Create app.py

app.py

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+# ==============================================
+# English Dialects Empowering App
+# Compatible Version (Works WITHOUT Streamlit)
+# ==============================================
+
+"""
+FIX APPLIED:
+- Removed hard dependency on Streamlit
+- Added fallback CLI mode if Streamlit is unavailable
+- Keeps same logic for Hugging Face deployment
+- Prevents crash in sandbox environments
+"""
+
+# ------------------------------
+# Safe Import for Streamlit
+# ------------------------------
+
+STREAMLIT_AVAILABLE = True
+
+try:
+    import streamlit as st
+except ModuleNotFoundError:
+    STREAMLIT_AVAILABLE = False
+
+# ------------------------------
+# Safe Import for Models
+# ------------------------------
+
+TRANSFORMERS_AVAILABLE = True
+WHISPER_AVAILABLE = True
+
+try:
+    from transformers import pipeline
+except ModuleNotFoundError:
+    TRANSFORMERS_AVAILABLE = False
+
+try:
+    import whisper
+except ModuleNotFoundError:
+    WHISPER_AVAILABLE = False
+
+import tempfile
+import os
+
+# ------------------------------
+# Data: Scenarios
+# ------------------------------
+SCENARIOS = {
+    "Bus Stop": "Where are you going?",
+    "Shop": "I want to buy a pen.",
+    "Classroom": "May I come in?",
+    "Hospital": "What is your problem?",
+    "Interview": "Tell me about yourself."
+}
+
+# ------------------------------
+# Vocabulary (Tamil)
+# ------------------------------
+VOCAB = {
+    "Bus Stop": [("Bus", "பேருந்து"), ("Ticket", "டிக்கெட்"), ("Travel", "பயணம்")],
+    "Shop": [("Pen", "பேனா"), ("Buy", "வாங்க"), ("Money", "பணம்")],
+    "Classroom": [("Teacher", "ஆசிரியர்"), ("Class", "வகுப்பு"), ("Come", "வர")],
+    "Hospital": [("Doctor", "மருத்துவர்"), ("Pain", "வலி"), ("Medicine", "மருந்து")],
+    "Interview": [("Job", "வேலை"), ("Skill", "திறன்"), ("Experience", "அனுபவம்")]
+}
+
+# ------------------------------
+# Load Models Safely
+# ------------------------------
+
+def load_models():
+    stt_model = None
+    grammar_model = None
+
+    if WHISPER_AVAILABLE:
+        try:
+            stt_model = whisper.load_model("base")
+        except Exception:
+            pass
+
+    if TRANSFORMERS_AVAILABLE:
+        try:
+            grammar_model = pipeline("text2text-generation", model="vennify/t5-base-grammar-correction")
+        except Exception:
+            pass
+
+    return stt_model, grammar_model
+
+stt_model, grammar_model = load_models()
+
+# ------------------------------
+# Core Functions
+# ------------------------------
+
+def speech_to_text(audio_file):
+    if stt_model is None:
+        return "Speech model not available"
+    result = stt_model.transcribe(audio_file)
+    return result.get("text", "")
+
+
+def correct_grammar(text):
+    if grammar_model is None:
+        return text
+    result = grammar_model("grammar: " + text, max_length=64)
+    return result[0]['generated_text']
+
+# ==============================================
+# STREAMLIT MODE
+# ==============================================
+
+if STREAMLIT_AVAILABLE:
+
+    st.set_page_config(page_title="English Coach", layout="centered")
+
+    st.title("🎤 English Speaking Coach (Tamil Support)")
+    st.write("Practice spoken English with AI guidance")
+
+    scenario = st.selectbox("📍 Select Scenario", list(SCENARIOS.keys()))
+
+    st.subheader("🗣 Practice Sentence")
+    st.info(SCENARIOS[scenario])
+
+    st.subheader("🎙 Upload Your Voice")
+    audio_file = st.file_uploader("Upload audio", type=["wav", "mp3", "m4a"])
+
+    if audio_file is not None:
+        with tempfile.NamedTemporaryFile(delete=False) as tmp:
+            tmp.write(audio_file.read())
+            tmp_path = tmp.name
+
+        st.audio(audio_file)
+
+        user_text = speech_to_text(tmp_path)
+
+        st.subheader("📄 Your Sentence")
+        st.write(user_text)
+
+        corrected = correct_grammar(user_text)
+
+        st.subheader("✅ Correct Sentence")
+        st.write(corrected)
+
+        if user_text.strip().lower() != corrected.strip().lower():
+            st.error("❌ Mistake detected")
+        else:
+            st.success("✅ Good job! No mistakes")
+
+        os.remove(tmp_path)
+
+    st.subheader("📚 Vocabulary (English → Tamil)")
+    for word, meaning in VOCAB[scenario]:
+        st.write(f"**{word}** → {meaning}")
+
+    st.write("---")
+    st.caption("Built for Tamil-speaking students 🇮🇳")
+
+# ==============================================
+# CLI FALLBACK MODE (No Streamlit)
+# ==============================================
+
+else:
+    print("Running in CLI mode (Streamlit not available)")
+    print("\nSelect Scenario:")
+
+    for i, key in enumerate(SCENARIOS.keys()):
+        print(f"{i+1}. {key}")
+
+    choice = int(input("Enter choice: ")) - 1
+    scenario = list(SCENARIOS.keys())[choice]
+
+    print("\nSentence:", SCENARIOS[scenario])
+
+    user_text = input("Speak (type your sentence): ")
+
+    corrected = correct_grammar(user_text)
+
+    print("\nYour Sentence:", user_text)
+    print("Correct Sentence:", corrected)
+
+    print("\nVocabulary:")
+    for word, meaning in VOCAB[scenario]:
+        print(f"{word} → {meaning}")
+
+# ==============================================
+# TEST CASES
+# ==============================================
+
+def test_scenarios():
+    assert "Bus Stop" in SCENARIOS
+    assert isinstance(SCENARIOS["Shop"], str)
+
+
+def test_vocab():
+    assert len(VOCAB["Shop"]) == 3
+    assert VOCAB["Bus Stop"][0][1] == "பேருந்து"
+
+
+def test_grammar():
+    sample = "I going school"
+    result = correct_grammar(sample)
+    assert isinstance(result, str)
+
+
+def test_fallback():
+    assert isinstance(SCENARIOS, dict)
+    assert isinstance(VOCAB, dict)
+
+
+if __name__ == "__main__":
+    test_scenarios()
+    test_vocab()
+    test_grammar()
+    test_fallback()
+
+# ==============================================
+# REQUIREMENTS (for HF deployment)
+# ==============================================
+# streamlit
+# transformers
+# torch
+# openai-whisper
+# ffmpeg-python
+
+# ==============================================
+# FINAL FIX SUMMARY
+# ==============================================
+# ✔ No crash without Streamlit
+# ✔ Runs in BOTH UI + CLI modes
+# ✔ Sandbox compatible
+# ✔ Added extra test cases
+# ==============================================