Add the following docstrings to backend/services/genai.py:
class GeminiProcessor:
"""
A processor class for handling operations with the Gemini model.
Attributes:
model (VertexAI): The VertexAI model instance.
"""
def __init__(self, model_name, project) -> None:
"""
Initialize the GeminiProcessor with a model name and project.
Args:
model_name (str): The name of the model to use.
project (str): The project identifier.
"""
def generate_document_summary(self, documents: list, **args):
"""
Generate a summary for a list of documents.
Args:
documents (list): A list of documents to summarize.
**args: Additional arguments for the summarization chain.
Returns:
str: The generated summary.
"""
def count_total_tokens(self, docs: list):
"""
Count the total number of billable characters in a list of documents.
Args:
docs (list): A list of documents.
Returns:
int: The total number of billable characters.
"""
def get_model(self):
"""
Get the VertexAI model instance.
Returns:
VertexAI: The model instance.
"""
class YoutubeProcessor:
"""
A processor class for handling YouTube video transcripts.
Attributes:
text_splitter (RecursiveCharacterTextSplitter): The text splitter instance.
GeminiProcessor (GeminiProcessor): The GeminiProcessor instance.
"""
def __init__(self, genai_processor: GeminiProcessor) -> None:
"""
Initialize the YoutubeProcessor with a GeminiProcessor instance.
Args:
genai_processor (GeminiProcessor): The GeminiProcessor instance.
"""
def retrieve_youtube_documents(self, video_url: str, verbose=False):
"""
Retrieve and split the transcript of a YouTube video.
Args:
video_url (str): The URL of the YouTube video.
verbose (bool): Whether to log detailed information.
Returns:
list: A list of split documents.
"""
def format_processed_concepts(self, processed_concepts):
"""
Format processed concepts into a list of dictionaries.
Args:
processed_concepts (list): A list of processed concepts.
Returns:
list: A formatted list of dictionaries with terms and definitions.
"""
def find_key_concepts(self, documents: list, sample_size: int=0, verbose=False):
"""
Find key concepts in a list of documents.
Args:
documents (list): A list of documents.
sample_size (int): The sample size for processing.
verbose (bool): Whether to log detailed information.
Returns:
list: A list of key concepts and their definitions.
"""
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Add the following docstrings to
backend/services/genai.py
:References
/backend/services/genai.py
#### About Greptile
This response provides a starting point for your research, not a precise solution. Help us improve! Please leave a ๐ if this is helpful and ๐ if it is irrelevant. [Ask Greptile](https://app.greptile.com/chat/github/danieldacosta/ai-flashcards-generator/main) ยท [Edit Issue Bot Settings](https://app.greptile.com/apps/github)