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https://github.com/ggml-org/llama.cpp.git
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59778f0196
* webui: Move static build output from `tools/server/public` to `build/ui` directory * refactor: Move to `tools/ui` * refactor: rename CMake variables and preprocessor defines - Rename LLAMA_BUILD_WEBUI -> LLAMA_BUILD_UI (old kept as deprecated) - Rename LLAMA_USE_PREBUILT_WEBUI -> LLAMA_USE_PREBUILT_UI (old kept as deprecated) - Backward compat: old vars auto-forward to new ones with DEPRECATION warning - Rename internal vars: WEBUI_SOURCE -> UI_SOURCE, WEBUI_SOURCE_DIR -> UI_SOURCE_DIR, etc. - Rename HF bucket: LLAMA_WEBUI_HF_BUCKET -> LLAMA_UI_HF_BUCKET - Emit both LLAMA_BUILD_WEBUI and LLAMA_BUILD_UI preprocessor defines - Emit both LLAMA_WEBUI_DEFAULT_ENABLED and LLAMA_UI_DEFAULT_ENABLED * refactor: rename CLI flags (--webui -> --ui) with backward compat - Add --ui/--no-ui (old --webui/--no-webui kept as deprecated aliases) - Add --ui-config (old --webui-config kept as deprecated alias) - Add --ui-config-file (old --webui-config-file kept as deprecated alias) - Add --ui-mcp-proxy/--no-ui-mcp-proxy (old --webui-mcp-proxy kept as deprecated) - Add new env vars: LLAMA_ARG_UI, LLAMA_ARG_UI_CONFIG, LLAMA_ARG_UI_CONFIG_FILE, LLAMA_ARG_UI_MCP_PROXY - C++ struct fields: params.ui, params.ui_config_json, params.ui_mcp_proxy added alongside old fields - Backward compat: old fields synced to new ones in g_params_to_internals * refactor: update C++ server internals with backward compat - Rename json_webui_settings -> json_ui_settings (both kept in server_context_meta) - Rename params.webui usage -> params.ui (both synced, old still works) - JSON API emits both "ui"/"ui_settings" and "webui"/"webui_settings" keys - Server routes use params.ui_mcp_proxy || params.webui_mcp_proxy - Preprocessor guards use #if defined(LLAMA_BUILD_UI) || defined(LLAMA_BUILD_WEBUI) * refactor: rename CI/CD workflows, artifacts, and build script - Rename webui-build.yml -> ui-build.yml; artifact webui-build -> ui-build - Rename webui-publish.yml -> ui-publish.yml; var HF_BUCKET_WEBUI_STATIC_OUTPUT -> HF_BUCKET_UI_STATIC_OUTPUT - Rename server-webui.yml -> server-ui.yml; job webui-build/checks -> ui-build/checks - Update server.yml: job/artifact refs webui-build -> ui-build - Update release.yml: all webui-build/publish refs -> ui-build/publish; HF_TOKEN_WEBUI_STATIC_OUTPUT -> HF_TOKEN_UI_STATIC_OUTPUT - Update server-self-hosted.yml: webui-build -> ui-build - Update build-self-hosted.yml: HF_WEBUI_VERSION -> HF_UI_VERSION - Rename webui-download.cmake -> ui-download.cmake (internal refs updated) - Update labeler.yml: server/webui -> server/ui path label * docs: update CODEOWNERS and server README docs - Update CODEOWNERS: team ggml-org/llama-webui -> ggml-org/llama-ui, path /tools/server/webui/ -> /tools/ui/ - Update server README.md: CLI tables show --ui flags with deprecated --webui aliases - Update server README-dev.md: "WebUI" -> "UI", paths updated to tools/ui/ * fix: Small fixes for UI build * fix: CMake.txt syntax * chore: Formatting * fix: `.editorconfig` for llama-ui * chore: Formatting * refactor: Use `APP_NAME` in Error route * refactor: Cleanup * refactor: Single migration service * make llama-ui a linkable target * fix: UI Build output * fix: Missing change * fix: separate llama-ui npm build output into build/tools/ui/dist subfolder + use cmake npm build instead of downloading ui-build.yml artifacts in CI * refactor: UI workflows cleanup --------- Co-authored-by: Xuan Son Nguyen <son@huggingface.co>
125 lines
2.9 KiB
TypeScript
125 lines
2.9 KiB
TypeScript
// Data Analysis Report
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export const DATA_ANALYSIS_MD = String.raw`
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# Q4 2024 Business Analytics Report
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*Executive Summary • Generated on January 15, 2025*
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## 📊 Key Performance Indicators
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${'```'}
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Daily Active Users (DAU): 1.2M (+65% YoY)
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Monthly Active Users (MAU): 4.5M (+48% YoY)
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User Retention (Day 30): 68% (+12pp YoY)
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Average Session Duration: 24min (+35% YoY)
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${'```'}
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## 🎯 Product Performance
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### Feature Adoption Rates
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1. **AI Assistant**: 78% of users (↑ from 45%)
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2. **Collaboration Tools**: 62% of users (↑ from 38%)
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3. **Analytics Dashboard**: 54% of users (↑ from 31%)
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4. **Mobile App**: 41% of users (↑ from 22%)
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### Customer Satisfaction
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| Metric | Q4 2024 | Q3 2024 | Change |
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|--------|---------|---------|--------|
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| **NPS Score** | 72 | 68 | +4 |
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| **CSAT** | 4.6/5 | 4.4/5 | +0.2 |
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| **Support Tickets** | 2,340 | 2,890 | -19% |
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| **Resolution Time** | 4.2h | 5.1h | -18% |
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## 💰 Revenue Metrics
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### Monthly Recurring Revenue (MRR)
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- **Current MRR**: $2.8M (+42% YoY)
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- **New MRR**: $340K
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- **Expansion MRR**: $180K
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- **Churned MRR**: $95K
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- **Net New MRR**: $425K
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### Customer Acquisition
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${'```'}
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Cost per Acquisition (CAC): $127 (-23% YoY)
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Customer Lifetime Value: $1,840 (+31% YoY)
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LTV:CAC Ratio: 14.5:1
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Payback Period: 3.2 months
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${'```'}
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## 🌍 Geographic Performance
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### Revenue by Region
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1. **North America**: 45% ($1.26M)
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2. **Europe**: 32% ($896K)
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3. **Asia-Pacific**: 18% ($504K)
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4. **Other**: 5% ($140K)
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### Growth Opportunities
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- **APAC**: 89% YoY growth potential
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- **Latin America**: Emerging market entry
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- **Middle East**: Enterprise expansion
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## 📱 Channel Performance
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### Traffic Sources
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| Channel | Sessions | Conversion | Revenue |
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|---------|----------|------------|---------|
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| **Organic Search** | 45% | 3.2% | $1.1M |
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| **Direct** | 28% | 4.1% | $850K |
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| **Social Media** | 15% | 2.8% | $420K |
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| **Paid Ads** | 12% | 5.5% | $430K |
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### Marketing ROI
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- **Content Marketing**: 340% ROI
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- **Email Campaigns**: 280% ROI
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- **Social Media**: 190% ROI
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- **Paid Search**: 220% ROI
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## 🔍 User Behavior Analysis
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### Session Patterns
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- **Peak Hours**: 9-11 AM, 2-4 PM EST
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- **Mobile Usage**: 67% of sessions
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- **Average Pages/Session**: 4.8
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- **Bounce Rate**: 23% (↓ from 31%)
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### Feature Usage Heatmap
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Most used features in order:
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1. Dashboard (89% of users)
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2. Search (76% of users)
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3. Reports (64% of users)
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4. Settings (45% of users)
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5. Integrations (32% of users)
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## 💡 Recommendations
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1. **Invest** in AI capabilities (+$2M budget)
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2. **Expand** sales team in APAC region
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3. **Improve** onboarding to reduce churn
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4. **Launch** enterprise security features
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## Appendix
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### Methodology
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Data collected from:
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- Internal analytics (Amplitude)
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- Customer surveys (n=2,450)
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- Financial systems (NetSuite)
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- Market research (Gartner)
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---
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*Report prepared by Data Analytics Team • [View Interactive Dashboard](https://analytics.example.com)*
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`;
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