app.py

import gradio as gr
from dotenv import load_dotenv

from cv_assistant.agent import Agent

load_dotenv()

agent = Agent(
    faiss_index_path="./content_assets/docs.index",
    faise_store_path="./content_assets/faiss_store.pkl",
)


def answer(query):
    return agent.answer(query=query)


description = """
### Ask about my experience, skills, and education!

I built this using [Gradio](https://gradio.app) and [LangChain](https://langchain.readthedocs.io/en/latest/).
"""
title = "Career Chatbot"

iface = gr.Interface(
    fn=answer,
    inputs=gr.Textbox(
        value="What's his experience in recommender systems?", label="Question"
    ),
    outputs=gr.Textbox(label="Answer"),
    description=description,
    title=title,
    analytics_enabled=True,
    allow_flagging="auto",
)
iface.launch()