collabinsightextractor
Overview
collabinsightextractor is a lightweight Python package that extracts structured insights about remote‑team collaboration from free‑form text such as blog posts, articles, or personal notes.
The extractor uses a large language model (LLM) to analyze the input and returns takeaways organized into categories like:
- Communication strategies
- Trust‑building techniques
- Common challenges
The results are wrapped in a consistent XML‑like format, making them easy to embed in reports, dashboards, or team‑guideline documents.
Installation
pip install collabinsightextractor
Quick Start
from collabinsightextractor import collabinsightextractor
# Example text you want to analyse
text = """
Remote teams often struggle with time‑zone differences and informal communication.
Setting up regular video stand‑ups and using async tools like Slack can bridge the gap.
Trust grows when you give teammates ownership of their tasks and celebrate small wins.
"""
# Use the default LLM (ChatLLM7) with environment variable LLM7_API_KEY or the free tier key
insights = collabinsightextractor(user_input=text)
print(insights)
Parameters
| Parameter | Type | Description |
|---|---|---|
user_input |
str |
The raw text (blog post, article, notes, …) to be processed. |
llm |
Optional[BaseChatModel] |
A LangChain‑compatible chat model. If omitted, the package creates a default ChatLLM7 instance. |
api_key |
Optional[str] |
API key for the LLM7 service. If omitted, the value is read from the environment variable LLM7_API_KEY. The free tier key can be obtained at https://token.llm7.io/. |
Using a Custom LLM
You can supply any LangChain chat model that follows the BaseChatModel interface.
OpenAI
from langchain_openai import ChatOpenAI
from collabinsightextractor import collabinsightextractor
llm = ChatOpenAI()
insights = collabinsightextractor(user_input=text, llm=llm)
Anthropic
from langchain_anthropic import ChatAnthropic
from collabinsightextractor import collabinsightextractor
llm = ChatAnthropic()
insights = collabinsightextractor(user_input=text, llm=llm)
Google Gemini
from langchain_google_genai import ChatGoogleGenerativeAI
from collabinsightextractor import collabinsightextractor
llm = ChatGoogleGenerativeAI()
insights = collabinsightextractor(user_input=text, llm=llm)
Rate Limits & API Keys
- The free tier of LLM7 provides sufficient quota for typical usage of this extractor.
- For higher throughput, set your own API key via the
LLM7_API_KEYenvironment variable or pass it directly:
insights = collabinsightextractor(user_input=text, api_key="your_llm7_api_key")
You can obtain a free API key by registering at https://token.llm7.io/.
Contributing & Support
- Issues & feature requests: https://github.com/chigwell/collabinsightextractor/issues
- Pull requests are welcome! Please follow the existing code style and include tests for new functionality.
License
This project is licensed under the MIT License.
Author
Eugene Evstafev – hi@euegne.plus – https://github.com/chigwell
Happy extracting!
Metadata
Release files for collabinsightextractor 2025.12.20201906
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| collabinsightextractor-2025.12.20201906-py3-none-any.whl | Python 3 | none | any | Details for collabinsightextractor-2025.12.20201906-py3-none-any.whl |
Total release size: 10.7 kB
Release files / collabinsightextractor-2025.12.20201906.tar.gz
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