idea‑distiller
idea‑distiller is a tiny utility package that extracts a concise, neutral summary of the core problem addressed by unconventional or controversial business and social initiatives.
It leverages a language model (LLM) to focus on the “problem statement” of the input text while stripping away technical details, implementation specifics, and sensitive content.
Installation
pip install idea_distiller
Quick start
from idea_distiller import idea_distiller
# Raw description of an initiative
user_input = """
In 2012 a program hired homeless people to become mobile Wi‑Fi hotspots,
providing free internet in public places while giving them a source of
income.
"""
# Get the distilled summary
summary = idea_distiller(user_input)
print(summary)
# → ['Problem: Lack of free public internet access and unemployment among homeless individuals.']
Function signature
def idea_distiller(
user_input: str,
llm: Optional[BaseChatModel] = None,
api_key: Optional[str] = None,
) -> List[str]:
| Parameter | Type | Description |
|---|---|---|
| user_input | str |
The raw text describing the initiative you want to distill. |
| llm | Optional[BaseChatModel] |
A LangChain LLM instance. If omitted, the package creates a ChatLLM7 instance automatically. |
| api_key | Optional[str] |
API key for the default ChatLLM7 service. If not supplied, the environment variable LLM7_API_KEY is used. |
The function returns a list of strings that match the validation pattern defined in the package (normally a single concise sentence).
Using a custom LLM
You can plug any LangChain‑compatible chat model instead of the default ChatLLM7.
OpenAI
from langchain_openai import ChatOpenAI
from idea_distiller import idea_distiller
llm = ChatOpenAI(model="gpt-4o-mini")
response = idea_distiller(user_input, llm=llm)
print(response)
Anthropic
from langchain_anthropic import ChatAnthropic
from idea_distiller import idea_distiller
llm = ChatAnthropic(model="claude-3-haiku-20240307")
response = idea_distiller(user_input, llm=llm)
print(response)
Google Gemini
from langchain_google_genai import ChatGoogleGenerativeAI
from idea_distiller import idea_distiller
llm = ChatGoogleGenerativeAI(model="gemini-1.5-flash")
response = idea_distiller(user_input, llm=llm)
print(response)
API key & rate limits (default LLM7)
- The free tier of LLM7 provides enough quota for most development and low‑volume use cases.
- To obtain a free API key, register at: https://token.llm7.io/.
- You can supply the key directly:
response = idea_distiller(user_input, api_key="YOUR_LLM7_API_KEY")
- Or set the environment variable beforehand:
export LLM7_API_KEY="YOUR_LLM7_API_KEY"
If higher rate limits are required, upgrade your LLM7 plan on the provider’s website.
Contributing & Support
- Issues & feature requests: https://github.com/chigwell/idea_distiller/issues
- Pull requests: Welcome! Please follow the contributor guidelines in the repository.
Author
Eugene Evstafev
📧 Email: hi@euegne.plus
🐙 GitHub: chigwell
License
This project is licensed under the MIT License. See the LICENSE file for details.
Metadata
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