Upload app.py

app.py

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+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()