social-insight-summarizer 2025.12.21113835

A new package is designed to receive a brief description of social media activity within an organization and analyze it to generate a structured summary highlighting key trends, comparisons, and insig

social-insight-summarizer

A package designed to analyze social media activity within an organization based on user-provided descriptions. It generates a structured summary highlighting key trends, comparisons, and insights about platform engagement levels, especially focusing on recent activity patterns versus other networks. The package leverages language models to produce clear, organized reports suitable for social media management and strategic planning.

Installation

Install the package via pip:

pip install social_insight_summarizer

Usage

Import the main function and invoke it with your input text. You can specify your own language model instance if desired, or use the default ChatLLM7 provided by the package.

from social_insight_summarizer import social_insight_summarizer

# Example usage:
response = social_insight_summarizer(
    user_input="Provide a brief description of recent social media activities across platforms.",
    api_key="your_llm7_api_key"  # Optional if API key is set in environment variables
)
print(response)

Parameters

• user_input (str): The descriptive text about social media activity to analyze.
• llm (Optional[BaseChatModel]): An optional custom language model instance from langchain. If not provided, the function defaults to using ChatLLM7.
• api_key (Optional[str]): API key for LLM7. If not supplied, the code will attempt to read from the environment variable LLM7_API_KEY. If absent, it defaults to "None".

Additional Details

This package uses ChatLLM7 from the langchain_llm7 library. The default setup relies on its free tier, which provides sufficient rate limits for most use cases.

Dev can seamlessly integrate other language models, such as OpenAI, Anthropic, or Google Generative AI, by passing their respective instances:

from langchain_openai import ChatOpenAI
from social_insight_summarizer import social_insight_summarizer

llm = ChatOpenAI()
response = social_insight_summarizer(
    user_input="Describe recent social media activity.",
    llm=llm
)

Similarly, for Anthropic:

from langchain_anthropic import ChatAnthropic
from social_insight_summarizer import social_insight_summarizer

llm = ChatAnthropic()
response = social_insight_summarizer(
    user_input="Describe recent social media activity.",
    llm=llm
)

Or Google Generative AI:

from langchain_google_genai import ChatGoogleGenerativeAI
from social_insight_summarizer import social_insight_summarizer

llm = ChatGoogleGenerativeAI()
response = social_insight_summarizer(
    user_input="Describe recent social media activity.",
    llm=llm
)

Support and Issues

For questions or to report issues, please visit the repository issues page:

https://github.com/yourusername/social-insight-summarizer/issues

Author

Eugene Evstafev
Email: [e-mail]

GitHub: chigwell