Delete app (1).py

app (1).py

@@ -1,180 +0,0 @@
-# Warning control
-import warnings
-warnings.filterwarnings('ignore')
-
-
-import fitz  # PyMuPDF for PDF processing
-import docx  # python-docx for DOCX processing
-import gradio as gr
-import os
-from crewai import Agent, Task, Crew
-from crewai_tools import SerperDevTool
-
-
-os.environ['OPENAI_API_KEY'] = os.getenv("openaikey")
-os.environ["OPENAI_MODEL_NAME"] = 'gpt-4o-mini'
-os.environ["SERPER_API_KEY"] = os.getenv("serper_key")
-
-
-
-def extract_text_from_pdf(file_path):
-    """Extracts text from a PDF file using PyMuPDF."""
-    doc = fitz.open(file_path)
-    text = ""
-    for page in doc:
-        text += page.get_text()
-    return text
-
-def extract_text_from_docx(file_path):
-    """Extracts text from a DOCX file using python-docx."""
-    doc = docx.Document(file_path)
-    fullText = []
-    for para in doc.paragraphs:
-        fullText.append(para.text)
-    return "\n".join(fullText)
-
-def extract_text_from_resume(file_path):
-    """Determines file type and extracts text."""
-    if file_path.endswith(".pdf"):
-        return extract_text_from_pdf(file_path)
-    elif file_path.endswith(".docx"):
-        return extract_text_from_docx(file_path)
-    else:
-        return "Unsupported file format."
-
-
-
-# Agent 1: Resume Strategist
-resume_feedback = Agent(
-    role="Professional Resume Advisor",
-    goal="Give feedback on the resume to make it stand out in the job market.",
-    verbose=True,
-    backstory="With a strategic mind and an eye for detail, you excel at providing feedback on resumes to highlight the most relevant skills and experiences."
-    )
-
-
-# Task for Resume Strategist Agent: Align Resume with Job Requirements
-resume_feedback_task = Task(
-    description=(
-        """Give feedback on the resume to make it stand out for recruiters. 
-        Review every section, inlcuding the summary, work experience, skills, and education. Suggest to add relevant sections if they are missing.  
-        Also give an overall score to the resume out of 10.  This is the resume: {resume}"""
-    ),
-    expected_output="The overall score of the resume followed by the feedback in bullet points.",
-    agent=resume_feedback
-)
-
-# Agent 2: Resume Strategist
-resume_advisor = Agent(
-    role="Professional Resume Writer",
-    goal="Based on the feedback recieved from Resume Advisor, make changes to the resume to make it stand out in the job market.",
-    verbose=True,
-    backstory="With a strategic mind and an eye for detail, you excel at refining resumes based on the feedback to highlight the most relevant skills and experiences."
-)
-
-# Task for Resume Strategist Agent: Align Resume with Job Requirements
-resume_advisor_task = Task(
-    description=(
-        """Rewrite the resume based on the feedback to make it stand out for recruiters. You can adjust and enhance the resume but don't make up facts. 
-        Review and update every section, including the summary, work experience, skills, and education to better reflect the candidates abilities. This is the resume: {resume}"""
-    ),
-    expected_output= "Resume in markdown format that effectively highlights the candidate's qualifications and experiences",
-    # output_file="improved_resume.md",
-    context=[resume_feedback_task],
-    agent=resume_advisor
-)
-
-search_tool = SerperDevTool()
-
-
-# Agent 3: Researcher
-job_researcher = Agent(
-    role = "Senior Recruitment Consultant",
-    goal = "Find the 5 most relevant, recently posted jobs based on the improved resume recieved from resume advisor and the location preference",
-    tools = [search_tool],
-    verbose = True,
-    backstory = """As a senior recruitment consultant your prowess in finding the most relevant jobs based on the resume and location preference is unmatched. 
-    You can scan the resume efficiently, identify the most suitable job roles and search for the best suited recently posted open job positions at the preffered location."""
-    )
-
-research_task = Task(
-    description = """Find the 5 most relevant recent job postings based on the resume recieved from resume advisor and location preference. This is the preferred location: {location} . 
-    Use the tools to gather relevant content and shortlist the 5 most relevant, recent, job openings""",
-    expected_output=(
-        "A bullet point list of the 5 job openings, with the appropriate links and detailed description about each job, in markdown format" 
-    ),
-#    output_file="relevant_jobs.md",
-    agent=job_researcher
-)
-
-
-crew = Crew(
-    agents=[resume_feedback, resume_advisor, job_researcher],
-    tasks=[resume_feedback_task, resume_advisor_task, research_task],
-    verbose=True
-)
-
-
-
-def resume_agent(file_path, location):
-    resume_text = extract_text_from_resume(file_path)
-
-    result = crew.kickoff(inputs={"resume": resume_text, "location": location})
-
-        # Extract outputs
-    feedback = resume_feedback_task.output.raw.strip("```markdown").strip("```").strip()
-    improved_resume = resume_advisor_task.output.raw.strip("```markdown").strip("```").strip()
-    job_roles = research_task.output.raw.strip("```markdown").strip("```").strip()
-
-    return feedback, improved_resume, job_roles
-        
-
-# Gradio Interface
-with gr.Blocks() as demo:
-    gr.Markdown("# Resume Feedback and Job Matching Tool")
-    gr.Markdown("*Expected Runtime: 1 Min*")
-    
-    with gr.Column():
-        with gr.Row():
-            resume_upload = gr.File(label="Upload Your Resume (PDF or DOCX)", height=120)
-            location_input = gr.Textbox(label="Preferred Location", placeholder="e.g., San Francisco")
-            submit_button = gr.Button("Submit")
-        
-        with gr.Column():
-            feedback_output = gr.Markdown(label="Resume Feedback")
-            improved_resume_output = gr.Markdown(label="Improved Resume")
-            job_roles_output = gr.Markdown(label="Relevant Job Roles")
-
-    # Define the click event for the submit button
-    def format_outputs(feedback, improved_resume, job_roles):
-        # Add bold headings to each section
-        feedback_with_heading = f"## Resume Feedback:**\n\n{feedback}"
-        improved_resume_with_heading = f"## Improved Resume:\n\n{improved_resume}"
-        job_roles_with_heading = f"## Relevant Job Roles:\n\n{job_roles}"
-        return feedback_with_heading, improved_resume_with_heading, job_roles_with_heading
-
-
-
-    submit_button.click(
-        lambda: gr.update(value="Processing..."),
-        inputs=[],
-        outputs=submit_button
-    ).then(
-        resume_agent,
-        inputs=[resume_upload, location_input],
-        outputs=[feedback_output, improved_resume_output, job_roles_output]
-    ).then(
-        format_outputs,
-        inputs=[feedback_output, improved_resume_output, job_roles_output],
-        outputs=[feedback_output, improved_resume_output, job_roles_output]
-    ).then(
-        lambda: gr.update(value="Submit"),
-        inputs=[],
-        outputs=submit_button
-    )
-
-demo.queue()
-demo.launch()
-
-
-