Rename .gitattributes to app.py

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app.py

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+import gradio as gr
+import openai
+import os
+import json
+import random
+import requests
+from transformers import pipeline
+from datetime import datetime
+
+# --- Setup ---
+openai.api_key = os.getenv("OPENAI_API_KEY")
+
+emotion_classifier = pipeline("text-classification",
+                              model="j-hartmann/emotion-english-distilroberta-base")
+
+USER_FILE = "user_data.json"
+QUOTE_API = "https://api.quotable.io/random"
+
+LOCAL_QUOTES = [
+    "Every sunrise brings new hope. Keep shining.",
+    "You are capable of more than you realize.",
+    "Each step, no matter how small, is progress.",
+    "Difficult roads often lead to beautiful destinations.",
+    "The best time for new beginnings is now.",
+    "Your inner light never fades—let it guide you."
+]
+
+# --- Helper functions ---
+def load_user_data():
+    if os.path.exists(USER_FILE):
+        with open(USER_FILE, "r") as f:
+            return json.load(f)
+    return {}
+
+def save_user_data(data):
+    with open(USER_FILE, "w") as f:
+        json.dump(data, f, indent=2)
+
+def fetch_quote():
+    try:
+        r = requests.get(QUOTE_API, timeout=5)
+        if r.status_code == 200:
+            q = r.json()
+            return f"“{q['content']}” — {q['author']}"
+    except Exception:
+        pass
+    return random.choice(LOCAL_QUOTES)
+
+def classify_emotion(text):
+    try:
+        result = emotion_classifier(text)
+        return result[0]["label"].lower()
+    except Exception:
+        return "neutral"
+
+def get_color_for_emotion(e):
+    palette = {
+        "happy": "#fff59d",
+        "joy": "#fff59d",
+        "sad": "#90caf9",
+        "angry": "#ff8a65",
+        "calm": "#a5d6a7",
+        "motivated": "#ffcc80",
+        "neutral": "#eeeeee",
+    }
+    return palette.get(e.lower(), "#f5f5f5")
+
+# --- Core logic ---
+def chat_with_bot(message, name, age, audio=None):
+    if not message and audio:
+        # if user spoke instead of typed
+        import speech_recognition as sr
+        recognizer = sr.Recognizer()
+        with sr.AudioFile(audio) as src:
+            audio_data = recognizer.record(src)
+        try:
+            message = recognizer.recognize_google(audio_data)
+        except Exception:
+            message = "..."
+
+    if not message:
+        return "Please say or type something.", None, None
+
+    user_id = "default"
+    users = load_user_data()
+    user = users.get(user_id, {"name": name, "age": age, "recent_mood": "neutral"})
+    emotion = classify_emotion(message)
+
+    # Motivational triggers
+    if "motivate" in message.lower() or "guidance" in message.lower():
+        quote = fetch_quote()
+        user["recent_mood"] = "motivated"
+        users[user_id] = user
+        save_user_data(users)
+        return quote, None, get_color_for_emotion("motivated")
+
+    # Normal empathetic reply
+    prompt = f"""
+You are a warm, empathetic emotional support companion.
+The user's name is {name}, age {age}, currently feeling {emotion}.
+Reply with kindness, encouragement, and positivity.
+Avoid therapy or diagnosis.
+
+User: {message}
+Assistant:
+"""
+    try:
+        response = openai.ChatCompletion.create(
+            model="gpt-4o-mini",
+            messages=[{"role": "user", "content": prompt}],
+            temperature=0.8
+        )
+        reply = response.choices[0].message["content"].strip()
+    except Exception:
+        reply = "I'm here for you. Tell me how you’re feeling today."
+
+    # Save user state
+    user["recent_mood"] = emotion
+    user["last_active"] = datetime.utcnow().strftime("%Y-%m-%d")
+    users[user_id] = user
+    save_user_data(users)
+
+    return reply, reply, get_color_for_emotion(emotion)
+
+# --- Gradio UI ---
+with gr.Blocks(title="Empathetic Voice Chatbot 🌼") as app:
+    gr.Markdown(
+        "## 🌼 Empathetic Voice Chatbot\n"
+        "Speak or type your feelings — your friendly listener will respond with warmth and understanding."
+    )
+
+    with gr.Row():
+        name = gr.Textbox(label="Your Name", value="Alex")
+        age = gr.Number(label="Your Age", value=25)
+
+    chatbox = gr.Textbox(label="Type your message", placeholder="Say something or click record below...")
+    mic = gr.Audio(sources=["microphone"], type="filepath", label="🎤 Speak here")
+    output_text = gr.Textbox(label="Assistant's Response")
+    audio_reply = gr.Audio(label="🔊 Spoken Reply")
+
+    send_btn = gr.Button("Send / Talk 💬")
+
+    def respond(msg, n, a, aud):
+        text_reply, tts_text, color = chat_with_bot(msg, n, a, aud)
+        if tts_text:
+            speech = openai.audio.speech.with_streaming_response.create(
+                model="gpt-4o-mini-tts",
+                voice="alloy",
+                input=tts_text
+            )
+            out_path = "reply.mp3"
+            with open(out_path, "wb") as f:
+                f.write(speech.read())
+        else:
+            out_path = None
+        # Dynamically change background color
+        app.theme = None
+        return gr.update(value=text_reply), out_path
+
+    send_btn.click(respond, [chatbox, name, age, mic], [output_text, audio_reply])
+
+app.launch()