Build a Conversational AI Backend with Python and Agora

Conversational AI is revolutionizing how people interact with artificial intelligence by enabling natural, real-time voice conversations between users and AI agents. Agora's Conversational AI Engine allows developers to connect their existing workflows to an Agora channel, facilitating real-time voice conversations without abandoning their current AI infrastructure. This guide builds a Python backend server using FastAPI and Uvicorn that handles the connection between users and Agora's Conversational AI Engine, powering voice-based AI conversations for applications. The server is configured with environment variables such as Agora app ID, customer secret, and LLM URL, which are set in a `.env` file. The server includes routes for inviting and removing agents from conversations, generating tokens, and handling health checks.

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