Update app.py

app.py

@@ -1,35 +1,179 @@
 import streamlit as st
 import requests
+import os
+from openai import OpenAI
 
 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.")
 
+# Sidebar for API keys
+with st.sidebar:
+    st.header("API Configuration")
+    openai_api_key = st.text_input("OpenAI API Key", type="password", help="Required for GPT-4")
+    hf_api_key = st.text_input("HuggingFace API Key", type="password", help="Required for HF models")
+
 # 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):
+def query_gpt4(code, api_key):
+    """Query OpenAI GPT-4 for code fixing"""
+    try:
+        client = OpenAI(api_key=api_key)
+        
+        prompt = f"""You are an expert in quantum computing and Qiskit. 
+Analyze the following Qiskit code for bugs and provide a fixed version.
+Explain what bugs you found and how you fixed them.
+
+Code to analyze:
+```python
+{code}
+```
+
+Provide your response in this format:
+BUGS FOUND:
+[List the bugs]
+
+FIXED CODE:
+```python
+[Your fixed code here]
+```
+
+EXPLANATION:
+[Explain the fixes]
+"""
+        
+        response = client.chat.completions.create(
+            model="gpt-4",
+            messages=[
+                {"role": "system", "content": "You are a Qiskit debugging expert."},
+                {"role": "user", "content": prompt}
+            ],
+            temperature=0.3,
+            max_tokens=2000
+        )
+        
+        return response.choices[0].message.content
+    
+    except Exception as e:
+        return f"Error querying GPT-4: {str(e)}"
+
+def query_huggingface(code, api_key, model_name):
+    """Query HuggingFace models for code fixing"""
+    try:
+        # Map model choice to HF model ID
+        model_map = {
+            "Granite-8B-Qiskit (HF)": "ibm-granite/granite-8b-code-instruct",
+            "Code Llama (HF)": "codellama/CodeLlama-13b-Instruct-hf"
+        }
+        
+        model_id = model_map.get(model_name, "codellama/CodeLlama-7b-Instruct-hf")
+        
+        headers = {
+            "Authorization": f"Bearer {api_key}",
+            "Content-Type": "application/json"
+        }
+        
+        prompt = f"""<s>[INST] You are an expert in quantum computing and Qiskit.
+Analyze this Qiskit code for bugs and provide a fixed version:
+
+{code}
+
+Identify bugs and provide corrected code. [/INST]"""
+        
+        payload = {
+            "inputs": prompt,
+            "parameters": {
+                "max_new_tokens": 1000,
+                "temperature": 0.3,
+                "top_p": 0.9,
+                "return_full_text": False
+            }
+        }
+        
+        api_url = f"https://api-inference.huggingface.co/models/{model_id}"
+        response = requests.post(api_url, headers=headers, json=payload, timeout=60)
+        
+        if response.status_code == 200:
+            result = response.json()
+            if isinstance(result, list) and len(result) > 0:
+                return result[0].get('generated_text', 'No response generated')
+            return str(result)
+        else:
+            return f"Error: {response.status_code} - {response.text}"
+    
+    except Exception as e:
+        return f"Error querying HuggingFace: {str(e)}"
+
+def query_llm(model, code, openai_key=None, hf_key=None):
+    """Main router function for LLM queries"""
     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])")
+        if not openai_key:
+            return "❌ Error: OpenAI API key required. Please enter it in the sidebar."
+        return query_gpt4(code, openai_key)
+    
+    elif model in ["Granite-8B-Qiskit (HF)", "Code Llama (HF)"]:
+        if not hf_key:
+            return "❌ Error: HuggingFace API key required. Please enter it in the sidebar."
+        return query_huggingface(code, hf_key, model)
+    
     return "No fix found."
 
 # Button to trigger repair
-if st.button("Fix My Code"):
+if st.button("🔧 Fix My Code", type="primary"):
     if not code_input.strip():
-        st.warning("Please paste some Qiskit code to analyze.")
+        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")
+        with st.spinner(f"🤔 Querying {model_choice}..."):
+            fixed_code = query_llm(
+                model_choice, 
+                code_input,
+                openai_api_key,
+                hf_api_key
+            )
+            
+            st.success("✅ Analysis complete!")
+            
+            # Display results in an expandable section
+            with st.expander("📝 LLM Response", expanded=True):
+                st.markdown(fixed_code)
+
+# Example code section
+with st.expander("💡 Try an Example"):
+    example_code = """from qiskit import QuantumCircuit, QuantumRegister
+from qiskit_aer import Aer
+from qiskit.visualization import plot_histogram
+
+# Create a quantum circuit with a bug
+q = QuantumRegister(2, 'q')
+qc = QuantumCircuit(q)
+
+qc.h(q[0])
+qc.cx(q[0], q[0])  # BUG: Control and target are the same qubit!
+
+qc.measure_all()"""
+    
+    st.code(example_code, language="python")
+    if st.button("Load Example"):
+        st.rerun()
 
 st.markdown("---")
 st.caption("Built by your Quantum AI copilot 🧠⚛️")
+
+# Instructions
+with st.sidebar:
+    st.markdown("---")
+    st.markdown("""
+    ### 📖 How to Use
+    1. Enter your API key(s) above
+    2. Paste Qiskit code in the main area
+    3. Select your preferred LLM
+    4. Click "Fix My Code"
+    
+    ### 🔑 Getting API Keys
+    - **OpenAI**: https://platform.openai.com/api-keys
+    - **HuggingFace**: https://huggingface.co/settings/tokens
+    """)