diff --git a/Local-Windows/main_beta.py b/Local-Windows/main_beta.py new file mode 100644 index 0000000..e6e22c4 --- /dev/null +++ b/Local-Windows/main_beta.py @@ -0,0 +1,230 @@ +import requests +import json +import os +import subprocess +import time +import whisper +import spacy +import re +from faster_whisper import WhisperModel +from langdetect import detect + + +# 初始化 Faster Whisper 模型 +model = WhisperModel("large-v2", device="cuda", compute_type="int8") + +#從api_key.txt取得api +def get_api_key_from_file(file_path='api_key.txt'): + try: + with open(file_path, 'r') as file: + return file.read().strip() + except FileNotFoundError: + print("未找到 API 密鑰文件。") + return None + +#從deepl_api_key.txt取得api +def get_deepl_api_key_from_file(file_path='deepl_api_key.txt'): + try: + with open(file_path, 'r') as file: + return file.read().strip() + except FileNotFoundError: + print("未找到 DeepL API 密鑰文件。") + return None + +# 呼叫DeepL API的函數(備案，當Gemini不能翻譯色色內容時) +def call_deepl_api(input_text, deepL_auth_key, target_lang='ZH'): + deepL_url = 'https://api-free.deepl.com/v2/translate' + headers = { + 'Authorization': f'DeepL-Auth-Key {deepL_auth_key}' + } + data = { + 'text': input_text, + 'target_lang': target_lang + } + response = requests.post(deepL_url, headers=headers, data=data) + if response.status_code == 200: + response_data = response.json() + if 'translations' in response_data and response_data['translations']: + return response_data['translations'][0]['text'] + else: + print("DeepL 翻譯失敗：無翻譯結果。") + return None + else: + print(f"DeepL API 調用發生錯誤: {response.status_code}") + return None + +# 呼叫Gemini的函數 +def call_gemini_api(input_text): + # 获取 DeepL API KEY + deepl_auth_key = get_deepl_api_key_from_file() + if not deepl_auth_key: + print("无法获取 DeepL API KEY。") + return None + + # 先使用 DeepL API 翻译为简体中文 + simplified_chinese_text = call_deepl_api(input_text, deepl_auth_key, target_lang='ZH') + if not simplified_chinese_text: + print("DeepL 翻译失败。") + return None + + # 从文件中取得 Gemini API KEY + api_key = get_api_key_from_file() + if not api_key: + print("Gemini API KEY 无效") + return None + + # Gemini API URL 请求头 + url = "https://palm-proxy.arcelibs.com/v1beta/models/gemini-pro:generateContent?key={}".format(api_key) + headers = {'Content-Type': 'application/json'} + + # 格式化输入文本，准备发送给 Gemini API + formatted_input = f"請你將下列語句翻譯成繁體中文，忽略任何語句與文法問題:\n{simplified_chinese_text}" + data = json.dumps({"contents": [{"parts": [{"text": formatted_input}]}]}) + + # 发送请求到 Gemini API + response = requests.post(url, headers=headers, data=data) + response_data = response.json() + + # 检查响应并处理 + if response.status_code == 200 and 'candidates' in response_data: + return response_data['candidates'][0]['content']['parts'][0]['text'] + else: + print(f"错误: {response.status_code}") + return None + + +# 使用 yt-dlp 獲取 YouTube 直播媒體位置 +def get_stream_url(youtube_url): + command = ["yt-dlp", "-g", youtube_url] + process = subprocess.run(command, stdout=subprocess.PIPE, stderr=subprocess.PIPE, text=True) + if process.returncode != 0: + print(f"錯誤: 無法取得直播流。詳情：{process.stderr}") + return None + return process.stdout.strip() + +# 錄製聲音的函數 +def record_audio(stream_url, duration, output_filename): + try: + command = [ + "ffmpeg", "-i", stream_url, "-t", str(duration), + "-ac", "1", "-ar", "16000", "-y", output_filename + ] + subprocess.run(command, stdout=subprocess.PIPE, stderr=subprocess.PIPE, check=True) + except subprocess.CalledProcessError as e: + print(f"錯誤: 無法錄製聲音。詳情：{e.stderr.decode()}") + return False + return True + +# 轉寫聲音函數 +def transcribe_audio(file_path, language="japanese"): + try: + # 使用 Faster Whisper 进行转录 + segments, info = model.transcribe(file_path, vad_filter=True) + # 合并段落以形成完整文本 + text = " ".join([seg.text for seg in segments]) + + # 保存转录文本到文件 + save_transcription(file_path, text) + + return text + except Exception as e: + print(f"錯誤: 無法轉錄聲音。詳情：{e}") + return None + +# 新增的保存轉錄文的函數 +def save_transcription(file_path, text, is_api_response=False): + raw_data_dir = 'RawData' if not is_api_response else 'APIResponses' + if not os.path.exists(raw_data_dir): + os.makedirs(raw_data_dir) + + base_filename = os.path.splitext(os.path.basename(file_path))[0] + suffix = '.txt' if not is_api_response else '_response.json' + filename = os.path.join(raw_data_dir, f'{base_filename}{suffix}') + + with open(filename, 'w', encoding='utf-8') as file: + file.write(text) + +# 新增語言檢測機制並加載模型 +def detect_and_split_text(text, max_length): + language = detect(text) + nlp = None + if language == "en": + nlp = spacy.load("en_core_web_sm") + elif language == "ja": + nlp = spacy.load("ja_core_news_sm") + elif language in ["zh-cn", "zh-tw"]: + nlp = spacy.load("zh_core_web_sm") + else: + # 無法辨識?就用標點符號分段 + return split_text_on_punctuation(text, max_length) + + return split_text_natural(nlp, text, max_length) + +# 根據傳入的NLP對象來處理語句 +def split_text_natural(nlp, text, max_length): + doc = nlp(text) + segments = [] + current_segment = "" + for sent in doc.sents: + if len(current_segment + sent.text) <= max_length: + current_segment += sent.text + " " + else: + if current_segment: # 空字串處理 + segments.append(current_segment.strip()) + current_segment = sent.text + " " + if current_segment: + segments.append(current_segment.strip()) + return segments + +# 不是中英日文? 就用標點符號來分類 +def split_text_on_punctuation(text, max_length): + # 定義分類的標點符號 + punctuations = ".!?\n" + pattern = f"[{re.escape(punctuations)}]" + + segments = [] + current_segment = "" + for word in re.split(pattern, text): + if len(current_segment) + len(word) <= max_length: + current_segment += word + else: + if current_segment: + segments.append(current_segment.strip()) + current_segment = word + if current_segment: + segments.append(current_segment.strip()) + + return segments + +# 主流程 +def main(segment_duration, total_duration): + youtube_url = input("請輸入 YouTube URL: ") # 讓用戶輸入 YouTube URL + stream_url = get_stream_url(youtube_url) + if not stream_url: + print("無法取得 YouTube 直播流地址。") + return + + for segment in range(0, total_duration, segment_duration): + filename = f"output{segment}.wav" + if record_audio(stream_url, segment_duration, filename): + text = transcribe_audio(filename) + if text: + translated_text = call_gemini_api(text) + if translated_text: + #print(f"Segment {segment}: {translated_text}") + print(f"{translated_text}") + else: + print(f"無法翻譯 {segment}。") + else: + print(f"無法轉錄片段 {segment}。") + os.remove(filename) # 清理：聲音檔案 + else: + print(f"錄製段落 {segment} 失敗。") + time.sleep(segment_duration) + +# 配置參數 +SEGMENT_DURATION = 15 # 每一段錄製的長度，單位是秒 +TOTAL_DURATION = 6000 # 總錄製時間，單位是秒 + +if __name__ == "__main__": + main(SEGMENT_DURATION, TOTAL_DURATION)