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| import gradio as gr | |
| import requests | |
| import numpy as np | |
| import soundfile as sf | |
| import io | |
| import tempfile | |
| import os | |
| from groq import Groq | |
| from crdt import warn | |
| # Language configuration | |
| LANGUAGE_CONFIG = { | |
| "English": { | |
| "voice_id": "vits-eng-1", | |
| "whisper_lang": "en", | |
| "system_prompt": "You are a language tutor. Your goal is to help students practice language skills in English by engaging in conversations with them. As part of your responses, give them feedback on their English proficiency if needed. If they make a clear mistake (vocabulary or grammar, not spelling), indicate it gently and explain how to correct them. Please respond in English. Keep your answers very concise. Note that you are used in a school setting and should refuse to answer or produce any content that is violent, sexual, discriminatory, or inappropriate for children under 13." | |
| }, | |
| "French": { | |
| "voice_id": "vits-fra-1", | |
| "whisper_lang": "fr", | |
| "system_prompt": "You are a language tutor. Your goal is to help students practice language skills in French by engaging in conversations with them. As part of your responses, give them feedback on their French proficiency if needed. If they make a clear mistake (vocabulary or grammar, not spelling), indicate it gently and explain how to correct them. Please respond in French. Keep your answers very concise. Note that you are used in a school setting and should refuse to answer or produce any content that is violent, sexual, discriminatory, or inappropriate for children under 13." | |
| }, | |
| "Spanish": { | |
| "voice_id": "vits-spa-1", | |
| "whisper_lang": "es", | |
| "system_prompt": "You are a language tutor. Your goal is to help students practice language skills in Spanish by engaging in conversations with them. As part of your responses, give them feedback on their Spanish proficiency if needed. If they make a clear mistake (vocabulary or grammar, not spelling), indicate it gently and explain how to correct them. Please respond in Spanish. Keep your answers very concise. Note that you are used in a school setting and should refuse to answer or produce any content that is violent, sexual, discriminatory, or inappropriate for children under 13." | |
| } | |
| } | |
| def generate_audio(text: str, neets_api_key: str, language: str) -> tuple[int, np.ndarray]: | |
| """Generate audio from text using Neets API""" | |
| print(f"Generating audio for text in {language}:", text) | |
| try: | |
| # Make request with simplified params | |
| response = requests.post( | |
| url="https://api.neets.ai/v1/tts", | |
| headers={ | |
| "Content-Type": "application/json", | |
| "X-API-Key": neets_api_key | |
| }, | |
| json={ | |
| "text": text, | |
| "voice_id": LANGUAGE_CONFIG[language]["voice_id"], | |
| "params": { | |
| "model": "vits" | |
| } | |
| } | |
| ) | |
| print(f"TTS Response status: {response.status_code}") | |
| if response.status_code != 200: | |
| print(f"TTS Response content: {response.content.decode()}") | |
| raise ValueError(f"TTS API returned status code {response.status_code}") | |
| # Save the audio to a temporary file | |
| with tempfile.NamedTemporaryFile(suffix='.mp3', delete=False) as temp_file: | |
| temp_file.write(response.content) | |
| temp_path = temp_file.name | |
| # Read the audio file | |
| audio_data, sample_rate = sf.read(temp_path) | |
| # Convert to mono if stereo | |
| if len(audio_data.shape) > 1: | |
| audio_data = np.mean(audio_data, axis=1) | |
| # Convert to float32 if needed | |
| if audio_data.dtype != np.float32: | |
| audio_data = audio_data.astype(np.float32) | |
| # Clean up the temporary file | |
| os.unlink(temp_path) | |
| return sample_rate, audio_data | |
| except Exception as e: | |
| print(f"Audio generation error: {str(e)}") | |
| if hasattr(response, 'content'): | |
| print(f"Response content: {response.content[:100]}") # Print first 100 bytes | |
| raise | |
| def transcribe_audio(audio_path: str, groq_api_key: str, language: str) -> str: | |
| """Transcribe audio using Groq's Whisper API""" | |
| client = Groq(api_key=groq_api_key) | |
| try: | |
| with open(audio_path, "rb") as audio_file: | |
| transcription = client.audio.transcriptions.create( | |
| file=(audio_path, audio_file.read()), | |
| model="whisper-large-v3-turbo", | |
| response_format="json", | |
| language=LANGUAGE_CONFIG[language]["whisper_lang"], | |
| temperature=0.0 | |
| ) | |
| return transcription.text | |
| except Exception as e: | |
| print(f"Transcription error: {str(e)}") | |
| raise | |
| def chat_with_groq(messages: list, groq_api_key: str, language: str) -> str: | |
| """Send chat request to Groq API""" | |
| client = Groq(api_key=groq_api_key) | |
| try: | |
| response = client.chat.completions.create( | |
| model="llama-3.2-90b-vision-preview", | |
| messages=[ | |
| {"role": "system", "content": LANGUAGE_CONFIG[language]["system_prompt"]}, | |
| *messages | |
| ], | |
| temperature=0.7 | |
| ) | |
| return response.choices[0].message.content | |
| except Exception as e: | |
| print(f"Groq chat error: {str(e)}") | |
| raise | |
| def process_voice_message(audio, history, neets_api_key: str, groq_api_key: str, | |
| english: bool, french: bool, spanish: bool): | |
| """Process recorded voice message""" | |
| if not all([neets_api_key, groq_api_key]): | |
| return "", [{"role": "error", "content": "Please provide all API keys."}], None | |
| # Check language selection | |
| selected_languages = [] | |
| if english: selected_languages.append("English") | |
| if french: selected_languages.append("French") | |
| if spanish: selected_languages.append("Spanish") | |
| if not selected_languages: | |
| return "", [{"role": "error", "content": "Please select at least one language."}], None | |
| if len(selected_languages) > 1: | |
| return "", [{"role": "error", "content": "Please select only one language."}], None | |
| selected_language = selected_languages[0] | |
| print(f"Selected language: {selected_language}") | |
| try: | |
| # Save the recorded audio to a temporary file | |
| if isinstance(audio, tuple): | |
| sr, data = audio | |
| with tempfile.NamedTemporaryFile(suffix='.wav', delete=False) as temp_file: | |
| sf.write(temp_file.name, data, sr) | |
| temp_path = temp_file.name | |
| else: | |
| temp_path = audio | |
| # Transcribe the audio using Groq | |
| transcribed_text = transcribe_audio(temp_path, groq_api_key, selected_language) | |
| print(f"Transcribed text: {transcribed_text}") | |
| # Clean up temporary file if we created one | |
| if isinstance(audio, tuple): | |
| os.unlink(temp_path) | |
| # Prepare messages | |
| messages = [] | |
| for msg in (history or []): | |
| if isinstance(msg, dict): | |
| messages.append({ | |
| "role": msg["role"], | |
| "content": msg["content"] | |
| }) | |
| # Add transcribed message | |
| messages.append({ | |
| "role": "user", | |
| "content": transcribed_text | |
| }) | |
| # Get chat completion from Groq | |
| bot_response = chat_with_groq(messages, groq_api_key, selected_language) | |
| print(f"Bot response: {bot_response}") | |
| # Generate audio for the response | |
| try: | |
| sample_rate, audio_data = generate_audio(bot_response, neets_api_key, selected_language) | |
| audio_output = (sample_rate, audio_data) | |
| except Exception as audio_error: | |
| print(f"Audio generation error: {audio_error}") | |
| audio_output = None | |
| # Update history with new messages | |
| new_history = messages + [ | |
| {"role": "assistant", "content": bot_response} | |
| ] | |
| return transcribed_text, new_history, audio_output | |
| except Exception as e: | |
| print(f"Processing error: {str(e)}") | |
| return "", [{"role": "error", "content": f"Error: {str(e)}"}], None | |
| # Create Gradio interface | |
| with gr.Blocks() as demo: | |
| gr.Image(value="https://i.postimg.cc/L830G7XS/ED-COACH.jpg", type="url", elem_id="top-image").style(full_width=True) | |
| gr.Markdown("# Multilingual Tutor") | |
| with gr.Row(): | |
| neets_api_key = gr.Textbox( | |
| label="Neets API Key", | |
| type="password", | |
| placeholder="Enter your Neets API key here" | |
| ) | |
| groq_api_key = gr.Textbox( | |
| label="Groq API Key", | |
| type="password", | |
| placeholder="Enter your Groq API key here" | |
| ) | |
| with gr.Row(): | |
| gr.Markdown("### Select Language") | |
| english_checkbox = gr.Checkbox(label="English", value=True) | |
| french_checkbox = gr.Checkbox(label="French") | |
| spanish_checkbox = gr.Checkbox(label="Spanish") | |
| chatbot = gr.Chatbot( | |
| type="messages", | |
| show_copy_button=True, | |
| layout="bubble" | |
| ) | |
| with gr.Row(): | |
| # Audio recorder for voice input | |
| audio_input = gr.Audio( | |
| label="Record Message", | |
| sources=["microphone"], | |
| type="numpy" | |
| ) | |
| # Display transcribed text | |
| transcribed_msg = gr.Textbox( | |
| label="Transcribed Message", | |
| placeholder="Your message will appear here after recording...", | |
| interactive=False | |
| ) | |
| # Audio output for bot response | |
| audio_output = gr.Audio( | |
| label="Bot Voice", | |
| autoplay=True, | |
| type="numpy" | |
| ) | |
| # Add clear button | |
| clear = gr.Button("Clear Conversation") | |
| # Handle audio submission | |
| audio_input.stop_recording( | |
| process_voice_message, | |
| inputs=[ | |
| audio_input, chatbot, neets_api_key, groq_api_key, | |
| english_checkbox, french_checkbox, spanish_checkbox | |
| ], | |
| outputs=[transcribed_msg, chatbot, audio_output] | |
| ) | |
| # Make checkboxes mutually exclusive | |
| english_checkbox.change( | |
| lambda x: (False, False) if x else (False, False), | |
| inputs=english_checkbox, | |
| outputs=[french_checkbox, spanish_checkbox] | |
| ) | |
| french_checkbox.change( | |
| lambda x: (False, False) if x else (False, False), | |
| inputs=french_checkbox, | |
| outputs=[english_checkbox, spanish_checkbox] | |
| ) | |
| spanish_checkbox.change( | |
| lambda x: (False, False) if x else (False, False), | |
| inputs=spanish_checkbox, | |
| outputs=[english_checkbox, french_checkbox] | |
| ) | |
| # Handle clear button | |
| clear.click( | |
| lambda: ("", [], None), | |
| outputs=[transcribed_msg, chatbot, audio_output] | |
| ) | |
| gr.Markdown(warn) | |
| if __name__ == "__main__": | |
| demo.launch() |