insightminer
insightminer is a lightweight Python package that extracts and structures key insights from opinionated articles, blog posts, tweets, and other short texts. It leverages the llmatch‑messages library together with a language model (LLM) to parse free‑form input into a predefined, regex‑validated structure, making downstream analysis (sentiment, trend tracking, etc.) straightforward and consistent.
✨ Features
- One‑function interface – Call
insightminer()with your text and get a list of extracted fields. - Built‑in LLM – Uses
ChatLLM7from thelangchain_llm7package by default (free tier suitable for most workloads). - Pluggable LLM – Pass any LangChain‑compatible chat model (OpenAI, Anthropic, Google, etc.) if you prefer a different provider.
- Regex‑driven pattern matching – Guarantees that the output conforms to the pattern you define.
- Simple installation – Available on PyPI.
📦 Installation
pip install insightminer
🚀 Quick Start
from insightminer import insightminer
user_input = "I Wouldn't Want John Solomon's New CMO Job at Mozilla"
results = insightminer(user_input)
print(results)
# Example output: ['John Solomon', 'new CMO job', 'Mozilla']
Parameters
| Parameter | Type | Description |
|---|---|---|
| user_input | str |
The text to be processed (e.g., a blog post title, tweet, etc.). |
| llm | Optional[BaseChatModel] |
A LangChain chat model instance. If omitted, the default ChatLLM7 is used. |
| api_key | Optional[str] |
API key for LLM7. If omitted, the function reads the LLM7_API_KEY environment variable or falls back to the default key ("None"). |
🔧 Using a Custom LLM
You can safely replace the default ChatLLM7 with any LangChain‑compatible chat model.
OpenAI
from langchain_openai import ChatOpenAI
from insightminer import insightminer
llm = ChatOpenAI()
response = insightminer("Your text here", llm=llm)
print(response)
Anthropic
from langchain_anthropic import ChatAnthropic
from insightminer import insightminer
llm = ChatAnthropic()
response = insightminer("Your text here", llm=llm)
print(response)
Google Generative AI
from langchain_google_genai import ChatGoogleGenerativeAI
from insightminer import insightminer
llm = ChatGoogleGenerativeAI()
response = insightminer("Your text here", llm=llm)
print(response)
🔑 LLM7 API Key
- Default behaviour: The function looks for an environment variable
LLM7_API_KEY. - Providing manually: Pass
api_key="YOUR_KEY"when callinginsightminer. - Free tier: Sufficient for typical usage of this package.
- Get a key: Register for free at https://token.llm7.io/.
📚 Documentation & References
ChatLLM7package: https://pypi.org/project/langchain-llm7/- LangChain LLM documentation: https://python.langchain.com/docs/
🐞 Issues & Contributions
If you encounter bugs or have feature requests, please open an issue:
Pull requests are welcome! Follow the standard GitHub workflow and ensure tests (if any) pass before submitting.
✉️ Author
Eugene Evstafev – hi@euegne.plus
GitHub: chigwell
📄 License
This project is licensed under the MIT License. See the LICENSE file for details.
Metadata
Release files for insightminer 2025.12.21123144
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | Actions |
|---|---|---|---|---|
| insightminer-2025.12.21123144.tar.gz | 5.8 kB | Without provenance | Details for insightminer-2025.12.21123144.tar.gz |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Actions Reset |
|---|---|---|---|---|
| insightminer-2025.12.21123144-py3-none-any.whl | Python 3 | none | any | Details for insightminer-2025.12.21123144-py3-none-any.whl |
Total release size: 12.3 kB
Release files / insightminer-2025.12.21123144.tar.gz
| Download URL | insightminer-2025.12.21123144.tar.gz |
|---|---|
| Size | 5.8 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
7fb8e1620cfc9deeeeb9e87d36f864234e55098cce1f0bb1e69e36b188083cb1
|
|
BLAKE2b-256 checksum How to use checksums |
c99030917fa18430cd5e14c690f7ca9a22dbb717bcc745a56ad57df030157cda
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/6.2.0 CPython/3.12.1
|
Release files / insightminer-2025.12.21123144-py3-none-any.whl
| Download URL | insightminer-2025.12.21123144-py3-none-any.whl |
|---|---|
| Size | 6.4 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
ae316072d053e0849ebb0fdcfa72d3fc928ae272d8ab9cb6584ca3c76ff03f49
|
|
BLAKE2b-256 checksum How to use checksums |
97543baf5f9f2ec523efb91bd23cfa71a2d0b41465093aab00e56590f22146e6
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/6.2.0 CPython/3.12.1
|
Security for insightminer 2025.12.21123144
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
No provenance found
None of the files in this release were uploaded with provenance metadata.
A note on package security
PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.
To learn more about protecting yourself from malicious actors, visit our package security documentation.