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scamp-analyzer

PyPI version License: MIT Downloads LinkedIn

scamp-analyzer is a lightweight Python package that evaluates user‑provided text descriptions of mischievous or cleverly unconventional behavior (a “scamp” scenario). It returns a structured XML‑like assessment of the act’s creativity, humor, and potential social impact, categorizing it as harmless fun, borderline, or potentially problematic.


Installation

pip install scamp_analyzer

Quick Start

from scamp_analyzer import scamp_analyzer

# Simple usage with the default LLM (ChatLLM7)
result = scamp_analyzer(
    user_input="I swapped the sugar with salt in the office kitchen."
)

print(result)   # → List of extracted XML‑like tags

Parameters

Name Type Description
user_input str The text description of the scamp scenario to be analysed.
llm Optional[BaseChatModel] A LangChain chat model. If omitted, the built‑in ChatLLM7 is used.
api_key Optional[str] API key for LLM7. If omitted, the function reads LLM7_API_KEY from the environment (or uses a placeholder).

Using a Custom LLM

You can provide any LangChain chat model that implements BaseChatModel. Below are a few examples.

OpenAI

from langchain_openai import ChatOpenAI
from scamp_analyzer import scamp_analyzer

llm = ChatOpenAI()
response = scamp_analyzer(
    user_input="I printed the boss's email signature on a birthday cake.",
    llm=llm
)

Anthropic

from langchain_anthropic import ChatAnthropic
from scamp_analyzer import scamp_analyzer

llm = ChatAnthropic()
response = scamp_analyzer(
    user_input="I replaced the office chairs with beanbags for a surprise.",
    llm=llm
)

Google Generative AI

from langchain_google_genai import ChatGoogleGenerativeAI
from scamp_analyzer import scamp_analyzer

llm = ChatGoogleGenerativeAI()
response = scamp_analyzer(
    user_input="I swapped the ‘Out of Office’ replies with a funny poem.",
    llm=llm
)

Default LLM (ChatLLM7)

If you don’t supply a custom llm, scamp_analyzer automatically creates a ChatLLM7 instance:

from scamp_analyzer import scamp_analyzer

response = scamp_analyzer(
    user_input="I anonymously left motivational sticky notes around the office."
)

Providing Your Own LLM7 API Key

You can either set the environment variable:

export LLM7_API_KEY="your_llm7_api_key"

or pass it directly:

response = scamp_analyzer(
    user_input="I organized a surprise flash mob at lunch.",
    api_key="your_llm7_api_key"
)

Obtain a free API key by registering at https://token.llm7.io/.


Contributing & Issues

If you encounter any problems or have feature requests, please open an issue:

👉 https://github....

We welcome contributions, documentation improvements, and bug fixes.


Author

Eugene Evstafev
📧 hi@euegne.plus
🐙 GitHub: chigwell


License

This project is licensed under the MIT License – see the LICENSE file for details.

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