Add tiered summarization based on pricing plans
- Implement advanced AI summarization with action items for Pro plan - Create basic bullet-point summarization for Freemium plan - Add plan tier validation and feature differentiation - Support speaker identification in transcripts - Define plan limits (600 mins Pro/200 mins Freemium)
This commit is contained in:
Michael Ikehi
+52
-30
@@ -28,7 +28,7 @@ def extract_audio(url: str, output_template=os.path.join(UPLOAD_FOLDER, "%(title
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"""
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Download and extract audio from a video URL using yt-dlp.
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The file will be saved in the 'upload' folder.
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Returns:
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str: The absolute path to the downloaded audio file (with a unique id appended).
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"""
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@@ -42,51 +42,51 @@ def extract_audio(url: str, output_template=os.path.join(UPLOAD_FOLDER, "%(title
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}],
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"quiet": True,
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}
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with yt_dlp.YoutubeDL(ydl_opts) as ydl:
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info = ydl.extract_info(url, download=True)
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# Prepare the filename from the info.
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# Note: prepare_filename returns the filename *before* postprocessing,
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# so we change the extension to mp3.
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original_filepath = os.path.splitext(ydl.prepare_filename(info))[0] + ".mp3"
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# Debug: list files in the upload folder
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if not os.path.exists(original_filepath):
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files = os.listdir(UPLOAD_FOLDER)
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print("Warning: Could not find expected file.")
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print("Files in upload folder:", files)
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raise FileNotFoundError(f"Expected audio file not found: {original_filepath}")
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# Get the video's title and sanitize it
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title = info.get('title', 'audio')
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safe_title = sanitize_filename(title)
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# Generate a unique identifier
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unique_id = uuid.uuid4().hex # Unique identifier in hex format
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# Construct the new filename with the unique id appended.
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new_audio_filename = f"{safe_title}_{unique_id}.mp3"
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new_audio_filepath = os.path.join(UPLOAD_FOLDER, new_audio_filename)
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# Rename the downloaded file to include the unique ID.
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os.rename(original_filepath, new_audio_filepath)
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print(f"Renamed file to: {new_audio_filepath}")
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# Return the absolute path to the renamed audio file.
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return os.path.abspath(new_audio_filepath)
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def transcribe_media(file_loc: str, media_type: str = "audio"):
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"""
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Transcribe media using Deepgram.
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If media_type is "audio" (remote URL), use Deepgram's URL transcription.
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If media_type is "video" (remote URL), extract audio locally (in the upload folder),
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transcribe via file, and then delete the local audio file.
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Args:
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file_loc (str): URL to the remote audio or video file.
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media_type (str): "audio" or "video".
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Returns:
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dict: The transcription response from Deepgram.
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"""
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@@ -100,22 +100,22 @@ def transcribe_media(file_loc: str, media_type: str = "audio"):
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smart_format=True,
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diarize=True,
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)
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if media_type.lower() == "audio":
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# For remote audio files, use the URL transcription method.
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response = deepgram.listen.rest.v("1").transcribe_url({"url": file_loc}, options)
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elif media_type.lower() == "video":
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# For remote video files, first extract the audio locally.
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local_audio_path = extract_audio(file_loc)
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print(f"Extracted audio to: {local_audio_path}")
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# Transcribe using the local file method.
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with open(local_audio_path, "rb") as file:
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buffer_data = file.read()
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payload: FileSource = {"buffer": buffer_data}
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response = deepgram.listen.rest.v("1").transcribe_file(payload, options)
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# Clean up: delete the local audio file.
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if os.path.exists(local_audio_path):
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os.remove(local_audio_path)
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@@ -123,7 +123,7 @@ def transcribe_media(file_loc: str, media_type: str = "audio"):
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else:
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raise ValueError("media_type must be either 'audio' or 'video'.")
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return response
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except Exception as e:
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@@ -137,54 +137,76 @@ def transcribe_media(file_loc: str, media_type: str = "audio"):
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def group_words_into_sentences(words, max_words=15):
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def group_words_into_sentences(words, max_words=15, include_speakers=True):
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"""
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Group words into sentences based on speaker changes.
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Args:
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words: List of word objects from the transcription
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max_words: Maximum number of words per sentence
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include_speakers: Whether to include speaker information in the output
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(True for Pro plan, False for Freemium plan)
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Returns:
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A dictionary containing the sentences
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"""
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sentences = []
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current_sentence = []
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current_speaker = None
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start_time = None
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for i, word_info in enumerate(words):
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word = word_info["punctuated_word"]
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speaker = word_info["speaker"]
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speaker = word_info["speaker"] if include_speakers else "speaker_0" # Use a default speaker if not including speakers
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start = word_info["start"]
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end = word_info["end"]
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# If speaker changes or sentence reaches max length, start a new sentence
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if speaker != current_speaker:
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if current_sentence:
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sentences.append({
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sentence_obj = {
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"sentence": " ".join([w["word"] for w in current_sentence]),
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"speaker": current_speaker,
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"start": start_time,
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"end": words[i-1]["end"],
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"words": current_sentence
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})
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}
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# Only include speaker information if include_speakers is True
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if include_speakers:
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sentence_obj["speaker"] = current_speaker
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sentences.append(sentence_obj)
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current_sentence = []
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current_speaker = speaker
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start_time = start
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# Append word with metadata inside the current sentence
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current_sentence.append({"word": word, "start": start, "end": end})
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# Append the last sentence if any words remain
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if current_sentence:
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sentences.append({
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sentence_obj = {
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"sentence": " ".join([w["word"] for w in current_sentence]),
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"speaker": current_speaker,
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"start": start_time,
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"end": words[-1]["end"],
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"words": current_sentence
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})
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}
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# Only include speaker information if include_speakers is True
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if include_speakers:
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sentence_obj["speaker"] = current_speaker
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sentences.append(sentence_obj)
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return {"sentences": sentences}
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if __name__ == "__main__":
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audio_url = "https://s3.us-east-2.amazonaws.com/com.mkdlabs.images/baas/jordan/019933724441Business%20English%20Conversation%20Lesson%2045_%20Meeting%20a%20New%20Colleague.mp3"
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video_url = "https://s3.us-east-2.amazonaws.com/com.mkdlabs.images/baas/jordan/038426704141Business%20English%20Conversation%20Lesson%2045_%20%20Meeting%20a%20New%20Colleague.mp4"
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# Folder for file uploads/downloads
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response = transcribe_media(video_url, media_type="video")
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print(response)
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