Linkedin_Automation_with_Generative_AI

This tool leverages the power of artificial intelligence and machine learning to automate the process of creating and posting high-quality content on LinkedIn. It utilizes Gen AI, a large language model, to generate engaging text and Information Ratri to extract relevant information from provided links.

Features

Automated content creation: Generate compelling LinkedIn posts based on your intent and provided links.
Intelligent posting: Determine the optimal time to post your content for maximum engagement.
Image capturing: Automatically find and include relevant images to accompany your posts.
Time-saving efficiency: Streamline your LinkedIn posting process and save valuable time.

Prerequisites

Python 3.x 🐍
Pip package installer 📦
Valid LinkedIn account 💼
Installation 🎯
Clone or download the repository 🚀

Quickstart

Python installation

Install our linkedin_automation psi repo

pip install -q git+https://github.com/gathnexadmin/Linkedin_Automation_with_Generative_AI.git

Import files and setup the credentials

To know more about how to create linkedin access token checkout previous blog : https://medium.com/@gathnex/automating-the-linkedin-posts-using-generative-ai-llm-part-1-how-to-create-linkedin-api-e5f77fa46e5f

#import this two files contain PSI automation system
from psi import llm_automation, Linkedin_post
#setup your credentials
OPENAI_API_KEY = "openai key"
access_token = "linkedin access token"

PSI function

def psi(prompt):
    llm = llm_automation.llm_auto(prompt, OPENAI_API_KEY)
    if llm.intent_indentifier() == "#Post":
        url = llm.prompt_link_capturer()
        res = Linkedin_post.LinkedinAutomate(access_token, url, OPENAI_API_KEY).main_func()
        return llm.posted_or_not(res)
    else:
        return llm.normal_gpt()

Now, you're ready to use Genrative AI with PSI tool

psi("create content about my new medium blog post https://medium.com/@gathnex/new-generative-ai-course-by-deeplearning-ai-daf34e24e9c8 and post it on my linkedin")

Contributing

We welcome contributions to this project. Please feel free to open issues or pull requests with your suggestions or code improvements.

License

This project is licensed under the MIT License.