build(deps): bump the uv group across 2 directories with 16 updates (#886 )

* build(deps): bump the uv group across 2 directories with 16 updates --- updated-dependencies: - dependency-name: aiohttp dependency-version: 3.13.3 dependency-type: indirect dependency-group: uv - dependency-name: filelock dependency-version: 3.20.3 dependency-type: indirect dependency-group: uv - dependency-name: fonttools dependency-version: 4.60.2 dependency-type: indirect dependency-group: uv - dependency-name: pillow dependency-version: 12.1.1 dependency-type: indirect dependency-group: uv - dependency-name: protobuf dependency-version: 6.33.5 dependency-type: indirect dependency-group: uv - dependency-name: python-multipart dependency-version: 0.0.22 dependency-type: indirect dependency-group: uv - dependency-name: starlette dependency-version: 0.49.1 dependency-type: indirect dependency-group: uv - dependency-name: urllib3 dependency-version: 2.6.3 dependency-type: indirect dependency-group: uv - dependency-name: aiohttp dependency-version: 3.13.3 dependency-type: indirect dependency-group: uv - dependency-name: protobuf dependency-version: 6.33.5 dependency-type: indirect dependency-group: uv - dependency-name: python-multipart dependency-version: 0.0.22 dependency-type: indirect dependency-group: uv - dependency-name: filelock dependency-version: 3.20.3 dependency-type: indirect dependency-group: uv - dependency-name: pillow dependency-version: 12.1.1 dependency-type: indirect dependency-group: uv - dependency-name: starlette dependency-version: 0.49.1 dependency-type: indirect dependency-group: uv - dependency-name: urllib3 dependency-version: 2.6.3 dependency-type: indirect dependency-group: uv - dependency-name: sentencepiece dependency-version: 0.2.1 dependency-type: direct:production dependency-group: uv - dependency-name: aiohttp dependency-version: 3.13.3 dependency-type: direct:production dependency-group: uv - dependency-name: filelock dependency-version: 3.20.3 dependency-type: indirect dependency-group: uv - dependency-name: pillow dependency-version: 12.1.1 dependency-type: indirect dependency-group: uv - dependency-name: protobuf dependency-version: 6.33.5 dependency-type: direct:production dependency-group: uv - dependency-name: python-multipart dependency-version: 0.0.22 dependency-type: direct:production dependency-group: uv - dependency-name: starlette dependency-version: 0.49.1 dependency-type: indirect dependency-group: uv - dependency-name: urllib3 dependency-version: 2.6.3 dependency-type: indirect dependency-group: uv - dependency-name: aiohttp dependency-version: 3.13.3 dependency-type: direct:production dependency-group: uv - dependency-name: sentencepiece dependency-version: 0.2.1 dependency-type: direct:production dependency-group: uv - dependency-name: protobuf dependency-version: 6.33.5 dependency-type: direct:production dependency-group: uv - dependency-name: python-multipart dependency-version: 0.0.22 dependency-type: direct:production dependency-group: uv - dependency-name: llama-index dependency-version: 0.13.0 dependency-type: direct:production dependency-group: uv - dependency-name: black dependency-version: 24.3.0 dependency-type: direct:development dependency-group: uv - dependency-name: cryptography dependency-version: 46.0.5 dependency-type: indirect dependency-group: uv - dependency-name: filelock dependency-version: 3.20.3 dependency-type: indirect dependency-group: uv - dependency-name: llama-index-core dependency-version: 0.13.6 dependency-type: indirect dependency-group: uv - dependency-name: marshmallow dependency-version: 3.26.2 dependency-type: indirect dependency-group: uv - dependency-name: pillow dependency-version: 12.1.1 dependency-type: indirect dependency-group: uv - dependency-name: pyasn1 dependency-version: 0.6.2 dependency-type: indirect dependency-group: uv - dependency-name: pypdf dependency-version: 6.7.3 dependency-type: indirect dependency-group: uv - dependency-name: starlette dependency-version: 0.49.1 dependency-type: indirect dependency-group: uv - dependency-name: urllib3 dependency-version: 2.6.3 dependency-type: indirect dependency-group: uv ... Signed-off-by: dependabot[bot] <support@github.com> * Upgrade fastapi-pagination and pydanti --------- Signed-off-by: dependabot[bot] <support@github.com> Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com> Co-authored-by: Sergey Mankovsky <sergey@mankovsky.dev>
build(deps): bump the npm_and_yarn group across 1 directory with 11 updates (#887 )
2026-03-22 07:06:47 +00:00 · 2026-02-26 03:26:59 +01:00 · 2026-02-26 00:22:41 +01:00 · 2026-02-26 00:00:22 +01:00 · 2026-02-25 17:58:13 -05:00 · 2026-02-25 23:34:33 +01:00
24 changed files with 3472 additions and 3259 deletions
--- a/.github/workflows/test_server.yml
+++ b/.github/workflows/test_server.yml
@@ -34,7 +34,7 @@ jobs:
          uv run -m pytest -v tests

  docker-amd64:
-    runs-on: linux-amd64
+    runs-on: [linux-amd64]
    concurrency:
      group: docker-amd64-${{ github.ref }}
      cancel-in-progress: true
@@ -52,12 +52,14 @@ jobs:
          github-token: ${{ secrets.GHA_CACHE_TOKEN }}

  docker-arm64:
-    runs-on: linux-arm64
+    runs-on: [linux-arm64]
    concurrency:
      group: docker-arm64-${{ github.ref }}
      cancel-in-progress: true
    steps:
      - uses: actions/checkout@v4
+      - name: Wait for Docker daemon
+        run: while ! docker version; do sleep 1; done
      - name: Set up Docker Buildx
        uses: docker/setup-buildx-action@v3
      - name: Build ARM64
--- a/.pre-commit-config.yaml
+++ b/.pre-commit-config.yaml
@@ -6,7 +6,7 @@ repos:
      - id: format
        name: run format
        language: system
-        entry: bash -c 'source "$HOME/.nvm/nvm.sh" && cd www && pnpm format'
+        entry: bash -c 'if [ -f "$HOME/.nvm/nvm.sh" ]; then source "$HOME/.nvm/nvm.sh"; fi; cd www && pnpm format'
        pass_filenames: false
        files: ^www/

--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -1,5 +1,13 @@
 # Changelog

+## [0.35.1](https://github.com/GreyhavenHQ/reflector/compare/v0.35.0...v0.35.1) (2026-02-25)
+
+
+### Bug Fixes
+
+* enable sentry on frontend ([#876](https://github.com/GreyhavenHQ/reflector/issues/876)) ([bc6bb63](https://github.com/GreyhavenHQ/reflector/commit/bc6bb63c32dc84be5d3b00388618d53f04f64e35))
+* switch structured output to tool-call with reflection retry ([#879](https://github.com/GreyhavenHQ/reflector/issues/879)) ([5d54758](https://github.com/GreyhavenHQ/reflector/commit/5d547586ef0f54514d1d65aacca8e57869013a82))
+
 ## [0.35.0](https://github.com/Monadical-SAS/reflector/compare/v0.34.0...v0.35.0) (2026-02-23)


--- a/README.md
+++ b/README.md
@@ -34,6 +34,8 @@ Reflector is an AI-powered audio transcription and meeting analysis platform tha
  </tr>
 </table>

+<p align="center" style="font-size: 1.5em; font-weight: bold;">By <a href="https://greyhaven.co">Greyhaven</a></p>
+
 ## What is Reflector?

 Reflector is a web application that utilizes local models to process audio content, providing:
@@ -210,7 +212,13 @@ All new contributions should be made in a separate branch, and goes through a Pu

 ## Future Plans

- **Daily.co integration with multitrack processing**: Support for Daily.co live rooms with per-participant audio tracks for improved diarization and transcription quality.
+- **Multi-language support enhancement**: Default language selection per room/user, automatic language detection improvements, multi-language diarization, and RTL language UI support
+- **Jitsi integration**: Self-hosted video conferencing rooms with no external API keys, full control over video infrastructure, and enhanced privacy
+- **Calendar integration**: Google Calendar and Microsoft Outlook synchronization, automatic meeting room creation, and post-meeting transcript delivery
+- **Enhanced analytics**: Meeting insights dashboard, speaker participation metrics, topic trends over time, and team collaboration patterns
+- **Advanced AI features**: Real-time sentiment analysis, emotion detection, meeting quality scores, and automated coaching suggestions
+- **Integration ecosystem**: Slack/Teams notifications, CRM integration (Salesforce, HubSpot), project management tools (Jira, Asana), and knowledge bases (Notion, Confluence)
+- **Performance improvements**: WebAssembly for client-side processing, edge computing support, and network optimization

 ## Legacy Documentation

--- a/docker-compose.yml
+++ b/docker-compose.yml
@@ -83,25 +83,21 @@ services:
    ports:
      - 6379:6379
  web:
-    image: node:22-alpine
+    build:
+      context: ./www
+      dockerfile: Dockerfile
    ports:
      - "3000:3000"
-    command: sh -c "corepack enable && pnpm install && pnpm dev"
-    restart: unless-stopped
-    working_dir: /app
-    volumes:
-      - ./www:/app/
-      - /app/node_modules
-      - next_cache:/app/.next
    env_file:
      - ./www/.env.local
    environment:
-      - NODE_ENV=development
-      - SERVER_API_URL=http://host.docker.internal:1250
+      NODE_ENV: development
+      SERVER_API_URL: http://host.docker.internal:1250
    extra_hosts:
      - "host.docker.internal:host-gateway"
    depends_on:
-      - server
+      redis:
+        condition: service_started

  postgres:
    image: postgres:17
--- a/docsv2/selfhosted-production.md
+++ b/docsv2/selfhosted-production.md
@@ -39,7 +39,6 @@ Deploy Reflector on a single server with everything running in Docker. Transcrip
  - **Any S3-compatible provider** (Backblaze B2, Cloudflare R2, DigitalOcean Spaces, etc.): same fields + custom endpoint URL

 **Optional add-ons (configure after initial setup):**
- **Daily.co** (live meeting rooms): Requires a Daily.co account (https://www.daily.co/), API key, subdomain, and an AWS S3 bucket + IAM Role for recording storage. See [Enabling Daily.co Live Rooms](#enabling-dailyco-live-rooms) below.
 - **Authentik** (user authentication): Requires an Authentik instance with an OAuth2/OIDC application configured for Reflector. See [Enabling Authentication](#enabling-authentication-authentik) below.

 ## Quick Start
@@ -86,6 +85,21 @@ Optionally add `--ollama-gpu` or `--ollama-cpu` for a **local Ollama instance**
 | `--llm-model MODEL` | Choose which Ollama model to download (default: `qwen2.5:14b`) | `--ollama-gpu` or `--ollama-cpu` |
 | *(omitted)* | User configures external LLM (OpenAI, Anthropic, etc.) | LLM API key |

+### macOS / Apple Silicon
+
+`--ollama-gpu` requires an NVIDIA GPU and **does not work on macOS**. Docker on macOS cannot access Apple GPU acceleration, so the containerized Ollama will run on CPU only regardless of the flag used.
+
+For the best performance on Mac, we recommend running Ollama **natively outside Docker** (install from https://ollama.com) — this gives Ollama direct access to Apple Metal GPU acceleration. Then omit `--ollama-gpu`/`--ollama-cpu` from the setup script and point the backend to your local Ollama instance:
+
+```env
+# In server/.env
+LLM_URL=http://host.docker.internal:11434/v1
+LLM_MODEL=qwen2.5:14b
+LLM_API_KEY=not-needed
+```
+
+`--ollama-cpu` does work on macOS but will be significantly slower than a native Ollama install with Metal acceleration.
+
 ### Choosing an Ollama model

 The default model is `qwen2.5:14b` (~9GB download, good multilingual support and summary quality). Override with `--llm-model`:
@@ -339,23 +353,6 @@ By default, authentication is disabled (`AUTH_BACKEND=none`, `FEATURE_REQUIRE_LO
   ```
 5. Restart: `docker compose -f docker-compose.selfhosted.yml down && ./scripts/setup-selfhosted.sh <same-flags>`

-## Enabling Daily.co Live Rooms
-
-Daily.co enables real-time meeting rooms with automatic recording and transcription.
-
-1. Create a [Daily.co](https://www.daily.co/) account
-2. Add to `server/.env`:
-   ```env
-   DEFAULT_VIDEO_PLATFORM=daily
-   DAILY_API_KEY=your-daily-api-key
-   DAILY_SUBDOMAIN=your-subdomain
-   DAILY_WEBHOOK_SECRET=your-webhook-secret
-   DAILYCO_STORAGE_AWS_BUCKET_NAME=reflector-dailyco
-   DAILYCO_STORAGE_AWS_REGION=us-east-1
-   DAILYCO_STORAGE_AWS_ROLE_ARN=arn:aws:iam::role/DailyCoAccess
-   ```
-3. Restart the server: `docker compose -f docker-compose.selfhosted.yml restart server worker`
-
 ## Enabling Real Domain with Let's Encrypt

 By default, Caddy uses self-signed certificates. For a real domain:
@@ -517,3 +514,9 @@ The setup script is idempotent — it won't overwrite existing secrets or env va
 ```

 All services communicate over Docker's internal network. Only Caddy (if enabled) exposes ports to the internet.
+
+## Future Plans for the Self-Hosted Script
+
+The following features are supported by Reflector but are **not yet integrated into the self-hosted setup script** and require manual configuration:
+
+- **Daily.co live rooms with multitrack processing**: Daily.co enables real-time meeting rooms with automatic recording and per-participant audio tracks for improved diarization. Requires a Daily.co account, API key, and an AWS S3 bucket for recording storage. Currently not automated in the script because the worker orchestration (hatchet) is not yet supported in the selfhosted compose setup.
--- a/gpu/self_hosted/uv.lock
+++ b/gpu/self_hosted/uv.lock
@@ -1,5 +1,5 @@
 version = 1
-revision = 2
+revision = 3
 requires-python = ">=3.12"

 [[package]]
@@ -13,7 +13,7 @@ wheels = [

 [[package]]
 name = "aiohttp"
-version = "3.12.15"
+version = "3.13.3"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
    { name = "aiohappyeyeballs" },
@@ -24,42 +24,76 @@ dependencies = [
    { name = "propcache" },
    { name = "yarl" },
 ]
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+sdist = { url = "https://files.pythonhosted.org/packages/50/42/32cf8e7704ceb4481406eb87161349abb46a57fee3f008ba9cb610968646/aiohttp-3.13.3.tar.gz", hash = "sha256:a949eee43d3782f2daae4f4a2819b2cb9b0c5d3b7f7a927067cc84dafdbb9f88", size = 7844556, upload-time = "2026-01-03T17:33:05.204Z" }
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+sdist = { url = "https://files.pythonhosted.org/packages/52/6d/fffca34caecc4a3f97bda81b2098da5e8ab7efc9a66e819074a11955d87e/pydantic_settings-2.13.1.tar.gz", hash = "sha256:b4c11847b15237fb0171e1462bf540e294affb9b86db4d9aa5c01730bdbe4025", size = 223826, upload-time = "2026-02-19T13:45:08.055Z" }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/00/4b/ccc026168948fec4f7555b9164c724cf4125eac006e176541483d2c959be/pydantic_settings-2.13.1-py3-none-any.whl", hash = "sha256:d56fd801823dbeae7f0975e1f8c8e25c258eb75d278ea7abb5d9cebb01b56237", size = 58929, upload-time = "2026-02-19T13:45:06.034Z" },
+]
+
 [[package]]
 name = "pygments"
 version = "2.19.2"
@@ -1907,11 +1991,11 @@ wheels = [

 [[package]]
 name = "python-multipart"
-version = "0.0.20"
+version = "0.0.22"
 source = { registry = "https://pypi.org/simple" }
-sdist = { url = "https://files.pythonhosted.org/packages/f3/87/f44d7c9f274c7ee665a29b885ec97089ec5dc034c7f3fafa03da9e39a09e/python_multipart-0.0.20.tar.gz", hash = "sha256:8dd0cab45b8e23064ae09147625994d090fa46f5b0d1e13af944c331a7fa9d13", size = 37158, upload-time = "2024-12-16T19:45:46.972Z" }
+sdist = { url = "https://files.pythonhosted.org/packages/94/01/979e98d542a70714b0cb2b6728ed0b7c46792b695e3eaec3e20711271ca3/python_multipart-0.0.22.tar.gz", hash = "sha256:7340bef99a7e0032613f56dc36027b959fd3b30a787ed62d310e951f7c3a3a58", size = 37612, upload-time = "2026-01-25T10:15:56.219Z" }
 wheels = [
-    { url = "https://files.pythonhosted.org/packages/45/58/38b5afbc1a800eeea951b9285d3912613f2603bdf897a4ab0f4bd7f405fc/python_multipart-0.0.20-py3-none-any.whl", hash = "sha256:8a62d3a8335e06589fe01f2a3e178cdcc632f3fbe0d492ad9ee0ec35aab1f104", size = 24546, upload-time = "2024-12-16T19:45:44.423Z" },
+    { url = "https://files.pythonhosted.org/packages/1b/d0/397f9626e711ff749a95d96b7af99b9c566a9bb5129b8e4c10fc4d100304/python_multipart-0.0.22-py3-none-any.whl", hash = "sha256:2b2cd894c83d21bf49d702499531c7bafd057d730c201782048f7945d82de155", size = 24579, upload-time = "2026-01-25T10:15:54.811Z" },
 ]

 [[package]]
@@ -2515,15 +2599,15 @@ wheels = [

 [[package]]
 name = "starlette"
-version = "0.47.3"
+version = "0.49.1"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
    { name = "anyio" },
    { name = "typing-extensions", marker = "python_full_version < '3.13'" },
 ]
-sdist = { url = "https://files.pythonhosted.org/packages/15/b9/cc3017f9a9c9b6e27c5106cc10cc7904653c3eec0729793aec10479dd669/starlette-0.47.3.tar.gz", hash = "sha256:6bc94f839cc176c4858894f1f8908f0ab79dfec1a6b8402f6da9be26ebea52e9", size = 2584144, upload-time = "2025-08-24T13:36:42.122Z" }
+sdist = { url = "https://files.pythonhosted.org/packages/1b/3f/507c21db33b66fb027a332f2cb3abbbe924cc3a79ced12f01ed8645955c9/starlette-0.49.1.tar.gz", hash = "sha256:481a43b71e24ed8c43b11ea02f5353d77840e01480881b8cb5a26b8cae64a8cb", size = 2654703, upload-time = "2025-10-28T17:34:10.928Z" }
 wheels = [
-    { url = "https://files.pythonhosted.org/packages/ce/fd/901cfa59aaa5b30a99e16876f11abe38b59a1a2c51ffb3d7142bb6089069/starlette-0.47.3-py3-none-any.whl", hash = "sha256:89c0778ca62a76b826101e7c709e70680a1699ca7da6b44d38eb0a7e61fe4b51", size = 72991, upload-time = "2025-08-24T13:36:40.887Z" },
+    { url = "https://files.pythonhosted.org/packages/51/da/545b75d420bb23b5d494b0517757b351963e974e79933f01e05c929f20a6/starlette-0.49.1-py3-none-any.whl", hash = "sha256:d92ce9f07e4a3caa3ac13a79523bd18e3bc0042bb8ff2d759a8e7dd0e1859875", size = 74175, upload-time = "2025-10-28T17:34:09.13Z" },
 ]

 [[package]]
@@ -2777,14 +2861,14 @@ wheels = [

 [[package]]
 name = "typing-inspection"
-version = "0.4.1"
+version = "0.4.2"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
    { name = "typing-extensions" },
 ]
-sdist = { url = "https://files.pythonhosted.org/packages/f8/b1/0c11f5058406b3af7609f121aaa6b609744687f1d158b3c3a5bf4cc94238/typing_inspection-0.4.1.tar.gz", hash = "sha256:6ae134cc0203c33377d43188d4064e9b357dba58cff3185f22924610e70a9d28", size = 75726, upload-time = "2025-05-21T18:55:23.885Z" }
+sdist = { url = "https://files.pythonhosted.org/packages/55/e3/70399cb7dd41c10ac53367ae42139cf4b1ca5f36bb3dc6c9d33acdb43655/typing_inspection-0.4.2.tar.gz", hash = "sha256:ba561c48a67c5958007083d386c3295464928b01faa735ab8547c5692e87f464", size = 75949, upload-time = "2025-10-01T02:14:41.687Z" }
 wheels = [
-    { url = "https://files.pythonhosted.org/packages/17/69/cd203477f944c353c31bade965f880aa1061fd6bf05ded0726ca845b6ff7/typing_inspection-0.4.1-py3-none-any.whl", hash = "sha256:389055682238f53b04f7badcb49b989835495a96700ced5dab2d8feae4b26f51", size = 14552, upload-time = "2025-05-21T18:55:22.152Z" },
+    { url = "https://files.pythonhosted.org/packages/dc/9b/47798a6c91d8bdb567fe2698fe81e0c6b7cb7ef4d13da4114b41d239f65d/typing_inspection-0.4.2-py3-none-any.whl", hash = "sha256:4ed1cacbdc298c220f1bd249ed5287caa16f34d44ef4e9c3d0cbad5b521545e7", size = 14611, upload-time = "2025-10-01T02:14:40.154Z" },
 ]

 [[package]]
@@ -2798,11 +2882,11 @@ wheels = [

 [[package]]
 name = "urllib3"
-version = "2.5.0"
+version = "2.6.3"
 source = { registry = "https://pypi.org/simple" }
-sdist = { url = "https://files.pythonhosted.org/packages/15/22/9ee70a2574a4f4599c47dd506532914ce044817c7752a79b6a51286319bc/urllib3-2.5.0.tar.gz", hash = "sha256:3fc47733c7e419d4bc3f6b3dc2b4f890bb743906a30d56ba4a5bfa4bbff92760", size = 393185, upload-time = "2025-06-18T14:07:41.644Z" }
+sdist = { url = "https://files.pythonhosted.org/packages/c7/24/5f1b3bdffd70275f6661c76461e25f024d5a38a46f04aaca912426a2b1d3/urllib3-2.6.3.tar.gz", hash = "sha256:1b62b6884944a57dbe321509ab94fd4d3b307075e0c2eae991ac71ee15ad38ed", size = 435556, upload-time = "2026-01-07T16:24:43.925Z" }
 wheels = [
-    { url = "https://files.pythonhosted.org/packages/a7/c2/fe1e52489ae3122415c51f387e221dd0773709bad6c6cdaa599e8a2c5185/urllib3-2.5.0-py3-none-any.whl", hash = "sha256:e6b01673c0fa6a13e374b50871808eb3bf7046c4b125b216f6bf1cc604cff0dc", size = 129795, upload-time = "2025-06-18T14:07:40.39Z" },
+    { url = "https://files.pythonhosted.org/packages/39/08/aaaad47bc4e9dc8c725e68f9d04865dbcb2052843ff09c97b08904852d84/urllib3-2.6.3-py3-none-any.whl", hash = "sha256:bf272323e553dfb2e87d9bfd225ca7b0f467b919d7bbd355436d3fd37cb0acd4", size = 131584, upload-time = "2026-01-07T16:24:42.685Z" },
 ]

 [[package]]
--- a/server/Dockerfile
+++ b/server/Dockerfile
@@ -17,9 +17,6 @@ WORKDIR /app
 COPY pyproject.toml uv.lock README.md /app/
 RUN uv sync --compile-bytecode --locked

-# pre-download nltk packages
-RUN uv run python -c "import nltk; nltk.download('punkt_tab'); nltk.download('averaged_perceptron_tagger_eng')"
-
 # bootstrap
 COPY alembic.ini runserver.sh /app/
 COPY images /app/images
--- a/server/pyproject.toml
+++ b/server/pyproject.toml
@@ -18,11 +18,10 @@ dependencies = [
    "fastapi[standard]>=0.100.1",
    "sentry-sdk[fastapi]>=1.29.2",
    "httpx>=0.24.1",
-    "fastapi-pagination>=0.12.6",
+    "fastapi-pagination>=0.14.2",
    "databases[aiosqlite, asyncpg]>=0.7.0",
    "sqlalchemy<1.5",
    "alembic>=1.11.3",
-    "nltk>=3.8.1",
    "prometheus-fastapi-instrumentator>=6.1.0",
    "sentencepiece>=0.1.99",
    "protobuf>=4.24.3",
@@ -40,6 +39,7 @@ dependencies = [
    "webvtt-py>=0.5.0",
    "icalendar>=6.0.0",
    "hatchet-sdk>=0.47.0",
+    "pydantic>=2.12.5",
 ]

 [dependency-groups]
--- a/server/reflector/llm.py
+++ b/server/reflector/llm.py
@@ -1,42 +1,23 @@
 import logging
 from contextvars import ContextVar
-from typing import Generic, Type, TypeVar
+from typing import Type, TypeVar
 from uuid import uuid4

 from llama_index.core import Settings
-from llama_index.core.output_parsers import PydanticOutputParser
+from llama_index.core.prompts import PromptTemplate
 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
-from workflows.errors import WorkflowTimeoutError

 from reflector.utils.retry import retry

 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:
-
-Analysis:
-{analysis}
-
-{format_instructions}
-"""
-

 class LLMParseError(Exception):
    """Raised when LLM output cannot be parsed after retries."""
@@ -50,157 +31,6 @@ class LLMParseError(Exception):
        )


-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_format enables grammar-based constrained decoding on backends
-        # that support it (DMR/llama.cpp, vLLM, Ollama, OpenAI).
-        response = await Settings.llm.acomplete(
-            json_prompt,
-            response_format={
-                "type": "json_schema",
-                "json_schema": {
-                    "name": self.output_cls.__name__,
-                    "schema": self.output_cls.model_json_schema(),
-                },
-            },
-        )
-        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 | None = None
@@ -225,7 +55,7 @@ class LLM:
            api_key=self.api_key,
            context_window=self.context_window,
            is_chat_model=True,
-            is_function_calling_model=False,
+            is_function_calling_model=True,
            temperature=self.temperature,
            max_tokens=self.max_tokens,
            timeout=self.settings_obj.LLM_REQUEST_TIMEOUT,
@@ -248,36 +78,91 @@ class LLM:
        tone_name: str | None = None,
        timeout: int | None = None,
    ) -> T:
-        """Get structured output from LLM with validation retry via Workflow."""
-        if timeout is None:
-            timeout = self.settings_obj.LLM_STRUCTURED_RESPONSE_TIMEOUT
+        """Get structured output from LLM using tool-call with reflection retry.

-        async def run_workflow():
-            workflow = StructuredOutputWorkflow(
+        Uses astructured_predict (function-calling / tool-call mode) for the
+        first attempt.  On ValidationError or parse failure the wrong output
+        and error are fed back as a reflection prompt and the call is retried
+        up to LLM_PARSE_MAX_RETRIES times.
+
+        The outer retry() wrapper handles transient network errors with
+        exponential back-off.
+        """
+        max_retries = self.settings_obj.LLM_PARSE_MAX_RETRIES
+
+        async def _call_with_reflection():
+            # Build full prompt: instruction + source texts
+            if texts:
+                texts_block = "\n\n".join(texts)
+                full_prompt = f"{prompt}\n\n{texts_block}"
+            else:
+                full_prompt = prompt
+
+            prompt_tmpl = PromptTemplate("{user_prompt}")
+            last_error: str | None = None
+
+            for attempt in range(1, max_retries + 2):  # +2: first try + retries
+                try:
+                    if attempt == 1:
+                        result = await Settings.llm.astructured_predict(
+                            output_cls, prompt_tmpl, user_prompt=full_prompt
+                        )
+                    else:
+                        reflection_tmpl = PromptTemplate(
+                            "{user_prompt}\n\n{reflection}"
+                        )
+                        result = await Settings.llm.astructured_predict(
+                            output_cls,
+                            reflection_tmpl,
+                            user_prompt=full_prompt,
+                            reflection=reflection,
+                        )
+
+                    if attempt > 1:
+                        logger.info(
+                            f"LLM structured_predict succeeded on attempt "
+                            f"{attempt}/{max_retries + 1} for {output_cls.__name__}"
+                        )
+                    return result
+
+                except (ValidationError, ValueError) as e:
+                    wrong_output = str(e)
+                    if len(wrong_output) > 2000:
+                        wrong_output = wrong_output[:2000] + "... [truncated]"
+
+                    last_error = self._format_validation_error(e)
+                    reflection = (
+                        f"Your previous response could not be parsed.\n\n"
+                        f"Error:\n{last_error}\n\n"
+                        "Please try again and return valid data matching the schema."
+                    )
+
+                    logger.error(
+                        f"LLM parse error (attempt {attempt}/{max_retries + 1}): "
+                        f"{type(e).__name__}: {e}\n"
+                        f"Raw response: {wrong_output[:500]}"
+                    )
+
+            raise LLMParseError(
                output_cls=output_cls,
-                max_retries=self.settings_obj.LLM_PARSE_MAX_RETRIES + 1,
-                timeout=timeout,
+                error_msg=last_error or "Max retries exceeded",
+                attempts=max_retries + 1,
            )

-            result = await workflow.run(
-                prompt=prompt,
-                texts=texts,
-                tone_name=tone_name,
-            )
-
-            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),
-                )
-
-            return result["success"]
-
-        return await retry(run_workflow)(
+        return await retry(_call_with_reflection)(
            retry_attempts=3,
            retry_backoff_interval=1.0,
            retry_backoff_max=30.0,
-            retry_ignore_exc_types=(WorkflowTimeoutError,),
+            retry_ignore_exc_types=(ConnectionError, TimeoutError, OSError),
        )
+
+    @staticmethod
+    def _format_validation_error(error: Exception) -> str:
+        """Format a validation/parse error for LLM reflection 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)
+        return f"Parse error: {str(error)}"
--- a/server/reflector/processors/transcript_topic_detector.py
+++ b/server/reflector/processors/transcript_topic_detector.py
@@ -14,10 +14,12 @@ class TopicResponse(BaseModel):
    title: str = Field(
        description="A descriptive title for the topic being discussed",
        validation_alias=AliasChoices("title", "Title"),
+        min_length=8,
    )
    summary: str = Field(
        description="A concise 1-2 sentence summary of the discussion",
        validation_alias=AliasChoices("summary", "Summary"),
+        min_length=8,
    )


--- a/server/tests/test_llm_retry.py
+++ b/server/tests/test_llm_retry.py
@@ -1,13 +1,11 @@
-"""Tests for LLM parse error recovery using llama-index Workflow"""
+"""Tests for LLM structured output with astructured_predict + reflection retry"""

-from time import monotonic
-from unittest.mock import AsyncMock, MagicMock, patch
+from unittest.mock import AsyncMock, patch

 import pytest
-from pydantic import BaseModel, Field
-from workflows.errors import WorkflowRuntimeError, WorkflowTimeoutError
+from pydantic import BaseModel, Field, ValidationError

-from reflector.llm import LLM, LLMParseError, StructuredOutputWorkflow
+from reflector.llm import LLM, LLMParseError
 from reflector.utils.retry import RetryException


@@ -19,51 +17,43 @@ class TestResponse(BaseModel):
    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"""
+    """Test parse error recovery with astructured_predict reflection loop"""

    @pytest.mark.asyncio
    async def test_parse_error_recovery_with_feedback(self, test_settings):
-        """Test that parse errors trigger retry with error feedback"""
+        """Test that parse errors trigger retry with reflection prompt"""
        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 astructured_predict_handler(output_cls, prompt_tmpl, **kwargs):
+            call_count["count"] += 1
+            if call_count["count"] == 1:
+                # First call: raise ValidationError (missing fields)
+                raise ValidationError.from_exception_data(
+                    title="TestResponse",
+                    line_errors=[
+                        {
+                            "type": "missing",
+                            "loc": ("summary",),
+                            "msg": "Field required",
+                            "input": {"title": "Test"},
+                        }
+                    ],
+                )
+            else:
+                # Second call: should have reflection in the prompt
+                assert "reflection" in kwargs
+                assert "could not be parsed" in kwargs["reflection"]
+                assert "Error:" in kwargs["reflection"]
+                return TestResponse(title="Test", summary="Summary", confidence=0.95)
+
+        with patch("reflector.llm.Settings") as mock_settings:
+            mock_settings.llm.astructured_predict = AsyncMock(
+                side_effect=astructured_predict_handler
            )

-            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
            )
@@ -71,8 +61,6 @@ class TestLLMParseErrorRecovery:
            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
@@ -80,56 +68,61 @@ class TestLLMParseErrorRecovery:
        """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"}'
-                )
+        # Always raise ValidationError
+        async def always_fail(output_cls, prompt_tmpl, **kwargs):
+            raise ValidationError.from_exception_data(
+                title="TestResponse",
+                line_errors=[
+                    {
+                        "type": "missing",
+                        "loc": ("summary",),
+                        "msg": "Field required",
+                        "input": {},
+                    }
+                ],
            )

+        with patch("reflector.llm.Settings") as mock_settings:
+            mock_settings.llm.astructured_predict = AsyncMock(side_effect=always_fail)
+
            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
+            assert mock_settings.llm.astructured_predict.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)

+        call_count = {"count": 0}
+
+        async def astructured_predict_handler(output_cls, prompt_tmpl, **kwargs):
+            call_count["count"] += 1
+            if call_count["count"] == 1:
+                raise ValidationError.from_exception_data(
+                    title="TestResponse",
+                    line_errors=[
+                        {
+                            "type": "missing",
+                            "loc": ("summary",),
+                            "msg": "Field required",
+                            "input": {"title": "Test"},
+                        }
+                    ],
+                )
+            return TestResponse(title="Test", summary="Summary", confidence=0.95)
+
        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)
+            mock_settings.llm.astructured_predict = AsyncMock(
+                side_effect=astructured_predict_handler
+            )

            result = await llm.get_structured_response(
                prompt="Test prompt", texts=["Test text"], output_cls=TestResponse
@@ -143,35 +136,45 @@ class TestLLMParseErrorRecovery:

    @pytest.mark.asyncio
    async def test_multiple_validation_errors_in_feedback(self, test_settings):
-        """Test that validation errors are included in feedback"""
+        """Test that validation errors are included in reflection 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}

-            call_count = {"count": 0}
+        async def astructured_predict_handler(output_cls, prompt_tmpl, **kwargs):
+            call_count["count"] += 1
+            if call_count["count"] == 1:
+                # Missing title and summary
+                raise ValidationError.from_exception_data(
+                    title="TestResponse",
+                    line_errors=[
+                        {
+                            "type": "missing",
+                            "loc": ("title",),
+                            "msg": "Field required",
+                            "input": {},
+                        },
+                        {
+                            "type": "missing",
+                            "loc": ("summary",),
+                            "msg": "Field required",
+                            "input": {},
+                        },
+                    ],
+                )
+            else:
+                # Should have schema validation errors in reflection
+                assert "reflection" in kwargs
+                assert (
+                    "Schema validation errors" in kwargs["reflection"]
+                    or "error" in kwargs["reflection"].lower()
+                )
+                return TestResponse(title="Test", summary="Summary", confidence=0.95)

-            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)
+        with patch("reflector.llm.Settings") as mock_settings:
+            mock_settings.llm.astructured_predict = AsyncMock(
+                side_effect=astructured_predict_handler
+            )

            result = await llm.get_structured_response(
                prompt="Test prompt", texts=["Test text"], output_cls=TestResponse
@@ -185,17 +188,10 @@ class TestLLMParseErrorRecovery:
        """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}'
+        with patch("reflector.llm.Settings") as mock_settings:
+            mock_settings.llm.astructured_predict = AsyncMock(
+                return_value=TestResponse(
+                    title="Test", summary="Summary", confidence=0.95
                )
            )

@@ -206,195 +202,28 @@ class TestLLMParseErrorRecovery:
            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
+            assert mock_settings.llm.astructured_predict.call_count == 1


 class TestNetworkErrorRetries:
-    """Test that network error retries are handled by OpenAILike, not Workflow"""
+    """Test that network errors are retried by the outer retry() wrapper"""

    @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
-
-
-class TestWorkflowTimeoutRetry:
-    """Test timeout retry mechanism in get_structured_response"""
-
-    @pytest.mark.asyncio
-    async def test_timeout_retry_succeeds_on_retry(self, test_settings):
-        """Test that WorkflowTimeoutError triggers retry and succeeds"""
+    async def test_network_error_retried_by_outer_wrapper(self, test_settings):
+        """Test that network errors trigger the outer retry wrapper"""
        llm = LLM(settings=test_settings, temperature=0.4, max_tokens=100)

        call_count = {"count": 0}

-        async def workflow_run_side_effect(*args, **kwargs):
+        async def astructured_predict_handler(output_cls, prompt_tmpl, **kwargs):
            call_count["count"] += 1
            if call_count["count"] == 1:
-                raise WorkflowTimeoutError("Operation timed out after 120 seconds")
-            return {
-                "success": TestResponse(
-                    title="Test", summary="Summary", confidence=0.95
-                )
-            }
+                raise ConnectionError("Connection refused")
+            return TestResponse(title="Test", summary="Summary", confidence=0.95)

-        with (
-            patch("reflector.llm.StructuredOutputWorkflow") as mock_workflow_class,
-            patch("reflector.llm.TreeSummarize") as mock_summarize,
-            patch("reflector.llm.Settings") as mock_settings,
-        ):
-            mock_workflow = MagicMock()
-            mock_workflow.run = AsyncMock(side_effect=workflow_run_side_effect)
-            mock_workflow_class.return_value = mock_workflow
-
-            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}'
-                )
+        with patch("reflector.llm.Settings") as mock_settings:
+            mock_settings.llm.astructured_predict = AsyncMock(
+                side_effect=astructured_predict_handler
            )

            result = await llm.get_structured_response(
@@ -402,36 +231,16 @@ class TestWorkflowTimeoutRetry:
            )

            assert result.title == "Test"
-            assert result.summary == "Summary"
            assert call_count["count"] == 2

    @pytest.mark.asyncio
-    async def test_timeout_retry_exhausts_after_max_attempts(self, test_settings):
-        """Test that timeout retry stops after max attempts"""
+    async def test_network_error_exhausts_retries(self, test_settings):
+        """Test that persistent network errors exhaust retry attempts"""
        llm = LLM(settings=test_settings, temperature=0.4, max_tokens=100)

-        call_count = {"count": 0}
-
-        async def workflow_run_side_effect(*args, **kwargs):
-            call_count["count"] += 1
-            raise WorkflowTimeoutError("Operation timed out after 120 seconds")
-
-        with (
-            patch("reflector.llm.StructuredOutputWorkflow") as mock_workflow_class,
-            patch("reflector.llm.TreeSummarize") as mock_summarize,
-            patch("reflector.llm.Settings") as mock_settings,
-        ):
-            mock_workflow = MagicMock()
-            mock_workflow.run = AsyncMock(side_effect=workflow_run_side_effect)
-            mock_workflow_class.return_value = mock_workflow
-
-            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}'
-                )
+        with patch("reflector.llm.Settings") as mock_settings:
+            mock_settings.llm.astructured_predict = AsyncMock(
+                side_effect=ConnectionError("Connection refused")
            )

            with pytest.raises(RetryException, match="Retry attempts exceeded"):
@@ -439,41 +248,129 @@ class TestWorkflowTimeoutRetry:
                    prompt="Test prompt", texts=["Test text"], output_cls=TestResponse
                )

-            assert call_count["count"] == 3
+            # 3 retry attempts
+            assert mock_settings.llm.astructured_predict.call_count == 3
+
+
+class TestTextsInclusion:
+    """Test that texts parameter is included in the prompt sent to astructured_predict"""

    @pytest.mark.asyncio
-    async def test_timeout_retry_with_backoff(self, test_settings):
-        """Test that exponential backoff is applied between retries"""
+    async def test_texts_included_in_prompt(self, test_settings):
+        """Test that texts content is appended to the prompt for astructured_predict"""
        llm = LLM(settings=test_settings, temperature=0.4, max_tokens=100)

-        call_times = []
+        captured_prompts = []

-        async def workflow_run_side_effect(*args, **kwargs):
-            call_times.append(monotonic())
-            if len(call_times) < 3:
-                raise WorkflowTimeoutError("Operation timed out after 120 seconds")
-            return {
-                "success": TestResponse(
-                    title="Test", summary="Summary", confidence=0.95
+        async def capture_prompt(output_cls, prompt_tmpl, **kwargs):
+            captured_prompts.append(kwargs.get("user_prompt", ""))
+            return TestResponse(title="Test", summary="Summary", confidence=0.95)
+
+        with patch("reflector.llm.Settings") as mock_settings:
+            mock_settings.llm.astructured_predict = AsyncMock(
+                side_effect=capture_prompt
+            )
+
+            await llm.get_structured_response(
+                prompt="Identify all participants",
+                texts=["Alice: Hello everyone", "Bob: Hi Alice"],
+                output_cls=TestResponse,
+            )
+
+            assert len(captured_prompts) == 1
+            prompt_sent = captured_prompts[0]
+            assert "Identify all participants" in prompt_sent
+            assert "Alice: Hello everyone" in prompt_sent
+            assert "Bob: Hi Alice" in prompt_sent
+
+    @pytest.mark.asyncio
+    async def test_empty_texts_uses_prompt_only(self, test_settings):
+        """Test that empty texts list sends only the prompt"""
+        llm = LLM(settings=test_settings, temperature=0.4, max_tokens=100)
+
+        captured_prompts = []
+
+        async def capture_prompt(output_cls, prompt_tmpl, **kwargs):
+            captured_prompts.append(kwargs.get("user_prompt", ""))
+            return TestResponse(title="Test", summary="Summary", confidence=0.95)
+
+        with patch("reflector.llm.Settings") as mock_settings:
+            mock_settings.llm.astructured_predict = AsyncMock(
+                side_effect=capture_prompt
+            )
+
+            await llm.get_structured_response(
+                prompt="Identify all participants",
+                texts=[],
+                output_cls=TestResponse,
+            )
+
+            assert len(captured_prompts) == 1
+            assert captured_prompts[0] == "Identify all participants"
+
+    @pytest.mark.asyncio
+    async def test_texts_included_in_reflection_retry(self, test_settings):
+        """Test that texts are included in the prompt even during reflection retries"""
+        llm = LLM(settings=test_settings, temperature=0.4, max_tokens=100)
+
+        captured_prompts = []
+        call_count = {"count": 0}
+
+        async def capture_and_fail_first(output_cls, prompt_tmpl, **kwargs):
+            call_count["count"] += 1
+            captured_prompts.append(kwargs.get("user_prompt", ""))
+            if call_count["count"] == 1:
+                raise ValidationError.from_exception_data(
+                    title="TestResponse",
+                    line_errors=[
+                        {
+                            "type": "missing",
+                            "loc": ("summary",),
+                            "msg": "Field required",
+                            "input": {},
+                        }
+                    ],
                )
-            }
+            return TestResponse(title="Test", summary="Summary", confidence=0.95)

-        with (
-            patch("reflector.llm.StructuredOutputWorkflow") as mock_workflow_class,
-            patch("reflector.llm.TreeSummarize") as mock_summarize,
-            patch("reflector.llm.Settings") as mock_settings,
-        ):
-            mock_workflow = MagicMock()
-            mock_workflow.run = AsyncMock(side_effect=workflow_run_side_effect)
-            mock_workflow_class.return_value = mock_workflow
+        with patch("reflector.llm.Settings") as mock_settings:
+            mock_settings.llm.astructured_predict = AsyncMock(
+                side_effect=capture_and_fail_first
+            )

-            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}'
-                )
+            await llm.get_structured_response(
+                prompt="Summarize this",
+                texts=["The meeting covered project updates"],
+                output_cls=TestResponse,
+            )
+
+            # Both first attempt and reflection retry should include the texts
+            assert len(captured_prompts) == 2
+            for prompt_sent in captured_prompts:
+                assert "Summarize this" in prompt_sent
+                assert "The meeting covered project updates" in prompt_sent
+
+
+class TestReflectionRetryBackoff:
+    """Test the reflection retry timing behavior"""
+
+    @pytest.mark.asyncio
+    async def test_value_error_triggers_reflection(self, test_settings):
+        """Test that ValueError (parse failure) also triggers reflection retry"""
+        llm = LLM(settings=test_settings, temperature=0.4, max_tokens=100)
+
+        call_count = {"count": 0}
+
+        async def astructured_predict_handler(output_cls, prompt_tmpl, **kwargs):
+            call_count["count"] += 1
+            if call_count["count"] == 1:
+                raise ValueError("Could not parse output")
+            assert "reflection" in kwargs
+            return TestResponse(title="Test", summary="Summary", confidence=0.95)
+
+        with patch("reflector.llm.Settings") as mock_settings:
+            mock_settings.llm.astructured_predict = AsyncMock(
+                side_effect=astructured_predict_handler
            )

            result = await llm.get_structured_response(
@@ -481,8 +378,20 @@ class TestWorkflowTimeoutRetry:
            )

            assert result.title == "Test"
-            if len(call_times) >= 2:
-                time_between_calls = call_times[1] - call_times[0]
-                assert (
-                    time_between_calls >= 1.5
-                ), f"Expected ~2s backoff, got {time_between_calls}s"
+            assert call_count["count"] == 2
+
+    @pytest.mark.asyncio
+    async def test_format_validation_error_method(self, test_settings):
+        """Test _format_validation_error produces correct feedback"""
+        # ValidationError
+        try:
+            TestResponse(title="x", summary="y", confidence=5.0)  # confidence > 1
+        except ValidationError as e:
+            result = LLM._format_validation_error(e)
+            assert "Schema validation errors" in result
+            assert "confidence" in result
+
+        # ValueError
+        result = LLM._format_validation_error(ValueError("bad input"))
+        assert "Parse error:" in result
+        assert "bad input" in result
--- a/server/uv.lock
+++ b/server/uv.lock
--- a/www/.env.example
+++ b/www/.env.example
@@ -27,5 +27,5 @@ WEBSOCKET_URL=ws://127.0.0.1:1250
 AUTH_CALLBACK_URL=http://localhost:3000/auth-callback

 # Sentry
-# SENTRY_DSN=https://your-dsn@sentry.io/project-id
+# NEXT_PUBLIC_SENTRY_DSN=https://your-dsn@sentry.io/project-id
 # SENTRY_IGNORE_API_RESOLUTION_ERROR=1
--- a/www/.env.selfhosted.example
+++ b/www/.env.selfhosted.example
@@ -50,4 +50,4 @@ AUTHENTIK_REFRESH_TOKEN_URL=
 # =======================================================
 # Sentry (Optional)
 # =======================================================
-# SENTRY_DSN=
+# NEXT_PUBLIC_SENTRY_DSN=
--- a/www/app/(app)/transcripts/useWebSockets.ts
+++ b/www/app/(app)/transcripts/useWebSockets.ts
@@ -346,9 +346,10 @@ export const useWebSockets = (transcriptId: string | null): UseWebSockets => {
    let intentionalClose = false;

    const connect = () => {
-      const subprotocols = auth.accessToken
-        ? ["bearer", auth.accessToken]
-        : undefined;
+      const subprotocols =
+        auth.status === "authenticated" && auth.accessToken
+          ? ["bearer", auth.accessToken]
+          : undefined;
      ws = new WebSocket(url, subprotocols);

      ws.onopen = () => {
--- a/www/app/lib/tests/authBackend.test.ts
+++ b/www/app/lib/tests/authBackend.test.ts
@@ -0,0 +1,88 @@
+// env vars must be set before any module imports
+process.env.AUTHENTIK_REFRESH_TOKEN_URL =
+  "https://authentik.example.com/application/o/token/";
+process.env.AUTHENTIK_ISSUER =
+  "https://authentik.example.com/application/o/reflector/";
+process.env.AUTHENTIK_CLIENT_ID = "test-client-id";
+process.env.AUTHENTIK_CLIENT_SECRET = "test-client-secret";
+process.env.SERVER_API_URL = "http://localhost:1250";
+process.env.FEATURE_REQUIRE_LOGIN = "true";
+// must NOT be "credentials" so authOptions() returns the Authentik path
+delete process.env.AUTH_PROVIDER;
+
+jest.mock("../next", () => ({ isBuildPhase: false }));
+
+jest.mock("../features", () => ({
+  featureEnabled: (name: string) => name === "requireLogin",
+}));
+
+jest.mock("../redisClient", () => ({
+  tokenCacheRedis: {},
+  redlock: {
+    using: jest.fn((_keys: string[], _ttl: number, fn: () => unknown) => fn()),
+  },
+}));
+
+jest.mock("../redisTokenCache", () => ({
+  getTokenCache: jest.fn().mockResolvedValue(null),
+  setTokenCache: jest.fn().mockResolvedValue(undefined),
+  deleteTokenCache: jest.fn().mockResolvedValue(undefined),
+}));
+
+const mockFetch = jest.fn();
+global.fetch = mockFetch;
+
+import { authOptions } from "../authBackend";
+
+describe("Authentik token refresh", () => {
+  beforeEach(() => {
+    mockFetch.mockReset();
+  });
+
+  test("refresh request preserves trailing slash in token URL", async () => {
+    mockFetch.mockResolvedValue({
+      ok: true,
+      json: async () => ({
+        access_token: "new-access-token",
+        expires_in: 300,
+        refresh_token: "new-refresh-token",
+      }),
+    });
+
+    const options = authOptions();
+    const jwtCallback = options.callbacks!.jwt!;
+
+    // Simulate a returning user whose access token has expired (no account/user = not initial login)
+    const expiredToken = {
+      sub: "test-user-123",
+      accessToken: "expired-access-token",
+      accessTokenExpires: Date.now() - 60_000,
+      refreshToken: "old-refresh-token",
+    };
+
+    await jwtCallback({
+      token: expiredToken,
+      user: undefined as any,
+      account: null,
+      profile: undefined,
+      trigger: "update",
+      isNewUser: false,
+      session: undefined,
+    });
+
+    // The refresh POST must go to the exact URL from the env var (trailing slash included)
+    expect(mockFetch).toHaveBeenCalledWith(
+      "https://authentik.example.com/application/o/token/",
+      expect.objectContaining({
+        method: "POST",
+        body: expect.any(String),
+      }),
+    );
+
+    const body = new URLSearchParams(mockFetch.mock.calls[0][1].body);
+    expect(body.get("grant_type")).toBe("refresh_token");
+    expect(body.get("refresh_token")).toBe("old-refresh-token");
+    expect(body.get("client_id")).toBe("test-client-id");
+    expect(body.get("client_secret")).toBe("test-client-secret");
+  });
+});
--- a/www/app/lib/authBackend.ts
+++ b/www/app/lib/authBackend.ts
@@ -53,7 +53,7 @@ const TOKEN_CACHE_TTL = REFRESH_ACCESS_TOKEN_BEFORE;
 const getAuthentikClientId = () => getNextEnvVar("AUTHENTIK_CLIENT_ID");
 const getAuthentikClientSecret = () => getNextEnvVar("AUTHENTIK_CLIENT_SECRET");
 const getAuthentikRefreshTokenUrl = () =>
-  getNextEnvVar("AUTHENTIK_REFRESH_TOKEN_URL").replace(/\/+$/, "");
+  getNextEnvVar("AUTHENTIK_REFRESH_TOKEN_URL");

 const getAuthentikIssuer = () => {
  const stringUrl = getNextEnvVar("AUTHENTIK_ISSUER");
@@ -62,7 +62,7 @@ const getAuthentikIssuer = () => {
  } catch (e) {
    throw new Error("AUTHENTIK_ISSUER is not a valid URL: " + stringUrl);
  }
-  return stringUrl.replace(/\/+$/, "");
+  return stringUrl;
 };

 export const authOptions = (): AuthOptions => {
--- a/www/app/lib/clientEnv.ts
+++ b/www/app/lib/clientEnv.ts
@@ -35,6 +35,7 @@ export type ClientEnvCommon = EnvFeaturePartial & {
  API_URL: NonEmptyString;
  WEBSOCKET_URL: NonEmptyString | null;
  AUTH_PROVIDER: AuthProviderType;
+  SENTRY_DSN: string | null;
 };

 let clientEnv: ClientEnvCommon | null = null;
@@ -86,6 +87,9 @@ export const getClientEnvServer = (): ClientEnvCommon => {
      API_URL: getNextEnvVar("API_URL"),
      WEBSOCKET_URL: parseMaybeNonEmptyString(process.env.WEBSOCKET_URL ?? ""),
      AUTH_PROVIDER: parseAuthProvider(),
+      SENTRY_DSN: parseMaybeNonEmptyString(
+        process.env.NEXT_PUBLIC_SENTRY_DSN ?? "",
+      ),
      ...features,
    };
  }
@@ -94,6 +98,9 @@ export const getClientEnvServer = (): ClientEnvCommon => {
    API_URL: getNextEnvVar("API_URL"),
    WEBSOCKET_URL: parseMaybeNonEmptyString(process.env.WEBSOCKET_URL ?? ""),
    AUTH_PROVIDER: parseAuthProvider(),
+    SENTRY_DSN: parseMaybeNonEmptyString(
+      process.env.NEXT_PUBLIC_SENTRY_DSN ?? "",
+    ),
    ...features,
  };
  return clientEnv;
--- a/www/instrumentation-client.ts
+++ b/www/instrumentation-client.ts
@@ -3,8 +3,9 @@
 // https://docs.sentry.io/platforms/javascript/guides/nextjs/

 import * as Sentry from "@sentry/nextjs";
+import { getClientEnv } from "./app/lib/clientEnv";

-const SENTRY_DSN = process.env.SENTRY_DSN;
+const SENTRY_DSN = getClientEnv().SENTRY_DSN;

 if (SENTRY_DSN) {
  Sentry.init({
--- a/www/package.json
+++ b/www/package.json
@@ -19,20 +19,20 @@
    "@fortawesome/fontawesome-svg-core": "^6.4.0",
    "@fortawesome/free-solid-svg-icons": "^6.4.0",
    "@fortawesome/react-fontawesome": "^0.2.0",
-    "@sentry/nextjs": "^10.11.0",
+    "@sentry/nextjs": "^10.40.0",
    "@tanstack/react-query": "^5.85.9",
    "@types/ioredis": "^5.0.0",
    "@whereby.com/browser-sdk": "^3.3.4",
    "autoprefixer": "10.4.20",
-    "axios": "^1.8.2",
+    "axios": "^1.13.5",
    "eslint": "^9.33.0",
    "eslint-config-next": "^15.5.3",
    "fontawesome": "^5.6.3",
    "ioredis": "^5.7.0",
    "jest-worker": "^29.6.2",
    "lucide-react": "^0.525.0",
-    "next": "^15.5.9",
-    "next-auth": "^4.24.7",
+    "next": "^15.5.10",
+    "next-auth": "^4.24.12",
    "next-themes": "^0.4.6",
    "nuqs": "^2.4.3",
    "openapi-fetch": "^0.14.0",
--- a/www/pnpm-lock.yaml
+++ b/www/pnpm-lock.yaml
--- a/www/sentry.edge.config.ts
+++ b/www/sentry.edge.config.ts
@@ -5,7 +5,7 @@

 import * as Sentry from "@sentry/nextjs";

-const SENTRY_DSN = process.env.SENTRY_DSN;
+const SENTRY_DSN = process.env.NEXT_PUBLIC_SENTRY_DSN;

 if (SENTRY_DSN) {
  Sentry.init({
--- a/www/sentry.server.config.ts
+++ b/www/sentry.server.config.ts
@@ -4,7 +4,7 @@

 import * as Sentry from "@sentry/nextjs";

-const SENTRY_DSN = process.env.SENTRY_DSN;
+const SENTRY_DSN = process.env.NEXT_PUBLIC_SENTRY_DSN;

 if (SENTRY_DSN) {
  Sentry.init({
Author	SHA1	Message	Date
dependabot[bot]	7f9ce7f13a	build(deps): bump the uv group across 2 directories with 16 updates (#886 ) * build(deps): bump the uv group across 2 directories with 16 updates --- updated-dependencies: - dependency-name: aiohttp dependency-version: 3.13.3 dependency-type: indirect dependency-group: uv - dependency-name: filelock dependency-version: 3.20.3 dependency-type: indirect dependency-group: uv - dependency-name: fonttools dependency-version: 4.60.2 dependency-type: indirect dependency-group: uv - dependency-name: pillow dependency-version: 12.1.1 dependency-type: indirect dependency-group: uv - dependency-name: protobuf dependency-version: 6.33.5 dependency-type: indirect dependency-group: uv - dependency-name: python-multipart dependency-version: 0.0.22 dependency-type: indirect dependency-group: uv - dependency-name: starlette dependency-version: 0.49.1 dependency-type: indirect dependency-group: uv - dependency-name: urllib3 dependency-version: 2.6.3 dependency-type: indirect dependency-group: uv - dependency-name: aiohttp dependency-version: 3.13.3 dependency-type: indirect dependency-group: uv - dependency-name: protobuf dependency-version: 6.33.5 dependency-type: indirect dependency-group: uv - dependency-name: python-multipart dependency-version: 0.0.22 dependency-type: indirect dependency-group: uv - dependency-name: filelock dependency-version: 3.20.3 dependency-type: indirect dependency-group: uv - dependency-name: pillow dependency-version: 12.1.1 dependency-type: indirect dependency-group: uv - dependency-name: starlette dependency-version: 0.49.1 dependency-type: indirect dependency-group: uv - dependency-name: urllib3 dependency-version: 2.6.3 dependency-type: indirect dependency-group: uv - dependency-name: sentencepiece dependency-version: 0.2.1 dependency-type: direct:production dependency-group: uv - dependency-name: aiohttp dependency-version: 3.13.3 dependency-type: direct:production dependency-group: uv - dependency-name: filelock dependency-version: 3.20.3 dependency-type: indirect dependency-group: uv - dependency-name: pillow dependency-version: 12.1.1 dependency-type: indirect dependency-group: uv - dependency-name: protobuf dependency-version: 6.33.5 dependency-type: direct:production dependency-group: uv - dependency-name: python-multipart dependency-version: 0.0.22 dependency-type: direct:production dependency-group: uv - dependency-name: starlette dependency-version: 0.49.1 dependency-type: indirect dependency-group: uv - dependency-name: urllib3 dependency-version: 2.6.3 dependency-type: indirect dependency-group: uv - dependency-name: aiohttp dependency-version: 3.13.3 dependency-type: direct:production dependency-group: uv - dependency-name: sentencepiece dependency-version: 0.2.1 dependency-type: direct:production dependency-group: uv - dependency-name: protobuf dependency-version: 6.33.5 dependency-type: direct:production dependency-group: uv - dependency-name: python-multipart dependency-version: 0.0.22 dependency-type: direct:production dependency-group: uv - dependency-name: llama-index dependency-version: 0.13.0 dependency-type: direct:production dependency-group: uv - dependency-name: black dependency-version: 24.3.0 dependency-type: direct:development dependency-group: uv - dependency-name: cryptography dependency-version: 46.0.5 dependency-type: indirect dependency-group: uv - dependency-name: filelock dependency-version: 3.20.3 dependency-type: indirect dependency-group: uv - dependency-name: llama-index-core dependency-version: 0.13.6 dependency-type: indirect dependency-group: uv - dependency-name: marshmallow dependency-version: 3.26.2 dependency-type: indirect dependency-group: uv - dependency-name: pillow dependency-version: 12.1.1 dependency-type: indirect dependency-group: uv - dependency-name: pyasn1 dependency-version: 0.6.2 dependency-type: indirect dependency-group: uv - dependency-name: pypdf dependency-version: 6.7.3 dependency-type: indirect dependency-group: uv - dependency-name: starlette dependency-version: 0.49.1 dependency-type: indirect dependency-group: uv - dependency-name: urllib3 dependency-version: 2.6.3 dependency-type: indirect dependency-group: uv ... Signed-off-by: dependabot[bot] <support@github.com> * Upgrade fastapi-pagination and pydanti --------- Signed-off-by: dependabot[bot] <support@github.com> Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com> Co-authored-by: Sergey Mankovsky <sergey@mankovsky.dev>	2026-02-26 03:26:59 +01:00
dependabot[bot]	66772efbfe	build(deps): bump the npm_and_yarn group across 1 directory with 11 updates (#887 ) Bumps the npm_and_yarn group with 7 updates in the /www directory: \| Package \| From \| To \| \| --- \| --- \| --- \| \| [minimatch](https://github.com/isaacs/minimatch) \| `3.1.2` \| `3.1.5` \| \| [ajv](https://github.com/ajv-validator/ajv) \| `6.12.6` \| `6.14.0` \| \| [js-yaml](https://github.com/nodeca/js-yaml) \| `3.14.1` \| `3.14.2` \| \| [mdast-util-to-hast](https://github.com/syntax-tree/mdast-util-to-hast) \| `13.2.0` \| `13.2.1` \| \| [axios](https://github.com/axios/axios) \| `1.11.0` \| `1.13.5` \| \| [next](https://github.com/vercel/next.js) \| `15.5.9` \| `15.5.10` \| \| [next-auth](https://github.com/nextauthjs/next-auth) \| `4.24.11` \| `4.24.12` \| Updates `minimatch` from 3.1.2 to 3.1.5 - [Changelog](https://github.com/isaacs/minimatch/blob/main/changelog.md) - [Commits](https://github.com/isaacs/minimatch/compare/v3.1.2...v3.1.5) Updates `ajv` from 6.12.6 to 6.14.0 - [Release notes](https://github.com/ajv-validator/ajv/releases) - [Commits](https://github.com/ajv-validator/ajv/compare/v6.12.6...v6.14.0) Updates `diff` from 4.0.2 to 4.0.4 - [Changelog](https://github.com/kpdecker/jsdiff/blob/master/release-notes.md) - [Commits](https://github.com/kpdecker/jsdiff/compare/v4.0.2...v4.0.4) Updates `js-yaml` from 3.14.1 to 3.14.2 - [Changelog](https://github.com/nodeca/js-yaml/blob/master/CHANGELOG.md) - [Commits](https://github.com/nodeca/js-yaml/compare/3.14.1...3.14.2) Updates `mdast-util-to-hast` from 13.2.0 to 13.2.1 - [Release notes](https://github.com/syntax-tree/mdast-util-to-hast/releases) - [Commits](https://github.com/syntax-tree/mdast-util-to-hast/compare/13.2.0...13.2.1) Updates `axios` from 1.11.0 to 1.13.5 - [Release notes](https://github.com/axios/axios/releases) - [Changelog](https://github.com/axios/axios/blob/v1.x/CHANGELOG.md) - [Commits](https://github.com/axios/axios/compare/v1.11.0...v1.13.5) Updates `next` from 15.5.9 to 15.5.10 - [Release notes](https://github.com/vercel/next.js/releases) - [Changelog](https://github.com/vercel/next.js/blob/canary/release.js) - [Commits](https://github.com/vercel/next.js/compare/v15.5.9...v15.5.10) Updates `next-auth` from 4.24.11 to 4.24.12 - [Release notes](https://github.com/nextauthjs/next-auth/releases) - [Commits](https://github.com/nextauthjs/next-auth/compare/next-auth@4.24.11...next-auth@4.24.12) Updates `@sentry/node` from 10.11.0 to 10.40.0 - [Release notes](https://github.com/getsentry/sentry-javascript/releases) - [Changelog](https://github.com/getsentry/sentry-javascript/blob/develop/CHANGELOG.md) - [Commits](https://github.com/getsentry/sentry-javascript/compare/10.11.0...10.40.0) Updates `preact` from 10.27.0 to 10.28.4 - [Release notes](https://github.com/preactjs/preact/releases) - [Commits](https://github.com/preactjs/preact/compare/10.27.0...10.28.4) Updates `rollup` from 4.50.1 to 4.59.0 - [Release notes](https://github.com/rollup/rollup/releases) - [Changelog](https://github.com/rollup/rollup/blob/master/CHANGELOG.md) - [Commits](https://github.com/rollup/rollup/compare/v4.50.1...v4.59.0) --- updated-dependencies: - dependency-name: minimatch dependency-version: 3.1.5 dependency-type: indirect dependency-group: npm_and_yarn - dependency-name: ajv dependency-version: 6.14.0 dependency-type: indirect dependency-group: npm_and_yarn - dependency-name: diff dependency-version: 4.0.4 dependency-type: indirect dependency-group: npm_and_yarn - dependency-name: js-yaml dependency-version: 3.14.2 dependency-type: indirect dependency-group: npm_and_yarn - dependency-name: mdast-util-to-hast dependency-version: 13.2.1 dependency-type: indirect dependency-group: npm_and_yarn - dependency-name: axios dependency-version: 1.13.5 dependency-type: direct:production dependency-group: npm_and_yarn - dependency-name: next dependency-version: 15.5.10 dependency-type: direct:production dependency-group: npm_and_yarn - dependency-name: next-auth dependency-version: 4.24.12 dependency-type: direct:production dependency-group: npm_and_yarn - dependency-name: "@sentry/node" dependency-version: 10.40.0 dependency-type: indirect dependency-group: npm_and_yarn - dependency-name: preact dependency-version: 10.28.4 dependency-type: indirect dependency-group: npm_and_yarn - dependency-name: rollup dependency-version: 4.59.0 dependency-type: indirect dependency-group: npm_and_yarn ... Signed-off-by: dependabot[bot] <support@github.com> Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com>	2026-02-26 00:22:41 +01:00
Sergey Mankovsky	d79ec4149a	Remove direct nltk dependency (#878 )	2026-02-26 00:00:22 +01:00
Juan Diego García	69f7cce0fd	fix trailing slash authentik (#885 )	2026-02-25 17:58:13 -05:00
Sergey Mankovsky	4fb60955d4	Build frontend image for local compose (#884 )	2026-02-25 23:34:33 +01:00
Sergey Mankovsky	f428b9e3f2	Fix sentry dsn on client (#882 )	2026-02-25 23:34:17 +01:00
Juan Diego García	25bcdb16a8	chore(main): release 0.35.1 (#877 )	2026-02-24 18:32:56 -06:00
Mathieu Virbel	5d547586ef	fix: switch structured output to tool-call with reflection retry (#879 ) * fix: switch structured output to tool-call with reflection retry Replace the two-pass StructuredOutputWorkflow (TreeSummarize → acomplete) with astructured_predict + reflection retry loop for structured LLM output. - Enable function-calling mode (is_function_calling_model=True) - Use astructured_predict with PromptTemplate for first attempt - On ValidationError/parse failure, retry with reflection feedback - Add min_length=10 to TopicResponse title/summary fields - Remove dead StructuredOutputWorkflow class and its event types - Rewrite tests to match new astructured_predict approach * fix: include texts parameter in astructured_predict prompt The switch to astructured_predict dropped the texts parameter entirely, causing summary prompts (participants, subjects, action items) to be sent without the transcript content. Combine texts with the prompt before calling astructured_predict, mirroring what TreeSummarize did. * fix: reduce TopicResponse min_length from 10 to 8 for title and summary * ci: try fixing spawning job in github * ci: fix for new arm64 builder	2026-02-24 18:28:11 -06:00
Juan Diego García	815e87056d	add note about mac gpu acceleration on docker (#875 )	2026-02-24 12:06:09 -05:00
Sergey Mankovsky	bc6bb63c32	fix: enable sentry on frontend (#876 )	2026-02-24 17:55:14 +01:00
Juan Diego García	e7dd8b57d1	docs: update readme future plans (#874 ) * update README * improve readme * readme	2026-02-23 12:49:55 -05:00