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Voice-Enabled WebRTC and LangGraph

Presenter

Karim Lalani is a local LLM and voice integration expert at Infinidigm LLC, specializing in Ollama implementations and WebRTC technologies. Based in Leander, TX, he has pioneered several innovative voice chat implementations and local LLM deployment strategies for the Austin LangChain community.

Connect with Karim:

Lab Overview

Learn how to implement voice-enabled WebRTC capabilities with LangGraph, creating real-time communication systems with AI integration.

Key Topics

  • WebRTC implementation
  • Voice control integration
  • LangGraph evolution
  • Real-time communication
  • Graph structure design

Features

  • Voice-enabled agents
  • Real-time interaction
  • Graph-based workflows
  • State management
  • Performance optimization

Technical Components

  • WebRTC setup
  • Voice processing
  • LangGraph configuration
  • State management
  • Response generation

Implementation Steps

  1. WebRTC configuration
  2. Voice integration
  3. LangGraph setup
  4. State management
  5. Performance tuning
  6. Testing and validation

Best Practices

  • Real-time processing
  • Voice handling
  • Graph optimization
  • Error management
  • Performance tuning

Use Cases

  • Voice assistants
  • Real-time communication
  • Interactive agents
  • Multi-modal systems
  • Collaborative tools

Prerequisites

  • Basic understanding of:
    • WebRTC
    • Voice processing
    • LangGraph
    • Python programming
  • Development environment setup

Resources