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feat(teamsbot): stop command detection, session context for AI, context summarization for long sessions

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Co-authored-by: Cursor <cursoragent@cursor.com>
This commit is contained in:
patrick-motsch 2026-02-16 09:29:03 +01:00
parent c7d1642f61
commit 4186ec6188
3 changed files with 94 additions and 1 deletions
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2
modules/features/teamsbot/datamodelTeamsbot.py
View file

@ -78,6 +78,7 @@ class TeamsbotSession(BaseModel):
startedByUserId: str = Field(description="User ID who started the session")
bridgeSessionId: Optional[str] = Field(default=None, description="Session ID on the .NET Media Bridge")
meetingChatId: Optional[str] = Field(default=None, description="Teams meeting chat ID for Graph API messages")
sessionContext: Optional[str] = Field(default=None, description="Custom context/knowledge provided by the user for this session")
summary: Optional[str] = Field(default=None, description="AI-generated meeting summary (after session ends)")
errorMessage: Optional[str] = Field(default=None, description="Error message if status is ERROR")
transcriptSegmentCount: int = Field(default=0, description="Number of transcript segments in this session")
@ -200,6 +201,7 @@ class TeamsbotStartSessionRequest(BaseModel):
backgroundImageUrl: Optional[str] = Field(default=None, description="Override background image for this session")
connectionId: Optional[str] = Field(default=None, description="Microsoft connection ID for Graph API access")
joinMode: Optional[TeamsbotJoinMode] = Field(default=None, description="How the bot joins: systemBot, anonymous, or userAccount. Defaults to systemBot if credentials configured, else anonymous.")
sessionContext: Optional[str] = Field(default=None, description="Custom context/knowledge to provide to the bot for this session (e.g. meeting agenda, documents, background info)")
class TeamsbotSessionResponse(BaseModel):

1
modules/features/teamsbot/routeFeatureTeamsbot.py
View file

@ -178,6 +178,7 @@ async def startSession(
meetingLink=cleanMeetingUrl,
botName=body.botName or config.botName,
backgroundImageUrl=body.backgroundImageUrl or config.backgroundImageUrl,
sessionContext=body.sessionContext,
status=TeamsbotSessionStatus.PENDING,
startedByUserId=str(context.user.id),
).model_dump()

92
modules/features/teamsbot/service.py
View file

@ -77,6 +77,8 @@ class TeamsbotService:
# State
self._lastAiCallTime: float = 0.0
self._contextBuffer: List[Dict[str, Any]] = []
self._sessionContext: Optional[str] = None # User-provided background context
self._contextSummary: Optional[str] = None # AI-generated summary of long context
# =========================================================================
# Session Lifecycle
@ -210,6 +212,13 @@ class TeamsbotService:
interface = interfaceDb.getInterface(self.currentUser, self.mandateId, self.instanceId)
voiceInterface = getVoiceInterface(self.currentUser, self.mandateId)
# Load session context (user-provided background knowledge)
session = interface.getSession(sessionId)
if session:
self._sessionContext = session.get("sessionContext")
if self._sessionContext:
logger.info(f"Session {sessionId}: Loaded session context ({len(self._sessionContext)} chars)")
logger.info(f"[WS-DEBUG] WebSocket handler started for session {sessionId}")
try:
@ -323,6 +332,23 @@ class TeamsbotService:
if not text:
return
# Check for STOP command: "<botname> stop" or "<botname> STOP"
# This immediately stops the bot from speaking and clears the audio queue.
botNameLower = self.config.botName.lower()
textLower = text.lower()
if botNameLower in textLower and "stop" in textLower:
logger.info(f"Session {sessionId}: STOP command detected: [{speaker}] {text[:60]}")
if websocket:
try:
await websocket.send_text(json.dumps({
"type": "stopAudio",
"sessionId": sessionId,
}))
except Exception as stopErr:
logger.warning(f"Failed to send stop command: {stopErr}")
# Don't trigger AI analysis for stop commands
return
# Filter out the bot's own speech from AI triggering.
# The bot hears itself via captions — these should be stored in the
# transcript for the record, but must NOT trigger AI analysis (feedback loop).
@ -351,6 +377,10 @@ class TeamsbotService:
# Keep only last N segments
maxSegments = self.config.contextWindowSegments
if len(self._contextBuffer) > maxSegments:
# When buffer overflows, summarize the older half to preserve context
# without losing information. The summary replaces the old segments.
if not self._contextSummary and len(self._contextBuffer) > maxSegments * 1.5:
asyncio.create_task(self._summarizeContextBuffer(sessionId))
self._contextBuffer = self._contextBuffer[-maxSegments:]
# Emit SSE event for live transcript
@ -473,7 +503,17 @@ class TeamsbotService:
else:
contextLines.append(f"[{speaker}]: {text}")
transcriptContext = f"BOT_NAME:{self.config.botName}\n" + "\n".join(contextLines)
# Include session context if provided by the user at session start
sessionContextStr = ""
if self._sessionContext:
sessionContextStr = f"\nSESSION_CONTEXT (background knowledge provided by the user):\n{self._sessionContext}\n"
# Include summary of earlier conversation if available
summaryStr = ""
if self._contextSummary:
summaryStr = f"\nEARLIER_CONVERSATION_SUMMARY:\n{self._contextSummary}\n"
transcriptContext = f"BOT_NAME:{self.config.botName}{sessionContextStr}{summaryStr}\nRECENT_TRANSCRIPT:\n" + "\n".join(contextLines)
# Call SPEECH_TEAMS
try:
@ -633,6 +673,56 @@ class TeamsbotService:
logger.error(f"SPEECH_TEAMS analysis failed for session {sessionId}: {type(e).__name__}: {e}", exc_info=True)
await _emitSessionEvent(sessionId, "error", {"message": f"AI analysis failed: {type(e).__name__}: {str(e)}"})
# =========================================================================
# Context Summarization (for long sessions)
# =========================================================================
async def _summarizeContextBuffer(self, sessionId: str):
"""Summarize the older part of the context buffer to preserve information
without exceeding the context window. This runs in the background."""
try:
if self._contextSummary:
return # Already summarized recently
# Take the older half of the buffer for summarization
halfPoint = len(self._contextBuffer) // 2
oldSegments = self._contextBuffer[:halfPoint]
if len(oldSegments) < 10:
return # Not enough to summarize
# Build text to summarize
lines = []
for seg in oldSegments:
speaker = seg.get("speaker", "Unknown")
text = seg.get("text", "")
lines.append(f"[{speaker}]: {text}")
textToSummarize = "\n".join(lines)
from modules.services.serviceAi.mainServiceAi import AiService
from modules.datamodels.datamodelAi import AiCallRequest, AiCallOptions, OperationTypeEnum, PriorityEnum
serviceContext = _ServiceContext(self.currentUser, self.mandateId, self.instanceId)
aiService = AiService(serviceCenter=serviceContext)
await aiService.ensureAiObjectsInitialized()
request = AiCallRequest(
prompt="Fasse das folgende Meeting-Transkript in 3-5 Saetzen zusammen. Nenne die wichtigsten Themen, Entscheidungen und offene Fragen. Antworte NUR mit der Zusammenfassung, keine Erklaerungen.",
context=textToSummarize,
options=AiCallOptions(
operationType=OperationTypeEnum.DATA_ANALYSE,
priority=PriorityEnum.SPEED,
)
)
response = await aiService.callAi(request)
if response and response.errorCount == 0:
self._contextSummary = response.content.strip()
logger.info(f"Session {sessionId}: Context summarized ({len(oldSegments)} segments -> {len(self._contextSummary)} chars)")
except Exception as e:
logger.warning(f"Context summarization failed for session {sessionId}: {e}")
# =========================================================================
# Meeting Summary
# =========================================================================