src/vsp/app/1st_gradio.py

import os

# Running the 'ls' command using Python's os module to list files in the current directory
print(os.listdir('/home/user/app'))



import gradio as gr
import nest_asyncio

# Apply nest_asyncio to allow nested event loops
nest_asyncio.apply()

from vsp.app.main import VspDataEnrichment

# Import your custom modules
from vsp.app.scrapers.linkedin_downloader import LinkedinDownloader



async def process_profile(profile_linkedin):
    downloader = LinkedinDownloader()
    enricher = VspDataEnrichment()
    profile = await downloader.fetch_linkedin_data(linkedin_url=profile_linkedin)
    enriched_profile = await enricher.process_linkedin_profile(profile=profile)
    return enriched_profile


async def analyze_profile(profile_linkedin):
    enriched_profile = await process_profile(profile_linkedin)
    # Generate output from enriched_profile
    education_outputs = []
    work_experience_outputs = []

    # Process classified educations
    for idx, edu in enumerate(enriched_profile.classified_educations, 1):
        school = edu.education.school_name
        degree = edu.education.degree
        year = edu.education.end.year if edu.education.end else "N/A"
        classification = edu.classification.output.value
        education_outputs.append(
            f"### Education {idx}\n"
            f"**School:** {school}\n\n"
            f"**Degree:** {degree}\n\n"
            f"**Year:** {year}\n\n"
            f"**Classification:** {classification}\n"
        )

    # Add total years of full-time work experience
    total_experience_years = enriched_profile.full_time_work_experience_years
    experience_by_secondary = enriched_profile.full_time_work_experience_by_secondary

    experience_output = f"### Total Full-Time Work Experience: {total_experience_years} years\n\n"

    if experience_by_secondary:
        experience_output += "### Work Experience by Secondary Job Type:\n"
        for secondary_job_type, years in experience_by_secondary.items():
            experience_output += f"- {secondary_job_type.value}: {years} years\n"

    # Process classified work experiences
    for idx, exp in enumerate(enriched_profile.classified_work_experiences, 1):
        company = exp.position.company_name
        start_year = exp.position.start.year if exp.position.start else "N/A"
        end_year = exp.position.end.year if (exp.position.end and exp.position.end.year) else "Present"
        time_range = f"{start_year} - {end_year}"
        title = exp.position.title
        primary_job_type = exp.work_experience_classification.primary_job_type.value
        secondary_job_type = exp.work_experience_classification.secondary_job_type.value

        work_exp_str = (
            f"### Work Experience {idx}\n"
            f"**Company:** {company}\n\n"
            f"**Time Range:** {time_range}\n\n"
            f"**Title:** {title}\n\n"
            f"**Primary Job Type:** {primary_job_type}\n\n"
            f"**Secondary Job Type:** {secondary_job_type}\n\n"
        )

        # Investing focus
        if exp.investing_focus_asset_class_classification:
            asset_class = exp.investing_focus_asset_class_classification.investing_focus_asset_class.value
            sector = (
                exp.investing_focus_sector_classification.investing_focus_sector.value
                if exp.investing_focus_sector_classification
                else "N/A"
            )
            work_exp_str += f"**Investing Focus (Asset Class):** {asset_class}\n\n"
            work_exp_str += f"**Investing Focus (Sector):** {sector}\n\n"

        # Investment banking classification
        if exp.investment_banking_classification:
            ib_group = exp.investment_banking_classification.investment_banking_group.value
            work_exp_str += f"**Investment Banking Group:** {ib_group}\n"

        work_experience_outputs.append(work_exp_str)

    # Combine outputs
    education_output = "\n\n".join(education_outputs)
    work_experience_output = "\n\n".join(work_experience_outputs)

    full_output = f"# Classified Educations\n\n{education_output}\n\n# Classified Work Experiences\n\n{experience_output}\n\n{work_experience_output}"
    return full_output


def main():
    # Define Gradio interface
    with gr.Blocks() as demo:
        gr.Markdown("# LinkedIn Profile Analyzer")
        gr.Markdown("Enter a LinkedIn profile URL to analyze educational and work experiences.")

        profile_linkedin = gr.Textbox(label="LinkedIn Profile URL")
        analyze_button = gr.Button("Analyze")
        output = gr.Markdown()

        async def on_analyze_click(profile_linkedin):
            if not profile_linkedin:
                return "Please enter a valid LinkedIn Profile URL."
            try:
                result = await analyze_profile(profile_linkedin)
                return result
            except Exception as e:
                return f"An error occurred: {str(e)}"

        analyze_button.click(fn=on_analyze_click, inputs=profile_linkedin, outputs=output)
    demo.launch()


if __name__ == "__main__":
    main()