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b4213c6 c0fd556 b4213c6 c0fd556 b4213c6 c0fd556 b4213c6 c0fd556 b4213c6 c0fd556 b4213c6 | 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 | import streamlit as st
import google.generativeai as genai
import os
# ---------- UI ----------
st.set_page_config(page_title="Python Code Reviewer 🤖", layout="centered")
st.title("🐍 Python Code Reviewer 🤖")
st.markdown("### Paste your code and a short prompt – the AI will review it for you!")
# 1️⃣ API key input (optional)
api_key_input = st.text_input(
"🔑 Google API Key (optional – leave blank to use the built‑in key)",
type="password",
help="If you have your own Gemini API key, enter it here. Otherwise the app will fall back to the default key."
)
# 2️⃣ System prompt (optional)
sys_prompt = st.text_input(
"🗒️ System Prompt (optional)",
placeholder="e.g., 'You are a friendly Python code reviewer.'",
help="Custom instructions for the model. If left empty, the environment variable USER_PROMPT is used."
)
# 3️⃣ Code box
code_box = st.text_area(
"💻 Your Python code:",
height=200,
placeholder="# Paste your Python code here"
)
# 4️⃣ Action prompt box
prompt_box = st.text_area(
"📝 What should the AI do with this code?",
height=80,
placeholder="e.g., 'Find bugs and suggest improvements.'"
)
# ---------- Logic ----------
if st.button("🚀 Review"):
# Validate that there is code to review
if not code_box.strip():
st.warning("⚠️ Please paste some Python code.")
st.stop()
# Choose API key: user‑provided > hard‑coded fallback
api_key = api_key_input.strip() or "AIzaSyBiAW2GQLid0HGe9Vs_ReKwkwsSVNegNzs"
genai.configure(api_key=api_key)
# Choose system instruction: user input > env var > none
system_instruction = (
sys_prompt.strip()
or os.getenv("USER_PROMPT")
or "You are a helpful Python code reviewer."
)
# Initialise model with the chosen system instruction
model = genai.GenerativeModel(
model_name="models/gemini-2.5-flash",
system_instruction=system_instruction,
)
# Build the full user message
user_message = f"Code:\n```python\n{code\_box}\n```\n\nTask: {prompt_box or 'Review the code.'}"
# Call Gemini
with st.spinner("Analyzing your code... 🧐"):
response = model.generate_content(user_message)
# Show result
st.markdown("### 🤖 Response")
st.success(response.text)
# Footer
st.markdown("---")
st.markdown("🛠️ **Built with Streamlit & Google Gemini AI** | ❤️ _Happy Coding!_ 🐍")
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