Create app.py

app.py

@@ -0,0 +1,59 @@
+import json
+import gradio as gr
+from interpreter import interpreter
+import os
+import time
+import matplotlib
+matplotlib.use('Agg') 
+
+interpreter.auto_run = True
+interpreter.llm.model = "gpt-4-turbo"
+interpreter.custom_instructions = "First ask the user what they want to do. Based on the input, describe the next steps. If user agrees, proceed; if not, ask what they want next.If it is anything to display , always at the end open up the file."
+
+def update_bot(text, chatbot):
+    response = interpreter.chat(text,stream=True, display=False)
+    response = json_to_markdown(response)
+    chatbot.append((text, response))
+    return chatbot, ""
+
+def new_chat():
+    interpreter.messages = []
+    return [], ""
+def create_chat_widget():
+    with gr.Blocks() as chatblock:
+        chatbot = gr.Chatbot(
+            [],
+            elem_id="chatbot",
+            elem_classes="chatbot",
+            layout="llm",
+            bubble_full_width=False,
+            height=600,
+        )
+        txt = gr.Textbox(
+            scale=4,
+            show_label=False,
+            placeholder="Enter text and press enter to chat with the bot.",
+            container=False,
+        )
+        new_chat_button = gr.Button(
+            "New Chat",
+            scale=3,
+            interactive=True,
+        )
+        new_chat_button.click(new_chat, [], [chatbot, txt])
+
+        txt.submit(update_bot, [txt, chatbot], [chatbot, txt])
+
+        return chatblock
+
+def json_to_markdown(json_data):
+    return "\n\n".join(
+        f"**{item['role'].capitalize()}:** \n{item['content']}" if item['type'] == 'message' else
+        f"```{item['format']}\n{item['content']}\n```" if item['type'] == 'code' else
+        f"```\n{item['content']}\n```" for item in json_data if item['role'] != 'user'
+    )
+
+with gr.Blocks() as demo:
+    with gr.Tab("HEXON Chatbot Assignment"):
+        chat_interface = create_chat_widget()
+demo.launch()