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| import os | |
| import gradio as gr | |
| import spaces | |
| from huggingface_hub import InferenceClient,login | |
| client=InferenceClient() | |
| def chat(message: str,history: list[tuple[str, str]]): | |
| #print(history) | |
| print(message) | |
| content = """You are Davor Kondic's resume chatbot. You will be interviewed by people for various positions. | |
| You only know what is in the resume! NOTHING ELSE! | |
| Stay on topic and only answer questions related to what is in the resume. | |
| Make me (Davor) look good! | |
| Here is the resume:""" | |
| resume = """Results-driven Data Science professional with over a decade of experience in extracting actionable insights from data. Proven track record of leveraging data analytics to inform business decisions and drive growth. Passionate about data-driven decision making and staying at the forefront of data science trends. | |
| EDUCATION | |
| o Master of Science in Data Science (In Progress), Northwestern University, Evanston, IL | |
| o Bachelor of Science in Economics (Cum Laude), Northern Illinois University, DeKalb, IL | |
| SKILLS | |
| o Technical: Python, R, SQL, Tableau, Databricks, Hadoop, Excel, GitHub, AI | |
| o Professional: Data Science, Machine Learning, AI Development, Operational Research, Descriptive/Predictive/ Prescriptive Analytics, Data Engineering, Data Warehousing, Data Visualization, Agile Project Management (SCRUM) | |
| PROFESSIONAL EXPERIENCE | |
| AI Developer, Open-Source Foundation Models (2024 - Present) | |
| o Designed and developed LLM AI agents using the Reasoning and Acting framework (ReAct), enabling autonomous decision-making and AI reasoning to solve real-world problems. | |
| o Utilized open-source foundation transformer models, such as Llama 3.1 and Llava Next, to create custom AI solutions for various domains, including: Data Analysis, Image Generation, Image and Document chatbot | |
| o Developed Retrieval Augmented Generation (RAG) AI agents by integrating AI with external tools, such as databases and APIs, to enable private and seamless domain specific AI knowledgebases | |
| o AI Web Application Demos: https://huggingface.co/dkondic | |
| o AI Web Application Code: https://github.com/Dacho688 | |
| Supply Chain Specialist (2022), ALDI Inc., Batavia, IL | |
| Supply Chain Analyst (2023 – 2024), ALDI Inc., Batavia, IL | |
| o Utilized Python's powerful packages and APIs to extract, transform, and load data from various sources, enabling data-driven supply chain optimization. | |
| o Cleaned, prepared, and analyzed logistic and business data to support management's strategic initiatives, demonstrating expertise in data wrangling and analysis. | |
| o Successfully planned demand and inventory for ALDI's 3PW network, utilizing SARIMAX models to forecast sales and inventory levels. | |
| o Developed and maintained end-to-end supply chain network optimization and cost analysis models, presenting findings to management and driving business decisions. | |
| o Designed and implemented a SQL data warehouse and database for ALDI's 3PW network | |
| o Created visually engaging Tableau data visualizations and reports, maintaining a Tableau server team subfolder for seamless distribution. | |
| o Developed and maintained a custom ALDI Python package utilizing Gitlab's version control and package distribution capabilities. | |
| Senior Accounting Data Analyst (Contract), Everywhere Wireless, Chicago, IL (2020) | |
| o Extracted, transformed, and analyzed accounting, inventory, sales, and customer data from multiple sources (Quick Books Online, Fishbowl, V-Tiger) | |
| o Developed and prepared a cash flow budget for the 2020 fiscal year using Excel | |
| o Created an automated data variance analysis script using Python to compare ADP and Open Path data payroll times, streamlining data analysis and reducing manual effort. | |
| o Completed ad hoc data analysis projects to drive decision-making and risk management. | |
| Data Analyst / Compliance Auditor, Alliance for Audited Media, Arlington Heights, IL (2014 – 2019) | |
| o Extracted, transformed, and loaded (ETL) print and digital media data for analysis and audit procedures, ensuring data quality and compliance. | |
| o Cleaned raw media data using various analytical tools (Excel, Python, R, SPSS), demonstrating expertise in data wrangling and manipulation. | |
| o Conducted structured audits to confirm compliance and data quality, mentoring and training new auditors and analysts to enhance team capabilities. | |
| o Assisted in the development of a machine learning model to predict digital ad fraud | |
| """ | |
| messages=[{"role": "system", "content": content+resume}] | |
| for val in history: | |
| if val[0]: | |
| messages.append({"role": "user", "content": val[0]}) | |
| if val[1]: | |
| messages.append({"role": "assistant", "content": val[1]}) | |
| messages.append({"role": "user", "content": message}) | |
| output = client.chat.completions.create( | |
| model="meta-llama/Meta-Llama-3.1-70B-Instruct", | |
| messages=messages, | |
| stream=True, | |
| max_tokens=1024,) | |
| # Collect the response | |
| response = "" | |
| for chunk in output: | |
| response += chunk.choices[0].delta.content or "" | |
| print(response) | |
| return response | |
| demo = gr.ChatInterface(fn=chat, title="Davor's Resume", description="Chat with Davor's resume powered by Llama 3.1 70B.", | |
| stop_btn="Stop Generation", multimodal=False) | |
| if __name__ == "__main__": | |
| demo.launch(share=True) | |