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TextAnalyzer is a project that streamlines routine text analysis tasks by using Large Language Models (LLMs) with specific prompts to quickly filter and extract desired information from various documents, saving time and effort in the content processing.

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textAnalyzer

TextAnalyzer is a project that streamlines routine text analysis tasks by using Large Language Models (LLMs) with specific prompts to quickly filter and extract desired information from various documents, saving time and effort in the content processing. Actually, it can define different prompts to filter, format, ... or analyze text with LLM for the repetitive work.

Disclaimer

  • This is a test project for text analysis using LLMs(suggest local LLM). It is not production ready, and it is not meant to be used in production.
  • Do not use models for analyzing your critical or production data!!
  • Do not use models for analyzing customer data to ensure data privacy and security!!
  • Do not use models for analyzing you private/sensitivity code respository!!

textAnalyzer

Deployment

  1. Setup the python 3.11.3 env and install
    • Suggest using virtual env
pip install -r requirement.txt
  1. Download the repository
git clone https://github.com/reid41/textAnalyzer.git
cd textAnalyzer
  1. Specify the LLM API(openai-like) in config/config.ini or set it after startup

  2. Startup

python llm_main.py
  1. Define the prompt and input the text to analyze

About

TextAnalyzer is a project that streamlines routine text analysis tasks by using Large Language Models (LLMs) with specific prompts to quickly filter and extract desired information from various documents, saving time and effort in the content processing.

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