app.py

from langchain.chat_models import ChatOpenAI
from langchain.schema import AIMessage, HumanMessage
import openai
import gradio as gr
import os

os.environ["OPENAI_API_KEY"] = os.getenv('OPENAI_API_KEY')
llm = ChatOpenAI(temperature=1.0, model='gpt-3.5-turbo-0613')

question_json = os.getenv('QUESTION_JSON')
cv_json = os.getenv('CV_JSON')

def predict(message, history):
    if find(message):
      # prompt = (
      # # f"As Jisu(she/her/hers)'s personal assistant,"
      # # f"Given that: {question_json}, How can I assist with information on: {message}"
      # )
     
    # prompt = "As Jisu(she/her/hers)'s personal assistant, Given that: {}, How can I assist with information on: {}".format(question_json, message)
        prompt = os.env('PREDICT_PROMPT').format(question_json, message)
          
        response = llm([HumanMessage(content=prompt)])
          
        return response.content
      
    prompt = (
        # os.getenv('PREDICT_PROMPT1')
        f"As Jisu(she/her/hers)'s personal assistant,"
        f"Given that: {cv_json}, How can I assist with information on: {message}"
        f"If source does not contains relevant information, I will state that the information is not available."
    )
        
    response = llm([HumanMessage(content=prompt)])
    return response.content

def find(message):
    prompt = (
        "Given the list of questions about Jisu's CV: \n"
        "- What are Jisu's current projects?\n"
        "- What are Jisu's publications?\n"
        "- How can I reach out to Jisu?\n"
        f"Determine if the following query matches any of the topics above: '{message}'. Answer 'Yes' if it matches, otherwise answer 'No'."
    )
    
    response = llm([HumanMessage(content=prompt)])
    if response.content.strip() == 'Yes':
        return True
    else:
        return False

# Example inputs as buttons
examples = [
    "What are Jisu's current projects?",
    "What are Jisu's publications?",
    "How can I reach out to Jisu?",
    # "How is the answer generated?"
]

with gr.Blocks(theme='gradio/soft', fill_height=True) as demo:
    gr.Markdown(
    """
    <img src="http://jisulog.kim/profile.png" alt="Profile Image" style="width: 200px; height: auto; border-radius: 50%;">
    
    # 😊 Hi, I am Jisu Kim!

    I am an MS candidate in the **Interactive Computing** at 🐝**Georgia Tech**. I am advised by [**Ashok Goel**](https://dilab.gatech.edu/ashok-k-goel/) and [**Richmond Wong**](https://richmondywong.com/), and was previously advised by [**Juho Kim**](https://juhokim.com/) at 🪿**KAIST**. 
    
    My research interests lie at the intersection of artificial intelligence (AI) and human-computer interaction (HCI). I am focused on enhancing both productivity tools and creativity support tools in learning environments. My goal is to develop AI technologies that enrich the learning experience and enhance human-AI interaction. Driven by my passion for creating human-centric AI technologies, I am applying to Ph.D. programs for Fall 2025!

    [**LinkedIn**](https://www.linkedin.com/in/jisulog/) | [**Twitter**](https://x.com/jisukiim?s=21) | [**CV**](https://ddiddu.github.io/JisuKim_CV.pdf) | [**YouTube**](https://youtu.be/btZOScj22jE?si=0zz5y61KNLsBJXcm)

    ---

    # 🤖 Hi, I am Jisu's personal assistant!

    **Ask about Jisu and I will provide you with the information as far as I know.** 

    I am currently under development. If there are errors or improvements, feel free to share with Jisu! You don't know how to reach out to Jisu? **Ask me!**
    """)
    gr.ChatInterface(predict, examples=examples)
    
if __name__ == "__main__":
    demo.launch(share=True)