Update app.py

app.py

@@ -10,34 +10,26 @@ import gradio as gr
 from PIL import Image
 from io import BytesIO
 import base64
-from smolagents import load_tool
 from typing import Any
 
-# class DuckDuckGoSearchTool(Tool):
-#     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=10, **kwargs):
-#         super().__init__()
-#         self.max_results = max_results
-#         try:
-#             from duckduckgo_search import DDGS
-#         except ImportError as e:
-#             raise ImportError(
-#                 "You must install package `duckduckgo_search` to run this tool: for instance run `pip install duckduckgo-search`."
-#             ) from e
-#         self.ddgs = DDGS(**kwargs)
-
-#     def forward(self, query: str) -> str:
-#         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)
-
+class DuckDuckGoSearchTool(Tool):
+    name = "web_search"
+    description = "Performs a DuckDuckGo web search."
+    inputs = {'query': {'type': 'string', 'description': 'Search query'}}
+    output_type = "string"
 
+    def __init__(self, max_results=10, **kwargs):
+        super().__init__()
+        self.max_results = max_results
+        self.ddgs = DDGS(**kwargs)
+
+    def forward(self, query: str) -> str:
+        results = self.ddgs.text(query, max_results=self.max_results)
+        if not results:
+            return "No results found."
+        return "\n\n".join(
+            f"[{r['title']}]({r['href']})\n{r['body']}" for r in results
+        )
 model = InferenceClientModel("qwen/Qwen2.5-0.5B-Instruct",
                             max_tokens=512,
                             system_message="""
@@ -112,7 +104,7 @@ tools = [
         name="image-captioning",
         description="Generates a caption for an input image."
     ),
-    DuckDuckGoSearchTool(),
+    DuckDuckGoSearchTool(max_results=5),
     WikipediaSearchTool(),
     PythonInterpreterTool(),
     UserInputTool(),
@@ -155,7 +147,7 @@ class BasicAgent:
 
 
     
-def run_agent_on_image(image):
+def run_agent_on_image(image, agent):
     try:
         # Wrap image as expected by the agent tool
         response = agent("Describe this image", inputs={"image": image})
@@ -189,7 +181,7 @@ def run_and_submit_all( profile: gr.OAuthProfile | None):
 
     # 1. Instantiate Agent ( modify this part to create your agent)
     try:
-        agent = BasicAgent()
+        agent = BasicAgent(model=model, tools=tools)
     except Exception as e:
         print(f"Error instantiating agent: {e}")
         return f"Error initializing agent: {e}", None