Implement AI orchestration wedding demo

backend/app/memory/context_builder.py

@@ -0,0 +1,33 @@
+from collections import deque
+from typing import Any
+
+from app.domain.schemas import TranscriptChunk
+
+
+class ContextBuilder:
+    """Maintains a Redis-compatible meeting context; uses memory for offline tests."""
+
+    def __init__(self, window_size: int = 12) -> None:
+        self.window_size = window_size
+        self._transcript: deque[TranscriptChunk] = deque(maxlen=window_size)
+        self._participants: set[str] = set()
+        self._recent_decisions: deque[dict[str, Any]] = deque(maxlen=10)
+
+    def add_chunk(self, chunk: TranscriptChunk) -> None:
+        self._transcript.append(chunk)
+        self._participants.add(chunk.speaker)
+
+    def add_decision(self, decision: dict[str, Any]) -> None:
+        self._recent_decisions.append(decision)
+
+    def snapshot(self, app_state: dict[str, Any] | None = None) -> dict[str, Any]:
+        return {
+            "meeting": {"id": "demo-meeting", "title": "Wedding Planning Review"},
+            "participants": sorted(self._participants),
+            "transcript_window": [chunk.model_dump(mode="json") for chunk in self._transcript],
+            "recent_ai_decisions": list(self._recent_decisions),
+            "application_state": app_state or {},
+        }
+
+    def transcript(self) -> list[TranscriptChunk]:
+        return list(self._transcript)