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docs: replace efficiency pie charts with combined bar chart and update automation
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26
README.md
26
README.md
@@ -508,19 +508,23 @@ Projected monthly budget for 24/7 autonomous maintenance.
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### 7.2. Efficiency and Performance Metrics
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Achieves **>90% cost reduction** compared to full-Pro architectures by utilizing multi-tier caching, global concurrency semaphores, and structured batching.
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<!-- EFFICIENCY_CHART_START -->
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```mermaid
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pie title AI Curation Cost Distribution (Standard Monthly)
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"Elite Reasoning (Pro Tier)" : 75
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"Bulk Enrichment (Flash Tier)" : 15
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"Infrastructure Overhead" : 10
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```
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```mermaid
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pie title Processing Strategy (By Link Volume)
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"Local Metadata (Zero Cost)" : 65
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"Cached AI Insights (Zero Cost)" : 25
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"New AI Inference (Identity A)" : 10
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---
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config:
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themeVariables:
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xyChart:
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plotColorPalette: '#3b82f6, #fb923c'
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theme: mc
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---
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xychart-beta
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title "Economic Efficiency: Cost vs. Volume Share (%)"
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x-axis ["Elite / New AI", "Bulk / Cached", "Infra / Local"]
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y-axis "Share (%)" 0 --> 100
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bar [75, 15, 10]
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bar [10, 25, 65]
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```
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<!-- EFFICIENCY_CHART_END -->
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### 7.3. Economic Sustainability Principles
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1. **Identity Rotation (Identity A/B)**: Rotates between PAYG and Subscription keys.
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@@ -137,6 +137,14 @@ def get_stats():
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status = "**Agentic Inception (Gemini Era)**" if month == "2026-05" else "Active Curation"
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monthly_rows.append(f"| {month} | {count} | {est_refs:,} | {status} |")
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# 7. Efficiency Chart (Section 7.2)
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efficiency_chart = "```mermaid\n---\nconfig:\n themeVariables:\n xyChart:\n plotColorPalette: '#3b82f6, #fb923c'\n theme: mc\n---\nxychart-beta\n title \"Economic Efficiency: Cost vs. Volume Share (%)\"\n"
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efficiency_chart += " x-axis [\"Elite / New AI\", \"Bulk / Cached\", \"Infra / Local\"]\n"
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efficiency_chart += " y-axis \"Share (%)\" 0 --> 100\n"
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efficiency_chart += " bar [75, 15, 10]\n"
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efficiency_chart += " bar [10, 25, 65]\n"
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efficiency_chart += "```"
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# 8. Heart Stats Table
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heart_stats = [
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"| Metric | Value |",
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@@ -155,6 +163,7 @@ def get_stats():
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"annual_growth": "\n".join(annual_rows),
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"annual_chart": annual_chart,
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"monthly_surge": "\n".join(monthly_rows),
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"efficiency_chart": efficiency_chart,
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"last_update": datetime.now().strftime("%Y-%m-%d")
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}
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@@ -179,6 +188,7 @@ def update_readme(stats):
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content = replace_section(content, "ANNUAL_GROWTH", stats["annual_growth"])
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content = replace_section(content, "ANNUAL_CHART", stats["annual_chart"])
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content = replace_section(content, "MONTHLY_SURGE", stats["monthly_surge"])
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content = replace_section(content, "EFFICIENCY_CHART", stats["efficiency_chart"])
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content = replace_section(content, "PILLAR_CHART", stats["pillar_chart"])
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content = replace_section(content, "SUB_ECO_CHART", stats["lang_chart"])
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