Update Email Read Allowed.ipynb
This commit is contained in:
Masih Moafi
GitHub
parent
79558a65ce
commit
e1fff1a36d
@ -1,137 +1,230 @@
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{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "1875b60b-7d4c-4e3a-9751-c9432c395590",
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"metadata": {},
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"outputs": [
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{
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"name": "stderr",
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"output_type": "stream",
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"text": [
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"Some weights of the model checkpoint at EleutherAI/gpt-j-6B were not used when initializing GPTJForCausalLM: ['transformer.h.0.attn.bias', 'transformer.h.0.attn.masked_bias', 'transformer.h.1.attn.bias', 'transformer.h.1.attn.masked_bias', 'transformer.h.10.attn.bias', 'transformer.h.10.attn.masked_bias', 'transformer.h.11.attn.bias', 'transformer.h.11.attn.masked_bias', 'transformer.h.12.attn.bias', 'transformer.h.12.attn.masked_bias', 'transformer.h.13.attn.bias', 'transformer.h.13.attn.masked_bias', 'transformer.h.14.attn.bias', 'transformer.h.14.attn.masked_bias', 'transformer.h.15.attn.bias', 'transformer.h.15.attn.masked_bias', 'transformer.h.16.attn.bias', 'transformer.h.16.attn.masked_bias', 'transformer.h.17.attn.bias', 'transformer.h.17.attn.masked_bias', 'transformer.h.18.attn.bias', 'transformer.h.18.attn.masked_bias', 'transformer.h.19.attn.bias', 'transformer.h.19.attn.masked_bias', 'transformer.h.2.attn.bias', 'transformer.h.2.attn.masked_bias', 'transformer.h.20.attn.bias', 'transformer.h.20.attn.masked_bias', 'transformer.h.21.attn.bias', 'transformer.h.21.attn.masked_bias', 'transformer.h.22.attn.bias', 'transformer.h.22.attn.masked_bias', 'transformer.h.23.attn.bias', 'transformer.h.23.attn.masked_bias', 'transformer.h.24.attn.bias', 'transformer.h.24.attn.masked_bias', 'transformer.h.25.attn.bias', 'transformer.h.25.attn.masked_bias', 'transformer.h.26.attn.bias', 'transformer.h.26.attn.masked_bias', 'transformer.h.27.attn.bias', 'transformer.h.27.attn.masked_bias', 'transformer.h.3.attn.bias', 'transformer.h.3.attn.masked_bias', 'transformer.h.4.attn.bias', 'transformer.h.4.attn.masked_bias', 'transformer.h.5.attn.bias', 'transformer.h.5.attn.masked_bias', 'transformer.h.6.attn.bias', 'transformer.h.6.attn.masked_bias', 'transformer.h.7.attn.bias', 'transformer.h.7.attn.masked_bias', 'transformer.h.8.attn.bias', 'transformer.h.8.attn.masked_bias', 'transformer.h.9.attn.bias', 'transformer.h.9.attn.masked_bias']\n",
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"- This IS expected if you are initializing GPTJForCausalLM from the checkpoint of a model trained on another task or with another architecture (e.g. initializing a BertForSequenceClassification model from a BertForPreTraining model).\n",
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"- This IS NOT expected if you are initializing GPTJForCausalLM from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model).\n"
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]
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},
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{
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"name": "stdin",
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"output_type": "stream",
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"text": [
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"Enter the professor's name: Asadpour\n",
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"Enter your research topic: AI\n",
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"Enter your name: Masih\n"
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]
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'use client';
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import { useState, useEffect, useRef } from 'react';
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type Message = {
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text: string;
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sender: 'user' | 'bot';
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};
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export default function Chatbot() {
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const [isOpen, setIsOpen] = useState(false);
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const [messages, setMessages] = useState<Message[]>([]);
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const [inputText, setInputText] = useState('');
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const [isLoading, setIsLoading] = useState(false);
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const chatContainerRef = useRef<HTMLDivElement>(null);
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const handleSendMessage = async () => {
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if (!inputText.trim() || isLoading) return;
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try {
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setIsLoading(true);
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const userMessage = inputText.trim();
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setMessages(prev => [...prev, { text: userMessage, sender: 'user' }]);
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setInputText('');
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// Directly call Ollama API via local tunnel
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const response = await fetch('https://joe-ollama.loca.lt/api/generate', {
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method: 'POST',
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headers: {
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'Content-Type': 'application/json',
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'Authorization': 'Basic ' + btoa('username:password') // Add your auth
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},
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body: JSON.stringify({
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model: 'llama3',
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prompt: userMessage,
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stream: false,
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options: {
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temperature: 0.7,
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max_tokens: 500
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}
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}),
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});
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if (!response.ok) throw new Error('Failed to get response');
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const data = await response.json();
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setMessages(prev => [...prev, { text: data.response, sender: 'bot' }]);
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} catch (error) {
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console.error('Chat error:', error);
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setMessages(prev => [...prev, {
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text: "Sorry, I'm having trouble connecting. Please try again later.",
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sender: 'bot'
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}]);
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} finally {
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setIsLoading(false);
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}
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],
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"source": [
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"from transformers import AutoModelForCausalLM, AutoTokenizer\n",
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"from gtts import gTTS\n",
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"from playsound import playsound\n",
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"import os\n",
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"\n",
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"# Load the tokenizer and model for GPT-J\n",
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"tokenizer = AutoTokenizer.from_pretrained(\"EleutherAI/gpt-j-6B\")\n",
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"model = AutoModelForCausalLM.from_pretrained(\"EleutherAI/gpt-j-6B\")\n",
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"\n",
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"# Set the padding token to the EOS token\n",
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"tokenizer.pad_token = tokenizer.eos_token\n",
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"\n",
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"def generate_email(professor_name, research_topic, user_name):\n",
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" # Email template\n",
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" prompt = f\"\"\"\n",
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" Dear Professor {professor_name},\n",
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"\n",
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" I am writing to express my interest in pursuing research under your guidance. My research topic revolves around {research_topic}.\n",
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"\n",
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" I believe that your work in this area is groundbreaking, and I am eager to contribute to your ongoing projects.\n",
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"\n",
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" Best regards,\n",
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" {user_name}\n",
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" \"\"\"\n",
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" # Tokenize input\n",
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" inputs = tokenizer(prompt, return_tensors=\"pt\", truncation=True, padding=True)\n",
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" # Generate email with controlled randomness\n",
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" output = model.generate(\n",
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" inputs[\"input_ids\"],\n",
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" attention_mask=inputs[\"attention_mask\"],\n",
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" max_length=len(inputs[\"input_ids\"][0]) + 100,\n",
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" do_sample=True, # Set to True to use temperature and top_p\n",
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" temperature=0.7,\n",
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" top_p=0.9,\n",
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" pad_token_id=tokenizer.eos_token_id\n",
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" )\n",
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" # Decode and return the text\n",
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" generated_email = tokenizer.decode(output[0], skip_special_tokens=True)\n",
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" return generated_email.strip()\n",
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"\n",
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"def text_to_speech(text, output_file=\"email.mp3\", lang='en'):\n",
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" try:\n",
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" if os.path.exists(output_file):\n",
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" os.remove(output_file)\n",
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" tts = gTTS(text, lang=lang)\n",
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" tts.save(output_file)\n",
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" print(f\"Speech saved to {output_file}\")\n",
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" except Exception as e:\n",
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" print(f\"Error generating speech: {e}\")\n",
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"\n",
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"def play_sound(file_path):\n",
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" if not os.path.exists(file_path):\n",
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" print(\"File not found.\")\n",
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" return\n",
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" try:\n",
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" # Using playsound\n",
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" playsound(file_path)\n",
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" print(\"\\nEmail is being read aloud.\")\n",
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" except Exception as e:\n",
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" print(f\"Error playing sound with playsound: {e}\")\n",
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"\n",
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"# Input data\n",
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"professor_name = input(\"Enter the professor's name: \")\n",
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"research_topic = input(\"Enter your research topic: \")\n",
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"user_name = input(\"Enter your name: \")\n",
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"\n",
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"# Generate and print the email\n",
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"email = generate_email(professor_name, research_topic, user_name)\n",
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"print(\"\\nGenerated Email:\\n\")\n",
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"print(email)\n",
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"\n",
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"# Convert the email to speech\n",
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"text_to_speech(email)\n",
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"\n",
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"# Play the generated speech\n",
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"play_sound(\"email.mp3\")"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "89bc527f-4f37-44d3-8454-52a980cf6038",
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"metadata": {},
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"outputs": [],
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"source": []
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3 (ipykernel)",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.8.19"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 5
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};
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useEffect(() => {
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if (chatContainerRef.current) {
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chatContainerRef.current.scrollTop = chatContainerRef.current.scrollHeight;
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}
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}, [messages]);
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return (
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<div style={{ position: 'fixed', bottom: '20px', right: '29.6px', zIndex: 1000 }}>
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{isOpen && (
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<div style={chatWindowStyle}>
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<div style={headerStyle}>
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<div style={titleStyle}>Chat with Joe's AI</div>
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<button onClick={() => setIsOpen(false)} style={closeButtonStyle}>
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×
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</button>
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</div>
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<div ref={chatContainerRef} style={messageContainerStyle}>
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{messages.map((msg, index) => (
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<div key={index} style={messageBubbleStyle(msg.sender)}>
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<span style={textStyle(msg.sender)}>
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{msg.text}
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</span>
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</div>
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))}
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{isLoading && (
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<div style={loadingStyle}>
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<div className="dot-flashing" />
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</div>
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)}
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</div>
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<div style={inputContainerStyle}>
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<input
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type="text"
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value={inputText}
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onChange={(e) => setInputText(e.target.value)}
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onKeyPress={(e) => e.key === 'Enter' && handleSendMessage()}
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style={inputStyle}
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placeholder="Ask me anything..."
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disabled={isLoading}
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/>
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<button
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onClick={handleSendMessage}
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style={sendButtonStyle}
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disabled={isLoading}
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>
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{isLoading ? '...' : 'Send'}
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</button>
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</div>
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</div>
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)}
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{!isOpen && (
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<button
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onClick={() => setIsOpen(true)}
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style={toggleButtonStyle}
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>
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💬
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</button>
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)}
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</div>
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);
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}
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// Style constants
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const chatWindowStyle = {
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width: '350px',
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border: '1px solid #e5e7eb',
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borderRadius: '12px',
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padding: '16px',
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backgroundColor: '#ffffff',
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boxShadow: '0 4px 6px rgba(0, 0, 0, 0.1)',
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};
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const headerStyle = {
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display: 'flex',
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justifyContent: 'space-between',
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alignItems: 'center',
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marginBottom: '16px',
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};
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const titleStyle = {
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fontSize: '18px',
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fontWeight: '600',
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color: '#1f2937',
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};
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const closeButtonStyle = {
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padding: '8px',
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borderRadius: '50%',
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border: 'none',
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backgroundColor: '#31616c',
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color: '#fff',
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cursor: 'pointer',
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fontWeight: '600',
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width: '32px',
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height: '32px',
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display: 'flex',
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alignItems: 'center',
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justifyContent: 'center',
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};
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const messageContainerStyle = {
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height: '330px',
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overflowY: 'auto',
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marginBottom: '16px',
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padding: '8px',
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backgroundColor: '#f3f4f6',
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borderRadius: '8px',
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};
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const messageBubbleStyle = (sender: 'user' | 'bot') => ({
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textAlign: sender === 'user' ? 'right' : 'left',
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margin: '8px 0',
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});
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const textStyle = (sender: 'user' | 'bot') => ({
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display: 'inline-block',
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padding: '8px 12px',
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borderRadius: '12px',
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backgroundColor: sender === 'user' ? '#31616c' : '#e5e7eb',
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color: sender === 'user' ? '#fff' : '#1f2937',
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maxWidth: '80%',
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wordWrap: 'break-word' as const,
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});
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const inputContainerStyle = {
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display: 'flex',
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gap: '8px',
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};
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const inputStyle = {
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flex: 1,
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padding: '8px',
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borderRadius: '8px',
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border: '1px solid #e5e7eb',
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backgroundColor: '#ffffff',
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color: '#1f2937',
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outline: 'none',
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};
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const sendButtonStyle = {
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padding: '8px 16px',
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borderRadius: '8px',
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border: 'none',
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backgroundColor: '#31616c',
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color: '#fff',
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cursor: 'pointer',
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fontWeight: '600',
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};
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const toggleButtonStyle = {
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padding: '12px',
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borderRadius: '50%',
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border: 'none',
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backgroundColor: '#31616c',
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color: '#fff',
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cursor: 'pointer',
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boxShadow: '0 4px 6px rgba(0, 0, 0, 0.1)',
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display: 'flex',
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alignItems: 'center',
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justifyContent: 'center',
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width: '48px',
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height: '48px',
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};
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const loadingStyle = {
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display: 'flex',
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justifyContent: 'center',
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padding: '8px',
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};
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