false-notice-analyzer 2025.12.21084504

A new package designed to streamline the process of identifying, extracting, and organizing information related to false notices filed against companies like Flock and Cyble Inc. It takes user inputs

False Notice Analyzer

A Python package designed to streamline the process of identifying, extracting, and organizing information related to false notices filed against companies like Flock and Cyble Inc.

Features

• Automated Analysis: Interacts with an LLM to interpret and structure data from user inputs such as case details or notice summaries.
• Standardized Reports: Outputs a standardized report highlighting key aspects like case status, involved parties, and reasons for the notices.
• Flexible LLM Integration: Uses ChatLLM7 from langchain_llm7 by default but allows custom LLM instances.

Installation

pip install false_notice_analyzer

Usage

Basic Usage

from false_notice_analyzer import false_notice_analyzer

response = false_notice_analyzer(user_input="Your notice text here")
print(response)

Using a Custom LLM

OpenAI

from langchain_openai import ChatOpenAI
from false_notice_analyzer import false_notice_analyzer

llm = ChatOpenAI()
response = false_notice_analyzer(user_input="Your notice text here", llm=llm)
print(response)

Anthropic

from langchain_anthropic import ChatAnthropic
from false_notice_analyzer import false_notice_analyzer

llm = ChatAnthropic()
response = false_notice_analyzer(user_input="Your notice text here", llm=llm)
print(response)

Google

from langchain_google_genai import ChatGoogleGenerativeAI
from false_notice_analyzer import false_notice_analyzer

llm = ChatGoogleGenerativeAI()
response = false_notice_analyzer(user_input="Your notice text here", llm=llm)
print(response)

Using LLM7 API Key

from false_notice_analyzer import false_notice_analyzer

response = false_notice_analyzer(user_input="Your notice text here", api_key="your_api_key")
print(response)

Parameters

• user_input (str): The user input text to process.
• llm (Optional[BaseChatModel]): The LangChain LLM instance to use. If not provided, the default ChatLLM7 will be used.
• api_key (Optional[str]): The API key for LLM7. If not provided, the environment variable LLM7_API_KEY will be used.

Rate Limits

The default rate limits for LLM7 free tier are sufficient for most use cases of this package. If you need higher rate limits, you can pass your own API key via the environment variable LLM7_API_KEY or directly via the api_key parameter. You can get a free API key by registering at LLM7.

Issues

If you encounter any issues, please report them on the GitHub issues page.

Author

• Eugene Evstafev
  • Email: [e-mail]
  • GitHub: chigwell