Update app.py

app.py

@@ -8,6 +8,7 @@ from datasets import Dataset, DatasetDict, load_dataset
 import difflib
 import openai
 from langchain_community.utilities.wikipedia import WikipediaAPIWrapper
+import gradio as gr
 
 REPO_ID_TECHSPARK_STAFF = "aslan-ng/CMU_TechSpark_Staff"
 REPO_ID_TECHSPARK_COURSES = "aslan-ng/CMU_TechSpark_Courses"
@@ -732,4 +733,38 @@ agent = smolagents.CodeAgent(
     add_base_tools=False,
     max_steps=10,
     verbosity_level=2,  # show steps in logs for class demo
-)
+)
+
+with gr.Blocks(title="TechSpark Agent") as demo:
+    gr.Markdown("## Beam Agent — Custom Tool Selection (smolagents)")
+    chat = gr.Chatbot(height=420)
+    inp = gr.Textbox(placeholder="Ask your question in natural language.", label="Your question")
+
+    # No gr.State for agent — just close over `agent`
+    def respond(message, history):
+        try:
+            # 1. Use agent.chat() to maintain internal history
+            out = str(agent.run(message))
+        except Exception as e:
+            out = f"[Error] {e}"
+
+        # This just updates the Gradio UI history
+        history = (history or []) + [(message, out)]
+        return "", history
+
+    gr.Examples(
+        examples=[
+            "Who is Ed?",
+            "Who to talk to to create a wooden table?",
+            "Can I use laser cutters?",
+            "Where is welding space?"
+        ],
+        inputs=[inp],
+        outputs=[inp, chat],
+        fn=respond,
+        cache_examples=False, # Set to False for dynamic content or to avoid caching issues
+    )
+
+    inp.submit(respond, [inp, chat], [inp, chat])
+
+demo.launch(share=True)