Rename translation/app.py to stt_app.py

stt_app.py

@@ -0,0 +1,24 @@
+import gradio as gr
+from transformers import pipeline
+
+# Load Whisper model
+stt_pipeline = pipeline("automatic-speech-recognition", model="openai/whisper-small")
+
+def transcribe(audio):
+    if audio is None:
+        return "Please record some audio."
+    result = stt_pipeline(audio)
+    return result["text"]
+
+with gr.Blocks() as demo:
+    gr.Markdown("# 🎙️ Speech to Text Converter")
+    gr.Markdown("Supports **English, Spanish, French, German, Portuguese, Italian, Russian, Chinese**")
+
+    with gr.Row():
+        with gr.Column():
+            audio_input = gr.Audio(sources=["microphone"], type="filepath", label="🎤 Record Speech")
+            transcribe_btn = gr.Button("Transcribe")
+        with gr.Column():
+            output_text = gr.Textbox(label="📝 Transcribed Text", lines=8)
+
+    transcribe_btn.click(fn=transcribe, inputs=audio_input, outputs=output_text)

translation/app.py

@@ -1,121 +0,0 @@
-import os
-import json
-import requests
-import gradio as gr
-from langdetect import detect, LangDetectException
-
-# Hugging Face Transformers
-from transformers import M2M100ForConditionalGeneration, M2M100Tokenizer
-
-# Groq SDK
-try:
-    from groq import Groq
-except Exception:
-    Groq = None
-
-# Config
-GROQ_API_KEY = os.getenv("GROQ_API_KEY")         
-GROQ_MODEL = os.getenv("GROQ_MODEL", "mixtral-8x7b-32768")
-HUGGINGFACE_TOKEN = os.getenv("HUGGINGFACE_TOKEN")
-
-# Init Groq
-groq_client = None
-if GROQ_API_KEY and Groq is not None:
-    try:
-        groq_client = Groq(api_key=GROQ_API_KEY)
-    except Exception as e:
-        print("Groq client init failed:", repr(e))
-
-# Universal translation model
-m2m_model_name = "facebook/m2m100_418M"
-m2m_tokenizer = M2M100Tokenizer.from_pretrained(m2m_model_name)
-m2m_model = M2M100ForConditionalGeneration.from_pretrained(m2m_model_name)
-
-# UI mapping
-LANG_UI_TO_CODE = {"English": "en", "Spanish": "es", "French": "fr"}
-
-SYSTEM_PROMPT = """
-You are a multilingual translation assistant.
-Task:
-1. Detect the input language automatically.
-2. Translate into the requested target language.
-3. Preserve meaning, tone, and formatting.
-4. Keep numbers, symbols, names, and special characters unchanged.
-5. If the input is already in the target language, return it unchanged.
-"""
-
-def call_groq(user_text, target_lang_ui):
-    if not groq_client:
-        raise RuntimeError("Groq client not configured")
-    messages = [
-        {"role": "system", "content": SYSTEM_PROMPT},
-        {"role": "user", "content": f"Target language: {target_lang_ui}\n\n{user_text}"},
-    ]
-    chat = groq_client.chat.completions.create(
-        model=GROQ_MODEL,
-        messages=messages,
-        temperature=0,
-        max_tokens=2048,
-    )
-    try:
-        return chat.choices[0].message.content.strip()
-    except Exception:
-        try:
-            return chat["choices"][0]["message"]["content"].strip()
-        except Exception as e:
-            print("Unexpected Groq response:", repr(e))
-            raise
-
-def call_m2m(user_text, target_code):
-    try:
-        src_code = detect(user_text)
-    except LangDetectException:
-        src_code = "en"  # fallback
-
-    # if already target language → return as-is
-    if src_code == target_code:
-        return user_text
-
-    m2m_tokenizer.src_lang = src_code
-    encoded = m2m_tokenizer(user_text, return_tensors="pt")
-    generated = m2m_model.generate(
-        **encoded, forced_bos_token_id=m2m_tokenizer.get_lang_id(target_code)
-    )
-    return m2m_tokenizer.decode(generated[0], skip_special_tokens=True)
-
-def translate_text(user_text, target_lang_ui):
-    user_text = (user_text or "").strip()
-    if not user_text:
-        return "⚠️ Please enter some text to translate."
-    target_code = LANG_UI_TO_CODE.get(target_lang_ui, "en")
-
-    # Try Groq first
-    try:
-        if groq_client:
-            out = call_groq(user_text, target_lang_ui)
-            if out:
-                return out
-    except Exception as e:
-        print("Groq call failed:", repr(e))
-
-    # Fallback → M2M100 universal translator
-    try:
-        return call_m2m(user_text, target_code)
-    except Exception as e:
-        print("M2M100 translation failed:", repr(e))
-        return "❌ Translation failed. Check logs."
-
-# ----------------- Gradio UI -----------------
-with gr.Blocks() as demo:
-    gr.Markdown("## 🌐 Hackathon Translator (Universal)")
-
-    with gr.Row():
-        txt = gr.Textbox(label="Enter your text", lines=6, placeholder="Type or paste text here...")
-        tgt = gr.Dropdown(choices=["English","Spanish","French"], value="English", label="Target Language")
-
-    out = gr.Textbox(label="Translated Output", lines=6)
-    btn = gr.Button("Translate")
-    btn.click(fn=translate_text, inputs=[txt, tgt], outputs=[out])
-
-if __name__ == "__main__":
-    demo.launch()