idea-extractor

idea‑extractor is a lightweight Python package that helps you pull high‑impact software ideas from community discussions.
Feed it text from forums like Hacker News, Reddit, or any discussion thread and it will parse, categorize, and summarize potential software ideas based on community trends, feasibility, and market impact.

Install

pip install idea_extractor

Quick Start

# Import the function – note the underscore instead of the hyphen in the module name
from idea_extractor import idea_extractor

# Plain text from a discussion thread
user_text = """
I've noticed that a lot of devs complain about the hassle of setting up CI/CD pipelines for small projects.
Maybe there's a lightweight, plug‑and‑play service that automatically generates GitHub Actions or CircleCI configs from a simple config file.
"""

# Call the function with the default LLM7 engine
ideas = idea_extractor(user_input=user_text)

# ideas is a list of strings, each representing a structured idea
print(ideas)

Customizing the LLM

By default idea_extractor will use the free tier of ChatLLM7 (via langchain_llm7).
If you prefer another LLM, simply pass an instance that follows the BaseChatModel API.

Using OpenAI

from langchain_openai import ChatOpenAI
from idea_extractor import idea_extractor

llm = ChatOpenAI()              # your OpenAI configuration is handled automatically
response = idea_extractor(user_input="...", llm=llm)

Using Anthropic

from langchain_anthropic import ChatAnthropic
from idea_extractor import idea_extractor

llm = ChatAnthropic()
response = idea_extractor(user_input="...", llm=llm)

Using Google Gemini

from langchain_google_genai import ChatGoogleGenerativeAI
from idea_extractor import idea_extractor

llm = ChatGoogleGenerativeAI()
response = idea_extractor(user_input="...", llm=llm)

API Reference

def idea_extractor(
    user_input: str,
    api_key: Optional[str] = None,
    llm: Optional[BaseChatModel] = None
) -> List[str]

The function returns a list of extracted ideas, each formatted as a concise sentence or short paragraph.

Configuration

LLM7 Free Tier

The default ChatLLM7 free tier includes sufficient rate limits for most projects.
If you need higher rates, supply your own key:

export LLM7_API_KEY="your_api_key_here"    # or pass directly via the api_key parameter

Free keys can be obtained by registering at https://token.llm7.io/.

Issues & Support

Found a bug or want to request a feature? Open an issue on GitHub: https://github.....

Author

• Name: Eugene Evstafev
• Email: hi@euegne.plus
• GitHub: chigwell