How dalouuu/mutech works
MuTech combines two product workflows: an SLR research pipeline and a choir pitch-tracking studio. The SLR workflow ingests and screens literature, mines text, models topics, analyzes networks and temporal change, and supports manuscript synthesis. The studio accepts choir audio, runs multif0 inference and intonation analysis, and presents results with audio playback and pitch visualization. Source excerpts substantiate key backend and UI calls; SLR phase capabilities and some orchestration links rely on README documentation, so unsampled internals are represented at subsystem level.
Main entry points: app.py MIR API · mf0_service.py multif0 Inference · pipeline_engine.py PRISMA Screening · main.ts Studio Browser
Components 24
SLR Research
- Literature Exports
slr/data/01_raw - PRISMA Screening
slr/src/pipeline_engine.py - Text Mining
slr/src/pipeline_engine.py - Topic Modeling
slr/src/pipeline_engine.py - Network Analysis
slr/src/pipeline_engine.py - Research Outputs
slr/outputs - Manuscript Synthesis
slr/manuscript - Pipeline CLI
slr/run_pipeline.py - Pipeline Dashboard
slr/pipeline_ui_server.py
Choir Studio
- Audio Upload
mvp/backend/audio_processor.py - multif0 Inference
mvp/backend/mf0_service.py - Pitch DSP
mvp/backend/dsp_utils.py - Voice Tracking
mvp/backend/contour_tracker.py - Intonation Analytics
mvp/backend/analytics.py - Async Jobs
mvp/backend/job_manager.py - MIR API
mvp/backend/app.py - MIDI Export
mvp/backend/midi_exporter.py - Pitch Results
Studio Interface
- Studio Browser
mvp/frontend/src/main.ts - API Client
mvp/frontend/src/api.ts - Pitch Visualization
mvp/frontend/src/plot.ts - Music Helpers
mvp/frontend/src/music.ts
Other components
- Researcher
- Choir User
Connections 26
- Researcher → Pipeline CLI: runs phases
README.md - Researcher → Pipeline Dashboard: runs phases
README.md - Pipeline CLI → PRISMA Screening: dispatches
README.md - Pipeline Dashboard → PRISMA Screening: runs
slr/pipeline_ui_server.py - Literature Exports → PRISMA Screening: provides records
slr/src/pipeline_engine.py - PRISMA Screening → Text Mining: precedes
README.md - Text Mining → Topic Modeling: precedes
README.md - Topic Modeling → Network Analysis: precedes
README.md - Network Analysis → Research Outputs: writes results
slr/src/pipeline_engine.py - Network Analysis → Manuscript Synthesis: supports synthesis
README.md - Choir User → Studio Browser: selects audio
README.md - Studio Browser → API Client: requests transcription
mvp/frontend/src/main.ts - API Client → MIR API: posts audio
README.md - MIR API → Audio Upload: decodes and conditions
mvp/backend/app.py - MIR API → multif0 Inference: requests inference
mvp/backend/app.py - multif0 Inference → Audio Upload: uses preprocessing
mvp/backend/mf0_service.py - multif0 Inference → Pitch DSP: refines pitches
mvp/backend/mf0_service.py - multif0 Inference → Voice Tracking: links contours
mvp/backend/mf0_service.py - MIR API → Intonation Analytics: analyzes results
mvp/backend/app.py - Intonation Analytics → Pitch DSP: uses pitch utilities
mvp/backend/analytics.py - MIR API → Async Jobs: manages async work
mvp/backend/app.py - MIR API → MIDI Export: creates MIDI
mvp/backend/app.py - MIR API → Pitch Results: returns analysis
mvp/backend/app.py - API Client → Pitch Results: receives results
mvp/frontend/src/api.ts - Studio Browser → Pitch Visualization: renders pitch chart
mvp/frontend/src/main.ts - Pitch Visualization → Music Helpers: formats notes
mvp/frontend/src/plot.ts