Merge branch 'main' of https://github.com/aki-008/prepAI into frontend

Backend/app/config.py

@@ -1,7 +1,8 @@
-import os
 from pydantic_settings import BaseSettings
 
 class Settings(BaseSettings):
+    DATABASE_URL: str
+    SECRET_KEY: str
     DATABASE_URL: str = os.getenv(
         "DATABASE_URL",
         "postgresql+asyncpg://postgres:mysecretpassword@localhost:5432/studentdb"
@@ -11,17 +12,15 @@ class Settings(BaseSettings):
     SECRET_KEY: str = os.getenv("SECRET_KEY", "production")
     ALGORITHM: str = "HS256"
     ACCESS_TOKEN_EXPIRE_MINUTES: int = 30
-    
-    # Application
+
     APP_NAME: str = "Student Management API"
     APP_VERSION: str = "1.0.0"
     APP_DESCRIPTION: str = "FastAPI + PostgreSQL with SQLAlchemy async"
-    
-    # CORS
+
     CORS_ORIGINS: list = ["*"]
-    
+
     class Config:
         env_file = ".env"
-        case_sensitive = True
+        extra = "ignore"  # optional
 
-settings = Settings()
+settings = Settings()

Frontend/src/components/auth/SignIn.tsx

@@ -8,9 +8,13 @@ interface SignInProps {
   onAuthSuccess: () => void;
 }
 
-const SignIn: React.FC<SignInProps> = ({ onClose, onSwitchToSignUp, onAuthSuccess }) => {
-  // const [email, setEmail] = useState("");
-  const [username, setUserName] = useState("");
+const SignIn: React.FC<SignInProps> = ({
+  onClose,
+  onSwitchToSignUp,
+  onAuthSuccess,
+}) => {
+  const [email, setEmail] = useState("");
+  // const [username, setUserName] = useState("");
   const [password, setPassword] = useState("");
   const [error, setError] = useState("");
 
@@ -20,7 +24,7 @@ const SignIn: React.FC<SignInProps> = ({ onClose, onSwitchToSignUp, onAuthSucces
 
     try {
       const res = await API.post("/auth/login", {
-        username: username,   // 🔥 FastAPI expects `username` (OAuth2PasswordRequestForm)
+        email: email, // 🔥 FastAPI expects `username` (OAuth2PasswordRequestForm)
         password,
       });
 
@@ -47,8 +51,8 @@ const SignIn: React.FC<SignInProps> = ({ onClose, onSwitchToSignUp, onAuthSucces
             <input
               type="string"
               placeholder="username or email"
-              value={username}
-              onChange={(e) => setUserName(e.target.value)}
+              value={email}
+              onChange={(e) => setEmail(e.target.value)}
               className="w-full pl-10 py-3 bg-slate-800 border border-slate-700 text-white rounded-lg"
               required
             />
@@ -78,10 +82,12 @@ const SignIn: React.FC<SignInProps> = ({ onClose, onSwitchToSignUp, onAuthSucces
 
       <p className="mt-8 text-center text-sm text-gray-400">
         Don’t have an account?
-        <button onClick={onSwitchToSignUp} className="ml-2 text-blue-400">Sign Up</button>
+        <button onClick={onSwitchToSignUp} className="ml-2 text-blue-400">
+          Sign Up
+        </button>
       </p>
     </>
   );
 };
 
-export default SignIn;
+export default SignIn;

test/voice.py

@@ -0,0 +1,62 @@
+import sounddevice as sd
+import numpy as np
+from faster_whisper import WhisperModel
+import ollama
+import subprocess
+import time
+
+# --- Configuration ---
+# STT Model: 'tiny' or 'base' are fast; 'small' is accurate.
+stt_model = WhisperModel("base.en", device="cuda", compute_type="float16") 
+
+def record_audio(duration=5, samplerate=16000):
+    """Simple recorder - in production, use VAD (Voice Activity Detection) to stop automatically."""
+    print("Listening...")
+    recording = sd.rec(int(duration * samplerate), samplerate=samplerate, channels=1, dtype='float32')
+    sd.wait()
+    return recording.flatten()
+
+def transcribe(audio_data):
+    """Convert Audio to Text"""
+    segments, info = stt_model.transcribe(audio_data, beam_size=5)
+    text = " ".join([segment.text for segment in segments])
+    return text.strip()
+
+def generate_response(prompt):
+    """Send text to Ollama (The Brain)"""
+    response = ollama.chat(model='llama3.2', messages=[
+      {'role': 'user', 'content': prompt},
+    ])
+    return response['message']['content']
+
+def speak(text):
+    """Convert Text to Audio (The Mouth) using Piper"""
+    # Assuming you have the piper binary and a voice model downloaded
+    # Command line: echo "text" | piper --model en_US-lessac-medium.onnx --output_file output.wav
+    
+    # For this example, we'll use a generic speak command for macOS/Linux 
+    # (Replace with Piper or pyttsx3 for true local/cross-platform)
+    subprocess.call(["say", text]) 
+
+# --- Main Loop ---
+def main():
+    print("Voice Agent Started (Ctrl+C to stop)")
+    while True:
+        # 1. Listen
+        audio_data = record_audio(duration=4) # Fixed duration for simplicity
+        
+        # 2. Transcribe
+        user_text = transcribe(audio_data)
+        if not user_text: continue
+        
+        print(f"You: {user_text}")
+        
+        # 3. Think
+        ai_response = generate_response(user_text)
+        print(f"AI: {ai_response}")
+        
+        # 4. Speak
+        speak(ai_response)
+
+if __name__ == "__main__":
+    main()