Create app.py

app.py

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+import gradio as gr
+import os
+import openai
+import speech_recognition as sr
+from gtts import gTTS
+from deep_translator import GoogleTranslator
+
+def translate_text(text, target_lang):
+    translator = GoogleTranslator(source='auto', target=target_lang)
+    return translator.translate(text)
+
+def get_llm_response(prompt):
+    response = openai.ChatCompletion.create(
+        model="gpt-4-0125-preview",
+        messages=[
+            {"role": "system", "content": "You are a helpful assistant that provides informative and concise responses."},
+            {"role": "user", "content": prompt}
+        ],
+        max_tokens=150
+    )
+    return response.choices[0].message.content.strip()
+
+def process_voice_or_text(input_audio, input_text, output_lang):
+    if output_lang not in ["ta", "en"]:
+        return "Invalid output language selected. Please choose either Tamil ('ta') or English ('en').", "", "", "", None
+
+    if input_audio is not None:
+        # Process audio input
+        recognizer = sr.Recognizer()
+        with sr.AudioFile(input_audio) as source:
+            audio = recognizer.record(source)
+        try:
+            input_text = recognizer.recognize_google(audio, language="ta-IN,en-IN")
+        except sr.UnknownValueError:
+            return "Could not understand the audio input.", "", "", "", None
+        except sr.RequestError as e:
+            return f"Speech recognition error: {e}", "", "", "", None
+
+    if not input_text:
+        return "Please provide a valid input.", "", "", "", None
+
+    # Translate input to English
+    english_query = translate_text(input_text, "en")
+
+    # Get response from LLM
+    llm_response = get_llm_response(english_query)
+
+    # Translate LLM response to desired output language
+    final_response = translate_text(llm_response, output_lang)
+
+    # Generate audio output
+    audio_file = text_to_speech(final_response, output_lang)
+
+    return input_text, english_query, llm_response, final_response, audio_file
+
+def text_to_speech(response, lang):
+    lang_code = "ta" if lang == "ta" else "en"
+    tts = gTTS(text=response, lang=lang_code)
+    audio_file = "response.mp3"
+    tts.save(audio_file)
+    return audio_file
+
+# Gradio interface
+iface = gr.Interface(
+    fn=process_voice_or_text,
+    inputs=[
+        gr.Audio(type="filepath", label="Voice Input (Tamil or English)"),
+        gr.Textbox(label="Text Input (Tamil or English)", placeholder="Type your input here..."),
+        gr.Radio(["ta", "en"], label="Output Language", value="en")
+    ],
+    outputs=[
+        gr.Textbox(label="Original Input"),
+        gr.Textbox(label="Translated English Query"),
+        gr.Textbox(label="LLM Response (English)"),
+        gr.Textbox(label="Final Response (Tamil/English)"),
+        gr.Audio(type="filepath", label="Audio Output (Tamil/English)")
+    ],
+    live=True,
+    title="Nisha - Tamil-English Voice Assistant",
+    description="Speak or type in Tamil or English, and get responses in your preferred language as text or audio!"
+)
+
+iface.launch()