A Python package designed to analyze and summarize video content by processing pre-extracted textual information such as transcripts, subtitles, and descriptions. It leverages structured pattern matching to extract key topics, themes, and insights from lengthy videos, providing concise summaries without processing multimedia directly.
This package helps users quickly grasp the essence of video content by summarizing textual data (transcripts, subtitles, etc.) using advanced language models. It is ideal for environments where only text data is available, enabling efficient content discovery and knowledge extraction.
Install the package via pip:
pip install video_text_summarizerfrom video_text_summarizer import video_text_summarizer
# Summarize text using the default LLM7 model
response = video_text_summarizer(
user_input="Your video transcript or text here..."
)
print(response)You can replace the default ChatLLM7 with any other LangChain-compatible LLM (e.g., OpenAI, Anthropic, Google Generative AI):
from langchain_openai import ChatOpenAI
from video_text_summarizer import video_text_summarizer
llm = ChatOpenAI()
response = video_text_summarizer(
user_input="Your video transcript or text here...",
llm=llm
)
print(response)from langchain_anthropic import ChatAnthropic
from video_text_summarizer import video_text_summarizer
llm = ChatAnthropic()
response = video_text_summarizer(
user_input="Your video transcript or text here...",
llm=llm
)
print(response)from langchain_google_genai import ChatGoogleGenerativeAI
from video_text_summarizer import video_text_summarizer
llm = ChatGoogleGenerativeAI()
response = video_text_summarizer(
user_input="Your video transcript or text here...",
llm=llm
)
print(response)| Parameter | Type | Description |
|---|---|---|
user_input |
str |
The text (e.g., transcript, subtitles) to summarize. |
api_key |
Optional[str] |
Your LLM7 API key (if not provided, falls back to LLM7_API_KEY environment variable). |
llm |
Optional[BaseChatModel] |
A custom LangChain-compatible LLM (e.g., ChatOpenAI, ChatAnthropic). If omitted, defaults to ChatLLM7. |
- Default LLM: Uses
ChatLLM7fromlangchain_llm7. - Free Tier: Sufficient for most use cases (check LLM7 docs for limits).
- Custom API Key: Pass via
api_keyparameter or setLLM7_API_KEYenvironment variable. - Get API Key: Register at LLM7 Token for free.
MIT License (see LICENSE for details).
For bugs, feature requests, or support, open an issue on GitHub.
Eugene Evstafev 📧 hi@euegne.plus 🔗 GitHub: chigwell