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from langchain_community.agent_toolkits import FileManagementToolkit
from config import CACHE_DIR
from langchain_core.tools import tool
import pandas as pd
__all__ = [
'save_file',
'read_file',
'analyze_csv',
'extract_text_from_image'
]
@tool
def save_file(filename: str, content: str) -> bool:
"""
Saves content to a file.
Args:
filename (str): The name of the file in the cache directory.
content (str): The content to save.
Returns:
bool: True if the file was saved successfully, False otherwise.
"""
try:
file_path = CACHE_DIR / filename
with open(file_path, "w") as f:
f.write(content)
return True
except Exception as e:
print(f"Error saving file {file_path}: {e}")
return False
@tool
def read_file(filename: str) -> str:
"""
Reads content from a file.
Args:
filename (str): The name of the file in the cache directory.
Returns:
str: The content of the file.
"""
try:
file_path = CACHE_DIR / filename
with open(file_path, "r") as f:
return f.read()
except Exception as e:
return (f"Error reading file {file_path}: {e}")
@tool
def analyze_csv(filename: str) -> str:
"""
Analyzes a CSV file using pandas, returning statistics about the file.
Args:
filename (str): The name of the CSV file in the cache directory.
Returns:
str: The analysis of the file.
"""
df = pd.read_csv(CACHE_DIR / filename)
if df is not None:
# Perform analysis on the DataFrame
result = f"CSV file: {len(df)} rows; {len(df.columns)} columns.\n"
result += f"Columns: {', '.join(df.columns)}\n\n"
result += "Summary:\n"
result += str(df.describe())
return result
@tool
def extract_text_from_image(filename: str) -> str:
"""
Extracts text from an image file using OCR.
Args:
filename (str): The name of the image file in the cache directory.
Returns:
str: The extracted text from the image.
"""
from PIL import Image
import pytesseract
try:
image_path = CACHE_DIR / filename
image = Image.open(image_path)
text = pytesseract.image_to_string(image)
return text
except Exception as e:
return f"Error extracting text from image {filename}: {e}" |