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LangGraph Agent Build | StateGraph + ToolNode + Groq LLM | 03/04 |
🧠 (03/04) This is the CORE video of the series. We build the actual AI Agent using LangGraph's StateGraph — connecting the LLM to tools with conditional routing.
By the end of this video, you'll understand exactly how an AI agent "thinks" — how it decides which tool to call, executes it, reads the result, and loops until it has an answer.
📌 What you'll learn:
• Setting up ChatGroq with LLaMA 3.1 8B Instant
• SQLDatabaseToolkit — auto-generated SQL tools
• Binding tools to the LLM (llm.bind_tools)
• Defining State with TypedDict and add_messages
• Building the Assistant Node (LLM reasoning)
• Building the Tools Node (ToolNode execution)
• Conditional edges — how the agent decides: tool or answer?
• Enforcing sequential tool calls (one at a time)
• Compiling the graph (builder.compile())
• Running the agent & reading state logs
• Full walkthrough: "What is revenue for SKU-6?"
📂 File covered:
• agent.py — The complete agent implementation
🔑 Key Concepts:
• StateGraph — a directed graph where state flows between nodes
• ToolNode — prebuilt node that executes tool calls
• tools_condition — routes to tools or END based on LLM output
• State accumulation — full message history enables multi-step reasoning
This is Part 3 of a 4-part series where we build a complete AI Agent with LangGraph + Groq + Streamlit.
🔗 Full Series:
▶️ Part 1: Theory (LangChain & LangGraph)
▶️ Part 2: Database, Tools & Prompt Setup
▶️ Part 3: Building the Agent (agent.py deep dive) — YOU ARE HERE
▶️ Part 4: Streamlit UI & Deploy on Replit
💻 Source Code: https://github.com/Suarj6133/Langchain_Langgraph_tutorial.git
⭐ Star the repo if this helps!
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
⏱️ TIMESTAMPS:
0:00 — Introduction — what makes this the "brain"
1:30 — Importing dependencies & architecture
6:31 — ChatGroq LLM setup (temperature=0 explained)
7:50 — SQLDatabaseToolkit — what tools it gives us
8:00 — Combining SQL tools + custom tools & giving LLM superpowers
9:30 — Defining State (TypedDict + add_messages)
10:20 — Assistant Node — the reasoning function
11:50 - State Graph sequential diagram
14:11 — Sequential Diagram -
15:30 - Adding nodes and edges
17:15 — add_edge & conditional_edge
18:15- Live demo — "What is revenue for SKU-6?"
━━━━━━━━━━━━━━━━━━━━━━━━━━━━
🔍 HASHTAGS:
#LangGraph #AIAgent #Python #StateGraph #Groq #LLaMA #LangChain #Tutorial #BuildAIAgent #ToolNode #MachineLearning #AgentPy #LLMAgent
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
Видео LangGraph Agent Build | StateGraph + ToolNode + Groq LLM | 03/04 | канала honest pm iimbangalore
By the end of this video, you'll understand exactly how an AI agent "thinks" — how it decides which tool to call, executes it, reads the result, and loops until it has an answer.
📌 What you'll learn:
• Setting up ChatGroq with LLaMA 3.1 8B Instant
• SQLDatabaseToolkit — auto-generated SQL tools
• Binding tools to the LLM (llm.bind_tools)
• Defining State with TypedDict and add_messages
• Building the Assistant Node (LLM reasoning)
• Building the Tools Node (ToolNode execution)
• Conditional edges — how the agent decides: tool or answer?
• Enforcing sequential tool calls (one at a time)
• Compiling the graph (builder.compile())
• Running the agent & reading state logs
• Full walkthrough: "What is revenue for SKU-6?"
📂 File covered:
• agent.py — The complete agent implementation
🔑 Key Concepts:
• StateGraph — a directed graph where state flows between nodes
• ToolNode — prebuilt node that executes tool calls
• tools_condition — routes to tools or END based on LLM output
• State accumulation — full message history enables multi-step reasoning
This is Part 3 of a 4-part series where we build a complete AI Agent with LangGraph + Groq + Streamlit.
🔗 Full Series:
▶️ Part 1: Theory (LangChain & LangGraph)
▶️ Part 2: Database, Tools & Prompt Setup
▶️ Part 3: Building the Agent (agent.py deep dive) — YOU ARE HERE
▶️ Part 4: Streamlit UI & Deploy on Replit
💻 Source Code: https://github.com/Suarj6133/Langchain_Langgraph_tutorial.git
⭐ Star the repo if this helps!
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
⏱️ TIMESTAMPS:
0:00 — Introduction — what makes this the "brain"
1:30 — Importing dependencies & architecture
6:31 — ChatGroq LLM setup (temperature=0 explained)
7:50 — SQLDatabaseToolkit — what tools it gives us
8:00 — Combining SQL tools + custom tools & giving LLM superpowers
9:30 — Defining State (TypedDict + add_messages)
10:20 — Assistant Node — the reasoning function
11:50 - State Graph sequential diagram
14:11 — Sequential Diagram -
15:30 - Adding nodes and edges
17:15 — add_edge & conditional_edge
18:15- Live demo — "What is revenue for SKU-6?"
━━━━━━━━━━━━━━━━━━━━━━━━━━━━
🔍 HASHTAGS:
#LangGraph #AIAgent #Python #StateGraph #Groq #LLaMA #LangChain #Tutorial #BuildAIAgent #ToolNode #MachineLearning #AgentPy #LLMAgent
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
Видео LangGraph Agent Build | StateGraph + ToolNode + Groq LLM | 03/04 | канала honest pm iimbangalore
langgraph agent tutorial langgraph stategraph build build ai agent python langchain groq tutorial langgraph toolnode langgraph conditional edges langgraph nodes and edges stategraph python langchain bind tools langgraph 2025 tutorial react agent python langgraph prebuilt tools tool routing ai agent langchain typescript messages add_messages langgraph ai agent step by step llm tool execution langgraph builder pattern agent.py tutorial
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11 июня 2026 г. 18:43:39
00:21:52
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