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Ollama Blog Generator with CrewAI on Mesop

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.

Table of Contents

Overview

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.

Requirements

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

Installation

  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

Usage

  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

Components

Agents

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.

Tasks

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

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

Crew

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.

Mesop Application

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.

Customization

  • 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.

Other

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

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