Update app.py

app.py

@@ -1,15 +1,24 @@
-import os
-import fitz
-import docx
+# 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
 
-# Initialize tools
-search_tool = SerperDevTool()
 
-# Resume Extraction Functions
+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:
@@ -17,6 +26,7 @@ def extract_text_from_pdf(file_path):
     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:
@@ -24,110 +34,121 @@ def extract_text_from_docx(file_path):
     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:
-        raise ValueError("Unsupported file format")
-
-# CrewAI Setup
-def setup_crewai(resume_text, location):
-    # Set up agents
-    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."
-    )
+        return "Unsupported file format."
 
-    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."
-    )
 
-    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."""
+
+# 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."
     )
 
-    # Define tasks
-    feedback_task = Task(
-        description= """Give feedback on the resume to make it stand out for recruiters. 
+
+# 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_text}""",
-        expected_output="The overall score of the resume followed by the feedback in bullet points.",
-        agent=resume_feedback
-    )
+        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()
+
 
-    rewrite_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_text}""",
-        expected_output="Resume in markdown format that effectively highlights the candidate's qualifications and experiences",
-        agent=resume_advisor,
-        context=[feedback_task]
+# 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} . 
+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", 
-        agent=job_researcher
-    )
+    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
+
 
-    # Create and run crew
-    crew = Crew(
-        agents=[resume_feedback, resume_advisor, job_researcher],
-        tasks=[feedback_task, rewrite_task, research_task],
-        verbose=True
-    )
-    
-    return crew.kickoff()
-
-# Gradio Interface
-def process_resume(file, location):
-    try:
-        # Extract text
-        resume_text = extract_text_from_resume(file.name)
-        
-        # Process with CrewAI
-        result = setup_crewai(resume_text, location)
-        
-        # Parse results
-        feedback = feedback_task.output.raw.strip("```markdown").strip("```").strip()
-        improved_resume = rewrite_task.output.raw.strip("```markdown").strip("```").strip()
-        jobs = research_task.output.raw.strip("```markdown").strip("```").strip()
-        
-        return feedback, improved_resume, jobs
-    
-    except Exception as e:
-        return str(e), "", ""
 
 with gr.Blocks() as demo:
-    gr.Markdown("# AI Resume Assistant 🤖")
-    
+    gr.Markdown("# Resume Feedback and Job Matching Tool")
     with gr.Row():
         with gr.Column():
-            file_input = gr.File(label="Upload Resume (PDF/DOCX)")
-            location_input = gr.Textbox(label="Preferred Job Location")
-            submit_btn = gr.Button("Process Resume")
-        
+            resume_upload = gr.File(label="Upload Your Resume (PDF or DOCX)")
+            location_input = gr.Textbox(label="Preferred Location", placeholder="e.g., San Francisco")
+            submit_button = gr.Button("Submit")
         with gr.Column():
-            feedback_output = gr.Textbox(label="Feedback", interactive=False)
+            feedback_output = gr.Markdown(label="Resume Feedback")
             improved_resume_output = gr.Markdown(label="Improved Resume")
-            jobs_output = gr.Markdown(label="Recommended Jobs")
-    
-    submit_btn.click(
-        fn=process_resume,
-        inputs=[file_input, location_input],
-        outputs=[feedback_output, improved_resume_output, jobs_output]
+            job_roles_output = gr.Markdown(label="Relevant Job Roles")
+
+    submit_button.click(
+        resume_agent,
+        inputs=[resume_upload, location_input],
+        outputs=[feedback_output, improved_resume_output, job_roles_output]
     )
 
-if __name__ == "__main__":
-    demo.launch()
+demo.launch()
+
+
+