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dating agent

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Basic Information

Dating Agent is a repository for a voice-enabled assistant built to interact with Locanto's dating section using natural language. The project bundles a Flask backend in Python and a Next.js frontend to provide voice and text interfaces that let users search profiles and listings, apply filters such as location and age, and engage in live communication. It integrates OpenAI for natural language processing, LiveKit for real-time communication, and is designed to be deployed on Azure with infrastructure defined via Bicep. The README includes installation steps for cloning the repo, installing Python and Node dependencies, configuration guidance via an azure-setup.md file, and commands to run the Flask server and Next.js development frontend. The repo aims to make matchmaking tasks more accessible by enabling voice commands and offering search and chat capabilities while being extensible through contributions and releases provided in the project.

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App URL
https://github.com/corrupt0303/dating-agent
Github Repository
https://github.com/corrupt0303/dating-agent/blob/main/README.md

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App Details

Features
The project emphasizes voice interaction allowing spoken queries to find matches and listings on Locanto. It supports text input as an alternative and provides search filters for narrowing results by parameters such as location and age. OpenAI integration is used to process natural language and improve conversational responses. LiveKit enables real-time chat or communication features for interactions with potential matches. The stack includes a Flask backend and a Next.js frontend for a user-friendly interface, and Playwright is listed for automated testing and browser interactions. Azure and Bicep are provided for hosting and infrastructure-as-code, and the README documents installation steps including pip and npm dependency installation plus commands to start the application locally.
Use Cases
This repository helps users interact with a dating platform using natural voice and text commands, which can speed up finding relevant profiles and make the experience more accessible. OpenAI integration aims to make queries and replies more conversational and context-aware. Live communication via LiveKit supports real-time conversations with matches, and search filters help refine results by common criteria like age and location. The combination of a Flask API and Next.js frontend allows running and testing locally, while Azure and Bicep provide a path to deploy at scale. Developers can extend the agent, contribute features, and run the provided automated tests to validate behavior. The project is positioned as a tool to enhance discovery and interaction on the Locanto dating section.

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