Big-Link-Man/jobs

Job File Format

Job files define batch content generation parameters using JSON format.

Structure

{
  "jobs": [
    {
      "project_id": 1,
      "tiers": {
        "tier1": {
          "count": 5,
          "min_word_count": 2000,
          "max_word_count": 2500,
          "min_h2_tags": 3,
          "max_h2_tags": 5,
          "min_h3_tags": 5,
          "max_h3_tags": 10
        }
      }
    }
  ]
}

Fields

Job Level

• project_id (required): The project ID to generate content for
• tiers (required): Dictionary of tier configurations
• deployment_targets (optional): Array of site custom_hostnames or site_deployment_ids to cycle through
• deployment_overflow (optional): Strategy when batch size exceeds deployment_targets ("round_robin", "random_available", or "none"). Default: "round_robin"

Tier Level

• count (required): Number of articles to generate for this tier
• min_word_count (optional): Minimum word count (uses defaults if not specified)
• max_word_count (optional): Maximum word count (uses defaults if not specified)
• min_h2_tags (optional): Minimum H2 headings (uses defaults if not specified)
• max_h2_tags (optional): Maximum H2 headings (uses defaults if not specified)
• min_h3_tags (optional): Minimum H3 subheadings total (uses defaults if not specified)
• max_h3_tags (optional): Maximum H3 subheadings total (uses defaults if not specified)

Tier Defaults

If tier parameters are not specified, these defaults are used:

tier1

• min_word_count: 2000
• max_word_count: 2500
• min_h2_tags: 3
• max_h2_tags: 5
• min_h3_tags: 5
• max_h3_tags: 10

tier2

• min_word_count: 1500
• max_word_count: 2000
• min_h2_tags: 2
• max_h2_tags: 4
• min_h3_tags: 3
• max_h3_tags: 8

tier3

• min_word_count: 1000
• max_word_count: 1500
• min_h2_tags: 2
• max_h2_tags: 3
• min_h3_tags: 2
• max_h3_tags: 6

Examples

Simple: Single Tier with Defaults

{
  "jobs": [
    {
      "project_id": 1,
      "tiers": {
        "tier1": {
          "count": 5
        }
      }
    }
  ]
}

Custom Word Counts

{
  "jobs": [
    {
      "project_id": 1,
      "tiers": {
        "tier1": {
          "count": 3,
          "min_word_count": 2500,
          "max_word_count": 3000
        }
      }
    }
  ]
}

Multi-Tier

{
  "jobs": [
    {
      "project_id": 1,
      "tiers": {
        "tier1": {
          "count": 5
        },
        "tier2": {
          "count": 10
        },
        "tier3": {
          "count": 15
        }
      }
    }
  ]
}

Multiple Projects

{
  "jobs": [
    {
      "project_id": 1,
      "tiers": {
        "tier1": {
          "count": 5
        }
      }
    },
    {
      "project_id": 2,
      "tiers": {
        "tier1": {
          "count": 3
        },
        "tier2": {
          "count": 8
        }
      }
    }
  ]
}

Usage

Run batch generation with:

python main.py generate-batch --job-file jobs/example_tier1_batch.json --username youruser --password yourpass

Options

• --job-file, -j: Path to job JSON file (required)
• --username, -u: Username for authentication
• --password, -p: Password for authentication
• --debug: Save AI responses to debug_output/
• --continue-on-error: Continue processing if article generation fails
• --model, -m: AI model to use (default: gpt-4o-mini)

Deployment Target Assignment (Story 2.5)

Optionally specify which sites/buckets to deploy articles to:

{
  "jobs": [
    {
      "project_id": 1,
      "deployment_targets": [
        "www.domain1.com",
        "www.domain2.com",
        "www.domain3.com"
      ],
      "deployment_overflow": "round_robin",
      "tiers": {
        "tier1": {
          "count": 10
        }
      }
    }
  ]
}

This generates 10 articles distributed across 3 sites:

• Articles 0, 3, 6, 9 → domain1.com
• Articles 1, 4, 7 → domain2.com
• Articles 2, 5, 8 → domain3.com

Overflow Strategies:

• round_robin (default): Cycle back through specified targets
• random_available: Use random sites not in the targets list
• none: Error if batch exceeds target count (strict mode)

If deployment_targets is omitted, articles receive random templates (no site assignment).

Debug Mode

When using --debug, AI responses are saved to debug_output/:

• title_project{id}_tier{tier}_article{n}_{timestamp}.txt
• outline_project{id}_tier{tier}_article{n}_{timestamp}.json
• content_project{id}_tier{tier}_article{n}_{timestamp}.html
• augmented_project{id}_tier{tier}_article{n}_{timestamp}.html (if augmented)