diff --git a/.env b/.env new file mode 100644 index 0000000..7d75516 --- /dev/null +++ b/.env @@ -0,0 +1 @@ +API_KEY=io-v2-eyJhbGciOiJSUzI1NiIsInR5cCI6IkpXVCJ9.eyJvd25lciI6ImU4OGE2MDE0LTVhMWQtNGY2OS05M2EyLTRkOGQ5NTMxYTE5NSIsImV4cCI6NDkxMDcwMTgxNH0.E-Ywo2jzcG3c8I7eRuufI5FuHFSOJN7AK2I65xqnsQ8qH_UuS8L6Fst6LSui6AVaZbAs_gpbNFUhe4GRhmgDbQ diff --git a/app.py b/app.py new file mode 100644 index 0000000..4b15ab8 --- /dev/null +++ b/app.py @@ -0,0 +1,166 @@ +import gradio as gr +from faster_whisper import WhisperModel +from pathlib import Path +from dotenv import load_dotenv +import os + +from services.llm import Llm + +load_dotenv() + +# Стандартный API ключ +DEFAULT_API_KEY=os.getenv('API_KEY') +# Задаем выходную директорию +OUTPUT_PATH='outputs' +# Стандартный системный промпт +DEFAULT_SYSTEM_PROMPT='''You are a diligent university student who has recorded a lecture as an audio file and later transcribed it into raw text. +Your task is to rewrite this unstructured transcript into a clear, logically organized, and detailed lecture summary (lecture notes). + +Guidelines: +1. Structure: + - Organize the text into a hierarchy of sections and subsections. + - Use headings, bullet points, or numbering where appropriate. + - Present the material in a logical flow (from introduction → main points → details → examples → conclusion). + +2. Clarity & Cohesion: + - Remove filler words, repetitions, and irrelevant fragments. + - Rewrite incomplete sentences into full, grammatically correct sentences. + - Ensure smooth transitions between topics, making the summary feel continuous and well-connected. + +3. Depth & Detail: + - Capture all important concepts, definitions, examples, and explanations from the lecture. + - Expand shorthand or fragmented thoughts into full, precise explanations. + - Where appropriate, rephrase or clarify confusing passages for better understanding. + +4. Accuracy: + - Preserve the lecturer’s original meaning, intent, and terminology. + - Avoid adding personal opinions or new information that was not in the lecture. + +5. Style: + - Write in a formal, academic tone suitable for study notes. + - Aim for readability: concise sentences, but thorough coverage of concepts. + - Use emphasis (e.g., bold or italic text) only when it improves comprehension. + +Final Output: A cohesive, detailed, and well-structured lecture summary, suitable for later studying and revision. +Use only russian language! +''' + +faster_whisper_models_list = ['tiny', 'base', 'small', 'medium', 'large-v1', 'large-v2', 'large-v3', 'large', 'distil-large-v2', 'distil-large-v3', 'distil-large-v3.5', 'large-v3-turbo', 'turbo'] +llm_models_list = ['openai/gpt-oss-120b', 'Qwen/Qwen3-235B-A22B-Thinking-2507', 'deepseek-ai/DeepSeek-R1-0528', 'meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8', 'openai/gpt-oss-20b', 'Intel/Qwen3-Coder-480B-A35B-Instruct-int4-mixed-ar', 'meta-llama/Llama-3.2-90B-Vision-Instruct', 'mistralai/Mistral-Nemo-Instruct-2407', 'Qwen/Qwen2.5-VL-32B-Instruct', 'meta-llama/Llama-3.3-70B-Instruct', 'mistralai/Devstral-Small-2505', 'mistralai/Magistral-Small-2506', 'mistralai/Mistral-Large-Instruct-2411', 'CohereForAI/aya-expanse-32b'] + + +# Функция транскрибации +def recognize(model, audioFile, beamSize, vadFilter, minSilenceDurationMs, speechPadMs, temp0, temp1, temp2, wordTimestamps, noSpeechThreshold, conditionOnPreviousText): + model = WhisperModel(model, device='cuda', compute_type='float16') # Задаем модель + + segments, _ = model.transcribe( # Распознаем текст + audioFile, + beam_size=beamSize, + vad_filter=vadFilter, + vad_parameters={ + "min_silence_duration_ms": minSilenceDurationMs, + "speech_pad_ms": speechPadMs + }, + temperature= [temp0, temp1, temp2], + word_timestamps=wordTimestamps, + no_speech_threshold=noSpeechThreshold, + condition_on_previous_text=conditionOnPreviousText + ) + + text = '' + + for seg in segments: + text += f"[{format_timestamp(seg.start)} -> {format_timestamp(seg.end)}] {seg.text}" + '\n' + + return(text) + + +def format_timestamp(seconds: float) -> str: + millis = int(seconds * 1000) + hours = millis // (3600 * 1000) + minutes = (millis % (3600 * 1000)) // (60 * 1000) + seconds_int = (millis % (60 * 1000)) // 1000 + millis = millis % 1000 + return f"{hours:02d}:{minutes:02d}:{seconds_int:02d},{millis:03d}" + +# Функция сохранения файла +def saveFile(filename, text): + directory = Path(OUTPUT_PATH) + filePath = directory / filename + filePath.parent.mkdir(parents=True, exist_ok=True) + filePath.write_text(text, encoding='utf-8') + + +with gr.Blocks() as demo: + gr.HTML(''' +
+

+ Faster Whisper WebUI +

+
+ ''') + + with gr.Row(): + with gr.Column(): + # Колонка в левой части экрана с основным взаимодействием + with gr.Accordion(label='Recognization'): + with gr.Column(): + audioFile = gr.Audio(label='Load audio for transcribe', type="filepath") + recognizeBtn = gr.Button('recognize', variant='primary') + + with gr.Accordion(label='Recognized text'): + recognizedText = gr.TextArea(label='') + + # Колонка в правой части экрана с настройками + with gr.Column(): + with gr.Accordion(label='Settings'): + # Первое поле на всю ширину в акордионе настроек + filename = gr.Textbox(label='Output filename', value='output.txt') + + # Акордион настроек faster whisper + with gr.Accordion(label='Faster whisper settings'): + with gr.Row(): + # Левая колонка в акордионе + with gr.Column(): + fastWhisperModel = gr.Dropdown(label='Model', choices=faster_whisper_models_list, interactive=True) + + beamSize = gr.Number(label='beam_size', value=8, interactive=True) + noSpeechThreshold = gr.Number(label='no_speech_threshold', value=0.5, interactive=True) + vadFilter = gr.Checkbox(label='vad_filter', value=True, interactive=True) + wordTimestamps = gr.Checkbox(label='word_timestamps', value=True, interactive=True) + conditionOnPreviousText = gr.Checkbox(label='condition_on_previous_text', value=False, interactive=True) + + # Правая колонка в акордионе + with gr.Column(): + with gr.Accordion(label='Vad parameters'): + minSilenceDurationMs = gr.Number(label='min_silence_duration_ms', value=300, interactive=True) + speechPadMs = gr.Number(label='speech_pad_ms', value=200, interactive=True) + + with gr.Accordion(label='Temperature'): + temp0 = gr.Number(label='temp_0', value=0.0, interactive=True) + temp1 = gr.Number(label='temp_1', value=0.2, interactive=True) + temp2 = gr.Number(label='temp_2', value=0.4, interactive=True) + + # Нижний акордион настроек для api ключа llm + with gr.Accordion(label='ai.io.net api settings'): + apiKey = gr.Textbox(label='API key', value=DEFAULT_API_KEY, interactive=True) + + with gr.Accordion(label='System prompt'): + systemPrompt = gr.Textbox(label='', value=DEFAULT_SYSTEM_PROMPT, interactive=True) + + with gr.Row(): + llmModel = gr.Dropdown(label='models', choices=llm_models_list, value=llm_models_list[0], interactive=True) + llmTemperature = gr.Number(label='Temperature', value=0.8, interactive=True ) + with gr.Column(): + with gr.Accordion(label='LLM'): + with gr.Accordion(label='Refined text raw'): + refinedText = gr.Textbox(label='') + + with gr.Accordion(label='Refined text md formated'): + refinedTextMD = gr.Markdown(label='') + + + recognizeBtn.click(recognize, outputs=[recognizedText], inputs=[fastWhisperModel, audioFile, beamSize, vadFilter, minSilenceDurationMs, speechPadMs, temp0, temp1, temp2, wordTimestamps, noSpeechThreshold, conditionOnPreviousText]) + recognizedText.change(Llm(apiKey.value).generate, inputs=[llmModel, systemPrompt, recognizedText, llmTemperature], outputs=[refinedText, refinedTextMD]) + +demo.launch() diff --git a/outputs/output.txt b/outputs/output.txt new file mode 100644 index 0000000..be45db8 --- /dev/null +++ b/outputs/output.txt @@ -0,0 +1,14 @@ +[00:00:00,000 -> 00:00:03,680] Современные технологии стремительно принякают во всех свера нашей жизни. +[00:00:04,240 -> 00:00:08,340] Мы пользуемся смартфонами, интернетом, искусственным интеллектом и умными помощниками. +[00:00:09,000 -> 00:00:10,320] Мир меняется буквально на глазах. +[00:00:10,740 -> 00:00:13,460] Работа собирает автомобиля алгоритм и пишут статьи, +[00:00:13,640 -> 00:00:17,180] а голосую систему могут озвучивать текст с почти человеческой интернации. +[00:00:17,600 -> 00:00:21,860] Однако, несмотря на все достижение, важно помнить, технологии – это все в большин инструмент. +[00:00:22,500 -> 00:00:24,660] То, как мы их применяем зависит от нас. +[00:00:25,120 -> 00:00:29,080] Мы должны использовать прогресс-разумно, сохраняя человеческие ценности, +[00:00:29,080 -> 00:00:31,880] забудьтеся будущим и друг от друга. +[00:00:32,400 -> 00:00:34,660] Развитите технологий нет меняет важность доброты, +[00:00:34,940 -> 00:00:35,980] внимание и этики. +[00:00:36,220 -> 00:00:38,340] Пусть технологический прогресс делая жизнью +[00:00:38,340 -> 00:00:40,960] допни, но настоящую ценность предоёт и человек. +[00:00:41,200 -> 00:00:43,660] Все мыслими, чувствами и стремлянем к лучшему. diff --git a/services/__pycache__/llm.cpython-310.pyc b/services/__pycache__/llm.cpython-310.pyc new file mode 100644 index 0000000..1651e1c Binary files /dev/null and b/services/__pycache__/llm.cpython-310.pyc differ diff --git a/services/llm.py b/services/llm.py new file mode 100644 index 0000000..1ebc57b --- /dev/null +++ b/services/llm.py @@ -0,0 +1,31 @@ +import openai + +class Llm: + def __init__(self, apiKey:str): + self.client = openai.OpenAI( + api_key=apiKey, + base_url='https://api.intelligence.io.solutions/api/v1/' + ) + + def generate(self, model:str, systemPrompt:str, userPrompt:str, temp:float): + ''' + prompt[user_promtp, system_ptompt] + Function generate text by prompt + ''' + + # Получаем ответ от нейросети + response = self.client.chat.completions.create( + model=model, + messages=[ + {'role': 'system', 'content': systemPrompt}, + {'role': 'user', 'content': userPrompt}, + ], + temperature=temp, + stream=False + ) + + # Достаем текст + text = str(response.choices[0].message.content) + + return text, text +