Content Entity and Extraction for Large Language Models

Summary: The video discusses how to effectively extract content from lengthy client contracts using Generative AI (Gen AI) technology. By leveraging large language models (LLMs) like Granite.13b.chat and Mistral Large, users can interact with contracts in a conversational manner and create summaries in a fraction of the time it would take to manually read through these documents.

Keypoints:

• Client contracts can be extensive, often exceeding 50 pages.
• Instead of manually scrolling through contracts, users can interact conversationally to extract needed information.
• The process involves using LLMs to generate a summary document in under 20 minutes.
• Granite.13b.chat is used to extract key pieces of information from the contract.
• Mistral Large transforms extracted data into an easily readable table format.
• Dependencies required for the project include link chain, dotenv, and axios for HTTP requests.
• Essential credentials such as IBM Cloud API key and Watsonx project ID must be defined beforehand.
• The solution is implemented in a single large function for simplicity.
• Output output from LLMs can contain unnecessary characters (e.g., backticks) that need filtering.
• The final summary is saved into a markdown (.md) file for easy access.