From 75bc73e04c4cfafe581474783f8e66954bbe14c6 Mon Sep 17 00:00:00 2001
From: feder-cr <85809106+feder-cr@users.noreply.github.com>
Date: Thu, 5 Dec 2024 00:57:48 +0100
Subject: [PATCH] First

---
 main.py                                       | 191 +++++++++++++---
 .../llm/llm_job_parser.py                     | 181 ---------------
 .../resume_style/__init__.py                  |   0
 src/job.py                                    |  20 +-
 src/job_application.py                        |  19 --
 src/{ai_hawk => }/libs/llm_manager.py         |   0
 .../libs/resume_and_cover_builder/__init__.py |   0
 .../libs/resume_and_cover_builder/config.py   |   0
 .../cover_letter_prompt}/__init__.py          |   0
 .../cover_letter_prompt/strings_feder-cr.py   |   2 +-
 .../llm/llm_generate_cover_letter_from_job.py |   0
 .../llm/llm_generate_resume.py                |   2 +-
 .../llm/llm_generate_resume_from_job.py       |   4 +-
 .../llm/llm_job_parser.py                     | 208 ++++++++++++++++++
 .../resume_and_cover_builder/module_loader.py |   0
 .../resume_and_cover_builder/resume_facade.py |  88 ++++++--
 .../resume_generator.py                       |  11 +-
 .../__init__.py                               |   0
 .../strings_feder-cr.py                       |   0
 .../resume_prompt}/__init__.py                |   0
 .../resume_prompt/strings_feder-cr.py         |   0
 .../resume_style}/__init__.py                 |   0
 .../resume_style/style_cloyola.css            |   0
 .../resume_style/style_josylad_blue.css       |   0
 .../resume_style/style_josylad_grey.css       |   0
 .../resume_style/style_krishnavalliappan.css  |   0
 .../resume_style/style_samodum_bold.css       |   0
 .../resume_and_cover_builder/style_manager.py |   2 +-
 .../resume_and_cover_builder/template_base.py |   0
 .../libs/resume_and_cover_builder/utils.py    |   0
 .../resume_schemas/job_application_profile.py |   0
 src/{ai_hawk => }/resume_schemas/resume.py    |   0
 32 files changed, 452 insertions(+), 276 deletions(-)
 delete mode 100644 src/ai_hawk/libs/resume_and_cover_builder/llm/llm_job_parser.py
 delete mode 100644 src/ai_hawk/libs/resume_and_cover_builder/resume_style/__init__.py
 delete mode 100644 src/job_application.py
 rename src/{ai_hawk => }/libs/llm_manager.py (100%)
 rename src/{ai_hawk => }/libs/resume_and_cover_builder/__init__.py (100%)
 rename src/{ai_hawk => }/libs/resume_and_cover_builder/config.py (100%)
 rename src/{ai_hawk => libs/resume_and_cover_builder/cover_letter_prompt}/__init__.py (100%)
 rename src/{ai_hawk => }/libs/resume_and_cover_builder/cover_letter_prompt/strings_feder-cr.py (97%)
 rename src/{ai_hawk => }/libs/resume_and_cover_builder/llm/llm_generate_cover_letter_from_job.py (100%)
 rename src/{ai_hawk => }/libs/resume_and_cover_builder/llm/llm_generate_resume.py (99%)
 rename src/{ai_hawk => }/libs/resume_and_cover_builder/llm/llm_generate_resume_from_job.py (96%)
 create mode 100644 src/libs/resume_and_cover_builder/llm/llm_job_parser.py
 rename src/{ai_hawk => }/libs/resume_and_cover_builder/module_loader.py (100%)
 rename src/{ai_hawk => }/libs/resume_and_cover_builder/resume_facade.py (56%)
 rename src/{ai_hawk => }/libs/resume_and_cover_builder/resume_generator.py (85%)
 rename src/{ai_hawk/libs/resume_and_cover_builder/cover_letter_prompt => libs/resume_and_cover_builder/resume_job_description_prompt}/__init__.py (100%)
 rename src/{ai_hawk => }/libs/resume_and_cover_builder/resume_job_description_prompt/strings_feder-cr.py (100%)
 rename src/{ai_hawk/libs/resume_and_cover_builder/resume_job_description_prompt => libs/resume_and_cover_builder/resume_prompt}/__init__.py (100%)
 rename src/{ai_hawk => }/libs/resume_and_cover_builder/resume_prompt/strings_feder-cr.py (100%)
 rename src/{ai_hawk/libs/resume_and_cover_builder/resume_prompt => libs/resume_and_cover_builder/resume_style}/__init__.py (100%)
 rename src/{ai_hawk => }/libs/resume_and_cover_builder/resume_style/style_cloyola.css (100%)
 rename src/{ai_hawk => }/libs/resume_and_cover_builder/resume_style/style_josylad_blue.css (100%)
 rename src/{ai_hawk => }/libs/resume_and_cover_builder/resume_style/style_josylad_grey.css (100%)
 rename src/{ai_hawk => }/libs/resume_and_cover_builder/resume_style/style_krishnavalliappan.css (100%)
 rename src/{ai_hawk => }/libs/resume_and_cover_builder/resume_style/style_samodum_bold.css (100%)
 rename src/{ai_hawk => }/libs/resume_and_cover_builder/style_manager.py (98%)
 rename src/{ai_hawk => }/libs/resume_and_cover_builder/template_base.py (100%)
 rename src/{ai_hawk => }/libs/resume_and_cover_builder/utils.py (100%)
 rename src/{ai_hawk => }/resume_schemas/job_application_profile.py (100%)
 rename src/{ai_hawk => }/resume_schemas/resume.py (100%)

diff --git a/main.py b/main.py
index 534b16bcb..b04bf4eef 100644
--- a/main.py
+++ b/main.py
@@ -12,9 +12,9 @@
 from selenium.webdriver.chrome.service import Service as ChromeService
 from webdriver_manager.chrome import ChromeDriverManager
 import re
-from src.ai_hawk.libs.resume_and_cover_builder import ResumeFacade, ResumeGenerator, StyleManager
-from src.ai_hawk.resume_schemas.job_application_profile import JobApplicationProfile
-from src.ai_hawk.resume_schemas.resume import Resume
+from src.libs.resume_and_cover_builder import ResumeFacade, ResumeGenerator, StyleManager
+from src.resume_schemas.job_application_profile import JobApplicationProfile
+from src.resume_schemas.resume import Resume
 from src.logging import logger
 from src.utils.chrome_utils import init_browser
 from src.utils.constants import (
@@ -217,20 +217,86 @@ def get_uploads(plain_text_resume_file: Path) -> Dict[str, Path]:
         return uploads
 
 
-def create_cv(parameters: dict, llm_api_key: str):
+def create_cover_letter(parameters: dict, llm_api_key: str):
     """
     Logic to create a CV.
     """
     try:
         logger.info("Generating a CV based on provided parameters.")
 
-        # Load plain text resume
+        # Carica il resume in testo semplice
         with open(parameters["uploads"]["plainTextResume"], "r", encoding="utf-8") as file:
             plain_text_resume = file.read()
 
         style_manager = StyleManager()
         style_manager.choose_style()
+        questions = [
+    inquirer.Text('job_url', message="Please enter the URL of the job description:")
+        ]
+        answers = inquirer.prompt(questions)
+        job_url = answers.get('job_url')
+        resume_generator = ResumeGenerator()
+        resume_object = Resume(plain_text_resume)
+        driver = init_browser()
+        resume_generator.set_resume_object(resume_object)
+        resume_facade = ResumeFacade(            
+            api_key=llm_api_key,
+            style_manager=style_manager,
+            resume_generator=resume_generator,
+            resume_object=resume_object,
+            output_path=Path("data_folder/output"),
+        )
+        resume_facade.set_driver(driver)
+        resume_facade.link_to_job(job_url)
+        result_base64, suggested_name = resume_facade.create_cover_letter()         
+
+        # Decodifica Base64 in dati binari
+        try:
+            pdf_data = base64.b64decode(result_base64)
+        except base64.binascii.Error as e:
+            logger.error("Error decoding Base64: %s", e)
+            raise
 
+        # Definisci il percorso della cartella di output utilizzando `suggested_name`
+        output_dir = Path(parameters["outputFileDirectory"]) / suggested_name
+
+        # Crea la cartella se non esiste
+        try:
+            output_dir.mkdir(parents=True, exist_ok=True)
+            logger.info(f"Cartella di output creata o già esistente: {output_dir}")
+        except IOError as e:
+            logger.error("Error creating output directory: %s", e)
+            raise
+        
+        output_path = output_dir / "cover_letter_tailored.pdf"
+        try:
+            with open(output_path, "wb") as file:
+                file.write(pdf_data)
+            logger.info(f"CV salvato in: {output_path}")
+        except IOError as e:
+            logger.error("Error writing file: %s", e)
+            raise
+    except Exception as e:
+        logger.exception(f"An error occurred while creating the CV: {e}")
+        raise
+
+
+def create_resume_pdf_job_tailored(parameters: dict, llm_api_key: str):
+    """
+    Logic to create a CV.
+    """
+    try:
+        logger.info("Generating a CV based on provided parameters.")
+
+        # Carica il resume in testo semplice
+        with open(parameters["uploads"]["plainTextResume"], "r", encoding="utf-8") as file:
+            plain_text_resume = file.read()
+
+        style_manager = StyleManager()
+        style_manager.choose_style()
+        questions = [inquirer.Text('job_url', message="Please enter the URL of the job description:")]
+        answers = inquirer.prompt(questions)
+        job_url = answers.get('job_url')
         resume_generator = ResumeGenerator()
         resume_object = Resume(plain_text_resume)
         driver = init_browser()
@@ -243,23 +309,32 @@ def create_cv(parameters: dict, llm_api_key: str):
             output_path=Path("data_folder/output"),
         )
         resume_facade.set_driver(driver)
-        result_base64 = resume_facade.create_cover_letter("Software engineer with Java experience")         
+        resume_facade.link_to_job(job_url)
+        result_base64, suggested_name = resume_facade.create_resume_pdf_job_tailored()         
 
-        # Decode Base64 to binary data
+        # Decodifica Base64 in dati binari
         try:
             pdf_data = base64.b64decode(result_base64)
         except base64.binascii.Error as e:
             logger.error("Error decoding Base64: %s", e)
             raise
 
-        # Define the output path
-        output_path = Path(parameters["outputFileDirectory"]) / "resume.pdf"
+        # Definisci il percorso della cartella di output utilizzando `suggested_name`
+        output_dir = Path(parameters["outputFileDirectory"]) / suggested_name
 
-        # Write binary data to the PDF file
+        # Crea la cartella se non esiste
+        try:
+            output_dir.mkdir(parents=True, exist_ok=True)
+            logger.info(f"Cartella di output creata o già esistente: {output_dir}")
+        except IOError as e:
+            logger.error("Error creating output directory: %s", e)
+            raise
+        
+        output_path = output_dir / "resume_tailored.pdf"
         try:
             with open(output_path, "wb") as file:
                 file.write(pdf_data)
-            logger.info(f"CV saved to {output_path}")
+            logger.info(f"CV salvato in: {output_path}")
         except IOError as e:
             logger.error("Error writing file: %s", e)
             raise
@@ -268,24 +343,67 @@ def create_cv(parameters: dict, llm_api_key: str):
         raise
 
 
-def create_cover_letter(parameters: dict, llm_api_key: str):
+def create_resume_pdf(parameters: dict, llm_api_key: str):
     """
-    Logic to create a cover letter.
+    Logic to create a CV.
     """
-    # try:
-    #     logger.info("Generating a cover letter based on provided parameters.")
-    #     # Example implementation for generating the letter
-    #     cover_letter_generator = CoverLetterGenerator(llm_api_key)
-    #     result = cover_letter_generator.generate(parameters)
-    #     output_path = Path(parameters["outputFileDirectory"]) / "cover_letter.docx"
-    #     with open(output_path, "w", encoding="utf-8") as file:
-    #         file.write(result)
-    #     logger.info(f"Cover letter saved to {output_path}")
-    # except Exception as e:
-    #     logger.exception(f"An error occurred while creating the cover letter: {e}")
-    #     raise
-    pass
+    try:
+        logger.info("Generating a CV based on provided parameters.")
+
+        # Carica il resume in testo semplice
+        with open(parameters["uploads"]["plainTextResume"], "r", encoding="utf-8") as file:
+            plain_text_resume = file.read()
+
+        style_manager = StyleManager()
+        style_manager.choose_style()
+        questions = [inquirer.Text('job_url', message="Please enter the URL of the job description:")]
+        answers = inquirer.prompt(questions)
+        job_url = answers.get('job_url')
+        resume_generator = ResumeGenerator()
+        resume_object = Resume(plain_text_resume)
+        driver = init_browser()
+        resume_generator.set_resume_object(resume_object)
+        resume_facade = ResumeFacade(            
+            api_key=llm_api_key,
+            style_manager=style_manager,
+            resume_generator=resume_generator,
+            resume_object=resume_object,
+            output_path=Path("data_folder/output"),
+        )
+        resume_facade.set_driver(driver)
+        resume_facade.link_to_job(job_url)
+        result_base64, suggested_name = resume_facade.create_resume_pdf()         
+
+        # Decodifica Base64 in dati binari
+        try:
+            pdf_data = base64.b64decode(result_base64)
+        except base64.binascii.Error as e:
+            logger.error("Error decoding Base64: %s", e)
+            raise
 
+        # Definisci il percorso della cartella di output utilizzando `suggested_name`
+        output_dir = Path(parameters["outputFileDirectory"]) / suggested_name
+
+        # Crea la cartella se non esiste
+        try:
+            output_dir.mkdir(parents=True, exist_ok=True)
+            logger.info(f"Cartella di output creata o già esistente: {output_dir}")
+        except IOError as e:
+            logger.error("Error creating output directory: %s", e)
+            raise
+        
+        output_path = output_dir / "resume.pdf"
+        try:
+            with open(output_path, "wb") as file:
+                file.write(pdf_data)
+            logger.info(f"CV salvato in: {output_path}")
+        except IOError as e:
+            logger.error("Error writing file: %s", e)
+            raise
+    except Exception as e:
+        logger.exception(f"An error occurred while creating the CV: {e}")
+        raise
+        
 def handle_inquiries(selected_actions: List[str], parameters: dict, llm_api_key: str):
     """
     Decide which function to call based on the selected user actions.
@@ -296,12 +414,18 @@ def handle_inquiries(selected_actions: List[str], parameters: dict, llm_api_key:
     """
     try:
         if selected_actions:
-            if "Create Cover Letter" in selected_actions:
-                logger.info("Creating a cover letter...")
+            if "Generate Resume" in selected_actions:
+                logger.info("Crafting a standout professional resume...")
+                create_resume_pdf(parameters, llm_api_key)
+                
+            if "Generate Resume Tailored for Job Description" in selected_actions:
+                logger.info("Customizing your resume to enhance your job application...")
+                create_resume_pdf_job_tailored(parameters, llm_api_key)
+                
+            if "Generate Tailored Cover Letter for Job Description" in selected_actions:
+                logger.info("Designing a personalized cover letter to enhance your job application...")
                 create_cover_letter(parameters, llm_api_key)
-            if "Create CV" in selected_actions:
-                logger.info("Creating a CV...")
-                create_cv(parameters, llm_api_key)
+
         else:
             logger.warning("No actions selected. Nothing to execute.")
     except Exception as e:
@@ -320,8 +444,9 @@ def prompt_user_action() -> str:
                 'action',
                 message="Select the action you want to perform:",
                 choices=[
-                    "Create Cover Letter",
-                    "Create CV",
+                    "Generate Resume",
+                    "Generate Resume Tailored for Job Description",
+                    "Generate Tailored Cover Letter for Job Description",
                 ],
             ),
         ]
diff --git a/src/ai_hawk/libs/resume_and_cover_builder/llm/llm_job_parser.py b/src/ai_hawk/libs/resume_and_cover_builder/llm/llm_job_parser.py
deleted file mode 100644
index 51762363c..000000000
--- a/src/ai_hawk/libs/resume_and_cover_builder/llm/llm_job_parser.py
+++ /dev/null
@@ -1,181 +0,0 @@
-import os
-import tempfile
-import textwrap
-import time
-from src.ai_hawk.libs.resume_and_cover_builder.utils import LoggerChatModel
-from langchain_core.output_parsers import StrOutputParser
-from langchain_core.prompts import ChatPromptTemplate, PromptTemplate
-from langchain_openai import ChatOpenAI
-from dotenv import load_dotenv
-from concurrent.futures import ThreadPoolExecutor, as_completed
-from loguru import logger
-from pathlib import Path
-from langchain_core.prompt_values import StringPromptValue
-from langchain_core.runnables import RunnablePassthrough
-from langchain_text_splitters import TokenTextSplitter
-from langchain_community.embeddings import OpenAIEmbeddings
-from langchain_community.vectorstores import FAISS
-from lib_resume_builder_AIHawk.config import global_config
-from langchain_community.document_loaders import TextLoader
-import logging
-import re  # Per la parsing regex, soprattutto in `parse_wait_time_from_error_message`
-from requests.exceptions import HTTPError as HTTPStatusError  # Gestione degli errori HTTP
-import openai
-
-# Carica le variabili d'ambiente dal file .env
-load_dotenv()
-
-# Configura il file di log
-log_folder = 'log/resume/gpt_resume'
-if not os.path.exists(log_folder):
-    os.makedirs(log_folder)
-log_path = Path(log_folder).resolve()
-logger.add(log_path / "gpt_resume.log", rotation="1 day", compression="zip", retention="7 days", level="DEBUG")
-
-
-class LLMResumer:
-    def __init__(self, openai_api_key, strings):
-        self.llm_cheap = LoggerChatModel(
-            ChatOpenAI(
-                model_name="gpt-4o-mini", openai_api_key=openai_api_key, temperature=0.4
-            )
-        )
-        self.strings = strings
-        self.llm_embeddings = OpenAIEmbeddings(openai_api_key=openai_api_key)  # Inizializza gli embeddings
-
-    @staticmethod
-    def _preprocess_template_string(template: str) -> str:
-        """
-        Preprocessa la stringa del template rimuovendo gli spazi bianchi iniziali e l'indentazione.
-        Args:
-            template (str): La stringa del template da preprocessare.
-        Returns:
-            str: La stringa del template preprocessata.
-        """
-        return textwrap.dedent(template)
-    
-    def get_job_description_from_url(self, url_job_description):
-        from lib_resume_builder_AIHawk.utils import create_driver_selenium
-        driver = create_driver_selenium()
-        driver.get(url_job_description)
-        time.sleep(3)
-        body_element = driver.find_element("tag name", "body")
-        response = body_element.get_attribute("outerHTML")
-        driver.quit()
-        with tempfile.NamedTemporaryFile(delete=False, suffix=".html", mode="w", encoding="utf-8") as temp_file:
-            temp_file.write(response)
-            temp_file_path = temp_file.name
-        try:
-            loader = TextLoader(temp_file_path, encoding="utf-8", autodetect_encoding=True)
-            document = loader.load()
-        finally:
-            os.remove(temp_file_path)
-        text_splitter = TokenTextSplitter(chunk_size=500, chunk_overlap=50)
-        all_splits = text_splitter.split_documents(document)
-        vectorstore = FAISS.from_documents(documents=all_splits, embedding=self.llm_embeddings)
-        prompt = PromptTemplate(
-            template="""
-            You are an expert job description analyst. Your role is to meticulously analyze and interpret job descriptions. 
-            After analyzing the job description, answer the following question in a clear, and informative manner.
-            
-            Question: {question}
-            Job Description: {context}
-            Answer:
-            """,
-            input_variables=["question", "context"]
-        )
-        def format_docs(docs):
-            return "\n\n".join(doc.page_content for doc in docs)
-        context_formatter = vectorstore.as_retriever() | format_docs
-        question_passthrough = RunnablePassthrough()
-        chain_job_description = prompt | self.llm_cheap | StrOutputParser()
-        summarize_prompt_template = self._preprocess_template_string(self.strings.summarize_prompt_template)
-        prompt_summarize = ChatPromptTemplate.from_template(summarize_prompt_template)
-        chain_summarize = prompt_summarize | self.llm_cheap | StrOutputParser()
-        qa_chain = (
-            {
-                "context": context_formatter,
-                "question": question_passthrough,
-            }
-            | chain_job_description
-            | (lambda output: {"text": output})
-            | chain_summarize
-        )
-        result = qa_chain.invoke("Provide, full job description")
-        self.job_description = result
-
-    def extract_company_name(self):
-        """
-        Estrae il nome dell'azienda dalla descrizione del lavoro.
-        Returns:
-            str: Il nome dell'azienda estratto.
-        """
-        return self._extract_information("What is the company name in this job description?")
-
-    def extract_role(self):
-        """
-        Estrae il ruolo/titolo ricercato dalla descrizione del lavoro.
-        Returns:
-            str: Il ruolo/titolo estratto.
-        """
-        return self._extract_information("What is the role or title being sought in this job description?")
-
-    def extract_location(self):
-        """
-        Estrae la località dalla descrizione del lavoro.
-        Returns:
-            str: La località estratta.
-        """
-        return self._extract_information("What is the location mentioned in this job description?")
-
-    def extract_recruiter_email(self):
-        """
-        Estrae l'email del recruiter dalla descrizione del lavoro.
-        Returns:
-            str: L'email del recruiter estratta.
-        """
-        return self._extract_information("What is the recruiter's email address in this job description?")
-
-    def _extract_information(self, question):
-        """
-        Metodo generico per estrarre informazioni specifiche basate sulla domanda fornita.
-        Args:
-            question (str): La domanda da porre al LLM per l'estrazione.
-        Returns:
-            str: L'informazione estratta.
-        """
-        if not hasattr(self, 'job_description'):
-            raise ValueError("Job description not found. Please run get_job_description_from_url first.")
-
-        prompt = PromptTemplate(
-            template="""
-            You are an expert in extracting specific information from job descriptions. 
-            Carefully read the job description below and provide a clear and concise answer to the question.
-
-            Job Description: {job_description}
-
-            Question: {question}
-            Answer:
-            """,
-            input_variables=["job_description", "question"]
-        )
-
-        chain = prompt | self.llm_cheap | StrOutputParser()
-        result = chain.invoke({
-            "job_description": self.job_description,
-            "question": question
-        })
-        return result.strip()
-
-    def extract_all_details(self):
-        """
-        Estrae il nome dell'azienda, il ruolo, la località e l'email del recruiter dalla descrizione del lavoro.
-        Returns:
-            dict: Un dizionario contenente tutti i dettagli estratti.
-        """
-        details = {}
-        details['company_name'] = self.extract_company_name()
-        details['role'] = self.extract_role()
-        details['location'] = self.extract_location()
-        details['recruiter_email'] = self.extract_recruiter_email()
-        return details
diff --git a/src/ai_hawk/libs/resume_and_cover_builder/resume_style/__init__.py b/src/ai_hawk/libs/resume_and_cover_builder/resume_style/__init__.py
deleted file mode 100644
index e69de29bb..000000000
diff --git a/src/job.py b/src/job.py
index 13ac84ba9..7a48e8df0 100644
--- a/src/job.py
+++ b/src/job.py
@@ -3,8 +3,7 @@
 
 @dataclass
 class Job:
-    id: str = ""
-    title: str = ""
+    role: str = ""
     company: str = ""
     location: str = ""
     link: str = ""
@@ -12,31 +11,18 @@ class Job:
     description: str = ""
     summarize_job_description: str = ""
     recruiter_link: str = ""
-    # TODO: to move these properties to JobApplication
     resume_path: str = ""
     cover_letter_path: str = ""
 
-    def set_summarize_job_description(self, summarize_job_description):
-        logger.debug(f"Setting summarized job description: {summarize_job_description}")
-        self.summarize_job_description = summarize_job_description
-
-    def set_job_description(self, description):
-        logger.debug(f"Setting job description: {description}")
-        self.description = description
-
-    def set_recruiter_link(self, recruiter_link):
-        logger.debug(f"Setting recruiter link: {recruiter_link}")
-        self.recruiter_link = recruiter_link
-
     def formatted_job_information(self):
         """
         Formats the job information as a markdown string.
         """
-        logger.debug(f"Formatting job information for job: {self.title} at {self.company}")
+        logger.debug(f"Formatting job information for job: {self.role} at {self.company}")
         job_information = f"""
         # Job Description
         ## Job Information 
-        - Position: {self.title}
+        - Position: {self.role}
         - At: {self.company}
         - Location: {self.location}
         - Recruiter Profile: {self.recruiter_link or 'Not available'}
diff --git a/src/job_application.py b/src/job_application.py
deleted file mode 100644
index ad3fe0047..000000000
--- a/src/job_application.py
+++ /dev/null
@@ -1,19 +0,0 @@
-from src.job import Job
-
-class JobApplication:
-
-    def __init__(self, job: Job):
-        self.job :Job = job
-        self.application = []
-        self.resume_path = ""
-        self.cover_letter_path = ""
-
-    def save_application_data(self, application_questions: dict):
-        self.application.append(application_questions)
-
-    def set_resume_path(self, resume_path: str):
-        self.resume_path = resume_path
-
-    def set_cover_letter_path(self, cv_path: str):
-        self.cover_letter_path = cv_path
-    
diff --git a/src/ai_hawk/libs/llm_manager.py b/src/libs/llm_manager.py
similarity index 100%
rename from src/ai_hawk/libs/llm_manager.py
rename to src/libs/llm_manager.py
diff --git a/src/ai_hawk/libs/resume_and_cover_builder/__init__.py b/src/libs/resume_and_cover_builder/__init__.py
similarity index 100%
rename from src/ai_hawk/libs/resume_and_cover_builder/__init__.py
rename to src/libs/resume_and_cover_builder/__init__.py
diff --git a/src/ai_hawk/libs/resume_and_cover_builder/config.py b/src/libs/resume_and_cover_builder/config.py
similarity index 100%
rename from src/ai_hawk/libs/resume_and_cover_builder/config.py
rename to src/libs/resume_and_cover_builder/config.py
diff --git a/src/ai_hawk/__init__.py b/src/libs/resume_and_cover_builder/cover_letter_prompt/__init__.py
similarity index 100%
rename from src/ai_hawk/__init__.py
rename to src/libs/resume_and_cover_builder/cover_letter_prompt/__init__.py
diff --git a/src/ai_hawk/libs/resume_and_cover_builder/cover_letter_prompt/strings_feder-cr.py b/src/libs/resume_and_cover_builder/cover_letter_prompt/strings_feder-cr.py
similarity index 97%
rename from src/ai_hawk/libs/resume_and_cover_builder/cover_letter_prompt/strings_feder-cr.py
rename to src/libs/resume_and_cover_builder/cover_letter_prompt/strings_feder-cr.py
index 5113fa6fe..9568da2df 100644
--- a/src/ai_hawk/libs/resume_and_cover_builder/cover_letter_prompt/strings_feder-cr.py
+++ b/src/libs/resume_and_cover_builder/cover_letter_prompt/strings_feder-cr.py
@@ -1,4 +1,4 @@
-from src.ai_hawk.libs.resume_and_cover_builder.template_base import prompt_cover_letter_template
+from src.libs.resume_and_cover_builder.template_base import prompt_cover_letter_template
 
 
 cover_letter_template = """
diff --git a/src/ai_hawk/libs/resume_and_cover_builder/llm/llm_generate_cover_letter_from_job.py b/src/libs/resume_and_cover_builder/llm/llm_generate_cover_letter_from_job.py
similarity index 100%
rename from src/ai_hawk/libs/resume_and_cover_builder/llm/llm_generate_cover_letter_from_job.py
rename to src/libs/resume_and_cover_builder/llm/llm_generate_cover_letter_from_job.py
diff --git a/src/ai_hawk/libs/resume_and_cover_builder/llm/llm_generate_resume.py b/src/libs/resume_and_cover_builder/llm/llm_generate_resume.py
similarity index 99%
rename from src/ai_hawk/libs/resume_and_cover_builder/llm/llm_generate_resume.py
rename to src/libs/resume_and_cover_builder/llm/llm_generate_resume.py
index b324d362d..6b0e44122 100644
--- a/src/ai_hawk/libs/resume_and_cover_builder/llm/llm_generate_resume.py
+++ b/src/libs/resume_and_cover_builder/llm/llm_generate_resume.py
@@ -4,7 +4,7 @@
 # app/libs/resume_and_cover_builder/gpt_resume.py
 import os
 import textwrap
-from src.ai_hawk.libs.resume_and_cover_builder.utils import LoggerChatModel
+from src.libs.resume_and_cover_builder.utils import LoggerChatModel
 from langchain_core.output_parsers import StrOutputParser
 from langchain_core.prompts import ChatPromptTemplate
 from langchain_openai import ChatOpenAI
diff --git a/src/ai_hawk/libs/resume_and_cover_builder/llm/llm_generate_resume_from_job.py b/src/libs/resume_and_cover_builder/llm/llm_generate_resume_from_job.py
similarity index 96%
rename from src/ai_hawk/libs/resume_and_cover_builder/llm/llm_generate_resume_from_job.py
rename to src/libs/resume_and_cover_builder/llm/llm_generate_resume_from_job.py
index 8ab861a61..1cff92064 100644
--- a/src/ai_hawk/libs/resume_and_cover_builder/llm/llm_generate_resume_from_job.py
+++ b/src/libs/resume_and_cover_builder/llm/llm_generate_resume_from_job.py
@@ -3,8 +3,8 @@
 """
 # app/libs/resume_and_cover_builder/llm_generate_resume_from_job.py
 import os
-from src.ai_hawk.libs.resume_and_cover_builder.llm.llm_generate_resume import LLMResumer
-from src.ai_hawk.libs.resume_and_cover_builder.utils import LoggerChatModel
+from src.libs.resume_and_cover_builder.llm.llm_generate_resume import LLMResumer
+from src.libs.resume_and_cover_builder.utils import LoggerChatModel
 from langchain_core.output_parsers import StrOutputParser
 from langchain_core.prompts import ChatPromptTemplate
 from langchain_openai import ChatOpenAI
diff --git a/src/libs/resume_and_cover_builder/llm/llm_job_parser.py b/src/libs/resume_and_cover_builder/llm/llm_job_parser.py
new file mode 100644
index 000000000..08302ff56
--- /dev/null
+++ b/src/libs/resume_and_cover_builder/llm/llm_job_parser.py
@@ -0,0 +1,208 @@
+import os
+import tempfile
+import textwrap
+import time
+import re  # For email validation
+from src.libs.resume_and_cover_builder.utils import LoggerChatModel
+from langchain_core.output_parsers import StrOutputParser
+from langchain_core.prompts import ChatPromptTemplate, PromptTemplate
+from langchain_openai import ChatOpenAI
+from dotenv import load_dotenv
+from concurrent.futures import ThreadPoolExecutor, as_completed
+from loguru import logger
+from pathlib import Path
+from langchain_core.prompt_values import StringPromptValue
+from langchain_core.runnables import RunnablePassthrough
+from langchain_text_splitters import TokenTextSplitter
+from langchain_community.embeddings import OpenAIEmbeddings
+from langchain_community.vectorstores import FAISS
+from lib_resume_builder_AIHawk.config import global_config
+from langchain_community.document_loaders import TextLoader
+from requests.exceptions import HTTPError as HTTPStatusError  # HTTP error handling
+import openai
+
+# Load environment variables from the .env file
+load_dotenv()
+
+# Configure the log file
+log_folder = 'log/resume/gpt_resume'
+if not os.path.exists(log_folder):
+    os.makedirs(log_folder)
+log_path = Path(log_folder).resolve()
+logger.add(log_path / "gpt_resume.log", rotation="1 day", compression="zip", retention="7 days", level="DEBUG")
+
+
+class LLMParser:
+    def __init__(self, openai_api_key):
+        self.llm = LoggerChatModel(
+            ChatOpenAI(
+                model_name="gpt-4o-mini", openai_api_key=openai_api_key, temperature=0.4
+            )
+        )
+        self.llm_embeddings = OpenAIEmbeddings(openai_api_key=openai_api_key)  # Initialize embeddings
+        self.vectorstore = None  # Will be initialized after document loading
+
+    @staticmethod
+    def _preprocess_template_string(template: str) -> str:
+        """
+        Preprocess the template string by removing leading whitespaces and indentation.
+        Args:
+            template (str): The template string to preprocess.
+        Returns:
+            str: The preprocessed template string.
+        """
+        return textwrap.dedent(template)
+    
+    def set_body_html(self, body_html):
+        """
+        Retrieves the job description from HTML, processes it, and initializes the vectorstore.
+        Args:
+            body_html (str): The HTML content to process.
+        """
+
+        # Save the HTML content to a temporary file
+        with tempfile.NamedTemporaryFile(delete=False, suffix=".html", mode="w", encoding="utf-8") as temp_file:
+            temp_file.write(body_html)
+            temp_file_path = temp_file.name 
+        try:
+            loader = TextLoader(temp_file_path, encoding="utf-8", autodetect_encoding=True)
+            document = loader.load()
+            logger.debug("Document successfully loaded.")
+        except Exception as e:
+            logger.error(f"Error during document loading: {e}")
+            raise
+        finally:
+            os.remove(temp_file_path)
+            logger.debug(f"Temporary file removed: {temp_file_path}")
+        
+        # Split the text into chunks
+        text_splitter = TokenTextSplitter(chunk_size=500, chunk_overlap=50)
+        all_splits = text_splitter.split_documents(document)
+        logger.debug(f"Text split into {len(all_splits)} fragments.")
+        
+        # Create the vectorstore using FAISS
+        try:
+            self.vectorstore = FAISS.from_documents(documents=all_splits, embedding=self.llm_embeddings)
+            logger.debug("Vectorstore successfully initialized.")
+        except Exception as e:
+            logger.error(f"Error during vectorstore creation: {e}")
+            raise
+
+    def _retrieve_context(self, query: str, top_k: int = 3) -> str:
+        """
+        Retrieves the most relevant text fragments using the retriever.
+        Args:
+            query (str): The search query.
+            top_k (int): Number of fragments to retrieve.
+        Returns:
+            str: Concatenated text fragments.
+        """
+        if not self.vectorstore:
+            raise ValueError("Vectorstore not initialized. Run extract_job_description first.")
+        
+        retriever = self.vectorstore.as_retriever()
+        retrieved_docs = retriever.get_relevant_documents(query)[:top_k]
+        context = "\n\n".join(doc.page_content for doc in retrieved_docs)
+        logger.debug(f"Context retrieved for query '{query}': {context[:200]}...")  # Log the first 200 characters
+        return context
+    
+    def _extract_information(self, question: str, retrieval_query: str) -> str:
+        """
+        Generic method to extract specific information using the retriever and LLM.
+        Args:
+            question (str): The question to ask the LLM for extraction.
+            retrieval_query (str): The query to use for retrieving relevant context.
+        Returns:
+            str: The extracted information.
+        """
+        context = self._retrieve_context(retrieval_query)
+        
+        prompt = ChatPromptTemplate.from_template(
+            template="""
+            You are an expert in extracting specific information from job descriptions. 
+            Carefully read the job description context below and provide a clear and concise answer to the question.
+
+            Context: {context}
+
+            Question: {question}
+            Answer:
+            """
+        )
+        
+        formatted_prompt = prompt.format(context=context, question=question)
+        logger.debug(f"Formatted prompt for extraction: {formatted_prompt[:200]}...")  # Log the first 200 characters
+        
+        try:
+            chain = prompt | self.llm | StrOutputParser()
+            result = chain.invoke({"context": context, "question": question})
+            extracted_info = result.strip()
+            logger.debug(f"Extracted information: {extracted_info}")
+            return extracted_info
+        except Exception as e:  
+            logger.error(f"Error during information extraction: {e}")
+            return ""
+    
+    def extract_job_description(self) -> str:
+        """
+        Extracts the company name from the job description.
+        Returns:
+            str: The extracted job description.
+        """
+        question = "What is the job description of the company?"
+        retrieval_query = "Job description"
+        logger.debug("Starting job description extraction.")
+        return self._extract_information(question, retrieval_query)
+    
+    def extract_company_name(self) -> str:
+        """
+        Extracts the company name from the job description.
+        Returns:
+            str: The extracted company name.
+        """
+        question = "What is the company's name?"
+        retrieval_query = "Company name"
+        logger.debug("Starting company name extraction.")
+        return self._extract_information(question, retrieval_query)
+    
+    def extract_role(self) -> str:
+        """
+        Extracts the sought role/title from the job description.
+        Returns:
+            str: The extracted role/title.
+        """
+        question = "What is the role or title sought in this job description?"
+        retrieval_query = "Job title"
+        logger.debug("Starting role/title extraction.")
+        return self._extract_information(question, retrieval_query)
+    
+    def extract_location(self) -> str:
+        """
+        Extracts the location from the job description.
+        Returns:
+            str: The extracted location.
+        """
+        question = "What is the location mentioned in this job description?"
+        retrieval_query = "Location"
+        logger.debug("Starting location extraction.")
+        return self._extract_information(question, retrieval_query)
+    
+    def extract_recruiter_email(self) -> str:
+        """
+        Extracts the recruiter's email from the job description.
+        Returns:
+            str: The extracted recruiter's email.
+        """
+        question = "What is the recruiter's email address in this job description?"
+        retrieval_query = "Recruiter email"
+        logger.debug("Starting recruiter email extraction.")
+        email = self._extract_information(question, retrieval_query)
+        
+        # Validate the extracted email using regex
+        email_regex = r'[\w\.-]+@[\w\.-]+\.\w+'
+        if re.match(email_regex, email):
+            logger.debug("Valid recruiter's email.")
+            return email
+        else:
+            logger.warning("Invalid or not found recruiter's email.")
+            return ""
+ 
diff --git a/src/ai_hawk/libs/resume_and_cover_builder/module_loader.py b/src/libs/resume_and_cover_builder/module_loader.py
similarity index 100%
rename from src/ai_hawk/libs/resume_and_cover_builder/module_loader.py
rename to src/libs/resume_and_cover_builder/module_loader.py
diff --git a/src/ai_hawk/libs/resume_and_cover_builder/resume_facade.py b/src/libs/resume_and_cover_builder/resume_facade.py
similarity index 56%
rename from src/ai_hawk/libs/resume_and_cover_builder/resume_facade.py
rename to src/libs/resume_and_cover_builder/resume_facade.py
index 39491c407..0119814d8 100644
--- a/src/ai_hawk/libs/resume_and_cover_builder/resume_facade.py
+++ b/src/libs/resume_and_cover_builder/resume_facade.py
@@ -1,13 +1,15 @@
 """
-This module contains the FacadeManager class, which is responsible for managing the interaction between the user and the other components of the application.
+This module contains the FacadeManager class, which is responsible for managing the interaction between the user and other components of the application.
 """
 # app/libs/resume_and_cover_builder/manager_facade.py
-import logging
-import os
-
+import hashlib
 import inquirer
 from pathlib import Path
 
+from loguru import logger
+
+from src.libs.resume_and_cover_builder.llm.llm_job_parser import LLMParser
+from src.job import Job
 from src.utils.chrome_utils import HTML_to_PDF
 from .config import global_config
 
@@ -33,7 +35,7 @@ def __init__(self, api_key, style_manager, resume_generator, resume_object, outp
         self.style_manager = style_manager
         self.resume_generator = resume_generator
         self.resume_generator.set_resume_object(resume_object)
-        self.selected_style = None  # Proprietà per memorizzare lo stile selezionato
+        self.selected_style = None  # Property to store the selected style
     
     def set_driver(self, driver):
          self.driver = driver
@@ -76,36 +78,88 @@ def choose_style(self) -> None:
         formatted_choices = self.style_manager.format_choices(styles)
         selected_choice = self.prompt_user(formatted_choices, "Which style would you like to adopt?")
         self.selected_style = selected_choice.split(' (')[0]
+        
+    def link_to_job(self, job_url):
+        self.driver.get(job_url)
+        self.driver.implicitly_wait(10)
+        body_element = self.driver.find_element("tag name", "body")
+        body_element = body_element.get_attribute("outerHTML")
+        self.llm_job_parser = LLMParser(openai_api_key=global_config.API_KEY)
+        self.llm_job_parser.set_body_html(body_element)
+
+        self.job = Job()
+        self.job.role = self.llm_job_parser.extract_role()
+        self.job.company = self.llm_job_parser.extract_company_name()
+        self.job.description = self.llm_job_parser.extract_job_description()
+        self.job.location = self.llm_job_parser.extract_location()
+        self.job.link = job_url
+        logger.info(f"Extracting job details from URL: {job_url}")
 
-    def create_resume_pdf(self, job_description_text=None) -> bytes:
+
+    def create_resume_pdf_job_tailored(self) -> tuple[bytes, str]:
         """
         Create a resume PDF using the selected style and the given job description text.
         Args:
+            job_url (str): The job URL to generate the hash for.
             job_description_text (str): The job description text to include in the resume.
         Returns:
-            bytes: The PDF content as bytes.
+            tuple: A tuple containing the PDF content as bytes and the unique filename.
         """
         if self.selected_style is None:
-            raise ValueError("Devi scegliere uno stile prima di generare il PDF.")
+            raise ValueError("You must choose a style before generating the PDF.")
         
         style_path = self.style_manager.get_style_path(self.selected_style)
 
-        if job_description_text is None:
-            html_resume = self.resume_generator.create_resume(style_path)
-        else:
-            html_resume = self.resume_generator.create_resume_job_description_text(style_path, job_description_text)
+        html_resume = self.resume_generator.create_resume_job_description_text(style_path, self.job.description)
+
+        # Generate a unique name using the job URL hash
+        suggested_name = hashlib.md5(self.job.link.encode()).hexdigest()[:10]
+        
         result = HTML_to_PDF(html_resume, self.driver)
         self.driver.quit()
-        return result
+        return result, suggested_name
     
-    def create_cover_letter(self, job_description_text: str) -> None:
+    
+    
+    def create_resume_pdf(self) -> tuple[bytes, str]:
+        """
+        Create a resume PDF using the selected style and the given job description text.
+        Args:
+            job_url (str): The job URL to generate the hash for.
+            job_description_text (str): The job description text to include in the resume.
+        Returns:
+            tuple: A tuple containing the PDF content as bytes and the unique filename.
         """
-        Create a cover letter based on the given job description text and format.
+        
+        if self.selected_style is None:
+            raise ValueError("You must choose a style before generating the PDF.")
+        
+        style_path = self.style_manager.get_style_path(self.selected_style)
+        html_resume = self.resume_generator.create_resume(style_path)
+        suggested_name = hashlib.md5(self.job.link.encode()).hexdigest()[:10]
+        result = HTML_to_PDF(html_resume, self.driver)
+        self.driver.quit()
+        return result, suggested_name
+
+    def create_cover_letter(self) -> tuple[bytes, str]:
+        """
+        Create a cover letter based on the given job description text and job URL.
         Args:
+            job_url (str): The job URL to generate the hash for.
             job_description_text (str): The job description text to include in the cover letter.
+        Returns:
+            tuple: A tuple containing the PDF content as bytes and the unique filename.
         """
+        if self.selected_style is None:
+            raise ValueError("You must choose a style before generating the PDF.")
+        
         style_path = self.style_manager.get_style_path()
-        cover_letter_html = self.resume_generator.create_cover_letter_job_description(style_path, job_description_text)
+        cover_letter_html = self.resume_generator.create_cover_letter_job_description(style_path, self.job.description)
+
+        # Generate a unique name using the job URL hash
+        suggested_name = hashlib.md5(self.job.link.encode()).hexdigest()[:10]
+
+        
         result = HTML_to_PDF(cover_letter_html, self.driver)
         self.driver.quit()
-        return result
+        return result, suggested_name
\ No newline at end of file
diff --git a/src/ai_hawk/libs/resume_and_cover_builder/resume_generator.py b/src/libs/resume_and_cover_builder/resume_generator.py
similarity index 85%
rename from src/ai_hawk/libs/resume_and_cover_builder/resume_generator.py
rename to src/libs/resume_and_cover_builder/resume_generator.py
index 6cd5a5816..8844b2876 100644
--- a/src/ai_hawk/libs/resume_and_cover_builder/resume_generator.py
+++ b/src/libs/resume_and_cover_builder/resume_generator.py
@@ -4,9 +4,9 @@
 # app/libs/resume_and_cover_builder/resume_generator.py
 from string import Template
 from typing import Any
-from src.ai_hawk.libs.resume_and_cover_builder.llm.llm_generate_resume import LLMResumer
-from src.ai_hawk.libs.resume_and_cover_builder.llm.llm_generate_resume_from_job import LLMResumeJobDescription
-from src.ai_hawk.libs.resume_and_cover_builder.llm.llm_generate_cover_letter_from_job import LLMCoverLetterJobDescription
+from src.libs.resume_and_cover_builder.llm.llm_generate_resume import LLMResumer
+from src.libs.resume_and_cover_builder.llm.llm_generate_resume_from_job import LLMResumeJobDescription
+from src.libs.resume_and_cover_builder.llm.llm_generate_cover_letter_from_job import LLMCoverLetterJobDescription
 from .module_loader import load_module
 from .config import global_config
 
@@ -41,4 +41,7 @@ def create_cover_letter_job_description(self, style_path: str, job_description_t
         gpt_answerer.set_job_description_from_text(job_description_text)
         cover_letter_html = gpt_answerer.generate_cover_letter()
         template = Template(global_config.html_template)
-        return template.substitute(body=cover_letter_html, style_path=style_path)
\ No newline at end of file
+        return template.substitute(body=cover_letter_html, style_path=style_path)
+    
+    
+    
\ No newline at end of file
diff --git a/src/ai_hawk/libs/resume_and_cover_builder/cover_letter_prompt/__init__.py b/src/libs/resume_and_cover_builder/resume_job_description_prompt/__init__.py
similarity index 100%
rename from src/ai_hawk/libs/resume_and_cover_builder/cover_letter_prompt/__init__.py
rename to src/libs/resume_and_cover_builder/resume_job_description_prompt/__init__.py
diff --git a/src/ai_hawk/libs/resume_and_cover_builder/resume_job_description_prompt/strings_feder-cr.py b/src/libs/resume_and_cover_builder/resume_job_description_prompt/strings_feder-cr.py
similarity index 100%
rename from src/ai_hawk/libs/resume_and_cover_builder/resume_job_description_prompt/strings_feder-cr.py
rename to src/libs/resume_and_cover_builder/resume_job_description_prompt/strings_feder-cr.py
diff --git a/src/ai_hawk/libs/resume_and_cover_builder/resume_job_description_prompt/__init__.py b/src/libs/resume_and_cover_builder/resume_prompt/__init__.py
similarity index 100%
rename from src/ai_hawk/libs/resume_and_cover_builder/resume_job_description_prompt/__init__.py
rename to src/libs/resume_and_cover_builder/resume_prompt/__init__.py
diff --git a/src/ai_hawk/libs/resume_and_cover_builder/resume_prompt/strings_feder-cr.py b/src/libs/resume_and_cover_builder/resume_prompt/strings_feder-cr.py
similarity index 100%
rename from src/ai_hawk/libs/resume_and_cover_builder/resume_prompt/strings_feder-cr.py
rename to src/libs/resume_and_cover_builder/resume_prompt/strings_feder-cr.py
diff --git a/src/ai_hawk/libs/resume_and_cover_builder/resume_prompt/__init__.py b/src/libs/resume_and_cover_builder/resume_style/__init__.py
similarity index 100%
rename from src/ai_hawk/libs/resume_and_cover_builder/resume_prompt/__init__.py
rename to src/libs/resume_and_cover_builder/resume_style/__init__.py
diff --git a/src/ai_hawk/libs/resume_and_cover_builder/resume_style/style_cloyola.css b/src/libs/resume_and_cover_builder/resume_style/style_cloyola.css
similarity index 100%
rename from src/ai_hawk/libs/resume_and_cover_builder/resume_style/style_cloyola.css
rename to src/libs/resume_and_cover_builder/resume_style/style_cloyola.css
diff --git a/src/ai_hawk/libs/resume_and_cover_builder/resume_style/style_josylad_blue.css b/src/libs/resume_and_cover_builder/resume_style/style_josylad_blue.css
similarity index 100%
rename from src/ai_hawk/libs/resume_and_cover_builder/resume_style/style_josylad_blue.css
rename to src/libs/resume_and_cover_builder/resume_style/style_josylad_blue.css
diff --git a/src/ai_hawk/libs/resume_and_cover_builder/resume_style/style_josylad_grey.css b/src/libs/resume_and_cover_builder/resume_style/style_josylad_grey.css
similarity index 100%
rename from src/ai_hawk/libs/resume_and_cover_builder/resume_style/style_josylad_grey.css
rename to src/libs/resume_and_cover_builder/resume_style/style_josylad_grey.css
diff --git a/src/ai_hawk/libs/resume_and_cover_builder/resume_style/style_krishnavalliappan.css b/src/libs/resume_and_cover_builder/resume_style/style_krishnavalliappan.css
similarity index 100%
rename from src/ai_hawk/libs/resume_and_cover_builder/resume_style/style_krishnavalliappan.css
rename to src/libs/resume_and_cover_builder/resume_style/style_krishnavalliappan.css
diff --git a/src/ai_hawk/libs/resume_and_cover_builder/resume_style/style_samodum_bold.css b/src/libs/resume_and_cover_builder/resume_style/style_samodum_bold.css
similarity index 100%
rename from src/ai_hawk/libs/resume_and_cover_builder/resume_style/style_samodum_bold.css
rename to src/libs/resume_and_cover_builder/resume_style/style_samodum_bold.css
diff --git a/src/ai_hawk/libs/resume_and_cover_builder/style_manager.py b/src/libs/resume_and_cover_builder/style_manager.py
similarity index 98%
rename from src/ai_hawk/libs/resume_and_cover_builder/style_manager.py
rename to src/libs/resume_and_cover_builder/style_manager.py
index 54a317052..d6aa23e80 100644
--- a/src/ai_hawk/libs/resume_and_cover_builder/style_manager.py
+++ b/src/libs/resume_and_cover_builder/style_manager.py
@@ -20,7 +20,7 @@ def __init__(self):
         project_root = current_file.parent.parent.parent.parent  # Adatta se la struttura cambia
         
         # Imposta la directory degli stili in modo robusto
-        self.styles_directory = project_root / "ai_hawk" / "libs" / "resume_and_cover_builder" / "resume_style"
+        self.styles_directory = project_root / "src" / "libs" / "resume_and_cover_builder" / "resume_style"
         
         logging.debug(f"Project root determinato come: {project_root}")
         logging.debug(f"Directory degli stili impostata su: {self.styles_directory}")
diff --git a/src/ai_hawk/libs/resume_and_cover_builder/template_base.py b/src/libs/resume_and_cover_builder/template_base.py
similarity index 100%
rename from src/ai_hawk/libs/resume_and_cover_builder/template_base.py
rename to src/libs/resume_and_cover_builder/template_base.py
diff --git a/src/ai_hawk/libs/resume_and_cover_builder/utils.py b/src/libs/resume_and_cover_builder/utils.py
similarity index 100%
rename from src/ai_hawk/libs/resume_and_cover_builder/utils.py
rename to src/libs/resume_and_cover_builder/utils.py
diff --git a/src/ai_hawk/resume_schemas/job_application_profile.py b/src/resume_schemas/job_application_profile.py
similarity index 100%
rename from src/ai_hawk/resume_schemas/job_application_profile.py
rename to src/resume_schemas/job_application_profile.py
diff --git a/src/ai_hawk/resume_schemas/resume.py b/src/resume_schemas/resume.py
similarity index 100%
rename from src/ai_hawk/resume_schemas/resume.py
rename to src/resume_schemas/resume.py