import gradio as gr
from huggingface_hub import InferenceClient
import pandas as pd

client = InferenceClient("microsoft/phi-4")

clothing_df = pd.read_csv("clothing_database.csv") #load clothing database

def respond(message,history): #function to return the history of messages sent
    messages = [{"role": "system", "content": "You are a clothing assistant. Based on the the user's request, suggest suitable clothing items from the database and return their image paths"}]

    if history:
        messages.extend(history)

    messages.append({"role": "user", "content":message})

#get AI reasoning    
    response = client.chat_completion(messages, max_tokens=200)
    ai_text = response
    return response['choices'][0]['message']['content'].strip()


chatbot = gr.ChatInterface(respond, type="messages", title = "Capstone project") 
# chatbot UI - conversation history and user input


#Load the clothing database
clothing_df = pd.read_csv("clothing_databse.csv")

def

def search_clothing(weather=None, formality=None):
    results = clothing_df
    if weather:
        results = results[results[weather].str.contain(weather, case=False)]
    if formality:
        results = results[results[formality].str.contains(formality, case=False)]
    return results






chatbot.launch()