small fix

agent.py

@@ -1,6 +1,4 @@
 import os
-from typing import Bool
-
 from dotenv import load_dotenv
 
 # Import models from SmolaAgents
@@ -10,7 +8,7 @@ from smolagents import CodeAgent, LiteLLMModel, OpenAIServerModel
 from smolagents.default_tools import FinalAnswerTool, PythonInterpreterTool
 
 # Import custom tools
-from Final_Assignment_Template.tools import (
+from tools import (
     AddDocumentToVectorStoreTool,
     ArxivSearchTool,
     DownloadFileFromLinkTool,
@@ -21,16 +19,15 @@ from Final_Assignment_Template.tools import (
     TranscribeAudioTool,
     VisitWebpageTool,
     WikipediaSearchTool,
+    image_question_answering
 )
 
 # Import utility functions
 from utils import extract_final_answer, replace_tool_mentions
 
-# Import tools from LangChain
-
 
 class BoomBot:
-    def __init__(self, provider="deepinfra"):
+    def __init__(self, provider="meta"):
         """
         Initialize the BoomBot with the specified provider.
 
@@ -134,6 +131,7 @@ class BoomBot:
             arxiv_search,
             add_doc_vectorstore,
             retrieve_doc_vectorstore,
+            image_question_answering,
             python_interpreter,
             final_answer,
         ]
@@ -246,7 +244,7 @@ class BoomBot:
           - Conclude with: FINAL ANSWER: <your_answer>
         """
 
-    def run(self, question: str, task_id: str, to_download: Bool) -> str:
+    def run(self, question: str, task_id: str, to_download) -> str:
         """
         Run the agent with the given question, task_id, and download flag.
 

tools.py

@@ -35,6 +35,11 @@ from markdownify import markdownify
 from smolagents import Tool, tool
 from smolagents.utils import truncate_content
 
+from typing import Dict, List
+
+import requests
+from bs4 import BeautifulSoup
+from urllib.parse import quote_plus
 
 class ReadFileContentTool(Tool):
     name = "read_file_content"
@@ -159,44 +164,6 @@ class WikipediaSearchTool(Tool):
             return f"Error wiki: {e}"
 
 
-class VisitWebpageTool(Tool):
-    name = "visit_webpage"
-    description = "Loads a webpage from a URL and converts its content to markdown format. Use this to browse websites, extract information, or identify downloadable resources from a specific web address."
-    inputs = {
-        "url": {
-            "type": "string",
-            "description": "The url of the webpage to visit.",
-        }
-    }
-    output_type = "string"
-
-    def forward(self, url: str) -> str:
-        try:
-            import re
-
-            import requests
-            from markdownify import markdownify
-            from requests.exceptions import RequestException
-            from smolagents.utils import truncate_content
-        except ImportError as e:
-            raise ImportError(
-                "You must install packages `markdownify` and `requests` to run this tool: for instance run `pip install markdownify requests`."
-            ) from e
-        try:
-            response = requests.get(url, timeout=20)
-            response.raise_for_status()  # Raise an exception for bad status codes
-            markdown_content = markdownify(response.text).strip()
-            markdown_content = re.sub(r"\n{3,}", "\n\n", markdown_content)
-            return truncate_content(markdown_content, 5000)
-
-        except requests.exceptions.Timeout:
-            return "The request timed out. Please try again later or check the URL."
-        except RequestException as e:
-            return f"Error fetching the webpage: {str(e)}"
-        except Exception as e:
-            return f"An unexpected error occurred: {str(e)}"
-
-
 class TranscribeAudioTool(Tool):
     name = "transcribe_audio"
     description = """Converts spoken content in audio files to text. Handles various audio formats and produces a transcript of the spoken content for analysis."""
@@ -577,7 +544,6 @@ class DuckDuckGoSearchTool(Tool):
 
         return f"❌ Failed to retrieve results after {max_retries} retries."
 
-
 huggingface_ef = embedding_functions.HuggingFaceEmbeddingFunction(
     api_key=os.environ["HF_TOKEN"], model_name="sentence-transformers/all-mpnet-base-v2"
 )
@@ -592,7 +558,6 @@ SUPPORTED_EXTENSIONS = [
     ".htm",
 ]
 
-
 class AddDocumentToVectorStoreTool(Tool):
     name = "add_document_to_vector_store"
     description = "Processes a document and adds it to the vector database for semantic search. Automatically chunks files and creates text embeddings to enable powerful content retrieval."
@@ -660,7 +625,6 @@ class AddDocumentToVectorStoreTool(Tool):
             traceback.print_exc()
             return f"Error: {e}"
 
-
 class QueryVectorStoreTool(Tool):
     name = "query_downloaded_documents"
     description = "Performs semantic searches across your downloaded documents. Use detailed queries to find specific information, concepts, or answers from your collected resources."
@@ -715,7 +679,6 @@ class QueryVectorStoreTool(Tool):
             traceback.print_exc()
             return f"Error querying vector store: {e}"
 
-
 @tool
 def image_question_answering(image_path: str, prompt: str) -> str:
     """
@@ -752,7 +715,6 @@ def image_question_answering(image_path: str, prompt: str) -> str:
 
     return response.message.content.strip()
 
-
 class VisitWebpageTool(Tool):
     name = "visit_webpage"
     description = "Loads a webpage from a URL and converts its content to markdown format. Use this to browse websites, extract information, or identify downloadable resources from a specific web address."
@@ -987,7 +949,6 @@ class VisitWebpageTool(Tool):
 
         return content
 
-
 class ArxivSearchTool(Tool):
     name = "arxiv_search"
     description = """Searches arXiv for academic papers and returns structured information including titles, authors, publication dates, abstracts, and download links."""
@@ -1045,13 +1006,6 @@ class ArxivSearchTool(Tool):
 
         return "\n".join(output_lines).strip()
 
-
-from typing import Dict, List
-
-import requests
-from bs4 import BeautifulSoup
-
-
 def fetch_and_parse_arxiv(url: str) -> List[Dict[str, str]]:
     """
     Fetches the given arXiv advanced‐search URL, parses the HTML,
@@ -1114,10 +1068,6 @@ def fetch_and_parse_arxiv(url: str) -> List[Dict[str, str]]:
 
     return results
 
-
-from urllib.parse import quote_plus
-
-
 def build_arxiv_url(
     query: str, from_date: str = None, to_date: str = None, size: int = 50
 ) -> str: