Create app.py

app.py

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+import os
+import time
+import streamlit as st
+from transformers import pipeline
+from youtubesearchpython import VideosSearch
+
+# -----------------------------
+# App Setup / Config
+# -----------------------------
+os.environ.setdefault("PYTORCH_ENABLE_MPS_FALLBACK", "1")  # quiet Mac MPS warnings
+st.set_page_config(page_title="Moodify 🎶", page_icon="🎵", layout="centered")
+
+st.title("🎵 Moodify – AI Music Recommender")
+st.caption("Type how you feel (or speak locally), I'll detect your emotion and play matching music 🎶")
+
+# Detect if we're on Hugging Face Space
+RUNNING_IN_SPACE = "SPACE_ID" in os.environ
+
+# -----------------------------
+# Optional voice input (only local)
+# -----------------------------
+use_voice = False
+if not RUNNING_IN_SPACE:
+    try:
+        import speech_recognition as sr  # optional local dependency
+        use_voice = True
+    except Exception:
+        # Keep running; voice is optional
+        pass
+
+# -----------------------------
+# Load emotion model (cached)
+# -----------------------------
+@st.cache_resource(show_spinner=False)
+def load_emotion_model():
+    # DistilRoBERTa emotion model (lightweight & accurate)
+    # Returns top label by default (pipeline default top_k=1)
+    return pipeline("sentiment-analysis", model="j-hartmann/emotion-english-distilroberta-base", device=-1)
+
+emotion_model = load_emotion_model()
+
+# -----------------------------
+# Utilities
+# -----------------------------
+def detect_emotion(text: str) -> str:
+    """Return lowercase emotion label from model."""
+    try:
+        res = emotion_model(text)[0]
+        label = res["label"].lower()
+        return label
+    except Exception:
+        return "neutral"
+
+# Map detected emotions → search moods/genres
+EMOTION_TO_MOOD = {
+    "joy": "happy",
+    "love": "romantic",
+    "anger": "calm",        # steer to calming music
+    "sadness": "sad",
+    "fear": "relaxing",
+    "surprise": "energetic",
+    "disgust": "moody",
+    "neutral": "chill"
+}
+
+# Extra moods you can pick manually
+MOOD_OPTIONS = sorted(list(set(EMOTION_TO_MOOD.values()) | {"lofi", "focus", "party", "workout", "sleep"}))
+
+@st.cache_data(show_spinner=False)
+def yt_search(query: str, limit: int = 6):
+    vs = VideosSearch(query, limit=limit)
+    data = vs.result()
+    items = data.get("result", [])
+    # Return (title, url, id)
+    parsed = []
+    for v in items:
+        title = v.get("title", "Untitled")
+        link = v.get("link")
+        vid_id = None
+        # Most links are standard watch?v=..; if not, just pass link to st.video()
+        if link and "watch?v=" in link:
+            vid_id = link.split("watch?v=")[-1].split("&")[0]
+        parsed.append((title, link, vid_id))
+    return parsed
+
+def get_voice_input() -> str | None:
+    """Record a short phrase and transcribe with Google (local only)."""
+    try:
+        recognizer = sr.Recognizer()
+        with sr.Microphone() as source:
+            st.info("🎙️ Speak now…")
+            audio = recognizer.listen(source, timeout=5, phrase_time_limit=7)
+        text = recognizer.recognize_google(audio)
+        st.success(f"You said: **{text}**")
+        return text
+    except sr.UnknownValueError:
+        st.error("I couldn't understand—try again.")
+    except sr.WaitTimeoutError:
+        st.error("No voice detected—try again.")
+    except Exception as e:
+        st.error(f"Voice error: {e}")
+    return None
+
+# -----------------------------
+# UI
+# -----------------------------
+st.write("### How do you want to share your mood?")
+if use_voice:
+    input_mode = st.radio("Input method", ["Type", "Speak"], horizontal=True)
+else:
+    input_mode = "Type"
+    if RUNNING_IN_SPACE:
+        st.info("🎙️ Voice input is disabled on Hugging Face Spaces. Use text input below.")
+
+user_text = ""
+if input_mode == "Type":
+    user_text = st.text_input("Tell me how you feel (e.g., “I feel lonely”, “I’m excited for tonight”)")
+else:
+    if st.button("🎤 Tap to Speak"):
+        said = get_voice_input()
+        if said:
+            user_text = said
+
+# If user gave any text, detect emotion → propose mood; else let them manually pick
+detected_emotion = None
+detected_mood = None
+
+if user_text.strip():
+    with st.spinner("Analyzing your feelings…"):
+        detected_emotion = detect_emotion(user_text)
+    st.write(f"**Detected emotion:** `{detected_emotion}`")
+    detected_mood = EMOTION_TO_MOOD.get(detected_emotion, "chill")
+
+# Manual override dropdown (preselect detected mood if we have it)
+st.write("### Choose/adjust mood")
+default_index = MOOD_OPTIONS.index(detected_mood) if detected_mood in MOOD_OPTIONS else MOOD_OPTIONS.index("chill")
+chosen_mood = st.selectbox(
+    "Adjust if needed (auto set from your feelings):",
+    MOOD_OPTIONS,
+    index=default_index
+)
+
+# Generate playlist
+if st.button("🎵 Generate Playlist"):
+    if not user_text.strip() and not detected_mood:
+        st.warning("Type how you feel or use the dropdown to pick a mood.")
+    else:
+        query = f"{chosen_mood} songs playlist"
+        with st.spinner(f"Finding {chosen_mood} tracks on YouTube…"):
+            songs = yt_search(query, limit=6)
+
+        if not songs:
+            st.error("No songs found. Try a different mood.")
+        else:
+            st.subheader("🎶 Your Moodify Playlist")
+            # Autoplay first track if possible
+            first = songs[0]
+            if first[2]:  # have video id
+                # Embed playlist style (first as main, others as queue)
+                ids = [s[2] for s in songs if s[2]]
+                if len(ids) > 1:
+                    embed_url = f"https://www.youtube.com/embed/{ids[0]}?autoplay=1&playlist={','.join(ids[1:])}"
+                else:
+                    embed_url = f"https://www.youtube.com/embed/{ids[0]}?autoplay=1"
+                st.components.v1.iframe(embed_url, height=420, width=720)
+            else:
+                # Fallback to direct video link
+                st.video(first[1])
+
+            with st.expander("Show track list"):
+                for title, link, _ in songs:
+                    st.markdown(f"- [{title}]({link})")
+
+            st.success("Enjoy your music! 🎧")