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| # openai_tts_tool.py | |
| from openai import OpenAI | |
| import os | |
| from langdetect import detect, DetectorFactory | |
| import logging | |
| # Set up logging configuration | |
| logging.basicConfig(level=logging.INFO, format='%(asctime)s | %(levelname)s | %(message)s') | |
| # Ensure consistent results from langdetect | |
| DetectorFactory.seed = 0 | |
| # Simple in-memory cache for translations | |
| translation_cache = {} | |
| def translate_text(api_key, text, target_language): | |
| """ | |
| Translate text to the target language using OpenAI's API with gpt-4o-mini model. | |
| Args: | |
| api_key (str): OpenAI API key | |
| text (str): Text to translate | |
| target_language (str): Target language code (e.g., 'en' for English) | |
| Returns: | |
| str: Translated text or error message | |
| """ | |
| cache_key = (text, target_language) | |
| if cache_key in translation_cache: | |
| logging.info("Fetching translation from cache.") | |
| return translation_cache[cache_key] | |
| try: | |
| logging.info("Starting translation process.") | |
| client = OpenAI(api_key=api_key) | |
| prompt = f"Translate the following text to {target_language}:\n\n{text}" | |
| response = client.completions.create( | |
| model="gpt-4o-mini", # Updated model name | |
| prompt=prompt, | |
| max_tokens=1000, | |
| temperature=0.3 | |
| ) | |
| translated_text = response.choices[0].text.strip() | |
| logging.info("Translation successful.") | |
| # Cache the translation | |
| translation_cache[cache_key] = translated_text | |
| return translated_text | |
| except Exception as e: | |
| logging.error(f"Error in translation: {str(e)}") | |
| return f"Error in translation: {str(e)}" | |
| def generate_audio_and_text(api_key, input_text, model_name, voice_type, voice_speed, language, output_option): | |
| """ | |
| Generate audio and text files from input text using OpenAI's TTS API. | |
| Args: | |
| api_key (str): OpenAI API key | |
| input_text (str): Text to convert to speech | |
| model_name (str): OpenAI model name | |
| voice_type (str): Voice type for TTS | |
| voice_speed (float): Speed of speech | |
| language (str): Language code for synthesis | |
| output_option (str): Output type ('audio', 'script_text', or 'both') | |
| Returns: | |
| tuple: (audio_file_path, script_file_path, status_message) | |
| """ | |
| if not input_text: | |
| logging.warning("No input text provided.") | |
| return None, None, "No input text provided" | |
| if not api_key: | |
| logging.warning("No API key provided.") | |
| return None, None, "No API key provided" | |
| try: | |
| logging.info("Initializing OpenAI client.") | |
| client = OpenAI(api_key=api_key) | |
| # Create temp directory if it doesn't exist | |
| temp_dir = os.path.join(os.getcwd(), 'temp') | |
| if not os.path.exists(temp_dir): | |
| os.makedirs(temp_dir) | |
| logging.info(f"Created temporary directory at {temp_dir}.") | |
| # Detect input language | |
| try: | |
| detected_language = detect(input_text) | |
| logging.info(f"Detected input language: {detected_language}") | |
| except Exception as e: | |
| logging.error(f"Error detecting language: {str(e)}") | |
| return None, None, f"Error detecting language: {str(e)}" | |
| # Map language codes if necessary (langdetect uses ISO 639-1 codes) | |
| target_language = language.lower()[:2] # e.g., 'en' for English | |
| # If detected language is different from target, translate | |
| if detected_language != target_language: | |
| logging.info("Input language differs from target language. Proceeding to translate.") | |
| translated_text = translate_text(api_key, input_text, target_language) | |
| if translated_text.startswith("Error in translation:"): | |
| return None, None, translated_text | |
| else: | |
| logging.info("Input language matches target language. No translation needed.") | |
| translated_text = input_text | |
| # Generate audio file | |
| audio_file = None | |
| if output_option in ["audio", "both"]: | |
| try: | |
| logging.info("Starting audio generation.") | |
| speech_response = client.audio.speech.create( | |
| model="tts-1", | |
| voice=voice_type, | |
| input=translated_text, | |
| speed=float(voice_speed) | |
| ) | |
| # Save the audio to a temporary file | |
| audio_filename = f"output_{hash(translated_text)}_{target_language}.mp3" | |
| audio_path = os.path.join(temp_dir, audio_filename) | |
| with open(audio_path, "wb") as f: | |
| for chunk in speech_response.iter_bytes(): | |
| f.write(chunk) | |
| logging.info(f"Audio file saved at {audio_path}.") | |
| audio_file = audio_path | |
| except Exception as e: | |
| logging.error(f"Error during audio generation: {str(e)}") | |
| return None, None, f"Error during audio generation: {str(e)}" | |
| # Save the (translated) text as a script file | |
| script_file = None | |
| if output_option in ["script_text", "both"]: | |
| try: | |
| logging.info("Starting script text generation.") | |
| script_text = translated_text | |
| script_filename = f"script_{hash(script_text)}_{target_language}.txt" | |
| script_path = os.path.join(temp_dir, script_filename) | |
| with open(script_path, "w", encoding='utf-8') as f: | |
| f.write(script_text) | |
| logging.info(f"Script file saved at {script_path}.") | |
| script_file = script_path | |
| except Exception as e: | |
| logging.error(f"Error during script text generation: {str(e)}") | |
| return None, None, f"Error during script text generation: {str(e)}" | |
| status_message = f"Generation completed successfully in {language}!" | |
| logging.info(status_message) | |
| return audio_file, script_file, status_message | |
| except Exception as e: | |
| logging.error(f"Unexpected error: {str(e)}") | |
| return None, None, f"Error: {str(e)}" | |