oo

.gradio/certificate.pem

@@ -0,0 +1,31 @@
+-----BEGIN CERTIFICATE-----
+MIIFazCCA1OgAwIBAgIRAIIQz7DSQONZRGPgu2OCiwAwDQYJKoZIhvcNAQELBQAw
+TzELMAkGA1UEBhMCVVMxKTAnBgNVBAoTIEludGVybmV0IFNlY3VyaXR5IFJlc2Vh
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+emyPxgcYxn/eR44/KJ4EBs+lVDR3veyJm+kXQ99b21/+jh5Xos1AnX5iItreGCc=
+-----END CERTIFICATE-----

Gradio_UI.py

@@ -17,6 +17,7 @@ import mimetypes
 import os
 import re
 import shutil
+import tempfile
 from typing import Optional
 
 from smolagents.agent_types import AgentAudio, AgentImage, AgentText, handle_agent_output_types
@@ -153,8 +154,9 @@ def stream_to_gradio(
         ):
             yield message
 
-    final_answer = step_log  # Last log is the run's final_answer
-    final_answer = handle_agent_output_types(final_answer)
+    # The last streamed item is typically a FinalAnswerStep, so unwrap its payload first.
+    raw_final_answer = getattr(step_log, "final_answer", step_log)
+    final_answer = handle_agent_output_types(raw_final_answer)
 
     if isinstance(final_answer, AgentText):
         yield gr.ChatMessage(
@@ -171,6 +173,15 @@ def stream_to_gradio(
             role="assistant",
             content={"path": final_answer.to_string(), "mime_type": "audio/wav"},
         )
+    elif hasattr(final_answer, "save"):
+        # Support PIL-style image objects by persisting them to a temp file for chat rendering.
+        fd, image_path = tempfile.mkstemp(prefix="smolagents_final_", suffix=".png")
+        os.close(fd)
+        final_answer.save(image_path)
+        yield gr.ChatMessage(
+            role="assistant",
+            content={"path": image_path, "mime_type": "image/png"},
+        )
     else:
         yield gr.ChatMessage(role="assistant", content=f"**Final answer:** {str(final_answer)}")
 
@@ -260,20 +271,26 @@ class GradioUI:
 
     def launch(self, **kwargs):
         import gradio as gr
+        import inspect
 
         with gr.Blocks(fill_height=True) as demo:
             stored_messages = gr.State([])
             file_uploads_log = gr.State([])
-            chatbot = gr.Chatbot(
-                label="Agent",
-                type="messages",
-                avatar_images=(
+            chatbot_kwargs = {
+                "label": "Agent",
+                "type": "messages",
+                "avatar_images": (
                     None,
                     "https://huggingface.co/datasets/agents-course/course-images/resolve/main/en/communication/Alfred.png",
                 ),
-                resizeable=True,
-                scale=1,
-            )
+                "resizeable": True,
+                "scale": 1,
+            }
+            supported_chatbot_args = set(inspect.signature(gr.Chatbot.__init__).parameters.keys())
+            filtered_chatbot_kwargs = {
+                key: value for key, value in chatbot_kwargs.items() if key in supported_chatbot_args
+            }
+            chatbot = gr.Chatbot(**filtered_chatbot_kwargs)
             # If an upload folder is provided, enable the upload feature
             if self.file_upload_folder is not None:
                 upload_file = gr.File(label="Upload a file")

app.py

@@ -1,9 +1,10 @@
-from smolagents import CodeAgent,DuckDuckGoSearchTool, HfApiModel,load_tool,tool
+from smolagents import CodeAgent, HfApiModel, load_tool, tool
 import datetime
-import requests
 import pytz
 import yaml
 from tools.final_answer import FinalAnswerTool
+from tools.web_search import DuckDuckGoSearchTool
+from tools.visit_webpage import VisitWebpageTool
 
 from Gradio_UI import GradioUI
 
@@ -49,13 +50,15 @@ custom_role_conversions=None,
 
 # Import tool from Hub
 image_generation_tool = load_tool("agents-course/text-to-image", trust_remote_code=True)
+web_search_tool = DuckDuckGoSearchTool()
+visit_webpage_tool = VisitWebpageTool()
 
 with open("prompts.yaml", 'r') as stream:
     prompt_templates = yaml.safe_load(stream)
     
 agent = CodeAgent(
     model=model,
-    tools=[final_answer], ## add your tools here (don't remove final answer)
+    tools=[final_answer, web_search_tool, visit_webpage_tool, image_generation_tool], ## add your tools here (don't remove final answer)
     max_steps=6,
     verbosity_level=1,
     grammar=None,

requirements.txt

@@ -1,5 +1,8 @@
 markdownify
-smolagents==1.13.0
+smolagents[gradio]==1.13.0
 requests
 duckduckgo_search
+ddgs
 pandas
+pytz
+PyYAML

tools/visit_webpage.py

@@ -1,8 +1,6 @@
 from typing import Any, Optional
 from smolagents.tools import Tool
-import requests
-import markdownify
-import smolagents
+import re
 
 class VisitWebpageTool(Tool):
     name = "visit_webpage"

tools/web_search.py

@@ -1,6 +1,5 @@
 from typing import Any, Optional
 from smolagents.tools import Tool
-import duckduckgo_search
 
 class DuckDuckGoSearchTool(Tool):
     name = "web_search"
@@ -12,15 +11,20 @@ class DuckDuckGoSearchTool(Tool):
         super().__init__()
         self.max_results = max_results
         try:
-            from duckduckgo_search import DDGS
+            # Preferred package name (new)
+            from ddgs 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
+            try:
+                # Backward-compatible fallback (old package name)
+                from duckduckgo_search import DDGS
+            except ImportError as inner_e:
+                raise ImportError(
+                    "You must install package `ddgs` (or legacy `duckduckgo_search`) to run this tool: for instance run `pip install ddgs`."
+                ) from inner_e
         self.ddgs = DDGS(**kwargs)
 
     def forward(self, query: str) -> str:
-        results = self.ddgs.text(query, max_results=self.max_results)
+        results = list(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]