transcript-insightful 2025.12.21185930

transcript-insightful extracts and structures key insights from video transcripts, delivering concise themes and implications.

Transcript Insightful

This package extracts and structures key insights from video summaries or transcripts. It takes a text input describing a video's content, such as a summary or transcript, and uses LLM7 to parse and return a structured response.

Overview

The package provides a simple way to extract the essence of a video without watching it in full. It's ideal for educational content, technical talks, or industry discussions. The structured output includes main themes, critical points, and potential implications discussed in the video.

Installation

pip install transcript_insightful

Usage

from transcript_insightful import transcript_insightful

response = transcript_insightful(
    user_input="Video summary or transcript text",
    api_key="Your LLM7 API key",
    llm="Your custom LLM instance (e.g. ChatOpenAI, ChatAnthropic, etc.)"
)
print(response)  # Output: {"themes": [...], "critical_points": [...], "implications": [...]}

Parameters

• user_input: The text input describing the video's content.
• llm: An optional BaseChatModel instance to use. Defaults to ChatLLM7 from langchain_llm7.
• api_key: An optional API key for LLM7. Defaults to None.

Using custom LLM instances

You can safely pass your own llm instance if you want to use another LLM, for example:

from langchain_openai import ChatOpenAI
from transcript_insightful import transcript_insightful

llm = ChatOpenAI()
response = transcript_insightful(llm=llm)

or for example to use the anthropic:

from langchain_anthropic import ChatAnthropic
from transcript_insightful import transcript_insightful

llm = ChatAnthropic()
response = transcript_insightful(llm=llm)

or google:

from langchain_google_genai import ChatGoogleGenerativeAI
from transcript_insightful import transcript_insightful

llm = ChatGoogleGenerativeAI()
response = transcript_insightful(llm=llm)

Rate limits

The default rate limits for LLM7 free tier are sufficient for most use cases of this package. If you need higher rate limits for LLM7, you can pass your own API key via environment variable LLM7_API_KEY or via passing it directly like transcript_insightful(api_key="your_api_key").

Getting a free API key

You can get a free API key by registering at https://token.llm7.io/

Issues

For any issues or feature requests, please visit https://github.com/chigwell/transcript-insightful

Author

Eugene Evstafev (github: @chigwell) [e-mail]