s4um1l/agent-tool-chainlit

Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

<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>

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

• —🤝 Breakout Room #1:
• —Install required libraries
• —Set Environment Variables
• —Creating our Tool Belt
• —Creating Our State
• —Creating and Compiling A Graph!

• —🤝 Breakout Room #2:
• —Part 1: LangSmith Evaluator:
• —Creating an Evaluation Dataset
• —Adding Evaluators
• —Part 2:
• —Adding Helpfulness Check and "Loop" Limits
• —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.

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.