Create tools.py

tools.py

@@ -0,0 +1,102 @@
+from smolagents import DuckDuckGoSearchTool
+from smolagents import Tool
+import random
+from huggingface_hub import list_models
+
+
+# Initialize the DuckDuckGo search tool
+#search_tool = DuckDuckGoSearchTool()
+
+# --------- Weather Info Tool ---------
+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"
+
+
+
+# --------- Hugging Face Hub Stats Tool ---------
+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)}"
+
+
+# --------- News Search Tool using ContextualWeb API ---------
+class NewsSearchTool(Tool):
+    name = "news_search"
+    description = "Fetches the latest news headlines about a specific topic using the ContextualWeb API."
+    inputs = {
+        "topic": {
+            "type": "string",
+            "description": "The topic to search for in recent news."
+        }
+    }
+    output_type = "string"
+
+    def __init__(self, api_key: str):
+        self.api_key = api_key
+
+    def forward(self, topic: str):
+        url = "https://contextualwebsearch-websearch-v1.p.rapidapi.com/api/Search/NewsSearchAPI"
+        params = {
+            "q": topic,
+            "pageNumber": "1",
+            "pageSize": "3",
+            "autoCorrect": "true"
+        }
+        headers = {
+            "X-RapidAPI-Key": self.api_key,
+            "X-RapidAPI-Host": "contextualwebsearch-websearch-v1.p.rapidapi.com"
+        }
+
+        try:
+            response = requests.get(url, headers=headers, params=params)
+            response.raise_for_status()
+            articles = response.json().get("value", [])
+
+            if not articles:
+                return f"No news articles found for topic '{topic}'."
+
+            return "\n\n".join(
+                f"📰 {a['title']}\n{a['description'] or ''}\nSource: {a['provider']['name']}\nLink: {a['url']}"
+                for a in articles
+            )
+        except Exception as e:
+            return f"Error retrieving news for topic '{topic}': {str(e)}"