Perplexity-Lite
Build Your Own Perplexity Lite Using LangGraph, GPT-4, and Tavily AI
Description:
- Delve into the fascinating world of creating search or discovery applications using cutting-edge tools.
- Unlocking Knowledge
By combining these powerful tools, I’ve successfully created an application similar to Perplexity AI. This application excels at unlocking knowledge through information discovery and sharing.
Key Features:
- Real-time Chat: Engage in dynamic conversations with other users.
- Multi-Actor Architecture: Understand how LangGraph manages actors and their interactions.
- GPT-4 Integration: Leverage GPT-4 for natural language understanding and generation.
- Tavily AI Insights: Explore rapid insights and comprehensive research capabilities.
Requirements:
- LangGraph, a library designed for building stateful, multi-actor applications. LangGraph, built on LangChain, allows for the coordination of multiple 'actors' in a cyclical computation process. This is particularly useful for adding cycles to your LLM applications, extending beyond the capabilities of a traditional DAG framework.
- Tavily AI, an incredible tool for rapid insights and comprehensive research. Tavily AI streamlines the research process, from source gathering to organizing results, making it an invaluable asset for developers.
- GPT-4, a large language model that's pivotal in the development of advanced AI applications.
- Application development with advanced AI technologies: By combining these tools, I've managed to create an application similar to Perplexity AI, known for its ability to unlock knowledge through information discovery and sharing.
Implementation Guide:
Link ▶️
©️ License ?
Distributed under the MIT License. See LICENSE for more information.
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