Updated the README and added the README to the app for viewing

.gitignore

@@ -1,5 +1,5 @@
 # Python-generated files
-__pycache__/
+*__pycache__/
 *.py[oc]
 build/
 dist/
@@ -24,3 +24,4 @@ htmlcov/
 .ruff_cache
 assets
 static
+.gradio

README.md

@@ -57,6 +57,10 @@ Once executed the whole process is summarised and returned to the user.
 Here is a link to the video demonstration [MCP Demo Shallow Research Code Assistant](https://www.loom.com/share/ea4584bc76c04adabefd6d39a4f8e279?sid=5d2408ff-03d1-421b-b956-9713ae390212)
 ---
 
+---
+<div style="position: relative; padding-bottom: 56.25%; height: 0;"><iframe src="https://www.loom.com/embed/ea4584bc76c04adabefd6d39a4f8e279?sid=12c1b246-5dcc-49ec-8ca0-1a45710f4e3e" frameborder="0" webkitallowfullscreen mozallowfullscreen allowfullscreen style="position: absolute; top: 0; left: 0; width: 100%; height: 100%;"></iframe></div>
+---
+
 ## Key information
 
 I've found that whilst using VS Code for the MCP interaction, its useful to type the main agent function name to ensure the right tool is picked.

app.py

@@ -2149,6 +2149,10 @@ CUSTOM_CSS = """
 }
 """
 
+# read the README.md file and convert it to a variable
+with open("README.md", encoding="utf-8") as f:
+    readme_content = f.read()
+
 
 with gr.Blocks(title="Shallow Research Code Assistant Hub", 
                theme=gr.themes.Ocean(),
@@ -2196,6 +2200,10 @@ with gr.Blocks(title="Shallow Research Code Assistant Hub",
         <h3>Agents And Flows:</h3>
         """
     )
+    with gr.Tab("README", scale=1):
+        gr.Markdown(
+            f"""{readme_content[393:]}
+            """)
     
     with gr.Tab("Orchestrator Flow", scale=1):
         gr.Markdown("## AI Research & Code Assistant")
@@ -2396,7 +2404,7 @@ if __name__ == "__main__":
         exit(0)
     
     signal.signal(signal.SIGINT, signal_handler)
-    signal.signal(signal.SIGTERM, signal_handler)
+    signal.signal(signal.SIGTERM, signal_handler) 
     
     try:
         hub.launch(