Update app.py

app.py

@@ -1,15 +1,10 @@
-from smolagents import CodeAgent,DuckDuckGoSearchTool, HfApiModel,load_tool,tool
-import datetime
-import requests
-import pytz
+import os
 import yaml
+import gradio as gr
+from smolagents import CodeAgent, DuckDuckGoSearchTool, HfApiModel, tool
 from tools.final_answer import FinalAnswerTool
 
-
-
-
-
-#new tool
+# 1. Define your custom tool
 @tool
 def get_daily_word() -> str:
     """A tool that returns a motivational word for English learners."""
@@ -17,65 +12,36 @@ def get_daily_word() -> str:
     words = ["Persistence", "Eloquence", "Clarity", "Resilience", "Impact"]
     return f"Today's word is: {random.choice(words)}"
 
-
-
 final_answer = FinalAnswerTool()
 
-# If the agent does not answer, the model is overloaded, please use another model or the following Hugging Face Endpoint that also contains qwen2.5 coder:
-# model_id='https://pflgm2locj2t89co.us-east-1.aws.endpoints.huggingface.cloud' 
-
+# 2. Setup the Model
 model = HfApiModel(
-max_tokens=2096,
-temperature=0.5,
-model_id='Qwen/Qwen2.5-Coder-32B-Instruct',# it is possible that this model may be overloaded
-custom_role_conversions=None,
+    model_id='Qwen/Qwen2.5-Coder-32B-Instruct',
+    token=os.getenv("HF_TOKEN")
 )
 
-
-
+# 3. Load prompts and initialize Agent
 with open("prompts.yaml", 'r') as stream:
     prompt_templates = yaml.safe_load(stream)
-    
+
 agent = CodeAgent(
     model=model,
-    tools=[final_answer,get_daily_word,DuckDuckGoSearchTool()], ## add your tools here (don't remove final answer)
+    tools=[final_answer, get_daily_word, DuckDuckGoSearchTool()],
     max_steps=6,
-    verbosity_level=1,
-    grammar=None,
-    planning_interval=None,
-    name=None,
-    description=None,
     prompt_templates=prompt_templates
 )
 
+# 4. Custom UI Logic (Safe for Gradio 6.0)
+def answer_task(message, history):
+    # This runs the agent and returns the string response
+    response = agent.run(message)
+    return response
 
-import gradio as gr
-
-def handle_query(query):
-    # This calls your agent and returns the generator/answer
-    yield agent.run(query)
-
-# Minimalist UI compatible with Gradio 4, 5, and 6
-with gr.Blocks() as demo:
-    gr.Markdown("# Agentic AI - Final Project")
-    chatbot = gr.Chatbot(label="Agent") # No 'type' argument = No crash
-    msg = gr.Textbox(label="Enter your task:")
-    clear = gr.Button("Clear")
-
-    def user(user_message, history):
-        return "", history + [[user_message, None]]
-
-    def bot(history):
-        # Access the last message sent by user
-        user_message = history[-1][0]
-        # Get response from your agent
-        bot_message = agent.run(user_message)
-        history[-1][1] = bot_message
-        yield history
-
-    msg.submit(user, [msg, chatbot], [msg, chatbot], queue=False).then(
-        bot, chatbot, chatbot
-    )
-    clear.click(lambda: None, None, chatbot, queue=False)
+demo = gr.ChatInterface(
+    fn=answer_task,
+    title="Hugging Face Agentic AI Project",
+    description="Ask me for a daily word or to search the web!"
+)
 
-demo.launch()
+if __name__ == "__main__":
+    demo.launch()