chore(main): release 0.23.0 (#770)

* Ignore act secrets

* Deploy frontend container to ECR

* Use published image

* Remove ecr workflows

* Trigger coolify deployment

* Deploy on release please pr merge

* Upgrade nextjs

* Update secrets example

.github/workflows/deploy.yml

@@ -1,90 +0,0 @@
-name: Build container/push to container registry
-
-on: [workflow_dispatch]
-
-env:
-  # 950402358378.dkr.ecr.us-east-1.amazonaws.com/reflector
-  AWS_REGION: us-east-1
-  ECR_REPOSITORY: reflector
-
-jobs:
-  build:
-    strategy:
-      matrix:
-        include:
-          - platform: linux/amd64
-            runner: linux-amd64
-            arch: amd64
-          - platform: linux/arm64
-            runner: linux-arm64
-            arch: arm64
-
-    runs-on: ${{ matrix.runner }}
-
-    permissions:
-      contents: read
-
-    outputs:
-      registry: ${{ steps.login-ecr.outputs.registry }}
-
-    steps:
-      - uses: actions/checkout@v4
-
-      - name: Configure AWS credentials
-        uses: aws-actions/configure-aws-credentials@v4
-        with:
-          aws-access-key-id: ${{ secrets.AWS_ACCESS_KEY_ID }}
-          aws-secret-access-key: ${{ secrets.AWS_SECRET_ACCESS_KEY }}
-          aws-region: ${{ env.AWS_REGION }}
-
-      - name: Login to Amazon ECR
-        id: login-ecr
-        uses: aws-actions/amazon-ecr-login@v2
-
-      - name: Set up Docker Buildx
-        uses: docker/setup-buildx-action@v3
-
-      - name: Build and push ${{ matrix.arch }}
-        uses: docker/build-push-action@v5
-        with:
-          context: server
-          platforms: ${{ matrix.platform }}
-          push: true
-          tags: ${{ steps.login-ecr.outputs.registry }}/${{ env.ECR_REPOSITORY }}:latest-${{ matrix.arch }}
-          cache-from: type=gha,scope=${{ matrix.arch }}
-          cache-to: type=gha,mode=max,scope=${{ matrix.arch }}
-          github-token: ${{ secrets.GHA_CACHE_TOKEN }}
-          provenance: false
-
-  create-manifest:
-    runs-on: ubuntu-latest
-    needs: [build]
-
-    permissions:
-      deployments: write
-      contents: read
-
-    steps:
-      - name: Configure AWS credentials
-        uses: aws-actions/configure-aws-credentials@v4
-        with:
-          aws-access-key-id: ${{ secrets.AWS_ACCESS_KEY_ID }}
-          aws-secret-access-key: ${{ secrets.AWS_SECRET_ACCESS_KEY }}
-          aws-region: ${{ env.AWS_REGION }}
-
-      - name: Login to Amazon ECR
-        uses: aws-actions/amazon-ecr-login@v2
-
-      - name: Create and push multi-arch manifest
-        run: |
-          # Get the registry URL (since we can't easily access job outputs in matrix)
-          ECR_REGISTRY=$(aws ecr describe-registry --query 'registryId' --output text).dkr.ecr.${{ env.AWS_REGION }}.amazonaws.com
-
-          docker manifest create \
-            $ECR_REGISTRY/${{ env.ECR_REPOSITORY }}:latest \
-            $ECR_REGISTRY/${{ env.ECR_REPOSITORY }}:latest-amd64 \
-            $ECR_REGISTRY/${{ env.ECR_REPOSITORY }}:latest-arm64
-
-          docker manifest push $ECR_REGISTRY/${{ env.ECR_REPOSITORY }}:latest
-
-          echo "✅ Multi-arch manifest pushed: $ECR_REGISTRY/${{ env.ECR_REPOSITORY }}:latest"

.github/workflows/dockerhub-backend.yml

@@ -1,35 +1,39 @@
-name: Build and Push Frontend Docker Image
+name: Build and Push Backend Docker Image (Docker Hub)
 
 on:
-  push:
-    branches:
-      - main
+  pull_request:
+    types:
+      - closed
     paths:
-      - 'www/**'
-      - '.github/workflows/docker-frontend.yml'
+      - "server/**"
+      - ".github/workflows/dockerhub-backend.yml"
   workflow_dispatch:
 
 env:
-  REGISTRY: ghcr.io
-  IMAGE_NAME: ${{ github.repository }}-frontend
+  REGISTRY: docker.io
+  IMAGE_NAME: monadicalsas/reflector-backend
 
 jobs:
   build-and-push:
     runs-on: ubuntu-latest
+    if: |
+      github.event_name == 'workflow_dispatch' ||
+      (github.event.pull_request.merged == true &&
+       startsWith(github.event.pull_request.head.ref, 'release-please--branches--'))
+
     permissions:
       contents: read
-      packages: write
 
     steps:
       - name: Checkout repository
         uses: actions/checkout@v4
 
-      - name: Log in to GitHub Container Registry
+      - name: Log in to Docker Hub
         uses: docker/login-action@v3
         with:
           registry: ${{ env.REGISTRY }}
-          username: ${{ github.actor }}
-          password: ${{ secrets.GITHUB_TOKEN }}
+          username: monadicalsas
+          password: ${{ secrets.DOCKERHUB_TOKEN }}
 
       - name: Extract metadata
         id: meta
@@ -47,11 +51,11 @@ jobs:
       - name: Build and push Docker image
         uses: docker/build-push-action@v5
         with:
-          context: ./www
-          file: ./www/Dockerfile
+          context: ./server
+          file: ./server/Dockerfile
           push: true
           tags: ${{ steps.meta.outputs.tags }}
           labels: ${{ steps.meta.outputs.labels }}
           cache-from: type=gha
           cache-to: type=gha,mode=max
-          platforms: linux/amd64,linux/arm64
+          platforms: linux/amd64,linux/arm64

.github/workflows/dockerhub-frontend.yml

@@ -0,0 +1,70 @@
+name: Build and Push Frontend Docker Image
+
+on:
+  pull_request:
+    types:
+      - closed
+    paths:
+      - "www/**"
+      - ".github/workflows/dockerhub-frontend.yml"
+  workflow_dispatch:
+
+env:
+  REGISTRY: docker.io
+  IMAGE_NAME: monadicalsas/reflector-frontend
+
+jobs:
+  build-and-push:
+    runs-on: ubuntu-latest
+    if: |
+      github.event_name == 'workflow_dispatch' ||
+      (github.event.pull_request.merged == true &&
+       startsWith(github.event.pull_request.head.ref, 'release-please--branches--'))
+
+    permissions:
+      contents: read
+
+    steps:
+      - name: Checkout repository
+        uses: actions/checkout@v4
+
+      - name: Log in to Docker Hub
+        uses: docker/login-action@v3
+        with:
+          registry: ${{ env.REGISTRY }}
+          username: monadicalsas
+          password: ${{ secrets.DOCKERHUB_TOKEN }}
+
+      - name: Extract metadata
+        id: meta
+        uses: docker/metadata-action@v5
+        with:
+          images: ${{ env.REGISTRY }}/${{ env.IMAGE_NAME }}
+          tags: |
+            type=ref,event=branch
+            type=sha,prefix={{branch}}-
+            type=raw,value=latest,enable={{is_default_branch}}
+          github-token: ${{ secrets.GITHUB_TOKEN }}
+
+      - name: Set up Docker Buildx
+        uses: docker/setup-buildx-action@v3
+
+      - name: Build and push Docker image
+        uses: docker/build-push-action@v5
+        with:
+          context: ./www
+          file: ./www/Dockerfile
+          push: true
+          tags: ${{ steps.meta.outputs.tags }}
+          labels: ${{ steps.meta.outputs.labels }}
+          cache-from: type=gha
+          cache-to: type=gha,mode=max
+          platforms: linux/amd64,linux/arm64
+
+      - name: Trigger Coolify deployment
+        if: success()
+        run: |
+          curl -X POST "${{ secrets.COOLIFY_WEBHOOK_URL }}" \
+            -H "Content-Type: application/json" \
+            -H "Authorization: Bearer ${{ secrets.COOLIFY_WEBHOOK_TOKEN }}" \
+            -f || (echo "Failed to trigger Coolify deployment" && exit 1)

.gitignore

@@ -18,3 +18,4 @@ CLAUDE.local.md
 www/.env.development
 www/.env.production
 .playwright-mcp
+.secrets

.secrets.example

@@ -0,0 +1,22 @@
+# Example secrets file for GitHub Actions workflows
+# Copy this to .secrets and fill in your values
+# These secrets should be configured in GitHub repository settings:
+# Settings > Secrets and variables > Actions
+
+# DockerHub Configuration (required for frontend and backend deployment)
+# Create a Docker Hub access token at https://hub.docker.com/settings/security
+# Username: monadicalsas
+DOCKERHUB_TOKEN=your-dockerhub-access-token
+
+# GitHub Token (required for frontend and backend deployment)
+# Used by docker/metadata-action for extracting image metadata
+# Can use the default GITHUB_TOKEN or create a personal access token
+GITHUB_TOKEN=your-github-token-or-use-default-GITHUB_TOKEN
+
+# Coolify Deployment Webhook (required for frontend deployment)
+# Used to trigger automatic deployment after image push
+COOLIFY_WEBHOOK_URL=https://app.monadical.io/api/v1/deploy?uuid=your-uuid&force=false
+COOLIFY_WEBHOOK_TOKEN=your-coolify-webhook-token
+
+# Optional: GitHub Actions Cache Token (for local testing with act)
+GHA_CACHE_TOKEN=your-github-token-or-empty

CHANGELOG.md

@@ -1,5 +1,57 @@
 # Changelog
 
+## [0.23.0](https://github.com/Monadical-SAS/reflector/compare/v0.22.4...v0.23.0) (2025-12-10)
+
+
+### Features
+
+* dockerhub ci ([#772](https://github.com/Monadical-SAS/reflector/issues/772)) ([00549f1](https://github.com/Monadical-SAS/reflector/commit/00549f153ade922cf4cb6c5358a7d11a39c426d2))
+* llm retries ([#739](https://github.com/Monadical-SAS/reflector/issues/739)) ([61f0e29](https://github.com/Monadical-SAS/reflector/commit/61f0e29d4c51eab54ee67af92141fbb171e8ccaa))
+
+
+### Bug Fixes
+
+* celery inspect bug sidestep in restart script ([#766](https://github.com/Monadical-SAS/reflector/issues/766)) ([ec17ed7](https://github.com/Monadical-SAS/reflector/commit/ec17ed7b587cf6ee143646baaee67a7c017044d4))
+* deploy frontend to coolify ([#779](https://github.com/Monadical-SAS/reflector/issues/779)) ([91650ec](https://github.com/Monadical-SAS/reflector/commit/91650ec65f65713faa7ee0dcfb75af427b7c4ba0))
+* hide rooms settings instead of disabling ([#763](https://github.com/Monadical-SAS/reflector/issues/763)) ([3ad78be](https://github.com/Monadical-SAS/reflector/commit/3ad78be7628c0d029296b301a0e87236c76b7598))
+* return participant emails from transcript endpoint ([#769](https://github.com/Monadical-SAS/reflector/issues/769)) ([d3a5cd1](https://github.com/Monadical-SAS/reflector/commit/d3a5cd12d2d0d9c32af2d5bd9322e030ef69b85d))
+
+## [0.22.4](https://github.com/Monadical-SAS/reflector/compare/v0.22.3...v0.22.4) (2025-12-02)
+
+
+### Bug Fixes
+
+* Multitrack mixdown optimisation 2 ([#764](https://github.com/Monadical-SAS/reflector/issues/764)) ([bd5df1c](https://github.com/Monadical-SAS/reflector/commit/bd5df1ce2ebf35d7f3413b295e56937a9a28ef7b))
+
+## [0.22.3](https://github.com/Monadical-SAS/reflector/compare/v0.22.2...v0.22.3) (2025-12-02)
+
+
+### Bug Fixes
+
+* align daily room settings ([#759](https://github.com/Monadical-SAS/reflector/issues/759)) ([28f87c0](https://github.com/Monadical-SAS/reflector/commit/28f87c09dc459846873d0dde65b03e3d7b2b9399))
+
+## [0.22.2](https://github.com/Monadical-SAS/reflector/compare/v0.22.1...v0.22.2) (2025-12-02)
+
+
+### Bug Fixes
+
+* daily auto refresh fix ([#755](https://github.com/Monadical-SAS/reflector/issues/755)) ([fe47c46](https://github.com/Monadical-SAS/reflector/commit/fe47c46489c5aa0cc538109f7559cc9accb35c01))
+* Skip mixdown for multitrack ([#760](https://github.com/Monadical-SAS/reflector/issues/760)) ([b51b7aa](https://github.com/Monadical-SAS/reflector/commit/b51b7aa9176c1a53ba57ad99f5e976c804a1e80c))
+
+## [0.22.1](https://github.com/Monadical-SAS/reflector/compare/v0.22.0...v0.22.1) (2025-11-27)
+
+
+### Bug Fixes
+
+* participants update from daily ([#749](https://github.com/Monadical-SAS/reflector/issues/749)) ([7f0b728](https://github.com/Monadical-SAS/reflector/commit/7f0b728991c1b9f9aae702c96297eae63b561ef5))
+
+## [0.22.0](https://github.com/Monadical-SAS/reflector/compare/v0.21.0...v0.22.0) (2025-11-26)
+
+
+### Features
+
+* Multitrack segmentation ([#747](https://github.com/Monadical-SAS/reflector/issues/747)) ([d63040e](https://github.com/Monadical-SAS/reflector/commit/d63040e2fdc07e7b272e85a39eb2411cd6a14798))
+
 ## [0.21.0](https://github.com/Monadical-SAS/reflector/compare/v0.20.0...v0.21.0) (2025-11-26)
 
 

docker-compose.prod.yml

@@ -3,10 +3,7 @@
 
 services:
   web:
-    build:
-      context: ./www
-      dockerfile: Dockerfile
-    image: reflector-frontend:latest
+    image: monadicalsas/reflector-frontend:latest
     environment:
       - KV_URL=${KV_URL:-redis://redis:6379}
       - SITE_URL=${SITE_URL}
@@ -36,4 +33,4 @@ services:
       - redis_data:/data
 
 volumes:
-  redis_data:
+  redis_data:

server/pyproject.toml

@@ -126,6 +126,7 @@ markers = [
 select = [
     "I",       # isort - import sorting
     "F401",    # unused imports
+    "E402",    # module level import not at top of file
     "PLC0415", # import-outside-top-level - detect inline imports
 ]
 

server/reflector/asynctask.py

@@ -1,13 +1,19 @@
 import asyncio
 import functools
+from uuid import uuid4
+
+from celery import current_task
 
 from reflector.db import get_database
+from reflector.llm import llm_session_id
 
 
 def asynctask(f):
     @functools.wraps(f)
     def wrapper(*args, **kwargs):
         async def run_with_db():
+            task_id = current_task.request.id if current_task else None
+            llm_session_id.set(task_id or f"random-{uuid4().hex}")
             database = get_database()
             await database.connect()
             try:

server/reflector/dailyco_api/requests.py

@@ -40,6 +40,10 @@ class RoomProperties(BaseModel):
     )
     enable_chat: bool = Field(default=True, description="Enable in-meeting chat")
     enable_screenshare: bool = Field(default=True, description="Enable screen sharing")
+    enable_knocking: bool = Field(
+        default=False,
+        description="Enable knocking for private rooms (allows participants to request access)",
+    )
     start_video_off: bool = Field(
         default=False, description="Start with video off for all participants"
     )

server/reflector/dailyco_api/responses.py

@@ -68,7 +68,7 @@ class MeetingParticipant(BaseModel):
     Reference: https://docs.daily.co/reference/rest-api/meetings/get-meeting-participants
     """
 
-    user_id: NonEmptyString = Field(description="User identifier")
+    user_id: NonEmptyString | None = Field(None, description="User identifier")
     participant_id: NonEmptyString = Field(description="Participant session identifier")
     user_name: NonEmptyString | None = Field(None, description="User display name")
     join_time: int = Field(description="Join timestamp (Unix epoch seconds)")

server/reflector/db/recordings.py

@@ -35,8 +35,15 @@ class Recording(BaseModel):
     status: Literal["pending", "processing", "completed", "failed"] = "pending"
     meeting_id: str | None = None
     # for multitrack reprocessing
+    # track_keys can be empty list [] if recording finished but no audio was captured (silence/muted)
+    # None means not a multitrack recording, [] means multitrack with no tracks
     track_keys: list[str] | None = None
 
+    @property
+    def is_multitrack(self) -> bool:
+        """True if recording has separate audio tracks (1+ tracks counts as multitrack)."""
+        return self.track_keys is not None and len(self.track_keys) > 0
+
 
 class RecordingController:
     async def create(self, recording: Recording):

server/reflector/db/users.py

@@ -88,5 +88,11 @@ class UserController:
         results = await get_database().fetch_all(query)
         return [User(**r) for r in results]
 
+    @staticmethod
+    async def get_by_ids(user_ids: list[NonEmptyString]) -> dict[str, User]:
+        query = users.select().where(users.c.id.in_(user_ids))
+        results = await get_database().fetch_all(query)
+        return {user.id: User(**user) for user in results}
+
 
 user_controller = UserController()

server/reflector/llm.py

@@ -1,14 +1,29 @@
 import logging
-from typing import Type, TypeVar
+from contextvars import ContextVar
+from typing import Generic, Type, TypeVar
+from uuid import uuid4
 
 from llama_index.core import Settings
 from llama_index.core.output_parsers import PydanticOutputParser
-from llama_index.core.program import LLMTextCompletionProgram
 from llama_index.core.response_synthesizers import TreeSummarize
+from llama_index.core.workflow import (
+    Context,
+    Event,
+    StartEvent,
+    StopEvent,
+    Workflow,
+    step,
+)
 from llama_index.llms.openai_like import OpenAILike
 from pydantic import BaseModel, ValidationError
 
 T = TypeVar("T", bound=BaseModel)
+OutputT = TypeVar("OutputT", bound=BaseModel)
+
+# Session ID for LiteLLM request grouping - set per processing run
+llm_session_id: ContextVar[str | None] = ContextVar("llm_session_id", default=None)
+
+logger = logging.getLogger(__name__)
 
 STRUCTURED_RESPONSE_PROMPT_TEMPLATE = """
 Based on the following analysis, provide the information in the requested JSON format:
@@ -20,6 +35,158 @@ Analysis:
 """
 
 
+class LLMParseError(Exception):
+    """Raised when LLM output cannot be parsed after retries."""
+
+    def __init__(self, output_cls: Type[BaseModel], error_msg: str, attempts: int):
+        self.output_cls = output_cls
+        self.error_msg = error_msg
+        self.attempts = attempts
+        super().__init__(
+            f"Failed to parse {output_cls.__name__} after {attempts} attempts: {error_msg}"
+        )
+
+
+class ExtractionDone(Event):
+    """Event emitted when LLM JSON formatting completes."""
+
+    output: str
+
+
+class ValidationErrorEvent(Event):
+    """Event emitted when validation fails."""
+
+    error: str
+    wrong_output: str
+
+
+class StructuredOutputWorkflow(Workflow, Generic[OutputT]):
+    """Workflow for structured output extraction with validation retry.
+
+    This workflow handles parse/validation retries only. Network error retries
+    are handled internally by Settings.llm (OpenAILike max_retries=3).
+    The caller should NOT wrap this workflow in additional retry logic.
+    """
+
+    def __init__(
+        self,
+        output_cls: Type[OutputT],
+        max_retries: int = 3,
+        **kwargs,
+    ):
+        super().__init__(**kwargs)
+        self.output_cls: Type[OutputT] = output_cls
+        self.max_retries = max_retries
+        self.output_parser = PydanticOutputParser(output_cls)
+
+    @step
+    async def extract(
+        self, ctx: Context, ev: StartEvent | ValidationErrorEvent
+    ) -> StopEvent | ExtractionDone:
+        """Extract structured data from text using two-step LLM process.
+
+        Step 1 (first call only): TreeSummarize generates text analysis
+        Step 2 (every call): Settings.llm.acomplete formats analysis as JSON
+        """
+        current_retries = await ctx.store.get("retries", default=0)
+        await ctx.store.set("retries", current_retries + 1)
+
+        if current_retries >= self.max_retries:
+            last_error = await ctx.store.get("last_error", default=None)
+            logger.error(
+                f"Max retries ({self.max_retries}) reached for {self.output_cls.__name__}"
+            )
+            return StopEvent(result={"error": last_error, "attempts": current_retries})
+
+        if isinstance(ev, StartEvent):
+            # First call: run TreeSummarize to get analysis, store in context
+            prompt = ev.get("prompt")
+            texts = ev.get("texts")
+            tone_name = ev.get("tone_name")
+            if not prompt or not isinstance(texts, list):
+                raise ValueError(
+                    "StartEvent must contain 'prompt' (str) and 'texts' (list)"
+                )
+
+            summarizer = TreeSummarize(verbose=False)
+            analysis = await summarizer.aget_response(
+                prompt, texts, tone_name=tone_name
+            )
+            await ctx.store.set("analysis", str(analysis))
+            reflection = ""
+        else:
+            # Retry: reuse analysis from context
+            analysis = await ctx.store.get("analysis")
+            if not analysis:
+                raise RuntimeError("Internal error: analysis not found in context")
+
+            wrong_output = ev.wrong_output
+            if len(wrong_output) > 2000:
+                wrong_output = wrong_output[:2000] + "... [truncated]"
+            reflection = (
+                f"\n\nYour previous response could not be parsed:\n{wrong_output}\n\n"
+                f"Error:\n{ev.error}\n\n"
+                "Please try again. Return ONLY valid JSON matching the schema above, "
+                "with no markdown formatting or extra text."
+            )
+
+        # Step 2: Format analysis as JSON using LLM completion
+        format_instructions = self.output_parser.format(
+            "Please structure the above information in the following JSON format:"
+        )
+
+        json_prompt = STRUCTURED_RESPONSE_PROMPT_TEMPLATE.format(
+            analysis=analysis,
+            format_instructions=format_instructions + reflection,
+        )
+
+        # Network retries handled by OpenAILike (max_retries=3)
+        response = await Settings.llm.acomplete(json_prompt)
+        return ExtractionDone(output=response.text)
+
+    @step
+    async def validate(
+        self, ctx: Context, ev: ExtractionDone
+    ) -> StopEvent | ValidationErrorEvent:
+        """Validate extracted output against Pydantic schema."""
+        raw_output = ev.output
+        retries = await ctx.store.get("retries", default=0)
+
+        try:
+            parsed = self.output_parser.parse(raw_output)
+            if retries > 1:
+                logger.info(
+                    f"LLM parse succeeded on attempt {retries}/{self.max_retries} "
+                    f"for {self.output_cls.__name__}"
+                )
+            return StopEvent(result={"success": parsed})
+
+        except (ValidationError, ValueError) as e:
+            error_msg = self._format_error(e, raw_output)
+            await ctx.store.set("last_error", error_msg)
+
+            logger.error(
+                f"LLM parse error (attempt {retries}/{self.max_retries}): "
+                f"{type(e).__name__}: {e}\nRaw response: {raw_output[:500]}"
+            )
+
+            return ValidationErrorEvent(
+                error=error_msg,
+                wrong_output=raw_output,
+            )
+
+    def _format_error(self, error: Exception, raw_output: str) -> str:
+        """Format error for LLM feedback."""
+        if isinstance(error, ValidationError):
+            error_messages = []
+            for err in error.errors():
+                field = ".".join(str(loc) for loc in err["loc"])
+                error_messages.append(f"- {err['msg']} in field '{field}'")
+            return "Schema validation errors:\n" + "\n".join(error_messages)
+        else:
+            return f"Parse error: {str(error)}"
+
+
 class LLM:
     def __init__(self, settings, temperature: float = 0.4, max_tokens: int = 2048):
         self.settings_obj = settings
@@ -30,11 +197,12 @@ class LLM:
         self.temperature = temperature
         self.max_tokens = max_tokens
 
-        # Configure llamaindex Settings
         self._configure_llamaindex()
 
     def _configure_llamaindex(self):
         """Configure llamaindex Settings with OpenAILike LLM"""
+        session_id = llm_session_id.get() or f"fallback-{uuid4().hex}"
+
         Settings.llm = OpenAILike(
             model=self.model_name,
             api_base=self.url,
@@ -44,6 +212,7 @@ class LLM:
             is_function_calling_model=False,
             temperature=self.temperature,
             max_tokens=self.max_tokens,
+            additional_kwargs={"extra_body": {"litellm_session_id": session_id}},
         )
 
     async def get_response(
@@ -61,43 +230,25 @@ class LLM:
         output_cls: Type[T],
         tone_name: str | None = None,
     ) -> T:
-        """Get structured output from LLM for non-function-calling models"""
-        logger = logging.getLogger(__name__)
-
-        summarizer = TreeSummarize(verbose=True)
-        response = await summarizer.aget_response(prompt, texts, tone_name=tone_name)
-
-        output_parser = PydanticOutputParser(output_cls)
-
-        program = LLMTextCompletionProgram.from_defaults(
-            output_parser=output_parser,
-            prompt_template_str=STRUCTURED_RESPONSE_PROMPT_TEMPLATE,
-            verbose=False,
+        """Get structured output from LLM with validation retry via Workflow."""
+        workflow = StructuredOutputWorkflow(
+            output_cls=output_cls,
+            max_retries=self.settings_obj.LLM_PARSE_MAX_RETRIES + 1,
+            timeout=120,
         )
 
-        format_instructions = output_parser.format(
-            "Please structure the above information in the following JSON format:"
+        result = await workflow.run(
+            prompt=prompt,
+            texts=texts,
+            tone_name=tone_name,
         )
 
-        try:
-            output = await program.acall(
-                analysis=str(response), format_instructions=format_instructions
+        if "error" in result:
+            error_msg = result["error"] or "Max retries exceeded"
+            raise LLMParseError(
+                output_cls=output_cls,
+                error_msg=error_msg,
+                attempts=result.get("attempts", 0),
             )
-        except ValidationError as e:
-            # Extract the raw JSON from the error details
-            errors = e.errors()
-            if errors and "input" in errors[0]:
-                raw_json = errors[0]["input"]
-                logger.error(
-                    f"JSON validation failed for {output_cls.__name__}. "
-                    f"Full raw JSON output:\n{raw_json}\n"
-                    f"Validation errors: {errors}"
-                )
-            else:
-                logger.error(
-                    f"JSON validation failed for {output_cls.__name__}. "
-                    f"Validation errors: {errors}"
-                )
-            raise
 
-        return output
+        return result["success"]

server/reflector/pipelines/main_file_pipeline.py

@@ -340,7 +340,6 @@ async def task_send_webhook_if_needed(*, transcript_id: str):
 @asynctask
 async def task_pipeline_file_process(*, transcript_id: str):
     """Celery task for file pipeline processing"""
-
     transcript = await transcripts_controller.get_by_id(transcript_id)
     if not transcript:
         raise Exception(f"Transcript {transcript_id} not found")

server/reflector/pipelines/main_multitrack_pipeline.py

@@ -9,7 +9,10 @@ from av.audio.resampler import AudioResampler
 from celery import chain, shared_task
 
 from reflector.asynctask import asynctask
+from reflector.dailyco_api import MeetingParticipantsResponse
 from reflector.db.transcripts import (
+    Transcript,
+    TranscriptParticipant,
     TranscriptStatus,
     TranscriptWaveform,
     transcripts_controller,
@@ -29,7 +32,12 @@ from reflector.processors.audio_waveform_processor import AudioWaveformProcessor
 from reflector.processors.types import TitleSummary
 from reflector.processors.types import Transcript as TranscriptType
 from reflector.storage import Storage, get_transcripts_storage
+from reflector.utils.daily import (
+    filter_cam_audio_tracks,
+    parse_daily_recording_filename,
+)
 from reflector.utils.string import NonEmptyString
+from reflector.video_platforms.factory import create_platform_client
 
 # Audio encoding constants
 OPUS_STANDARD_SAMPLE_RATE = 48000
@@ -414,7 +422,15 @@ class PipelineMainMultitrack(PipelineMainBase):
             # Open all containers with cleanup guaranteed
             for i, url in enumerate(valid_track_urls):
                 try:
-                    c = av.open(url)
+                    c = av.open(
+                        url,
+                        options={
+                            # it's trying to stream from s3 by default
+                            "reconnect": "1",
+                            "reconnect_streamed": "1",
+                            "reconnect_delay_max": "5",
+                        },
+                    )
                     containers.append(c)
                 except Exception as e:
                     self.logger.warning(
@@ -443,6 +459,8 @@ class PipelineMainMultitrack(PipelineMainBase):
                         frame = next(dec)
                     except StopIteration:
                         active[i] = False
+                        # causes stream to move on / unclogs memory
+                        inputs[i].push(None)
                         continue
 
                     if frame.sample_rate != target_sample_rate:
@@ -462,8 +480,6 @@ class PipelineMainMultitrack(PipelineMainBase):
                         mixed.time_base = Fraction(1, target_sample_rate)
                         await writer.push(mixed)
 
-            for in_ctx in inputs:
-                in_ctx.push(None)
             while True:
                 try:
                     mixed = sink.pull()
@@ -494,6 +510,90 @@ class PipelineMainMultitrack(PipelineMainBase):
                 transcript=transcript, event="WAVEFORM", data=waveform
             )
 
+    async def update_participants_from_daily(
+        self, transcript: Transcript, track_keys: list[str]
+    ) -> None:
+        """Update transcript participants with user_id and names from Daily.co API."""
+        if not transcript.recording_id:
+            return
+
+        try:
+            async with create_platform_client("daily") as daily_client:
+                id_to_name = {}
+                id_to_user_id = {}
+
+                try:
+                    rec_details = await daily_client.get_recording(
+                        transcript.recording_id
+                    )
+                    mtg_session_id = rec_details.mtgSessionId
+                    if mtg_session_id:
+                        try:
+                            payload: MeetingParticipantsResponse = (
+                                await daily_client.get_meeting_participants(
+                                    mtg_session_id
+                                )
+                            )
+                            for p in payload.data:
+                                pid = p.participant_id
+                                name = p.user_name
+                                user_id = p.user_id
+                                if name:
+                                    id_to_name[pid] = name
+                                if user_id:
+                                    id_to_user_id[pid] = user_id
+                        except Exception as e:
+                            self.logger.warning(
+                                "Failed to fetch Daily meeting participants",
+                                error=str(e),
+                                mtg_session_id=mtg_session_id,
+                                exc_info=True,
+                            )
+                    else:
+                        self.logger.warning(
+                            "No mtgSessionId found for recording; participant names may be generic",
+                            recording_id=transcript.recording_id,
+                        )
+                except Exception as e:
+                    self.logger.warning(
+                        "Failed to fetch Daily recording details",
+                        error=str(e),
+                        recording_id=transcript.recording_id,
+                        exc_info=True,
+                    )
+                    return
+
+                cam_audio_keys = filter_cam_audio_tracks(track_keys)
+
+                for idx, key in enumerate(cam_audio_keys):
+                    try:
+                        parsed = parse_daily_recording_filename(key)
+                        participant_id = parsed.participant_id
+                    except ValueError as e:
+                        self.logger.error(
+                            "Failed to parse Daily recording filename",
+                            error=str(e),
+                            key=key,
+                            exc_info=True,
+                        )
+                        continue
+
+                    default_name = f"Speaker {idx}"
+                    name = id_to_name.get(participant_id, default_name)
+                    user_id = id_to_user_id.get(participant_id)
+
+                    participant = TranscriptParticipant(
+                        id=participant_id, speaker=idx, name=name, user_id=user_id
+                    )
+                    await transcripts_controller.upsert_participant(
+                        transcript, participant
+                    )
+
+        except Exception as e:
+            self.logger.warning(
+                "Failed to map participant names", error=str(e), exc_info=True
+            )
+
     async def process(self, bucket_name: str, track_keys: list[str]):
         transcript = await self.get_transcript()
         async with self.transaction():
@@ -502,9 +602,12 @@ class PipelineMainMultitrack(PipelineMainBase):
                 {
                     "events": [],
                     "topics": [],
+                    "participants": [],
                 },
             )
 
+        await self.update_participants_from_daily(transcript, track_keys)
+
         source_storage = get_transcripts_storage()
         transcript_storage = source_storage
 

server/reflector/processors/types.py

@@ -1,6 +1,7 @@
 import io
 import re
 import tempfile
+from collections import defaultdict
 from pathlib import Path
 from typing import Annotated, TypedDict
 
@@ -16,6 +17,17 @@ class DiarizationSegment(TypedDict):
 
 
 PUNC_RE = re.compile(r"[.;:?!…]")
+SENTENCE_END_RE = re.compile(r"[.?!…]$")
+
+# Max segment length for words_to_segments() - breaks on any punctuation (. ; : ? ! …)
+# when segment exceeds this limit. Used for non-multitrack recordings.
+MAX_SEGMENT_CHARS = 120
+
+# Max segment length for words_to_segments_by_sentence() - only breaks on sentence-ending
+# punctuation (. ? ! …) when segment exceeds this limit. Higher threshold allows complete
+# sentences in multitrack recordings where speakers overlap.
+# similar number to server/reflector/processors/transcript_liner.py
+MAX_SENTENCE_SEGMENT_CHARS = 1000
 
 
 class AudioFile(BaseModel):
@@ -76,7 +88,6 @@ def words_to_segments(words: list[Word]) -> list[TranscriptSegment]:
     # but separate if the speaker changes, or if the punctuation is a . , ; : ? !
     segments = []
     current_segment = None
-    MAX_SEGMENT_LENGTH = 120
 
     for word in words:
         if current_segment is None:
@@ -106,7 +117,7 @@ def words_to_segments(words: list[Word]) -> list[TranscriptSegment]:
         current_segment.end = word.end
 
         have_punc = PUNC_RE.search(word.text)
-        if have_punc and (len(current_segment.text) > MAX_SEGMENT_LENGTH):
+        if have_punc and (len(current_segment.text) > MAX_SEGMENT_CHARS):
             segments.append(current_segment)
             current_segment = None
 
@@ -116,6 +127,70 @@ def words_to_segments(words: list[Word]) -> list[TranscriptSegment]:
     return segments
 
 
+def words_to_segments_by_sentence(words: list[Word]) -> list[TranscriptSegment]:
+    """Group words by speaker, then split into sentences.
+
+    For multitrack recordings where words from different speakers are interleaved
+    by timestamp, this function first groups all words by speaker, then creates
+    segments based on sentence boundaries within each speaker's words.
+
+    This produces cleaner output than words_to_segments() which breaks on every
+    speaker change, resulting in many tiny segments when speakers overlap.
+    """
+    if not words:
+        return []
+
+    # Group words by speaker, preserving order within each speaker
+    by_speaker: dict[int, list[Word]] = defaultdict(list)
+    for w in words:
+        by_speaker[w.speaker].append(w)
+
+    segments: list[TranscriptSegment] = []
+
+    for speaker, speaker_words in by_speaker.items():
+        current_text = ""
+        current_start: float | None = None
+        current_end: float = 0.0
+
+        for word in speaker_words:
+            if current_start is None:
+                current_start = word.start
+
+            current_text += word.text
+            current_end = word.end
+
+            # Check for sentence end or max length
+            is_sentence_end = SENTENCE_END_RE.search(word.text.strip())
+            is_too_long = len(current_text) >= MAX_SENTENCE_SEGMENT_CHARS
+
+            if is_sentence_end or is_too_long:
+                segments.append(
+                    TranscriptSegment(
+                        text=current_text,
+                        start=current_start,
+                        end=current_end,
+                        speaker=speaker,
+                    )
+                )
+                current_text = ""
+                current_start = None
+
+        # Flush remaining words for this speaker
+        if current_text and current_start is not None:
+            segments.append(
+                TranscriptSegment(
+                    text=current_text,
+                    start=current_start,
+                    end=current_end,
+                    speaker=speaker,
+                )
+            )
+
+    # Sort segments by start time
+    segments.sort(key=lambda s: s.start)
+    return segments
+
+
 class Transcript(BaseModel):
     translation: str | None = None
     words: list[Word] = []
@@ -154,7 +229,9 @@ class Transcript(BaseModel):
             word.start += offset
             word.end += offset
 
-    def as_segments(self) -> list[TranscriptSegment]:
+    def as_segments(self, is_multitrack: bool = False) -> list[TranscriptSegment]:
+        if is_multitrack:
+            return words_to_segments_by_sentence(self.words)
         return words_to_segments(self.words)
 
 

server/reflector/services/transcript_process.py

@@ -160,7 +160,10 @@ def dispatch_transcript_processing(config: ProcessingConfig) -> AsyncResult:
 def task_is_scheduled_or_active(task_name: str, **kwargs):
     inspect = celery.current_app.control.inspect()
 
-    for worker, tasks in (inspect.scheduled() | inspect.active()).items():
+    scheduled = inspect.scheduled() or {}
+    active = inspect.active() or {}
+    all = scheduled | active
+    for worker, tasks in all.items():
         for task in tasks:
             if task["name"] == task_name and task["kwargs"] == kwargs:
                 return True

server/reflector/settings.py

@@ -74,6 +74,10 @@ class Settings(BaseSettings):
     LLM_API_KEY: str | None = None
     LLM_CONTEXT_WINDOW: int = 16000
 
+    LLM_PARSE_MAX_RETRIES: int = (
+        3  # Max retries for JSON/validation errors (total attempts = retries + 1)
+    )
+
     # Diarization
     DIARIZATION_ENABLED: bool = True
     DIARIZATION_BACKEND: str = "modal"

server/reflector/utils/daily.py

@@ -64,6 +64,11 @@ def recording_lock_key(recording_id: NonEmptyString) -> NonEmptyString:
     return f"recording:{recording_id}"
 
 
+def filter_cam_audio_tracks(track_keys: list[str]) -> list[str]:
+    """Filter track keys to cam-audio tracks only (skip screen-audio, etc.)."""
+    return [k for k in track_keys if "cam-audio" in k]
+
+
 def extract_base_room_name(daily_room_name: DailyRoomName) -> NonEmptyString:
     """
     Extract base room name from Daily.co timestamped room name.

server/reflector/utils/transcript_formats.py

@@ -6,9 +6,6 @@ from reflector.db.transcripts import TranscriptParticipant, TranscriptTopic
 from reflector.processors.types import (
     Transcript as ProcessorTranscript,
 )
-from reflector.processors.types import (
-    words_to_segments,
-)
 from reflector.schemas.transcript_formats import TranscriptSegment
 from reflector.utils.webvtt import seconds_to_timestamp
 
@@ -32,7 +29,9 @@ def format_timestamp_mmss(seconds: float | int) -> str:
 
 
 def transcript_to_text(
-    topics: list[TranscriptTopic], participants: list[TranscriptParticipant] | None
+    topics: list[TranscriptTopic],
+    participants: list[TranscriptParticipant] | None,
+    is_multitrack: bool = False,
 ) -> str:
     """Convert transcript topics to plain text with speaker names."""
     lines = []
@@ -41,7 +40,7 @@ def transcript_to_text(
             continue
 
         transcript = ProcessorTranscript(words=topic.words)
-        segments = transcript.as_segments()
+        segments = transcript.as_segments(is_multitrack)
 
         for segment in segments:
             speaker_name = get_speaker_name(segment.speaker, participants)
@@ -52,7 +51,9 @@ def transcript_to_text(
 
 
 def transcript_to_text_timestamped(
-    topics: list[TranscriptTopic], participants: list[TranscriptParticipant] | None
+    topics: list[TranscriptTopic],
+    participants: list[TranscriptParticipant] | None,
+    is_multitrack: bool = False,
 ) -> str:
     """Convert transcript topics to timestamped text with speaker names."""
     lines = []
@@ -61,7 +62,7 @@ def transcript_to_text_timestamped(
             continue
 
         transcript = ProcessorTranscript(words=topic.words)
-        segments = transcript.as_segments()
+        segments = transcript.as_segments(is_multitrack)
 
         for segment in segments:
             speaker_name = get_speaker_name(segment.speaker, participants)
@@ -73,7 +74,9 @@ def transcript_to_text_timestamped(
 
 
 def topics_to_webvtt_named(
-    topics: list[TranscriptTopic], participants: list[TranscriptParticipant] | None
+    topics: list[TranscriptTopic],
+    participants: list[TranscriptParticipant] | None,
+    is_multitrack: bool = False,
 ) -> str:
     """Convert transcript topics to WebVTT format with participant names."""
     vtt = webvtt.WebVTT()
@@ -82,7 +85,8 @@ def topics_to_webvtt_named(
         if not topic.words:
             continue
 
-        segments = words_to_segments(topic.words)
+        transcript = ProcessorTranscript(words=topic.words)
+        segments = transcript.as_segments(is_multitrack)
 
         for segment in segments:
             speaker_name = get_speaker_name(segment.speaker, participants)
@@ -100,19 +104,23 @@ def topics_to_webvtt_named(
 
 
 def transcript_to_json_segments(
-    topics: list[TranscriptTopic], participants: list[TranscriptParticipant] | None
+    topics: list[TranscriptTopic],
+    participants: list[TranscriptParticipant] | None,
+    is_multitrack: bool = False,
 ) -> list[TranscriptSegment]:
     """Convert transcript topics to a flat list of JSON segments."""
-    segments = []
+    result = []
 
     for topic in topics:
         if not topic.words:
             continue
 
         transcript = ProcessorTranscript(words=topic.words)
-        for segment in transcript.as_segments():
+        segments = transcript.as_segments(is_multitrack)
+
+        for segment in segments:
             speaker_name = get_speaker_name(segment.speaker, participants)
-            segments.append(
+            result.append(
                 TranscriptSegment(
                     speaker=segment.speaker,
                     speaker_name=speaker_name,
@@ -122,4 +130,4 @@ def transcript_to_json_segments(
                 )
             )
 
-    return segments
+    return result

server/reflector/video_platforms/daily.py

@@ -31,6 +31,7 @@ class DailyClient(VideoPlatformClient):
     PLATFORM_NAME: Platform = "daily"
     TIMESTAMP_FORMAT = "%Y%m%d%H%M%S"
     RECORDING_NONE: RecordingType = "none"
+    RECORDING_LOCAL: RecordingType = "local"
     RECORDING_CLOUD: RecordingType = "cloud"
 
     def __init__(self, config: VideoPlatformConfig):
@@ -54,19 +55,23 @@ class DailyClient(VideoPlatformClient):
         timestamp = datetime.now().strftime(self.TIMESTAMP_FORMAT)
         room_name = f"{room_name_prefix}{ROOM_PREFIX_SEPARATOR}{timestamp}"
 
+        enable_recording = None
+        if room.recording_type == self.RECORDING_LOCAL:
+            enable_recording = "local"
+        elif room.recording_type == self.RECORDING_CLOUD:
+            enable_recording = "raw-tracks"
+
         properties = RoomProperties(
-            enable_recording="raw-tracks"
-            if room.recording_type != self.RECORDING_NONE
-            else False,
+            enable_recording=enable_recording,
             enable_chat=True,
             enable_screenshare=True,
+            enable_knocking=room.is_locked,
             start_video_off=False,
             start_audio_off=False,
             exp=int(end_date.timestamp()),
         )
 
-        # Only configure recordings_bucket if recording is enabled
-        if room.recording_type != self.RECORDING_NONE:
+        if room.recording_type == self.RECORDING_CLOUD:
             daily_storage = get_dailyco_storage()
             assert daily_storage.bucket_name, "S3 bucket must be configured"
             properties.recordings_bucket = RecordingsBucketConfig(
@@ -172,15 +177,16 @@ class DailyClient(VideoPlatformClient):
     async def create_meeting_token(
         self,
         room_name: DailyRoomName,
-        enable_recording: bool,
+        start_cloud_recording: bool,
+        enable_recording_ui: bool,
         user_id: NonEmptyString | None = None,
         is_owner: bool = False,
     ) -> NonEmptyString:
         properties = MeetingTokenProperties(
             room_name=room_name,
             user_id=user_id,
-            start_cloud_recording=enable_recording,
-            enable_recording_ui=False,
+            start_cloud_recording=start_cloud_recording,
+            enable_recording_ui=enable_recording_ui,
             is_owner=is_owner,
         )
         request = CreateMeetingTokenRequest(properties=properties)

server/reflector/views/rooms.py

@@ -89,7 +89,7 @@ class CreateRoom(BaseModel):
     ics_url: Optional[str] = None
     ics_fetch_interval: int = 300
     ics_enabled: bool = False
-    platform: Optional[Platform] = None
+    platform: Platform
 
 
 class UpdateRoom(BaseModel):
@@ -248,7 +248,7 @@ async def rooms_create(
         ics_url=room.ics_url,
         ics_fetch_interval=room.ics_fetch_interval,
         ics_enabled=room.ics_enabled,
-        platform=room.platform or settings.DEFAULT_VIDEO_PLATFORM,
+        platform=room.platform,
     )
 
 
@@ -310,6 +310,22 @@ async def rooms_create_meeting(
                     room=room, current_time=current_time
                 )
 
+                if meeting is not None:
+                    settings_match = (
+                        meeting.is_locked == room.is_locked
+                        and meeting.room_mode == room.room_mode
+                        and meeting.recording_type == room.recording_type
+                        and meeting.recording_trigger == room.recording_trigger
+                        and meeting.platform == room.platform
+                    )
+                    if not settings_match:
+                        logger.info(
+                            f"Room settings changed for {room_name}, creating new meeting",
+                            room_id=room.id,
+                            old_meeting_id=meeting.id,
+                        )
+                        meeting = None
+
             if meeting is None:
                 end_date = current_time + timedelta(hours=8)
 
@@ -549,21 +565,16 @@ async def rooms_join_meeting(
     if meeting.end_date <= current_time:
         raise HTTPException(status_code=400, detail="Meeting has ended")
 
-    if meeting.platform == "daily":
+    if meeting.platform == "daily" and user_id is not None:
         client = create_platform_client(meeting.platform)
-        enable_recording = room.recording_trigger != "none"
         token = await client.create_meeting_token(
             meeting.room_name,
-            enable_recording=enable_recording,
+            start_cloud_recording=meeting.recording_type == "cloud",
+            enable_recording_ui=meeting.recording_type == "local",
             user_id=user_id,
             is_owner=user_id == room.user_id,
         )
         meeting = meeting.model_copy()
         meeting.room_url = add_query_param(meeting.room_url, "t", token)
-        if meeting.host_room_url:
-            meeting.host_room_url = add_query_param(meeting.host_room_url, "t", token)
-
-    if user_id != room.user_id and meeting.platform == "whereby":
-        meeting.host_room_url = ""
 
     return meeting

server/reflector/views/transcripts.py

@@ -16,6 +16,7 @@ from pydantic import (
 
 import reflector.auth as auth
 from reflector.db import get_database
+from reflector.db.recordings import recordings_controller
 from reflector.db.search import (
     DEFAULT_SEARCH_LIMIT,
     SearchLimit,
@@ -36,6 +37,7 @@ from reflector.db.transcripts import (
     TranscriptTopic,
     transcripts_controller,
 )
+from reflector.db.users import user_controller
 from reflector.processors.types import Transcript as ProcessorTranscript
 from reflector.processors.types import Word
 from reflector.schemas.transcript_formats import TranscriptFormat, TranscriptSegment
@@ -60,6 +62,14 @@ ALGORITHM = "HS256"
 DOWNLOAD_EXPIRE_MINUTES = 60
 
 
+async def _get_is_multitrack(transcript) -> bool:
+    """Detect if transcript is from multitrack recording."""
+    if not transcript.recording_id:
+        return False
+    recording = await recordings_controller.get_by_id(transcript.recording_id)
+    return recording is not None and recording.is_multitrack
+
+
 def create_access_token(data: dict, expires_delta: timedelta):
     to_encode = data.copy()
     expire = datetime.now(timezone.utc) + expires_delta
@@ -102,8 +112,12 @@ class GetTranscriptMinimal(BaseModel):
     audio_deleted: bool | None = None
 
 
+class TranscriptParticipantWithEmail(TranscriptParticipant):
+    email: str | None = None
+
+
 class GetTranscriptWithParticipants(GetTranscriptMinimal):
-    participants: list[TranscriptParticipant] | None
+    participants: list[TranscriptParticipantWithEmail] | None
 
 
 class GetTranscriptWithText(GetTranscriptWithParticipants):
@@ -360,7 +374,7 @@ class GetTranscriptTopic(BaseModel):
     segments: list[GetTranscriptSegmentTopic] = []
 
     @classmethod
-    def from_transcript_topic(cls, topic: TranscriptTopic):
+    def from_transcript_topic(cls, topic: TranscriptTopic, is_multitrack: bool = False):
         if not topic.words:
             # In previous version, words were missing
             # Just output a segment with speaker 0
@@ -384,7 +398,7 @@ class GetTranscriptTopic(BaseModel):
                     start=segment.start,
                     speaker=segment.speaker,
                 )
-                for segment in transcript.as_segments()
+                for segment in transcript.as_segments(is_multitrack)
             ]
         return cls(
             id=topic.id,
@@ -401,8 +415,8 @@ class GetTranscriptTopicWithWords(GetTranscriptTopic):
     words: list[Word] = []
 
     @classmethod
-    def from_transcript_topic(cls, topic: TranscriptTopic):
-        instance = super().from_transcript_topic(topic)
+    def from_transcript_topic(cls, topic: TranscriptTopic, is_multitrack: bool = False):
+        instance = super().from_transcript_topic(topic, is_multitrack)
         if topic.words:
             instance.words = topic.words
         return instance
@@ -417,8 +431,8 @@ class GetTranscriptTopicWithWordsPerSpeaker(GetTranscriptTopic):
     words_per_speaker: list[SpeakerWords] = []
 
     @classmethod
-    def from_transcript_topic(cls, topic: TranscriptTopic):
-        instance = super().from_transcript_topic(topic)
+    def from_transcript_topic(cls, topic: TranscriptTopic, is_multitrack: bool = False):
+        instance = super().from_transcript_topic(topic, is_multitrack)
         if topic.words:
             words_per_speakers = []
             # group words by speaker
@@ -457,6 +471,20 @@ async def transcript_get(
         transcript_id, user_id=user_id
     )
 
+    is_multitrack = await _get_is_multitrack(transcript)
+
+    participants = []
+    if transcript.participants:
+        user_ids = [p.user_id for p in transcript.participants if p.user_id is not None]
+        users_dict = await user_controller.get_by_ids(user_ids) if user_ids else {}
+        for p in transcript.participants:
+            user = users_dict.get(p.user_id) if p.user_id else None
+            participants.append(
+                TranscriptParticipantWithEmail(
+                    **p.model_dump(), email=user.email if user else None
+                )
+            )
+
     base_data = {
         "id": transcript.id,
         "user_id": transcript.user_id,
@@ -476,21 +504,23 @@ async def transcript_get(
         "source_kind": transcript.source_kind,
         "room_id": transcript.room_id,
         "audio_deleted": transcript.audio_deleted,
-        "participants": transcript.participants,
+        "participants": participants,
     }
 
     if transcript_format == "text":
         return GetTranscriptWithText(
             **base_data,
             transcript_format="text",
-            transcript=transcript_to_text(transcript.topics, transcript.participants),
+            transcript=transcript_to_text(
+                transcript.topics, transcript.participants, is_multitrack
+            ),
         )
     elif transcript_format == "text-timestamped":
         return GetTranscriptWithTextTimestamped(
             **base_data,
             transcript_format="text-timestamped",
             transcript=transcript_to_text_timestamped(
-                transcript.topics, transcript.participants
+                transcript.topics, transcript.participants, is_multitrack
             ),
         )
     elif transcript_format == "webvtt-named":
@@ -498,7 +528,7 @@ async def transcript_get(
             **base_data,
             transcript_format="webvtt-named",
             transcript=topics_to_webvtt_named(
-                transcript.topics, transcript.participants
+                transcript.topics, transcript.participants, is_multitrack
             ),
         )
     elif transcript_format == "json":
@@ -506,7 +536,7 @@ async def transcript_get(
             **base_data,
             transcript_format="json",
             transcript=transcript_to_json_segments(
-                transcript.topics, transcript.participants
+                transcript.topics, transcript.participants, is_multitrack
             ),
         )
     else:
@@ -565,9 +595,12 @@ async def transcript_get_topics(
         transcript_id, user_id=user_id
     )
 
+    is_multitrack = await _get_is_multitrack(transcript)
+
     # convert to GetTranscriptTopic
     return [
-        GetTranscriptTopic.from_transcript_topic(topic) for topic in transcript.topics
+        GetTranscriptTopic.from_transcript_topic(topic, is_multitrack)
+        for topic in transcript.topics
     ]
 
 
@@ -584,9 +617,11 @@ async def transcript_get_topics_with_words(
         transcript_id, user_id=user_id
     )
 
+    is_multitrack = await _get_is_multitrack(transcript)
+
     # convert to GetTranscriptTopicWithWords
     return [
-        GetTranscriptTopicWithWords.from_transcript_topic(topic)
+        GetTranscriptTopicWithWords.from_transcript_topic(topic, is_multitrack)
         for topic in transcript.topics
     ]
 
@@ -605,13 +640,17 @@ async def transcript_get_topics_with_words_per_speaker(
         transcript_id, user_id=user_id
     )
 
+    is_multitrack = await _get_is_multitrack(transcript)
+
     # get the topic from the transcript
     topic = next((t for t in transcript.topics if t.id == topic_id), None)
     if not topic:
         raise HTTPException(status_code=404, detail="Topic not found")
 
     # convert to GetTranscriptTopicWithWordsPerSpeaker
-    return GetTranscriptTopicWithWordsPerSpeaker.from_transcript_topic(topic)
+    return GetTranscriptTopicWithWordsPerSpeaker.from_transcript_topic(
+        topic, is_multitrack
+    )
 
 
 @router.post("/transcripts/{transcript_id}/zulip")

server/reflector/worker/process.py

@@ -2,6 +2,7 @@ import json
 import os
 import re
 from datetime import datetime, timezone
+from typing import List
 from urllib.parse import unquote
 
 import av
@@ -11,7 +12,7 @@ from celery import shared_task
 from celery.utils.log import get_task_logger
 from pydantic import ValidationError
 
-from reflector.dailyco_api import MeetingParticipantsResponse
+from reflector.dailyco_api import RecordingResponse
 from reflector.db.daily_participant_sessions import (
     DailyParticipantSession,
     daily_participant_sessions_controller,
@@ -21,7 +22,6 @@ from reflector.db.recordings import Recording, recordings_controller
 from reflector.db.rooms import rooms_controller
 from reflector.db.transcripts import (
     SourceKind,
-    TranscriptParticipant,
     transcripts_controller,
 )
 from reflector.pipelines.main_file_pipeline import task_pipeline_file_process
@@ -38,7 +38,7 @@ from reflector.storage import get_transcripts_storage
 from reflector.utils.daily import (
     DailyRoomName,
     extract_base_room_name,
-    parse_daily_recording_filename,
+    filter_cam_audio_tracks,
     recording_lock_key,
 )
 from reflector.video_platforms.factory import create_platform_client
@@ -273,15 +273,7 @@ async def _process_multitrack_recording_inner(
     # else: Recording already exists; metadata set at creation time
 
     transcript = await transcripts_controller.get_by_recording_id(recording.id)
-    if transcript:
-        await transcripts_controller.update(
-            transcript,
-            {
-                "topics": [],
-                "participants": [],
-            },
-        )
-    else:
+    if not transcript:
         transcript = await transcripts_controller.add(
             "",
             source_kind=SourceKind.ROOM,
@@ -294,79 +286,10 @@ async def _process_multitrack_recording_inner(
             room_id=room.id,
         )
 
-    try:
-        async with create_platform_client("daily") as daily_client:
-            id_to_name = {}
-            id_to_user_id = {}
-
-            try:
-                rec_details = await daily_client.get_recording(recording_id)
-                mtg_session_id = rec_details.mtgSessionId
-                if mtg_session_id:
-                    try:
-                        payload: MeetingParticipantsResponse = (
-                            await daily_client.get_meeting_participants(mtg_session_id)
-                        )
-                        for p in payload.data:
-                            pid = p.participant_id
-                            assert (
-                                pid is not None
-                            ), "panic! participant id cannot be None"
-                            name = p.user_name
-                            user_id = p.user_id
-                            if name:
-                                id_to_name[pid] = name
-                            if user_id:
-                                id_to_user_id[pid] = user_id
-                    except Exception as e:
-                        logger.warning(
-                            "Failed to fetch Daily meeting participants",
-                            error=str(e),
-                            mtg_session_id=mtg_session_id,
-                            exc_info=True,
-                        )
-                else:
-                    logger.warning(
-                        "No mtgSessionId found for recording; participant names may be generic",
-                        recording_id=recording_id,
-                    )
-            except Exception as e:
-                logger.warning(
-                    "Failed to fetch Daily recording details",
-                    error=str(e),
-                    recording_id=recording_id,
-                    exc_info=True,
-                )
-
-            for idx, key in enumerate(track_keys):
-                try:
-                    parsed = parse_daily_recording_filename(key)
-                    participant_id = parsed.participant_id
-                except ValueError as e:
-                    logger.error(
-                        "Failed to parse Daily recording filename",
-                        error=str(e),
-                        key=key,
-                        exc_info=True,
-                    )
-                    continue
-
-                default_name = f"Speaker {idx}"
-                name = id_to_name.get(participant_id, default_name)
-                user_id = id_to_user_id.get(participant_id)
-
-                participant = TranscriptParticipant(
-                    id=participant_id, speaker=idx, name=name, user_id=user_id
-                )
-                await transcripts_controller.upsert_participant(transcript, participant)
-
-    except Exception as e:
-        logger.warning("Failed to map participant names", error=str(e), exc_info=True)
-
     task_pipeline_multitrack_process.delay(
         transcript_id=transcript.id,
         bucket_name=bucket_name,
-        track_keys=track_keys,
+        track_keys=filter_cam_audio_tracks(track_keys),
     )
 
 
@@ -391,7 +314,7 @@ async def poll_daily_recordings():
 
     async with create_platform_client("daily") as daily_client:
         # latest 100. TODO cursor-based state
-        api_recordings = await daily_client.list_recordings()
+        api_recordings: List[RecordingResponse] = await daily_client.list_recordings()
 
     if not api_recordings:
         logger.debug(
@@ -422,17 +345,19 @@ async def poll_daily_recordings():
 
     for recording in missing_recordings:
         if not recording.tracks:
-            assert recording.status != "finished", (
-                f"Recording {recording.id} has status='finished' but no tracks. "
-                f"Daily.co API guarantees finished recordings have tracks available. "
-                f"room_name={recording.room_name}"
-            )
-            logger.debug(
-                "No tracks in recording yet",
-                recording_id=recording.id,
-                room_name=recording.room_name,
-                status=recording.status,
-            )
+            if recording.status == "finished":
+                logger.warning(
+                    "Finished recording has no tracks (no audio captured)",
+                    recording_id=recording.id,
+                    room_name=recording.room_name,
+                )
+            else:
+                logger.debug(
+                    "No tracks in recording yet",
+                    recording_id=recording.id,
+                    room_name=recording.room_name,
+                    status=recording.status,
+                )
             continue
 
         track_keys = [t.s3Key for t in recording.tracks if t.type == "audio"]

server/tests/conftest.py

@@ -318,6 +318,14 @@ async def dummy_storage():
         yield
 
 
+@pytest.fixture
+def test_settings():
+    """Provide isolated settings for tests to avoid modifying global settings"""
+    from reflector.settings import Settings
+
+    return Settings()
+
+
 @pytest.fixture(scope="session")
 def celery_enable_logging():
     return True

server/tests/test_llm_retry.py

@@ -0,0 +1,357 @@
+"""Tests for LLM parse error recovery using llama-index Workflow"""
+
+from unittest.mock import AsyncMock, MagicMock, patch
+
+import pytest
+from pydantic import BaseModel, Field
+from workflows.errors import WorkflowRuntimeError
+
+from reflector.llm import LLM, LLMParseError, StructuredOutputWorkflow
+
+
+class TestResponse(BaseModel):
+    """Test response model for structured output"""
+
+    title: str = Field(description="A title")
+    summary: str = Field(description="A summary")
+    confidence: float = Field(description="Confidence score", ge=0, le=1)
+
+
+def make_completion_response(text: str):
+    """Create a mock CompletionResponse with .text attribute"""
+    response = MagicMock()
+    response.text = text
+    return response
+
+
+class TestLLMParseErrorRecovery:
+    """Test parse error recovery with Workflow feedback loop"""
+
+    @pytest.mark.asyncio
+    async def test_parse_error_recovery_with_feedback(self, test_settings):
+        """Test that parse errors trigger retry with error feedback"""
+        llm = LLM(settings=test_settings, temperature=0.4, max_tokens=100)
+
+        with (
+            patch("reflector.llm.TreeSummarize") as mock_summarize,
+            patch("reflector.llm.Settings") as mock_settings,
+        ):
+            mock_summarizer = MagicMock()
+            mock_summarize.return_value = mock_summarizer
+            # TreeSummarize returns plain text analysis (step 1)
+            mock_summarizer.aget_response = AsyncMock(
+                return_value="The analysis shows a test with summary and high confidence."
+            )
+
+            call_count = {"count": 0}
+
+            async def acomplete_handler(prompt, *args, **kwargs):
+                call_count["count"] += 1
+                if call_count["count"] == 1:
+                    # First JSON formatting call returns invalid JSON
+                    return make_completion_response('{"title": "Test"}')
+                else:
+                    # Second call should have error feedback in prompt
+                    assert "Your previous response could not be parsed:" in prompt
+                    assert '{"title": "Test"}' in prompt
+                    assert "Error:" in prompt
+                    assert "Please try again" in prompt
+                    return make_completion_response(
+                        '{"title": "Test", "summary": "Summary", "confidence": 0.95}'
+                    )
+
+            mock_settings.llm.acomplete = AsyncMock(side_effect=acomplete_handler)
+
+            result = await llm.get_structured_response(
+                prompt="Test prompt", texts=["Test text"], output_cls=TestResponse
+            )
+
+            assert result.title == "Test"
+            assert result.summary == "Summary"
+            assert result.confidence == 0.95
+            # TreeSummarize called once, Settings.llm.acomplete called twice
+            assert mock_summarizer.aget_response.call_count == 1
+            assert call_count["count"] == 2
+
+    @pytest.mark.asyncio
+    async def test_max_parse_retry_attempts(self, test_settings):
+        """Test that parse error retry stops after max attempts"""
+        llm = LLM(settings=test_settings, temperature=0.4, max_tokens=100)
+
+        with (
+            patch("reflector.llm.TreeSummarize") as mock_summarize,
+            patch("reflector.llm.Settings") as mock_settings,
+        ):
+            mock_summarizer = MagicMock()
+            mock_summarize.return_value = mock_summarizer
+            mock_summarizer.aget_response = AsyncMock(return_value="Some analysis")
+
+            # Always return invalid JSON from acomplete
+            mock_settings.llm.acomplete = AsyncMock(
+                return_value=make_completion_response(
+                    '{"invalid": "missing required fields"}'
+                )
+            )
+
+            with pytest.raises(LLMParseError, match="Failed to parse"):
+                await llm.get_structured_response(
+                    prompt="Test prompt", texts=["Test text"], output_cls=TestResponse
+                )
+
+            expected_attempts = test_settings.LLM_PARSE_MAX_RETRIES + 1
+            # TreeSummarize called once, acomplete called max_retries times
+            assert mock_summarizer.aget_response.call_count == 1
+            assert mock_settings.llm.acomplete.call_count == expected_attempts
+
+    @pytest.mark.asyncio
+    async def test_raw_response_logging_on_parse_error(self, test_settings, caplog):
+        """Test that raw response is logged when parse error occurs"""
+        llm = LLM(settings=test_settings, temperature=0.4, max_tokens=100)
+
+        with (
+            patch("reflector.llm.TreeSummarize") as mock_summarize,
+            patch("reflector.llm.Settings") as mock_settings,
+            caplog.at_level("ERROR"),
+        ):
+            mock_summarizer = MagicMock()
+            mock_summarize.return_value = mock_summarizer
+            mock_summarizer.aget_response = AsyncMock(return_value="Some analysis")
+
+            call_count = {"count": 0}
+
+            async def acomplete_handler(*args, **kwargs):
+                call_count["count"] += 1
+                if call_count["count"] == 1:
+                    return make_completion_response('{"title": "Test"}')  # Invalid
+                return make_completion_response(
+                    '{"title": "Test", "summary": "Summary", "confidence": 0.95}'
+                )
+
+            mock_settings.llm.acomplete = AsyncMock(side_effect=acomplete_handler)
+
+            result = await llm.get_structured_response(
+                prompt="Test prompt", texts=["Test text"], output_cls=TestResponse
+            )
+
+            assert result.title == "Test"
+
+            error_logs = [r for r in caplog.records if r.levelname == "ERROR"]
+            raw_response_logged = any("Raw response:" in r.message for r in error_logs)
+            assert raw_response_logged, "Raw response should be logged on parse error"
+
+    @pytest.mark.asyncio
+    async def test_multiple_validation_errors_in_feedback(self, test_settings):
+        """Test that validation errors are included in feedback"""
+        llm = LLM(settings=test_settings, temperature=0.4, max_tokens=100)
+
+        with (
+            patch("reflector.llm.TreeSummarize") as mock_summarize,
+            patch("reflector.llm.Settings") as mock_settings,
+        ):
+            mock_summarizer = MagicMock()
+            mock_summarize.return_value = mock_summarizer
+            mock_summarizer.aget_response = AsyncMock(return_value="Some analysis")
+
+            call_count = {"count": 0}
+
+            async def acomplete_handler(prompt, *args, **kwargs):
+                call_count["count"] += 1
+                if call_count["count"] == 1:
+                    # Missing title and summary
+                    return make_completion_response('{"confidence": 0.5}')
+                else:
+                    # Should have schema validation errors in prompt
+                    assert (
+                        "Schema validation errors" in prompt
+                        or "error" in prompt.lower()
+                    )
+                    return make_completion_response(
+                        '{"title": "Test", "summary": "Summary", "confidence": 0.95}'
+                    )
+
+            mock_settings.llm.acomplete = AsyncMock(side_effect=acomplete_handler)
+
+            result = await llm.get_structured_response(
+                prompt="Test prompt", texts=["Test text"], output_cls=TestResponse
+            )
+
+            assert result.title == "Test"
+            assert call_count["count"] == 2
+
+    @pytest.mark.asyncio
+    async def test_success_on_first_attempt(self, test_settings):
+        """Test that no retry happens when first attempt succeeds"""
+        llm = LLM(settings=test_settings, temperature=0.4, max_tokens=100)
+
+        with (
+            patch("reflector.llm.TreeSummarize") as mock_summarize,
+            patch("reflector.llm.Settings") as mock_settings,
+        ):
+            mock_summarizer = MagicMock()
+            mock_summarize.return_value = mock_summarizer
+            mock_summarizer.aget_response = AsyncMock(return_value="Some analysis")
+
+            mock_settings.llm.acomplete = AsyncMock(
+                return_value=make_completion_response(
+                    '{"title": "Test", "summary": "Summary", "confidence": 0.95}'
+                )
+            )
+
+            result = await llm.get_structured_response(
+                prompt="Test prompt", texts=["Test text"], output_cls=TestResponse
+            )
+
+            assert result.title == "Test"
+            assert result.summary == "Summary"
+            assert result.confidence == 0.95
+            assert mock_summarizer.aget_response.call_count == 1
+            assert mock_settings.llm.acomplete.call_count == 1
+
+
+class TestStructuredOutputWorkflow:
+    """Direct tests for the StructuredOutputWorkflow"""
+
+    @pytest.mark.asyncio
+    async def test_workflow_retries_on_validation_error(self):
+        """Test workflow retries when validation fails"""
+        workflow = StructuredOutputWorkflow(
+            output_cls=TestResponse,
+            max_retries=3,
+            timeout=30,
+        )
+
+        with (
+            patch("reflector.llm.TreeSummarize") as mock_summarize,
+            patch("reflector.llm.Settings") as mock_settings,
+        ):
+            mock_summarizer = MagicMock()
+            mock_summarize.return_value = mock_summarizer
+            mock_summarizer.aget_response = AsyncMock(return_value="Some analysis")
+
+            call_count = {"count": 0}
+
+            async def acomplete_handler(*args, **kwargs):
+                call_count["count"] += 1
+                if call_count["count"] < 2:
+                    return make_completion_response('{"title": "Only title"}')
+                return make_completion_response(
+                    '{"title": "Test", "summary": "Summary", "confidence": 0.9}'
+                )
+
+            mock_settings.llm.acomplete = AsyncMock(side_effect=acomplete_handler)
+
+            result = await workflow.run(
+                prompt="Extract data",
+                texts=["Some text"],
+                tone_name=None,
+            )
+
+            assert "success" in result
+            assert result["success"].title == "Test"
+            assert call_count["count"] == 2
+
+    @pytest.mark.asyncio
+    async def test_workflow_returns_error_after_max_retries(self):
+        """Test workflow returns error after exhausting retries"""
+        workflow = StructuredOutputWorkflow(
+            output_cls=TestResponse,
+            max_retries=2,
+            timeout=30,
+        )
+
+        with (
+            patch("reflector.llm.TreeSummarize") as mock_summarize,
+            patch("reflector.llm.Settings") as mock_settings,
+        ):
+            mock_summarizer = MagicMock()
+            mock_summarize.return_value = mock_summarizer
+            mock_summarizer.aget_response = AsyncMock(return_value="Some analysis")
+
+            # Always return invalid JSON
+            mock_settings.llm.acomplete = AsyncMock(
+                return_value=make_completion_response('{"invalid": true}')
+            )
+
+            result = await workflow.run(
+                prompt="Extract data",
+                texts=["Some text"],
+                tone_name=None,
+            )
+
+            assert "error" in result
+            # TreeSummarize called once, acomplete called max_retries times
+            assert mock_summarizer.aget_response.call_count == 1
+            assert mock_settings.llm.acomplete.call_count == 2
+
+
+class TestNetworkErrorRetries:
+    """Test that network error retries are handled by OpenAILike, not Workflow"""
+
+    @pytest.mark.asyncio
+    async def test_network_error_propagates_after_openai_retries(self, test_settings):
+        """Test that network errors are retried by OpenAILike and then propagate.
+
+        Network retries are handled by OpenAILike (max_retries=3), not by our
+        StructuredOutputWorkflow. This test verifies that network errors propagate
+        up after OpenAILike exhausts its retries.
+        """
+        llm = LLM(settings=test_settings, temperature=0.4, max_tokens=100)
+
+        with (
+            patch("reflector.llm.TreeSummarize") as mock_summarize,
+            patch("reflector.llm.Settings") as mock_settings,
+        ):
+            mock_summarizer = MagicMock()
+            mock_summarize.return_value = mock_summarizer
+            mock_summarizer.aget_response = AsyncMock(return_value="Some analysis")
+
+            # Simulate network error from acomplete (after OpenAILike retries exhausted)
+            network_error = ConnectionError("Connection refused")
+            mock_settings.llm.acomplete = AsyncMock(side_effect=network_error)
+
+            # Network error wrapped in WorkflowRuntimeError
+            with pytest.raises(WorkflowRuntimeError, match="Connection refused"):
+                await llm.get_structured_response(
+                    prompt="Test prompt", texts=["Test text"], output_cls=TestResponse
+                )
+
+            # acomplete called only once - network error propagates, not retried by Workflow
+            assert mock_settings.llm.acomplete.call_count == 1
+
+    @pytest.mark.asyncio
+    async def test_network_error_not_retried_by_workflow(self, test_settings):
+        """Test that Workflow does NOT retry network errors (OpenAILike handles those).
+
+        This verifies the separation of concerns:
+        - StructuredOutputWorkflow: retries parse/validation errors
+        - OpenAILike: retries network errors (internally, max_retries=3)
+        """
+        workflow = StructuredOutputWorkflow(
+            output_cls=TestResponse,
+            max_retries=3,
+            timeout=30,
+        )
+
+        with (
+            patch("reflector.llm.TreeSummarize") as mock_summarize,
+            patch("reflector.llm.Settings") as mock_settings,
+        ):
+            mock_summarizer = MagicMock()
+            mock_summarize.return_value = mock_summarizer
+            mock_summarizer.aget_response = AsyncMock(return_value="Some analysis")
+
+            # Network error should propagate immediately, not trigger Workflow retry
+            mock_settings.llm.acomplete = AsyncMock(
+                side_effect=TimeoutError("Request timed out")
+            )
+
+            # Network error wrapped in WorkflowRuntimeError
+            with pytest.raises(WorkflowRuntimeError, match="Request timed out"):
+                await workflow.run(
+                    prompt="Extract data",
+                    texts=["Some text"],
+                    tone_name=None,
+                )
+
+            # Only called once - Workflow doesn't retry network errors
+            assert mock_settings.llm.acomplete.call_count == 1

server/tests/test_processor_transcript_segment.py

@@ -159,3 +159,78 @@ def test_processor_transcript_segment():
     assert segments[3].start == 30.72
     assert segments[4].start == 31.56
     assert segments[5].start == 32.38
+
+
+def test_processor_transcript_segment_multitrack_interleaved():
+    """Test as_segments(is_multitrack=True) with interleaved speakers.
+
+    Multitrack recordings have words from different speakers sorted by start time,
+    causing frequent speaker alternation. The multitrack mode should group by
+    speaker first, then split into sentences.
+    """
+    from reflector.processors.types import Transcript, Word
+
+    # Simulate real multitrack data: words sorted by start time, speakers interleave
+    # Speaker 0 says: "Hello there."
+    # Speaker 1 says: "I'm good."
+    # When sorted by time, words interleave
+    transcript = Transcript(
+        words=[
+            Word(text="Hello ", start=0.0, end=0.5, speaker=0),
+            Word(text="I'm ", start=0.5, end=0.8, speaker=1),
+            Word(text="there.", start=0.5, end=1.0, speaker=0),
+            Word(text="good.", start=1.0, end=1.5, speaker=1),
+        ]
+    )
+
+    # Default behavior (is_multitrack=False): breaks on every speaker change = 4 segments
+    segments_default = transcript.as_segments(is_multitrack=False)
+    assert len(segments_default) == 4
+
+    # Multitrack behavior: groups by speaker, then sentences = 2 segments
+    segments_multitrack = transcript.as_segments(is_multitrack=True)
+    assert len(segments_multitrack) == 2
+
+    # Check content - sorted by start time
+    assert segments_multitrack[0].speaker == 0
+    assert segments_multitrack[0].text == "Hello there."
+    assert segments_multitrack[0].start == 0.0
+    assert segments_multitrack[0].end == 1.0
+
+    assert segments_multitrack[1].speaker == 1
+    assert segments_multitrack[1].text == "I'm good."
+    assert segments_multitrack[1].start == 0.5
+    assert segments_multitrack[1].end == 1.5
+
+
+def test_processor_transcript_segment_multitrack_overlapping_timestamps():
+    """Test multitrack with exactly overlapping timestamps (real Daily.co data pattern)."""
+    from reflector.processors.types import Transcript, Word
+
+    # Real pattern from transcript 38d84d57: words with identical timestamps
+    transcript = Transcript(
+        words=[
+            Word(text="speaking ", start=6.71, end=7.11, speaker=0),
+            Word(text="Speaking ", start=6.71, end=7.11, speaker=1),
+            Word(text="at ", start=7.11, end=7.27, speaker=0),
+            Word(text="at ", start=7.11, end=7.27, speaker=1),
+            Word(text="the ", start=7.27, end=7.43, speaker=0),
+            Word(text="the ", start=7.27, end=7.43, speaker=1),
+            Word(text="same ", start=7.43, end=7.59, speaker=0),
+            Word(text="same ", start=7.43, end=7.59, speaker=1),
+            Word(text="time.", start=7.59, end=8.0, speaker=0),
+            Word(text="time.", start=7.59, end=8.0, speaker=1),
+        ]
+    )
+
+    # Default: 10 segments (one per speaker change)
+    segments_default = transcript.as_segments(is_multitrack=False)
+    assert len(segments_default) == 10
+
+    # Multitrack: 2 segments (one per speaker sentence)
+    segments_multitrack = transcript.as_segments(is_multitrack=True)
+    assert len(segments_multitrack) == 2
+
+    # Both should have complete sentences
+    assert "speaking at the same time." in segments_multitrack[0].text
+    assert "Speaking at the same time." in segments_multitrack[1].text

server/tests/test_transcript_formats.py

@@ -273,8 +273,17 @@ async def test_transcript_formats_with_multiple_speakers():
 
 
 @pytest.mark.asyncio
-async def test_transcript_formats_with_overlapping_speakers():
-    """Test format conversion when multiple speakers speak at the same time (overlapping timestamps)."""
+async def test_transcript_formats_with_overlapping_speakers_multitrack():
+    """Test format conversion for multitrack recordings with truly interleaved words.
+
+    Multitrack recordings have words from different speakers sorted by start time,
+    causing frequent speaker alternation. This tests the sentence-based segmentation
+    that groups each speaker's words into complete sentences.
+    """
+    # Real multitrack data: words sorted by start time, speakers interleave
+    # Alice says: "Hello there." (0.0-1.0)
+    # Bob says: "I'm good." (0.5-1.5)
+    # When sorted by time, words interleave: Hello, I'm, there., good.
     topics = [
         TranscriptTopic(
             id="1",
@@ -282,11 +291,10 @@ async def test_transcript_formats_with_overlapping_speakers():
             summary="Summary 1",
             timestamp=0.0,
             words=[
-                Word(text="Hello", start=0.0, end=0.5, speaker=0),
-                Word(text=" there.", start=0.5, end=1.0, speaker=0),
-                # Speaker 1 overlaps with speaker 0 at 0.5-1.0
-                Word(text="I'm", start=0.5, end=1.0, speaker=1),
-                Word(text=" good.", start=1.0, end=1.5, speaker=1),
+                Word(text="Hello ", start=0.0, end=0.5, speaker=0),
+                Word(text="I'm ", start=0.5, end=0.8, speaker=1),
+                Word(text="there.", start=0.5, end=1.0, speaker=0),
+                Word(text="good.", start=1.0, end=1.5, speaker=1),
             ],
         ),
     ]
@@ -296,20 +304,9 @@ async def test_transcript_formats_with_overlapping_speakers():
         TranscriptParticipant(id="2", speaker=1, name="Bob"),
     ]
 
-    text_result = transcript_to_text(topics, participants)
-    lines = text_result.split("\n")
-    assert len(lines) >= 2
-    assert any("Alice:" in line for line in lines)
-    assert any("Bob:" in line for line in lines)
-
-    timestamped_result = transcript_to_text_timestamped(topics, participants)
-    timestamped_lines = timestamped_result.split("\n")
-    assert len(timestamped_lines) >= 2
-    assert any("Alice:" in line for line in timestamped_lines)
-    assert any("Bob:" in line for line in timestamped_lines)
-    assert any("[00:00]" in line for line in timestamped_lines)
-
-    webvtt_result = topics_to_webvtt_named(topics, participants)
+    # With is_multitrack=True, should produce 2 segments (one per speaker sentence)
+    # not 4 segments (one per speaker change)
+    webvtt_result = topics_to_webvtt_named(topics, participants, is_multitrack=True)
     expected_webvtt = """WEBVTT
 
 00:00:00.000 --> 00:00:01.000
@@ -320,23 +317,26 @@ async def test_transcript_formats_with_overlapping_speakers():
 """
     assert webvtt_result == expected_webvtt
 
-    segments = transcript_to_json_segments(topics, participants)
-    assert len(segments) >= 2
-    speakers = {seg.speaker for seg in segments}
-    assert 0 in speakers and 1 in speakers
+    text_result = transcript_to_text(topics, participants, is_multitrack=True)
+    lines = text_result.split("\n")
+    assert len(lines) == 2
+    assert "Alice: Hello there." in lines[0]
+    assert "Bob: I'm good." in lines[1]
 
-    alice_seg = next(seg for seg in segments if seg.speaker == 0)
-    bob_seg = next(seg for seg in segments if seg.speaker == 1)
+    timestamped_result = transcript_to_text_timestamped(
+        topics, participants, is_multitrack=True
+    )
+    timestamped_lines = timestamped_result.split("\n")
+    assert len(timestamped_lines) == 2
+    assert "[00:00] Alice: Hello there." in timestamped_lines[0]
+    assert "[00:00] Bob: I'm good." in timestamped_lines[1]
 
-    # Verify timestamps overlap: Alice (0.0-1.0) and Bob (0.5-1.5) overlap at 0.5-1.0
-    assert alice_seg.start < bob_seg.end, "Alice segment should start before Bob ends"
-    assert bob_seg.start < alice_seg.end, "Bob segment should start before Alice ends"
-
-    overlap_start = max(alice_seg.start, bob_seg.start)
-    overlap_end = min(alice_seg.end, bob_seg.end)
-    assert (
-        overlap_start < overlap_end
-    ), f"Segments should overlap between {overlap_start} and {overlap_end}"
+    segments = transcript_to_json_segments(topics, participants, is_multitrack=True)
+    assert len(segments) == 2
+    assert segments[0].speaker_name == "Alice"
+    assert segments[0].text == "Hello there."
+    assert segments[1].speaker_name == "Bob"
+    assert segments[1].text == "I'm good."
 
 
 @pytest.mark.asyncio
@@ -573,3 +573,207 @@ async def test_api_transcript_format_default_is_text(client):
 
     assert data["transcript_format"] == "text"
     assert "transcript" in data
+
+
+@pytest.mark.asyncio
+async def test_api_topics_endpoint_multitrack_segmentation(client):
+    """Test GET /transcripts/{id}/topics uses sentence-based segmentation for multitrack.
+
+    This tests the fix for TASKS2.md - ensuring /topics endpoints correctly detect
+    multitrack recordings and use sentence-based segmentation instead of fragmenting
+    on every speaker change.
+    """
+    from datetime import datetime, timezone
+
+    from reflector.db.recordings import Recording, recordings_controller
+    from reflector.db.transcripts import (
+        TranscriptParticipant,
+        TranscriptTopic,
+        transcripts_controller,
+    )
+    from reflector.processors.types import Word
+
+    # Create a multitrack recording (has track_keys)
+    recording = Recording(
+        bucket_name="test-bucket",
+        object_key="test-key",
+        recorded_at=datetime.now(timezone.utc),
+        track_keys=["track1.webm", "track2.webm"],  # This makes it multitrack
+    )
+    await recordings_controller.create(recording)
+
+    # Create transcript linked to the recording
+    transcript = await transcripts_controller.add(
+        name="Multitrack Test",
+        source_kind="file",
+        recording_id=recording.id,
+    )
+
+    await transcripts_controller.update(
+        transcript,
+        {
+            "participants": [
+                TranscriptParticipant(id="1", speaker=0, name="Alice").model_dump(),
+                TranscriptParticipant(id="2", speaker=1, name="Bob").model_dump(),
+            ]
+        },
+    )
+
+    # Add interleaved words (as they appear in real multitrack data)
+    await transcripts_controller.upsert_topic(
+        transcript,
+        TranscriptTopic(
+            title="Topic 1",
+            summary="Summary 1",
+            timestamp=0,
+            words=[
+                Word(text="Hello ", start=0.0, end=0.5, speaker=0),
+                Word(text="I'm ", start=0.5, end=0.8, speaker=1),
+                Word(text="there.", start=0.5, end=1.0, speaker=0),
+                Word(text="good.", start=1.0, end=1.5, speaker=1),
+            ],
+        ),
+    )
+
+    # Test /topics endpoint
+    response = await client.get(f"/transcripts/{transcript.id}/topics")
+    assert response.status_code == 200
+    data = response.json()
+
+    assert len(data) == 1
+    topic = data[0]
+
+    # Key assertion: multitrack should produce 2 segments (one per speaker sentence)
+    # Not 4 segments (one per speaker change)
+    assert len(topic["segments"]) == 2
+
+    # Check content
+    segment_texts = [s["text"] for s in topic["segments"]]
+    assert "Hello there." in segment_texts
+    assert "I'm good." in segment_texts
+
+
+@pytest.mark.asyncio
+async def test_api_topics_endpoint_non_multitrack_segmentation(client):
+    """Test GET /transcripts/{id}/topics uses default segmentation for non-multitrack.
+
+    Ensures backward compatibility - transcripts without multitrack recordings
+    should continue using the default speaker-change-based segmentation.
+    """
+    from reflector.db.transcripts import (
+        TranscriptParticipant,
+        TranscriptTopic,
+        transcripts_controller,
+    )
+    from reflector.processors.types import Word
+
+    # Create transcript WITHOUT recording (defaulted as not multitrack) TODO better heuristic
+    response = await client.post("/transcripts", json={"name": "Test transcript"})
+    assert response.status_code == 200
+    tid = response.json()["id"]
+
+    transcript = await transcripts_controller.get_by_id(tid)
+
+    await transcripts_controller.update(
+        transcript,
+        {
+            "participants": [
+                TranscriptParticipant(id="1", speaker=0, name="Alice").model_dump(),
+                TranscriptParticipant(id="2", speaker=1, name="Bob").model_dump(),
+            ]
+        },
+    )
+
+    # Add interleaved words
+    await transcripts_controller.upsert_topic(
+        transcript,
+        TranscriptTopic(
+            title="Topic 1",
+            summary="Summary 1",
+            timestamp=0,
+            words=[
+                Word(text="Hello ", start=0.0, end=0.5, speaker=0),
+                Word(text="I'm ", start=0.5, end=0.8, speaker=1),
+                Word(text="there.", start=0.5, end=1.0, speaker=0),
+                Word(text="good.", start=1.0, end=1.5, speaker=1),
+            ],
+        ),
+    )
+
+    # Test /topics endpoint
+    response = await client.get(f"/transcripts/{tid}/topics")
+    assert response.status_code == 200
+    data = response.json()
+
+    assert len(data) == 1
+    topic = data[0]
+
+    # Non-multitrack: should produce 4 segments (one per speaker change)
+    assert len(topic["segments"]) == 4
+
+
+@pytest.mark.asyncio
+async def test_api_topics_with_words_endpoint_multitrack(client):
+    """Test GET /transcripts/{id}/topics/with-words uses multitrack segmentation."""
+    from datetime import datetime, timezone
+
+    from reflector.db.recordings import Recording, recordings_controller
+    from reflector.db.transcripts import (
+        TranscriptParticipant,
+        TranscriptTopic,
+        transcripts_controller,
+    )
+    from reflector.processors.types import Word
+
+    # Create multitrack recording
+    recording = Recording(
+        bucket_name="test-bucket",
+        object_key="test-key-2",
+        recorded_at=datetime.now(timezone.utc),
+        track_keys=["track1.webm", "track2.webm"],
+    )
+    await recordings_controller.create(recording)
+
+    transcript = await transcripts_controller.add(
+        name="Multitrack Test 2",
+        source_kind="file",
+        recording_id=recording.id,
+    )
+
+    await transcripts_controller.update(
+        transcript,
+        {
+            "participants": [
+                TranscriptParticipant(id="1", speaker=0, name="Alice").model_dump(),
+                TranscriptParticipant(id="2", speaker=1, name="Bob").model_dump(),
+            ]
+        },
+    )
+
+    await transcripts_controller.upsert_topic(
+        transcript,
+        TranscriptTopic(
+            title="Topic 1",
+            summary="Summary 1",
+            timestamp=0,
+            words=[
+                Word(text="Hello ", start=0.0, end=0.5, speaker=0),
+                Word(text="I'm ", start=0.5, end=0.8, speaker=1),
+                Word(text="there.", start=0.5, end=1.0, speaker=0),
+                Word(text="good.", start=1.0, end=1.5, speaker=1),
+            ],
+        ),
+    )
+
+    response = await client.get(f"/transcripts/{transcript.id}/topics/with-words")
+    assert response.status_code == 200
+    data = response.json()
+
+    assert len(data) == 1
+    topic = data[0]
+
+    # Should have 2 segments (multitrack sentence-based)
+    assert len(topic["segments"]) == 2
+    # Should also have words field
+    assert "words" in topic
+    assert len(topic["words"]) == 4

www/app/(app)/rooms/page.tsx

@@ -15,9 +15,12 @@ import {
   createListCollection,
   useDisclosure,
   Tabs,
+  Popover,
+  Text,
+  HStack,
 } from "@chakra-ui/react";
 import { useEffect, useMemo, useState } from "react";
-import { LuEye, LuEyeOff } from "react-icons/lu";
+import { LuEye, LuEyeOff, LuInfo } from "react-icons/lu";
 import useRoomList from "./useRoomList";
 import type { components } from "../../reflector-api";
 import {
@@ -67,6 +70,11 @@ const recordingTypeOptions: SelectOption[] = [
   { label: "Cloud", value: "cloud" },
 ];
 
+const platformOptions: SelectOption[] = [
+  { label: "Whereby", value: "whereby" },
+  { label: "Daily", value: "daily" },
+];
+
 const roomInitialState = {
   name: "",
   zulipAutoPost: false,
@@ -82,6 +90,7 @@ const roomInitialState = {
   icsUrl: "",
   icsEnabled: false,
   icsFetchInterval: 5,
+  platform: "whereby",
 };
 
 export default function RoomsList() {
@@ -99,6 +108,11 @@ export default function RoomsList() {
   const recordingTypeCollection = createListCollection({
     items: recordingTypeOptions,
   });
+
+  const platformCollection = createListCollection({
+    items: platformOptions,
+  });
+
   const [roomInput, setRoomInput] = useState<null | typeof roomInitialState>(
     null,
   );
@@ -143,15 +157,24 @@ export default function RoomsList() {
             zulipStream: detailedEditedRoom.zulip_stream,
             zulipTopic: detailedEditedRoom.zulip_topic,
             isLocked: detailedEditedRoom.is_locked,
-            roomMode: detailedEditedRoom.room_mode,
+            roomMode:
+              detailedEditedRoom.platform === "daily"
+                ? "group"
+                : detailedEditedRoom.room_mode,
             recordingType: detailedEditedRoom.recording_type,
-            recordingTrigger: detailedEditedRoom.recording_trigger,
+            recordingTrigger:
+              detailedEditedRoom.platform === "daily"
+                ? detailedEditedRoom.recording_type === "cloud"
+                  ? "automatic-2nd-participant"
+                  : "none"
+                : detailedEditedRoom.recording_trigger,
             isShared: detailedEditedRoom.is_shared,
             webhookUrl: detailedEditedRoom.webhook_url || "",
             webhookSecret: detailedEditedRoom.webhook_secret || "",
             icsUrl: detailedEditedRoom.ics_url || "",
             icsEnabled: detailedEditedRoom.ics_enabled || false,
             icsFetchInterval: detailedEditedRoom.ics_fetch_interval || 5,
+            platform: detailedEditedRoom.platform,
           }
         : null,
     [detailedEditedRoom],
@@ -277,21 +300,32 @@ export default function RoomsList() {
         return;
       }
 
+      const platform: "whereby" | "daily" | null =
+        room.platform === "whereby" || room.platform === "daily"
+          ? room.platform
+          : null;
+
       const roomData = {
         name: room.name,
         zulip_auto_post: room.zulipAutoPost,
         zulip_stream: room.zulipStream,
         zulip_topic: room.zulipTopic,
         is_locked: room.isLocked,
-        room_mode: room.roomMode,
+        room_mode: platform === "daily" ? "group" : room.roomMode,
         recording_type: room.recordingType,
-        recording_trigger: room.recordingTrigger,
+        recording_trigger:
+          platform === "daily"
+            ? room.recordingType === "cloud"
+              ? "automatic-2nd-participant"
+              : "none"
+            : room.recordingTrigger,
         is_shared: room.isShared,
         webhook_url: room.webhookUrl,
         webhook_secret: room.webhookSecret,
         ics_url: room.icsUrl,
         ics_enabled: room.icsEnabled,
         ics_fetch_interval: room.icsFetchInterval,
+        platform,
       };
 
       if (isEditing) {
@@ -339,15 +373,21 @@ export default function RoomsList() {
       zulipStream: roomData.zulip_stream,
       zulipTopic: roomData.zulip_topic,
       isLocked: roomData.is_locked,
-      roomMode: roomData.room_mode,
+      roomMode: roomData.platform === "daily" ? "group" : roomData.room_mode, // Daily always uses 2-200
       recordingType: roomData.recording_type,
-      recordingTrigger: roomData.recording_trigger,
+      recordingTrigger:
+        roomData.platform === "daily"
+          ? roomData.recording_type === "cloud"
+            ? "automatic-2nd-participant"
+            : "none"
+          : roomData.recording_trigger,
       isShared: roomData.is_shared,
       webhookUrl: roomData.webhook_url || "",
       webhookSecret: roomData.webhook_secret || "",
       icsUrl: roomData.ics_url || "",
       icsEnabled: roomData.ics_enabled || false,
       icsFetchInterval: roomData.ics_fetch_interval || 5,
+      platform: roomData.platform,
     });
     setEditRoomId(roomId);
     setIsEditing(true);
@@ -482,6 +522,52 @@ export default function RoomsList() {
                       )}
                     </Field.Root>
 
+                    <Field.Root mt={4}>
+                      <Field.Label>Platform</Field.Label>
+                      <Select.Root
+                        value={[room.platform]}
+                        onValueChange={(e) => {
+                          const newPlatform = e.value[0] as "whereby" | "daily";
+                          const updates: Partial<typeof room> = {
+                            platform: newPlatform,
+                          };
+                          if (newPlatform === "daily") {
+                            updates.roomMode = "group";
+                            updates.recordingTrigger =
+                              room.recordingType === "cloud"
+                                ? "automatic-2nd-participant"
+                                : "none";
+                          } else {
+                            if (room.recordingType !== "cloud") {
+                              updates.recordingTrigger = "none";
+                            }
+                          }
+                          setRoomInput({ ...room, ...updates });
+                        }}
+                        collection={platformCollection}
+                      >
+                        <Select.HiddenSelect />
+                        <Select.Control>
+                          <Select.Trigger>
+                            <Select.ValueText placeholder="Select platform" />
+                          </Select.Trigger>
+                          <Select.IndicatorGroup>
+                            <Select.Indicator />
+                          </Select.IndicatorGroup>
+                        </Select.Control>
+                        <Select.Positioner>
+                          <Select.Content>
+                            {platformOptions.map((option) => (
+                              <Select.Item key={option.value} item={option}>
+                                {option.label}
+                                <Select.ItemIndicator />
+                              </Select.Item>
+                            ))}
+                          </Select.Content>
+                        </Select.Positioner>
+                      </Select.Root>
+                    </Field.Root>
+
                     <Field.Root mt={4}>
                       <Checkbox.Root
                         name="isLocked"
@@ -504,50 +590,95 @@ export default function RoomsList() {
                         <Checkbox.Label>Locked room</Checkbox.Label>
                       </Checkbox.Root>
                     </Field.Root>
+                    {room.platform !== "daily" && (
+                      <Field.Root mt={4}>
+                        <Field.Label>Room size</Field.Label>
+                        <Select.Root
+                          value={[room.roomMode]}
+                          onValueChange={(e) =>
+                            setRoomInput({ ...room, roomMode: e.value[0] })
+                          }
+                          collection={roomModeCollection}
+                        >
+                          <Select.HiddenSelect />
+                          <Select.Control>
+                            <Select.Trigger>
+                              <Select.ValueText placeholder="Select room size" />
+                            </Select.Trigger>
+                            <Select.IndicatorGroup>
+                              <Select.Indicator />
+                            </Select.IndicatorGroup>
+                          </Select.Control>
+                          <Select.Positioner>
+                            <Select.Content>
+                              {roomModeOptions.map((option) => (
+                                <Select.Item key={option.value} item={option}>
+                                  {option.label}
+                                  <Select.ItemIndicator />
+                                </Select.Item>
+                              ))}
+                            </Select.Content>
+                          </Select.Positioner>
+                        </Select.Root>
+                      </Field.Root>
+                    )}
                     <Field.Root mt={4}>
-                      <Field.Label>Room size</Field.Label>
-                      <Select.Root
-                        value={[room.roomMode]}
-                        onValueChange={(e) =>
-                          setRoomInput({ ...room, roomMode: e.value[0] })
-                        }
-                        collection={roomModeCollection}
-                      >
-                        <Select.HiddenSelect />
-                        <Select.Control>
-                          <Select.Trigger>
-                            <Select.ValueText placeholder="Select room size" />
-                          </Select.Trigger>
-                          <Select.IndicatorGroup>
-                            <Select.Indicator />
-                          </Select.IndicatorGroup>
-                        </Select.Control>
-                        <Select.Positioner>
-                          <Select.Content>
-                            {roomModeOptions.map((option) => (
-                              <Select.Item key={option.value} item={option}>
-                                {option.label}
-                                <Select.ItemIndicator />
-                              </Select.Item>
-                            ))}
-                          </Select.Content>
-                        </Select.Positioner>
-                      </Select.Root>
-                    </Field.Root>
-                    <Field.Root mt={4}>
-                      <Field.Label>Recording type</Field.Label>
+                      <HStack gap={2} alignItems="center">
+                        <Field.Label>Recording type</Field.Label>
+                        <Popover.Root>
+                          <Popover.Trigger asChild>
+                            <IconButton
+                              aria-label="Recording type help"
+                              variant="ghost"
+                              size="xs"
+                              colorPalette="gray"
+                            >
+                              <LuInfo />
+                            </IconButton>
+                          </Popover.Trigger>
+                          <Popover.Positioner>
+                            <Popover.Content>
+                              <Popover.Arrow />
+                              <Popover.Body>
+                                <Text fontSize="sm" lineHeight="1.6">
+                                  <strong>None:</strong> No recording will be
+                                  created.
+                                  <br />
+                                  <br />
+                                  <strong>Local:</strong> Recording happens on
+                                  each participant's device. Files are saved
+                                  locally.
+                                  <br />
+                                  <br />
+                                  <strong>Cloud:</strong> Recording happens on
+                                  the platform's servers and is available after
+                                  the meeting ends.
+                                </Text>
+                              </Popover.Body>
+                            </Popover.Content>
+                          </Popover.Positioner>
+                        </Popover.Root>
+                      </HStack>
                       <Select.Root
                         value={[room.recordingType]}
-                        onValueChange={(e) =>
-                          setRoomInput({
-                            ...room,
-                            recordingType: e.value[0],
-                            recordingTrigger:
-                              e.value[0] !== "cloud"
+                        onValueChange={(e) => {
+                          const newRecordingType = e.value[0];
+                          const updates: Partial<typeof room> = {
+                            recordingType: newRecordingType,
+                          };
+                          if (room.platform === "daily") {
+                            updates.recordingTrigger =
+                              newRecordingType === "cloud"
+                                ? "automatic-2nd-participant"
+                                : "none";
+                          } else {
+                            updates.recordingTrigger =
+                              newRecordingType !== "cloud"
                                 ? "none"
-                                : room.recordingTrigger,
-                          })
-                        }
+                                : room.recordingTrigger;
+                          }
+                          setRoomInput({ ...room, ...updates });
+                        }}
                         collection={recordingTypeCollection}
                       >
                         <Select.HiddenSelect />
@@ -571,40 +702,77 @@ export default function RoomsList() {
                         </Select.Positioner>
                       </Select.Root>
                     </Field.Root>
-                    <Field.Root mt={4}>
-                      <Field.Label>Cloud recording start trigger</Field.Label>
-                      <Select.Root
-                        value={[room.recordingTrigger]}
-                        onValueChange={(e) =>
-                          setRoomInput({
-                            ...room,
-                            recordingTrigger: e.value[0],
-                          })
-                        }
-                        collection={recordingTriggerCollection}
-                        disabled={room.recordingType !== "cloud"}
-                      >
-                        <Select.HiddenSelect />
-                        <Select.Control>
-                          <Select.Trigger>
-                            <Select.ValueText placeholder="Select trigger" />
-                          </Select.Trigger>
-                          <Select.IndicatorGroup>
-                            <Select.Indicator />
-                          </Select.IndicatorGroup>
-                        </Select.Control>
-                        <Select.Positioner>
-                          <Select.Content>
-                            {recordingTriggerOptions.map((option) => (
-                              <Select.Item key={option.value} item={option}>
-                                {option.label}
-                                <Select.ItemIndicator />
-                              </Select.Item>
-                            ))}
-                          </Select.Content>
-                        </Select.Positioner>
-                      </Select.Root>
-                    </Field.Root>
+                    {room.recordingType === "cloud" &&
+                      room.platform !== "daily" && (
+                        <Field.Root mt={4}>
+                          <HStack gap={2} alignItems="center">
+                            <Field.Label>Recording start trigger</Field.Label>
+                            <Popover.Root>
+                              <Popover.Trigger asChild>
+                                <IconButton
+                                  aria-label="Recording start trigger help"
+                                  variant="ghost"
+                                  size="xs"
+                                  colorPalette="gray"
+                                >
+                                  <LuInfo />
+                                </IconButton>
+                              </Popover.Trigger>
+                              <Popover.Positioner>
+                                <Popover.Content>
+                                  <Popover.Arrow />
+                                  <Popover.Body>
+                                    <Text fontSize="sm" lineHeight="1.6">
+                                      <strong>None:</strong> Recording must be
+                                      started manually by a participant.
+                                      <br />
+                                      <br />
+                                      <strong>Prompt:</strong> Participants will
+                                      be prompted to start recording when they
+                                      join.
+                                      <br />
+                                      <br />
+                                      <strong>Automatic:</strong> Recording
+                                      starts automatically when a second
+                                      participant joins.
+                                    </Text>
+                                  </Popover.Body>
+                                </Popover.Content>
+                              </Popover.Positioner>
+                            </Popover.Root>
+                          </HStack>
+                          <Select.Root
+                            value={[room.recordingTrigger]}
+                            onValueChange={(e) =>
+                              setRoomInput({
+                                ...room,
+                                recordingTrigger: e.value[0],
+                              })
+                            }
+                            collection={recordingTriggerCollection}
+                          >
+                            <Select.HiddenSelect />
+                            <Select.Control>
+                              <Select.Trigger>
+                                <Select.ValueText placeholder="Select trigger" />
+                              </Select.Trigger>
+                              <Select.IndicatorGroup>
+                                <Select.Indicator />
+                              </Select.IndicatorGroup>
+                            </Select.Control>
+                            <Select.Positioner>
+                              <Select.Content>
+                                {recordingTriggerOptions.map((option) => (
+                                  <Select.Item key={option.value} item={option}>
+                                    {option.label}
+                                    <Select.ItemIndicator />
+                                  </Select.Item>
+                                ))}
+                              </Select.Content>
+                            </Select.Positioner>
+                          </Select.Root>
+                        </Field.Root>
+                      )}
 
                     <Field.Root mt={4}>
                       <Checkbox.Root

www/app/(app)/transcripts/[transcriptId]/page.tsx

@@ -117,15 +117,6 @@ export default function TranscriptDetails(details: TranscriptDetails) {
     return <Modal title="Loading" text={"Loading transcript..."} />;
   }
 
-  if (mp3.error) {
-    return (
-      <Modal
-        title="Transcription error"
-        text={`There was an error loading the recording. Error: ${mp3.error}`}
-      />
-    );
-  }
-
   return (
     <>
       <Grid
@@ -147,7 +138,12 @@ export default function TranscriptDetails(details: TranscriptDetails) {
               />
             ) : !mp3.loading && (waveform.error || mp3.error) ? (
               <Box p={4} bg="red.100" borderRadius="md">
-                <Text>Error loading this recording</Text>
+                <Text>
+                  Error loading{" "}
+                  {[waveform.error && "waveform", mp3.error && "mp3"]
+                    .filter(Boolean)
+                    .join(" and ")}
+                </Text>
               </Box>
             ) : (
               <Skeleton h={14} />

www/app/[roomName]/components/DailyRoom.tsx

@@ -11,6 +11,7 @@ import {
   recordingTypeRequiresConsent,
 } from "../../lib/consent";
 import { useRoomJoinMeeting } from "../../lib/apiHooks";
+import { assertExists } from "../../lib/utils";
 
 type Meeting = components["schemas"]["Meeting"];
 
@@ -22,16 +23,15 @@ export default function DailyRoom({ meeting }: DailyRoomProps) {
   const router = useRouter();
   const params = useParams();
   const auth = useAuth();
-  const status = auth.status;
+  const authLastUserId = auth.lastUserId;
   const containerRef = useRef<HTMLDivElement>(null);
   const joinMutation = useRoomJoinMeeting();
   const [joinedMeeting, setJoinedMeeting] = useState<Meeting | null>(null);
 
   const roomName = params?.roomName as string;
 
-  // Always call /join to get a fresh token with user_id
   useEffect(() => {
-    if (status === "loading" || !meeting?.id || !roomName) return;
+    if (authLastUserId === undefined || !meeting?.id || !roomName) return;
 
     const join = async () => {
       try {
@@ -50,18 +50,17 @@ export default function DailyRoom({ meeting }: DailyRoomProps) {
     };
 
     join();
-  }, [meeting?.id, roomName, status]);
+  }, [meeting?.id, roomName, authLastUserId]);
 
-  const roomUrl = joinedMeeting?.host_room_url || joinedMeeting?.room_url;
-  const isLoading =
-    status === "loading" || joinMutation.isPending || !joinedMeeting;
+  const roomUrl = joinedMeeting?.room_url;
 
   const handleLeave = useCallback(() => {
     router.push("/browse");
   }, [router]);
 
   useEffect(() => {
-    if (isLoading || !roomUrl || !containerRef.current) return;
+    if (authLastUserId === undefined || !roomUrl || !containerRef.current)
+      return;
 
     let frame: DailyCall | null = null;
     let destroyed = false;
@@ -92,7 +91,15 @@ export default function DailyRoom({ meeting }: DailyRoomProps) {
 
         frame.on("joined-meeting", async () => {
           try {
-            await frame.startRecording({ type: "raw-tracks" });
+            const frameInstance = assertExists(
+              frame,
+              "frame object got lost somewhere after frame.on was called",
+            );
+
+            if (meeting.recording_type === "cloud") {
+              console.log("Starting cloud recording");
+              await frameInstance.startRecording({ type: "raw-tracks" });
+            }
           } catch (error) {
             console.error("Failed to start recording:", error);
           }
@@ -104,7 +111,9 @@ export default function DailyRoom({ meeting }: DailyRoomProps) {
       }
     };
 
-    createAndJoin();
+    createAndJoin().catch((error) => {
+      console.error("Failed to create and join meeting:", error);
+    });
 
     return () => {
       destroyed = true;
@@ -114,9 +123,9 @@ export default function DailyRoom({ meeting }: DailyRoomProps) {
         });
       }
     };
-  }, [roomUrl, isLoading, handleLeave]);
+  }, [roomUrl, authLastUserId, handleLeave]);
 
-  if (isLoading) {
+  if (authLastUserId === undefined) {
     return (
       <Center width="100vw" height="100vh">
         <Spinner size="xl" />

www/app/lib/AuthProvider.tsx

@@ -1,6 +1,6 @@
 "use client";
 
-import { createContext, useContext } from "react";
+import { createContext, useContext, useRef } from "react";
 import { useSession as useNextAuthSession } from "next-auth/react";
 import { signOut, signIn } from "next-auth/react";
 import { configureApiAuth } from "./apiClient";
@@ -25,6 +25,9 @@ type AuthContextType = (
   update: () => Promise<Session | null>;
   signIn: typeof signIn;
   signOut: typeof signOut;
+  // TODO probably rename isLoading to isReloading and make THIS field "isLoading"
+  // undefined is "not known", null is "is certainly logged out"
+  lastUserId: CustomSession["user"]["id"] | null | undefined;
 };
 
 const AuthContext = createContext<AuthContextType | undefined>(undefined);
@@ -41,10 +44,15 @@ const noopAuthContext: AuthContextType = {
   signOut: async () => {
     throw new Error("signOut not supposed to be called");
   },
+  lastUserId: undefined,
 };
 
 export function AuthProvider({ children }: { children: React.ReactNode }) {
   const { data: session, status, update } = useNextAuthSession();
+  // referential comparison done in component, must be primitive /or cached
+  const lastUserId = useRef<CustomSession["user"]["id"] | null | undefined>(
+    null,
+  );
 
   const contextValue: AuthContextType = isAuthEnabled
     ? {
@@ -73,11 +81,16 @@ export function AuthProvider({ children }: { children: React.ReactNode }) {
             case "authenticated": {
               const customSession = assertCustomSession(session);
               if (customSession?.error === REFRESH_ACCESS_TOKEN_ERROR) {
+                // warning: call order-dependent
+                lastUserId.current = null;
                 // token had expired but next auth still returns "authenticated" so show user unauthenticated state
                 return {
                   status: "unauthenticated" as const,
                 };
               } else if (customSession?.accessToken) {
+                // updates anyways with updated properties below
+                // warning! execution order conscience, must be ran before reading lastUserId.current below
+                lastUserId.current = customSession.user.id;
                 return {
                   status,
                   accessToken: customSession.accessToken,
@@ -92,6 +105,8 @@ export function AuthProvider({ children }: { children: React.ReactNode }) {
               }
             }
             case "unauthenticated": {
+              // warning: call order-dependent
+              lastUserId.current = null;
               return { status: "unauthenticated" as const };
             }
             default: {
@@ -103,6 +118,8 @@ export function AuthProvider({ children }: { children: React.ReactNode }) {
         update,
         signIn,
         signOut,
+        // for optimistic cases when we assume "loading" doesn't immediately invalidate the user
+        lastUserId: lastUserId.current,
       }
     : noopAuthContext;
 

www/app/lib/authBackend.ts

@@ -148,7 +148,7 @@ export const authOptions = (): AuthOptions =>
           },
           async session({ session, token }) {
             const extendedToken = token as JWTWithAccessToken;
-
+            console.log("extendedToken", extendedToken);
             const userId = await getUserId(extendedToken.accessToken);
 
             return {

www/package.json

@@ -31,7 +31,7 @@
     "ioredis": "^5.7.0",
     "jest-worker": "^29.6.2",
     "lucide-react": "^0.525.0",
-    "next": "^15.5.3",
+    "next": "^15.5.7",
     "next-auth": "^4.24.7",
     "next-themes": "^0.4.6",
     "nuqs": "^2.4.3",

www/pnpm-lock.yaml

@@ -27,7 +27,7 @@ importers:
         version: 0.2.3(@fortawesome/fontawesome-svg-core@6.7.2)(react@18.3.1)
       "@sentry/nextjs":
         specifier: ^10.11.0
-        version: 10.11.0(@opentelemetry/context-async-hooks@2.1.0(@opentelemetry/api@1.9.0))(@opentelemetry/core@2.1.0(@opentelemetry/api@1.9.0))(@opentelemetry/sdk-trace-base@2.1.0(@opentelemetry/api@1.9.0))(next@15.5.3(@babel/core@7.28.3)(@opentelemetry/api@1.9.0)(babel-plugin-macros@3.1.0)(react-dom@18.3.1(react@18.3.1))(react@18.3.1)(sass@1.90.0))(react@18.3.1)(webpack@5.101.3)
+        version: 10.11.0(@opentelemetry/context-async-hooks@2.1.0(@opentelemetry/api@1.9.0))(@opentelemetry/core@2.1.0(@opentelemetry/api@1.9.0))(@opentelemetry/sdk-trace-base@2.1.0(@opentelemetry/api@1.9.0))(next@15.5.7(@babel/core@7.28.3)(@opentelemetry/api@1.9.0)(babel-plugin-macros@3.1.0)(react-dom@18.3.1(react@18.3.1))(react@18.3.1)(sass@1.90.0))(react@18.3.1)(webpack@5.101.3)
       "@tanstack/react-query":
         specifier: ^5.85.9
         version: 5.85.9(react@18.3.1)
@@ -62,17 +62,17 @@ importers:
         specifier: ^0.525.0
         version: 0.525.0(react@18.3.1)
       next:
-        specifier: ^15.5.3
-        version: 15.5.3(@babel/core@7.28.3)(@opentelemetry/api@1.9.0)(babel-plugin-macros@3.1.0)(react-dom@18.3.1(react@18.3.1))(react@18.3.1)(sass@1.90.0)
+        specifier: ^15.5.7
+        version: 15.5.7(@babel/core@7.28.3)(@opentelemetry/api@1.9.0)(babel-plugin-macros@3.1.0)(react-dom@18.3.1(react@18.3.1))(react@18.3.1)(sass@1.90.0)
       next-auth:
         specifier: ^4.24.7
-        version: 4.24.11(next@15.5.3(@babel/core@7.28.3)(@opentelemetry/api@1.9.0)(babel-plugin-macros@3.1.0)(react-dom@18.3.1(react@18.3.1))(react@18.3.1)(sass@1.90.0))(react-dom@18.3.1(react@18.3.1))(react@18.3.1)
+        version: 4.24.11(next@15.5.7(@babel/core@7.28.3)(@opentelemetry/api@1.9.0)(babel-plugin-macros@3.1.0)(react-dom@18.3.1(react@18.3.1))(react@18.3.1)(sass@1.90.0))(react-dom@18.3.1(react@18.3.1))(react@18.3.1)
       next-themes:
         specifier: ^0.4.6
         version: 0.4.6(react-dom@18.3.1(react@18.3.1))(react@18.3.1)
       nuqs:
         specifier: ^2.4.3
-        version: 2.4.3(next@15.5.3(@babel/core@7.28.3)(@opentelemetry/api@1.9.0)(babel-plugin-macros@3.1.0)(react-dom@18.3.1(react@18.3.1))(react@18.3.1)(sass@1.90.0))(react@18.3.1)
+        version: 2.4.3(next@15.5.7(@babel/core@7.28.3)(@opentelemetry/api@1.9.0)(babel-plugin-macros@3.1.0)(react-dom@18.3.1(react@18.3.1))(react@18.3.1)(sass@1.90.0))(react@18.3.1)
       openapi-fetch:
         specifier: ^0.14.0
         version: 0.14.0
@@ -1184,10 +1184,10 @@ packages:
         integrity: sha512-ZVWUcfwY4E/yPitQJl481FjFo3K22D6qF0DuFH6Y/nbnE11GY5uguDxZMGXPQ8WQ0128MXQD7TnfHyK4oWoIJQ==,
       }
 
-  "@next/env@15.5.3":
+  "@next/env@15.5.7":
     resolution:
       {
-        integrity: sha512-RSEDTRqyihYXygx/OJXwvVupfr9m04+0vH8vyy0HfZ7keRto6VX9BbEk0J2PUk0VGy6YhklJUSrgForov5F9pw==,
+        integrity: sha512-4h6Y2NyEkIEN7Z8YxkA27pq6zTkS09bUSYC0xjd0NpwFxjnIKeZEeH591o5WECSmjpUhLn3H2QLJcDye3Uzcvg==,
       }
 
   "@next/eslint-plugin-next@15.5.3":
@@ -1196,73 +1196,73 @@ packages:
         integrity: sha512-SdhaKdko6dpsSr0DldkESItVrnPYB1NS2NpShCSX5lc7SSQmLZt5Mug6t2xbiuVWEVDLZSuIAoQyYVBYp0dR5g==,
       }
 
-  "@next/swc-darwin-arm64@15.5.3":
+  "@next/swc-darwin-arm64@15.5.7":
     resolution:
       {
-        integrity: sha512-nzbHQo69+au9wJkGKTU9lP7PXv0d1J5ljFpvb+LnEomLtSbJkbZyEs6sbF3plQmiOB2l9OBtN2tNSvCH1nQ9Jg==,
+        integrity: sha512-IZwtxCEpI91HVU/rAUOOobWSZv4P2DeTtNaCdHqLcTJU4wdNXgAySvKa/qJCgR5m6KI8UsKDXtO2B31jcaw1Yw==,
       }
     engines: { node: ">= 10" }
     cpu: [arm64]
     os: [darwin]
 
-  "@next/swc-darwin-x64@15.5.3":
+  "@next/swc-darwin-x64@15.5.7":
     resolution:
       {
-        integrity: sha512-w83w4SkOOhekJOcA5HBvHyGzgV1W/XvOfpkrxIse4uPWhYTTRwtGEM4v/jiXwNSJvfRvah0H8/uTLBKRXlef8g==,
+        integrity: sha512-UP6CaDBcqaCBuiq/gfCEJw7sPEoX1aIjZHnBWN9v9qYHQdMKvCKcAVs4OX1vIjeE+tC5EIuwDTVIoXpUes29lg==,
       }
     engines: { node: ">= 10" }
     cpu: [x64]
     os: [darwin]
 
-  "@next/swc-linux-arm64-gnu@15.5.3":
+  "@next/swc-linux-arm64-gnu@15.5.7":
     resolution:
       {
-        integrity: sha512-+m7pfIs0/yvgVu26ieaKrifV8C8yiLe7jVp9SpcIzg7XmyyNE7toC1fy5IOQozmr6kWl/JONC51osih2RyoXRw==,
+        integrity: sha512-NCslw3GrNIw7OgmRBxHtdWFQYhexoUCq+0oS2ccjyYLtcn1SzGzeM54jpTFonIMUjNbHmpKpziXnpxhSWLcmBA==,
       }
     engines: { node: ">= 10" }
     cpu: [arm64]
     os: [linux]
 
-  "@next/swc-linux-arm64-musl@15.5.3":
+  "@next/swc-linux-arm64-musl@15.5.7":
     resolution:
       {
-        integrity: sha512-u3PEIzuguSenoZviZJahNLgCexGFhso5mxWCrrIMdvpZn6lkME5vc/ADZG8UUk5K1uWRy4hqSFECrON6UKQBbQ==,
+        integrity: sha512-nfymt+SE5cvtTrG9u1wdoxBr9bVB7mtKTcj0ltRn6gkP/2Nu1zM5ei8rwP9qKQP0Y//umK+TtkKgNtfboBxRrw==,
       }
     engines: { node: ">= 10" }
     cpu: [arm64]
     os: [linux]
 
-  "@next/swc-linux-x64-gnu@15.5.3":
+  "@next/swc-linux-x64-gnu@15.5.7":
     resolution:
       {
-        integrity: sha512-lDtOOScYDZxI2BENN9m0pfVPJDSuUkAD1YXSvlJF0DKwZt0WlA7T7o3wrcEr4Q+iHYGzEaVuZcsIbCps4K27sA==,
+        integrity: sha512-hvXcZvCaaEbCZcVzcY7E1uXN9xWZfFvkNHwbe/n4OkRhFWrs1J1QV+4U1BN06tXLdaS4DazEGXwgqnu/VMcmqw==,
       }
     engines: { node: ">= 10" }
     cpu: [x64]
     os: [linux]
 
-  "@next/swc-linux-x64-musl@15.5.3":
+  "@next/swc-linux-x64-musl@15.5.7":
     resolution:
       {
-        integrity: sha512-9vWVUnsx9PrY2NwdVRJ4dUURAQ8Su0sLRPqcCCxtX5zIQUBES12eRVHq6b70bbfaVaxIDGJN2afHui0eDm+cLg==,
+        integrity: sha512-4IUO539b8FmF0odY6/SqANJdgwn1xs1GkPO5doZugwZ3ETF6JUdckk7RGmsfSf7ws8Qb2YB5It33mvNL/0acqA==,
       }
     engines: { node: ">= 10" }
     cpu: [x64]
     os: [linux]
 
-  "@next/swc-win32-arm64-msvc@15.5.3":
+  "@next/swc-win32-arm64-msvc@15.5.7":
     resolution:
       {
-        integrity: sha512-1CU20FZzY9LFQigRi6jM45oJMU3KziA5/sSG+dXeVaTm661snQP6xu3ykGxxwU5sLG3sh14teO/IOEPVsQMRfA==,
+        integrity: sha512-CpJVTkYI3ZajQkC5vajM7/ApKJUOlm6uP4BknM3XKvJ7VXAvCqSjSLmM0LKdYzn6nBJVSjdclx8nYJSa3xlTgQ==,
       }
     engines: { node: ">= 10" }
     cpu: [arm64]
     os: [win32]
 
-  "@next/swc-win32-x64-msvc@15.5.3":
+  "@next/swc-win32-x64-msvc@15.5.7":
     resolution:
       {
-        integrity: sha512-JMoLAq3n3y5tKXPQwCK5c+6tmwkuFDa2XAxz8Wm4+IVthdBZdZGh+lmiLUHg9f9IDwIQpUjp+ysd6OkYTyZRZw==,
+        integrity: sha512-gMzgBX164I6DN+9/PGA+9dQiwmTkE4TloBNx8Kv9UiGARsr9Nba7IpcBRA1iTV9vwlYnrE3Uy6I7Aj6qLjQuqw==,
       }
     engines: { node: ">= 10" }
     cpu: [x64]
@@ -6863,10 +6863,10 @@ packages:
       react: ^16.8 || ^17 || ^18 || ^19 || ^19.0.0-rc
       react-dom: ^16.8 || ^17 || ^18 || ^19 || ^19.0.0-rc
 
-  next@15.5.3:
+  next@15.5.7:
     resolution:
       {
-        integrity: sha512-r/liNAx16SQj4D+XH/oI1dlpv9tdKJ6cONYPwwcCC46f2NjpaRWY+EKCzULfgQYV6YKXjHBchff2IZBSlZmJNw==,
+        integrity: sha512-+t2/0jIJ48kUpGKkdlhgkv+zPTEOoXyr60qXe68eB/pl3CMJaLeIGjzp5D6Oqt25hCBiBTt8wEeeAzfJvUKnPQ==,
       }
     engines: { node: ^18.18.0 || ^19.8.0 || >= 20.0.0 }
     hasBin: true
@@ -9877,34 +9877,34 @@ snapshots:
       "@tybys/wasm-util": 0.10.0
     optional: true
 
-  "@next/env@15.5.3": {}
+  "@next/env@15.5.7": {}
 
   "@next/eslint-plugin-next@15.5.3":
     dependencies:
       fast-glob: 3.3.1
 
-  "@next/swc-darwin-arm64@15.5.3":
+  "@next/swc-darwin-arm64@15.5.7":
     optional: true
 
-  "@next/swc-darwin-x64@15.5.3":
+  "@next/swc-darwin-x64@15.5.7":
     optional: true
 
-  "@next/swc-linux-arm64-gnu@15.5.3":
+  "@next/swc-linux-arm64-gnu@15.5.7":
     optional: true
 
-  "@next/swc-linux-arm64-musl@15.5.3":
+  "@next/swc-linux-arm64-musl@15.5.7":
     optional: true
 
-  "@next/swc-linux-x64-gnu@15.5.3":
+  "@next/swc-linux-x64-gnu@15.5.7":
     optional: true
 
-  "@next/swc-linux-x64-musl@15.5.3":
+  "@next/swc-linux-x64-musl@15.5.7":
     optional: true
 
-  "@next/swc-win32-arm64-msvc@15.5.3":
+  "@next/swc-win32-arm64-msvc@15.5.7":
     optional: true
 
-  "@next/swc-win32-x64-msvc@15.5.3":
+  "@next/swc-win32-x64-msvc@15.5.7":
     optional: true
 
   "@nodelib/fs.scandir@2.1.5":
@@ -10684,7 +10684,7 @@ snapshots:
 
   "@sentry/core@8.55.0": {}
 
-  "@sentry/nextjs@10.11.0(@opentelemetry/context-async-hooks@2.1.0(@opentelemetry/api@1.9.0))(@opentelemetry/core@2.1.0(@opentelemetry/api@1.9.0))(@opentelemetry/sdk-trace-base@2.1.0(@opentelemetry/api@1.9.0))(next@15.5.3(@babel/core@7.28.3)(@opentelemetry/api@1.9.0)(babel-plugin-macros@3.1.0)(react-dom@18.3.1(react@18.3.1))(react@18.3.1)(sass@1.90.0))(react@18.3.1)(webpack@5.101.3)":
+  "@sentry/nextjs@10.11.0(@opentelemetry/context-async-hooks@2.1.0(@opentelemetry/api@1.9.0))(@opentelemetry/core@2.1.0(@opentelemetry/api@1.9.0))(@opentelemetry/sdk-trace-base@2.1.0(@opentelemetry/api@1.9.0))(next@15.5.7(@babel/core@7.28.3)(@opentelemetry/api@1.9.0)(babel-plugin-macros@3.1.0)(react-dom@18.3.1(react@18.3.1))(react@18.3.1)(sass@1.90.0))(react@18.3.1)(webpack@5.101.3)":
     dependencies:
       "@opentelemetry/api": 1.9.0
       "@opentelemetry/semantic-conventions": 1.37.0
@@ -10698,7 +10698,7 @@ snapshots:
       "@sentry/vercel-edge": 10.11.0
       "@sentry/webpack-plugin": 4.3.0(webpack@5.101.3)
       chalk: 3.0.0
-      next: 15.5.3(@babel/core@7.28.3)(@opentelemetry/api@1.9.0)(babel-plugin-macros@3.1.0)(react-dom@18.3.1(react@18.3.1))(react@18.3.1)(sass@1.90.0)
+      next: 15.5.7(@babel/core@7.28.3)(@opentelemetry/api@1.9.0)(babel-plugin-macros@3.1.0)(react-dom@18.3.1(react@18.3.1))(react@18.3.1)(sass@1.90.0)
       resolve: 1.22.8
       rollup: 4.50.1
       stacktrace-parser: 0.1.11
@@ -14093,13 +14093,13 @@ snapshots:
 
   neo-async@2.6.2: {}
 
-  next-auth@4.24.11(next@15.5.3(@babel/core@7.28.3)(@opentelemetry/api@1.9.0)(babel-plugin-macros@3.1.0)(react-dom@18.3.1(react@18.3.1))(react@18.3.1)(sass@1.90.0))(react-dom@18.3.1(react@18.3.1))(react@18.3.1):
+  next-auth@4.24.11(next@15.5.7(@babel/core@7.28.3)(@opentelemetry/api@1.9.0)(babel-plugin-macros@3.1.0)(react-dom@18.3.1(react@18.3.1))(react@18.3.1)(sass@1.90.0))(react-dom@18.3.1(react@18.3.1))(react@18.3.1):
     dependencies:
       "@babel/runtime": 7.28.2
       "@panva/hkdf": 1.2.1
       cookie: 0.7.2
       jose: 4.15.9
-      next: 15.5.3(@babel/core@7.28.3)(@opentelemetry/api@1.9.0)(babel-plugin-macros@3.1.0)(react-dom@18.3.1(react@18.3.1))(react@18.3.1)(sass@1.90.0)
+      next: 15.5.7(@babel/core@7.28.3)(@opentelemetry/api@1.9.0)(babel-plugin-macros@3.1.0)(react-dom@18.3.1(react@18.3.1))(react@18.3.1)(sass@1.90.0)
       oauth: 0.9.15
       openid-client: 5.7.1
       preact: 10.27.0
@@ -14113,9 +14113,9 @@ snapshots:
       react: 18.3.1
       react-dom: 18.3.1(react@18.3.1)
 
-  next@15.5.3(@babel/core@7.28.3)(@opentelemetry/api@1.9.0)(babel-plugin-macros@3.1.0)(react-dom@18.3.1(react@18.3.1))(react@18.3.1)(sass@1.90.0):
+  next@15.5.7(@babel/core@7.28.3)(@opentelemetry/api@1.9.0)(babel-plugin-macros@3.1.0)(react-dom@18.3.1(react@18.3.1))(react@18.3.1)(sass@1.90.0):
     dependencies:
-      "@next/env": 15.5.3
+      "@next/env": 15.5.7
       "@swc/helpers": 0.5.15
       caniuse-lite: 1.0.30001734
       postcss: 8.4.31
@@ -14123,14 +14123,14 @@ snapshots:
       react-dom: 18.3.1(react@18.3.1)
       styled-jsx: 5.1.6(@babel/core@7.28.3)(babel-plugin-macros@3.1.0)(react@18.3.1)
     optionalDependencies:
-      "@next/swc-darwin-arm64": 15.5.3
-      "@next/swc-darwin-x64": 15.5.3
-      "@next/swc-linux-arm64-gnu": 15.5.3
-      "@next/swc-linux-arm64-musl": 15.5.3
-      "@next/swc-linux-x64-gnu": 15.5.3
-      "@next/swc-linux-x64-musl": 15.5.3
-      "@next/swc-win32-arm64-msvc": 15.5.3
-      "@next/swc-win32-x64-msvc": 15.5.3
+      "@next/swc-darwin-arm64": 15.5.7
+      "@next/swc-darwin-x64": 15.5.7
+      "@next/swc-linux-arm64-gnu": 15.5.7
+      "@next/swc-linux-arm64-musl": 15.5.7
+      "@next/swc-linux-x64-gnu": 15.5.7
+      "@next/swc-linux-x64-musl": 15.5.7
+      "@next/swc-win32-arm64-msvc": 15.5.7
+      "@next/swc-win32-x64-msvc": 15.5.7
       "@opentelemetry/api": 1.9.0
       sass: 1.90.0
       sharp: 0.34.3
@@ -14159,12 +14159,12 @@ snapshots:
     dependencies:
       path-key: 3.1.1
 
-  nuqs@2.4.3(next@15.5.3(@babel/core@7.28.3)(@opentelemetry/api@1.9.0)(babel-plugin-macros@3.1.0)(react-dom@18.3.1(react@18.3.1))(react@18.3.1)(sass@1.90.0))(react@18.3.1):
+  nuqs@2.4.3(next@15.5.7(@babel/core@7.28.3)(@opentelemetry/api@1.9.0)(babel-plugin-macros@3.1.0)(react-dom@18.3.1(react@18.3.1))(react@18.3.1)(sass@1.90.0))(react@18.3.1):
     dependencies:
       mitt: 3.0.1
       react: 18.3.1
     optionalDependencies:
-      next: 15.5.3(@babel/core@7.28.3)(@opentelemetry/api@1.9.0)(babel-plugin-macros@3.1.0)(react-dom@18.3.1(react@18.3.1))(react@18.3.1)(sass@1.90.0)
+      next: 15.5.7(@babel/core@7.28.3)(@opentelemetry/api@1.9.0)(babel-plugin-macros@3.1.0)(react-dom@18.3.1(react@18.3.1))(react@18.3.1)(sass@1.90.0)
 
   oauth@0.9.15: {}