Create app.py

app.py

@@ -0,0 +1,114 @@
+import gradio as gr
+from groq import Groq
+import edge_tts
+import asyncio
+import random
+import os
+
+# --- INITIALIZATION ---
+# Hugging Face will look for the secret 'API_KEY_IS_HERE' in the Settings tab
+api_key = os.environ.get("API_KEY_IS_HERE")
+client = Groq(api_key=api_key)
+
+LLM_MODEL = "llama-3.3-70b-versatile"
+STT_MODEL = "whisper-large-v3"
+
+# --- DATASET ---
+LOGIC_VAULT = [
+    "Synthesize an optimization strategy for a sharded database architecture.",
+    "Evaluate the logical implications of CAP theorem in a globally distributed system.",
+    "Design a zero-trust security protocol for high-latency neural networks.",
+    "Analyze the structural integrity of a non-blocking I/O multiplexing system."
+]
+
+# --- CORE LOGIC ---
+def mentor_brain(user_text):
+    challenge = random.choice(LOGIC_VAULT)
+    sys_prompt = f"""You are a Lead Systems Architect. 
+    1. Acknowledge user input with high-level precision.
+    2. Present this architectural challenge: {challenge}
+    3. Use bold, technical language.
+    4. Maximum 35 words."""
+    
+    completion = client.chat.completions.create(
+        model=LLM_MODEL,
+        messages=[{"role": "system", "content": sys_prompt}, {"role": "user", "content": user_text}]
+    )
+    return completion.choices[0].message.content
+
+def transcribe_voice(audio_path):
+    with open(audio_path, "rb") as file:
+        return client.audio.transcriptions.create(file=(audio_path, file.read()), model=STT_MODEL, response_format="text")
+
+async def synthesize_voice(text):
+    output_file = "mentor_hq.mp3"
+    communicate = edge_tts.Communicate(text, "en-US-AndrewNeural")
+    await communicate.save(output_file)
+    return output_file
+
+async def master_process(audio_path):
+    if not audio_path: return "AWAITING SIGNAL...", "...", None
+    try:
+        user_speech = transcribe_voice(audio_path)
+        mentor_text = mentor_brain(user_speech)
+        mentor_audio = await synthesize_voice(mentor_text)
+        return user_speech, mentor_text, mentor_audio
+    except Exception as e:
+        return f"Error: {str(e)}", "Please check API Key secrets.", None
+
+# --- UI STYLING ---
+titan_css = """
+.gradio-container {background-color: #000000 !important; font-family: 'Helvetica', 'Arial', sans-serif !important;}
+#main-header {text-align: center; color: #ffffff !important; font-weight: 900 !important; font-size: 4em !important; letter-spacing: -3px; margin-bottom: 0px; text-transform: uppercase;}
+#dev-tag {text-align: center; color: #00e5ff !important; font-weight: 800 !important; font-size: 1.2em !important; margin-top: -15px; letter-spacing: 5px; text-transform: uppercase;}
+.glow-divider {height: 3px; background: linear-gradient(90deg, transparent, #00e5ff, #0051ff, transparent); margin: 30px 0; box-shadow: 0 0 20px rgba(0, 229, 255, 0.4);}
+.titan-btn {
+    background: #00e5ff !important;
+    border: none !important;
+    color: #000000 !important;
+    border-radius: 0px !important;
+    font-weight: 900 !important;
+    text-transform: uppercase !important;
+    letter-spacing: 2px !important;
+    height: 50px !important;
+    transition: all 0.3s cubic-bezier(0.175, 0.885, 0.32, 1.275) !important;
+}
+.titan-btn:hover {
+    background: #ffffff !important;
+    box-shadow: 0 0 30px rgba(0, 229, 255, 0.6);
+    transform: translateY(-3px);
+}
+.obsidian-panel {
+    border: 1px solid #111111 !important;
+    background: #050505 !important;
+    padding: 35px !important;
+    border-radius: 0px !important;
+}
+input, textarea {
+    background-color: #080808 !important;
+    border: 1px solid #1a1a1a !important;
+    color: #ffffff !important;
+    font-weight: 700 !important;
+}
+"""
+
+with gr.Blocks(css=titan_css, theme=gr.themes.Base()) as demo:
+    gr.Markdown("# LOGICFORGE", elem_id="main-header")
+    gr.Markdown("MUHAMMAD BILAL / SENIOR DEVELOPER", elem_id="dev-tag")
+    gr.HTML("<div class='glow-divider'></div>")
+    
+    with gr.Row():
+        with gr.Column(scale=4, elem_classes="obsidian-panel"):
+            gr.Markdown("### 📡 NEURAL INPUT")
+            audio_input = gr.Audio(sources="microphone", type="filepath", label="Voice Stream")
+            submit_btn = gr.Button("INITIATE PROTOCOL", elem_classes="titan-btn")
+            
+        with gr.Column(scale=6, elem_classes="obsidian-panel"):
+            gr.Markdown("### 🧠 LOGIC SYNTHESIS")
+            user_transcript = gr.Textbox(label="Raw Transcription")
+            ai_text_reply = gr.Textbox(label="Strategic Output")
+            audio_output = gr.Audio(label="Auditory Feedback", autoplay=True)
+
+    submit_btn.click(master_process, inputs=audio_input, outputs=[user_transcript, ai_text_reply, audio_output])
+
+demo.launch()