Getting Started

Getting Started with Agentic-Writer

This guide will help you get up and running with Agentic-Writer in just a few minutes.

Prerequisites

Before you begin, ensure you have:

• Python 3.8 or higher installed on your system
• pip package manager
• An OpenAI API key (required) - Get one here
• Optional: Unsplash API key for image search
• Optional: Medium API token for publishing to Medium

Quick Start (5 Minutes)

Step 1: Clone the Repository

git clone https://github.com/eggressive/agentic-writer.git
cd agentic-writer

Step 2: Install Dependencies

pip install -r requirements.txt

Or install in development mode:

pip install -e .

Step 3: Configure API Keys

Copy the example environment file:

cp .env.example .env

Edit .env and add your OpenAI API key:

# Required
OPENAI_API_KEY=sk-your-actual-api-key-here

# Optional - for enhanced features
MEDIUM_ACCESS_TOKEN=your-medium-token
UNSPLASH_ACCESS_KEY=your-unsplash-key

Step 4: Verify Installation

Run the verification script:

python verify_installation.py

You should see:

✓ All checks passed!
✓ Configuration is valid
✓ All dependencies are installed

Step 5: Check Configuration

python main.py config

Expected output:

╭───────────────────────╮
│ Current Configuration │
╰───────────────────────╯

OpenAI Model: gpt-4-turbo-preview
Temperature: 0.7
Max Research Sources: 5
Log Level: INFO

API Keys Status:
  OpenAI: ✓ Set
  Medium: ○ Optional
  Unsplash: ○ Optional

Step 6: Create Your First Article

python main.py create "The Future of Artificial Intelligence"

The system will:

1. 🔍 Research the topic (10-30 seconds)
2. ✍️ Write a comprehensive article (30-60 seconds)
3. 🖼️ Find relevant images (5-15 seconds)
4. 📤 Save to output/ directory (<5 seconds)

Step 7: View Your Article

cat output/the_future_of_artificial_intelligence.md

Your First Article - Detailed Example

Let's create an article with custom options:

python main.py create "Introduction to Machine Learning" \
  --style casual \
  --audience "beginners with no technical background" \
  --platform file \
  --output-dir ./my-articles

What this does:

• Topic: "Introduction to Machine Learning"
• Style: Casual, conversational tone
• Audience: Written for beginners
• Platform: Saves to file system
• Output: Saves to ./my-articles/ directory

Understanding the Output

Each content creation produces two files:

1. Markdown Article (.md)

# Introduction to Machine Learning

**Topic:** Introduction to Machine Learning
**Word Count:** 1342
**Tags:** machine learning, AI, data science, beginners, technology

**Meta Description:** A beginner-friendly introduction to machine learning concepts and applications...

---

[Full article content with proper markdown formatting]

2. Metadata JSON (_metadata.json)

{
  "title": "Introduction to Machine Learning",
  "topic": "Introduction to Machine Learning",
  "word_count": 1342,
  "tags": ["machine learning", "AI", "data science", "beginners", "technology"],
  "meta_description": "A beginner-friendly introduction...",
  "images": [
    {
      "url": "https://images.unsplash.com/...",
      "description": "AI and machine learning visualization",
      "author": "Photographer Name",
      "author_url": "https://unsplash.com/@photographer"
    }
  ],
  "sources_count": 5
}

Common Use Cases

1. Blog Post Generation

python main.py create "10 Benefits of Remote Work" \
  --style professional \
  --audience "business professionals"

2. Technical Tutorial

python main.py create "Getting Started with Docker" \
  --style technical \
  --audience "software developers"

3. Educational Content

python main.py create "Understanding Climate Change" \
  --style accessible \
  --audience "high school students"

4. Business Article

python main.py create "Digital Marketing Trends 2024" \
  --style professional \
  --audience "marketing executives"

Using the Python API

For more control, use the Python API directly:

from src.orchestrator import ContentCreationOrchestrator
from src.utils import Config, setup_logger

# Setup logging
logger = setup_logger(level="INFO")

# Load and validate configuration
config = Config.from_env()
config.validate_required()

# Initialize orchestrator
orchestrator = ContentCreationOrchestrator(config)

# Create content
results = orchestrator.create_content(
    topic="The Future of Quantum Computing",
    style="technical",
    target_audience="technology enthusiasts",
    platforms=["file"],
    output_dir="./articles"
)

# Check status
if results["status"] == "completed":
    print("✓ Article created successfully!")
    article = results["article"]
    print(f"Title: {article['title']}")
    print(f"Words: {article['word_count']}")
    print(f"Tags: {', '.join(article['tags'])}")
else:
    print(f"✗ Failed: {results.get('error', 'Unknown error')}")

Next Steps

Now that you're set up, explore these resources:

1. Usage Guide - Learn all the command options, features, and see real-world examples
2. Architecture - Understand how the system works
3. API Reference - Dive into the Python API
4. FAQ - Find answers to common questions

Troubleshooting Quick Fixes

"OPENAI_API_KEY is required but not set"

Solution: Add your API key to the .env file

"No module named 'langchain'"

Solution: Run pip install -r requirements.txt

Rate limiting errors

Solution: Wait a few minutes or use gpt-3.5-turbo model

Slow execution

Solution: Normal! Content creation takes 2-5 minutes

For more issues, see the Troubleshooting Guide.

Getting Help

• 📖 Read the FAQ
• 🐛 Report an issue
• 💬 Start a discussion
• 📧 Contact the maintainers

What's Next?

• ⭐ Star the repository on GitHub
• 🔔 Watch for updates and new features
• 🤝 Contribute improvements (see Contributing Guide)
• 📢 Share your experience and feedback

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Ready to dive deeper? Continue to the Usage Guide for comprehensive documentation.