feat: add speaker mapping and workflow improvements

.env.example

@@ -4,6 +4,7 @@ MKA_FFMPEG_EXECUTABLE=ffmpeg
 MKA_PROTOCOL_MODEL=qwen3.8:27b
 MKA_OLLAMA_ENDPOINT=http://127.0.0.1:11434
 MKA_DATA_ROOT=data/meetings
+MKA_GLOSSARY_DATABASE=data/database/glossary.sqlite3
 MKA_WHISPER_THREADS=auto
 MKA_DIARIZATION_MODE=auto
 MKA_DIARIZATION_RUNTIME=native

PROJECT_KNOWLEDGE.md

@@ -37,9 +37,17 @@ Meeting Assistant owns user interaction and product workflow:
 - structured Meeting Context editing
 - participant management
 - versioned YAML import/export for reusable People lists, using replace semantics
+- versioned JSON import/export for the complete user-configurable run-input
+  form; source media is represented only by optional filename metadata and must
+  be selected again after import
 - optional explicit speaker mapping
+- post-diarization speaker review and protocol-only regeneration from existing
+  run artifacts
 - pipeline launch and progress display
 - protocol review and editing
+- a global SQLite terminology glossary whose active canonical core terms and
+  recognition aliases are rendered through Meeting Context into direct
+  protocol prompts
 - export and presentation of protocol versions
 
 Processing logic must not be duplicated in the application.

README.md

@@ -42,6 +42,12 @@ compatibility path. Diarization is optional and produces anonymous speaker
 labels. A label identifies a participant only when the user explicitly
 confirms the mapping; automatic speaker-name inference is not allowed.
 
+After a diarized run, the result view lists detected `SPEAKER_XX` labels with
+short transcript excerpts. Confirmed mappings regenerate only the protocol
+from the existing diarized transcript; audio preparation, Whisper and Pyannote
+are not rerun. `Unmapped / Unknown` remains valid, and the original anonymous
+diarized transcript is preserved.
+
 ## Product Outputs
 
 The product direction includes:
@@ -108,6 +114,41 @@ Optional machine-specific settings include:
 - `MKA_DIARIZATION_CONTAINER_IMAGE` (required for container diarization)
 - `MKA_DIARIZATION_CONTAINER_ARGS` (default: no extra arguments), encoded as a
   JSON array of strings so ordering and leading dashes are preserved exactly
+- `MKA_GLOSSARY_DATABASE` (default: `data/database/glossary.sqlite3`), the local
+  SQLite file used by the global terminology glossary
+
+## Terminology glossary
+
+The Streamlit **Terminology glossary** section manages recurring product,
+material, organization, acronym, and technical names. Store canonical core
+terms such as `Secugrid HS`, not every compound such as `Secugrid HS Düse`.
+Aliases help the protocol model recognize transcript variants while retaining
+the surrounding wording. Only active entries are added to Meeting Context as
+authoritative terminology for direct protocol generation; inactive entries
+remain stored but are omitted. The production database starts empty.
+
+The database defaults to `data/database/glossary.sqlite3`. It is created and
+bootstrapped automatically and can be moved with `MKA_GLOSSARY_DATABASE`.
+Glossary integration does not rewrite raw or diarized transcript artifacts.
+
+## Input configuration import and export
+
+Use **Export inputs** to save the current Meeting Assistant run-input form as a
+small, versioned JSON file and **Import inputs** to restore it later. The file
+contains meeting metadata, participant records, language, date, audio
+normalization, and diarization choices. It contains form configuration only:
+generated prompts, protocols, run artifacts, and source-media contents are not
+included.
+
+The original source filename may be retained as a reminder, but importing does
+not restore an upload. Select the audio file explicitly before starting the new
+run.
+
+Protocol generation with `qwen3.8:27b` explicitly requests a 32,768-token
+Ollama context with thinking disabled; Ollama's machine default may otherwise
+be only 4,096. Keep normal prompt input at approximately 29,000 tokens or less.
+Although a 31,038-token synthetic prompt passed, larger input is not assumed
+safe merely because the model advertises a 262,144-token native context.
 
 For example, a compatible AMD ROCm workstation can configure validated
 container access without adding controls to the Streamlit UI:

src/mka/application/config.py

@@ -18,6 +18,7 @@ class AppSettings:
 
     data_root: Path
     whisper_model: Path | None
+    glossary_database: Path = Path("data/database/glossary.sqlite3")
     whisper_executable: str = "whisper-cli"
     ffmpeg_executable: str = "ffmpeg"
     protocol_model: str = "qwen3.8:27b"
@@ -40,9 +41,12 @@ class AppSettings:
         return cls(
             data_root=Path(os.getenv("MKA_DATA_ROOT", "data/meetings")),
             whisper_model=Path(whisper_model) if whisper_model else None,
+            glossary_database=Path(
+                os.getenv("MKA_GLOSSARY_DATABASE", "data/database/glossary.sqlite3")
+            ),
             whisper_executable=os.getenv("MKA_WHISPER_EXECUTABLE", "whisper-cli"),
             ffmpeg_executable=os.getenv("MKA_FFMPEG_EXECUTABLE", "ffmpeg"),
-            protocol_model=os.getenv("MKA_PROTOCOL_MODEL", "qwen3.8:27B"),
+            protocol_model=os.getenv("MKA_PROTOCOL_MODEL", "qwen3.8:27b"),
             ollama_endpoint=os.getenv("MKA_OLLAMA_ENDPOINT", "http://127.0.0.1:11434"),
             language=os.getenv("MKA_LANGUAGE", "de"),
             threads=parsed_threads,

src/mka/application/glossary.py

@@ -0,0 +1,294 @@
+"""SQLite-backed global terminology glossary."""
+
+from __future__ import annotations
+
+import sqlite3
+from collections.abc import Iterable, Iterator
+from contextlib import contextmanager
+from dataclasses import dataclass
+from datetime import UTC, datetime
+from pathlib import Path
+
+GLOSSARY_CATEGORIES = (
+    "product",
+    "material",
+    "organization",
+    "technical_term",
+    "acronym",
+    "other",
+)
+
+
+class GlossaryConflictError(ValueError):
+    """Raised when a canonical term or alias conflicts with existing terminology."""
+
+
+@dataclass(frozen=True)
+class GlossaryEntry:
+    id: int
+    canonical_term: str
+    category: str
+    description: str | None
+    is_active: bool
+    aliases: tuple[str, ...]
+    created_at: str
+    updated_at: str
+
+
+class GlossaryRepository:
+    """Small data-access boundary for the local glossary database."""
+
+    def __init__(self, database_path: Path) -> None:
+        self.database_path = Path(database_path)
+
+    def initialize(self) -> None:
+        """Create the database and current schema when absent."""
+        self.database_path.parent.mkdir(parents=True, exist_ok=True)
+        with self._connect() as connection:
+            connection.executescript(
+                """
+                CREATE TABLE IF NOT EXISTS glossary_entries (
+                    id INTEGER PRIMARY KEY,
+                    canonical_term TEXT NOT NULL COLLATE NOCASE UNIQUE,
+                    category TEXT NOT NULL CHECK (category IN (
+                        'product', 'material', 'organization',
+                        'technical_term', 'acronym', 'other'
+                    )),
+                    description TEXT,
+                    is_active INTEGER NOT NULL DEFAULT 1 CHECK (is_active IN (0, 1)),
+                    created_at TEXT NOT NULL,
+                    updated_at TEXT NOT NULL
+                );
+                CREATE TABLE IF NOT EXISTS glossary_aliases (
+                    id INTEGER PRIMARY KEY,
+                    entry_id INTEGER NOT NULL REFERENCES glossary_entries(id)
+                        ON DELETE CASCADE,
+                    alias TEXT NOT NULL COLLATE NOCASE UNIQUE,
+                    created_at TEXT NOT NULL
+                );
+                CREATE INDEX IF NOT EXISTS idx_glossary_aliases_entry_id
+                    ON glossary_aliases(entry_id);
+                PRAGMA user_version = 1;
+                """
+            )
+
+    def create(
+        self,
+        canonical_term: str,
+        category: str,
+        *,
+        aliases: Iterable[str] = (),
+        description: str | None = None,
+        is_active: bool = True,
+    ) -> GlossaryEntry:
+        canonical, normalized_aliases = self._validate_values(canonical_term, category, aliases)
+        now = _timestamp()
+        try:
+            with self._connect() as connection:
+                self._ensure_terms_available(connection, canonical, normalized_aliases)
+                cursor = connection.execute(
+                    """INSERT INTO glossary_entries
+                    (canonical_term, category, description, is_active, created_at, updated_at)
+                    VALUES (?, ?, ?, ?, ?, ?)""",
+                    (canonical, category, _optional_text(description), is_active, now, now),
+                )
+                entry_id = int(cursor.lastrowid)
+                connection.executemany(
+                    "INSERT INTO glossary_aliases (entry_id, alias, created_at) VALUES (?, ?, ?)",
+                    ((entry_id, alias, now) for alias in normalized_aliases),
+                )
+        except sqlite3.IntegrityError as exc:
+            raise GlossaryConflictError("Canonical term or alias already exists.") from exc
+        return self.get(entry_id)
+
+    def get(self, entry_id: int) -> GlossaryEntry:
+        with self._connect() as connection:
+            row = connection.execute(
+                "SELECT * FROM glossary_entries WHERE id = ?", (entry_id,)
+            ).fetchone()
+            if row is None:
+                raise KeyError(f"Unknown glossary entry: {entry_id}")
+            return self._to_entry(connection, row)
+
+    def list(self, search: str = "", *, active_only: bool = False) -> list[GlossaryEntry]:
+        clauses: list[str] = []
+        parameters: list[object] = []
+        if active_only:
+            clauses.append("entry.is_active = 1")
+        if search.strip():
+            clauses.append(
+                "(entry.canonical_term LIKE ? COLLATE NOCASE "
+                "OR entry.category LIKE ? COLLATE NOCASE "
+                "OR entry.description LIKE ? COLLATE NOCASE "
+                "OR alias.alias LIKE ? COLLATE NOCASE)"
+            )
+            pattern = f"%{search.strip()}%"
+            parameters.extend([pattern] * 4)
+        where = f"WHERE {' AND '.join(clauses)}" if clauses else ""
+        with self._connect() as connection:
+            rows = connection.execute(
+                f"""SELECT DISTINCT entry.* FROM glossary_entries AS entry
+                LEFT JOIN glossary_aliases AS alias ON alias.entry_id = entry.id
+                {where} ORDER BY entry.canonical_term COLLATE NOCASE""",  # noqa: S608
+                parameters,
+            ).fetchall()
+            return [self._to_entry(connection, row) for row in rows]
+
+    def update(
+        self,
+        entry_id: int,
+        canonical_term: str,
+        category: str,
+        *,
+        aliases: Iterable[str] = (),
+        description: str | None = None,
+        is_active: bool = True,
+    ) -> GlossaryEntry:
+        canonical, normalized_aliases = self._validate_values(canonical_term, category, aliases)
+        try:
+            with self._connect() as connection:
+                exists = connection.execute(
+                    "SELECT 1 FROM glossary_entries WHERE id = ?", (entry_id,)
+                ).fetchone()
+                if exists is None:
+                    raise KeyError(f"Unknown glossary entry: {entry_id}")
+                self._ensure_terms_available(
+                    connection, canonical, normalized_aliases, excluding_entry_id=entry_id
+                )
+                now = _timestamp()
+                connection.execute(
+                    """UPDATE glossary_entries SET canonical_term = ?, category = ?,
+                    description = ?, is_active = ?, updated_at = ? WHERE id = ?""",
+                    (
+                        canonical,
+                        category,
+                        _optional_text(description),
+                        is_active,
+                        now,
+                        entry_id,
+                    ),
+                )
+                connection.execute("DELETE FROM glossary_aliases WHERE entry_id = ?", (entry_id,))
+                connection.executemany(
+                    "INSERT INTO glossary_aliases (entry_id, alias, created_at) VALUES (?, ?, ?)",
+                    ((entry_id, alias, now) for alias in normalized_aliases),
+                )
+        except sqlite3.IntegrityError as exc:
+            raise GlossaryConflictError("Canonical term or alias already exists.") from exc
+        return self.get(entry_id)
+
+    def set_active(self, entry_id: int, is_active: bool) -> GlossaryEntry:
+        entry = self.get(entry_id)
+        return self.update(
+            entry.id,
+            entry.canonical_term,
+            entry.category,
+            aliases=entry.aliases,
+            description=entry.description,
+            is_active=is_active,
+        )
+
+    def delete(self, entry_id: int) -> None:
+        with self._connect() as connection:
+            cursor = connection.execute("DELETE FROM glossary_entries WHERE id = ?", (entry_id,))
+            if cursor.rowcount == 0:
+                raise KeyError(f"Unknown glossary entry: {entry_id}")
+
+    @contextmanager
+    def _connect(self) -> Iterator[sqlite3.Connection]:
+        connection = sqlite3.connect(self.database_path, timeout=5)
+        try:
+            connection.row_factory = sqlite3.Row
+            connection.execute("PRAGMA foreign_keys = ON")
+            connection.execute("PRAGMA journal_mode = WAL")
+            connection.execute("PRAGMA busy_timeout = 5000")
+            with connection:
+                yield connection
+        finally:
+            connection.close()
+
+    @staticmethod
+    def _validate_values(
+        canonical_term: str, category: str, aliases: Iterable[str]
+    ) -> tuple[str, tuple[str, ...]]:
+        canonical = canonical_term.strip()
+        if not canonical:
+            raise ValueError("Canonical term is required.")
+        if category not in GLOSSARY_CATEGORIES:
+            raise ValueError(f"Unsupported glossary category: {category}")
+        normalized_aliases = tuple(
+            dict.fromkeys(alias.strip() for alias in aliases if alias.strip())
+        )
+        folded = [alias.casefold() for alias in normalized_aliases]
+        if len(folded) != len(set(folded)) or canonical.casefold() in folded:
+            raise GlossaryConflictError(
+                "Aliases must be unique and differ from the canonical term."
+            )
+        return canonical, normalized_aliases
+
+    @staticmethod
+    def _ensure_terms_available(
+        connection: sqlite3.Connection,
+        canonical: str,
+        aliases: tuple[str, ...],
+        *,
+        excluding_entry_id: int | None = None,
+    ) -> None:
+        terms = (canonical, *aliases)
+        placeholders = ", ".join("?" for _ in terms)
+        exclusion = "AND entry_id != ?" if excluding_entry_id is not None else ""
+        alias_parameters: list[object] = [*terms]
+        if excluding_entry_id is not None:
+            alias_parameters.append(excluding_entry_id)
+        alias_conflict = connection.execute(
+            f"SELECT 1 FROM glossary_aliases WHERE alias IN ({placeholders}) {exclusion} LIMIT 1",  # noqa: S608
+            alias_parameters,
+        ).fetchone()
+        entry_exclusion = "AND id != ?" if excluding_entry_id is not None else ""
+        entry_parameters: list[object] = [*terms]
+        if excluding_entry_id is not None:
+            entry_parameters.append(excluding_entry_id)
+        canonical_conflict = connection.execute(
+            f"SELECT 1 FROM glossary_entries WHERE canonical_term IN ({placeholders}) "  # noqa: S608
+            f"{entry_exclusion} LIMIT 1",
+            entry_parameters,
+        ).fetchone()
+        if alias_conflict or canonical_conflict:
+            raise GlossaryConflictError("Canonical term or alias already exists.")
+
+    @staticmethod
+    def _to_entry(connection: sqlite3.Connection, row: sqlite3.Row) -> GlossaryEntry:
+        aliases = connection.execute(
+            "SELECT alias FROM glossary_aliases WHERE entry_id = ? ORDER BY alias COLLATE NOCASE",
+            (row["id"],),
+        ).fetchall()
+        return GlossaryEntry(
+            id=row["id"],
+            canonical_term=row["canonical_term"],
+            category=row["category"],
+            description=row["description"],
+            is_active=bool(row["is_active"]),
+            aliases=tuple(alias["alias"] for alias in aliases),
+            created_at=row["created_at"],
+            updated_at=row["updated_at"],
+        )
+
+
+def render_glossary_terms(entries: Iterable[GlossaryEntry]) -> list[str]:
+    """Render concise canonical terms with recognition aliases for Meeting Context."""
+    rendered = []
+    for entry in entries:
+        item = entry.canonical_term
+        if entry.aliases:
+            item += f" (aliases: {', '.join(entry.aliases)})"
+        rendered.append(item)
+    return rendered
+
+
+def _timestamp() -> str:
+    return datetime.now(UTC).isoformat(timespec="seconds")
+
+
+def _optional_text(value: str | None) -> str | None:
+    stripped = value.strip() if value else ""
+    return stripped or None

src/mka/application/meeting_service.py

@@ -12,7 +12,10 @@ from pathlib import Path
 from typing import Any, Protocol
 from uuid import uuid4
 
+import yaml
+
 from mka.application.config import AppSettings
+from mka.application.glossary import GlossaryRepository, render_glossary_terms
 
 STAGES = ("preparing", "transcription", "diarization", "protocol_generation")
 
@@ -31,6 +34,14 @@ class MeetingLabPort(Protocol):
         progress_sink: Callable[[Any], None],
     ) -> Any: ...
 
+    def regenerate_protocol(
+        self,
+        run_dir: Path,
+        meeting_context: Any,
+        progress_sink: Callable[[Any], None],
+        **options: Any,
+    ) -> Any: ...
+
 
 @dataclass(frozen=True)
 class MeetingDetails:
@@ -73,6 +84,20 @@ class ProcessingOutcome:
     protocol_path: Path | None
     failed_stage: str | None = None
     error_message: str | None = None
+    speaker_attribution_available: bool | None = None
+
+
+@dataclass(frozen=True)
+class SpeakerReview:
+    speaker_label: str
+    excerpts: tuple[str, ...]
+
+
+@dataclass(frozen=True)
+class SpeakerMappingReview:
+    speakers: tuple[SpeakerReview, ...]
+    participants: tuple[tuple[str, str], ...]
+    current_mappings: dict[str, str]
 
 
 def stable_id(value: str) -> str:
@@ -84,9 +109,16 @@ def stable_id(value: str) -> str:
 class MeetingProcessingService:
     """Translate UI input into Meeting Lab calls and persisted artifacts."""
 
-    def __init__(self, settings: AppSettings, meeting_lab: MeetingLabPort) -> None:
+    def __init__(
+        self,
+        settings: AppSettings,
+        meeting_lab: MeetingLabPort,
+        glossary: GlossaryRepository | None = None,
+    ) -> None:
         self.settings = settings
         self.meeting_lab = meeting_lab
+        self.glossary = glossary or GlossaryRepository(settings.glossary_database)
+        self.glossary.initialize()
 
     def build_context(
         self,
@@ -154,6 +186,7 @@ class MeetingProcessingService:
                 "mentioned_people_are_not_participants": True,
             },
         }
+        self._apply_glossary(data)
         return self.meeting_lab.create_context(data)
 
     def preserve_upload(self, meeting_id: str, filename: str, source: Any) -> Path:
@@ -253,8 +286,164 @@ class MeetingProcessingService:
             run_dir=result.run_dir,
             original_protocol=protocol_path.read_text(encoding="utf-8"),
             protocol_path=protocol_path,
+            speaker_attribution_available=self._speaker_attribution_available(result.run_dir),
         )
 
+    def load_speaker_mapping_review(
+        self,
+        run_dir: Path,
+        *,
+        excerpts_per_speaker: int = 3,
+        minimum_excerpt_characters: int = 20,
+    ) -> SpeakerMappingReview | None:
+        """Load detected labels and small deterministic identification excerpts."""
+        run_dir = Path(run_dir)
+        transcript_path = run_dir / "diarization" / "transcript_diarized.json"
+        context_path = run_dir / "context" / "meeting_context.yaml"
+        if not transcript_path.is_file() or not context_path.is_file():
+            return None
+        transcript = json.loads(transcript_path.read_text(encoding="utf-8-sig"))
+        context_data = yaml.safe_load(context_path.read_text(encoding="utf-8"))
+        if not isinstance(transcript, dict) or not isinstance(context_data, dict):
+            raise ValueError("Existing run contains malformed speaker review artifacts.")
+        segments = transcript.get("segments")
+        if not isinstance(segments, list):
+            raise ValueError("Diarized transcript has no segments list.")
+
+        texts_by_speaker: dict[str, list[str]] = {}
+        short_by_speaker: dict[str, list[str]] = {}
+        for segment in segments:
+            if not isinstance(segment, dict):
+                continue
+            label = segment.get("speaker_id")
+            text = segment.get("text")
+            if (
+                not isinstance(label, str)
+                or not label.startswith("SPEAKER_")
+                or label == "SPEAKER_UNASSIGNED"
+                or not isinstance(text, str)
+                or not text.strip()
+            ):
+                continue
+            normalized = " ".join(text.split())
+            target = (
+                texts_by_speaker
+                if len(normalized) >= minimum_excerpt_characters
+                else short_by_speaker
+            )
+            target.setdefault(label, []).append(normalized)
+
+        labels = sorted(set(texts_by_speaker) | set(short_by_speaker))
+        speakers = []
+        for label in labels:
+            candidates = texts_by_speaker.get(label) or short_by_speaker.get(label, [])
+            speakers.append(SpeakerReview(label, tuple(candidates[:excerpts_per_speaker])))
+        participants = tuple(
+            (participant["participant_id"], participant["display_name"])
+            for participant in context_data.get("participants", [])
+            if isinstance(participant, dict)
+            and isinstance(participant.get("participant_id"), str)
+            and isinstance(participant.get("display_name"), str)
+        )
+        mappings = context_data.get("speaker_mappings")
+        return SpeakerMappingReview(
+            speakers=tuple(speakers),
+            participants=participants,
+            current_mappings=dict(mappings) if isinstance(mappings, dict) else {},
+        )
+
+    def regenerate_protocol(
+        self,
+        run_dir: Path,
+        speaker_mappings: dict[str, str],
+        progress_sink: Callable[[AppProgressEvent], None] | None = None,
+    ) -> ProcessingOutcome:
+        """Persist confirmed mappings and regenerate only the direct protocol."""
+        review = self.load_speaker_mapping_review(run_dir)
+        if review is None:
+            raise ValueError("This run has no diarization artifacts to map.")
+        detected = {speaker.speaker_label for speaker in review.speakers}
+        participant_ids = {participant_id for participant_id, _ in review.participants}
+        unknown_labels = sorted(set(speaker_mappings) - detected)
+        if unknown_labels:
+            raise ValueError(f"Unknown diarization speaker label: {unknown_labels[0]}")
+        unknown_participants = sorted(set(speaker_mappings.values()) - participant_ids)
+        if unknown_participants:
+            raise ValueError(f"Unknown participant ID: {unknown_participants[0]}")
+        assigned_participants = list(speaker_mappings.values())
+        if len(assigned_participants) != len(set(assigned_participants)):
+            raise ValueError("A participant may be assigned to only one speaker label.")
+
+        context_path = Path(run_dir) / "context" / "meeting_context.yaml"
+        context_data = yaml.safe_load(context_path.read_text(encoding="utf-8"))
+        if not isinstance(context_data, dict):
+            raise ValueError("Existing run contains malformed Meeting Context.")
+        context_data["speaker_mappings"] = dict(sorted(speaker_mappings.items()))
+        self._apply_glossary(context_data)
+        context = self.meeting_lab.create_context(context_data)
+
+        def relay(event: Any) -> None:
+            if progress_sink is not None:
+                progress_sink(
+                    AppProgressEvent(
+                        stage=event.stage,
+                        status=event.status,
+                        elapsed_seconds=event.elapsed_seconds,
+                        progress=event.progress,
+                        message=event.message,
+                    )
+                )
+
+        result = self.meeting_lab.regenerate_protocol(
+            Path(run_dir),
+            context,
+            relay,
+            model=self.settings.protocol_model,
+            ollama_endpoint=self.settings.ollama_endpoint,
+            protocol_num_ctx=self.settings.protocol_num_ctx,
+            protocol_safe_input_token_budget=(self.settings.protocol_safe_input_token_budget),
+        )
+        protocol_path = Path(result.protocol_path)
+        return ProcessingOutcome(
+            succeeded=True,
+            run_dir=Path(result.run_dir),
+            original_protocol=protocol_path.read_text(encoding="utf-8"),
+            protocol_path=protocol_path,
+            speaker_attribution_available=self._speaker_attribution_available(result.run_dir),
+        )
+
+    def _apply_glossary(self, context_data: dict[str, Any]) -> None:
+        """Merge active terminology into context without discarding other entities."""
+        glossary_terms = render_glossary_terms(self.glossary.list(active_only=True))
+        known_entities = context_data.setdefault("known_entities", {})
+        if glossary_terms:
+            known_entities["Authoritative terminology"] = glossary_terms
+        else:
+            known_entities.pop("Authoritative terminology", None)
+        rules = context_data.setdefault("context_rules", {})
+        rules["glossary_canonical_spelling"] = (
+            "Use canonical glossary spellings only when the meeting clearly refers to "
+            "those terms; do not invent matches or replace unrelated words."
+        )
+        rules["glossary_core_terms"] = (
+            "Preserve surrounding context and use canonical core terms inside compounds "
+            "where appropriate."
+        )
+
+    @staticmethod
+    def _speaker_attribution_available(run_dir: Path | None) -> bool | None:
+        if run_dir is None:
+            return None
+        metadata_path = Path(run_dir) / "protocol" / "runtime_metadata.json"
+        if not metadata_path.is_file():
+            return None
+        try:
+            metadata = json.loads(metadata_path.read_text(encoding="utf-8"))
+        except (OSError, json.JSONDecodeError):
+            return None
+        value = metadata.get("speaker_attribution_available")
+        return value if isinstance(value, bool) else None
+
     @staticmethod
     def _read_failure(run_dir: Path | None) -> dict[str, str]:
         if run_dir is None:

src/mka/application/run_inputs.py

@@ -0,0 +1,218 @@
+"""Versioned JSON import/export for the user-facing run input form."""
+
+from __future__ import annotations
+
+import json
+from collections.abc import Sequence
+from dataclasses import dataclass
+from datetime import date
+from pathlib import Path
+from typing import Any
+
+from mka.application.meeting_service import ParticipantInput, stable_id
+from mka.application.people_yaml import ATTENDANCE_VALUES, PARTICIPANT_ID_PATTERN
+
+RUN_INPUT_SCHEMA_VERSION = 1
+SUPPORTED_LANGUAGES = frozenset({"de", "en"})
+
+
+class RunInputJsonError(ValueError):
+    """Raised when a run-input JSON document is malformed or unsupported."""
+
+
+@dataclass(frozen=True)
+class RunInputState:
+    """All user-configurable values needed before starting a processing run."""
+
+    title: str
+    description: str
+    language: str
+    meeting_date: date | None
+    participants: tuple[ParticipantInput, ...]
+    audio_normalization: bool
+    diarization_enabled: bool
+    source_file_name: str | None = None
+
+    @classmethod
+    def defaults(cls) -> RunInputState:
+        return cls(
+            title="",
+            description="",
+            language="de",
+            meeting_date=date.today(),
+            participants=(ParticipantInput(participant_id="", display_name=""),),
+            audio_normalization=True,
+            diarization_enabled=False,
+        )
+
+
+def export_run_inputs(state: RunInputState) -> str:
+    """Serialize form state as deterministic, human-readable JSON."""
+    source_file_name = _source_file_name(state.source_file_name)
+    document = {
+        "schema_version": RUN_INPUT_SCHEMA_VERSION,
+        "meeting": {
+            "title": state.title,
+            "description": state.description,
+            "language": state.language,
+            "date": state.meeting_date.isoformat() if state.meeting_date else None,
+            "participants": [
+                {
+                    "participant_id": person.participant_id,
+                    "display_name": person.display_name,
+                    "role": person.role,
+                    "organization": person.organization,
+                    "attendance_status": person.attendance_status,
+                }
+                for person in state.participants
+            ],
+        },
+        "processing": {
+            "audio_normalization": state.audio_normalization,
+            "diarization_enabled": state.diarization_enabled,
+        },
+        "source_file_name": source_file_name,
+    }
+    return json.dumps(document, ensure_ascii=False, indent=2) + "\n"
+
+
+def import_run_inputs(content: str | bytes) -> RunInputState:
+    """Parse supported fields, applying current defaults to omitted optional fields."""
+    try:
+        if isinstance(content, bytes):
+            content = content.decode("utf-8")
+        document = json.loads(content)
+    except (UnicodeDecodeError, json.JSONDecodeError) as exc:
+        raise RunInputJsonError(f"Malformed input JSON: {exc}") from exc
+    if not isinstance(document, dict):
+        raise RunInputJsonError("Input JSON must contain a top-level object.")
+    version = document.get("schema_version")
+    if type(version) is not int or version != RUN_INPUT_SCHEMA_VERSION:
+        raise RunInputJsonError(
+            f"Unsupported input schema_version {version!r}; expected {RUN_INPUT_SCHEMA_VERSION}."
+        )
+
+    defaults = RunInputState.defaults()
+    meeting = _optional_mapping(document, "meeting")
+    processing = _optional_mapping(document, "processing")
+    title = _optional_text(meeting, "title", defaults.title)
+    description = _optional_text(meeting, "description", defaults.description)
+    language = _optional_text(meeting, "language", defaults.language)
+    if language not in SUPPORTED_LANGUAGES:
+        raise RunInputJsonError(f"Unsupported meeting language: {language!r}.")
+    meeting_date = _meeting_date(meeting, defaults.meeting_date)
+    participants = _participants(meeting, defaults.participants)
+    audio_normalization = _optional_bool(
+        processing, "audio_normalization", defaults.audio_normalization
+    )
+    diarization_enabled = _optional_bool(
+        processing, "diarization_enabled", defaults.diarization_enabled
+    )
+    source_file_name = _source_file_name(document.get("source_file_name"))
+    return RunInputState(
+        title=title,
+        description=description,
+        language=language,
+        meeting_date=meeting_date,
+        participants=participants,
+        audio_normalization=audio_normalization,
+        diarization_enabled=diarization_enabled,
+        source_file_name=source_file_name,
+    )
+
+
+def run_input_filename(title: str) -> str:
+    """Build a stable download filename without filesystem-specific characters."""
+    suffix = stable_id(title) if title.strip() else "untitled"
+    return f"meeting-inputs-{suffix}.json"
+
+
+def _optional_mapping(document: dict[str, Any], field: str) -> dict[str, Any]:
+    value = document.get(field, {})
+    if not isinstance(value, dict):
+        raise RunInputJsonError(f"Field {field!r} must be an object.")
+    return value
+
+
+def _optional_text(document: dict[str, Any], field: str, default: str) -> str:
+    value = document.get(field, default)
+    if not isinstance(value, str):
+        raise RunInputJsonError(f"Field {field!r} must be text.")
+    return value
+
+
+def _optional_bool(document: dict[str, Any], field: str, default: bool) -> bool:
+    value = document.get(field, default)
+    if type(value) is not bool:
+        raise RunInputJsonError(f"Field {field!r} must be true or false.")
+    return value
+
+
+def _meeting_date(document: dict[str, Any], default: date | None) -> date | None:
+    if "date" not in document:
+        return default
+    value = document["date"]
+    if value is None:
+        return None
+    if not isinstance(value, str):
+        raise RunInputJsonError("Field 'date' must be an ISO date or null.")
+    try:
+        return date.fromisoformat(value)
+    except ValueError as exc:
+        raise RunInputJsonError("Field 'date' must be a valid ISO date or null.") from exc
+
+
+def _participants(
+    document: dict[str, Any], default: Sequence[ParticipantInput]
+) -> tuple[ParticipantInput, ...]:
+    if "participants" not in document:
+        return tuple(default)
+    entries = document["participants"]
+    if not isinstance(entries, list):
+        raise RunInputJsonError("Field 'participants' must be a list.")
+    people: list[ParticipantInput] = []
+    seen_ids: set[str] = set()
+    for index, entry in enumerate(entries, start=1):
+        if not isinstance(entry, dict):
+            raise RunInputJsonError(f"Participant {index} must be an object.")
+        participant_id = _optional_text(entry, "participant_id", "")
+        display_name = _optional_text(entry, "display_name", "")
+        role = _optional_text(entry, "role", "")
+        organization = _optional_text(entry, "organization", "")
+        attendance = _optional_text(entry, "attendance_status", "present")
+        if bool(participant_id) != bool(display_name):
+            raise RunInputJsonError(
+                f"Participant {index} must provide both participant_id and display_name."
+            )
+        if participant_id and PARTICIPANT_ID_PATTERN.fullmatch(participant_id) is None:
+            raise RunInputJsonError(
+                f"Participant {index} has invalid participant_id {participant_id!r}."
+            )
+        if participant_id in seen_ids:
+            raise RunInputJsonError(f"Duplicate participant_id: {participant_id!r}.")
+        if participant_id:
+            seen_ids.add(participant_id)
+        if attendance not in ATTENDANCE_VALUES:
+            raise RunInputJsonError(
+                f"Participant {index} has invalid attendance_status {attendance!r}."
+            )
+        people.append(
+            ParticipantInput(
+                participant_id=participant_id,
+                display_name=display_name,
+                role=role,
+                organization=organization,
+                attendance_status=attendance,
+            )
+        )
+    return tuple(people)
+
+
+def _source_file_name(value: Any) -> str | None:
+    if value is None:
+        return None
+    if not isinstance(value, str) or not value.strip():
+        raise RunInputJsonError("Field 'source_file_name' must be non-empty text or null.")
+    if Path(value).name != value:
+        raise RunInputJsonError("Field 'source_file_name' must be a filename, not a path.")
+    return value

src/mka/integrations/meeting_lab.py

@@ -18,6 +18,7 @@ class MeetingLabGateway:
             from src.meeting_lab.models.meeting_context import create_meeting_context
             from src.meeting_lab.orchestration.mvp import (
                 MvpMeetingConfig,
+                regenerate_mvp_protocol,
                 run_mvp_meeting,
             )
         except ImportError as exc:
@@ -28,6 +29,7 @@ class MeetingLabGateway:
         self._config_type = MvpMeetingConfig
         self._create_context = create_meeting_context
         self._run_mvp_meeting = run_mvp_meeting
+        self._regenerate_mvp_protocol = regenerate_mvp_protocol
 
     def create_context(self, data: dict[str, Any]) -> Any:
         """Validate structured context through Meeting Lab's domain boundary."""
@@ -49,3 +51,18 @@ class MeetingLabGateway:
             meeting_context=meeting_context,
             progress_sink=progress_sink,
         )
+
+    def regenerate_protocol(
+        self,
+        run_dir: Any,
+        meeting_context: Any,
+        progress_sink: Callable[[Any], None],
+        **options: Any,
+    ) -> Any:
+        """Regenerate protocol artifacts without rerunning media processing."""
+        return self._regenerate_mvp_protocol(
+            run_dir,
+            meeting_context=meeting_context,
+            progress_sink=progress_sink,
+            **options,
+        )

src/mka/ui/streamlit_app.py

@@ -9,6 +9,11 @@ from uuid import uuid4
 import streamlit as st
 
 from mka.application.config import AppSettings, ConfigurationError
+from mka.application.glossary import (
+    GLOSSARY_CATEGORIES,
+    GlossaryConflictError,
+    GlossaryRepository,
+)
 from mka.application.meeting_service import (
     STAGES,
     AppProgressEvent,
@@ -23,6 +28,13 @@ from mka.application.people_yaml import (
     export_people_yaml,
     import_people_yaml,
 )
+from mka.application.run_inputs import (
+    RunInputJsonError,
+    RunInputState,
+    export_run_inputs,
+    import_run_inputs,
+    run_input_filename,
+)
 from mka.integrations.meeting_lab import (
     MeetingLabGateway,
     MeetingLabUnavailableError,
@@ -36,6 +48,87 @@ STAGE_LABELS = {
 }
 
 
+def _parse_aliases(value: str) -> tuple[str, ...]:
+    """Parse one alias per line while tolerating comma-separated input."""
+    return tuple(
+        alias.strip() for line in value.splitlines() for alias in line.split(",") if alias.strip()
+    )
+
+
+def _render_glossary(repository: GlossaryRepository) -> None:
+    """Render simple global glossary CRUD controls."""
+    with st.expander("Terminology glossary", expanded=False):
+        st.caption(
+            "Store canonical core terms and recognition aliases. Compound phrases are "
+            "composed from meeting context during protocol generation."
+        )
+        with st.form("glossary_add"):
+            columns = st.columns(2)
+            canonical = columns[0].text_input("Canonical term")
+            category = columns[1].selectbox("Category", GLOSSARY_CATEGORIES)
+            aliases = st.text_area("Aliases", help="One per line or comma-separated.")
+            description = st.text_area("Optional description")
+            if st.form_submit_button("Add glossary entry"):
+                try:
+                    repository.create(
+                        canonical,
+                        category,
+                        aliases=_parse_aliases(aliases),
+                        description=description,
+                    )
+                except (GlossaryConflictError, ValueError) as exc:
+                    st.error(str(exc))
+                else:
+                    st.success("Glossary entry added.")
+                    st.rerun()
+
+        search = st.text_input("Search glossary")
+        active_only = st.checkbox("Show active entries only")
+        entries = repository.list(search, active_only=active_only)
+        st.caption(f"{len(entries)} glossary entries")
+        for entry in entries:
+            status = "active" if entry.is_active else "inactive"
+            with (
+                st.expander(f"{entry.canonical_term} · {entry.category} · {status}"),
+                st.form(f"glossary_edit_{entry.id}"),
+            ):
+                columns = st.columns(2)
+                edited_canonical = columns[0].text_input("Canonical term", entry.canonical_term)
+                edited_category = columns[1].selectbox(
+                    "Category",
+                    GLOSSARY_CATEGORIES,
+                    index=GLOSSARY_CATEGORIES.index(entry.category),
+                )
+                edited_aliases = st.text_area("Aliases", "\n".join(entry.aliases))
+                edited_description = st.text_area("Optional description", entry.description or "")
+                edited_active = st.checkbox("Active", value=entry.is_active)
+                delete_confirmed = st.checkbox(
+                    "Permanently delete this entry",
+                    help="Prefer clearing Active for normal use.",
+                )
+                action_columns = st.columns(2)
+                save = action_columns[0].form_submit_button("Save changes")
+                delete = action_columns[1].form_submit_button(
+                    "Delete", disabled=not delete_confirmed
+                )
+                try:
+                    if save:
+                        repository.update(
+                            entry.id,
+                            edited_canonical,
+                            edited_category,
+                            aliases=_parse_aliases(edited_aliases),
+                            description=edited_description,
+                            is_active=edited_active,
+                        )
+                        st.rerun()
+                    if delete:
+                        repository.delete(entry.id)
+                        st.rerun()
+                except (GlossaryConflictError, ValueError) as exc:
+                    st.error(str(exc))
+
+
 def _new_participant() -> dict[str, str]:
     return {
         "row_id": uuid4().hex,
@@ -51,6 +144,51 @@ def _initialize_state() -> None:
     st.session_state.setdefault("participants", [_new_participant()])
     st.session_state.setdefault("outcome", None)
     st.session_state.setdefault("edited_protocol", "")
+    st.session_state.setdefault("source_media_widget_generation", 0)
+    _apply_pending_run_inputs()
+    _apply_pending_edited_protocol()
+
+
+def _queue_run_inputs(value: RunInputState) -> None:
+    """Defer form restoration until the beginning of the next Streamlit run."""
+    st.session_state["pending_run_inputs"] = value
+
+
+def _apply_pending_run_inputs() -> None:
+    """Restore imported values before any corresponding widget is instantiated."""
+    value = st.session_state.pop("pending_run_inputs", None)
+    if value is None:
+        return
+    st.session_state.update(
+        {
+            "meeting_title": value.title,
+            "meeting_description": value.description,
+            "meeting_language": value.language,
+            "meeting_has_date": value.meeting_date is not None,
+            "meeting_date": value.meeting_date or date.today(),
+            "participants": _people_to_rows(list(value.participants)),
+            "audio_normalization": value.audio_normalization,
+            "diarization_enabled": value.diarization_enabled,
+            "imported_source_file_name": value.source_file_name,
+            "run_input_import_message": (
+                "Meeting inputs imported. Select the source media before processing."
+            ),
+            "source_media_widget_generation": (
+                st.session_state.get("source_media_widget_generation", 0) + 1
+            ),
+        }
+    )
+
+
+def _apply_pending_edited_protocol() -> None:
+    """Apply a deferred widget value before the widget is instantiated."""
+    if "pending_edited_protocol" in st.session_state:
+        st.session_state["edited_protocol"] = st.session_state.pop("pending_edited_protocol")
+
+
+def _queue_edited_protocol(value: str) -> None:
+    """Defer an edited-protocol widget update until the next Streamlit run."""
+    st.session_state["pending_edited_protocol"] = value
 
 
 def _people_to_rows(people: list[ParticipantInput]) -> list[dict[str, str]]:
@@ -68,6 +206,27 @@ def _people_to_rows(people: list[ParticipantInput]) -> list[dict[str, str]]:
     ]
 
 
+def _render_run_input_import() -> None:
+    """Render import controls before the widgets whose state they restore."""
+    st.subheader("Input configuration")
+    imported_file = st.file_uploader(
+        "Import inputs",
+        type=["json"],
+        key="run_input_import_file",
+        help="Restore form values only; source media is never included.",
+    )
+    if st.button("Import input configuration", disabled=imported_file is None):
+        try:
+            imported = import_run_inputs(imported_file.getvalue())
+        except RunInputJsonError as exc:
+            st.error(str(exc))
+        else:
+            _queue_run_inputs(imported)
+            st.rerun()
+    if message := st.session_state.pop("run_input_import_message", None):
+        st.success(message)
+
+
 def _render_participants() -> list[ParticipantInput]:
     st.subheader("People")
     st.caption("Record whether each relevant person attended or was only mentioned.")
@@ -196,6 +355,13 @@ def _render_result() -> None:
 
     st.success("Processing completed. Review the generated protocol before use.")
     st.caption(f"Run artifacts: {outcome.run_dir}")
+    if outcome.speaker_attribution_available is False:
+        st.warning(
+            "Speaker attribution was unavailable for this protocol because the "
+            "safe-budget fallback removed diarization labels from the prompt."
+        )
+    if message := st.session_state.pop("speaker_mapping_message", None):
+        st.success(message)
     with st.expander("Original generated protocol", expanded=False):
         st.markdown(outcome.original_protocol or "")
     edited = st.text_area(
@@ -208,6 +374,60 @@ def _render_result() -> None:
         path = MeetingProcessingService.save_edited_protocol(outcome.run_dir, edited)
         st.success(f"Saved edited protocol to {path}")
 
+    try:
+        service = MeetingProcessingService(AppSettings.from_environment(), MeetingLabGateway())
+        review = service.load_speaker_mapping_review(outcome.run_dir)
+    except (MeetingLabUnavailableError, OSError, ValueError) as exc:
+        st.warning(f"Speaker mapping is unavailable: {exc}")
+        return
+    if review is None or not review.speakers:
+        return
+
+    st.subheader("Identify diarized speakers")
+    st.caption(
+        "Confirm identities explicitly. Unmapped speakers remain anonymous; "
+        "the diarized source transcript is not modified."
+    )
+    participant_names = dict(review.participants)
+    options = [None, *participant_names]
+    selections: dict[str, str] = {}
+    for speaker in review.speakers:
+        current = review.current_mappings.get(speaker.speaker_label)
+        selected = st.selectbox(
+            speaker.speaker_label,
+            options=options,
+            index=options.index(current) if current in options else 0,
+            format_func=lambda value, names=participant_names: (
+                "Unmapped / Unknown" if value is None else names[value]
+            ),
+            key=f"speaker_mapping_{outcome.run_dir.name}_{speaker.speaker_label}",
+        )
+        if selected is not None:
+            selections[speaker.speaker_label] = selected
+        for excerpt in speaker.excerpts:
+            st.caption(f"“{excerpt}”")
+
+    duplicate_assignments = len(selections.values()) != len(set(selections.values()))
+    if duplicate_assignments:
+        st.error("Each participant can be assigned to only one detected speaker.")
+    if st.button(
+        "Regenerate protocol with confirmed speakers",
+        disabled=duplicate_assignments,
+        type="primary",
+    ):
+        try:
+            with st.spinner("Regenerating protocol without rerunning audio processing..."):
+                regenerated = service.regenerate_protocol(outcome.run_dir, selections)
+        except (OSError, RuntimeError, ValueError) as exc:
+            st.error(f"Protocol regeneration failed: {exc}")
+        else:
+            st.session_state.outcome = regenerated
+            _queue_edited_protocol(regenerated.original_protocol or "")
+            st.session_state.speaker_mapping_message = (
+                "Speaker mappings saved and protocol regenerated."
+            )
+            st.rerun()
+
 
 def main() -> None:
     st.set_page_config(page_title="Meeting Assistant", layout="wide")
@@ -215,15 +435,36 @@ def main() -> None:
     st.title("Meeting Assistant")
     st.caption("Create meeting context, run Meeting Lab, and review the protocol.")
 
+    settings = AppSettings.from_environment()
+    glossary = GlossaryRepository(settings.glossary_database)
+    glossary.initialize()
+    _render_glossary(glossary)
+
+    _render_run_input_import()
+
     st.header("Meeting and audio")
-    audio = st.file_uploader("Audio recording", type=["wav", "flac", "m4a"])
-    title = st.text_input("Meeting title")
-    description = st.text_area("Description / context", height=100)
+    audio = st.file_uploader(
+        "Audio recording",
+        type=["wav", "flac", "m4a"],
+        key=f"source_media_{st.session_state.source_media_widget_generation}",
+    )
+    imported_source_name = st.session_state.get("imported_source_file_name")
+    if audio is None and imported_source_name:
+        st.caption(
+            f"Previous source filename: {imported_source_name}. "
+            "Select the media file again before processing."
+        )
+    title = st.text_input("Meeting title", key="meeting_title")
+    description = st.text_area("Description / context", height=100, key="meeting_description")
     metadata_columns = st.columns(3)
-    language = metadata_columns[0].selectbox("Meeting language", options=["de", "en"])
-    has_date = metadata_columns[1].checkbox("Meeting date is known", value=True)
+    language = metadata_columns[0].selectbox(
+        "Meeting language", options=["de", "en"], key="meeting_language"
+    )
+    has_date = metadata_columns[1].checkbox(
+        "Meeting date is known", value=True, key="meeting_has_date"
+    )
     selected_date: date | None = (
-        metadata_columns[2].date_input("Meeting date") if has_date else None
+        metadata_columns[2].date_input("Meeting date", key="meeting_date") if has_date else None
     )
 
     participants = _render_participants()
@@ -232,6 +473,7 @@ def main() -> None:
     audio_normalization = st.checkbox(
         "Audio normalization",
         value=True,
+        key="audio_normalization",
         help=(
             "Normalize speech loudness during preparation. WAV, FLAC, and M4A "
             "are always converted to the canonical Meeting Lab audio format, "
@@ -240,9 +482,28 @@ def main() -> None:
     )
     diarization_enabled = st.checkbox(
         "Enable speaker diarization",
+        key="diarization_enabled",
         help="Speaker labels remain anonymous; identities are never inferred.",
     )
 
+    current_inputs = RunInputState(
+        title=title,
+        description=description,
+        language=language,
+        meeting_date=selected_date,
+        participants=tuple(participants),
+        audio_normalization=audio_normalization,
+        diarization_enabled=diarization_enabled,
+        source_file_name=(audio.name if audio is not None else imported_source_name),
+    )
+    st.download_button(
+        "Export inputs",
+        data=export_run_inputs(current_inputs).encode("utf-8"),
+        file_name=run_input_filename(title),
+        mime="application/json",
+        help="Download the current form configuration without source media or run results.",
+    )
+
     if st.button("Start processing", type="primary", disabled=audio is None):
         if not title.strip():
             st.error("Meeting title is required.")
@@ -252,9 +513,8 @@ def main() -> None:
         ):
             st.error("Every person row needs a name and participant ID.")
         else:
-            settings = AppSettings.from_environment()
             try:
-                service = MeetingProcessingService(settings, MeetingLabGateway())
+                service = MeetingProcessingService(settings, MeetingLabGateway(), glossary)
                 meeting = MeetingDetails(
                     title=title,
                     language=language,

tests/test_application_config.py

@@ -39,6 +39,14 @@ def test_environment_defaults_to_no_diarization_container_args(monkeypatch) -> N
     settings = AppSettings.from_environment()
 
     assert settings.diarization_container_args == ()
+    assert settings.glossary_database == Path("data/database/glossary.sqlite3")
+
+
+def test_environment_configures_glossary_database(monkeypatch, tmp_path: Path) -> None:
+    database = tmp_path / "terms.sqlite3"
+    monkeypatch.setenv("MKA_GLOSSARY_DATABASE", str(database))
+
+    assert AppSettings.from_environment().glossary_database == database
 
 
 def test_environment_parses_multiple_ordered_container_args(monkeypatch) -> None:

tests/test_glossary.py

@@ -0,0 +1,78 @@
+import sqlite3
+from pathlib import Path
+
+import pytest
+
+from mka.application.glossary import GlossaryConflictError, GlossaryRepository
+
+
+def repository(tmp_path: Path) -> GlossaryRepository:
+    result = GlossaryRepository(tmp_path / "database" / "glossary.sqlite3")
+    result.initialize()
+    return result
+
+
+def test_initialization_creates_empty_versioned_database(tmp_path: Path) -> None:
+    glossary = repository(tmp_path)
+
+    assert glossary.database_path.is_file()
+    assert glossary.list() == []
+    with sqlite3.connect(glossary.database_path) as connection:
+        assert connection.execute("PRAGMA user_version").fetchone()[0] == 1
+        tables = {
+            row[0]
+            for row in connection.execute("SELECT name FROM sqlite_master WHERE type = 'table'")
+        }
+    assert {"glossary_entries", "glossary_aliases"} <= tables
+
+
+def test_create_read_update_and_deactivate_with_multiple_aliases(tmp_path: Path) -> None:
+    glossary = repository(tmp_path)
+    created = glossary.create(
+        "Secugrid HS",
+        "product",
+        aliases=("Sikirgut", "Secugrid H S"),
+        description="Canonical core product name",
+    )
+
+    assert glossary.get(created.id).aliases == ("Secugrid H S", "Sikirgut")
+    assert glossary.list("sikir")[0].canonical_term == "Secugrid HS"
+
+    updated = glossary.update(
+        created.id,
+        "Secugrid HS",
+        "technical_term",
+        aliases=("Sekugrid HS",),
+        description="Updated",
+        is_active=False,
+    )
+
+    assert updated.category == "technical_term"
+    assert updated.aliases == ("Sekugrid HS",)
+    assert not updated.is_active
+    assert glossary.list(active_only=True) == []
+
+
+def test_terms_and_aliases_are_unique_case_insensitively_across_entries(
+    tmp_path: Path,
+) -> None:
+    glossary = repository(tmp_path)
+    glossary.create("PBAT", "acronym", aliases=("Polybutylene adipate terephthalate",))
+
+    with pytest.raises(GlossaryConflictError):
+        glossary.create("pbat", "material")
+    with pytest.raises(GlossaryConflictError):
+        glossary.create("Other", "other", aliases=("PBAT",))
+    with pytest.raises(GlossaryConflictError):
+        glossary.create("Polybutylene adipate terephthalate", "material")
+
+
+def test_delete_removes_entry_and_aliases(tmp_path: Path) -> None:
+    glossary = repository(tmp_path)
+    entry = glossary.create("Luminy", "product", aliases=("Lumini",))
+
+    glossary.delete(entry.id)
+
+    assert glossary.list() == []
+    with sqlite3.connect(glossary.database_path) as connection:
+        assert connection.execute("SELECT COUNT(*) FROM glossary_aliases").fetchone()[0] == 0

tests/test_meeting_service.py

@@ -5,6 +5,8 @@ from pathlib import Path
 from types import SimpleNamespace
 from typing import Any
 
+import pytest
+
 from mka.application.config import AppSettings
 from mka.application.meeting_service import (
     MeetingDetails,
@@ -29,6 +31,7 @@ class FakeMeetingLab:
         self.context_data: dict[str, Any] | None = None
         self.config_values: dict[str, Any] | None = None
         self.fail = False
+        self.regeneration: dict[str, Any] | None = None
 
     def create_context(self, data: dict[str, Any]) -> FakeContext:
         self.context_data = data
@@ -99,6 +102,36 @@ class FakeMeetingLab:
         protocol.write_text("# Generated protocol\n", encoding="utf-8")
         return SimpleNamespace(exit_code=0, run_dir=self.run_dir, protocol_path=protocol)
 
+    def regenerate_protocol(
+        self,
+        run_dir: Path,
+        meeting_context: Any,
+        progress_sink: Any,
+        **options: Any,
+    ) -> Any:
+        self.regeneration = {
+            "run_dir": run_dir,
+            "meeting_context": meeting_context,
+            "options": options,
+        }
+        progress_sink(
+            SimpleNamespace(
+                stage="protocol_generation",
+                status="started",
+                elapsed_seconds=0.0,
+                progress=None,
+                message=None,
+            )
+        )
+        protocol = Path(run_dir) / "protocol.md"
+        protocol.write_text("# Regenerated protocol\n", encoding="utf-8")
+        protocol_dir = Path(run_dir) / "protocol"
+        protocol_dir.mkdir(exist_ok=True)
+        (protocol_dir / "runtime_metadata.json").write_text(
+            json.dumps({"speaker_attribution_available": True}), encoding="utf-8"
+        )
+        return SimpleNamespace(exit_code=0, run_dir=run_dir, protocol_path=protocol)
+
 
 def make_service(tmp_path: Path) -> tuple[MeetingProcessingService, FakeMeetingLab]:
     model = tmp_path / "model.bin"
@@ -107,6 +140,7 @@ def make_service(tmp_path: Path) -> tuple[MeetingProcessingService, FakeMeetingL
     settings = AppSettings(
         data_root=tmp_path / "meetings",
         whisper_model=model,
+        glossary_database=tmp_path / "glossary.sqlite3",
         whisper_executable="/opt/whisper-cli",
         protocol_model="test:model",
         diarization_mode="gpu",
@@ -139,6 +173,60 @@ def participants() -> list[ParticipantInput]:
     ]
 
 
+def write_speaker_review_artifacts(run_dir: Path) -> Path:
+    diarization_dir = run_dir / "diarization"
+    context_dir = run_dir / "context"
+    diarization_dir.mkdir(parents=True)
+    context_dir.mkdir()
+    transcript_path = diarization_dir / "transcript_diarized.json"
+    transcript_path.write_text(
+        json.dumps(
+            {
+                "speaker_labels_anonymous": True,
+                "segments": [
+                    {
+                        "speaker_id": "SPEAKER_01",
+                        "text": "I will prepare all raw materials before Wednesday.",
+                    },
+                    {"speaker_id": "SPEAKER_00", "text": "Yes."},
+                    {
+                        "speaker_id": "SPEAKER_00",
+                        "text": "We will run the production trial on Wednesday.",
+                    },
+                    {
+                        "speaker_id": "SPEAKER_00",
+                        "text": "The trial requires the complete production team.",
+                    },
+                    {"speaker_id": None, "text": "Unassigned text."},
+                ],
+            }
+        ),
+        encoding="utf-8",
+    )
+    (context_dir / "meeting_context.yaml").write_text(
+        json.dumps(
+            {
+                "schema_version": "1",
+                "meeting": {
+                    "meeting_id": "speaker-review",
+                    "title": "Speaker review",
+                    "language": "en",
+                },
+                "participants": [
+                    {"participant_id": "martin", "display_name": "Martin"},
+                    {"participant_id": "anna", "display_name": "Anna"},
+                ],
+                "speaker_mappings": {},
+                "mentioned_people": [],
+                "organization": {"departments": []},
+                "known_entities": {},
+            }
+        ),
+        encoding="utf-8",
+    )
+    return transcript_path
+
+
 def test_build_context_uses_actual_v1_shape(tmp_path: Path) -> None:
     service, gateway = make_service(tmp_path)
 
@@ -171,6 +259,40 @@ def test_build_context_preserves_explicit_speaker_mapping(tmp_path: Path) -> Non
     assert gateway.context_data["speaker_mappings"] == {"SPEAKER_00": "martin"}
 
 
+def test_build_context_includes_only_active_authoritative_glossary_terms(
+    tmp_path: Path,
+) -> None:
+    service, gateway = make_service(tmp_path)
+    service.glossary.create("Secugrid HS", "product", aliases=("Sikirgut", "Secugrid H S"))
+    inactive = service.glossary.create("Old Name", "other")
+    service.glossary.set_active(inactive.id, False)
+
+    service.build_context(meeting(), participants())
+
+    assert gateway.context_data is not None
+    assert gateway.context_data["known_entities"] == {
+        "Authoritative terminology": ["Secugrid HS (aliases: Secugrid H S, Sikirgut)"]
+    }
+    rules = gateway.context_data["context_rules"]
+    assert "do not invent matches" in rules["glossary_canonical_spelling"]
+    assert "inside compounds" in rules["glossary_core_terms"]
+    assert "Old Name" not in str(gateway.context_data)
+
+
+def test_glossary_is_rendered_into_meeting_lab_protocol_context(tmp_path: Path) -> None:
+    meeting_context = pytest.importorskip("src.meeting_lab.models.meeting_context")
+    service, gateway = make_service(tmp_path)
+    service.glossary.create("PBAT", "acronym", aliases=("P B A T",))
+    context = service.build_context(meeting(), participants())
+
+    real_context = meeting_context.create_meeting_context(context.data)
+    prompt_context = meeting_context.render_meeting_context_for_prompt(real_context)
+
+    assert "Authoritative terminology: PBAT (aliases: P B A T)" in prompt_context
+    assert "Use canonical glossary spellings" in prompt_context
+    assert "use canonical core terms inside compounds" in prompt_context
+
+
 def test_build_context_translates_mentioned_only_person(tmp_path: Path) -> None:
     service, gateway = make_service(tmp_path)
     people = participants() + [
@@ -331,6 +453,96 @@ def test_failure_reports_stage_and_preserves_run_dir(tmp_path: Path) -> None:
     assert (gateway.run_dir / "run_metadata.json").is_file()
 
 
+def test_speaker_review_lists_detected_labels_participants_and_excerpts(
+    tmp_path: Path,
+) -> None:
+    service, gateway = make_service(tmp_path)
+    source = write_speaker_review_artifacts(gateway.run_dir)
+
+    review = service.load_speaker_mapping_review(gateway.run_dir, excerpts_per_speaker=2)
+
+    assert review is not None
+    assert [speaker.speaker_label for speaker in review.speakers] == [
+        "SPEAKER_00",
+        "SPEAKER_01",
+    ]
+    assert review.speakers[0].excerpts == (
+        "We will run the production trial on Wednesday.",
+        "The trial requires the complete production team.",
+    )
+    assert review.participants == (("martin", "Martin"), ("anna", "Anna"))
+    assert review.current_mappings == {}
+    assert "SPEAKER_00" in source.read_text(encoding="utf-8")
+
+
+def test_protocol_only_regeneration_persists_mappings_without_rewriting_transcript(
+    tmp_path: Path,
+) -> None:
+    service, gateway = make_service(tmp_path)
+    service.glossary.create("ENLYZE", "organization", aliases=("Enlyse",))
+    source = write_speaker_review_artifacts(gateway.run_dir)
+    original_source = source.read_bytes()
+    events = []
+
+    outcome = service.regenerate_protocol(
+        gateway.run_dir,
+        {"SPEAKER_00": "martin"},
+        progress_sink=events.append,
+    )
+
+    assert outcome.succeeded
+    assert outcome.original_protocol == "# Regenerated protocol\n"
+    assert outcome.speaker_attribution_available is True
+    assert gateway.context_data is not None
+    assert gateway.context_data["speaker_mappings"] == {"SPEAKER_00": "martin"}
+    assert gateway.context_data["known_entities"] == {
+        "Authoritative terminology": ["ENLYZE (aliases: Enlyse)"]
+    }
+    assert gateway.regeneration is not None
+    assert gateway.regeneration["meeting_context"].data["speaker_mappings"] == {
+        "SPEAKER_00": "martin"
+    }
+    assert gateway.regeneration["options"]["protocol_num_ctx"] == 32_768
+    assert events[0].stage == "protocol_generation"
+    assert source.read_bytes() == original_source
+
+
+def test_protocol_regeneration_allows_unmapped_and_rejects_duplicate_participant(
+    tmp_path: Path,
+) -> None:
+    service, gateway = make_service(tmp_path)
+    write_speaker_review_artifacts(gateway.run_dir)
+
+    outcome = service.regenerate_protocol(gateway.run_dir, {})
+
+    assert outcome.succeeded
+    assert gateway.context_data is not None
+    assert gateway.context_data["speaker_mappings"] == {}
+
+    with pytest.raises(ValueError, match="only one speaker"):
+        service.regenerate_protocol(
+            gateway.run_dir,
+            {"SPEAKER_00": "martin", "SPEAKER_01": "martin"},
+        )
+
+
+def test_fallback_attribution_loss_is_read_from_runtime_metadata(tmp_path: Path) -> None:
+    run_dir = tmp_path / "run"
+    protocol_dir = run_dir / "protocol"
+    protocol_dir.mkdir(parents=True)
+    (protocol_dir / "runtime_metadata.json").write_text(
+        json.dumps(
+            {
+                "speaker_attribution_available": False,
+                "speaker_attribution_loss_reason": "plain_transcript_fallback",
+            }
+        ),
+        encoding="utf-8",
+    )
+
+    assert MeetingProcessingService._speaker_attribution_available(run_dir) is False
+
+
 def test_uploaded_source_is_preserved_in_meeting_directory(tmp_path: Path) -> None:
     service, _ = make_service(tmp_path)
     source = SimpleNamespace(getbuffer=lambda: b"source audio")

tests/test_run_inputs.py

@@ -0,0 +1,136 @@
+import json
+from datetime import date
+
+import pytest
+
+from mka.application.meeting_service import ParticipantInput
+from mka.application.run_inputs import (
+    RunInputJsonError,
+    RunInputState,
+    export_run_inputs,
+    import_run_inputs,
+    run_input_filename,
+)
+
+
+def populated_state() -> RunInputState:
+    return RunInputState(
+        title="F&E Technik Abteilungs Jour Fixe",
+        description="Review the production trial.",
+        language="de",
+        meeting_date=date(2026, 8, 25),
+        participants=(
+            ParticipantInput(
+                participant_id="martin",
+                display_name="Martin Tazl",
+                role="Project lead",
+                organization="Engineering",
+            ),
+            ParticipantInput(
+                participant_id="alex",
+                display_name="Alexander Funk",
+                attendance_status="mentioned_only",
+            ),
+        ),
+        audio_normalization=False,
+        diarization_enabled=True,
+        source_file_name="2026-08-25_jour_fixe.wav",
+    )
+
+
+def test_current_form_state_serializes_with_schema_and_all_supported_values() -> None:
+    document = json.loads(export_run_inputs(populated_state()))
+
+    assert document["schema_version"] == 1
+    assert document["meeting"]["title"] == "F&E Technik Abteilungs Jour Fixe"
+    assert document["meeting"]["description"] == "Review the production trial."
+    assert document["meeting"]["language"] == "de"
+    assert document["meeting"]["date"] == "2026-08-25"
+    assert document["meeting"]["participants"][1] == {
+        "participant_id": "alex",
+        "display_name": "Alexander Funk",
+        "role": "",
+        "organization": "",
+        "attendance_status": "mentioned_only",
+    }
+    assert document["processing"] == {
+        "audio_normalization": False,
+        "diarization_enabled": True,
+    }
+
+
+def test_export_import_round_trip_restores_form_and_participants() -> None:
+    original = populated_state()
+
+    restored = import_run_inputs(export_run_inputs(original))
+
+    assert restored == original
+    assert restored.participants[0].participant_id == "martin"
+    assert restored.participants[0].display_name == "Martin Tazl"
+
+
+def test_missing_optional_fields_use_current_defaults() -> None:
+    restored = import_run_inputs('{"schema_version": 1}')
+
+    defaults = RunInputState.defaults()
+    assert restored == defaults
+
+
+def test_unknown_safe_fields_are_ignored() -> None:
+    restored = import_run_inputs(
+        json.dumps(
+            {
+                "schema_version": 1,
+                "meeting": {"title": "Known", "future_field": {"value": 1}},
+                "processing": {"future_toggle": True},
+                "future_section": [1, 2, 3],
+            }
+        )
+    )
+
+    assert restored.title == "Known"
+
+
+@pytest.mark.parametrize("content", ["not-json", "[]", b"\xff"])
+def test_malformed_json_is_rejected(content: str | bytes) -> None:
+    with pytest.raises(RunInputJsonError, match="Malformed|top-level"):
+        import_run_inputs(content)
+
+
+def test_unsupported_future_schema_is_rejected() -> None:
+    with pytest.raises(RunInputJsonError, match="Unsupported.*schema_version"):
+        import_run_inputs('{"schema_version": 2}')
+
+
+def test_media_contents_are_never_serialized() -> None:
+    exported = export_run_inputs(populated_state())
+
+    assert "2026-08-25_jour_fixe.wav" in exported
+    assert "audio_bytes" not in exported
+    assert "base64" not in exported
+
+
+def test_source_filename_must_not_be_a_machine_specific_path() -> None:
+    with pytest.raises(RunInputJsonError, match="filename, not a path"):
+        import_run_inputs('{"schema_version": 1, "source_file_name": "/tmp/meeting.wav"}')
+
+
+def test_invalid_or_duplicate_participants_are_not_silently_reinterpreted() -> None:
+    document = {
+        "schema_version": 1,
+        "meeting": {
+            "participants": [
+                {"participant_id": "martin", "display_name": "Martin"},
+                {"participant_id": "martin", "display_name": "Someone else"},
+            ]
+        },
+    }
+
+    with pytest.raises(RunInputJsonError, match="Duplicate participant_id"):
+        import_run_inputs(json.dumps(document))
+
+
+def test_export_filename_is_readable_and_machine_independent() -> None:
+    assert run_input_filename("F&E Technik Jour Fixe") == (
+        "meeting-inputs-f-e-technik-jour-fixe.json"
+    )

tests/test_streamlit_app.py

@@ -0,0 +1,68 @@
+from datetime import date
+
+from mka.application.meeting_service import ParticipantInput
+from mka.application.run_inputs import RunInputState
+from mka.ui import streamlit_app
+
+
+def test_alias_input_accepts_lines_and_commas() -> None:
+    assert streamlit_app._parse_aliases("Sikirgut\nSekugrid HS, Secugrid H S") == (
+        "Sikirgut",
+        "Sekugrid HS",
+        "Secugrid H S",
+    )
+
+
+def test_regenerated_protocol_widget_value_is_deferred_until_next_run(
+    monkeypatch,
+) -> None:
+    state = {"edited_protocol": "old protocol"}
+    monkeypatch.setattr(streamlit_app.st, "session_state", state)
+
+    streamlit_app._queue_edited_protocol("regenerated protocol")
+
+    assert state["edited_protocol"] == "old protocol"
+    assert state["pending_edited_protocol"] == "regenerated protocol"
+
+    streamlit_app._apply_pending_edited_protocol()
+
+    assert state["edited_protocol"] == "regenerated protocol"
+    assert "pending_edited_protocol" not in state
+
+
+def test_imported_inputs_are_applied_via_pending_state_before_widgets(
+    monkeypatch,
+) -> None:
+    existing_upload = object()
+    state = {"source_media_0": existing_upload, "source_media_widget_generation": 0}
+    monkeypatch.setattr(streamlit_app.st, "session_state", state)
+    imported = RunInputState(
+        title="Imported meeting",
+        description="Imported context",
+        language="en",
+        meeting_date=date(2026, 8, 25),
+        participants=(ParticipantInput("martin", "Martin"),),
+        audio_normalization=False,
+        diarization_enabled=True,
+        source_file_name="meeting.wav",
+    )
+
+    streamlit_app._queue_run_inputs(imported)
+
+    assert "meeting_title" not in state
+    assert state["pending_run_inputs"] == imported
+
+    streamlit_app._apply_pending_run_inputs()
+
+    assert state["meeting_title"] == "Imported meeting"
+    assert state["meeting_description"] == "Imported context"
+    assert state["meeting_language"] == "en"
+    assert state["meeting_has_date"] is True
+    assert state["participants"][0]["participant_id"] == "martin"
+    assert state["audio_normalization"] is False
+    assert state["diarization_enabled"] is True
+    assert state["imported_source_file_name"] == "meeting.wav"
+    assert state["source_media_widget_generation"] == 1
+    assert "source_media_1" not in state
+    assert "pending_run_inputs" not in state
+    assert state["source_media_0"] is existing_upload