How to Automate Youtube and Blog Content with LangChain & OpenAI: A Step-by-Step Guide

This repo contains the code for AI-powered Marketing Assistant that uses LangChain and OpenAI to streamline your content creation process. Using LangChain you will create a SequentialChain that consists of a series of chains - a blog post chain, a YouTube script chain, and a YouTube visuals chain.

The detailed step-by-step guide can be found in either our YouTube or Medium article below.

YouTube https://www.youtube.com/@principlesofai/videos

Medium https://medium.com/@wayne923/fc6ed231ffa6

Overview of the Code

The code consists of an app.py file that is used to set up and run the AI-powered marketing assistant.

The app.py includes:

• Setting up the environment
• Building Blocks of LangChain
• Mastering the Basics of Chains in LangChain
• Integrating the assistant with Streamlit to build a Web App

The .env file is used to securely store your OpenAI API key.

Example of what you will learn

# LLMChain Example

# Model
llm = OpenAI(temperature=0.9)

# Prompt
blog_prompt_template = PromptTemplate(
    input_variables = ['product_description'],
    template = 'Write a blog post on {product_description}'
)

# Chain
blog_chain = LLMChain(llm=llm, prompt=blog_prompt_template, verbose=True)

# Run
product_description = 'best eco-friendly coffee'
blog_chain.run(product_description)

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