Update app.py

app.py

@@ -3,7 +3,7 @@ import gradio as gr
 import requests
 import inspect
 import pandas as pd
-from smolagents import CodeAgent, InferenceClientModel, DuckDuckGoSearchTool,Tool,tool,VisitWebpageTool,FinalAnswerTool
+from smolagents import CodeAgent, InferenceClientModel,huggingface_hub, DuckDuckGoSearchTool,Tool,tool,VisitWebpageTool,PythonInterpreterTool,FinalAnswerTool
 import base64
 
 # (Keep Constants as is)
@@ -95,48 +95,58 @@ class BasicAgent:
                 reader = PdfReader(file_path)
                 return "\n".join(page.extract_text() or "" for page in reader.pages)
 
-        @tool
-        def analyze_image(file_path: str, question: str) -> str:
-            """
-            Analyzes an image and answers a question about its contents.
-            
-            Args: 
-                 file_path: Local path to the image file.
-                 question: What to look for or answer about the image.
-
-            Returns: 
-                 A text answer describing what's found in the image.
-                  """
-            client = InferenceClient(token=os.environ["HF_TOKEN"])
+        class AnalyzeImageTool(Tool):
+            name = "analyze_image"
+            description = "Analyzes an image and answers a question about its contents."
+            inputs = {
+                    "file_path": {
+                    "type": "string",
+                    "description": "Local path to the image file.",
+                     },
+                    "question": {
+                    "type": "string",
+                    "description": "What to look for or answer about the image.",
+                    },
+                }
+            output_type = "string"
+
+        def forward(self, file_path: str, question: str) -> str:
+            import base64
+            from huggingface_hub import InferenceClient
 
+            client = InferenceClient(token=os.environ["HF_TOKEN"])
             with open(file_path, "rb") as f:
                 image_bytes = f.read()
             image_b64 = base64.b64encode(image_bytes).decode("utf-8")
 
             result = client.chat_completion(
-                 model="Qwen/Qwen2.5-VL-72B-Instruct",
-                  messages=[
-                      {
-                          "role": "user",
-                          "content": [
-                              {"type": "text", "text": question},
-                              {"type": "image_url", "image_url": {"url": f"data:image/jpeg;base64,{image_b64}"}},
-                          ]
-                      }
-                  ]
-             )
+                model="Qwen/Qwen2.5-VL-72B-Instruct",
+                messages=[
+                     {
+                        "role": "user",
+                        "content": [
+                            {"type": "text", "text": question},
+                            {"type": "image_url", "image_url": {"url": f"data:image/jpeg;base64,{image_b64}"}},
+                        ],
+                     }
+                ],
+            )
             return result.choices[0].message.content
-        @tool
-        def transcribe_audio(file_path: str) -> str:
-            """
-            Transcribes speech from an audio file to text.
-            
-            Args:
-                file_path: Local path to the audio file.
-                
-            Returns:
-                The transcribed text.
-                """
+
+
+        class TranscribeAudioTool(Tool):
+            name = "transcribe_audio"
+            description = "Transcribes speech from an audio file to text."
+            inputs = {
+                "file_path": {
+                "type": "string",
+                "description": "Local path to the audio file.",
+            }
+        }
+            output_type = "string"
+
+        def forward(self, file_path: str) -> str:
+            from huggingface_hub import InferenceClient
             client = InferenceClient(token=os.environ["HF_TOKEN"])
             result = client.automatic_speech_recognition(
                 file_path,
@@ -152,22 +162,23 @@ class BasicAgent:
             tools=[
                 DuckDuckGoSearchTool(),
                 VisitWebpageTool(),
-                #PythonInterpreterTool(),
+                PythonInterpreterTool(),
                 FinalAnswerTool(),
                 #pdf_tool,
                 fetch_task_file,
                 #read_pdf,
                 read_spreadsheet,
                 get_youtube_transcript,
-                analyze_image,
-                transcribe_audio,
+                AnalyzeImageTool,
+                TranscribeAudioTool
                 ],
             model= InferenceClientModel("Qwen/Qwen2.5-Coder-32B-Instruct") ,
             additional_authorized_imports=["pandas", "requests", "re"],
             instructions = ("You are an advanced CodeAgent that will show your capabilities to work in the real world by being tested in GAIA, the agent testing platform. If the question includes a task_id and mentions a file, call fetch_task_file first; route YouTube URLs to get_youtube_transcript, other URLs to visit_webpage, PDFs to pdf_tool, and spreadsheets to read_spreadsheet, using web_search only when no URL or file is given,then respond with only the exact final answer value, no explanation, no prefix."
                            "Use the Thought Action observation to produce high quality results and only answer when you are sure you have performed the necessary steps for the task and question"
-                           "If the file is an image, use analyze_image with a specific question about "
-                           "what to find. If the file is audio, use transcribe_audio first, then reason over the transcribed text "),
+                           "If the file is an image, use AnalyzeImageTool with a specific question about it"
+                           "what to find. If the file is audio, use TranscribeAudioTool first, then reason over the transcribed text "
+                           "Use the PythonInterpreterTool for code interpretation in python"),
             max_steps=20,
         )
 #answering questions