| import gradio as gr
|
| import pandas as pd
|
| import random
|
| import time
|
| import google.generativeai as genai
|
| from dotenv import load_dotenv
|
| import os
|
|
|
|
|
| initial_message = [
|
| {
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| "role": "assistant",
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| "content": "👋 Hi! I'm your **AI Growth Assistant**.\n\nCan I help you optimize your e-commerce today?"
|
| }
|
| ]
|
|
|
|
|
|
|
|
|
| load_dotenv()
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| genai.configure(api_key=os.getenv("GEMINI_API_KEY"))
|
| model = genai.GenerativeModel("gemini-3-flash-preview")
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| def build_prompt(message):
|
| prompt = f"""
|
| You are an AI assistant for an E-commerce Prediction System.
|
|
|
| User question:
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| {message}
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|
|
| Answer clearly, in bullet points if helpful.
|
| """
|
| return prompt
|
|
|
| def chat_interface(message, history):
|
| history = history or []
|
|
|
| if not message or message.strip() == "":
|
| return "", history
|
|
|
|
|
| history.append({
|
| "role": "user",
|
| "content": message
|
| })
|
| history.append({
|
| "role": "assistant",
|
| "content": "🤖 <span class='typing'><span></span><span></span><span></span></span>"
|
| })
|
| try:
|
| prompt = build_prompt(message)
|
| response = model.generate_content(prompt)
|
|
|
| if (
|
| response
|
| and response.candidates
|
| and response.candidates[0].content
|
| and response.candidates[0].content.parts
|
| ):
|
| reply = response.candidates[0].content.parts[0].text
|
| else:
|
| reply = "⚠️ AI did not return text content."
|
|
|
| except Exception as e:
|
| reply = f"❌ Gemini API error:\n{str(e)}"
|
|
|
|
|
| history.append({
|
| "role": "assistant",
|
| "content": reply
|
| })
|
|
|
| return "", history
|
|
|
|
|
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|
|
|
