feat: refresh pipeline, reorganize draft generation, polish public pages
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Pipeline refresh:
- Extract ideas from 46 remaining drafts (844 total ideas now)
- Clear stale llm_cache entries blocking re-extraction
- Re-run gap analysis with expanded corpus: 10 gaps (was 12), fresh IDs #1-#10
- Re-link 3 proposals to new gap IDs
- Add scripts/pipeline-refresh.sh for reproducible runs

Draft generation moved from gaps to proposals:
- Remove "Generate Internet-Draft" section from gap detail page
- Add it to proposal detail page instead (proposals → generate I-D flow)
- New route POST /proposals/<id>/generate with richer context
  (proposal title + description + linked gap topics)
- Remove misleading "Search related drafts" link from gap page
  (related drafts already shown inline)

Public page polish:
- Overview: update subtitle to mention all 6 standards bodies
- About: describe multi-source scope (IETF, ISO, ITU-T, ETSI, NIST, W3C)
- About: add guiding question ("Where is the AI agent standards race heading?")
- Obsidian export button hidden in production mode (prior commit)

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
This commit is contained in:
2026-03-09 05:39:13 +01:00
parent f8ed2b83e9
commit 42b4546ded
7 changed files with 215 additions and 159 deletions

30
scripts/pipeline-refresh.sh Executable file
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#!/usr/bin/env bash
# Pipeline refresh: extract missing ideas, re-score, then re-run gap analysis
# Run from project root: bash scripts/pipeline-refresh.sh
set -euo pipefail
cd "$(dirname "$0")/.."
export PYTHONPATH=src
echo "=== Step 1/3: Extract ideas from 38 remaining drafts ==="
python -m ietf_analyzer.cli ideas --all --cheap --batch 5 --limit 50
echo ""
echo "=== Step 2/3: Score new ideas for novelty ==="
python -m ietf_analyzer.cli ideas score --cheap --batch 10
echo ""
echo "=== Step 3/3: Re-run gap analysis ==="
python -m ietf_analyzer.cli gaps --refresh
echo ""
echo "=== Done ==="
python -c "
from ietf_analyzer.config import Config
from ietf_analyzer.db import Database
cfg = Config.load()
db = Database(cfg)
ideas = db.conn.execute('SELECT count(*) FROM ideas').fetchone()[0]
gaps = db.conn.execute('SELECT count(*) FROM gaps').fetchone()[0]
print(f'Ideas: {ideas}, Gaps: {gaps}')
"