Commit graph

3 commits

Author SHA1 Message Date
DJP
bc778ce7af P2: Iterative prompting + RFP brief analysis engine
Iterative Prompting:
- Chat box on Match Review tab for natural language refinement
- "re-run under 70%" / "ignore zero volume" / "set all volumes to 1"
- Claude interprets instruction into structured actions
- Actions: rematch_below_threshold, rematch_specific, delete_assets, set_volume
- Re-matches affected assets automatically after refinement
- Chat log shows instruction history

RFP/Brief Analysis:
- New "Brief Analysis" tab between Upload and Match Review
- Extracts: summary, objectives, KPIs, channels, audiences, deliverable categories,
  constraints, timeline, budget, complexity assessment
- Generates prioritized discovery questions (Red/Amber/Green)
- Questions include category, rationale, and priority level
- Stored as JSON in project.brief_analysis field
- Uploaded files now saved to data dir for re-analysis
- Re-analyze button to refresh analysis

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-04-09 14:15:31 -04:00
DJP
26d3435be0 Improve matching, upload UX, collapse fix, full catalog approach
- Upload now shows live stage progress (uploading -> extracting -> AI parsing -> done)
- Fix match group collapse: proper React state instead of DOM manipulation
- Replace pre-filter with full GMAL catalog sent to Claude (~3k tokens, <$0.01)
  - FTS and keyword matching missed too many semantic matches
  - Claude now sees all 243 assets and uses semantic understanding
- Improved system prompt with terminology bridges for better scoring
- Per-project AI cost tracking persisted to DB
- Parallel matching with cancel support
- Auto-select matches >= 80%, YOLO button for rest
- Debug panel for AI call inspection

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-03-27 19:22:08 -04:00
DJP
e18976fdb2 Initial commit - GMAL Scope Builder
Dockerized web app (FastAPI + React + PostgreSQL) for scoping client ratecards
against the GMAL master asset database. Features:
- GMAL data ingestion from Excel (390 assets, 120 roles, 5 model types)
- AI-powered document parsing and asset extraction (Claude Opus 4.6)
- AI matching engine with parallel batching, confidence scoring, caveats
- Ratecard builder with hours x volume calculation
- Excel and PDF export
- GMAL browser and inline editor
- AI cost tracking per project (persisted to DB)
- Debug panel for AI call inspection
- Dark theme UI with gold (#FFC407) accent

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-03-27 17:35:14 -04:00