Fin-Trend-Analyzer

Financial Trend Analyzer for AI and Technology Stocks

A Python package that analyzes financial news and sentiment to identify and summarize market trends and risks related to AI and technology stocks.

Overview

Fin-Trend-Analyzer is a linguistic tool that quickly assesses market perceptions and potential bubble indicators by processing text inputs from news articles, reports, or social media posts. It returns structured insights, such as key risk factors, sentiment scores, and trend summaries, using pattern matching to ensure consistent and reliable output.

Installation

pip install fin_trend_analyzer

Usage

from fin_trend_analyzer import fin_trend_analyzer

response = fin_trend_analyzer(user_input="This week's earnings report was outstanding.")

API Documentation

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

  • user_input: The user input text to process.
  • api_key: The API key for LLM7, default is None and will use the environment variable LLM7_API_KEY.
  • llm: The langchain LLM instance to use, default is ChatLLM7 from langchain_llm7.

  Example using a custom LLM instance (e.g., OpenAI, Anthropic, or Google):

  from langchain_openai import ChatOpenAI
  from fin_trend_analyzer import fin_trend_analyzer
  
  llm = ChatOpenAI()
  response = fin_trend_analyzer(user_input="This week's earnings report was outstanding.", llm=llm)

Rate Limits

The default rate limits for LLM7 free tier are sufficient for most use cases of this package. If higher rate limits are needed, pass your own API key via environment variable LLM7_API_KEY or via passing it directly:

from fin_trend_analyzer import fin_trend_analyzer

response = fin_trend_analyzer(user_input="This week's earnings report was outstanding.", api_key="your_api_key")

You can get a free API key by registering at https://token.llm7.io/.

Author

Eugene Evstafev

• Email: hi@euegne.plus
• GitHub: https://github.com/chigwell