How to Build an Advanced AI Agent with Search (LangGraph, Python, Bright Data & More)
Unlock all features
FREE: Get instant access to 10 AI summaries, chats, or transcripts per day.
Unlock all features
FREE: Get instant access to 10 AI summaries, chats, or transcripts per day.
Unlock all features
FREE: Get instant access to 10 AI summaries, chats, or transcripts per day.
Unlock all features
FREE: Get instant access to 10 AI summaries, chats, or transcripts per day.
Unlock all features
FREE: Get instant access to 10 AI summaries, chats, or transcripts per day.
Related videos
How to learn Python coding fast - Step by step roadmap
Tech With Tim
31.7k views
Build & Deploy a Python AI Agent in 20 Minutes
Tech With Tim
38.6k views
Build a Python AI Agent in 10 Minutes
Tech With Tim
84.2k views
How to Write Production Python Code
Tech With Tim
63.1k views
How I Would Learn Python Web Development If I Started Over
Tech With Tim
42.1k views
How to Build AI Agents in Python
Tech With Tim
46.7k views
How to Build a Production-Ready RAG AI Agent in Python (Step-by-Step)
Tech With Tim
77.8k views
Coding is Changing… The Most Advanced AI Tool Yet
Tech With Tim
1.4m views
The Fastest Way to Build AI Agents With Your Data (MindsDB Walkthrough)
Tech With Tim
45.3k views
Build ANYTHING With an Advanced MCP Server (Python, Authentication, Databases & More)
Tech With Tim
70.5k views
Top Comments (10)
Can we get an updated ADVANCED Livekit voice agents detailed tutorial please
I learned a lot from studying the code of that advanced AI agent you created awhile go.
Excellent video 👍
As an absolute n00b, can you do a video showing the differences btwn langgraph and n8n. Seems the nodes and vertices are interchanged?
Thanks for this fantastic deep dive. The LangGraph architecture is brilliant for multi-agent systems. I especially appreciate you highlighting the use of Pydantic for structured output. That's a crucial practice for building truly reliable and scalable agents. This is a great example of how to build robust, production-ready AI.
Thanks Tim, great tutorial
Thanks tim and ask god to guide you. The most important thing I got... how langraph structured ? how we can force the llms format by pydantic ? , how can we handle the api inputs and outputs generally and espcially for Bright Data, how the general project structured and cleaned.. I've got a lot of benefits. I've tried to do and I will apply for other projects' ideas. Thanks again..
This is great. thank you for this
Amazing tutorial thanks
Tim, thx a bunch for the amazing tut. Btw, I guess you meant LangGraph, not LangFlow in the description😊
Unlock the Data Inside
Turn Videos into Knowledge
- Get FREE 10/day: transcripts, summaries, chats
- Chat with videos, export text & PDF
- $1 free API credit for RAG, chatbots & research
Free forever plan • All features unlocked
Top Comments (10)
Can we get an updated ADVANCED Livekit voice agents detailed tutorial please
I learned a lot from studying the code of that advanced AI agent you created awhile go.
Excellent video 👍
As an absolute n00b, can you do a video showing the differences btwn langgraph and n8n. Seems the nodes and vertices are interchanged?
Thanks for this fantastic deep dive. The LangGraph architecture is brilliant for multi-agent systems. I especially appreciate you highlighting the use of Pydantic for structured output. That's a crucial practice for building truly reliable and scalable agents. This is a great example of how to build robust, production-ready AI.
Thanks Tim, great tutorial
Thanks tim and ask god to guide you. The most important thing I got... how langraph structured ? how we can force the llms format by pydantic ? , how can we handle the api inputs and outputs generally and espcially for Bright Data, how the general project structured and cleaned.. I've got a lot of benefits. I've tried to do and I will apply for other projects' ideas. Thanks again..
This is great. thank you for this
Amazing tutorial thanks
Tim, thx a bunch for the amazing tut. Btw, I guess you meant LangGraph, not LangFlow in the description😊