Скачать или смотреть AI Voice Agent — Real-Time Conversational Assistant

Overview:-
A fully deployed, real-time AI voice assistant built as part of the 30 Days of AI Voice Agents challenge.
The system supports natural voice conversations, contextual responses, live web actions, and cloud-scale deployment — going far beyond a prototype into a production-ready AI system.
This project focuses on real-time audio processing, LLM orchestration, and end-to-end system design, covering everything from microphone input to cloud deployment.

Github Repo:-
https://github.com/KOLLIJAYANTHESWAR/30-Da...

Key Capabilities:-
Real-Time Voice Conversations:-
End-to-end pipeline: Speech-to-Text → LLM → Text-to-Speech with low latency.

Persona-Aware & Contextual Responses:-
Maintains conversation context and adapts tone/personality dynamically.

Live Web Search & Intelligent Summaries:-
Fetches real-time information and presents concise, user-friendly responses.

Weather Intelligence:-
Provides weather forecasts with actionable suggestions instead of raw data.

Voice-Driven Actions:-
Opens websites and triggers live actions based on user intent.

Interactive UI Experience:-
Smart record button, voice visualizer, and responsive UI for a smooth user experience.

User-Controlled API Keys:-
Allows users to plug in their own API keys for flexibility and security.

Cloud-Deployed & Production-Ready:
Fully deployed with proper static file handling and backend stability.

Engineering Challenges & Solutions:

Real-Time Audio Synchronization:
Solved streaming audio glitches by fixing WAV headers and implementing intelligent buffering.

Dynamic Tool Invocation:
Designed a secure intent-parsing system that lets the LLM trigger live actions like web search and site navigation.

Cloud Deployment Debugging:
Resolved real-world deployment issues such as missing static assets and environment mismatches during Render deployment.

Tech Stack:-
Frontend: React
Backend: FastAPI
AI & Voice: STT, LLM orchestration, TTS
UI: Real-time visualizer & interaction controls

Deployment: Cloud (Render):-
APIs: Web search, weather services, AI providers

What This Project Demonstrates:-
Real-time systems engineering
AI agent orchestration & intent handling
Cloud deployment & debugging under real constraints
Strong focus on user experience, not just AI accuracy