Week 2: Technical Assistant - Salah (Bootcamp)

week2/community-contributions/salah/v2/src/ui/gradio_interface.py

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+import gradio as gr
+
+class AssistantUI:
+    def __init__(self, ai_client, audio_service, conversation_manager):
+        self.ai_client = ai_client
+        self.audio_service = audio_service
+        self.conversation = conversation_manager
+        self.display_history = []
+        
+    def handle_text_message(self, message):
+        if not message.strip():
+            return self.display_history, ""
+            
+        # Add user message
+        self.conversation.add_user_message(message)
+        self.display_history.append({"role": "user", "content": message})
+        
+        # Get AI response
+        api_messages = self.conversation.get_api_messages()
+        response = self.ai_client.chat(api_messages)
+        
+        # Check if response is an error
+        is_error = response.startswith("Error:")
+        
+        if is_error:
+            print(f"AI Client Error: {response}")
+            # Show error in chat but don't add to conversation history
+            self.display_history.append({"role": "assistant", "content": response})
+            return self.display_history, ""
+        
+        # Add successful response to conversation
+        self.conversation.add_assistant_message(response)
+        self.display_history.append({"role": "assistant", "content": response})
+        
+        return self.display_history, ""
+    
+    def handle_voice_message(self, audio_file):
+        if not audio_file:
+            return self.display_history, None
+            
+        # Transcribe audio
+        text = self.audio_service.speech_to_text(audio_file)
+        if not text:
+            return self.display_history, None
+            
+        # Add transcribed message to display
+        self.display_history.append({
+            "role": "user", 
+            "content": {"path": audio_file, "alt_text": f"Voice: {text}"}
+        })
+        
+        # Process as text message
+        self.conversation.add_user_message(text)
+        api_messages = self.conversation.get_api_messages()
+        response = self.ai_client.chat(api_messages)
+        
+        # Check if response is an error
+        is_error = response.startswith("Error:")
+        
+        if is_error:
+            print(f"AI Client Error: {response}")
+            # Show error in chat but don't convert to speech
+            self.display_history.append({"role": "assistant", "content": response})
+            return self.display_history, None
+        
+        self.conversation.add_assistant_message(response)
+        
+        # Generate audio response only for successful responses
+        audio_response = self.audio_service.text_to_speech(response)
+        
+        if audio_response:
+            self.display_history.append({
+                "role": "assistant",
+                "content": {"path": audio_response, "alt_text": response[:100] + "..."}
+            })
+        else:
+            self.display_history.append({"role": "assistant", "content": response})
+            
+        return self.display_history, None
+    
+    def analyze_code(self, code, language):
+        if not code.strip():
+            return self.display_history
+            
+        result = self.ai_client.analyze_code(code, language)
+        
+        # Check for errors
+        is_error = result.startswith("Error:")
+        
+        if is_error:
+            print(f"Code Analysis Error: {result}")
+            self.display_history.append({"role": "user", "content": f"Code analysis ({language})"})
+            self.display_history.append({"role": "assistant", "content": result})
+            return self.display_history
+        
+        # Add to conversation only if successful
+        self.conversation.add_user_message(f"Analyze {language} code")
+        self.conversation.add_assistant_message(result)
+        
+        # Add to display
+        self.display_history.append({"role": "user", "content": f"Code analysis ({language})"})
+        self.display_history.append({"role": "assistant", "content": result})
+        
+        return self.display_history
+    
+    def generate_linkedin_post(self, topic, tone):
+        if not topic.strip():
+            return self.display_history
+            
+        result = self.ai_client.generate_linkedin_post(topic, tone)
+        
+        # Check for errors
+        is_error = result.startswith("Error:")
+        
+        if is_error:
+            print(f"LinkedIn Post Generation Error: {result}")
+            self.display_history.append({"role": "user", "content": f"LinkedIn post ({tone}): {topic}"})
+            self.display_history.append({"role": "assistant", "content": result})
+            return self.display_history
+        
+        # Add to conversation only if successful
+        self.conversation.add_user_message(f"Generate LinkedIn post about: {topic}")
+        self.conversation.add_assistant_message(result)
+        
+        # Add to display
+        self.display_history.append({"role": "user", "content": f"LinkedIn post ({tone}): {topic}"})
+        self.display_history.append({"role": "assistant", "content": result})
+        
+        return self.display_history
+    
+    def create_interface(self):
+        with gr.Blocks() as app:
+            gr.Markdown("# AI Assistant")
+            gr.Markdown("Chat with text or voice")
+            
+            # Main chat
+            chat = gr.Chatbot(type="messages", height=500)
+            
+            # Input area
+            with gr.Row():
+                msg = gr.Textbox(
+                    label="Message", 
+                    placeholder="Type or record...",
+                    scale=9,
+                    container=False
+                )
+                mic = gr.Audio(
+                    sources=["microphone"],
+                    type="filepath", 
+                    label="Record",
+                    scale=1
+                )
+            
+            # Wire up events
+            msg.submit(self.handle_text_message, msg, [chat, msg])
+            mic.stop_recording(self.handle_voice_message, mic, [chat, mic])
+            
+            # Code analysis tool
+            with gr.Accordion("Code Analysis", open=False):
+                code_input = gr.Textbox(label="Code", lines=8)
+                lang_select = gr.Dropdown(
+                    choices=["python", "javascript", "java"],
+                    value="python",
+                    label="Language"
+                )
+                analyze_btn = gr.Button("Analyze")
+                
+                analyze_btn.click(
+                    self.analyze_code, 
+                    [code_input, lang_select], 
+                    chat
+                )
+            
+            # LinkedIn post generator
+            with gr.Accordion("LinkedIn Post Generator", open=False):
+                topic_input = gr.Textbox(
+                    label="Topic", 
+                    placeholder="What do you want to post about?",
+                    lines=2
+                )
+                tone_select = gr.Dropdown(
+                    choices=["professional", "casual", "inspirational", "educational"],
+                    value="professional",
+                    label="Tone"
+                )
+                generate_btn = gr.Button("Generate Post")
+                
+                generate_btn.click(
+                    self.generate_linkedin_post,
+                    [topic_input, tone_select],
+                    chat
+                )
+        
+        return app