document. The document summarization tool leverages the LLM capabilities to distill key points from uploaded files.
- Functionality:
- Users can upload PDF or text files.
- The application produces a concise summary, saving time and enhancing productivity.
3. Interactive Q&A Platform
This application elevates user engagement by allowing users to ask questions related to specific content. By integrating LLM-driven responses, it transforms static content into an interactive experience.
- User Experience:
- Users submit questions linked to uploaded files.
- The application replies with relevant answers derived from the content, making it an invaluable resource for researchers and students alike.
Deploying on Vercel
All these applications are deployable on Vercel with a single click! Each GitHub repository comes equipped with a Deploy button on the README page, making it straightforward to get your application live in no time.
Fun Facts about LLMs
Did you know?
- The first large language models were primarily focused on text generation, but they have now evolved to perform a myriad of tasks including translation, summarization, and even creative writing.
- LLMs can be fine-tuned on specific datasets, allowing them to adapt to particular domains or industries.
As we continue to explore the synergies of Next.js, Vercel, and Graphlit, I can’t help but envision a future where LLM-driven applications become ubiquitous in our daily lives. They are not just tools; they are companions that augment our capabilities and enhance our experiences. Whether you're a developer looking to innovate or a user eager to harness the power of AI, the time to dive into this exciting realm is now.
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