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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(scroll=True) 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()
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