feat: base tools script for LangGraph Gala agent

tools.py

@@ -1,56 +1,42 @@
-from smolagents import DuckDuckGoSearchTool
-from smolagents import Tool
 import random
-from huggingface_hub import list_models
-
-
-# Initialize the DuckDuckGo search tool
-#search_tool = DuckDuckGoSearchTool()
-
-
-class WeatherInfoTool(Tool):
-    name = "weather_info"
-    description = "Fetches dummy weather information for a given location."
-    inputs = {
-        "location": {
-            "type": "string",
-            "description": "The location to get weather information for."
-        }
-    }
-    output_type = "string"
-
-    def forward(self, location: str):
-        # Dummy weather data
-        weather_conditions = [
-            {"condition": "Rainy", "temp_c": 15},
-            {"condition": "Clear", "temp_c": 25},
-            {"condition": "Windy", "temp_c": 20}
-        ]
-        # Randomly select a weather condition
-        data = random.choice(weather_conditions)
-        return f"Weather in {location}: {data['condition']}, {data['temp_c']}°C"
-
-class HubStatsTool(Tool):
-    name = "hub_stats"
-    description = "Fetches the most downloaded model from a specific author on the Hugging Face Hub."
-    inputs = {
-        "author": {
-            "type": "string",
-            "description": "The username of the model author/organization to find models from."
-        }
-    }
-    output_type = "string"
-
-    def forward(self, author: str):
-        try:
-            # List models from the specified author, sorted by downloads
-            models = list(list_models(author=author, sort="downloads", direction=-1, limit=1))
-            
-            if models:
-                model = models[0]
-                return f"The most downloaded model by {author} is {model.id} with {model.downloads:,} downloads."
-            else:
-                return f"No models found for author {author}."
-        except Exception as e:
-            return f"Error fetching models for {author}: {str(e)}"
 
+from huggingface_hub import list_models
+from langchain.tools import Tool
+
+
+def get_weather_info(location: str) -> str:
+    weather_conditions = [
+        {"condition": "Rainy", "temp_c": 15},
+        {"condition": "Clear", "temp_c": 25},
+        {"condition": "Windy", "temp_c": 20}
+    ]
+    # Randomly select a weather condition
+    data = random.choice(weather_conditions)
+    return f"Weather in {location}: {data['condition']}, {data['temp_c']}°C"
+
+
+weather_info_tool = Tool(
+    name="weather_info",
+    func=get_weather_info,
+    description="Fetches dummy weather information for a given location."
+)
+
+def get_hub_stats(author: str) -> str:
+    try:
+        # List models from the specified author, sorted by downloads
+        models = list(list_models(author=author, sort="downloads", direction=-1, limit=1))
+
+        if models:
+            model = models[0]
+            return f"The most downloaded model by {author} is {model.id} with {model.downloads:,} downloads."
+        else:
+            return f"No models found for author {author}."
+    except Exception as e:
+        return f"Error fetching models for {author}: {str(e)}"
+
+
+hub_stats_tool = Tool(
+    name="hub_stats",
+    func=get_hub_stats,
+    description="Fetches the most downloaded model from a specific author on the Hugging Face Hub."
+)