smartNamer.py

smartNamer.py is a Python script designed to rename PDF files based on their content using a language model.

Overview

This script reads the content of each PDF file in the specified directory, generates a new name based on the content using a language model, and then renames the files accordingly.

Features

• Uses OpenAI's GPT-3.5-turbo language model
• Processes PDF content to generate meaningful file names
• Automates renaming of PDF files

How It Works

Imports Required Libraries

• ChatOpenAI from langchain_openai to use OpenAI's language model.
• PyPDFLoader from langchain_community.document_loaders to load PDF files.
• Other necessary libraries such as os for file operations.

Initialize the Language Model

The script initializes a ChatOpenAI model with specified parameters like temperature and model name.

llm = ChatOpenAI(
    temperature=0, 
    model_name="gpt-3.5-turbo",
    api_key="openai_api_key"
)

Define the PDF Directory

The variable pdfs holds the path to the directory containing PDF files.

pdfs = 'C:\\Users\\walte\\Desktop\\pdf_ai_reader\\pdfs'

List PDF Files

files contains the list of PDF files in the specified directory.

files = os.listdir(pdfs)

AI Reader Function

The function ai_reader() processes each PDF file, extracts its content, and uses the language model to generate a new name for the file based on its content.

• Constructs a prompt to instruct the language model to create a short but perfect file name based on the content.
• Uses ChatPromptTemplate and StrOutputParser to format the prompt and parse the response.
• Iterates over each PDF file, loads its content, and invokes the language model to generate a new name.
• Collects the generated names in a list res.

def ai_reader():
    res = []
    user_input = 'create a short but perfect file name according to the content of the file provided'

    from langchain_core.prompts import ChatPromptTemplate
    rag_prompt = ChatPromptTemplate.from_messages([
        ("system", 'You are a helpful assistant. Use the following context when responding:\n\n{context}.'),
        ("human", "{question}")
    ])

    from langchain_core.output_parsers import StrOutputParser
    output_parser = StrOutputParser()
    rag_chain = rag_prompt | llm | StrOutputParser()

    for f in files:
        pdf_path = pdfs + f"\\{f}"
        loader = PyPDFLoader(file_path=pdf_path)
        documents = loader.load()
        response = rag_chain.invoke({
            "question": user_input,
            "context": documents
        })
        res.append(response)

    return res

Rename Function

The rename() function takes the list of original file names and the generated names, then renames each file accordingly.

def rename():
    names = ai_reader()
    print(names)
    for i, j in zip(files, names):
        old_file_path = pdfs + f"\\{i}"
        new_file_path = pdfs + f"\\{j}"
        os.rename(old_file_path, new_file_path)

Main Function

The main() function calls the ai_reader() and rename() functions to perform the renaming operation.

def main():
    ai_reader()
    rename()

main()

"# name_your_pdf_with_ai"