Update README.md

README.md

@@ -1,10 +1,10 @@
 ---
-title: Template Final Assignment
+title: Final Assignment
 emoji: 🕵🏻‍♂️
 colorFrom: indigo
 colorTo: indigo
 sdk: gradio
-sdk_version: 5.25.2
+sdk_version: 5.29.0
 app_file: app.py
 pinned: false
 hf_oauth: true
@@ -22,5 +22,22 @@ license: mit
   <p align="center" style="width:50%">
     Final hands-on assignment for the Hugging Face Agents course. In this project I built a multi-agent solution, evaluated it against questions from the General AI Assistants (GAIA) benchmark (level one only), and got creative with some agent and tool improvements. 
 </div>
+## About The Project
+
+![[HF Space Screen Shot][images/submit_answers.jpg]](https://huggingface.co/spaces/civerson916/Final_Assignment_Template)
+
+Achieving 30 points for the certification was relatively easy with the template provided and a powerful enough LLM. However, evaluation revealed the unique types of implementation challenges with AI agents. Some of which include...
+
+* Cost
+* Response Times
+* Reliability
+
+Beyond what looks like a smolagents guided tour, you can find the following in this repo... 
+
+* Research agent armed with Google search via [Serper](https://serper.dev/) and both Audo and Video Understanding via [Gemini] (https://ai.google.dev/gemini-api/docs/)video-understanding#python)
+* Chess agent leveraging my [board_to_fen](https://github.com/civerson/board_to_fen) fork and a Stockfish API.
+* [Langfuse](https://langfuse.com/) setup boilerplate, a working example. This is an absolute must.
+* [Pydantic](https://docs.pydantic.dev/latest/) settings for type safety, centralized, and encapsulated config.
+* Basic parallel agent task execution, compatible with [Gradio](https://www.gradio.app/), no extra abstractions.
 
 Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference