This project demonstrates how to use the CrewAI framework to automate the process of generating blog posts using a collaborative approach between two AI agents: a Tech Writer and a Tech Researcher. The agents leverage the ChatOpenAI language model to generate and iterate on content, managed within a Mesop web application.

• Overview
• Requirements
• Installation
• Usage
• Components
  • Agents
  • Tasks
  • Crew
  • Mesop Application
• Customization
• Other

This repository contains a Python project that creates a web application using Mesop, where users can generate short blog posts about a given topic. The application is powered by CrewAI, which manages the collaboration between two specialized agents: a Tech Writer and a Tech Researcher.

The Tech Researcher gathers key points, keywords, and trends on the given topic, while the Tech Writer crafts a blog post based on the research. The project uses the llama3.1 model hosted locally.

• Python 3.11
• Mesop
• CrewAI
• langchain_openai
• Ollama LLM hosted locally

1. Clone the repository:

   git clone https://github.com/rapidarchitect/ollama-crew-mesop.git
   cd ollama-crew-mesop

2. Install the required python packages

    pip install -r requirements.txt

3. Pull llama3.1 for ollama (NOTE: Ollama must already be installed, if not see https://ollama.ai)

    ollama pull llama3.1

1. Run the mesop server:

   mesop ollama_crew.py

2. Open your browser to the link provided by mesop

3. Enter a topic to write a blog post about

Tech Writer: Responsible for writing and iterating a high-quality blog post.

Tech Researcher: Focuses on gathering keywords, key points, and trends for the given topic.

Task 1: The Researcher lists relevant keywords, key points, and trends.

Task 2: The Writer creates a blog post based on the research.

The Crew class manages the execution of tasks in a sequential process, ensuring the output from the researcher is used by the writer to generate a blog post.

The application uses the Mesop framework to create a web interface where users can input a topic and view the generated blog content. The state of agent messages is managed and displayed within the web interface.

• Agents: Modify the role, backstory, or goal attributes to adjust the behavior of the agents.
• Tasks: Customize the task descriptions to change the focus of research or writing.
• Model: Replace llama3.1 with another model supported by Ollama.

Three additional scripts are included for educational purposes, an OpenAI version of the same app, a cli version and a simple crewAI example using a math professor