---
license: apache-2.0
title: My first agent with Langgraph
sdk: static
emoji: 🚀
colorFrom: green
colorTo: yellow
app_file: Introduction_to_LangGraph_for_Agents_Assignment_Version.ipynb
---
<p align = "center" draggable=”false” ><img src="https://github.com/AI-Maker-Space/LLM-Dev-101/assets/37101144/d1343317-fa2f-41e1-8af1-1dbb18399719" 
     width="200px"
     height="auto"/>
</p>

## <h1 align="center" id="heading">Session 5: Our First Agent with LangGraph</h1>

| 🤓 Pre-work | 📰 Session Sheet | ⏺️ Recording     | 🖼️ Slides        | 👨‍💻 Repo         | 📝 Homework      | 📁 Feedback       |
|:-----------------|:-----------------|:-----------------|:-----------------|:-----------------|:-----------------|:-----------------|
| [Session 5: Pre-Work](https://www.notion.so/Session-5-Agents-with-LangGraph-1c8cd547af3d81068e44d4e4b901a9a8?pvs=4#1c8cd547af3d81578bedd1d2b11ab888)| [Session 5: Agents with LangGraph](https://www.notion.so/Session-5-Agents-with-LangGraph-1c8cd547af3d81068e44d4e4b901a9a8) | [Recording](https://us02web.zoom.us/rec/play/YvHRbOKYx8QDcTMwli7QjH-npGauB8wkk2gcN7ax7TV_oxQZbPRPdyxUebtH91uVQ8lRgCbP6u0iicmP.Vvroz4VC2XA7DILn?accessLevel=meeting&canPlayFromShare=true&from=my_recording&continueMode=true&componentName=rec-play&originRequestUrl=https%3A%2F%2Fus02web.zoom.us%2Frec%2Fshare%2F-fJk79tgwkAw3gJS0V69OeDvOUJ0EUE0qgOFey9-1uJPnL6oNT6vLmVygOWHl-JV.mYe1JWztYuHqsYWx)  (ck*A3y%t) | [Session 5: Agents](https://www.canva.com/design/DAGjaRyDT1Y/Sy7YaHwHOc19gomlhpq7hw/edit?utm_content=DAGjaRyDT1Y&utm_campaign=designshare&utm_medium=link2&utm_source=sharebutton)| You Are Here!| [Session 5 Assignment: Agents with LangGraph](https://forms.gle/bA9BN2bgNLMNB9HXA)| [AIE6 Feedback 4/15](https://forms.gle/Fgb5K4PDKokvtX787)


In today's assignment, we'll be creating an Agentic LangChain RAG Application.

- 🤝 Breakout Room #1:
  1. Install required libraries
  2. Set Environment Variables
  3. Creating our Tool Belt
  4. Creating Our State
  5. Creating and Compiling A Graph!
  
- 🤝 Breakout Room #2:
  - Part 1: LangSmith Evaluator:
    1. Creating an Evaluation Dataset
    2. Adding Evaluators
  - Part 2:
    3. Adding Helpfulness Check and "Loop" Limits
    4. LangGraph for the "Patterns" of GenAI

### Advanced Build

You are tasked to create an agent with 3 tools that can research a specific domain of your choice.

You must deploy the resultant agent with a Chainlit (or Custom) frontend.

## Homework
How Does the Model Determine Which Tool to Use?
Similar to any other model “decision” by generating tokens! Using the tools description + query the llm will make a decision if the user query could benefit from tool use.

Is There a Limit to How Many Times We Can Cycle?
25

How Are Correct Answers Associated with Questions?
If the answer contains the must mention keywords for a given question based on the list.

## Ship 🚢

The completed notebook!

### Deliverables

- A short Loom of the notebook, and a 1min. walkthrough of the application in full

## Share 🚀

Make a social media post about your final application!

### Deliverables

- Make a post on any social media platform about what you built!

Here's a template to get you started:

```
🚀 Exciting News! 🚀

I am thrilled to announce that I have just built and shipped an Agentic Retrieval Augmented Generation Application with LangChain! 🎉🤖

🔍 Three Key Takeaways:
1️⃣ 
2️⃣ 
3️⃣ 

Let's continue pushing the boundaries of what's possible in the world of AI and question-answering. Here's to many more innovations! 🚀
Shout out to @AIMakerspace !

#LangChain #QuestionAnswering #RetrievalAugmented #Innovation #AI #TechMilestone

Feel free to reach out if you're curious or would like to collaborate on similar projects! 🤝🔥
```

> #### NOTE: PLEASE SHUTDOWN YOUR INSTANCES WHEN YOU HAVE COMPLETED THE ASSIGNMENT TO PREVENT UNESSECARY CHARGES.