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3b35c3e 8df7deb 3b35c3e 8df7deb 3b35c3e 8df7deb 3b35c3e c2bd3a1 3b35c3e bfa2513 3b35c3e a8c66cd | 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 | import gradio as gr
import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, BitsAndBytesConfig
MODEL_ID = "Qwen/Qwen2.5-Coder-1.5B-Instruct"
tokenizer = AutoTokenizer.from_pretrained(MODEL_ID)
model = AutoModelForCausalLM.from_pretrained(
MODEL_ID,
device_map="auto",
)
SYSTEM_PROMPT = """You are an expert code reviewer. Analyze the provided code and give structured feedback in this exact format:
## 🐛 Bugs & Errors
List any bugs, logic errors, or runtime issues. If none, say "None found."
## 🔒 Security Issues
List any security vulnerabilities (SQL injection, XSS, hardcoded secrets, etc.). If none, say "None found."
## 🎨 Code Style & Readability
Comment on naming conventions, formatting, comments, and clarity.
## ⚡ Performance
Identify any inefficiencies or bottlenecks.
## ✅ Suggestions
Top 3 actionable improvements the developer should make.
Be specific, concise, and constructive. Reference line numbers where possible."""
def build_prompt(code: str, language: str) -> str:
return f"""<s>[INST] <<SYS>>
{SYSTEM_PROMPT}
<</SYS>>
Please review the following {language} code:
```{language.lower()}
{code}
```
[/INST]"""
def review_code(code: str, language: str, max_new_tokens: int = 800):
try:
if not code.strip():
return "⚠️ Please paste some code to review."
prompt = build_prompt(code, language)
inputs = tokenizer(prompt, return_tensors="pt")
inputs = {k: v.to(model.device) for k, v in inputs.items()}
with torch.no_grad():
outputs = model.generate(
**inputs,
max_new_tokens=512,
temperature=0.2,
do_sample=True,
top_p=0.95,
repetition_penalty=1.1,
eos_token_id=tokenizer.eos_token_id,
pad_token_id=tokenizer.eos_token_id,
use_cache=True
)
# Decode only the newly generated tokens (skip the prompt)
response = tokenizer.decode(
outputs[0][inputs["input_ids"].shape[1]:],
skip_special_tokens=True
)
return response.strip() or "⚠️ Model returned an empty response."
except Exception as e:
return f"❌ Error:\n\n{str(e)}"
# --- Gradio UI ---
with gr.Blocks(title="AI Code Reviewer", theme=gr.themes.Soft()) as demo:
gr.Markdown("# 🔍 AI Code Reviewer\nPowered by CodeLlama-7B · Paste your code and get structured feedback instantly.")
with gr.Row():
with gr.Column(scale=2):
language = gr.Dropdown(
choices=["Python", "JavaScript", "TypeScript", "Java", "C++", "Go", "Rust", "SQL"],
value="Python",
label="Language"
)
code_input = gr.Code(
language="python",
label="Your Code",
lines=20,
value="# Paste your code here...",
)
submit_btn = gr.Button("Review Code ↗", variant="primary")
with gr.Column(scale=2):
output = gr.Markdown(label="Review", value="*Review will appear here...*")
submit_btn.click(
fn=review_code,
inputs=[code_input, language],
outputs=output,
show_progress="full"
)
gr.Examples(
examples=[
["def divide(a, b):\n return a / b\n\nresult = divide(10, 0)\nprint(result)", "Python"],
["SELECT * FROM users WHERE name = '" + "' + username + '", "SQL"],
],
inputs=[code_input, language],
label="Try an example"
)
demo.queue(max_size=10).launch() |