Spaces:
Sleeping
Sleeping
File size: 4,141 Bytes
65796a2 a4bcde0 65796a2 7067153 65796a2 7067153 65796a2 7067153 65796a2 7067153 a4bcde0 7067153 a4bcde0 7067153 a4bcde0 7067153 a4bcde0 7067153 a4bcde0 7067153 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 |
import streamlit as st
from transformers import AutoTokenizer, AutoModelForCausalLM
from datetime import datetime
# Custom CSS for a Grok/ChatGPT-like look
st.markdown("""
<style>
.main { background-color: #f9f9f9; padding: 20px; }
.stTextArea textarea {
border: 1px solid #ddd;
border-radius: 8px;
padding: 10px;
font-family: 'Roboto', sans-serif;
font-size: 16px;
background-color: #fff;
box-shadow: 0 2px 4px rgba(0,0,0,0.1);
}
.stButton button {
background-color: #4a90e2;
color: white;
border-radius: 8px;
padding: 10px 20px;
font-family: 'Roboto', sans-serif;
font-size: 14px;
}
.stButton button:hover {
background-color: #357abd;
}
.code-output {
background-color: #2b2b2b;
color: #f0f0f0;
padding: 15px;
border-radius: 8px;
font-family: 'Courier New', monospace;
font-size: 14px;
margin-top: 10px;
}
.title {
font-family: 'Roboto', sans-serif;
font-size: 28px;
font-weight: bold;
color: #333;
margin-bottom: 10px;
}
.subtitle {
font-family: 'Roboto', sans-serif;
font-size: 16px;
color: #666;
margin-bottom: 20px;
}
.chat-message {
font-family: 'Roboto', sans-serif;
font-size: 16px;
color: #333;
margin-bottom: 5px;
}
</style>
""", unsafe_allow_html=True)
# Load model and tokenizer
try:
checkpoint = "Salesforce/codegen-350M-mono"
tokenizer = AutoTokenizer.from_pretrained(checkpoint)
model = AutoModelForCausalLM.from_pretrained(checkpoint)
except Exception as e:
st.error(f"Error loading model: {e}")
st.stop()
# Function to generate code
def generate_code(description):
prompt = f"Generate Python code for the following task: {description}\n"
inputs = tokenizer(prompt, return_tensors="pt")
outputs = model.generate(
**inputs,
max_length=500,
num_return_sequences=1,
pad_token_id=tokenizer.eos_token_id
)
code = tokenizer.decode(outputs[0], skip_special_tokens=True)
return code[len(prompt):].strip()
# Initialize chat history in session state
if "chat_history" not in st.session_state:
st.session_state.chat_history = []
# UI Layout
st.markdown('<div class="title">Code Generation Bot</div>', unsafe_allow_html=True)
st.markdown('<div class="subtitle">Describe your task, and I’ll generate Python code for you!</div>', unsafe_allow_html=True)
with st.container():
# Input area
description = st.text_area(
"Enter your description here",
placeholder="e.g., Write a function to calculate the factorial of a number",
height=150
)
col1, col2 = st.columns([1, 1]) # Adjusted for two buttons
with col1:
if st.button("Generate"):
if description.strip():
with st.spinner("Thinking..."):
generated_code = generate_code(description)
# Append to chat history with timestamp
st.session_state.chat_history.append({
"input": description,
"output": generated_code,
"time": datetime.now().strftime("%H:%M:%S")
})
else:
st.warning("Please enter a description first!")
with col2:
if st.button("Clear History"):
st.session_state.chat_history = []
st.success("Chat history cleared!")
# Display chat history
if st.session_state.chat_history:
st.write("### Chat History")
for chat in st.session_state.chat_history:
st.markdown(f'<div class="chat-message"><strong>You ({chat["time"]}):</strong> {chat["input"]}</div>', unsafe_allow_html=True)
st.markdown(f'<div class="code-output">{chat["output"]}</div>', unsafe_allow_html=True)
st.markdown("---") # Separator for readability
# Optional tip at the bottom
st.info("Tip: Check the generated code for accuracy before using it!") |