Delete document_parser.py

document_parser.py

@@ -1,160 +0,0 @@
-import os
-import uuid
-import requests
-import tempfile
-from PIL import Image
-import pytesseract
-import pandas as pd
-from urllib.parse import urlparse
-from langchain_core.tools import tool
-from typing import Optional
-import logging
-import pandasql as psql
-
-# ------------------- 🔧 Logger Setup -------------------
-def setup_logger():
-    logger = logging.getLogger("FileToolLogger")
-    logger.setLevel(logging.INFO)
-    if not logger.handlers:
-        handler = logging.StreamHandler()
-        formatter = logging.Formatter('%(asctime)s - %(levelname)s - %(message)s')
-        handler.setFormatter(formatter)
-        logger.addHandler(handler)
-    return logger
-
-logger = setup_logger()
-
-# ------------------- 📄 Save Content to File -------------------
-@tool
-def save_and_read_file(content: str, filename: Optional[str] = None) -> str:
-    """
-    Save content to a file and return the path.
-    Args:
-        content (str): the content to save to the file
-        filename (str, optional): the name of the file. If not provided, a random name file will be created.
-    """
-    temp_dir = tempfile.gettempdir()
-    if filename is None:
-        temp_file = tempfile.NamedTemporaryFile(delete=False, dir=temp_dir)
-        filepath = temp_file.name
-    else:
-        filepath = os.path.join(temp_dir, filename)
-
-    with open(filepath, "w") as f:
-        f.write(content)
-
-    return f"File saved to {filepath}. You can read this file to process its contents."
-
-# ------------------- 📄 Save Content to File -------------------
-
-@tool
-def download_file_from_url(url: str, filename: Optional[str] = None) -> str:
-    """
-    Download a file from a URL and save it to a temporary location.
-    Args:
-        url (str): the URL of the file to download.
-        filename (str, optional): the name of the file. If not provided, a random name file will be created.
-    """
-    try:
-        # Parse URL to get filename if not provided
-        if not filename:
-            path = urlparse(url).path
-            filename = os.path.basename(path)
-            if not filename:
-                filename = f"downloaded_{uuid.uuid4().hex[:8]}"
-
-        # Create temporary file
-        temp_dir = tempfile.gettempdir()
-        filepath = os.path.join(temp_dir, filename)
-
-        # Download the file
-        response = requests.get(url, stream=True)
-        response.raise_for_status()
-
-        # Save the file
-        with open(filepath, "wb") as f:
-            for chunk in response.iter_content(chunk_size=8192):
-                f.write(chunk)
-
-        return f"File downloaded to {filepath}. You can read this file to process its contents."
-    except Exception as e:
-        return f"Error downloading file: {str(e)}"
-
-@tool
-def extract_text_from_image(image_path: str) -> str:
-    """
-    Extract text from an image using OCR library pytesseract (if available).
-    Args:
-        image_path (str): the path to the image file.
-    """
-    try:
-        
-        # Open the image
-        image = Image.open(image_path)
-        
-        # Extract text from the image
-        text = pytesseract.image_to_string(image)
-        return f"Extracted text from image:\n\n{text}"
-        
-    except Exception as e:
-        return f"Error extracting text from image: {str(e)}"
-
-@tool
-def analyze_csv_file(file_path: str, query: Optional[str] = None) -> str:
-
-    """
-    Analyze a CSV file using pandas and answer a question about it.
-    Args:
-        file_path (str): the path to the CSV file.
-        query (str): Question about the data
-    """
-    if not os.path.isfile(file_path) or not file_path.endswith((".csv")):
-            return "Invalid or missing csv file."
-    try :
-        
-        df = pd.read_csv(file_path)
-        columns = df.columns
-        result = [f"CSV loaded with shape: {df.shape}", f" Columns: {', '.join(columns)}"]
-
-        if query:
-            result.append(f"\n Query: {query}")
-            result_df = psql.sqldf(query, {"df": df})
-            result.append("Query Result:\n" + result_df.to_string(index=False))
-        else:
-            result.append("\nSummary:\n" + str(df.describe(include='all')))
-
-        return "\n".join(result)
-
-    except Exception as e:
-        return f"Error analyzing CSV file: {str(e)}"
-
-@tool
-def analyze_excel_file(file_path: str, query: Optional[str] = None) -> str:
-
-    """
-    Analyze a excel file using pandas and answer a question about it.
-    Args:
-        file_path (str): the path to the xls or xlsx file.
-        query (str): Question about the data
-    """
-    if not os.path.isfile(file_path) or not file_path.endswith((".xls", ".xlsx")):
-            return "Invalid or missing Excel file."
-
-    try :
-
-        df = pd.read_excel(file_path)
-        columns = df.columns
-        result = [f"CSV loaded with shape: {df.shape}", f" Columns: {', '.join(columns)}"]
-
-        if query:
-            result.append(f"\n Query: {query}")
-            result_df = psql.sqldf(query, {"df": df})
-            result.append("Query Result:\n" + result_df.to_string(index=False))
-        else:
-            result.append("\nSummary:\n" + str(df.describe(include='all')))
-
-        return "\n".join(result)
-
-    except Exception as e:
-        return f"Error analyzing Excel file: {str(e)}"
-