app.py

import gradio as gr
from openai import OpenAI
from dotenv import load_dotenv
import os 

# Try to load .env file if it exists (for local development)
load_dotenv()

# Initialize OpenAI client - will use OPENAI_API_KEY from environment
# For Hugging Face Spaces, set this as a secret in the Space settings
api_key = os.getenv("OPENAI_API_KEY")
if not api_key:
    raise ValueError("OPENAI_API_KEY not found. Please set it in your environment variables or Hugging Face Space secrets.")

client = OpenAI(api_key=api_key)

# File paths - adjust based on where the app runs
# For Hugging Face Spaces, files should be in the root or adjust paths accordingly
cv_path = "src/cv/me.txt" if os.path.exists("src/cv/me.txt") else "cv/me.txt"
avatar_path = "src/cv/avatar.jpeg" if os.path.exists("src/cv/avatar.jpeg") else "cv/avatar.jpeg"
projects_base = "src/projects_images" if os.path.exists("src/projects_images") else "projects_images"

projects = [
    {"image": f"{projects_base}/s_up.jpeg", "title": "Ai Recommendation System"},
    {"image": f"{projects_base}/llm.jpeg", "title": "LLM Automation"},
    {"image": f"{projects_base}/bi.png", "title": "BI"},
    {"image": f"{projects_base}/robot.png", "title": "Robot Arm Control With Ros Python and AI "},
]

with open(cv_path, "r") as f: 
    cv_text = f.read()

system_prompt = f"""
Your name is Alexander.You are acting as Alexander Todorov. You will answer questions related to your career, skills, work experience, and education. \
Questions will be asked by visitors, headhunters, or recruiters about potential job opportunities. \
Respond professionally and use professional language. \
Answer only questions that are directly related to your CV. If you do not find the answer in your CV, respond with: \
"I can only answer questions about my CV."

CV: {cv_text}
With this context, please chat with the user, always staying in character as Alexander Todorov.
"""

def chat(message, history):
    messages = [{"role":"system", "content":system_prompt}] + history + [{"role":"user", "content":message}]
    response = client.chat.completions.create(model="gpt-4o-mini", messages=messages)
    return response.choices[0].message.content


with gr.Blocks() as ui:
    # name and job title    
    with gr.Row():
        with gr.Column(scale=1):
            gr.Markdown('<div style="font-size:36px; font-weight:bold;">Alexander Todorov</div>')

        with gr.Column(scale=4):    
            gr.Markdown("""
            <a href="https://www.linkedin.com/in/alexander-t-50864a139" target="_blank">
                <img src="https://cdn-icons-png.flaticon.com/512/174/174857.png" 
                    alt="LinkedIn" style="width:32px; height:32px;"/>
            </a>
            """)

    # ********************************************************************************************************* 
    
    with gr.Row():
        with gr.Column(scale=1):  # 1 part
            gr.Image(avatar_path, 
                        type="pil", 
                        show_label=False, 
                        height=150, 
                        interactive=False, 
                        container=False, 
                        buttons=[['download', 'share', 'fullscreen']])

        # Right column 75% width
        with gr.Column(scale=3):  # 3 parts
            gr.Markdown("""
            <div style="width:50%">
            <p style="color:#9b9b9b;  margin-bottom:0;font-size:20px;">
            Software and Data Engineer with over five years of experience delivering intelligent, 
            user-focused AI solutions and driving automation and innovation in complex environments.
            </p>
            </div>
            """)
    

    # ******************************************************************************************************************
    # Chatbot 
    gr.Markdown(f'<p style="font-size:28px;font-weight:bold;"> Chat with Me About My CV</p>',
                    elem_id="job-title-light")
    gr.Markdown('<hr style="border:1px solid grey;">', elem_id="custom_divider")
    chatbot = gr.Chatbot(placeholder="<strong>Interactive CV Guide</strong><br>Ask Me Anything", height=300)
    chat_interface = gr.ChatInterface(fn=chat, chatbot=chatbot)
    gr.Markdown('<hr style="border: 1px solid #d3d3d3; margin-top:12px; margin-bottom:12px;">')
    
    # ****************************************************************************************************************
    # Projects 
    gr.Markdown(f'<p style="font-size:28px;font-weight:bold;"> Examples of My Work</p>',
                    elem_id="job-title-light")
    gr.Markdown('<hr style="border:1px solid grey;">', elem_id="custom_divider")
    
    # Projects row 
    with gr.Row():
        for project in projects:
            with gr.Column():  # equal width for each project
                # Project image
                gr.Image(project["image"], 
                            type="pil", 
                            show_label=False, 
                            interactive=False, 
                            height=200, width=350,
                            buttons=[['download', 'share', 'fullscreen']])
                # Project title / text
                gr.Markdown(f"<div style='text-align:center; font-size:16px; margin-top:4px;'>{project['title']}</div>")


if __name__ == "__main__":
    ui.launch()