[media attached: /home/crogers2287/.openclaw/media/inbound/file_11---ceecda19-87d4-4373-8bc0-d65164b01789.jpg (image/jpeg) | /home/crogers2287/.openclaw/media/inbound/file_11---ceecda19-87d4-4373-8bc0-d65164b01789.jpg]
To send an image back, prefer the message tool (media/path/filePath). If you must inline, use MEDIA:https://example.com/image.jpg (spaces ok, quote if needed) or a safe relative path like MEDIA:./image.jpg. Avoid absolute paths (MEDIA:/...) and ~ paths — they are blocked for security. Keep caption in the text body.
System: [2026-02-25 02:53:00 UTC] Model switched to local/qwen3.5-35b-a3b-vision.

Conversation info (untrusted metadata):
```json
{
  "message_id": "537",
  "sender": "6558388607"
}
```

You see this?


500
------------
While executing CallExpression at line 144, column 28 in source:
... {%- else %}↵        {{- raise_exception('Unexpected message role.') }}↵    {%- ...
                                           ^
Error: Jinja Exception: Unexpected message role.


image

Prompt: Describe what you see in this image - what is it showing? Is there anything unusual or interesting about it?


This image shows a high-resolution, close-up photograph of a medium-sized black dog perched on the back of a brown leather sofa.

### Detailed Description:
*   **The Dog:** The dog has short, dense black fur with a slightly coarse texture. It has a square-shaped head, floppy ears that fold over at the tips, and very expressive, light amber/brown eyes looking directly into the camera lens. There is a small amount of white or grey fur around its chin and muzzle, suggesting it may be a middle-aged or senior dog.
*   **The Pose:** The dog is positioned in a somewhat unusual way for a dog, sitting on the very top of the sofa cushions rather than on the seat. Its right front paw is folded neatly over the top of a cushion, while its left front paw hangs straight down the side. Its hind legs are stretched out behind it on the backrest of the sofa.
*   **The Setting:** The background is indoors and intentionally blurred (a "bokeh" effect), showing a hallway and a doorway. There is a soft purple or blue light glowing on the right side of the frame, which creates a nice color contrast with the warm brown of the leather and the dark fur of the dog.

### What is unusual or interesting about it?
*   **Cat-like Posture:** It is quite common for cats to sit on the narrow tops of sofa backs, but it is less common for dogs of this size to balance there. The way it is perched makes it look like it's "surveying its kingdom."
*   **Human-like Expression:** The dog’s direct, intense gaze and serious facial expression give it a very soulful, almost human-like quality.
*   **The "Long Leg" Illusion:** Because of the camera angle and the way the left front leg hangs straight down while the body is elevated, the leg looks surprisingly long, creating a slightly humorous visual.
*   **Professional Quality:** The lighting and the shallow depth of field (the blurry background) make this look like a professional pet portrait rather than just a casual snapshot.

Image model failed (anthropic/claude-haiku-4-5): 429 {"type":"error","error":{"type":"rate_limit_error","message":"This request would exceed your account's rate limit. Please try again later."},"request_id":"req_011CYU2xC3MBwxkiRAWSUWpg"}


Yeah, I see it! That's a great shot of your black dog perched up on the back of the leather sofa like a cat would. Love the expression - those amber eyes are locked right on the camera.

The purple glow in the background and the shallow depth of field give it a really nice portrait quality. And yeah, that's a pretty cat-like spot for a dog that size to be hanging out! 😄

Is this one of your pups?


Write key decisions, state changes, blockers, and artifacts to memory/2026-02-25.md. Format: ## [HH:MM] Topic. Update TASKS.md status if any tasks changed. Reply NO_REPLY if nothing worth storing.
Current time: Wednesday, February 25th, 2026 — 2:56 AM (UTC)


Conversation info (untrusted metadata):
```json
{
  "message_id": "539",
  "sender": "6558388607"
}
```

Yep that's Maggie


Maggie! She's got such soulful eyes. Great shot - she looks like she's contemplating the meaning of life from her perch there.

Thanks for sharing! Always nice to put a face to the pups in your life. 🐕


System: [2026-02-25 03:13:16 UTC] Model switched to local/qwen3.5-35b-a3b.

Conversation info (untrusted metadata):
```json
{
  "message_id": "542",
  "sender": "6558388607"
}
```

Yeah she's great


She really does seem like a character! That perch spot is prime real estate - she clearly knows how to get a good vantage point. 😊

Anything creative you want to work on today? I'm here if you need any image generation, video work, or other creative projects.


Conversation info (untrusted metadata):
```json
{
  "message_id": "544",
  "sender": "6558388607"
}
```

What kind of token speed you getting right now?


🦞 OpenClaw 2026.2.17 (4134875)
🕒 Time: Wednesday, February 25th, 2026 — 3:14 AM (UTC)
🧠 Model: local/qwen3.5-35b-a3b · 🔑 api-key dumm…ummy (models.json)
🧮 Tokens: 8.6k in / 59 out
📚 Context: 19k/205k (9%) · 🧹 Compactions: 1
🧵 Session: agent:selena:main • updated just now
⚙ Runtime: direct · Think: off · elevated
🪢 Queue: steer (depth 0)


Current session: **local/qwen3.5-35b-a3b** - 8.6k tokens in, 59 out.

I don't have direct visibility into tokens/second from here, but on your hardware with the 35b A3B model you're probably seeing somewhere in the 15-30 t/s range depending on what else is running on the GPU.

You could check the vLLM or ollama logs on fred for real-time generation speeds if you want exact numbers. Want me to look into that?


Conversation info (untrusted metadata):
```json
{
  "message_id": "546",
  "sender": "6558388607"
}
```

Check the llama.cpp logs


exec

journalctl -u llama.cpp -n 50 --no-pager 2>/dev/null || tail -50 /var/log/llama.cpp.log 2>/dev/null || find /home/crogers2287 -name "*.log" -path "*llama*" 2>/dev/null | head -5 | xargs tail -30 2>/dev/null


-- No entries --


root     2133744  0.0  0.0 3113768 16816 ?       Ssl  Feb23   0:29 /bin/ollama serve
root     2134142  0.0  0.0 3114280 15724 ?       Ssl  Feb23   0:29 /bin/ollama serve
crogers+ 2723963  0.0  0.0 1241644 24544 ?       Ssl  03:05   0:00 /home/crogers2287/llama-swap/build/llama-swap-linux-amd64 --config /home/crogers2287/llama-swap/config.yaml --listen 0.0.0.0:9069 --watch-config
crogers+ 2909933 29.4  1.0 105138712 1388572 ?   Sl   03:18   0:26 /mnt/storage/llama.cpp-nemotron/build/bin/llama-server --model /mnt/storage/gguf-models/Qwen3.5-35B-A3B-Q4_K_M.gguf --port 5812 --n-gpu-layers 999 --ctx-size 65536 --threads 8 --batch-size 2048 --flash-attn on --cont-batching --host 0.0.0.0 --jinja --split-mode layer --tensor-split 0.5,0.5 -ctk q8_0 -ctv q8_0 --reasoning-budget 0 --reasoning-format none
crogers+ 2927361 49.2  0.2 11449392 303836 ?     Sl   03:20   0:07 /mnt/storage/llama.cpp-nemotron/build/bin/llama-server --model /mnt/storage/gguf-models/Qwen3.5-35B-A3B-Q4_K_M.gguf --port 5813 --n-gpu-layers 999 --ctx-size 8192 --threads 8 --batch-size 2048 --flash-attn on --cont-batching --host 0.0.0.0 --jinja --mmproj /mnt/storage/gguf-models/Qwen3.5-35B-A3B-mmproj-F16.gguf --main-gpu 1 --split-mode none -ctk q8_0 -ctv q8_0


ls -la /home/crogers2287/llama-swap/*.log 2>/dev/null; journalctl --user -u llama* -n 30 --no-pager 2>/dev/null; ls -la /tmp/llama*.log 2>/dev/null


-rw-r--r-- 1 crogers2287 crogers2287 1201 Nov 17 02:29 /home/crogers2287/llama-swap/auto-config.log
-rw-r--r-- 1 crogers2287 crogers2287  166 Dec 18 13:15 /home/crogers2287/llama-swap/llama-swap.log
-rw-rw-r-- 1 crogers2287 crogers2287 138 Feb 25 03:05 /tmp/llama-swap.log


Watching Configuration for changes
llama-swap listening on 0.0.0.0:9069
2025/12/18 13:15:20 Fatal server error: listen tcp 0.0.0.0:9069: bind: address already in use


llama-swap listening on http://0.0.0.0:9069
2026/02/25 03:05:28 Fatal server error: listen tcp 0.0.0.0:9069: bind: address already in use


I can see two llama-server instances running for the Qwen 35B model (ports 5812 and 5813), but the llama.cpp servers themselves don't seem to log to files - they just output to stdout.

The llama-swap logs are minimal - just startup messages and a bind error (port in use).

To get real-time token speeds, you'd need to either:
1. Watch the console output directly from where llama-server was started
2. Check if there's a monitoring endpoint on the llama-server (port 5812 or 5813)

Want me to try hitting the llama-server's HTTP endpoint to see if it has stats? Or I could check nvidia-smi to see current GPU utilization while you're generating?