Update Email Read Allowed.ipynb

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Masih Moafi 2025-01-26 15:45:47 +03:30 committed by GitHub
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@ -1,230 +1,110 @@
'use client'; ],
"source": [
import { useState, useEffect, useRef } from 'react'; "from transformers import AutoModelForCausalLM, AutoTokenizer\n",
"from gtts import gTTS\n",
type Message = { "from playsound import playsound\n",
text: string; "import os\n",
sender: 'user' | 'bot'; "\n",
}; "# Load the tokenizer and model for GPT-J\n",
"tokenizer = AutoTokenizer.from_pretrained(\"EleutherAI/gpt-j-6B\")\n",
export default function Chatbot() { "model = AutoModelForCausalLM.from_pretrained(\"EleutherAI/gpt-j-6B\")\n",
const [isOpen, setIsOpen] = useState(false); "\n",
const [messages, setMessages] = useState<Message[]>([]); "# Set the padding token to the EOS token\n",
const [inputText, setInputText] = useState(''); "tokenizer.pad_token = tokenizer.eos_token\n",
const [isLoading, setIsLoading] = useState(false); "\n",
const chatContainerRef = useRef<HTMLDivElement>(null); "def generate_email(professor_name, research_topic, user_name):\n",
" # Email template\n",
const handleSendMessage = async () => { " prompt = f\"\"\"\n",
if (!inputText.trim() || isLoading) return; " Dear Professor {professor_name},\n",
"\n",
try { " I am writing to express my interest in pursuing research under your guidance. My research topic revolves around {research_topic}.\n",
setIsLoading(true); "\n",
const userMessage = inputText.trim(); " I believe that your work in this area is groundbreaking, and I am eager to contribute to your ongoing projects.\n",
setMessages(prev => [...prev, { text: userMessage, sender: 'user' }]); "\n",
setInputText(''); " Best regards,\n",
" {user_name}\n",
// Directly call Ollama API via local tunnel " \"\"\"\n",
const response = await fetch('https://joe-ollama.loca.lt/api/generate', { " # Tokenize input\n",
method: 'POST', " inputs = tokenizer(prompt, return_tensors=\"pt\", truncation=True, padding=True)\n",
headers: { " # Generate email with controlled randomness\n",
'Content-Type': 'application/json', " output = model.generate(\n",
'Authorization': 'Basic ' + btoa('username:password') // Add your auth " inputs[\"input_ids\"],\n",
" attention_mask=inputs[\"attention_mask\"],\n",
" max_length=len(inputs[\"input_ids\"][0]) + 100,\n",
" do_sample=True, # Set to True to use temperature and top_p\n",
" temperature=0.7,\n",
" top_p=0.9,\n",
" pad_token_id=tokenizer.eos_token_id\n",
" )\n",
" # Decode and return the text\n",
" generated_email = tokenizer.decode(output[0], skip_special_tokens=True)\n",
" return generated_email.strip()\n",
"\n",
"def text_to_speech(text, output_file=\"email.mp3\", lang='en'):\n",
" try:\n",
" if os.path.exists(output_file):\n",
" os.remove(output_file)\n",
" tts = gTTS(text, lang=lang)\n",
" tts.save(output_file)\n",
" print(f\"Speech saved to {output_file}\")\n",
" except Exception as e:\n",
" print(f\"Error generating speech: {e}\")\n",
"\n",
"def play_sound(file_path):\n",
" if not os.path.exists(file_path):\n",
" print(\"File not found.\")\n",
" return\n",
" try:\n",
" # Using playsound\n",
" playsound(file_path)\n",
" print(\"\\nEmail is being read aloud.\")\n",
" except Exception as e:\n",
" print(f\"Error playing sound with playsound: {e}\")\n",
"\n",
"# Input data\n",
"professor_name = input(\"Enter the professor's name: \")\n",
"research_topic = input(\"Enter your research topic: \")\n",
"user_name = input(\"Enter your name: \")\n",
"\n",
"# Generate and print the email\n",
"email = generate_email(professor_name, research_topic, user_name)\n",
"print(\"\\nGenerated Email:\\n\")\n",
"print(email)\n",
"\n",
"# Convert the email to speech\n",
"text_to_speech(email)\n",
"\n",
"# Play the generated speech\n",
"play_sound(\"email.mp3\")"
]
}, },
body: JSON.stringify({ {
model: 'llama3', "cell_type": "code",
prompt: userMessage, "execution_count": null,
stream: false, "id": "89bc527f-4f37-44d3-8454-52a980cf6038",
options: { "metadata": {},
temperature: 0.7, "outputs": [],
max_tokens: 500 "source": []
} }
}), ],
}); "metadata": {
"kernelspec": {
if (!response.ok) throw new Error('Failed to get response'); "display_name": "Python 3 (ipykernel)",
"language": "python",
const data = await response.json(); "name": "python3"
setMessages(prev => [...prev, { text: data.response, sender: 'bot' }]); },
} catch (error) { "language_info": {
console.error('Chat error:', error); "codemirror_mode": {
setMessages(prev => [...prev, { "name": "ipython",
text: "Sorry, I'm having trouble connecting. Please try again later.", "version": 3
sender: 'bot' },
}]); "file_extension": ".py",
} finally { "mimetype": "text/x-python",
setIsLoading(false); "name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.8.19"
} }
}; },
"nbformat": 4,
useEffect(() => { "nbformat_minor": 5
if (chatContainerRef.current) {
chatContainerRef.current.scrollTop = chatContainerRef.current.scrollHeight;
}
}, [messages]);
return (
<div style={{ position: 'fixed', bottom: '20px', right: '29.6px', zIndex: 1000 }}>
{isOpen && (
<div style={chatWindowStyle}>
<div style={headerStyle}>
<div style={titleStyle}>Chat with Joe's AI</div>
<button onClick={() => setIsOpen(false)} style={closeButtonStyle}>
×
</button>
</div>
<div ref={chatContainerRef} style={messageContainerStyle}>
{messages.map((msg, index) => (
<div key={index} style={messageBubbleStyle(msg.sender)}>
<span style={textStyle(msg.sender)}>
{msg.text}
</span>
</div>
))}
{isLoading && (
<div style={loadingStyle}>
<div className="dot-flashing" />
</div>
)}
</div>
<div style={inputContainerStyle}>
<input
type="text"
value={inputText}
onChange={(e) => setInputText(e.target.value)}
onKeyPress={(e) => e.key === 'Enter' && handleSendMessage()}
style={inputStyle}
placeholder="Ask me anything..."
disabled={isLoading}
/>
<button
onClick={handleSendMessage}
style={sendButtonStyle}
disabled={isLoading}
>
{isLoading ? '...' : 'Send'}
</button>
</div>
</div>
)}
{!isOpen && (
<button
onClick={() => setIsOpen(true)}
style={toggleButtonStyle}
>
💬
</button>
)}
</div>
);
}
// Style constants
const chatWindowStyle = {
width: '350px',
border: '1px solid #e5e7eb',
borderRadius: '12px',
padding: '16px',
backgroundColor: '#ffffff',
boxShadow: '0 4px 6px rgba(0, 0, 0, 0.1)',
};
const headerStyle = {
display: 'flex',
justifyContent: 'space-between',
alignItems: 'center',
marginBottom: '16px',
};
const titleStyle = {
fontSize: '18px',
fontWeight: '600',
color: '#1f2937',
};
const closeButtonStyle = {
padding: '8px',
borderRadius: '50%',
border: 'none',
backgroundColor: '#31616c',
color: '#fff',
cursor: 'pointer',
fontWeight: '600',
width: '32px',
height: '32px',
display: 'flex',
alignItems: 'center',
justifyContent: 'center',
};
const messageContainerStyle = {
height: '330px',
overflowY: 'auto',
marginBottom: '16px',
padding: '8px',
backgroundColor: '#f3f4f6',
borderRadius: '8px',
};
const messageBubbleStyle = (sender: 'user' | 'bot') => ({
textAlign: sender === 'user' ? 'right' : 'left',
margin: '8px 0',
});
const textStyle = (sender: 'user' | 'bot') => ({
display: 'inline-block',
padding: '8px 12px',
borderRadius: '12px',
backgroundColor: sender === 'user' ? '#31616c' : '#e5e7eb',
color: sender === 'user' ? '#fff' : '#1f2937',
maxWidth: '80%',
wordWrap: 'break-word' as const,
});
const inputContainerStyle = {
display: 'flex',
gap: '8px',
};
const inputStyle = {
flex: 1,
padding: '8px',
borderRadius: '8px',
border: '1px solid #e5e7eb',
backgroundColor: '#ffffff',
color: '#1f2937',
outline: 'none',
};
const sendButtonStyle = {
padding: '8px 16px',
borderRadius: '8px',
border: 'none',
backgroundColor: '#31616c',
color: '#fff',
cursor: 'pointer',
fontWeight: '600',
};
const toggleButtonStyle = {
padding: '12px',
borderRadius: '50%',
border: 'none',
backgroundColor: '#31616c',
color: '#fff',
cursor: 'pointer',
boxShadow: '0 4px 6px rgba(0, 0, 0, 0.1)',
display: 'flex',
alignItems: 'center',
justifyContent: 'center',
width: '48px',
height: '48px',
};
const loadingStyle = {
display: 'flex',
justifyContent: 'center',
padding: '8px',
};