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import requests
import pandas as pd
from io import BytesIO
from markitdown import MarkItDown
from langchain_core.tools import tool
@tool
def extract_transcript_from_youtube(url: str) -> str:
"""
Extracts the transcript from a YouTube video given its URL.
Args:
url (str): The YouTube video URL.
Returns:
transcript (str): The transcript of the video, or an error message if extraction fails.
"""
transcript_str = "### Transcript"
md = MarkItDown(enable_plugins=True)
try:
result = md.convert(url)
except Exception as e:
return f"Failed to extract transcript from YouTube video: {str(e)}"
parts = result.text_content.split(transcript_str)
if len(parts) < 2:
return result.text_content
transcript = (transcript_str + "\n" + parts[1]).strip()
return transcript
@tool
def extract_data_from_excel(url: str) -> str:
"""
Downloads and extracts data from an Excel file at the given URL.
Args:
url (str): The URL of the Excel file.
Returns:
str: A string representation of the data in the first sheet of the Excel file.
"""
try:
response = requests.get(url)
response.raise_for_status()
excel_file = BytesIO(response.content)
df = pd.read_excel(excel_file)
# Optional: Remove unnamed columns often created by Excel
df = df.loc[:, ~df.columns.str.contains('^Unnamed')]
# Convert all numeric columns to float
for col in df.select_dtypes(include=["number"]).columns:
df[col] = df[col].astype(float)
return df.to_string(index=False)
except Exception as e:
return f"Failed to process Excel file from URL: {str(e)}"
@tool
def extract_transcript_from_audio(url: str) -> str:
"""
Extracts the transcript from an audio file given its URL.
Supported formats: mp3, wav.
Args:
url (str): The URL of the audio file.
Returns:
str: The transcript of the audio file, or an error message if extraction fails.
"""
md = MarkItDown(enable_plugins=True)
try:
result = md.convert(url)
except Exception as e:
return f"Failed to extract transcript from audio: {str(e)}"
return result.text_content |