Add hf hub stats and weather info tools

app.py

@@ -2,6 +2,7 @@ import gradio as gr
 import os
 from smolagents import CodeAgent, HfApiModel, LiteLLMModel
 from retriever import load_guest_dataset
+from tools import *
 
 is_running_on_space = os.environ.get('SPACE_ID') is not None
 if is_running_on_space:
@@ -12,15 +13,18 @@ else:
     api_base="http://127.0.0.1:11434",
     num_ctx=8192,)
 
-guest_info_tool = load_guest_dataset()
+# guest_info_tool = load_guest_dataset()
 
 # Create Alfred, our gala agent, with the guest info tool
-alfred = CodeAgent(tools=[guest_info_tool], model=model)
+alfred = CodeAgent(tools=[hub_stats_tool, search_tool, weather_info_tool], model=model)
 
 
 def query_guest(guest_name):
   return alfred.run(f"Tell me about our guest named '{guest_name}'.")
 
+def ai_builder(builder):
+  return alfred.run(f"What is {builder} most downloaded model on huggingface hub?")
 
-demo = gr.Interface(fn=query_guest, inputs="text", outputs="text")
+
+demo = gr.Interface(fn=ai_builder, inputs="text", outputs="text")
 demo.launch()

tools.py

@@ -0,0 +1,58 @@
+from huggingface_hub import list_models
+from smolagents import DuckDuckGoSearchTool, Tool
+import random
+
+# 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"
+
+# Initialize the tool
+weather_info_tool = WeatherInfoTool()
+
+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)}"
+
+# Initialize the tool
+hub_stats_tool = HubStatsTool()