When a subsequent revision of a proof is uploaded, the analysis now takes
place in context of the previous version's results. The system identifies:
- Resolved issues: fixed in the new revision
- Outstanding issues: still present from previous version
- New issues: introduced in the new revision
Key changes:
- Add resolvedIssues, outstandingIssues, newIssues fields to SubReview
- Add PreviousReviewContext model for passing previous review data
- Update all specialist agents to accept previous_review context
- Extend GeminiService with include_revision_fields parameter
- Add get_latest_version_review() repository method
- Update LeadAgent to synthesize cross-version context in summary
- Fetch previous analysis in WebSocket handler for revisions
First version analysis continues to work exactly as before with revision
fields set to null.
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
- Remove Tone Agent (tone is now part of Brand specs)
- Split Channel Agent into Channel Best Practices Agent and Channel Tech Specs Agent
- Convert Legal Agent from stub to full Gemini-powered implementation
- Add new prompt files for channel_best_practices.md, channel_tech_specs.md, legal.md
- Update ReferenceDocsService with new methods for loading specs
- Update schemas and analysis service to use new agent structure
- Update all frontend components to use new agent names and properties
- Update mock data in Projects.tsx and Campaigns.tsx
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
- Add brand field to AnalyzeProofOptions interface and WebSocket message
- Pass campaign's brandGuidelines to analyzeProof in App.tsx (upload & retry)
- Extract brand from WebSocket message in handlers.py and pass to analysis
- Update AnalysisService.analyze_proof to accept brand parameter
- Refactor BrandAgent to dynamically select brand spec based on brand param
- Add get_barclays_brand_spec() method to ReferenceDocsService (placeholder)
The brand agent now uses the appropriate specification (Barclaycard spec or
Barclays spec when available) based on the campaign's brandGuidelines setting.
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
- Create prompts/brand_barclaycard.md with structured brand guidelines
covering logo, Card Portal, colors, typography, and accessibility
- Update ReferenceDocsService with get_barclaycard_brand_spec() method
- Update BrandAgent to use the new spec instead of raw reference docs
- Spec is ~15KB vs ~293KB of raw docs for more efficient analysis
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
Add explicit formatting instructions to agent prompts requesting bullet-point
output instead of verbose paragraphs. Update JSON schema descriptions for
feedback and summary fields to enforce concise, outline-style format.
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
PDFs are now converted to PNG images at 200 DPI before being sent to
Gemini for analysis. This fixes the unreliable iframe-based PDF preview
and ensures all pages are properly analyzed.
- Add PyMuPDF dependency for PDF rasterization
- Create pdf_service.py with rasterize() and get_page_count()
- Update agent interfaces to accept list of images for multi-page support
- Add analyze_with_images() to Gemini service for multi-image analysis
- Return rasterized PDF pages via WebSocket for frontend display
- Add page navigation UI for multi-page PDFs in preview components
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
