Rename src/streamlit_app.py to src/qcode_app.py

src/qcode_app.py

@@ -0,0 +1,35 @@
+import streamlit as st
+import requests
+
+st.set_page_config(page_title="Qcode Agent: Qiskit Bug Fixer", layout="centered")
+st.title("🤖 Qcode Agent: LLM-Powered Quantum Code Repair")
+st.markdown("Paste your Qiskit code below and let an LLM find and fix bugs.")
+
+# Code input
+code_input = st.text_area("Qiskit Code Input", height=300, placeholder="Paste your Qiskit code here...")
+
+# Backend selection
+model_choice = st.selectbox("Choose LLM Backend", ["GPT-4 (OpenAI)", "Granite-8B-Qiskit (HF)", "Code Llama (HF)"])
+
+# API setup (mocked)
+def query_llm(model, code):
+    if model == "GPT-4 (OpenAI)":
+        return "# Fixed by GPT-4\n" + code.replace("cx(q[0], q[0])", "cx(q[0], q[1])")
+    elif model == "Granite-8B-Qiskit (HF)":
+        return "# Granite-8B fix suggestion:\n" + code.replace("cx(q[0], q[0])", "cx(q[0], q[1])")
+    elif model == "Code Llama (HF)":
+        return "# Code Llama fix suggestion:\n" + code.replace("cx(q[0], q[0])", "cx(q[0], q[1])")
+    return "No fix found."
+
+# Button to trigger repair
+if st.button("Fix My Code"):
+    if not code_input.strip():
+        st.warning("Please paste some Qiskit code to analyze.")
+    else:
+        with st.spinner("Querying the selected LLM..."):
+            fixed_code = query_llm(model_choice, code_input)
+            st.success("Patch generated successfully!")
+            st.code(fixed_code, language="python")
+
+st.markdown("---")
+st.caption("Built by your Quantum AI copilot 🧠⚛️")

src/streamlit_app.py

@@ -1,40 +0,0 @@
-import altair as alt
-import numpy as np
-import pandas as pd
-import streamlit as st
-
-"""
-# Welcome to Streamlit!
-
-Edit `/streamlit_app.py` to customize this app to your heart's desire :heart:.
-If you have any questions, checkout our [documentation](https://docs.streamlit.io) and [community
-forums](https://discuss.streamlit.io).
-
-In the meantime, below is an example of what you can do with just a few lines of code:
-"""
-
-num_points = st.slider("Number of points in spiral", 1, 10000, 1100)
-num_turns = st.slider("Number of turns in spiral", 1, 300, 31)
-
-indices = np.linspace(0, 1, num_points)
-theta = 2 * np.pi * num_turns * indices
-radius = indices
-
-x = radius * np.cos(theta)
-y = radius * np.sin(theta)
-
-df = pd.DataFrame({
-    "x": x,
-    "y": y,
-    "idx": indices,
-    "rand": np.random.randn(num_points),
-})
-
-st.altair_chart(alt.Chart(df, height=700, width=700)
-    .mark_point(filled=True)
-    .encode(
-        x=alt.X("x", axis=None),
-        y=alt.Y("y", axis=None),
-        color=alt.Color("idx", legend=None, scale=alt.Scale()),
-        size=alt.Size("rand", legend=None, scale=alt.Scale(range=[1, 150])),
-    ))