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--- |
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license: apache-2.0 |
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title: My first agent with Langgraph |
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sdk: static |
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emoji: 🚀 |
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colorFrom: green |
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colorTo: yellow |
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app_file: Introduction_to_LangGraph_for_Agents_Assignment_Version.ipynb |
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--- |
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<p align = "center" draggable=”false” ><img src="https://github.com/AI-Maker-Space/LLM-Dev-101/assets/37101144/d1343317-fa2f-41e1-8af1-1dbb18399719" |
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width="200px" |
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height="auto"/> |
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</p> |
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## <h1 align="center" id="heading">Session 5: Our First Agent with LangGraph</h1> |
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| 🤓 Pre-work | 📰 Session Sheet | ⏺️ Recording | 🖼️ Slides | 👨💻 Repo | 📝 Homework | 📁 Feedback | |
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|:-----------------|:-----------------|:-----------------|:-----------------|:-----------------|:-----------------|:-----------------| |
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| [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) |
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In today's assignment, we'll be creating an Agentic LangChain RAG Application. |
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- 🤝 Breakout Room #1: |
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1. Install required libraries |
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2. Set Environment Variables |
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3. Creating our Tool Belt |
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4. Creating Our State |
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5. Creating and Compiling A Graph! |
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- 🤝 Breakout Room #2: |
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- Part 1: LangSmith Evaluator: |
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1. Creating an Evaluation Dataset |
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2. Adding Evaluators |
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- Part 2: |
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3. Adding Helpfulness Check and "Loop" Limits |
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4. LangGraph for the "Patterns" of GenAI |
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### Advanced Build |
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You are tasked to create an agent with 3 tools that can research a specific domain of your choice. |
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You must deploy the resultant agent with a Chainlit (or Custom) frontend. |
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## Homework |
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How Does the Model Determine Which Tool to Use? |
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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. |
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Is There a Limit to How Many Times We Can Cycle? |
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25 |
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How Are Correct Answers Associated with Questions? |
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If the answer contains the must mention keywords for a given question based on the list. |
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## Ship 🚢 |
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The completed notebook! |
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### Deliverables |
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- A short Loom of the notebook, and a 1min. walkthrough of the application in full |
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## Share 🚀 |
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Make a social media post about your final application! |
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### Deliverables |
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- Make a post on any social media platform about what you built! |
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Here's a template to get you started: |
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``` |
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🚀 Exciting News! 🚀 |
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I am thrilled to announce that I have just built and shipped an Agentic Retrieval Augmented Generation Application with LangChain! 🎉🤖 |
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🔍 Three Key Takeaways: |
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1️⃣ |
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2️⃣ |
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3️⃣ |
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Let's continue pushing the boundaries of what's possible in the world of AI and question-answering. Here's to many more innovations! 🚀 |
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Shout out to @AIMakerspace ! |
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#LangChain #QuestionAnswering #RetrievalAugmented #Innovation #AI #TechMilestone |
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Feel free to reach out if you're curious or would like to collaborate on similar projects! 🤝🔥 |
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``` |
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> #### NOTE: PLEASE SHUTDOWN YOUR INSTANCES WHEN YOU HAVE COMPLETED THE ASSIGNMENT TO PREVENT UNESSECARY CHARGES. |
