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from langchain_community.tools import WikipediaQueryRun, ArxivQueryRun, DuckDuckGoSearchRun
from langchain_community.utilities import WikipediaAPIWrapper, ArxivAPIWrapper, DuckDuckGoSearchAPIWrapper
from langchain_core.tools import tool
from datetime import datetime
import requests
import io
import pandas as pd
wikipedia_tool = WikipediaQueryRun(
api_wrapper=WikipediaAPIWrapper(top_k_results=2, doc_content_chars_max=4000,lang="en")
)
ddg_search_tool = DuckDuckGoSearchRun(
api_wrapper=DuckDuckGoSearchAPIWrapper(max_results=5)
)
arxiv_tool = ArxivQueryRun(
api_wrapper=ArxivAPIWrapper(top_k_results=3, doc_content_chars_max=4000)
)
@tool
def get_current_year() -> str:
"""returns the current year"""
return str(datetime.now().year)
@tool
def get_youtube_transcript(url: str) -> str:
"""
Get the full transcript/subtitles from a YouTube video.
Use this tool whenever the question contains a YouTube URL (youtube.com or youtu.be).
Extract the URL from the question and pass it as the argument.
Example: if question says 'In the video https://www.youtube.com/watch?v=ABC123, what...'
then call this tool with url='https://www.youtube.com/watch?v=ABC123'
"""
try:
from youtube_transcript_api import YouTubeTranscriptApi
if "v=" in url:
video_id = url.split("v=")[-1].split("&")[0]
elif "youtu.be/" in url:
video_id = url.split("youtu.be/")[-1].split("?")[0]
else:
return "Could not extract video ID from URL."
transcript = YouTubeTranscriptApi.get_transcript(video_id)
return " ".join([t["text"] for t in transcript])[:5000]
except Exception as e:
return f"Transcript unavailable: {e}"
@tool
def fetch_url_content(url: str) -> str:
"""Fetch and return the text content of any URL. Useful for web pages and articles."""
try:
headers = {'User-Agent': 'Mozilla/5.0'}
response = requests.get(url, headers=headers, timeout=10)
response.raise_for_status()
text = response.text
import re
text = re.sub(r'<[^>]+>', ' ', text)
text = re.sub(r'\s+', ' ', text).strip()
return text[:6000]
except Exception as e:
return f"Could not fetch URL: {e}"
@tool
def get_gaia_file(task_id: str) -> str:
"""Download and read a file attachment for a GAIA task. Use when question mentions an attached file."""
try:
url = f"https://agents-course-unit4-scoring.hf.space/files/{task_id}"
resp = requests.get(url, timeout=15)
if resp.status_code != 200:
return f"Could not fetch file for task {task_id}"
content_type = resp.headers.get("content-type", "")
content_disposition = resp.headers.get("content-disposition", "")
filename = ""
if "filename=" in content_disposition:
filename = content_disposition.split("filename=")[-1].strip('"')
if filename.endswith(".py") or "text/plain" in content_type:
return resp.text
if filename.endswith(".xlsx") or filename.endswith(".xls") or "spreadsheet" in content_type or "excel" in content_type:
df = pd.read_excel(io.BytesIO(resp.content))
return df.to_string()
if filename.endswith(".csv") or "csv" in content_type:
df = pd.read_csv(io.BytesIO(resp.content))
return df.to_string()
if filename.endswith(".mp3") or "audio" in content_type:
return "This is an audio file. Audio transcription is not supported."
try:
return resp.text[:5000]
except:
return "File could not be read."
except Exception as e:
return f"Error fetching file: {e}"
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