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import os
from langchain.tools import tool
@tool
def read_python(file_path):
"""
Reads a Python file and returns its content as a string.
Args:
file_path (str): The path to the Python file.
Returns:
str: The content of the Python file.
"""
try:
if not os.path.exists(file_path):
return f"Error: File not found at {file_path}"
with open(file_path, "r", encoding="utf-8") as file:
content = file.read()
return content
except Exception as e:
return f"Error reading Python file: {str(e)}"
@tool
def read_excel(file_path):
"""
Reads an Excel file and returns its content as a string.
Args:
file_path (str): The path to the Excel file.
Returns:
str: The content of the Excel file.
"""
if not file_path.endswith(('.xls', '.xlsx')):
return "Error: File is not an Excel file."
try:
if not os.path.exists(file_path):
return f"Error: File not found at {file_path}"
import pandas as pd
df = pd.read_excel(file_path)
return df.to_string()
except Exception as e:
return f"Error reading Excel file: {str(e)}"
@tool
def transcribe_audio(file_path):
"""
Transcribes an audio file and returns its content as a string.
Args:
file_path (str): The path to the audio file.
Returns:
str: The transcribed text from the audio file.
"""
if not file_path.endswith(('.wav', '.mp3', '.m4a')):
return "Error: File is not an audio file."
try:
if not os.path.exists(file_path):
return f"Error: File not found at {file_path}"
import whisper
model = whisper.load_model("base")
result = model.transcribe(file_path, language="en")
text = result["text"]
return text
except Exception as e:
return f"Error transcribing audio file: {str(e)}" |