The Future of AI: Transcribing Conversations Instantly

Unlock the full potential of AI with this comprehensive AutoGen tutorial! Discover how to build and orchestrate intelligent, multi-agent systems that can perform complex tasks and interact seamlessly with humans and external tools.
⚙️ Resources:
🔗 AutoGen: microsoft.gith...
🔗 AgentOps: www.agentops.ai/
🔗 WhisperAPI: openai.com/ind...
🔗 AssemblyAI: www.assemblyai...
In this in-depth guide, we'll explore Microsoft's AutoGen framework, a game-changer in artificial intelligence and large language models (LLMs). Whether you're a seasoned AI developer or just starting your journey, this tutorial will equip you with the skills to harness the full potential of conversational AI agents.
What You'll Learn:
AutoGen Fundamentals:
- What are AI agents and multi-agent systems, and why are they revolutionizing the AI landscape?
- Introduction to AutoGen, its core concepts, and its benefits for AI development
- Understanding Conversable Agents, their roles, and their capabilities
Conversation Programming:
- Orchestrating interactions between multiple agents using natural language or code
- Controlling conversation flow with human_input_mode and max_consecutive_auto_reply
- Defining custom termination conditions for conversations
Building Custom Tools:
- Empowering your agents with specialized tools for calculations, data retrieval, and more
- Understanding tool registration and how agents interact with them
Practical Examples:
- Creating a simple "chef" and "nutritionist" agent interaction to illustrate core concepts
- Building a multi-agent transcription comparison system using WhisperAPI and AssemblyAI
- Showcasing how agents collaborate to solve complex tasks
Monitoring with AgentOps:
- Integrating AgentOps for real-time monitoring and analytics
- Gaining insights into agent performance, identifying potential issues, and optimizing your multi-agent systems
Who Should Watch:
- AI enthusiasts and developers eager to build intelligent, multi-agent systems
- Anyone interested in exploring the capabilities of AutoGen and conversational AI
- Professionals seeking to automate complex tasks and streamline workflows with AI
- Students and researchers looking to expand their knowledge of AI technology
Why This Matters:
AutoGen empowers you to create adaptable, scalable, and interactive AI applications. From simple chatbots to sophisticated multi-agent systems, AutoGen provides the tools and flexibility you need to unlock AI's full potential.
Multi-agent systems are revolutionizing our interactions with AI, enabling more complex and sophisticated applications. AutoGen makes building and managing these systems more straightforward than ever, opening up a world of possibilities for innovation and problem-solving.
Ready to embark on your AutoGen journey? Hit the play button and start building intelligent agents today!
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/ @atefataya
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TIMESTAMPS:
00:06 Introduction
01:20 Introduction
02:15 Why is AutoGen a game-changer?
03:34 Conversable Agents
04:30 Conversable Agents Demo
09:29 Conversation Programming
10:16 Roles & Conversation
12:40 Max Consecutive Auto Reply
13:55 Is Termination Msg
15:20 Multi-Agent System (WhisperAPI Agent)
18:12 AssemblyAI Agent
20:53 Transcription Comparison Agent
26:01 Monitoring Agents Using AgentOps
28:01 Final Thoughts
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⚙️ Github Project for you to follow along in this tutorial:
1. Jupyter Notebook for you to follow along:
🔗 tinyurl.com/2j...
⚙️ Related KZbin Tutorials:
1. Whisper API: The Future of Speech Recognition
🔗 tinyurl.com/2s...
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⚡️ Social Media:
🔗 Twitter: x.com/atef_ataya
🔗 Github: github.com/ate...
🔗 Medium: / atef.ataya
⚙️ Links:
🔗 AutoGen: microsoft.gith...
🔗 AgentOps: www.agentops.ai/
🔗 WhisperAPI: openai.com/ind...
🔗 AssemblyAI: www.assemblyai...
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#chatgpt #langchain #aitutorial #aiprogramming #machinelearning #nlp #naturallanguageprocessing #deeplearning

[@atefataya]

👋Let's connect! 🚀Excited about the potential of AutoGen? What kind of multi-agent systems would YOU like to build? 👇 Share your ideas in the comments! #AutoGen #AIagents #AIinnovation #AIcommunity

[@iPhotoGear]

Great tutorial thanks , I am just curious how autogen is compared to other frameworks like Langchain in building multi-agent system?

[@atefataya]

Thanks for your comment. AutoGen is the best for building complex multi steps with multiple agents system. LangChain is great for chaining LLMs calls. In addition to that , AutoGen allows for dynamic and complex interaction, built-in code execution, human interactions, and customization.

[@Claude-s1t]

transcribethis AI fixes this. Transcribing conversations instantly using AI.

[@MohdUAE-o5b]

What are the security implications of using multiple AI agents that can execute code? How it is handled using AutoGen when connecting to external tools or API

[@atefataya]

That's a great question, AutoGen has several features to address security concerns such as code execution in an isolated environments like docker, containers to prevent malicious code. Also there is Human Oversight (human-in-the-loop) configuration and you can restrict file system access or network calls for the operations agents as well