j2machado / langchain-entity-extraction

An example implementation of Entity Extraction with LangChain + OpenAI without any additional dependencies. All the extraction and output is done by the LLM.

LangChain Entity Extraction

The goal is to create a chatbot capable of parsing all the entities from the user input required to fulfill the user's request.

Below is the example of a simple chatbot that interfaces between the user and the WordPress admin, capable of parsing all the user requirements and fulfill the user's request.

Example Scenario:

USER: I want to create a blog post titled My amazing adventure learning LangChain.
AI AGENT: { response: { "post_title": "My amazing adventure learning LangChain", "post_content": "Lorem Ipsum", "post_category": "Uncategorized" } }

Based on Conversational Bot with Entity Extraction, and ported to NodeJS.