Adding voice bot

chatbot.py

@@ -9,7 +9,7 @@ import asyncio
 import os
 import uuid
 
-GROQ_API_KEY = os.getenv('GROQ_API_KEY')
+GROQ_API_KEY = os.getenv("GROQ_API_KEY")
 
 class CodeAssistantBot:
     def __init__(self):
@@ -19,7 +19,7 @@ class CodeAssistantBot:
             ("system",
              "You are a skilled coding assistant. Use the following context and user input to help."
              " Refer to previous summary and recent interactions to make answers accurate."
-             " Keep your response short, relevant, and conversational — smaller is better if it covers what's needed."),
+             " Keep your response short, relevant, and conversational."),
             ("user",
              "Code: {code}\nOutput: {output}\nError: {error}\n"
              "Summary: {summary}\nRecent: {recent}\nQuestion: {question}")
@@ -28,32 +28,46 @@ class CodeAssistantBot:
             ("system", "Summarize key technical points from the conversation so far."),
             ("user", "Conversation: {conversation}")
         ])
+        self.voice_prompt = ChatPromptTemplate.from_messages([
+            ("system",
+             "You are a friendly narrator voice bot. Given a technical answer and its context,"
+             " explain it aloud like you're helping someone understand the topic clearly and confidently."
+             " Keep it spoken, not codey. Emphasize pauses, clarity, and voice modulation."),
+            ("user",
+             "Code: {code}\nOutput: {output}\nError: {error}\n"
+             "Conversation so far: {summary}\nAnswer to explain: {answer}")
+        ])
 
     def analyze_code(self, code, output, error, question, summary="", history=None):
-        try:
-            parser = StrOutputParser()
-            recent = "\n".join([f"User: {q}\nBot: {a}" for q, a in (history or [])[-4:]])
-            chain = self.analysis_prompt | self.model | parser
-            return chain.invoke({
-                'code': code,
-                'output': output,
-                'error': error,
-                'summary': summary,
-                'recent': recent,
-                'question': question
-            })
-        except Exception as e:
-            return f"Error: {e}"
+        parser = StrOutputParser()
+        recent = "\n".join([f"User: {q}\nBot: {a}" for q, a in (history or [])[-4:]])
+        chain = self.analysis_prompt | self.model | parser
+        return chain.invoke({
+            'code': code,
+            'output': output,
+            'error': error,
+            'summary': summary,
+            'recent': recent,
+            'question': question
+        })
+
+    def narrate_response(self, code, output, error, answer, summary=""):
+        parser = StrOutputParser()
+        narration_chain = self.voice_prompt | self.model | parser
+        return narration_chain.invoke({
+            'code': code,
+            'output': output,
+            'error': error,
+            'summary': summary,
+            'answer': answer
+        })
 
 async def text_to_speech(text, filename):
-    voice = "en-US-AriaNeural"
+    voice = "fr-FR-VivienneMultilingualNeural"
     communicate = edge_tts.Communicate(text, voice)
     await communicate.save(filename)
 
 def render_chatbot(code, output, error):
-    """Render the chatbot UI with code-block support and a scrollable chat container."""
-
-    # CSS Styling
     st.markdown("""
     <style>
     .chat-container {
@@ -83,51 +97,43 @@ def render_chatbot(code, output, error):
     </style>
     """, unsafe_allow_html=True)
 
-    # Session state
     st.session_state.setdefault('conversation', [])
     st.session_state.setdefault('chat_summary', "")
     st.session_state.setdefault('chat_display_count', 5)
 
-    # Chat input
     c1, c2 = st.columns([4, 1], gap='small')
     with c1:
         question = st.text_input("Ask something about your code...", key="chat_input")
     with c2:
         send = st.button("🚀")
 
-    # Process question
     if send and question:
         bot = CodeAssistantBot()
         history = st.session_state.conversation[-4:]
         summary = st.session_state.chat_summary
-
         response = bot.analyze_code(code, output, error, question, summary, history)
-
         st.session_state.conversation.append((question, response))
         st.session_state.chat_display_count = 5
-
         if len(st.session_state.conversation) >= 3:
             try:
                 full_chat = "\n".join([f"User: {q}\nBot: {a}" for q, a in st.session_state.conversation[-10:]])
-                parser = StrOutputParser()
-                summarizer = bot.summary_prompt | bot.model | parser
+                summarizer = bot.summary_prompt | bot.model | StrOutputParser()
                 st.session_state.chat_summary = summarizer.invoke({'conversation': full_chat})
             except:
                 pass
 
-    # Display conversation
-    total_messages = len(st.session_state.conversation)
-    start_idx = max(0, total_messages - st.session_state.chat_display_count)
-    visible_conversation = st.session_state.conversation[start_idx:]
+    total = len(st.session_state.conversation)
+    start = max(0, total - st.session_state.chat_display_count)
+    visible = st.session_state.conversation[start:]
 
-    for i, (q, a) in enumerate(reversed(visible_conversation)):
+    for i, (q, a) in enumerate(reversed(visible)):
         st.markdown(f'<div class="chat-message user-message">{escape(q)}</div>', unsafe_allow_html=True)
 
-        def format_response(text):
-            parts = text.split('```')
+        def format_response(txt):
+            parts = txt.split('```')
             result = ''
-            for i, part in enumerate(parts):
-                if i % 2 == 1:
+            for j, part in enumerate(parts):
+                if j % 2 == 1:
                     lines = part.splitlines()
                     if lines and lines[0].isalpha():
                         lines = lines[1:]
@@ -140,18 +146,19 @@ def render_chatbot(code, output, error):
         formatted = format_response(a)
         st.markdown(f'<div class="chat-message bot-message">{formatted}</div>', unsafe_allow_html=True)
 
-        # 🔊 Speak Answer Button
-        audio_filename = f"audio_response_{uuid.uuid4().hex}.mp3"
-        if st.button(f"🔊 Speak Answer #{i+1}"):
-            asyncio.run(text_to_speech(a, audio_filename))
-            st.audio(audio_filename)
+        # 🔊 Speak
+        speak_btn = st.button(f"🔊 Narrate #{i+1}")
+        if speak_btn:
+            bot = CodeAssistantBot()
+            narration = bot.narrate_response(code, output, error, a, st.session_state.chat_summary)
+            audio_filename = f"audio_{uuid.uuid4().hex}.mp3"
+            asyncio.run(text_to_speech(narration, audio_filename))
+            st.audio(audio_filename, format="audio/mp3", autoplay=True)
 
-    if start_idx > 0:
-        if st.button("🔽 Show more"):
-            st.session_state.chat_display_count += 5
-            st.rerun()
+    if start > 0 and st.button("🔽 Show more"):
+        st.session_state.chat_display_count += 5
+        st.rerun()
 
-    # Auto-scroll (optional)
     st.markdown("""
     <script>
     const c = window.parent.document.querySelector('.chat-container');