Upload agent

agent.json

@@ -1,6 +1,7 @@
 {
     "class": "CodeAgent",
     "tools": [
+        "web_search",
         "final_answer"
     ],
     "model": {
@@ -32,6 +33,7 @@
     "name": null,
     "description": null,
     "requirements": [
+        "ddgs",
         "smolagents"
     ],
     "authorized_imports": [

app.py

@@ -5,6 +5,7 @@ from smolagents import GradioUI, CodeAgent, InferenceClientModel
 # Get current directory path
 CURRENT_DIR = os.path.dirname(os.path.abspath(__file__))
 
+from tools.web_search import DuckDuckGoSearchTool as WebSearch
 from tools.final_answer import FinalAnswerTool as FinalAnswer
 
 
@@ -13,6 +14,7 @@ model = InferenceClientModel(
 model_id='Qwen/Qwen3-Next-80B-A3B-Thinking',
 )
 
+web_search = WebSearch()
 final_answer = FinalAnswer()
 
 
@@ -21,7 +23,7 @@ with open(os.path.join(CURRENT_DIR, "prompts.yaml"), 'r') as stream:
 
 agent = CodeAgent(
     model=model,
-    tools=[],
+    tools=[web_search],
     managed_agents=[],
     max_steps=20,
     verbosity_level=1,

requirements.txt

@@ -1 +1,2 @@
+ddgs
 smolagents

tools/web_search.py

@@ -0,0 +1,60 @@
+from typing import Any, Optional
+from smolagents.tools import Tool
+import ddgs
+import time
+
+class DuckDuckGoSearchTool(Tool):
+    """Web search tool that performs searches using the DuckDuckGo search engine.
+
+    Args:
+        max_results (`int`, default `10`): Maximum number of search results to return.
+        rate_limit (`float`, default `1.0`): Maximum queries per second. Set to `None` to disable rate limiting.
+        **kwargs: Additional keyword arguments for the `DDGS` client.
+
+    Examples:
+        ```python
+        >>> from smolagents import DuckDuckGoSearchTool
+        >>> web_search_tool = DuckDuckGoSearchTool(max_results=5, rate_limit=2.0)
+        >>> results = web_search_tool("Hugging Face")
+        >>> print(results)
+        ```
+    """
+    name = "web_search"
+    description = "Performs a duckduckgo web search based on your query (think a Google search) then returns the top search results."
+    inputs = {'query': {'type': 'string', 'description': 'The search query to perform.'}}
+    output_type = "string"
+
+    def __init__(self, max_results: int = 10, rate_limit: float | None = 1.0, **kwargs):
+        super().__init__()
+        self.max_results = max_results
+        self.rate_limit = rate_limit
+        self._min_interval = 1.0 / rate_limit if rate_limit else 0.0
+        self._last_request_time = 0.0
+        try:
+            from ddgs import DDGS
+        except ImportError as e:
+            raise ImportError(
+                "You must install package `ddgs` to run this tool: for instance run `pip install ddgs`."
+            ) from e
+        self.ddgs = DDGS(**kwargs)
+
+    def forward(self, query: str) -> str:
+        self._enforce_rate_limit()
+        results = self.ddgs.text(query, max_results=self.max_results)
+        if len(results) == 0:
+            raise Exception("No results found! Try a less restrictive/shorter query.")
+        postprocessed_results = [f"[{result['title']}]({result['href']})\n{result['body']}" for result in results]
+        return "## Search Results\n\n" + "\n\n".join(postprocessed_results)
+
+    def _enforce_rate_limit(self) -> None:
+        import time
+
+        # No rate limit enforced
+        if not self.rate_limit:
+            return
+
+        now = time.time()
+        elapsed = now - self._last_request_time
+        if elapsed < self._min_interval:
+            time.sleep(self._min_interval - elapsed)
+        self._last_request_time = time.time()