Merge branch 'arc53:main' into main

docs/content/Agents/notifications.mdx

@@ -70,7 +70,7 @@ GET /api/messages/<message_id>/events
 This replays the message's events past your last-seen sequence number and tails the rest live. It is backed by the Postgres `message_events` journal (retained for `MESSAGE_EVENTS_RETENTION_DAYS`, default 14).
 
 <Callout type="warning" emoji="⚠️">
-The chat reconnect endpoint is a native-async route served by the ASGI entrypoint. Under a plain `flask run` dev server it returns `404`; run the backend via the ASGI app (`uvicorn docsgpt.asgi:asgi_app`) or the production gunicorn uvicorn worker to use it. See the [Development Environment](/Deploying/Development-Environment) guide.
+Both channels are native-async routes served by the ASGI entrypoint. Under a plain `flask run` dev server they return `404`; run the backend via the ASGI app (`uvicorn docsgpt.asgi:asgi_app`) or the production gunicorn uvicorn worker to use them. See the [Development Environment](/Deploying/Development-Environment) guide.
 </Callout>
 
 ## Settings
@@ -81,6 +81,7 @@ The chat reconnect endpoint is a native-async route served by the ASGI entrypoin
 | `EVENTS_STREAM_MAXLEN` | `1000` | Per-user backlog cap (approximate). |
 | `SSE_KEEPALIVE_SECONDS` | `15` | Keepalive comment-frame cadence (keep below your proxy's idle timeout). |
 | `SSE_MAX_CONCURRENT_PER_USER` | `8` | Max simultaneous SSE connections per user (`0` disables the cap). |
+| `ASYNC_REDIS_MAX_CONNECTIONS` | `2000` | Redis connection pool per API worker. Each open SSE connection holds one, so this caps concurrent streams per worker. |
 | `EVENTS_REPLAY_MAX_PER_REQUEST` | `200` | Max backlog entries per replay request. |
 | `EVENTS_REPLAY_BUDGET_REQUESTS_PER_WINDOW` | `30` | Per-user replay requests per window (`0` disables). |
 | `EVENTS_REPLAY_BUDGET_WINDOW_SECONDS` | `60` | Replay budget window length. |

docs/content/Deploying/Development-Environment.mdx

@@ -133,7 +133,7 @@ To run the DocsGPT backend locally, you'll need to set up a Python environment a
     flask --app docsgpt/app.py run --host=0.0.0.0 --port=7091
     ```
 
-    But it serves **only** the WSGI Flask app and omits the routes mounted on the ASGI shell in `docsgpt/asgi.py`: the `/mcp` FastMCP endpoint and the native-async SSE reconnect reader `GET /api/messages/<id>/events`. Under `flask run` those paths return 404 — chat still works (`POST /stream` is a Flask route), but a stream interrupted by a disconnect won't auto-resume on reconnect. Use `flask run` only when you don't need those routes.
+    But it serves **only** the WSGI Flask app and omits the native-async routes mounted on the ASGI shell in `docsgpt/asgi.py`: the `/mcp` FastMCP endpoint, the chat reconnect reader `GET /api/messages/<id>/events`, the notification stream `GET /api/events`, the remote-device command stream `GET /api/devices/sessions/<id>/events`, and artifact downloads `GET /api/artifacts/<id>/download`. Under `flask run` those paths return 404 — chat still works (`POST /stream` is a Flask route), but live notifications, stream auto-resume, paired devices and artifact downloads don't. Use `flask run` only when you don't need them.
 
 6.  **Start the Celery Worker:**
 

docs/content/Guides/Architecture.mdx

@@ -22,7 +22,7 @@ flowchart TB
     Clients["Web UI, widgets and API clients"] --> API
 
     subgraph Runtime["DocsGPT processes"]
-        API["API process<br/>Flask routes and agent execution<br/>ASGI shell: MCP and chat reconnect"]
+        API["API process<br/>Flask routes and agent execution<br/>ASGI shell: MCP and streaming routes"]
         Redis["Redis<br/>Task broker, results and realtime delivery"]
         Worker["Celery workers<br/>Ingestion, parsing, embeddings<br/>and background agent runs"]
         API -->|"Enqueue work"| Redis
@@ -63,7 +63,7 @@ The storage boxes describe responsibilities, not a required number of servers. F
 
 ### API entry points
 
-[The ASGI application](https://github.com/arc53/DocsGPT/blob/main/docsgpt/asgi.py) mounts Flask through a WSGI adapter, the FastMCP server, and native asynchronous chat-reconnect readers in one process.
+[The ASGI application](https://github.com/arc53/DocsGPT/blob/main/docsgpt/asgi.py) mounts Flask through a WSGI adapter, the FastMCP server, and native asynchronous routes in one process. The asynchronous routes are the ones that hold a response open: the notification stream, chat reconnect, the remote-device command stream, and artifact downloads. They run on the event loop, so an idle connection doesn't occupy a Flask worker thread.
 
 | Interface | Purpose |
 | --- | --- |
@@ -76,7 +76,7 @@ The storage boxes describe responsibilities, not a required number of servers. F
 DocsGPT also acts as an **MCP client**: agents can call external MCP servers through the [MCP tool integration](/Guides/Integrations/mcp-tool-integration). This is a separate direction from exposing DocsGPT search at `/mcp`.
 
 <Callout type="info">
-Use the ASGI entry point for the complete application. A plain `flask run` server omits `/mcp` and the native async chat-reconnect routes. See [Development Environment](/Deploying/Development-Environment).
+Use the ASGI entry point for the complete application. A plain `flask run` server omits `/mcp` and the native asynchronous routes: notifications, chat reconnect, the remote-device command stream, and artifact downloads. See [Development Environment](/Deploying/Development-Environment).
 </Callout>
 
 ### Agents and retrieval

docs/content/Guides/ocr.mdx

@@ -150,6 +150,15 @@ takes over as the fallback parser. If that fallback also extracts almost
 nothing — OCR off, or no engine available — the upload fails with a clear
 message instead of silently indexing an empty document.
 
+Chat attachments are the exception: a scanned PDF attached from the message
+box is kept with no text (`extraction.status: no_text`), because the file
+itself is what a model reads. Models that take PDFs get the document; models
+that take only images get its pages as images; a text-only model is told it
+cannot read the file, and the message box warns before sending. Images work
+the same way with OCR off, and TIFF and BMP attachments are stored as PNG,
+since model providers do not accept those formats. A TIFF or BMP larger than
+40 million pixels is refused instead of converted.
+
 Mixed documents — text pages with scanned pages among them — convert
 through anydoc, which reads the text pages and skips the scanned ones. With
 OCR on, DocsGPT probes every page's text layer, OCRs the pages that have