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import torch
from transformers import AutoTokenizer, AutoModelForCausalLM
# ==============================
# 🔐 HIDE STREAMLIT MENU
# ==============================
st.markdown("""
<style>
#MainMenu {visibility: hidden;}
header {visibility: hidden;}
footer {visibility: hidden;}
.stDeployButton {display:none;}
</style>
""", unsafe_allow_html=True)
# ==============================
# PAGE CONFIG
# ==============================
st.set_page_config(page_title="💻 AI Code Generator", layout="wide")
# ==============================
# LOAD MODEL (FAST)
# ==============================
@st.cache_resource
def load_model():
model_name = "microsoft/phi-2"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(
model_name,
torch_dtype=torch.float32, # CPU friendly
device_map=None # avoid GPU issues
)
return tokenizer, model
tokenizer, model = load_model()
# ==============================
# CODE GENERATION FUNCTION
# ==============================
def generate_code(prompt, language):
full_prompt = f"""### Instruction:
Write a {language} program for the following task.
Task:
{prompt}
### Response:
"""
inputs = tokenizer(full_prompt, return_tensors="pt")
outputs = model.generate(
**inputs,
max_new_tokens=150,
temperature=0.2,
top_p=0.9,
do_sample=False
)
result = tokenizer.decode(outputs[0], skip_special_tokens=True)
# Extract only response part
if "### Response:" in result:
result = result.split("### Response:")[-1]
return result.strip()
# ==============================
# UI
# ==============================
st.title("💻 AI Code Generator (Fast & Accurate)")
col1, col2 = st.columns(2)
with col1:
user_prompt = st.text_area("Describe your task", height=200)
with col2:
language = st.selectbox(
"Select Programming Language",
["Python", "JavaScript", "SQL", "Java", "C++", "HTML", "CSS"]
)
# ==============================
# GENERATE BUTTON
# ==============================
if st.button("🚀 Generate Code"):
if not user_prompt.strip():
st.warning("Please enter a task")
else:
with st.spinner("Generating code..."):
try:
code = generate_code(user_prompt, language)
st.success("✅ Generated Code")
st.code(code, language=language.lower())
except Exception as e:
st.error(f"❌ Error: {str(e)}") |