Initial commit of EAC Translator

.gitignore

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+# Python cache
+__pycache__/
+*.pyc
+
+# Audio output
+*.wav
+
+# Virtual environments
+venv/
+env/
+opus-env/
+
+# System files
+.DS_Store
+Thumbs.db

README.md

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+# 🌍 EAC Translator
+
+A multilingual translator for English, French, and Swahili with voice input and output. Built with ❤️ by [Eng. Jobbers – Qtrinova Inc](https://eng-jobbers.vercel.app/).
+
+## ✨ Features
+
+- 🎙️ Voice input via microphone
+- 🧠 Automatic language detection
+- 🔁 English ↔ French ↔ Swahili (with pivot logic)
+- 🎛️ Tone control (Neutral, Formal, Casual, Romantic)
+- 🔊 Text-to-speech with voice selection (David, Zira, etc.)
+- 📱 Mobile-friendly UI
+- 📤 Audio playback and download
+
+## 🚀 Built With
+
+- [Gradio](https://gradio.app)
+- [Hugging Face Transformers](https://huggingface.co/transformers/)
+- [pyttsx3](https://pypi.org/project/pyttsx3/)
+- [SpeechRecognition](https://pypi.org/project/SpeechRecognition/)
+- [langid](https://pypi.org/project/langid/)
+
+## 📦 Installation (Optional for Local Use, especially VScode env setup, well tested)
+
+```bash
+pip install -r requirements.txt
+python app.py

app.py

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+import gradio as gr
+from transformers import MarianMTModel, MarianTokenizer
+from datetime import datetime
+import langid
+import os
+import pyttsx3
+import time
+import warnings
+
+warnings.filterwarnings("ignore", message="Recommended: pip install sacremoses.")
+os.environ["PATH"] += os.pathsep + r"C:\ffmpeg\bin"
+langid.set_languages(['en', 'fr', 'sw'])
+
+MODEL_MAP = {
+    "English → Swahili": "Helsinki-NLP/opus-mt-en-sw",
+    "English → French": "Helsinki-NLP/opus-mt-en-fr",
+    "French → English": "Helsinki-NLP/opus-mt-fr-en",
+    "French → Swahili (via English)": ["Helsinki-NLP/opus-mt-fr-en", "Helsinki-NLP/opus-mt-en-sw"]
+}
+
+TONE_MODIFIERS = {
+    "Neutral": "",
+    "Romantic": "Express this romantically: ",
+    "Formal": "Translate this in a formal tone: ",
+    "Casual": "Make this sound casual: "
+}
+
+loaded_models = {}
+
+def load_model(model_name):
+    if model_name not in loaded_models:
+        tokenizer = MarianTokenizer.from_pretrained(model_name)
+        model = MarianMTModel.from_pretrained(model_name)
+        loaded_models[model_name] = (tokenizer, model)
+    return loaded_models[model_name]
+
+def detect_language(text):
+    try:
+        lang, score = langid.classify(text)
+        return lang
+    except:
+        return "unknown"
+
+def translate(text, direction, tone):
+    detected_lang = detect_language(text)
+    expected_src = direction.split(" → ")[0].lower()
+    warning = ""
+    if expected_src.startswith("english") and detected_lang != "en":
+        warning = f"⚠️ Detected language is '{detected_lang}', but you selected English as source."
+    elif expected_src.startswith("french") and detected_lang != "fr":
+        warning = f"⚠️ Detected language is '{detected_lang}', but you selected French as source."
+    elif expected_src.startswith("swahili") and detected_lang != "sw":
+        warning = f"⚠️ Detected language is '{detected_lang}', but you selected Swahili as source."
+
+    prompt = TONE_MODIFIERS[tone] + text
+    model_info = MODEL_MAP[direction]
+
+    if isinstance(model_info, list):
+        tokenizer1, model1 = load_model(model_info[0])
+        encoded1 = tokenizer1(prompt, return_tensors="pt", padding=True, truncation=True)
+        intermediate = model1.generate(**encoded1)
+        intermediate_text = tokenizer1.decode(intermediate[0], skip_special_tokens=True)
+
+        tokenizer2, model2 = load_model(model_info[1])
+        encoded2 = tokenizer2(intermediate_text, return_tensors="pt", padding=True, truncation=True)
+        final = model2.generate(**encoded2)
+        translation = tokenizer2.decode(final[0], skip_special_tokens=True)
+    else:
+        tokenizer, model = load_model(model_info)
+        encoded = tokenizer(prompt, return_tensors="pt", padding=True, truncation=True)
+        generated = model.generate(**encoded)
+        translation = tokenizer.decode(generated[0], skip_special_tokens=True)
+
+    with open("translation_log.txt", "a", encoding="utf-8") as f:
+        f.write(f"[{datetime.now()}] {direction} | Tone: {tone}\n")
+        f.write(f"Input: {text}\nOutput: {translation}\n\n")
+
+    return f"{warning}\n{translation}" if warning else translation
+
+engine = pyttsx3.init()
+voices = engine.getProperty('voices')
+voice_names = [voice.name for voice in voices]
+
+def speak_text_to_file(text, voice_name):
+    try:
+        engine = pyttsx3.init()
+        engine.setProperty('rate', 150)
+        for voice in voices:
+            if voice.name == voice_name:
+                engine.setProperty('voice', voice.id)
+                break
+        output_path = "tts_output.wav"
+        engine.save_to_file(text, output_path)
+        engine.runAndWait()
+        return output_path
+    except Exception:
+        return None
+
+def transcribe_and_translate(audio_path, direction, tone):
+    import speech_recognition as sr
+    recognizer = sr.Recognizer()
+    try:
+        with sr.AudioFile(audio_path) as source:
+            audio = recognizer.record(source)
+        if len(audio.frame_data) < 10000:
+            return "⚠️ Audio too short or empty. Please try again."
+        text = recognizer.recognize_google(audio)
+        return translate(text, direction, tone)
+    except Exception as e:
+        return f"⚠️ Could not transcribe audio: {e}"
+
+with gr.Blocks(theme=gr.themes.Soft()) as demo:
+    gr.Markdown("## 🌍 EAC Translator")
+    gr.Markdown("Supports English, French, and Swahili. Includes tone control, language detection, voice input, and speech playback.")
+
+    with gr.Tabs():
+        with gr.Tab("📝 Text Translation"):
+            with gr.Column():
+                input_text = gr.Textbox(label="Text to Translate", lines=3)
+                direction = gr.Dropdown(choices=list(MODEL_MAP.keys()), label="Translation Direction", value="English → Swahili")
+                tone = gr.Radio(choices=list(TONE_MODIFIERS.keys()), label="Tone", value="Neutral")
+                output_text = gr.Textbox(label="Translated Text", lines=3)
+                voice_choice = gr.Dropdown(choices=voice_names, label="Voice for Playback", value=voice_names[0])
+                with gr.Row():
+                    translate_btn = gr.Button("Translate", scale=1)
+                    speak_btn = gr.Button("🔊 Listen to Translation", scale=1)
+                audio_output = gr.Audio(label="Playback", interactive=False)
+
+        with gr.Tab("🎙️ Voice Translation"):
+            with gr.Column():
+                audio_input = gr.Audio(sources=["microphone"], type="filepath", label="Speak Now")
+                direction_voice = gr.Dropdown(choices=list(MODEL_MAP.keys()), label="Translation Direction", value="English → Swahili")
+                tone_voice = gr.Radio(choices=list(TONE_MODIFIERS.keys()), label="Tone", value="Neutral")
+                voice_output = gr.Textbox(label="Translated Text")
+                voice_choice2 = gr.Dropdown(choices=voice_names, label="Voice for Playback", value=voice_names[0])
+                with gr.Row():
+                    voice_translate_btn = gr.Button("Transcribe & Translate", scale=1)
+                    voice_speak_btn = gr.Button("🔊 Listen to Translation", scale=1)
+                audio_output2 = gr.Audio(label="Playback", interactive=False)
+
+        translate_btn.click(fn=translate, inputs=[input_text, direction, tone], outputs=output_text)
+        speak_btn.click(fn=speak_text_to_file, inputs=[output_text, voice_choice], outputs=audio_output)
+        voice_translate_btn.click(fn=transcribe_and_translate, inputs=[audio_input, direction_voice, tone_voice], outputs=voice_output)
+        voice_speak_btn.click(fn=speak_text_to_file, inputs=[voice_output, voice_choice2], outputs=audio_output2)
+
+    gr.Markdown(
+        """<div style='text-align: center;'>
+        <a href='https://eng-jobbers.vercel.app/' target='_blank' style='text-decoration: none; font-weight: bold;'>
+        By Eng. Jobbers – Qtrinova Inc. NLP❤️
+        </a>
+        </div>""",
+        elem_id="footer"
+    )
+
+demo.launch()

requirements.txt

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+gradio==5.35.0
+transformers==4.53.0
+torch==2.7.1
+sentencepiece==0.2.0
+langid
+speechrecognition
+pydub
+pyttsx3
+sacremoses