This project demonstrates the integration of LangFlow APIs into a Next.js application to interact with advanced language models. LangFlow is a platform that facilitates the execution of workflows involving Groq and Mistral AI-powered language models for tasks such as text generation, summarization, and classification. By integrating LangFlow into a Next.js app, this project provides a streamlined interface to interact with these workflows.
- Integration with LangFlow APIs for workflow execution.
- User-friendly interface for initiating sessions and processing requests.
- Supports customizable inputs and outputs for workflows.
- Easily extendable to include additional LangFlow workflows.
- Astra Daatastax DB:Database for storing vectorized data.
- Next.js: Framework for building React-based web applications.
- LangFlow API: Backend service for managing and executing AI workflows.
- Tailwind CSS: Styling framework for designing UI components.
- Node.js: Runtime for server-side functionality.
- Node.js (v14+)
- npm or Yarn
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Clone the repository:
git clone <repository_url> cd my-nextjs-app
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Install dependencies:
npm install # or yarn install -
Create a
.env.localfile in the root directory and add the following environment variables:NEXT_PUBLIC_LANGFLOW_API_URL=https://api.langflow.astra.datastax.com NEXT_PUBLIC_LANGFLOW_APP_TOKEN=<your_application_token>
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Start the development server:
npm run dev
Open http://localhost:3000 in your browser.
- Access the app at
http://localhost:3000. - Use the provided interface to input data and initiate workflows.
- View and analyze the outputs generated by the LangFlow workflow.
Contributions are welcome! If you encounter issues or have suggestions for improvements, please feel free to open an issue or submit a pull request.
Special thanks to the creators of LangFlow and Datastax Astra for providing robust tools for managing AI workflows.