Update app.py

app.py

@@ -1,45 +1,48 @@
 # app.py
-from smolagents import CodeAgent, DuckDuckGoSearchTool, load_tool, tool
-from smolagents.models import HuggingFaceLLM  # unified model class in latest versions
+from smolagents import CodeAgent, DuckDuckGoSearchTool, load_tool, tool, InferenceClientModel
 import datetime
+import requests
 import pytz
 import yaml
+from tools.final_answer import FinalAnswerTool
 
-# Weather-related imports
+# Weather-specific imports
 import openmeteo_requests
 import pandas as pd
 import requests_cache
 from retry_requests import retry
 
-from tools.final_answer import FinalAnswerTool
 from Gradio_UI import GradioUI
 
-
-# Example tool: fetch hourly temperature from Open-Meteo API
+# Example tool
 @tool
-def hourly_temperature(lat: float, lon: float) -> pd.Series:
-    """Fetch hourly temperature for given latitude and longitude."""
+def hourly_temperature(latitude: float, longitude: float) -> str:
+    """Fetch hourly temperature from Open-Meteo API.
+
+    Args:
+        latitude: Latitude of the location
+        longitude: Longitude of the location
+    """
     cache_session = requests_cache.CachedSession('.cache', expire_after=3600)
     retry_session = retry(cache_session, retries=5, backoff_factor=0.2)
-    client = openmeteo_requests.Client(session=retry_session)
+    openmeteo = openmeteo_requests.Client(session=retry_session)
 
     url = "https://api.open-meteo.com/v1/forecast"
     params = {
-        "latitude": lat,
-        "longitude": lon,
+        "latitude": latitude,
+        "longitude": longitude,
         "hourly": "temperature_2m",
     }
-    response = client.weather_api(url, params=params)
-    hourly_data = response.Hourly()
-    temp_series = hourly_data.Variables(0).ValuesAsNumpy()
-
-    return pd.Series(temp_series, name="temperature_2m")
+    response = openmeteo.weather_api(url, params=params)
+    hourly = response.Hourly()
+    hourly_temperature_2m = hourly.Variables(0).ValuesAsNumpy()
 
+    data = {"temperature_2m": hourly_temperature_2m}
+    return data["temperature_2m"]
 
-# Tool: get current time in timezone
 @tool
 def get_current_time_in_timezone(timezone: str) -> str:
-    """Return current time in the specified timezone."""
+    """Fetch current local time for a given timezone."""
     try:
         tz = pytz.timezone(timezone)
         local_time = datetime.datetime.now(tz).strftime("%Y-%m-%d %H:%M:%S")
@@ -51,43 +54,36 @@ def get_current_time_in_timezone(timezone: str) -> str:
 # Final answer tool
 final_answer = FinalAnswerTool()
 
-
-# HuggingFace LLM model
-model = HuggingFaceLLM(
-    max_tokens=2096,
+# Create model using latest smolagents class
+model = InferenceClientModel(
+    model_id="Qwen/Qwen2.5-Coder-32B-Instruct",
     temperature=0.5,
-    model_id='Qwen/Qwen2.5-Coder-32B-Instruct',  # can switch to another HF endpoint if overloaded
-    custom_role_conversions=None,
+    max_new_tokens=2048
 )
 
-
-# Load a remote tool from HuggingFace Hub
+# Load additional tool from Hub
 image_generation_tool = load_tool("agents-course/text-to-image", trust_remote_code=True)
 
-
 # Load prompt templates
-with open("prompts.yaml", "r") as stream:
+with open("prompts.yaml", 'r') as stream:
     prompt_templates = yaml.safe_load(stream)
 
-
-# Create the agent
+# Create agent
 agent = CodeAgent(
     model=model,
-    tools=[final_answer, hourly_temperature, get_current_time_in_timezone],
+    tools=[final_answer, hourly_temperature, get_current_time_in_timezone, image_generation_tool],
     max_steps=6,
     verbosity_level=1,
     grammar=None,
     planning_interval=None,
-    name=None,
-    description=None,
+    name="DormAI",
+    description="AI agent for dorm management",
     prompt_templates=prompt_templates
 )
 
-
-# Example calls (optional, can remove in prod)
+# Test the tools
 hourly_temperature(32.9, 15)
-get_current_time_in_timezone("Africa/Kigali")
-
+get_current_time_in_timezone('Africa/Kigali')
 
-# Launch the Gradio UI
+# Launch UI
 GradioUI(agent).launch()