Add Streamlit meeting assistant MVP

README.md

@@ -8,8 +8,9 @@ local processing backend.
 
 The first product milestone is a desktop GUI that lets a user:
 
-- select an existing audio recording
-- create and edit structured meeting metadata and participants
+- select an existing WAV, FLAC, or M4A recording
+- create and edit structured meeting metadata and relevant people, including whether
+  they were present or only mentioned
 - optionally map anonymous `SPEAKER_XX` labels to known participants
 - start the Meeting Lab processing pipeline
 - follow stage-based progress
@@ -23,7 +24,7 @@ reference recorder, but imported audio is not tied to OBS-specific behavior.
 
 ```text
 Audio file
-    -> FFmpeg preparation (mono, 16 kHz PCM WAV)
+    -> FFmpeg preparation (mono, 16 kHz PCM WAV; normalization optional)
     -> whisper.cpp transcription (large-v3-turbo)
     -> optional pyannote.audio Community-1 diarization
     -> direct full-transcript protocol generation
@@ -58,8 +59,67 @@ orchestration and protocol-generation logic. Meeting Assistant owns the GUI,
 context and participant editing, explicit speaker mapping, progress display,
 protocol editing and export.
 
-The code currently contains the initial Meeting Assistant project and domain
-foundation. The GUI has not yet been implemented.
+Audio normalization is enabled by default and can be disabled in the processing
+options. This controls loudness normalization only: Meeting Lab still prepares
+every WAV, FLAC or M4A source as canonical audio before transcription.
+
+## Run the Streamlit MVP
+
+The development setup expects `meeting-assistant` and `meeting-lab` to be
+sibling repositories. Meeting Lab currently imports its API through the
+`src.meeting_lab` package path, so its repository root must be supplied on
+`PYTHONPATH`. Meeting Assistant does not modify `sys.path` at runtime.
+
+Create a virtual environment and install Meeting Assistant, including
+Streamlit:
+
+```bash
+python3 -m venv .venv
+.venv/bin/pip install -e '.[dev]'
+.venv/bin/pip install -e ../meeting-lab
+```
+
+Configure at least the local whisper.cpp model. All supported values are shown
+in `.env.example`; export them in the shell because the application does not
+load `.env` files implicitly:
+
+```bash
+export MKA_WHISPER_MODEL=/path/to/ggml-large-v3-turbo.bin
+export MKA_WHISPER_EXECUTABLE=whisper-cli
+export MKA_FFMPEG_EXECUTABLE=ffmpeg
+export MKA_PROTOCOL_MODEL=qwen3.8:27B
+```
+
+Optional machine-specific settings include:
+
+- `MKA_DATA_ROOT` (default: `data/meetings`)
+- `MKA_OLLAMA_ENDPOINT` (default: `http://127.0.0.1:11434`)
+- `MKA_WHISPER_THREADS` (default: `auto`)
+- `MKA_FFMPEG_EXECUTABLE` (default: `ffmpeg` found on `PATH`)
+- `MKA_DIARIZATION_MODE` (`auto`, `cpu`, or `gpu`; default: `auto`)
+- `MKA_DIARIZATION_RUNTIME` (`native` or `container`; default: `native`)
+- `MKA_DIARIZATION_CONTAINER_IMAGE` (required for container diarization)
+
+From the Meeting Assistant repository, start the UI with:
+
+```bash
+PYTHONPATH=src:../meeting-lab .venv/bin/streamlit run src/mka/ui/streamlit_app.py
+```
+
+Streamlit opens `http://localhost:8501` by default. Installing the sibling
+Meeting Lab project supplies its runtime requirements such as PyYAML and
+Requests. Optional diarization dependencies are needed only when diarization
+is enabled.
+
+Uploaded source files are stored under
+`data/meetings/<meeting-id>/uploads/`. Meeting Lab run artifacts are stored
+under `data/meetings/<meeting-id>/runs/`. The reviewed protocol is saved as
+`protocol_edited.md` inside its run directory; the generated `protocol.md`
+remains unchanged.
+
+The upload remains in its original format and is passed unchanged to Meeting Lab.
+Meeting Lab creates the canonical mono 16 kHz signed PCM16 WAV run artifact used by
+transcription; Meeting Assistant does not duplicate audio conversion.
 
 See [Architecture](docs/architecture.md), [Project Knowledge](PROJECT_KNOWLEDGE.md),
 [Roadmap](ROADMAP.md) and [ADR 0011](docs/adr/0011-use-meeting-lab-mvp-backend.md).