Update app.py

app.py

@@ -2,7 +2,8 @@ import streamlit as st
 import difflib
 import requests
 import datetime
-import streamlit.components.v1 as components
+import base64
+import io
 
 # --- CONFIG ---
 GROQ_API_KEY = st.secrets.get('GROQ_API_KEY', 'YOUR_GROQ_API_KEY')
@@ -21,7 +22,7 @@ EXAMPLE_QUESTIONS = [
     "How can I make this code more readable?"
 ]
 
-# --- API STUBS ---
+# --- API CALLS ---
 def call_groq_api(prompt, model="llama3-70b-8192"):
     headers = {"Authorization": f"Bearer {GROQ_API_KEY}", "Content-Type": "application/json"}
     data = {"model": model, "messages": [{"role": "user", "content": prompt}]}
@@ -31,14 +32,21 @@ def call_groq_api(prompt, model="llama3-70b-8192"):
     else:
         return f"[Groq API Error] {response.text}"
 
-def call_blackbox_agent(messages):
-    url = "https://api.code.blackbox.ai/v1/chat/completions"
+def call_blackbox_agent(messages, model="gpt-4o"):
+    """
+    messages: list of dicts, e.g.
+      [
+        {"role": "system", "content": "You are a helpful coding assistant."},
+        {"role": "user", "content": "Refactor this code: ..."}
+      ]
+    """
+    url = "https://api.blackbox.ai/v1/chat/completions"
     headers = {
         "Content-Type": "application/json",
         "Authorization": f"Bearer {BLACKBOX_API_KEY}"
     }
     data = {
-        "model": "code-chat",
+        "model": model,
         "messages": messages
     }
     response = requests.post(url, headers=headers, json=data)
@@ -49,14 +57,12 @@ def call_blackbox_agent(messages):
 
 # --- UTILS ---
 def code_matches_language(code, language):
-    # Simple heuristic, can be improved
     if language.lower() in code.lower():
         return True
-    return True  # For demo, always True
+    return True 
 
 def calculate_code_complexity(code):
-    # Dummy complexity metric
-    lines = code.count('\n') + 1
+    lines = code.count('\\n') + 1
     return f"{lines} lines"
 
 def get_inline_diff(original, modified):
@@ -67,36 +73,25 @@ def get_inline_diff(original, modified):
         fromfile='Original',
         tofile='Refactored'
     )
-    return '\n'.join(diff)
-
-def is_coding_question(question):
-    messages = [
-        {"role": "system", "content": "You are a helpful coding assistant."},
-        {"role": "user", "content": f"Is the following question about programming or code? Answer only 'yes' or 'no'. Question: {question}"}
-    ]
-    try:
-        response = call_blackbox_agent(messages)
-        return 'yes' in response.lower()
-    except Exception:
-        return False
+    return '\\n'.join(diff)
 
 # --- STREAMLIT APP ---
-st.set_page_config(page_title="AI Workflow App", layout="wide")
-st.title("AI Assistant with Workflow (Streamlit Edition)")
+st.set_page_config(page_title="Code Workflows", layout="wide")
+st.title("CodeGenie")
 
 # Navigation
-page = st.sidebar.radio("Navigate", ["Home", "AI Workflow", "Semantic Search"])
+page = st.sidebar.radio("Navigate", ["Home", "Code Workflow", "Semantic Search"])
 
 if page == "Home":
-    st.header("Welcome to the AI Assistant!")
+    st.header("Welcome to the Code Genie!")
     st.markdown("""
-    - **Full AI Workflow:** Complete code analysis pipeline with explanation, refactoring, review, and testing (powered by Groq/Blackbox)
+    - **Full Code Workflow:** Complete code analysis pipeline with explanation, refactoring, review, and testing (powered by Groq/Blackbox)
     - **Semantic Search:** Ask natural language questions about your code and get intelligent answers
     """)
     st.info("Select a feature from the sidebar to get started.")
 
-elif page == "AI Workflow":
-    st.header("Full AI Workflow")
+elif page == "Code Workflow":
+    st.header("Full Code Workflow")
     code_input = st.text_area("Paste your code here", height=200)
     uploaded_file = st.file_uploader("Or upload a code file", type=["py", "js", "ts", "java", "cpp", "cs"])
     if uploaded_file:
@@ -119,7 +114,7 @@ elif page == "AI Workflow":
         elif not code_matches_language(code_input, programming_language):
             st.error(f"Language mismatch. Please check your code and language selection.")
         else:
-            with st.spinner("Running AI Workflow..."):
+            with st.spinner("Running Code Workflow..."):
                 steps = [
                     ("Explain", call_groq_api(f"Explain this {programming_language} code for a {skill_level} {user_role} in {explanation_language}:\n{code_input}")),
                     ("Refactor", call_blackbox_agent([
@@ -137,12 +132,14 @@ elif page == "AI Workflow":
                 for t in timeline:
                     st.subheader(t["step"])
                     st.write(t["output"])
+                # Show code diff (Original vs Refactored)
                 st.subheader("Code Diff (Original vs Refactored)")
-                refactored_code = steps[1][1]
+                refactored_code = steps[1][1]  # Blackbox agent output
                 st.code(get_inline_diff(code_input, refactored_code), language=programming_language.lower())
-                report = f"AI Workflow Report\nGenerated on: {datetime.datetime.now()}\nLanguage: {programming_language}\nSkill Level: {skill_level}\nRole: {user_role}\n\n"
+                # Download report
+                report = f"Code Workflow Report\\nGenerated on: {datetime.datetime.now()}\\nLanguage: {programming_language}\\nSkill Level: {skill_level}\\nRole: {user_role}\\n\\n"
                 for t in timeline:
-                    report += f"## {t['step']}\n{t['output']}\n\n---\n\n"
+                    report += f"## {t['step']}\\n{t['output']}\\n\\n---\\n\\n"
                 st.download_button("Download Report", report, file_name="ai_workflow_report.txt")
 
 elif page == "Semantic Search":
@@ -162,59 +159,29 @@ elif page == "Semantic Search":
     with col4:
         explanation_language = st.selectbox("Explanation Language", EXPLANATION_LANGUAGES, key="sem_expl")
 
+    # Audio recorder for voice input
+    audio_bytes = st.file_uploader("Record your question (wav format)", type=["wav"], key="audio_input")
+    question = st.text_input("Ask a question about your code")
+
+    if audio_bytes is not None:
+        audio_data = audio_bytes.read()
+        audio_base64 = base64.b64encode(audio_data).decode("utf-8")
+        # Prepare message for Blackbox AI agent to transcribe audio
+        messages = [
+            {"role": "system", "content": "You are a helpful assistant that transcribes audio to text."},
+            {"role": "user", "content": f"Transcribe this audio (base64 encoded wav): {audio_base64}"}
+        ]
+        transcription = call_blackbox_agent(messages)
+        st.session_state['voice_question'] = transcription
+        st.experimental_rerun()
+
+    # Use transcribed question if available
+    if 'voice_question' in st.session_state and st.session_state['voice_question']:
+        question = st.session_state['voice_question']
+
     st.caption("Example questions:")
     st.write(", ".join(EXAMPLE_QUESTIONS))
 
-    # --- Voice input widget ---
-    if "sem_question" not in st.session_state:
-        st.session_state["sem_question"] = ""
-
-    voice_input = components.html('''
-    <button id="voice-btn" style="margin-bottom:8px;">🎤 Speak your question</button>
-    <span id="voice-status" style="margin-left:8px;"></span>
-    <script>
-    const btn = document.getElementById('voice-btn');
-    const status = document.getElementById('voice-status');
-    let recognition;
-    if ('webkitSpeechRecognition' in window) {
-        recognition = new webkitSpeechRecognition();
-        recognition.lang = 'en-US';
-        recognition.continuous = false;
-        recognition.interimResults = false;
-        btn.onclick = function() {
-            recognition.start();
-            status.textContent = 'Listening...';
-        };
-        recognition.onresult = function(event) {
-            const transcript = event.results[0][0].transcript;
-            window.parent.postMessage({isStreamlitMessage: true, type: 'streamlit:setComponentValue', value: transcript}, '*');
-            status.textContent = 'Heard: ' + transcript;
-        };
-        recognition.onerror = function() {
-            status.textContent = 'Voice error';
-        };
-        recognition.onend = function() {
-            if (status.textContent === 'Listening...') status.textContent = '';
-        };
-    } else {
-        btn.disabled = true;
-        status.textContent = 'Voice not supported';
-    }
-    </script>
-    ''', height=60)
-
-    # If voice input is received, update the question field directly in session state
-    if voice_input and isinstance(voice_input, str) and voice_input.strip():
-        if is_coding_question(voice_input):
-            st.session_state["sem_question"] = voice_input
-            st.success(f"Question recognized: {voice_input}")
-        else:
-            st.warning("Please ask a relevant question.")
-
-    # Single input field for question (typed or spoken)
-    question = st.text_input("Ask a question about your code", key="sem_question")
-
-    # Run Semantic Search button
     if st.button("Run Semantic Search"):
         if not code_input.strip() or not question.strip():
             st.error("Both code and question are required.")
@@ -224,4 +191,4 @@ elif page == "Semantic Search":
             with st.spinner("Running Semantic Search..."):
                 answer = call_groq_api(f"{question}\n\nCode:\n{code_input}")
                 st.success("Answer:")
-                st.write(answer)
+                st.write(answer)