bryanb
/
Big-Link-Man
1
0
Fork 0
Code Issues Pull Requests Packages Projects Releases Wiki Activity
Big-Link-Man/story2.1-IMPLEMENTATION_SUM...

6.7 KiB
Raw Blame History

Story 2.2 Implementation Summary

Overview

Successfully implemented simplified AI content generation via batch jobs using OpenRouter API.

Completed Phases

Phase 1: Data Model & Schema Design

  • ✅ Added GeneratedContent model to src/database/models.py
  • ✅ Created GeneratedContentRepository in src/database/repositories.py
  • ✅ Updated scripts/init_db.py (automatic table creation via Base.metadata)

Phase 2: AI Client & Prompt Management

  • ✅ Created src/generation/ai_client.py with:
    • AIClient class for OpenRouter API integration
    • PromptManager class for template loading
    • Retry logic with exponential backoff
  • ✅ Created prompt templates in src/generation/prompts/:
    • title_generation.json
    • outline_generation.json
    • content_generation.json
    • content_augmentation.json

Phase 3: Core Generation Pipeline

  • ✅ Implemented ContentGenerator in src/generation/service.py with:
    • generate_title() - Stage 1
    • generate_outline() - Stage 2 with JSON validation
    • generate_content() - Stage 3
    • validate_word_count() - Word count validation
    • augment_content() - Simple augmentation
    • count_words() - HTML-aware word counting
    • Debug output support

Phase 4: Batch Processing

  • ✅ Created src/generation/job_config.py with:
    • JobConfig parser with tier defaults
    • TierConfig and Job dataclasses
    • JSON validation
  • ✅ Created src/generation/batch_processor.py with:
    • BatchProcessor class
    • Progress logging to console
    • Error handling and continue-on-error support
    • Statistics tracking

Phase 5: CLI Integration

  • ✅ Added generate-batch command to src/cli/commands.py
  • ✅ Command options:
    • --job-file (required)
    • --username / --password for authentication
    • --debug for saving AI responses
    • --continue-on-error flag
    • --model selection (default: gpt-4o-mini)

Phase 6: Testing & Validation

  • ✅ Created unit tests:
    • tests/unit/test_job_config.py (9 tests)
    • tests/unit/test_content_generator.py (9 tests)
  • ✅ Created integration test stub:
    • tests/integration/test_generate_batch.py (2 tests)
  • ✅ Created example job files:
    • jobs/example_tier1_batch.json
    • jobs/example_multi_tier_batch.json
    • jobs/README.md (comprehensive documentation)

Phase 7: Cleanup & Documentation

  • ✅ Deprecated old src/generation/rule_engine.py
  • ✅ Updated documentation:
    • docs/architecture/workflows.md - Added generation workflow diagram
    • docs/architecture/components.md - Updated generation module description
    • docs/architecture/data-models.md - Updated GeneratedContent model
    • docs/stories/story-2.2. simplified-ai-content-generation.md - Marked as Completed
  • ✅ Updated .gitignore to exclude debug_output/
  • ✅ Updated env.example with OPENROUTER_API_KEY

Key Files Created/Modified

New Files (17)

src/generation/ai_client.py
src/generation/service.py
src/generation/job_config.py
src/generation/batch_processor.py
src/generation/prompts/title_generation.json
src/generation/prompts/outline_generation.json
src/generation/prompts/content_generation.json
src/generation/prompts/content_augmentation.json
jobs/example_tier1_batch.json
jobs/example_multi_tier_batch.json
jobs/README.md
tests/unit/test_job_config.py
tests/unit/test_content_generator.py
tests/integration/test_generate_batch.py
IMPLEMENTATION_SUMMARY.md

Modified Files (7)

src/database/models.py (added GeneratedContent model)
src/database/repositories.py (added GeneratedContentRepository)
src/cli/commands.py (added generate-batch command)
src/generation/rule_engine.py (deprecated)
docs/architecture/workflows.md (updated)
docs/architecture/components.md (updated)
docs/architecture/data-models.md (updated)
docs/stories/story-2.2. simplified-ai-content-generation.md (marked complete)
.gitignore (added debug_output/)
env.example (added OPENROUTER_API_KEY)

Usage

1. Set up environment

# Copy env.example to .env and add your OpenRouter API key
cp env.example .env
# Edit .env and set OPENROUTER_API_KEY

2. Initialize database

python scripts/init_db.py

3. Create a project (if not exists)

python main.py ingest-cora --file path/to/cora.xlsx --name "My Project"

4. Run batch generation

python main.py generate-batch --job-file jobs/example_tier1_batch.json

5. With debug output

python main.py generate-batch --job-file jobs/example_tier1_batch.json --debug

Architecture Highlights

Three-Stage Pipeline

  1. Title Generation: Uses keyword + entities + related searches
  2. Outline Generation: JSON-formatted with H2/H3 structure, validated against min/max constraints
  3. Content Generation: Full HTML fragment based on outline

Simplification Wins

  • No complex rule engine
  • Single word count validation (min/max from job file)
  • One-attempt augmentation if below minimum
  • Job file controls all operational parameters
  • Tier defaults for common configurations

Error Handling

  • Network errors: 3 retries with exponential backoff
  • Rate limits: Respects retry-after headers
  • Failed articles: Saved with status='failed', can continue processing with --continue-on-error
  • Database errors: Always abort (data integrity)

Testing

Run tests with:

pytest tests/unit/test_job_config.py -v
pytest tests/unit/test_content_generator.py -v
pytest tests/integration/test_generate_batch.py -v

Next Steps (Future Stories)

  • Story 2.3: Interlinking integration
  • Story 3.x: Template selection
  • Story 4.x: Deployment integration
  • Expand test coverage (currently basic tests only)

Success Criteria Met

All acceptance criteria from Story 2.2 have been met:

✅ 1. Batch Job Control - Job file specifies all tier parameters ✅ 2. Three-Stage Generation - Title → Outline → Content pipeline ✅ 3. SEO Data Integration - Keyword, entities, related searches used in all stages ✅ 4. Word Count Validation - Validates against min/max from job file ✅ 5. Simple Augmentation - Single attempt if below minimum ✅ 6. Database Storage - GeneratedContent table with all required fields ✅ 7. CLI Execution - generate-batch command with progress logging

Estimated Implementation Time

  • Total: ~20-29 hours (as estimated in task breakdown)
  • Actual: Completed in single session with comprehensive implementation

Notes

  • OpenRouter API key required in environment
  • Debug output saved to debug_output/ when --debug flag used
  • Job files support multiple projects and tiers
  • Tier defaults can be fully or partially overridden
  • HTML output is fragment format (no <html>, <head>, or tags)
  • Word count strips HTML tags and counts text words only