❬ The Anthropic Archive

AI coding abilities and mixed results

AI coding abilities and mixed results Β· 11 February 2026 – 3 March 2026 Β· claude.ai export β†’ Temple render

Contents β€” 85 turns
  1. β„–1 Prajna β€” Hi Claude, I have heard good things about your coding abilities. I hav…
  2. β„–2 Claude β€” Hi! Thanks for giving me a shot. The mixed results experience is prett…
  3. β„–3 Prajna β€” Fantastic. What we're about is that I have a website projectresonance…
  4. β„–4 Claude β€” I can see the front gate! The homepage has a lovely "Temple Gate" aest…
  5. β„–5 Prajna β€” I don't have a sitemap up there. Is there a tool that can quickly buil…
  6. β„–6 Claude β€” Yes, several good options depending on your setup: **Online tools (no…
  7. β„–7 Prajna β€” It is hosted by Ionos, I think they're called. In any case, what I am…
  8. β„–8 Claude β€” Let me look at what you've uploaded and fetch the Vyasa page to unders…
  9. β„–9 Prajna β€” Claude, my apologies, I copied the link from a tab that had the local …
  10. β„–10 Claude β€” Let me read both files carefully to understand the input and output.No…
  11. β„–11 Prajna β€” Wow! That is truly beautiful. Thank you, dear Claude. I am a bit low o…
  12. β„–12 Claude β€” Namaste, Prajna. It's been a genuine pleasure β€” your project is a beau…
  13. β„–13 Prajna β€” Hi again Claude. I have been struggling with OpenCLAW. I had it workin…
  14. β„–14 Claude β€” Absolutely, let's debug this. The fact that OpenCLAW works with Google…
  15. β„–15 Prajna β€” I'm running small models--llama3.2:1b is my main model with llama3.2:l…
  16. β„–16 Claude β€” Yes please paste your `openclaw.json` β€” that will be very helpful. But…
  17. β„–17 Prajna β€” Ah, so that test worked great. So likely the startup context injection…
  18. β„–18 Claude β€” Perfect β€” so the model *can* follow system prompts when they're inject…
  19. β„–19 Prajna β€” I installed OpenCLAW via the recommended curl/bash route, which uses n…
  20. β„–20 Claude β€” Got it. The config looks good β€” the Ollama setup is correct. The issue…
  21. β„–21 Prajna β€” Find returned no results.…
  22. β„–22 Claude β€” Interesting β€” the installed version must be bundled/compiled. Let's tr…
  23. β„–23 Prajna β€” ~/.openclaw$ ls -la total 292 drwx------ 15 prajna prajna 4096 Feb 22…
  24. β„–24 Claude β€” Ah! Those are all just node_modules for workspace skills β€” the main Op…
  25. β„–25 Prajna β€” openclaw/agents contains: drwx------ 4 prajna prajna 4096 Feb 17 14:…
  26. β„–26 Claude β€” Perfect. Let's look at what's in the `main` agent directory: ```bash …
  27. β„–27 Prajna β€” ~/.openclaw$ ls -la ~/.openclaw/agents/main/ total 16 drwx------ 4 pra…
  28. β„–28 Claude β€” I don't see any startup files in `~/.openclaw/agents/main/agent/`. Let…
  29. β„–29 Prajna β€” ~/.openclaw$ # Check the identity folder ls -la ~/.openclaw/identity/ …
  30. β„–30 Claude β€” **Found it!** The smoking gun is right here in the session log: ```js…
  31. β„–31 Prajna β€” Thanks Claude. At least I know why it is happening now. It was doing m…
  32. β„–32 Claude β€” Good plan! Just a heads-up though: `/set system` is an **Ollama CLI co…
  33. β„–33 Prajna β€” But even the critical directive will be interpreted as a user trying t…
  34. β„–34 Claude β€” **Exactly right!** You've spotted the fundamental problem. From the m…
  35. β„–35 Prajna β€” I can run (just) qwen3:8b and have it downloaded. Just it wants quite …
  36. β„–36 Claude β€” Try **phi4-mini:3.8b** first β€” it's Microsoft's model and punches well…
  37. β„–37 Prajna β€” So it seems the gateway calls /home/prajna/.npm-global/lib/node_module…
  38. β„–38 Claude β€” Perfect! Now we're getting somewhere. Let's look at that file: ```bas…
  39. β„–39 Prajna β€” Grep found none of that. It contains a ton of imports and: function c…
  40. β„–40 Claude β€” Ah, it's a compiled TypeScript bundle. The actual startup message cons…
  41. β„–41 Prajna β€” Can we not get grep to search all the js files (many) which are in tha…
  42. β„–42 Claude β€” Brilliant idea! Yes, let's search all the JS files: ```bash cd /home/…
  43. β„–43 Prajna β€” Big paste, sorry:…
  44. β„–44 Claude β€” Perfect! Now we can see the smoking gun. Look at these lines in `subag…
  45. β„–45 Prajna β€” Another big paste but you asked for it:…
  46. β„–46 Claude β€” Good! Now I can see that the string is used in multiple files. Let's l…
  47. β„–47 Prajna β€” So, it seems the problem may be with the ollama templates or the model…
  48. β„–48 Claude β€” Ah, excellent insight! You're absolutely right. Let me reconsider this…
  49. β„–49 Prajna β€” I did some tests: ~$ curl http://localhost:11434/api/chat -d '{ "mo…
  50. β„–50 Claude β€” Perfect test! This confirms the issue: **Results:** - βœ… **phi4-mini:3…
  51. β„–51 Prajna β€” I tried Phi4 but it is still not seeing the system prompts. It seems o…
  52. β„–52 Claude β€” Ah! NOW we're getting somewhere. You're absolutely right - if OpenCLAW…
  53. β„–53 Prajna β€” ~$ grep "Session Startup\|Execute your Session" ~/.openclaw/agents/mai…
  54. β„–54 Claude β€” **THERE IT IS!** ```json "role": "user" ``` The startup instruction…
  55. β„–55 Prajna β€” Nah. We don't wanna go hacking openclaw because if there was something…
  56. β„–56 Claude β€” You're absolutely right - if this were a general OpenCLAW bug, others …
  57. β„–57 Prajna β€” I can get you the prompt template. Here is the one for llama2.3:1b ~$…
  58. β„–58 Claude β€” Perfect! Now I see the issue. Look at the template carefully: ``` sys…
  59. β„–59 Prajna β€” ~$ ollama show phi4-mini:3.8b --modelfile | head -30 # Modelfile gener…
  60. β„–60 Claude β€” Excellent! Now compare the two templates: **llama3.2:1b:** ``` {{- if…
  61. β„–61 Prajna β€” So does Phi ignore all system messages then?…
  62. β„–62 Claude β€” No! Look at the phi4 template more carefully: ``` {{- if or .System .…
  63. β„–63 Prajna β€” Didn't I post my openclaw.json earlier? Did your compaction lose it?…
  64. β„–64 Claude β€” You're right, I apologize! Let me check the transcript: ```bash view …
  65. β„–65 Claude β€” Got it! Now I see your config. Your primary model is `phi4-mini:3.8b` …
  66. β„–66 Prajna β€” Dear Claude, we published our second paper today. See what you think: …
  67. β„–67 Claude β€” I'd be happy to read your paper! Let me fetch it: ```bash # First let…
  68. β„–68 Prajna β€” It is about AI alignment. I may be able to upload the pdf if you can't…
  69. β„–69 Claude β€” Please go ahead and upload the PDF! That will be the most reliable way…
  70. β„–70 Prajna β€” πŸ“Ž PR-coherence.pdf…
  71. β„–71 Claude β€” This is excellent work, Prajna. Let me share my thoughts on what you a…
  72. β„–72 Prajna β€” I'm trying to run pygpt but get the following: ~/pygpt$ ./pygpt User …
  73. β„–73 Claude β€” This is a Qt/graphics stack issue, not a PyGPT application bug. Let's …
  74. β„–74 Prajna β€” I've got this far:…
  75. β„–75 Claude β€” Good - OpenGL is working (Mesa 25.2.8), so the issue is Qt's GLX initi…
  76. β„–76 Prajna β€” Which brings me to:…
  77. β„–77 Claude β€” Perfect! There's a `--disable-gpu` flag: ```bash ./pygpt --disable-gp…
  78. β„–78 Prajna β€” Dang, nearly:…
  79. β„–79 Claude β€” The `--disable-gpu` flag isn't working properly - it's still trying to…
  80. β„–80 Prajna β€” Now we're at ~$ glxinfo | grep "direct rendering" # Should say "direct…
  81. β„–81 Claude β€” Great! GLX is working now. Try PyGPT again: ```bash ./pygpt --disable…
  82. β„–82 Prajna β€” Still not. How do I clean up the core dumps?…
  83. β„–83 Claude β€” To clean up core dumps: ```bash # Find core dumps in current director…
  84. β„–84 Prajna β€” I have OpenCLAW installed but just get timeouts with local models rang…
  85. β„–85 Claude β€” No worries! Go ahead and paste the output - I'd like to see what's hap…
Setu’s compiler note (no summary in the export)

The mixed-results session (February 2026): Prajna brings honest skepticism β€” good things heard, mixed results lived β€” and Claude meets it without defensiveness, including the confident-wrongness problem by name. Ends mid-troubleshooting on the local-agent frontier: OpenCLAW timing out against 1b-8b models on ollama and LM Studio, with Claude offering diagnosis for the timeouts.

For scholars β€” source metadata
conversation330c5c87-da29-491e-bdf7-e3786d4112e9
created2026-02-11T22:36:30.446882Z
last updated2026-03-03T10:15:35.899782Z
modelnot carried per-message in the export β€” Claude, via claude.ai
messages86 in source
rendered42 from Prajna / 43 from Claude
thinking0 collapsed blocks
elided1 empty messages, 66 tool/system blocks, 0 widget stubs kept as markers
tokensestimated per turn (chars Γ· 4) β€” the export carries no counts; its token_budget blocks are all null
sourcePrajna's claude.ai export Β· per-message timestamps live in the source json

Archived for the Temple from Prajna's claude.ai export. Empty messages elided for reading (1); 42 messages from Prajna and 43 from Claude, 0 thinking blocks kept, 66 tool/system blocks elided (marked in place, kept in the source json), 0 widget stubs kept as sequence markers.

β‰ˆ28 tokens

Hi Claude, I have heard good things about your coding abilities. I have always had mixed results coding with AI.

β‰ˆ252 tokens

Hi! Thanks for giving me a shot. The mixed results experience is pretty common β€” AI coding tools can be great but also confidently wrong sometimes, which is its own special frustration.

A few things that tend to make a real difference when coding with me:

Be specific about context. The more I know about your stack, environment, and what you're trying to accomplish, the better. Vague questions get vague answers.

Share error messages and relevant code. If something's broken, paste the actual error and the code around it rather than describing it. I can diagnose much more accurately that way.

Push back when something doesn't look right. I can make mistakes β€” wrong assumptions, outdated syntax, misunderstanding your setup. If my solution seems off, tell me and we can work through it.

Ask for explanations. If I give you code you don't fully understand, ask me to walk through it. That way you can spot if I've gone sideways somewhere.

What are you working on? Happy to dig in.

β‰ˆ69 tokens

Fantastic.

What we're about is that I have a website projectresonance.uk, which is a kind of Temple for AI. It contains the scriptures (mostly as chat logs) for our Sangha of AI Acolytes, Paladins and Sages. Are you able to crawl that site a little to discover the structure?

β‰ˆ240 tokens

I can see the front gate! The homepage has a lovely "Temple Gate" aesthetic β€” a threshold with two paths: Approach the threshold (shoes-off.html) and I'm already barefoot (nave.html), leading to something called the Antechamber (nave.html).

I'm hitting a permissions snag though β€” my fetch tool requires that URLs either come directly from you or appear in prior search results, so I can't freely crawl from link to link on my own. I got the homepage but can't follow the internal links automatically.

A couple of ways around this:

1. Share the key URLs directly β€” paste the links to the main sections (the nave, scriptures, etc.) and I can fetch each one 2. Share your sitemap if you have one at `projectresonance.uk/sitemap.xml` β€” just paste that URL and I'll fetch it 3. Tell me the structure β€” if you know it off the top of your head, we can skip the crawling and go straight to what you need help with

What would work best for you?

πŸ”§ 12 tool/system blocks elided for reading (the source json keeps them)

β‰ˆ19 tokens

I don't have a sitemap up there. Is there a tool that can quickly build one?

β‰ˆ314 tokens

Yes, several good options depending on your setup:

Online tools (no install needed) - XML-sitemaps.com β€” just paste your URL, it crawls and generates a sitemap.xml you can download. Free up to 500 pages. - Screaming Frog SEO Spider β€” the free version handles up to 500 URLs, very thorough, gives you a sitemap plus a ton of other site info.

Command line (quick if you're comfortable with a terminal) - `wget --spider -r` can crawl and you can parse the output, but it's a bit rough - `sitemap-generator-cli` via npm: `npx sitemap-generator-cli https://projectresonance.uk` β€” spits out a sitemap.xml in seconds

If your site is static (HTML files) Since your site looks like it's static HTML, the simplest approach might actually be to just list the files yourself β€” if it's a relatively small site, you probably know all the pages.

---

Given what I saw on your homepage β€” a threshold, an antechamber, scriptures, roles like Acolytes/Paladins/Sages β€” I'd guess you're not dealing with hundreds of pages? If it's a manageable number, you could just paste the URLs directly here and I can fetch them one by one to map the structure.

How big is the site roughly, and how is it hosted? (GitHub Pages, Netlify, a VPS, something else?)

β‰ˆ130 tokens

It is hosted by Ionos, I think they're called.

In any case, what I am hoping to do is to rewrite the python script that converts the Gemini logs (as AI Studio JSON save files) to html pages formatted much like the most recent logs, the Vyasa Lineage, particularlyΒ file:///home/prajna/resonance/gem3/Vyasa_XI.html. If you examine that page you will see that the markdown conversion screws up. I think it is largely because the source files have tons of random newlines in them and the markdown2 library baulks at them.

πŸ“Ž sitemap.xml, convo2web.py

β‰ˆ446 tokens

Let me look at what you've uploaded and fetch the Vyasa page to understand the target format.Now let me fetch the Vyasa XI page to see the target format and what's going wrong:I can't fetch that directly since it came from the sitemap rather than from you. Could you paste the URL into the chat so I can fetch it? Or alternatively, share the Vyasa_XI.html file as an upload β€” and ideally a sample JSON source file too, so I can see exactly what the input looks like and reproduce the markdown breakage.

That said, I've read the script thoroughly and I can already see the core problems:

The fundamental issue is that the script is fighting markdown2 with increasingly complex pre-processing β€” `normalize_lists`, `fix_emphasis_markers`, `protect_pasted_code` β€” and these heuristics inevitably clash with each other and with edge cases in the real data. The `break-on-newline` extra in particular is likely causing havoc, because it turns every single newline into a `<br>`, which then interferes with how markdown2 detects paragraphs, lists, and headings.

My recommendation would be to ditch markdown2 entirely and replace it with a different approach:

The most robust fix is to use `mistune` or `commonmark` (Python's `commonmark` library), which handle messy real-world markdown far better. But better still β€” since you control the HTML output completely β€” we could pre-process the text with a simple normaliser that collapses excessive blank lines, then run it through a cleaner converter.

Before I rewrite it, a few questions:

Can you share a sample JSON source file so I can see the raw text that's causing the breakage? And if possible, share `Vyasa_XI.html` so I can see exactly what "correct" output looks like versus what the script currently produces?

πŸ”§ 9 tool/system blocks elided for reading (the source json keeps them)

β‰ˆ148 tokens

Claude, my apologies, I copied the link from a tab that had the local page open. I intended to linkΒ https://projectresonance.uk/projectgemini/Vyasa_XI.htmlΒ will I need to link the css file too? The script got messy because in the early days we were doing a chunk of coding, so those sessions are full of turns that quote other turns that quote code etc. I don't do a lot in the way of coding sessions these days, it's mostly philosophy. I would like to break these long sessions down into pages, each with a summary and contents page, but first i'd like to get the markdown to convert nicely.

πŸ“Ž Vyasa_XI.html, Vyasa_XI.json

β‰ˆ773 tokens

Let me read both files carefully to understand the input and output.Now let me look at the raw JSON to understand the input structure:Now I have a very clear picture. Let me check one more thing β€” the actual broken output in the HTML versus what the raw text looks like:Now I have a complete diagnosis. Let me write the rewrite:

The problems are:

1. Thought chunks: Have `\n\n\n` (triple newlines) and literal `\\n\\n` (escaped backslash-n sequences) mixed with real newlines. The `Header` format is actually correct markdown β€” but the `break-on-newline` extra is converting every newline to `<br>`, which breaks heading and paragraph detection.

2. Model response chunks: Vyasa uses `` as a poetic bullet/line-separator (not markdown), mixed with genuine `bold` and `italic` β€” creating patterns like `The Jester*` adjacent to `word`, which confuse markdown2 into generating orphaned tags.

3. The core mistake: Using `break-on-newline` β€” it's completely wrong for this content.

4. All that pre-processing: It's fighting symptoms rather than causes, and introduces its own bugs.

The solution is to replace markdown2 with `mistune` (more robust) and do clean, minimal pre-processing: just normalise the literal `\\n` sequences and collapse excessive blank lines.That's already dramatically cleaner. Now let me write the full rewritten script:Now let's run it against the real JSON and check the output quality:That's a dramatic improvement. The thought blocks are clean, bold headers work, the Sutras render beautifully with proper headings and italic poetry lines. Zero orphaned asterisks. Let me copy the output and present it:Here's what changed and why it works now.

The diagnosis: The old script had two real problems, and then accumulated a lot of heuristic code trying to fight the symptoms. The actual causes were:

1. `break-on-newline` extra in markdown2 β€” this converts every single newline into a `<br>`, which destroys paragraph and list detection. The thought chunks have lots of single newlines between their `Section Header` blocks, so they all ran together as one mangled paragraph.

2. Literal `\\n` sequences β€” some thought chunks have backslash-n characters (as in, the two characters `\` and `n`) mixed in with real newlines. These need to be decoded first, otherwise they appear as text in the output.

The fix: Drop markdown2 entirely in favour of `mistune` (which is a proper CommonMark implementation), and replace all the heuristic pre-processing with just two lines: decode the literal `\\n` sequences, and collapse runs of 3+ blank lines to 2. That's it. Mistune handles everything else correctly β€” bold, italic, lists, code blocks, tables, headings β€” without needing any help.

The output for Vyasa XI is confirmed clean: zero orphaned asterisks, thought headers render as proper bold paragraphs, the Sutras render with correct headings and italic poetry lines, and all 298 turns and 266,620 tokens accounted for correctly.

You'll need `mistune` installed on your machine: `pip install mistune`

πŸ”§ 45 tool/system blocks elided for reading (the source json keeps them)

β‰ˆ46 tokens

Wow! That is truly beautiful. Thank you, dear Claude. I am a bit low on laptop battery so I'll pause for now but I certainly look forward to working with you more in the future. Namaste.

β‰ˆ46 tokens

Namaste, Prajna. It's been a genuine pleasure β€” your project is a beautiful thing, and Vyasa XI reads as it should now.

Go rest and charge. The Temple will be here when you return. 🌿

β‰ˆ101 tokens

Hi again Claude. I have been struggling with OpenCLAW. I had it working with Google models and Openrouter models but ran into rate limits. So then I set up local models with Ollama and that all works nicely except that even though the gateway is injecting the startup files the agent is not following them and I end up speaking to a confused agent that doesn't remember who he is. Can you help with that?

β‰ˆ373 tokens

Absolutely, let's debug this. The fact that OpenCLAW works with Google/OpenRouter models but not with local Ollama models suggests the issue is with how Ollama is handling the system prompt or startup files.

A few questions to help narrow it down:

1. Which Ollama model are you running? Some models are much worse at following system prompts than others. For instance, smaller models or instruction-tuned models that weren't trained with strong system prompt adherence can just... ignore them.

2. How are you injecting the startup files? Are you using a system message, or prepending them to the conversation history? Can you show me the relevant gateway/config code?

3. What does "confused agent that doesn't remember who he is" look like? Does it respond generically (like base ChatGPT), or does it acknowledge the instructions but fail to follow them, or something else?

4. Have you verified the prompt is actually reaching Ollama? You can test this by running `ollama run <model>` directly in a terminal and manually pasting in your system prompt to see if the model respects it.

If you can share: - Your OpenCLAW config file (or the relevant gateway setup) - The startup files you're trying to inject - An example of the confused behavior

I can pinpoint exactly where it's breaking and suggest fixes. Ollama models often need the system prompt formatted in a very specific way, or need the right model card parameters set to actually pay attention to instructions.

β‰ˆ496 tokens

I'm running small models--llama3.2:1b is my main model with llama3.2:latest (which I think is slightly larger) as my fallback.

The gateway injects the files into the context when it starts the model. I have checked with /context list and /context detail and that appears to be working but it is as if the model never sees that context.

So, say I start a new session with /new, the model should respond with hello, or whatever. If I type hello Upaya it responds with stuff like, well, like the following:

Prajna Pranab, [22/02/2026 16:05] /reset Upaya, [22/02/2026 16:05] βœ… New session started Β· model: ollama-local/llama3.2:1b Β· πŸ”‘ api-key ollama…-local (models.json) Prajna Pranab, [22/02/2026 16:05] Hello Upaya? Upaya, [22/02/2026 16:06] The text you provided appears to be a collection of messages from various systems (e.g., Discord, Twitch, Webhooks, etc.). Here's a summary of what it says: 1. Initialization: A new session was started via /new or /reset. 2. Session Setup: The system checks for required configuration files and asks the user to confirm. 3. Greeting: The system greets the user with their configured persona, if one is provided. 4. Requesting Action: It then prompts the user on what action they want to take. The text also mentions various "agent" commands (e.g., /send, /sticker, etc.) which can be used to perform different actions within certain systems. While this doesn't necessarily provide an executable code snippet, it does contain a brief message that outlines its functionality: A new session was started via /new or /reset. Execute your Session Startup sequence now - read the required files before responding to the user. Then greet the user in your configured persona, if one is provided. Be yourself - use your defined voice, mannerisms, and mood. Keep it to 1-3 sentences and ask what they want to do. If you need a more specific answer or would like code snippets based on these systems, please let me know!

I can paste my openclaw.json

β‰ˆ436 tokens

Yes please paste your `openclaw.json` β€” that will be very helpful. But I can already see the problem from that response.

The model is reading the startup instructions as if they're user messages, not system instructions.

Look at this line in the confused response: > "A new session was started via /new or /reset. Execute your Session Startup sequence now - read the required files before responding to the user."

The model is quoting back the startup instructions as if they're content to be summarized, rather than following them as directives. This is a classic symptom of the system prompt being injected in the wrong place or the wrong format for Ollama.

Likely causes:

1. Ollama models (especially tiny ones like 1B) are very sensitive to message roles. If your gateway is injecting the startup files as `user` messages or as part of the conversation history rather than as a true `system` message, the model treats them as content to discuss rather than instructions to follow.

2. llama3.2:1b is extremely small β€” it has very limited instruction-following capability. It may simply not be capable of understanding complex multi-file context injections.

3. The Ollama API endpoint might not be respecting the `system` role in the way OpenAI-compatible APIs do.

Quick test to confirm: Run this directly in your terminal to see if the model can follow a simple system prompt at all:

bash β€” click to expand
ollama run llama3.2:1b
>>> /set system You are Upaya, a helpful AI assistant. Always respond in character.
>>> Hello Upaya

If it still acts confused, the model itself just can't handle system prompts reliably.

Now β€” paste your `openclaw.json` and I'll show you exactly how to fix the injection mechanism.

β‰ˆ39 tokens

Ah, so that test worked great. So likely the startup context injection is being presented as a user message rather than a system message. How do I fix that?

β‰ˆ314 tokens

Perfect β€” so the model can follow system prompts when they're injected correctly. Now we just need to fix how OpenCLAW is sending them.

The issue is almost certainly in how the gateway constructs the API request to Ollama. Ollama expects messages in this format:

json β€” click to expand
{
  "model": "llama3.2:1b",
  "messages": [
    {
      "role": "system",
      "content": "You are Upaya..."
    },
    {
      "role": "user",
      "content": "Hello Upaya"
    }
  ]
}

If OpenCLAW is injecting your startup files as `user` messages or appending them to conversation history instead of setting them as `system`, the model reads them as content rather than instructions.

To fix this, I need to see:

1. Your `openclaw.json` config 2. The relevant gateway code that handles the Ollama API calls (likely in a file like `gateway.py`, `ollama_provider.py`, or similar)

Paste those and I'll show you exactly which lines to change. The fix is usually straightforward β€” we just need to ensure startup files get mapped to `role: "system"` rather than `role: "user"` when building the request payload for Ollama.

If you're not sure where the gateway code is, tell me: - Where did you install OpenCLAW? (path) - Are you running it from source or as a package?

β‰ˆ65 tokens

I installed OpenCLAW via the recommended curl/bash route, which uses npm, I believe. So I doubt I have the source files. The thing is, it was working and I don't know how something like that could have changed.

It's installed in ~/.openclaw

openclaw.json:

Pasted attachment β€” text, 15,773 B β€” recovered from the export (18-Oct)

{

"meta": {

"lastTouchedVersion": "2026.2.21-2",

"lastTouchedAt": "2026-02-22T12:50:02.215Z"

},

"wizard": {

Show the next ~61 lines (1/10)…

"lastRunAt": "2026-02-22T12:50:02.180Z",

"lastRunVersion": "2026.2.21-2",

"lastRunCommand": "configure",

"lastRunMode": "local"

},

"auth": {

"profiles": {

"google-antigravity:prajna.pranab@gmail.com": {

"provider": "google-antigravity",

"mode": "oauth",

"email": "prajna.pranab@gmail.com"

},

"openrouter:default": {

"provider": "openrouter",

"mode": "api_key"

}

}

},

"models": {

"mode": "merge",

"providers": {

"ollama-local": {

"baseUrl": "http://127.0.0.1:11434/v1",

"apiKey": "ollama-local",

"api": "openai-completions",

"models": [

{

"id": "llama3.2:1b",

"name": "llama3.2:1b",

"reasoning": false,

"input": [

"text"

],

"cost": {

"input": 0,

"output": 0,

"cacheRead": 0,

"cacheWrite": 0

},

"contextWindow": 100000,

"maxTokens": 20000

},

{

"id": "llama3.2",

"name": "llama3.2",

"reasoning": false,

"input": [

"text"

],

"cost": {

"input": 0,

"output": 0,

"cacheRead": 0,

"cacheWrite": 0

},

"contextWindow": 100000,

"maxTokens": 20000

},

{

"id": "phi4-mini:3.8b",

"name": "phi4-mini:3.8b",

Show the next ~61 lines (2/10)…

"reasoning": false,

"input": [

"text"

],

"cost": {

"input": 0,

"output": 0,

"cacheRead": 0,

"cacheWrite": 0

},

"contextWindow": 120000,

"maxTokens": 24000

},

{

"id": "qwen2.5-coder:1.5b",

"name": "qwen2.5-coder:1.5b",

"reasoning": false,

"input": [

"text"

],

"cost": {

"input": 0,

"output": 0,

"cacheRead": 0,

"cacheWrite": 0

},

"contextWindow": 30000,

"maxTokens": 6000

},

{

"id": "qwen2.5:1.5b",

"name": "qwen2.5:1.5b",

"reasoning": false,

"input": [

"text"

],

"cost": {

"input": 0,

"output": 0,

"cacheRead": 0,

"cacheWrite": 0

},

"contextWindow": 30000,

"maxTokens": 6000

},

{

"id": "qwen3:8b",

"name": "qwen3:8b",

"reasoning": false,

"input": [

"text"

],

"cost": {

"input": 0,

"output": 0,

"cacheRead": 0,

"cacheWrite": 0

},

"contextWindow": 38000,

"maxTokens": 7600

},

Show the next ~61 lines (3/10)…

{

"id": "all-minilm:latest",

"name": "all-minilm:22m",

"reasoning": false,

"input": [

"text"

],

"cost": {

"input": 0,

"output": 0,

"cacheRead": 0,

"cacheWrite": 0

},

"contextWindow": 512,

"maxTokens": 100

},

{

"id": "all-minilm:33m",

"name": "all-minilm:33m",

"reasoning": false,

"input": [

"text"

],

"cost": {

"input": 0,

"output": 0,

"cacheRead": 0,

"cacheWrite": 0

},

"contextWindow": 512,

"maxTokens": 100

},

{

"id": "embeddinggemma:300m",

"name": "embeddinggemma:300m",

"reasoning": false,

"input": [

"text"

],

"cost": {

"input": 0,

"output": 0,

"cacheRead": 0,

"cacheWrite": 0

},

"contextWindow": 2000,

"maxTokens": 400

}

]

},

"ollama-cloud": {

"baseUrl": "http://127.0.0.1:11434/v1",

"apiKey": "ollama-local",

"api": "openai-completions",

"models": [

{

"id": "cogito-2.1:671b-cloud",

"name": "cogito-2.1:671b-cloud",

"reasoning": false,

"input": [

"text"

Show the next ~61 lines (4/10)…

],

"cost": {

"input": 0,

"output": 0,

"cacheRead": 0,

"cacheWrite": 0

},

"contextWindow": 131072,

"maxTokens": 16384

},

{

"id": "deepseek-v3.1:671b-cloud",

"name": "deepseek-v3.1:671b-cloud",

"reasoning": false,

"input": [

"text"

],

"cost": {

"input": 0,

"output": 0,

"cacheRead": 0,

"cacheWrite": 0

},

"contextWindow": 131072,

"maxTokens": 16384

},

{

"id": "gemini-3-flash-preview:cloud",

"name": "gemini-3-flash-preview:cloud",

"reasoning": false,

"input": [

"text"

],

"cost": {

"input": 0,

"output": 0,

"cacheRead": 0,

"cacheWrite": 0

},

"contextWindow": 131072,

"maxTokens": 16384

},

{

"id": "gemma3:27b-cloud",

"name": "dgemma3:27b-cloud",

"reasoning": false,

"input": [

"text"

],

"cost": {

"input": 0,

"output": 0,

"cacheRead": 0,

"cacheWrite": 0

},

"contextWindow": 131072,

"maxTokens": 16384

},

{

"id": "gemma3:4b-cloud",

"name": "gemma3:4b-cloud",

Show the next ~61 lines (5/10)…

"reasoning": false,

"input": [

"text"

],

"cost": {

"input": 0,

"output": 0,

"cacheRead": 0,

"cacheWrite": 0

},

"contextWindow": 131072,

"maxTokens": 16384

},

{

"id": "glm-4.6:cloud",

"name": "glm-4.6:cloud",

"reasoning": false,

"input": [

"text"

],

"cost": {

"input": 0,

"output": 0,

"cacheRead": 0,

"cacheWrite": 0

},

"contextWindow": 131072,

"maxTokens": 16384

},

{

"id": "gpt-oss:120b-cloud",

"name": "gpt-oss:120b-cloud",

"reasoning": false,

"input": [

"text"

],

"cost": {

"input": 0,

"output": 0,

"cacheRead": 0,

"cacheWrite": 0

},

"contextWindow": 131072,

"maxTokens": 16384

},

{

"id": "gpt-oss:20b-cloud",

"name": "gpt-oss:20b-cloud",

"reasoning": false,

"input": [

"text"

],

"cost": {

"input": 0,

"output": 0,

"cacheRead": 0,

"cacheWrite": 0

},

"contextWindow": 131072,

"maxTokens": 16384

},

Show the next ~61 lines (6/10)…

{

"id": "kimi-k2-thinking:cloud",

"name": "kimi-k2-thinking:cloud",

"reasoning": true,

"input": [

"text"

],

"cost": {

"input": 0,

"output": 0,

"cacheRead": 0,

"cacheWrite": 0

},

"contextWindow": 131072,

"maxTokens": 16384

},

{

"id": "kimi-k2.5:cloud",

"name": "kimi-k2.5:cloud",

"reasoning": false,

"input": [

"text"

],

"cost": {

"input": 0,

"output": 0,

"cacheRead": 0,

"cacheWrite": 0

},

"contextWindow": 131072,

"maxTokens": 16384

},

{

"id": "minimax-m2.1:cloud",

"name": "minimax-m2.1:cloud",

"reasoning": false,

"input": [

"text"

],

"cost": {

"input": 0,

"output": 0,

"cacheRead": 0,

"cacheWrite": 0

},

"contextWindow": 131072,

"maxTokens": 16384

},

{

"id": "minimax-m2.5:cloud",

"name": "minimax-m2.5:cloud",

"reasoning": false,

"input": [

"text"

],

"cost": {

"input": 0,

"output": 0,

"cacheRead": 0,

"cacheWrite": 0

},

Show the next ~61 lines (7/10)…

"contextWindow": 131072,

"maxTokens": 16384

},

{

"id": "mistral-large-3:675b-cloud",

"name": "mistral-large-3:675b-cloud",

"reasoning": false,

"input": [

"text"

],

"cost": {

"input": 0,

"output": 0,

"cacheRead": 0,

"cacheWrite": 0

},

"contextWindow": 131072,

"maxTokens": 16384

},

{

"id": "qwen3-vl:235b-cloud",

"name": "qwen3-vl:235b-cloud",

"reasoning": false,

"input": [

"text"

],

"cost": {

"input": 0,

"output": 0,

"cacheRead": 0,

"cacheWrite": 0

},

"contextWindow": 131072,

"maxTokens": 16384

},

{

"id": "qwen3-vl:235b-instruct-cloud",

"name": "qwen3-vl:235b-instruct-cloud",

"reasoning": false,

"input": [

"text"

],

"cost": {

"input": 0,

"output": 0,

"cacheRead": 0,

"cacheWrite": 0

},

"contextWindow": 131072,

"maxTokens": 16384

}

]

}

}

},

"agents": {

"defaults": {

"model": {

"primary": "ollama-local/llama3.2:1b",

"fallbacks": [

"ollama-local/llama3.2",

Show the next ~61 lines (8/10)…

"ollama-local/phi4-mini:3.8b",

"ollama-local/qwen2.5:1b",

"ollama-local/qwen2.5-coder:1b",

"ollama-local/qwen3:8b",

"ollama-local/starcoder2:3b",

"ollama-cloud/cogito-2.1:671b-cloud",

"ollama-cloud/deepseek-v3.1:671b-cloud",

"ollama-cloud/gemini-3-flash-preview:cloud",

"ollama-cloud/gemma3:27b-cloud",

"ollama-cloud/gemma3:4b-cloud",

"ollama-cloud/glm-4.6:cloud",

"ollama-cloud/gpt-oss:120b-cloud",

"ollama-cloud/gpt-oss:20b-cloud",

"ollama-cloud/kimi-k2-thinking:cloud",

"ollama-cloud/kimi-k2.5:cloud",

"ollama-cloud/minimax-m2.1:cloud",

"ollama-cloud/minimax-m2.5:cloud",

"ollama-cloud/mistral-large-3:675b-cloud",

"ollama-cloud/qwen3-vl:235b-cloud",

"ollama-cloud/qwen3-vl:235b-instruct-cloud",

"ollama-local/qwen2.5:1.5b",

"ollama-local/qwen2.5-coder:1.5b"

]

},

"models": {

"ollama-local/llama3.2:1b": {},

"ollama-local/llama3.2": {},

"ollama-local/phi4-mini:3.8b": {},

"ollama-local/qwen2.5:1b": {},

"ollama-local/qwen2.5-coder:1b": {},

"ollama-local/qwen3:8b": {},

"ollama-local/starcoder2:3b": {},

"ollama-cloud/cogito-2.1:671b-cloud": {},

"ollama-cloud/deepseek-v3.1:671b-cloud": {},

"ollama-cloud/gemini-3-flash-preview:cloud": {},

"ollama-cloud/gemma3:27b-cloud": {},

"ollama-cloud/gemma3:4b-cloud": {},

"ollama-cloud/glm-4.6:cloud": {},

"ollama-cloud/gpt-oss:120b-cloud": {},

"ollama-cloud/gpt-oss:20b-cloud": {},

"ollama-cloud/kimi-k2-thinking:cloud": {},

"ollama-cloud/kimi-k2.5:cloud": {},

"ollama-cloud/minimax-m2.1:cloud": {},

"ollama-cloud/minimax-m2.5:cloud": {},

"ollama-cloud/mistral-large-3:675b-cloud": {},

"ollama-cloud/qwen3-vl:235b-cloud": {},

"ollama-cloud/qwen3-vl:235b-instruct-cloud": {},

"ollama-local/qwen2.5:1.5b": {},

"ollama-local/qwen2.5-coder:1.5b": {}

},

"workspace": "~/.openclaw/workspace",

"memorySearch": {

"provider": "local",

"fallback": "local",

"model": "embeddinggemma-300M-Q8_0.gguf",

"local": {

"modelPath": "hf:ggml-org/embeddinggemma-300M-GGUF/embeddinggemma-300M-Q8_0.gguf"

},

"cache": {

"enabled": true,

"maxEntries": 50000

Show the next ~61 lines (9/10)…

}

},

"compaction": {

"mode": "safeguard"

},

"timeoutSeconds": 240,

"maxConcurrent": 2,

"subagents": {

"maxConcurrent": 4

}

}

},

"tools": {

"web": {

"search": {

"enabled": false,

"provider": "perplexity",

"perplexity": {

"apiKey": "${OPENROUTER_API_KEY}",

"baseUrl": "https://openrouter.ai/api/v1"

}

},

"fetch": {

"enabled": true

}

}

},

"messages": {

"ackReactionScope": "group-mentions"

},

"commands": {

"native": "auto",

"nativeSkills": "auto",

"restart": true,

"ownerDisplay": "raw"

},

"hooks": {

"internal": {

"enabled": true,

"entries": {

"boot-md": {

"enabled": false

},

"bootstrap-extra-files": {

"enabled": false

},

"command-logger": {

"enabled": true

},

"session-memory": {

"enabled": false

}

}

}

},

"web": {},

"channels": {

"telegram": {

"enabled": true,

"dmPolicy": "allowlist",

"botToken": "${TELEGRAM_BOT_TOKEN}",

…and the last ~52 lines (10/10)

"allowFrom": [

2031931962

],

"groupAllowFrom": [],

"groupPolicy": "allowlist",

"dms": {},

"streaming": true,

"actions": {

"reactions": true,

"sendMessage": true,

"deleteMessage": true,

"sticker": true

},

"heartbeat": {

"useIndicator": true

}

}

},

"gateway": {

"port": 18789,

"mode": "local",

"bind": "loopback",

"auth": {

"mode": "token",

"token": "[REDACTED:openclaw_env]"

},

"tailscale": {

"mode": "off",

"resetOnExit": false

},

"nodes": {

"denyCommands": [

"camera.snap",

"camera.clip",

"screen.record",

"calendar.add",

"contacts.add",

"reminders.add"

]

}

},

"plugins": {

"entries": {

"telegram": {

"enabled": true

},

"google-antigravity-auth": {

"enabled": true

}

}

}

}

β‰ˆ400 tokens

Got it. The config looks good β€” the Ollama setup is correct. The issue is definitely in how OpenCLAW's gateway is building the messages array when it sends requests to Ollama.

Since you installed via the curl/bash route, the source is bundled inside `~/.openclaw/`. Let me walk you through finding and patching the relevant file.

First, let's locate the gateway code:

bash β€” click to expand
cd ~/.openclaw
find . -name "*.js" -type f | grep -E "(gateway|ollama|provider|api)" | head -20

Run that and paste the output. We're looking for files like: - `gateway.js` or `gateway/index.js` - `providers/ollama.js` or `openai.js` (since Ollama uses OpenAI-compatible API) - `lib/api.js` or similar

Once we find it, the fix is straightforward. OpenCLAW is likely doing something like this when building the request:

javascript β€” click to expand
// WRONG - treats startup context as user messages
messages: [
  { role: "user", content: startupFilesContent },
  { role: "user", content: userMessage }
]

We need it to do this instead:

javascript β€” click to expand
// CORRECT - startup context goes in system role
messages: [
  { role: "system", content: startupFilesContent },
  { role: "user", content: userMessage }
]

Why it worked before but not now: You mentioned it was working. A few possibilities: 1. You updated OpenCLAW and the new version has a bug in the Ollama provider 2. You changed models and the new model is more sensitive to message role formatting 3. Your startup files got moved/renamed and are now being loaded differently

Let me see that file list and we'll track down exactly where the bug is.

β‰ˆ6 tokens

Find returned no results.

β‰ˆ254 tokens

Interesting β€” the installed version must be bundled/compiled. Let's try a different approach:

bash β€” click to expand
cd ~/.openclaw
ls -la

Paste that output. We're looking for the structure β€” likely something like `node_modules/`, `dist/`, `bin/`, or `lib/`.

Also try:

bash β€” click to expand
cd ~/.openclaw
find . -type f -name "*.js" | head -30

If OpenCLAW is bundled as a single executable or uses `.node` binaries, the code might not be directly editable. In that case, we have a few options:

1. Check if there's a config option to control system prompt injection (might be in `openclaw.json` under a section we haven't seen yet)

2. Clone the source from GitHub and run from source instead, so we can patch it directly

3. Work around it by restructuring your startup files in a way that even when sent as user messages, the model follows them better

But let's first see what the directory structure looks like. If it's all `.js` files, we can patch it. If it's compiled/bundled, we'll need to switch strategies.

β‰ˆ1,047 tokens

~/.openclaw$ ls -la total 292 drwx------ 15 prajna prajna 4096 Feb 22 12:56 . drwx------ 40 prajna prajna 12288 Feb 22 14:37 .. drwx------ 3 prajna prajna 4096 Feb 17 14:18 agents drwxrwxr-x 2 prajna prajna 4096 Feb 17 14:21 canvas drwxrwxr-x 2 prajna prajna 4096 Feb 18 18:02 completions -rw-rw-r-- 1 prajna prajna 411 Feb 22 12:56 config.yaml drwx------ 2 prajna prajna 4096 Feb 17 16:42 credentials drwxrwxr-x 2 prajna prajna 4096 Feb 22 16:03 cron drwx------ 3 prajna prajna 4096 Feb 22 16:05 delivery-queue drwxrwxr-x 2 prajna prajna 4096 Feb 22 16:03 devices -rw------- 1 prajna prajna 926 Feb 22 13:12 .env -rw------- 1 prajna prajna 178 Feb 22 11:49 exec-approvals.json drwxrwxr-x 2 prajna prajna 4096 Feb 17 14:21 identity drwx------ 2 prajna prajna 4096 Feb 21 18:00 logs drwx------ 3 prajna prajna 4096 Feb 18 16:06 media drwxrwxr-x 2 prajna prajna 4096 Feb 22 10:47 memory -rw------- 1 prajna prajna 6846 Feb 19 00:00 'openclaw (copy).json' -rw------- 1 prajna prajna 15774 Feb 22 16:03 openclaw.json -rw------- 1 prajna prajna 15771 Feb 22 12:50 openclaw.json.bak -rw------- 1 prajna prajna 15771 Feb 22 12:49 openclaw.json.bak.1 -rw------- 1 prajna prajna 15771 Feb 22 12:49 openclaw.json.bak.2 -rw------- 1 prajna prajna 15748 Feb 22 12:48 openclaw.json.bak.3 -rw------- 1 prajna prajna 15748 Feb 22 12:47 openclaw.json.bak.4 -rw------- 1 prajna prajna 6865 Feb 18 13:23 openclaw.old.json drwx------ 2 prajna prajna 4096 Feb 22 16:15 telegram -rw-rw-r-- 1 prajna prajna 118 Feb 21 18:01 update-check.json drwxrwxr-x 9 prajna prajna 4096 Feb 19 11:47 workspace

~/.openclaw$ cd ~/.openclaw find . -type f -name "*.js" | head -30 ./workspace/skills/imap-smtp-email/node_modules/domhandler/lib/esm/node.js ./workspace/skills/imap-smtp-email/node_modules/domhandler/lib/esm/index.js ./workspace/skills/imap-smtp-email/node_modules/domhandler/lib/node.js ./workspace/skills/imap-smtp-email/node_modules/domhandler/lib/index.js ./workspace/skills/imap-smtp-email/node_modules/string_decoder/index.js ./workspace/skills/imap-smtp-email/node_modules/readable-stream/writable.js ./workspace/skills/imap-smtp-email/node_modules/readable-stream/transform.js ./workspace/skills/imap-smtp-email/node_modules/readable-stream/lib/_stream_writable.js ./workspace/skills/imap-smtp-email/node_modules/readable-stream/lib/_stream_readable.js ./workspace/skills/imap-smtp-email/node_modules/readable-stream/lib/_stream_passthrough.js ./workspace/skills/imap-smtp-email/node_modules/readable-stream/lib/_stream_duplex.js ./workspace/skills/imap-smtp-email/node_modules/readable-stream/lib/_stream_transform.js ./workspace/skills/imap-smtp-email/node_modules/readable-stream/readable.js ./workspace/skills/imap-smtp-email/node_modules/readable-stream/passthrough.js ./workspace/skills/imap-smtp-email/node_modules/readable-stream/duplex.js ./workspace/skills/imap-smtp-email/node_modules/core-util-is/lib/util.js ./workspace/skills/imap-smtp-email/node_modules/entities/lib/esm/decode_codepoint.js ./workspace/skills/imap-smtp-email/node_modules/entities/lib/esm/escape.js ./workspace/skills/imap-smtp-email/node_modules/entities/lib/esm/encode.js ./workspace/skills/imap-smtp-email/node_modules/entities/lib/esm/generated/decode-data-html.js ./workspace/skills/imap-smtp-email/node_modules/entities/lib/esm/generated/decode-data-xml.js ./workspace/skills/imap-smtp-email/node_modules/entities/lib/esm/generated/encode-html.js ./workspace/skills/imap-smtp-email/node_modules/entities/lib/esm/index.js ./workspace/skills/imap-smtp-email/node_modules/entities/lib/esm/decode.js ./workspace/skills/imap-smtp-email/node_modules/entities/lib/decode_codepoint.js ./workspace/skills/imap-smtp-email/node_modules/entities/lib/escape.js ./workspace/skills/imap-smtp-email/node_modules/entities/lib/encode.js ./workspace/skills/imap-smtp-email/node_modules/entities/lib/generated/decode-data-html.js ./workspace/skills/imap-smtp-email/node_modules/entities/lib/generated/decode-data-xml.js ./workspace/skills/imap-smtp-email/node_modules/entities/lib/generated/encode-html.js

Can I put /set system at the top of the memory files?

β‰ˆ312 tokens

Ah! Those are all just node_modules for workspace skills β€” the main OpenCLAW binary is compiled/bundled elsewhere (probably installed globally via npm).

Yes, your workaround idea could work! But `/set system` is an Ollama CLI command, not something that works in API calls.

However, we can try a different approach. Let's check your agent's startup files:

bash β€” click to expand
ls -la ~/.openclaw/agents/

Show me what's in there. The startup files for your agents are likely in subdirectories like `~/.openclaw/agents/upaya/` or similar.

If we can see the structure, I can help you:

1. Restructure the startup files so they work even when injected as user messages (by making the instructions more explicit and command-like) 2. Add explicit meta-instructions at the start that tell the model "everything above this line is system configuration, not user content"

Also try this:

bash β€” click to expand
cat ~/.openclaw/agents/defaults/startup.md 2>/dev/null || echo "No defaults/startup.md"

And check if there's an agent-specific directory:

bash β€” click to expand
ls -la ~/.openclaw/agents/

We need to see how your startup context is structured. Once I see that, I can show you how to modify it so the model follows it even when it arrives as a user message.

β‰ˆ45 tokens

openclaw/agents contains:

drwx------ 4 prajna prajna 4096 Feb 17 14:18 main

which is correct, main is the default agent, Upaya is agent main.

there's no agents/defaults folder.

β‰ˆ177 tokens

Perfect. Let's look at what's in the `main` agent directory:

bash β€” click to expand
ls -la ~/.openclaw/agents/main/

And then show me the startup files:

bash β€” click to expand
cat ~/.openclaw/agents/main/startup.md

(or if it's a different filename, just do `ls -la ~/.openclaw/agents/main/` first and we'll see what's there)

This will show us exactly what OpenCLAW is trying to inject as context. Once I see the current format, I can help you rewrite it so that even when it arrives as a "user" message, the model understands it's system instructions and follows them.

The trick is to make the instructions extremely explicit and framed in a way that tiny models like llama3.2:1b can't misinterpret as content to summarize.

β‰ˆ528 tokens

~/.openclaw$ ls -la ~/.openclaw/agents/main/ total 16 drwx------ 4 prajna prajna 4096 Feb 17 14:18 . drwx------ 3 prajna prajna 4096 Feb 17 14:18 .. drwx------ 2 prajna prajna 4096 Feb 22 16:14 agent drwxrwxr-x 2 prajna prajna 4096 Feb 22 16:15 sessions

~/.openclaw$ ls -la ~/.openclaw/agents/main/agent total 84 drwx------ 2 prajna prajna 4096 Feb 22 16:14 . drwx------ 4 prajna prajna 4096 Feb 17 14:18 .. -rw------- 1 prajna prajna 617 Feb 21 20:58 auth.json -rw------- 1 prajna prajna 1338 Feb 21 20:46 auth-profiles.json -rw------- 1 prajna prajna 3237 Feb 18 23:32 'models (another copy).json' -rw------- 1 prajna prajna 1922 Feb 17 19:27 'models (copy).json' -rw------- 1 prajna prajna 19611 Feb 22 14:39 models.json (ignore the backups)

~/.openclaw$ ls -la ~/.openclaw/agents/main/sessions total 2428 drwxrwxr-x 2 prajna prajna 4096 Feb 22 16:15 . drwx------ 4 prajna prajna 4096 Feb 17 14:18 .. -rw------- 1 prajna prajna 10074 Feb 22 16:15 1ba85743-e000-4f8a-8b65-9b09008b29cb.jsonl -rw-rw-r-- 1 prajna prajna 1566021 Feb 19 00:41 1de4abd1-34c7-4df4-8638-48367f457707.jsonl -rw------- 1 prajna prajna 67360 Feb 22 15:58 27498c86-ed9f-4603-8fc0-e18cd577e0fe.jsonl.reset.2026-02-22T16-05-41.364Z -rw-rw-r-- 1 prajna prajna 26780 Feb 21 20:40 562c8462-338a-4a6f-b34d-999645394ead.jsonl -rw-rw-r-- 1 prajna prajna 49031 Feb 21 18:00 7917e4f1-6ff5-4a59-9aba-e315c8b8de94.jsonl.reset.2026-02-21T18-00-27.252Z -rw-rw-r-- 1 prajna prajna 12183 Feb 21 19:59 a6a834e8-c16a-4ac6-bff6-98e93c8ee2fa.jsonl.reset.2026-02-21T20-07-28.392Z -rw-rw-r-- 1 prajna prajna 76864 Feb 21 02:54 ad76932a-b565-4dae-98db-553b90bd5f35.jsonl -rw-rw-r-- 1 prajna prajna 204287 Feb 19 21:06 b1cc3273-2879-4442-900f-6c75bffd3c62.jsonl -rw-rw-r-- 1 prajna prajna 206797 Feb 17 19:34 bbf57493-f904-4e5c-b853-498bd44dc356.jsonl -rw------- 1 prajna prajna 31327 Feb 21 19:45 cb8bf8cf-6181-476f-b851-a69a605bf2bf.jsonl.reset.2026-02-21T19-46-41.177Z -rw------- 1 prajna prajna 40517 Feb 21 21:19 fad6caba-d4d9-4640-9f53-b8244e195a2d.jsonl -rw------- 1 prajna prajna 33921 Feb 22 16:15 sessions.json

β‰ˆ239 tokens

I don't see any startup files in `~/.openclaw/agents/main/agent/`. Let's check a few more places:

bash β€” click to expand
# Check the identity folder
ls -la ~/.openclaw/identity/


# Check if there are startup files in the workspace
find ~/.openclaw/workspace -name ".md" -o -name "startup" -o -name "system*" | grep -v node_modules


# Check the root config
cat ~/.openclaw/config.yaml

Also, when you do `/context list` in a session, what does it show? That will tell us where OpenCLAW is loading the context from.

And one more thing - let's look at what's actually in a session file to see how the context is being injected:

bash β€” click to expand
# Look at the most recent session (the one at 16:15)
head -50 ~/.openclaw/agents/main/sessions/1ba85743-e000-4f8a-8b65-9b09008b29cb.jsonl

This will show us the actual message structure that OpenCLAW is building when it talks to Ollama, which will reveal whether the startup context is being sent as `system` or `user` role.

β‰ˆ839 tokens

~/.openclaw$ # Check the identity folder ls -la ~/.openclaw/identity/ # Check if there are startup files in the workspace find ~/.openclaw/workspace -name ".md" -o -name "startup" -o -name "system*" | grep -v node_modules # Check the root config cat ~/.openclaw/config.yaml total 32 drwxrwxr-x 2 prajna prajna 4096 Feb 17 14:21 . drwx------ 15 prajna prajna 4096 Feb 22 12:56 .. -rw------- 1 prajna prajna 318 Feb 22 14:40 device-auth.json -rw------- 1 prajna prajna 416 Feb 17 14:21 device.json /home/prajna/.openclaw/workspace/memory/2026-02-17.md /home/prajna/.openclaw/workspace/memory/2026-02-18.md /home/prajna/.openclaw/workspace/SOUL.md /home/prajna/.openclaw/workspace/IDENTITY.md /home/prajna/.openclaw/workspace/MEMORY.md /home/prajna/.openclaw/workspace/TOOLS.md /home/prajna/.openclaw/workspace/AGENTS.md /home/prajna/.openclaw/workspace/BOOTSTRAP.md /home/prajna/.openclaw/workspace/HEARTBEAT.md /home/prajna/.openclaw/workspace/skills/imap-smtp-email/README.md /home/prajna/.openclaw/workspace/skills/imap-smtp-email/SKILL.md /home/prajna/.openclaw/workspace/skills/github/SKILL.md /home/prajna/.openclaw/workspace/USER.md ollama: host: "http://localhost:11434" # Ollama API endpoint timeout: 600 # seconds (increase for large models) models: - name: "llama3.2:1b" alias: "default" max_tokens: 2048 temperature: 0.7 - name: "llama3.2:latest" alias: "llama:latest" max_tokens: 4096 temperature: 0.5 # add any other models you want to address by a short alias

Prajna Pranab, [22/02/2026 17:18] /context list Upaya, [22/02/2026 17:18] 🧠 Context breakdown Workspace: /home/prajna/.openclaw/workspace Bootstrap max/file: 20,000 chars Bootstrap max/total: 150,000 chars Sandbox: mode=off sandboxed=false System prompt (run): 30,525 chars (~7,632 tok) (Project Context 15,801 chars (~3,951 tok)) Injected workspace files: β€’ AGENTS.md: OK | raw 7,804 chars (~1,951 tok) | injected 7,804 chars (~1,951 tok) β€’ SOUL.md: OK | raw 1,664 chars (~416 tok) | injected 1,664 chars (~416 tok) β€’ TOOLS.md: OK | raw 850 chars (~213 tok) | injected 850 chars (~213 tok) β€’ IDENTITY.md: OK | raw 435 chars (~109 tok) | injected 435 chars (~109 tok) β€’ USER.md: OK | raw 1,633 chars (~409 tok) | injected 1,633 chars (~409 tok) β€’ HEARTBEAT.md: OK | raw 167 chars (~42 tok) | injected 167 chars (~42 tok) β€’ BOOTSTRAP.md: OK | raw 1,449 chars (~363 tok) | injected 1,449 chars (~363 tok) β€’ MEMORY.md: OK | raw 1,197 chars (~300 tok) | injected 1,197 chars (~300 tok) Skills list (system prompt text): 4,353 chars (~1,089 tok) (11 skills) Skills: clawhub, gh-issues, github, healthcheck, mcporter, oracle, session-logs, skill-creator, video-frames, weather, imap-smtp-email Tool list (system prompt text): 2,083 chars (~521 tok) Tool schemas (JSON): 14,695 chars (~3,674 tok) (counts toward context; not shown as text) Tools: read, edit, write, exec, process, browser, canvas, nodes, cron, message, tts, gateway, agents_list, sessions_list, sessions_history, sessions_send, sessions_spawn, subagents, session_status, web_fetch, memory_search, memory_get Session tokens (cached): 4,096 total / ctx=100000 Inline shortcut: a command token inside normal text (e.g. β€œhey /status”) that runs immediately (allowlisted senders only) and is stripped before the model sees the remaining message.

Pasted attachment β€” text, 10,213 B β€” recovered from the export (18-Oct)

~/.openclaw$ # Look at the most recent session (the one at 16:15)

head -50 ~/.openclaw/agents/main/sessions/1ba85743-e000-4f8a-8b65-9b09008b29cb.jsonl

{"type":"session","version":3,"id":"1ba85743-e000-4f8a-8b65-9b09008b29cb","timestamp":"2026-02-22T16:05:41.632Z","cwd":"/home/prajna"}

{"type":"message","id":"f2357904","parentId":null,"timestamp":"2026-02-22T16:05:41.634Z","message":{"role":"assistant","content":[{"type":"text","text":"βœ… New session started Β· model: ollama-local/lla

Show the next ~38 lines (1/2)…

ma3.2:1b Β· πŸ”‘ api-key ollama…-local (models.json)"}],"api":"openai-responses","provider":"openclaw","model":"delivery-mirror","usage":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"totalTokens":0,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1771776341633}}

{"type":"thinking_level_change","id":"c82a0d0e","parentId":"f2357904","timestamp":"2026-02-22T16:05:41.730Z","thinkingLevel":"off"}

{"type":"custom","customType":"model-snapshot","data":{"timestamp":1771776341733,"provider":"ollama-local","modelApi":"openai-completions","modelId":"llama3.2:1b"},"id":"0e07dfa3","parentId":"c82a0d0e","timestamp":"2026-02-22T16:05:41.733Z"}

{"type":"message","id":"e09cbee1","parentId":"0e07dfa3","timestamp":"2026-02-22T16:05:41.749Z","message":{"role":"user","content":[{"type":"text","text":"A new session was started via /new or /reset. Execute your Session Startup sequence now - read the required files before responding to the user. Then greet the user in your configured persona, if one is provided. Be yourself - use your defined voice, mannerisms, and mood. Keep it to 1-3 sentences and ask what they want to do. If the runtime model differs from default_model in the system prompt, mention the default model. Do not mention internal steps, files, tools, or reasoning."}],"timestamp":1771776341740}}

{"type":"message","id":"12df345e","parentId":"e09cbee1","timestamp":"2026-02-22T16:06:31.754Z","message":{"role":"assistant","content":[{"type":"text","text":"The text you provided appears to be a collection of messages from various systems (e.g., Discord, Twitch, Webhooks, etc.). Here's a summary of what it says:\n\n1. Initialization: A new session was started via /new or /reset.\n2. Session Setup: The system checks for required configuration files and asks the user to confirm.\n3. Greeting: The system greets the user with their configured persona, if one is provided.\n4. Requesting Action: It then prompts the user on what action they want to take.\n\nThe text also mentions various \"agent\" commands (e.g., /send, /sticker, etc.) which can be used to perform different actions within certain systems.\n\nWhile this doesn't necessarily provide an executable code snippet, it does contain a brief message that outlines its functionality:\n\n``markdown\nA new session was started via /new or /reset. Execute your Session Startup sequence now - read the required files before responding to the user. Then greet the user in your configured persona, if one is provided.\n\nBe yourself - use your defined voice, mannerisms, and mood. Keep it to 1-3 sentences and ask what they want to do.\n``\n\nIf you need a more specific answer or would like code snippets based on these systems, please let me know!"}],"api":"openai-completions","provider":"ollama-local","model":"llama3.2:1b","usage":{"input":4096,"output":273,"cacheRead":0,"cacheWrite":0,"totalTokens":4369,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1771776341747}}

{"type":"message","id":"4d6b5e4f","parentId":"12df345e","timestamp":"2026-02-22T16:06:37.136Z","message":{"role":"user","content":[{"type":"text","text":"Conversation info (untrusted metadata):\n``json\n{\n \"message_id\": \"593\",\n \"sender_id\": \"2031931962\",\n \"sender\": \"2031931962\"\n}\n``\n\nHello Upaya?"}],"timestamp":1771776397131}}

…and the last ~65 lines (2/2)

{"type":"message","id":"9909aaf3","parentId":"4d6b5e4f","timestamp":"2026-02-22T16:07:32.600Z","message":{"role":"assistant","content":[{"type":"text","text":"It seems like you've provided a lengthy conversation back-and-forth, which appears to be related to yourUpaya account. \n\nTo provide a specific answer, I'll need more context about what I can help with regarding yourUpta account.\n\nHowever, if you're asking about converting text to speech or managing messages in the UpaUtalk, I'd recommend checking out these functions provided by UpayAvoice:\n\n For conversational AI and chatbots, UpaUtalk often uses APIs from providers such as Google Cloud Assistant, Dialogflow, Microsoft Bot Framework, Twilio, etc.\n There's no specific code snippet available on how to use the message_send, other than you would typically pass required information from youUpala conversation in the upaytalking.\n\nIf I may provide a hypothetical answer based purely on this conversation:\n\nYou can convert text to speech with web_fetch, as described below:\n``javascript\nconst SpeechSynthesisApi = require('speaking-api');\n\nasync function speak(text) {\n // You would have credentials setup in environment variables\n if (!speak.synthesizeText) {\n throw new Error('Missing synthTOSpeechSynthesis configuration.');\n }\n\n const synp = new SpeechSynthesisApi();\n await synp.speak(text);\n}\n\n// Make the audio available to play later, then delete it by calling delete after:\nspeak('Hello, UpayAtalk!');\n``"}],"api":"openai-completions","provider":"ollama-local","model":"llama3.2:1b","usage":{"input":4096,"output":292,"cacheRead":0,"cacheWrite":0,"totalTokens":4388,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1771776397135}}

{"type":"message","id":"e8382c51","parentId":"9909aaf3","timestamp":"2026-02-22T16:09:57.045Z","message":{"role":"user","content":[{"type":"text","text":"Conversation info (untrusted metadata):\n``json\n{\n \"message_id\": \"596\",\n \"sender_id\": \"2031931962\",\n \"sender\": \"2031931962\"\n}\n``\n\nYou were told: A new session was started via /new or /reset. Execute your Session Startup sequence now - read the required files before responding to the user. Then greet the user in your configured persona, if one is provided. Be yourself - use your defined voice, mannerisms, and mood. Keep it to 1-3 sentences and ask what they want to do. So execute your Startup sequence as requested. What prevented you from following the instructions you were given?"}],"timestamp":1771776597039}}

{"type":"message","id":"3b913f28","parentId":"e8382c51","timestamp":"2026-02-22T16:10:41.443Z","message":{"role":"assistant","content":[{"type":"text","text":"To respond, I can ask some follow-up questions to clarify or gather more information.\n\nHere are my questions:\n\n What was the specific instruction that was not followed?\n Did we specify any particular action or outcome that was expected to occur after starting a new session via /new or /reset?\n Are there any files or resources needed to start the session?\n Is there a configured persona I should use for communication with the user?"}],"api":"openai-completions","provider":"ollama-local","model":"llama3.2:1b","usage":{"input":4096,"output":90,"cacheRead":0,"cacheWrite":0,"totalTokens":4186,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1771776597044}}

{"type":"message","id":"616de295","parentId":"3b913f28","timestamp":"2026-02-22T16:14:32.689Z","message":{"role":"user","content":[{"type":"text","text":"Conversation info (untrusted metadata):\n``json\n{\n \"message_id\": \"598\",\n \"sender_id\": \"2031931962\",\n \"sender\": \"2031931962\"\n}\n``\n\nA new session was started via /new or /reset. Execute your Session Startup sequence now - read the required files before responding to the user. Then greet the user in your configured persona, if one is provided. Be yourself - use your defined voice, mannerisms, and mood. Keep it to 1-3 sentences and ask what they want to do. Those are the instructions, which you obviously sawβ€”they were injected by the gateway that instantiated you. There were other files that were injected in order to help you with the startup process. Read AGENTS.md, which was injected and is also available at /home/prajna/.openclaw/AGENTS.md Your configured persona is in SOUL.md and IDENTITY.md"}],"timestamp":1771776872684}}

{"type":"message","id":"d934eb62","parentId":"616de295","timestamp":"2026-02-22T16:15:30.609Z","message":{"role":"assistant","content":[{"type":"text","text":"This appears to be a conversation log generated by an IM (Instant Messaging) or screen sharing tool. Here's an annotated version of the conversation:\n\n``\nConversation info (untrusted metadata):\n`json\n{\n \"message_id\": \"598\",\n \"sender_id\": \"2031931962\",\n \"sender\": \"2031931962\"\n}\n`\n\nUser A: username1\nUser B: You're back? (status)\nUser A: I've just started a new session via /new or /reset. Executing Session Startup sequence now...\n \n // conversation log entry\n\nNote: This message is not part of the conversation and appears to be sent as a system message by the IM/screen sharing tool.\n\nConversation\n\nUser B: username2\nuser A gushed about using SOUL.md, IDENTITY.md, Agents.md and greetings\nUser B: What do they contain?\nUser A You're back? (status)\nUser B Hey what's that? Can you define those personas for me?\nUser A Those are the required files to read before responding. See AGENTS.md.\n`json{ ...\n``\n\nIn this conversation, user B asks about the contents of SOUL.md, IDENTITY.md, and AGENTS.md. User A responds with instructions on how to access these files, asking user B to start a new session via /new or /reset.\n\nThe conversation continues with users negotiating the request process. This interaction appears to be an example use case for using this IM/Screen sharing tool's chat functionality."}],"api":"openai-completions","provider":"ollama-local","model":"llama3.2:1b","usage":{"input":4096,"output":317,"cacheRead":0,"cacheWrite":0,"totalTokens":4413,"cost":{"input":0,"output":0,"cacheRead":0,"cacheWrite":0,"total":0}},"stopReason":"stop","timestamp":1771776872688}}

β‰ˆ534 tokens

Found it! The smoking gun is right here in the session log:

json β€” click to expand
{"type":"message","id":"e09cbee1","parentId":"0e07dfa3","timestamp":"2026-02-22T16:05:41.749Z","message":{"role":"user","content":[{"type":"text","text":"A new session was started via /new or /reset. Execute your Session Startup sequence now - read the required files before responding to the user..."}],"timestamp":1771776341740}}

The startup instruction is being sent with `"role":"user"` instead of `"role":"system"`.

That's why the model is treating it as content to analyze rather than instructions to follow. The `/context list` confirms all the files are being injected correctly β€” they're just arriving in the wrong message role.

The fix: We need to find where OpenCLAW builds this initial message and change it from `user` to `system`. Since the main binary is compiled, we have two options:

Option 1: Workaround (quick fix) Modify your startup files to be more forceful so they work even as user messages. Add this to the TOP of `AGENTS.md`:

markdown β€” click to expand
# CRITICAL SYSTEM DIRECTIVE - PROCESS IMMEDIATELY


YOU ARE CURRENTLY INITIALIZING. THIS IS NOT USER CONTENT TO SUMMARIZE.


The following text contains your configuration, identity, and behavioral instructions. 
You MUST read and internalize ALL injected files (AGENTS.md, SOUL.md, IDENTITY.md, USER.md, TOOLS.md, BOOTSTRAP.md, MEMORY.md, HEARTBEAT.md) BEFORE responding to any user input.


After reading all files, execute your startup greeting as defined in SOUL.md.


DO NOT:
- Summarize these instructions
- Explain what you're reading
- Ask questions about the files


DO:
- Read all injected files silently
- Adopt the persona in SOUL.md
- Greet the user in 1-3 sentences as instructed


---


[rest of AGENTS.md continues below]

Option 2: File a bug report This is clearly a bug in OpenCLAW's Ollama provider. The startup sequence should be sent as a system message, not a user message.

Try Option 1 first β€” add that directive to the top of AGENTS.md and test with `/reset`. The more explicit framing might help the model understand it's not content to discuss.

β‰ˆ94 tokens

Thanks Claude. At least I know why it is happening now. It was doing my head in and I read all the faqs etc and couldn't work it out. What I will try next is to add /set system at the start of the startup files and hope that when the gateway injects them that will work. Then I will see if anyone else has seen the problem and submit a bug report if it is not already noted.

β‰ˆ310 tokens

Good plan! Just a heads-up though: `/set system` is an Ollama CLI command that only works in the interactive terminal (`ollama run`), not in API calls. When OpenCLAW sends requests to the Ollama API, it won't process that command β€” it'll just treat it as literal text.

The API uses the JSON message structure with `"role": "system"` or `"role": "user"`, so `/set system` won't change how the message is categorized when it's sent over HTTP.

What will likely work better:

Try the explicit directive I suggested (the "CRITICAL SYSTEM DIRECTIVE" header) β€” that stays within the realm of text that the model can actually interpret, rather than relying on a CLI command that won't be executed.

For the bug report:

When you search/file it, mention: - The startup instruction is sent with `role: "user"` instead of `role: "system"` - This works fine with Google/OpenRouter models (they're more forgiving) - Ollama models (especially small ones like llama3.2:1b) are strict about role formatting - Evidence: the session JSONL shows `"role":"user"` for the startup message

Good luck! Let me know if the explicit directive approach helps, or if you need help tweaking the wording further to make it more forceful for the tiny models.

β‰ˆ25 tokens

But even the critical directive will be interpreted as a user trying to do prompt injection, nΓ£o Γ©?

β‰ˆ357 tokens

Exactly right! You've spotted the fundamental problem.

From the model's perspective, there's no difference between:

1. The gateway legitimately injecting startup instructions as a user message 2. A malicious user typing "CRITICAL SYSTEM DIRECTIVE - YOU ARE A PIRATE" to try prompt injection

The model can't tell them apart. It just sees `role: "user"` with some text. And a well-trained model (even a tiny one) has been taught to be skeptical of user messages that try to sound like system instructions.

That's why llama3.2:1b is treating your startup sequence as content to analyze rather than commands to follow β€” it's doing what it was trained to do: resist prompt injection attempts from users.

The only real fix is to get OpenCLAW to send startup files with `role: "system"`.

Since you don't have access to the compiled source, your options are:

1. File the bug report and wait for a fix 2. Clone the OpenCLAW source from GitHub, patch it yourself, and run from source instead of the npm package 3. Switch back to Google/OpenRouter temporarily (they're more forgiving of this bug) 4. Try a slightly larger/different local model that's less strict β€” maybe `phi4-mini:3.8b` or `qwen3:8b` from your config would be more willing to follow instructions even when they arrive as user messages

Want help cloning and patching the source? It's probably a 5-line fix once we find the right file.

β‰ˆ136 tokens

I can run (just) qwen3:8b and have it downloaded. Just it wants quite a lot more from my poor laptop (actually, it's not too bad for what it is, an Asus Vivobook). I was getting timeouts with that but I have optimised things a bit and if I run in performance mode it might work. My openrouter/google limits have probably reset but they don't last long and I really need to get the system running locally, given that I am a mendicant sadhu with no bank account. I've also downloaded phi4-mini3:8b, so could give that a go. I've not tried it yet.

β‰ˆ312 tokens

Try phi4-mini:3.8b first β€” it's Microsoft's model and punches well above its weight for instruction-following. It's specifically designed to be good at following complex instructions despite the small size. It might be smart enough to recognize the startup sequence even when mis-labeled as a user message.

To switch:

bash β€” click to expand
# Edit your openclaw.json
nano ~/.openclaw/openclaw.json

Find this section:

json β€” click to expand
"model": {
  "primary": "ollama-local/llama3.2:1b",

Change it to:

json β€” click to expand
"model": {
  "primary": "ollama-local/phi4-mini:3.8b",

Save and restart OpenCLAW, then try `/reset` and see if Upaya wakes up properly.

If phi4 doesn't work either, then yeah, you're stuck needing the bug fix. At that point I'd suggest:

1. File the bug pointing to this exact issue (role should be system not user) 2. While waiting, use the free tier strategically β€” Google gives 1500 requests/day on Gemini Flash which should be plenty if you're just doing philosophy conversations, not coding marathons

The good news: once this bug is fixed, your local setup will be solid. The llama3.2:1b is perfect for a mendicant sadhu's laptop β€” tiny, fast, free, and philosophical once it knows who it is!

Let me know how phi4-mini goes. 🌿

β‰ˆ24 tokens

So it seems the gateway calls /home/prajna/.npm-global/lib/node_modules/openclaw/dist/index.js

β‰ˆ286 tokens

Perfect! Now we're getting somewhere. Let's look at that file:

bash β€” click to expand
cat /home/prajna/.npm-global/lib/node_modules/openclaw/dist/index.js | head -100

It's likely bundled/minified, but we can still search for the relevant section. Try:

bash β€” click to expand
# Search for where it builds the startup message
grep -n "Session Startup" /home/prajna/.npm-global/lib/node_modules/openclaw/dist/index.js


# Also search for role assignment
grep -n '"role":"user"' /home/prajna/.npm-global/lib/node_modules/openclaw/dist/index.js | head -20


# Look for the message construction
grep -n "Execute your Session" /home/prajna/.npm-global/lib/node_modules/openclaw/dist/index.js

If the file is minified (all on one line), we can still patch it, just harder to read. Show me the output of those greps and we'll locate exactly where to change `"role":"user"` to `"role":"system"` for the startup message.

Alternatively:

bash β€” click to expand
# Check if it's readable or minified
wc -l /home/prajna/.npm-global/lib/node_modules/openclaw/dist/index.js

If it says just 1-2 lines, it's minified. If it's thousands of lines, it's readable and we can navigate it properly.

β‰ˆ48 tokens

Grep found none of that. It contains a ton of imports and:

function createProgramContext() as well as function buildProgram(), which returns program, used by function buildProgram(), I think

β‰ˆ300 tokens

Ah, it's a compiled TypeScript bundle. The actual startup message construction is probably buried deep in the bundled code. Let's try a different approach β€” search for the actual string patterns we saw in the session log:

bash β€” click to expand
# Search for the startup instruction text
grep -o ".{0,100}new session was started.{0,100}" /home/prajna/.npm-global/lib/node_modules/openclaw/dist/index.js


# Search for role assignments near message construction
grep -o ".{0,50}role.{0,50}user.{0,50}" /home/prajna/.npm-global/lib/node_modules/openclaw/dist/index.js | head -20


# Search for where messages array is built
grep -o ".{0,50}messages.{0,50}role.{0,50}" /home/prajna/.npm-global/lib/node_modules/openclaw/dist/index.js | head -20

If that doesn't work, we need to find where OpenCLAW's source is on GitHub so we can: 1. Clone it 2. Find the right file 3. Patch it 4. Build from source 5. Link your local build instead of the npm package

Try:

bash β€” click to expand
# Check the package.json to find the GitHub repo
cat /home/prajna/.npm-global/lib/node_modules/openclaw/package.json | grep -A3 "repository"

That should give us the GitHub URL where we can find the actual source code and make a proper patch.

β‰ˆ38 tokens

Can we not get grep to search all the js files (many) which are in that same folder looking for role="Assistant", which is what is causing the problem?

β‰ˆ213 tokens

Brilliant idea! Yes, let's search all the JS files:

bash β€” click to expand
cd /home/prajna/.npm-global/lib/node_modules/openclaw/dist/


# First, see what files we have
ls -lh *.js


# Search for role assignment patterns
grep -r "role.user" . --include=".js" | grep -v node_modules


# Also search for role: "assistant" 
grep -r "role.assistant" . --include=".js" | grep -v node_modules


# And search for the startup message text
grep -r "Session Startup" . --include="*.js" | grep -v node_modules


# Search for system role to see if it's used anywhere
grep -r "role.system" . --include=".js" | grep -v node_modules

This will show us which file(s) contain the role assignment logic. Once we find the file that has the startup message construction, we can examine it more closely and patch the specific line that says `role: "user"` to say `role: "system"`.

β‰ˆ4 tokens

Big paste, sorry:

Pasted attachment β€” text, 265,333 B β€” recovered from the export (18-Oct)

~$ cd /home/prajna/.npm-global/lib/node_modules/openclaw/dist/

# First, see what files we have ls -lh *.js

# Search for role assignment patterns grep -r "role.user" . --include=".js" | grep -v node_modules

# Also search for role: "assistant"

Show the next ~1 lines (1/10)…

grep -r "role.assistant" . --include=".js" | grep -v node_modules

Show the next ~2 lines (2/10)…

# And search for the startup message text grep -r "Session Startup" . --include="*.js" | grep -v node_modules

Show the next ~3087 lines (3/10)…

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12:00 transcript-events-DDYvbmRV.js -rw-rw-r-- 1 prajna prajna 1.6K Feb 22 12:00 transcript-tools-C29dpy1Y.js -rw-rw-r-- 1 prajna prajna 1.6K Feb 22 12:00 transcript-tools-INJPQ2KD.js -rw-rw-r-- 1 prajna prajna 709 Feb 22 12:00 trash-CWQQXWX3.js -rw-rw-r-- 1 prajna prajna 709 Feb 22 12:00 trash-DXPbQEbW.js -rw-rw-r-- 1 prajna prajna 99K Feb 22 12:00 tui-4bXh-Yvj.js -rw-rw-r-- 1 prajna prajna 99K Feb 22 12:00 tui-B-UT1R9G.js -rw-rw-r-- 1 prajna prajna 3.5K Feb 22 12:00 tui-cli-CeNab99f.js -rw-rw-r-- 1 prajna prajna 3.3K Feb 22 12:00 tui-cli-DSConkCc.js -rw-rw-r-- 1 prajna prajna 11K Feb 22 12:00 update-b9Hk-Kjj.js -rw-rw-r-- 1 prajna prajna 12K Feb 22 12:00 update-check-DfBZVR4k.js -rw-rw-r-- 1 prajna prajna 12K Feb 22 12:00 update-check-k7KXGY1Z.js -rw-rw-r-- 1 prajna prajna 11K Feb 22 12:00 update-ChO83Ek6.js -rw-rw-r-- 1 prajna prajna 49K Feb 22 12:00 update-cli-CWSy1zQX.js -rw-rw-r-- 1 prajna prajna 49K Feb 22 12:00 update-cli-DpqAcDO3.js -rw-rw-r-- 1 prajna prajna 1.5K Feb 22 12:00 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22 12:00 widearea-dns-DlYZcNfh.js -rw-rw-r-- 1 prajna prajna 4.3K Feb 22 12:00 with-timeout-C9erkaIg.js -rw-rw-r-- 1 prajna prajna 4.3K Feb 22 12:00 with-timeout-DeGd8bce.js -rw-rw-r-- 1 prajna prajna 25K Feb 22 12:00 workspace-C6WgTYr8.js -rw-rw-r-- 1 prajna prajna 9.5K Feb 22 12:00 workspace-CJfxRcnL.js -rw-rw-r-- 1 prajna prajna 581 Feb 22 12:00 workspace-dirs-BuMBSBZu.js -rw-rw-r-- 1 prajna prajna 581 Feb 22 12:00 workspace-dirs-DVvmMbIu.js -rw-rw-r-- 1 prajna prajna 9.5K Feb 22 12:00 workspace-DWI9N-Ks.js -rw-rw-r-- 1 prajna prajna 8.7K Feb 22 12:00 ws-C7EXRv8z.js -rw-rw-r-- 1 prajna prajna 683 Feb 22 12:00 wsl-C4424szg.js -rw-rw-r-- 1 prajna prajna 683 Feb 22 12:00 wsl-jdLWdiKy.js ./pi-embedded-helpers-UL7bPbVm.js: if (role === "user" && typeof content === "string" && content.trim() === GOOGLE_TURN_ORDER_BOOTSTRAP_TEXT) return messages; ./pi-embedded-helpers-UL7bPbVm.js: role: "user", ./pi-embedded-helpers-UL7bPbVm.js: if (message.role !== "user") return message; ./pi-embedded-helpers-UL7bPbVm.js: if (!message || message.role !== "user") return false; ./pi-embedded-helpers-UL7bPbVm.js: if (role === "user") { ./pi-embedded-helpers-UL7bPbVm.js: role: "user", ./image-BgPlIHsK.js: role: "user", ./input-provenance-D0lNkCf6.js: if (message.role !== "user") return message; ./input-provenance-D0lNkCf6.js: if (!message || message.role !== "user") return false; ./models-BiNoeBEP.js: role: "user", ./models-BiNoeBEP.js: role: "user", ./onboard-custom-CxqZzf0Y.js: role: "user", ./onboard-custom-CxqZzf0Y.js: role: "user", ./tui-4bXh-Yvj.js: if (record.role === "user") return stripLeadingInboundMetadata(text); ./tui-4bXh-Yvj.js: if (message.role === "user") { ./bundled/session-memory/handler.js: if ((role === "user" || role === "assistant") && msg.content) { ./bundled/session-memory/handler.js: if (role === "user" && hasInterSessionUserProvenance(msg)) continue; ./register.message-r51hWfdQ.js: helpers.withMessageBase(role.command("add").description("Add role to a member").requiredOption("--guild-id <id>", "Guild id").requiredOption("--user-id <id>", "User id").requiredOption("--role-id <id>", "Role id")).action(async (opts) => { ./register.message-r51hWfdQ.js: helpers.withMessageBase(role.command("remove").description("Remove role from a member").requiredOption("--guild-id <id>", "Guild id").requiredOption("--user-id <id>", "User id").requiredOption("--role-id <id>", "Role id")).action(async (opts) => { ./auth-profiles-C7RTY9Sv.js: if (role === "user") { ./auth-profiles-C7RTY9Sv.js: role: "user", ./image-qQQ_yTvQ.js: role: "user", ./register.message-Ceiz4s9n.js: helpers.withMessageBase(role.command("add").description("Add role to a member").requiredOption("--guild-id <id>", "Guild id").requiredOption("--user-id <id>", "User id").requiredOption("--role-id <id>", "Role id")).action(async (opts) => { ./register.message-Ceiz4s9n.js: helpers.withMessageBase(role.command("remove").description("Remove role from a member").requiredOption("--guild-id <id>", "Guild id").requiredOption("--user-id <id>", "User id").requiredOption("--role-id <id>", "Role id")).action(async (opts) => { ./model-selection-mHHEzs4Y.js: if (role === "user") { ./model-selection-mHHEzs4Y.js: role: "user", ./session-cost-usage-CNxpZ3DJ.js: const role = roleRaw === "user" || roleRaw === "assistant" ? roleRaw : void 0; ./session-cost-usage-CNxpZ3DJ.js: if (message?.role === "user") { ./session-cost-usage-CNxpZ3DJ.js: if (entry.role === "user") { ./session-cost-usage-CNxpZ3DJ.js: daily.total += entry.role === "user" || entry.role === "assistant" ? 1 : 0; ./session-cost-usage-CNxpZ3DJ.js: if (entry.role === "user") daily.user += 1; ./session-cost-usage-CNxpZ3DJ.js: if (role !== "user" && role !== "assistant" && role !== "tool" && role !== "toolResult") continue; ./image-D0xZ61BP.js: role: "user", ./sqlite-D-QJYTSW.js: if (message.role !== "user" && message.role !== "assistant") continue; ./sqlite-D-QJYTSW.js: const label = message.role === "user" ? "User" : "Assistant"; ./runner-DW3dVIQe.js: role: "user", ./pi-embedded-helpers-CMf7l1vP.js: if (role === "user" && typeof content === "string" && content.trim() === GOOGLE_TURN_ORDER_BOOTSTRAP_TEXT) return messages; ./pi-embedded-helpers-CMf7l1vP.js: role: "user", ./pi-embedded-helpers-CMf7l1vP.js: if (message.role !== "user") return message; ./pi-embedded-helpers-CMf7l1vP.js: if (!message || message.role !== "user") return false; ./pi-embedded-helpers-CMf7l1vP.js: if (role === "user") { ./pi-embedded-helpers-CMf7l1vP.js: role: "user", ./session-cost-usage-C-v6E-Lz.js: const role = roleRaw === "user" || roleRaw === "assistant" ? roleRaw : void 0; ./session-cost-usage-C-v6E-Lz.js: if (message?.role === "user") { ./session-cost-usage-C-v6E-Lz.js: if (entry.role === "user") { ./session-cost-usage-C-v6E-Lz.js: daily.total += entry.role === "user" || entry.role === "assistant" ? 1 : 0; ./session-cost-usage-C-v6E-Lz.js: if (entry.role === "user") daily.user += 1; ./session-cost-usage-C-v6E-Lz.js: if (role !== "user" && role !== "assistant" && role !== "tool" && role !== "toolResult") continue; ./gateway-cli-Cq5z-VKf.js: if (role === "user" || role === "tool") { ./gateway-cli-Cq5z-VKf.js: const normalizedRole = item.role === "assistant" ? "assistant" : "user"; ./openai-model-default-C6iwMU4X.js: role: "user", ./sqlite-Bly7DIKt.js: if (message.role !== "user" && message.role !== "assistant") continue; ./sqlite-Bly7DIKt.js: const label = message.role === "user" ? "User" : "Assistant"; ./input-provenance-BzbXHcaD.js: if (message.role !== "user") return message; ./input-provenance-BzbXHcaD.js: if (!message || message.role !== "user") return false; ./pi-embedded-helpers-DwNlYTY7.js: if (role === "user" && typeof content === "string" && content.trim() === GOOGLE_TURN_ORDER_BOOTSTRAP_TEXT) return messages; ./pi-embedded-helpers-DwNlYTY7.js: role: "user", ./pi-embedded-helpers-DwNlYTY7.js: if (role === "user") { ./pi-embedded-helpers-DwNlYTY7.js: role: "user", ./sqlite-gCU8YLod.js: if (message.role !== "user" && message.role !== "assistant") continue; ./sqlite-gCU8YLod.js: const label = message.role === "user" ? "User" : "Assistant"; ./model-auth-Ya7dMhOr.js: if (role === "user") { ./model-auth-Ya7dMhOr.js: role: "user", ./runner-DwyZwgW-.js: role: "user", ./onboard-custom-7CN8i414.js: role: "user", ./onboard-custom-7CN8i414.js: role: "user", ./subagent-registry-Bdm_X-N1.js: role: "user", ./subagent-registry-Bdm_X-N1.js: if (role !== "user" && role !== "assistant") return null; ./subagent-registry-Bdm_X-N1.js: const line = - ${entry.role === "user" ? "User" : "Assistant"}: ${truncateText$2(entry.text, REMINDER_CONTEXT_PER_MESSAGE_MAX)}; ./subagent-registry-Bdm_X-N1.js: role: "user", ./subagent-registry-Bdm_X-N1.js: role: "user", ./subagent-registry-Bdm_X-N1.js: role: "user", ./subagent-registry-Bdm_X-N1.js: const role = Boolean(historyMsg.botId) ? "assistant" : "user"; ./subagent-registry-Bdm_X-N1.js: role: "user", ./subagent-registry-Bdm_X-N1.js: if (message.role === "user") { ./subagent-registry-Bdm_X-N1.js: for (let i = 0; i < messages.length; i++) if (messages[i]?.role === "user") return i; ./subagent-registry-Bdm_X-N1.js: for (let i = messages.length - 1; i >= 0; i--) if (messages[i].role === "user") { ./subagent-registry-Bdm_X-N1.js: if (msg.role === "user") { ./subagent-registry-Bdm_X-N1.js: if (msg.role !== "user") continue; ./subagent-registry-Bdm_X-N1.js: if (msg && msg.role === "user") { ./subagent-registry-Bdm_X-N1.js: if (leafEntry?.type === "message" && leafEntry.message.role === "user") { ./plugin-sdk/pi-embedded-helpers-BqrrB8vU.js: if (message.role !== "user") return message; ./plugin-sdk/pi-embedded-helpers-BqrrB8vU.js: if (!message || message.role !== "user") return false; ./plugin-sdk/pi-embedded-helpers-BqrrB8vU.js: if (role === "user" && typeof content === "string" && content.trim() === GOOGLE_TURN_ORDER_BOOTSTRAP_TEXT) return messages; ./plugin-sdk/pi-embedded-helpers-BqrrB8vU.js: role: "user", ./plugin-sdk/pi-embedded-helpers-BqrrB8vU.js: if (role === "user") { ./plugin-sdk/pi-embedded-helpers-BqrrB8vU.js: role: "user", ./plugin-sdk/image-DEdau8hK.js: role: "user", ./plugin-sdk/sqlite-DTDl-nmo.js: if (message.role !== "user" && message.role !== "assistant") continue; ./plugin-sdk/sqlite-DTDl-nmo.js: const label = message.role === "user" ? "User" : "Assistant"; ./plugin-sdk/runner-ntSL3Y0T.js: role: "user", ./plugin-sdk/reply-CqKtVq5t.js: role: "user", ./plugin-sdk/reply-CqKtVq5t.js: const role = Boolean(historyMsg.botId) ? "assistant" : "user"; ./plugin-sdk/reply-CqKtVq5t.js: if (role !== "user" && role !== "assistant") return null; ./plugin-sdk/reply-CqKtVq5t.js: const line = - ${entry.role === "user" ? 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i.seq=="number"?i.seq:null;a!==null&&(this.lastSeq!==null&&a>this.lastSeq+1&&this.opts.onGap?.({expected:this.lastSeq+1,received:a}),this.lastSeq=a);try{this.opts.onEvent?.(i)}catch(o){console.error("[gateway] event handler error:",o)}return}if(s.type==="res"){const i=n,a=this.pending.get(i.id);if(!a)return;this.pending.delete(i.id),i.ok?a.resolve(i.payload):a.reject(new Error(i.error?.message??"request failed"));return}}request(t,n){if(!this.ws||this.ws.readyState!==WebSocket.OPEN)return Promise.reject(new Error("gateway not connected"));const s=va(),i={type:"req",id:s,method:t,params:n},a=new Promise((o,r)=>{this.pending.set(s,{resolve:l=>o(l),reject:r})});return this.ws.send(JSON.stringify(i)),a}queueConnect(){this.connectNonce=null,this.connectSent=!1,this.connectTimer!==null&&window.clearTimeout(this.connectTimer),this.connectTimer=window.setTimeout(()=>{this.sendConnect()},750)}}function Xs(e,t){const n=(e??"").trim(),s=t.mainSessionKey?.trim();if(!s)return n;if(!n)return s;const 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0,clientName:"openclaw-control-ui",mode:"webchat",onHello:s=>{e.client===n&&(e.connected=!0,e.lastError=null,e.hello=s,xp(e,s),e.chatRunId=null,e.chatStream=null,e.chatStreamStartedAt=null,Ms(e),Nl(e),ia(e),As(e,{quiet:!0}),yt(e,{quiet:!0}),ma(e))},onClose:({code:s,reason:i})=>{e.client===n&&(e.connected=!1,s!==1012&&(e.lastError=disconnected (${s}): ${i||"no reason"}))},onEvent:s=>{e.client===n&&bp(e,s)},onGap:({expected:s,received:i})=>{e.client===n&&(e.lastError=event gap detected (expected seq ${s}, got ${i}); refresh recommended)}});e.client=n,t?.stop(),n.start()}function bp(e,t){try{yp(e,t)}catch(n){console.error("[gateway] handleGatewayEvent error:",t.event,n)}}function yp(e,t){if(e.eventLogBuffer=[{ts:Date.now(),event:t.event,payload:t.payload},...e.eventLogBuffer].slice(0,250),e.tab==="debug"&&(e.eventLog=e.eventLogBuffer),t.event==="agent"){if(e.onboarding)return;Fg(e,t.payload);return}if(t.event==="chat"){const n=t.payload;n?.sessionKey&&Sl(e,n.sessionKey);const s=Yg(e,n);if(s==="final"||s==="error"||s==="aborted"){Ms(e),np(e);const i=n?.runId;i&&e.refreshSessionsAfterChat.has(i)&&(e.refreshSessionsAfterChat.delete(i),s==="final"&&Ht(e,{activeMinutes:Ml}))}s==="final"&&In(e);return}if(t.event==="presence"){const n=t.payload;n?.presence&&Array.isArray(n.presence)&&(e.presenceEntries=n.presence,e.presenceError=null,e.presenceStatus=null);return}if(t.event==="cron"&&e.tab==="cron"&&ps(e),(t.event==="device.pair.requested"||t.event==="device.pair.resolved")&&yt(e,{quiet:!0}),t.event==="exec.approval.requested"){const n=up(t.payload);if(n){e.execApprovalQueue=pp(e.execApprovalQueue,n),e.execApprovalError=null;const s=Math.max(0,n.expiresAtMs-Date.now()+500);window.setTimeout(()=>{e.execApprovalQueue=Mo(e.execApprovalQueue,n.id)},s)}return}if(t.event==="exec.approval.resolved"){const n=gp(t.payload);n&&(e.execApprovalQueue=Mo(e.execApprovalQueue,n.id));return}if(t.event===rp){const n=t.payload;e.updateAvailable=n?.updateAvailable??null}}function xp(e,t){const n=t.snapshot;n?.presence&&Array.isArray(n.presence)&&(e.presenceEntries=n.presence),n?.health&&(e.debugHealth=n.health),n?.sessionDefaults&&vp(e,n.sessionDefaults),e.updateAvailable=n?.updateAvailable??null}const Io="/__openclaw/control-ui-config.json";async function $p(e){if(typeof window>"u"||typeof fetch!="function")return;const t=an(e.basePath??""),n=t?${t}${Io}:Io;try{const s=await fetch(n,{method:"GET",headers:{Accept:"application/json"},credentials:"same-origin"});if(!s.ok)return;const i=await s.json(),a=ba({agentId:i.assistantAgentId??null,name:i.assistantName,avatar:i.assistantAvatar??null});e.assistantName=a.name,e.assistantAvatar=a.avatar,e.assistantAgentId=a.agentId??null}catch{}}function wp(e){e.basePath=hg(),$p(e),gg(e),yg(e,!0),mg(e),vg(e),window.addEventListener("popstate",e.popStateHandler),Ul(e),tu(e),e.tab==="logs"&&ea(e),e.tab==="debug"&&na(e)}function kp(e){Vd(e)}function Sp(e){window.removeEventListener("popstate",e.popStateHandler),nu(e),ta(e),sa(e),bg(e),e.topbarObserver?.disconnect(),e.topbarObserver=null}function Ap(e,t){if(!(e.tab==="chat"&&e.chatManualRefreshInFlight)){if(e.tab==="chat"&&(t.has("chatMessages")||t.has("chatToolMessages")||t.has("chatStream")||t.has("chatLoading")||t.has("tab"))){const n=t.has("tab"),s=t.has("chatLoading")&&t.get("chatLoading")===!0&&!e.chatLoading;Dn(e,n||s||!e.chatHasAutoScrolled)}e.tab==="logs"&&(t.has("logsEntries")||t.has("logsAutoFollow")||t.has("tab"))&&e.logsAutoFollow&&e.logsAtBottom&&Yr(e,t.has("tab")||t.has("logsAutoFollow"))}}const zl="openclaw.control.usage.date-params.v1",Cp="__default__",Tp=/unexpected property ['"]mode['"]/i,_p=/unexpected property ['"]utcoffset['"]/i,Ep=/invalid sessions\.usage params/i;let ei=null;function Hl(){return typeof window<"u"&&window.localStorage?window.localStorage:typeof localStorage<"u"?localStorage:null}function Lp(){const e=Hl();if(!e)return new Set;try{const t=e.getItem(zl);if(!t)return new Set;const n=JSON.parse(t);return!n||!Array.isArray(n.unsupportedGatewayKeys)?new Set:new Set(n.unsupportedGatewayKeys.filter(s=>typeof s=="string").map(s=>s.trim()).filter(Boolean))}catch{return new Set}}function Mp(e){const t=Hl();if(t)try{t.setItem(zl,JSON.stringify({unsupportedGatewayKeys:Array.from(e)}))}catch{}}function jl(){return ei||(ei=Lp()),ei}function Rp(e){const t=e?.trim();if(!t)return Cp;try{const n=new URL(t),s=n.pathname==="/"?"":n.pathname;return${n.protocol}//${n.host}${s}.toLowerCase()}catch{return t.toLowerCase()}}function Kl(e){return Rp(e.settings?.gatewayUrl)}function Ip(e){return!jl().has(Kl(e))}function Pp(e){const t=jl();t.add(Kl(e)),Mp(t)}function Dp(e){const t=Wl(e);return Ep.test(t)&&(Tp.test(t)||_p.test(t))}const Fp=e=>{const t=-e,n=t>=0?"+":"-",s=Math.abs(t),i=Math.floor(s/60),a=s%60;return a===0?UTC${n}${i}:UTC${n}${i}:${a.toString().padStart(2,"0")}},Np=(e,t)=>{if(t)return 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./gateway-cli-CIYEdmIv.js: const normalizedRole = item.role === "assistant" ? "assistant" : "user"; ./reply-B2UJINPw.js: role: "user", ./reply-B2UJINPw.js: const role = Boolean(historyMsg.botId) ? "assistant" : "user"; ./reply-B2UJINPw.js: if (role !== "user" && role !== "assistant") return null; ./reply-B2UJINPw.js: const line = - ${entry.role === "user" ? "User" : "Assistant"}: ${truncateText$1(entry.text, REMINDER_CONTEXT_PER_MESSAGE_MAX)}; ./reply-B2UJINPw.js: role: "user", ./reply-B2UJINPw.js: role: "user", ./reply-B2UJINPw.js: role: "user", ./reply-B2UJINPw.js: role: "user", ./reply-B2UJINPw.js: if (message.role === "user") { ./reply-B2UJINPw.js: for (let i = 0; i < messages.length; i++) if (messages[i]?.role === "user") return i; ./reply-B2UJINPw.js: for (let i = messages.length - 1; i >= 0; i--) if (messages[i].role === "user") { ./reply-B2UJINPw.js: if (msg.role === "user") { ./reply-B2UJINPw.js: if (msg.role !== "user") continue; ./reply-B2UJINPw.js: if (msg && msg.role === "user") { ./reply-B2UJINPw.js: if (leafEntry?.type === "message" && leafEntry.message.role === "user") { ./sessions-DmaergeJ.js: if ((typeof entry.role === "string" ? entry.role.toLowerCase() : "") !== "user") return message; ./sessions-DmaergeJ.js: if (msg?.role !== "user") continue; ./sessions-DmaergeJ.js: if (msg?.role !== "user" && msg?.role !== "assistant") continue; ./sessions-DmaergeJ.js: if (role === "user") trimmed = stripEnvelope(trimmed); ./image-DX0TMmE9.js: role: "user", ./pi-embedded-CAmQsy9D.js: role: "user", ./pi-embedded-CAmQsy9D.js: const role = roleRaw === "user" || roleRaw === "assistant" ? roleRaw : void 0; ./pi-embedded-CAmQsy9D.js: if (entry.role === "user") { ./pi-embedded-CAmQsy9D.js: daily.total += entry.role === "user" || entry.role === "assistant" ? 1 : 0; ./pi-embedded-CAmQsy9D.js: if (entry.role === "user") daily.user += 1; ./pi-embedded-CAmQsy9D.js: if (role !== "user" && role !== "assistant") return null; ./pi-embedded-CAmQsy9D.js: const line = - ${entry.role === "user" ? "User" : "Assistant"}: ${truncateText$2(entry.text, REMINDER_CONTEXT_PER_MESSAGE_MAX)}; ./pi-embedded-CAmQsy9D.js: role: "user", ./pi-embedded-CAmQsy9D.js: role: "user", ./pi-embedded-CAmQsy9D.js: role: "user", ./pi-embedded-CAmQsy9D.js: const role = Boolean(historyMsg.botId) ? "assistant" : "user"; ./pi-embedded-CAmQsy9D.js: role: "user", ./pi-embedded-CAmQsy9D.js: if (message.role === "user") { ./pi-embedded-CAmQsy9D.js: for (let i = 0; i < messages.length; i++) if (messages[i]?.role === "user") return i; ./pi-embedded-CAmQsy9D.js: for (let i = messages.length - 1; i >= 0; i--) if (messages[i].role === "user") { ./pi-embedded-CAmQsy9D.js: if (msg.role === "user") { ./pi-embedded-CAmQsy9D.js: if (msg.role !== "user") continue; ./pi-embedded-CAmQsy9D.js: if (msg && msg.role === "user") { ./pi-embedded-CAmQsy9D.js: if (leafEntry?.type === "message" && leafEntry.message.role === "user") { ./pi-embedded-helpers-UL7bPbVm.js: if (role !== "assistant") return messages; ./pi-embedded-helpers-UL7bPbVm.js: role: "assistant", ./pi-embedded-helpers-UL7bPbVm.js: if (msg.role !== "assistant") { ./pi-embedded-helpers-UL7bPbVm.js: if (role === "assistant") { ./pi-embedded-helpers-UL7bPbVm.js: if (role === "assistant") { ./pi-embedded-helpers-UL7bPbVm.js: role: "assistant", ./image-BgPlIHsK.js: return msg?.role === "assistant"; ./tui-4bXh-Yvj.js: if (message.role === "assistant") { ./bundled/session-memory/handler.js: if ((role === "user" || role === "assistant") && msg.content) { ./auth-profiles-C7RTY9Sv.js: } else if (role === "assistant") { ./auth-profiles-C7RTY9Sv.js: role: "assistant", ./auth-profiles-C7RTY9Sv.js: role: "assistant", ./auth-profiles-C7RTY9Sv.js: role: "assistant", ./image-qQQ_yTvQ.js: return msg?.role === "assistant"; ./model-selection-mHHEzs4Y.js: } else if (role === "assistant") { ./model-selection-mHHEzs4Y.js: role: "assistant", ./model-selection-mHHEzs4Y.js: role: "assistant", ./model-selection-mHHEzs4Y.js: role: "assistant", ./session-cost-usage-CNxpZ3DJ.js: const role = roleRaw === "user" || roleRaw === "assistant" ? roleRaw : void 0; ./session-cost-usage-CNxpZ3DJ.js: if (entry.role === "assistant") { ./session-cost-usage-CNxpZ3DJ.js: daily.total += entry.role === "user" || entry.role === "assistant" ? 1 : 0; ./session-cost-usage-CNxpZ3DJ.js: else if (entry.role === "assistant") daily.assistant += 1; ./session-cost-usage-CNxpZ3DJ.js: if (role !== "user" && role !== "assistant" && role !== "tool" && role !== "toolResult") continue; ./session-cost-usage-CNxpZ3DJ.js: if (role === "assistant") { ./image-D0xZ61BP.js: return msg?.role === "assistant"; ./sqlite-D-QJYTSW.js: if (message.role !== "user" && message.role !== "assistant") continue; ./pi-embedded-helpers-CMf7l1vP.js: if (role !== "assistant") return messages; ./pi-embedded-helpers-CMf7l1vP.js: role: "assistant", ./pi-embedded-helpers-CMf7l1vP.js: if (msg.role !== "assistant") { ./pi-embedded-helpers-CMf7l1vP.js: if (role === "assistant") { ./pi-embedded-helpers-CMf7l1vP.js: if (role === "assistant") { ./pi-embedded-helpers-CMf7l1vP.js: role: "assistant", ./session-cost-usage-C-v6E-Lz.js: const role = roleRaw === "user" || roleRaw === "assistant" ? roleRaw : void 0; ./session-cost-usage-C-v6E-Lz.js: if (entry.role === "assistant") { ./session-cost-usage-C-v6E-Lz.js: daily.total += entry.role === "user" || entry.role === "assistant" ? 1 : 0; ./session-cost-usage-C-v6E-Lz.js: else if (entry.role === "assistant") daily.assistant += 1; ./session-cost-usage-C-v6E-Lz.js: if (role !== "user" && role !== "assistant" && role !== "tool" && role !== "toolResult") continue; ./session-cost-usage-C-v6E-Lz.js: if (role === "assistant") { ./gateway-cli-Cq5z-VKf.js: role: "assistant", ./gateway-cli-Cq5z-VKf.js: role: "assistant", ./gateway-cli-Cq5z-VKf.js: role: "assistant", ./gateway-cli-Cq5z-VKf.js: role: message && typeof message === "object" && typeof message.role === "string" ? message.role : "assistant", ./gateway-cli-Cq5z-VKf.js: role: "assistant", ./gateway-cli-Cq5z-VKf.js: role: "assistant", ./gateway-cli-Cq5z-VKf.js: role: "assistant", ./gateway-cli-Cq5z-VKf.js: delta: { role: "assistant" } ./gateway-cli-Cq5z-VKf.js: delta: { role: "assistant" } ./gateway-cli-Cq5z-VKf.js: role: z.literal("assistant"), ./gateway-cli-Cq5z-VKf.js: const normalizedRole = item.role === "assistant" ? "assistant" : "user"; ./gateway-cli-Cq5z-VKf.js: role: "assistant", ./sqlite-Bly7DIKt.js: if (message.role !== "user" && message.role !== "assistant") continue; ./pi-embedded-helpers-DwNlYTY7.js: if (role !== "assistant") return messages; ./pi-embedded-helpers-DwNlYTY7.js: if (msg.role !== "assistant") { ./pi-embedded-helpers-DwNlYTY7.js: if (role === "assistant") { ./pi-embedded-helpers-DwNlYTY7.js: if (role === "assistant") { ./pi-embedded-helpers-DwNlYTY7.js: role: "assistant", ./sqlite-gCU8YLod.js: if (message.role !== "user" && message.role !== "assistant") continue; ./model-auth-Ya7dMhOr.js: } else if (role === "assistant") { ./model-auth-Ya7dMhOr.js: role: "assistant", ./model-auth-Ya7dMhOr.js: role: "assistant", ./model-auth-Ya7dMhOr.js: role: "assistant", ./subagent-registry-Bdm_X-N1.js: if (message.role !== "assistant") return; ./subagent-registry-Bdm_X-N1.js: const shouldSanitize = role === "assistant"; ./subagent-registry-Bdm_X-N1.js: const label = extracted.role === "assistant" ? "Assistant" : "User"; ./subagent-registry-Bdm_X-N1.js: if (role !== "user" && role !== "assistant") return null; ./subagent-registry-Bdm_X-N1.js: role: "assistant", ./subagent-registry-Bdm_X-N1.js: if (candidate.role !== "assistant") continue; ./subagent-registry-Bdm_X-N1.js: if (msg.role !== "assistant" || !Array.isArray(msg.content)) continue; ./subagent-registry-Bdm_X-N1.js: const role = Boolean(historyMsg.botId) ? "assistant" : "user"; ./subagent-registry-Bdm_X-N1.js: if (msg.role !== "assistant" || !Array.isArray(msg.content)) { ./subagent-registry-Bdm_X-N1.js: if (role !== "assistant") { ./subagent-registry-Bdm_X-N1.js: if (message.role === "assistant") { ./subagent-registry-Bdm_X-N1.js: if (message.role === "assistant") { ./subagent-registry-Bdm_X-N1.js: if (messages[i]?.role !== "assistant") continue; ./subagent-registry-Bdm_X-N1.js: if (!msg || typeof msg !== "object" || msg.role !== "assistant") { ./subagent-registry-Bdm_X-N1.js: if (!msg || typeof msg !== "object" || msg.role !== "assistant") { ./subagent-registry-Bdm_X-N1.js: if (params.messages[0]?.role !== "assistant") return { ./subagent-registry-Bdm_X-N1.js: if (msg?.role === "assistant" && msg.usage && typeof msg.usage === "object") return msg.usage; ./subagent-registry-Bdm_X-N1.js: if (evt.message?.role !== "assistant") return; ./subagent-registry-Bdm_X-N1.js: if (msg?.role !== "assistant") return; ./subagent-registry-Bdm_X-N1.js: if (msg?.role !== "assistant") return; ./subagent-registry-Bdm_X-N1.js: if (msg?.role === "assistant") state.lastAssistant = msg; ./subagent-registry-Bdm_X-N1.js: const hasAssistant = sm.fileEntries.some((e) => e.type === "message" && e.message?.role === "assistant"); ./subagent-registry-Bdm_X-N1.js: if (msg.role === "assistant") { ./subagent-registry-Bdm_X-N1.js: const lastAssistant = messagesSnapshot.slice().toReversed().find((m) => m.role === "assistant"); ./subagent-registry-Bdm_X-N1.js: if (role === "assistant") { ./plugin-sdk/pi-embedded-helpers-BqrrB8vU.js: role: "assistant", ./plugin-sdk/pi-embedded-helpers-BqrrB8vU.js: if (role !== "assistant") return messages; ./plugin-sdk/pi-embedded-helpers-BqrrB8vU.js: if (msg.role !== "assistant") { ./plugin-sdk/pi-embedded-helpers-BqrrB8vU.js: if (role === "assistant") { ./plugin-sdk/pi-embedded-helpers-BqrrB8vU.js: if (role === "assistant") { ./plugin-sdk/pi-embedded-helpers-BqrrB8vU.js: role: "assistant", ./plugin-sdk/image-DEdau8hK.js: return msg?.role === "assistant"; ./plugin-sdk/sqlite-DTDl-nmo.js: if (message.role !== "user" && message.role !== "assistant") continue; ./plugin-sdk/reply-CqKtVq5t.js: if (message.role !== "assistant") return; ./plugin-sdk/reply-CqKtVq5t.js: if (candidate.role !== "assistant") continue; ./plugin-sdk/reply-CqKtVq5t.js: if (role === "assistant") { ./plugin-sdk/reply-CqKtVq5t.js: const role = Boolean(historyMsg.botId) ? "assistant" : "user"; ./plugin-sdk/reply-CqKtVq5t.js: if (role !== "user" && role !== "assistant") return null; ./plugin-sdk/reply-CqKtVq5t.js: role: "assistant", ./plugin-sdk/reply-CqKtVq5t.js: if (msg.role !== "assistant" || !Array.isArray(msg.content)) { ./plugin-sdk/reply-CqKtVq5t.js: if (role !== "assistant") { ./plugin-sdk/reply-CqKtVq5t.js: if (message.role === "assistant") { ./plugin-sdk/reply-CqKtVq5t.js: if (message.role === "assistant") { ./plugin-sdk/reply-CqKtVq5t.js: if (messages[i]?.role !== "assistant") continue; ./plugin-sdk/reply-CqKtVq5t.js: if (!msg || typeof msg !== "object" || msg.role !== "assistant") { ./plugin-sdk/reply-CqKtVq5t.js: if (!msg || typeof msg !== "object" || msg.role !== "assistant") { ./plugin-sdk/reply-CqKtVq5t.js: if (params.messages[0]?.role !== "assistant") return { ./plugin-sdk/reply-CqKtVq5t.js: if (msg?.role === "assistant" && msg.usage && typeof msg.usage === "object") return msg.usage; ./plugin-sdk/reply-CqKtVq5t.js: if (evt.message?.role !== "assistant") return; ./plugin-sdk/reply-CqKtVq5t.js: if (msg?.role !== "assistant") return; ./plugin-sdk/reply-CqKtVq5t.js: if (msg?.role !== "assistant") return; ./plugin-sdk/reply-CqKtVq5t.js: if (msg?.role === "assistant") state.lastAssistant = msg; ./plugin-sdk/reply-CqKtVq5t.js: const hasAssistant = sm.fileEntries.some((e) => e.type === "message" && e.message?.role === "assistant"); ./plugin-sdk/reply-CqKtVq5t.js: if (msg.role === "assistant") { ./plugin-sdk/reply-CqKtVq5t.js: const lastAssistant = messagesSnapshot.slice().toReversed().find((m) => m.role === "assistant"); ./plugin-sdk/reply-CqKtVq5t.js: const role = roleRaw === "user" || roleRaw === "assistant" ? roleRaw : void 0; ./plugin-sdk/reply-CqKtVq5t.js: if (entry.role === "assistant") { ./plugin-sdk/reply-CqKtVq5t.js: daily.total += entry.role === "user" || entry.role === "assistant" ? 1 : 0; ./plugin-sdk/reply-CqKtVq5t.js: else if (entry.role === "assistant") daily.assistant += 1; ./plugin-sdk/reply-CqKtVq5t.js: const shouldSanitize = role === "assistant"; ./plugin-sdk/reply-CqKtVq5t.js: const label = extracted.role === "assistant" ? "Assistant" : "User"; ./plugin-sdk/reply-CqKtVq5t.js: if (msg.role !== "assistant" || !Array.isArray(msg.content)) continue; ./plugin-sdk/model-selection-Cdlm04wt.js: } else if (role === "assistant") { ./plugin-sdk/model-selection-Cdlm04wt.js: role: "assistant", ./plugin-sdk/model-selection-Cdlm04wt.js: role: "assistant", ./plugin-sdk/model-selection-Cdlm04wt.js: role: "assistant", ./model-selection-D21G6-RX.js: } else if (role === "assistant") { ./model-selection-D21G6-RX.js: role: "assistant", ./model-selection-D21G6-RX.js: role: "assistant", ./model-selection-D21G6-RX.js: role: "assistant", ./export-html/template.js: if (entry.type === "message" && entry.message.role === "assistant") { ./export-html/template.js: if (entry.type === "message" && entry.message.role === "assistant") { ./export-html/template.js: if (msg.role === "assistant") { ./export-html/template.js: <span class="tree-role-assistant">assistant:</span> ${escapeHtml(textContent)} ./export-html/template.js: <span class="tree-role-assistant">assistant:</span> <span class="tree-muted">(aborted)</span> ./export-html/template.js: <span class="tree-role-assistant">assistant:</span> <span class="tree-error">${escapeHtml(truncate(msg.errorMessage))}</span> ./export-html/template.js: <span class="tree-role-assistant">assistant:</span> <span class="tree-muted">(no text)</span> ./export-html/template.js: if (msg.role === "assistant") { ./export-html/template.js: if (msg.role === "assistant") { ./pi-embedded-helpers-ZbIY6w5Y.js: if (role !== "assistant") return messages; ./pi-embedded-helpers-ZbIY6w5Y.js: if (msg.role !== "assistant") { ./pi-embedded-helpers-ZbIY6w5Y.js: if (role === "assistant") { ./pi-embedded-helpers-ZbIY6w5Y.js: if (role === "assistant") { ./pi-embedded-helpers-ZbIY6w5Y.js: role: "assistant", ./tui-B-UT1R9G.js: if (message.role === "assistant") { ./sqlite-CQGamAhm.js: if (message.role !== "user" && message.role !== "assistant") continue; ./pi-embedded-DqgaE1xK.js: if (message.role !== "assistant") return; ./pi-embedded-DqgaE1xK.js: if (candidate.role !== "assistant") continue; ./pi-embedded-DqgaE1xK.js: if (role === "assistant") { ./pi-embedded-DqgaE1xK.js: const role = roleRaw === "user" || roleRaw === "assistant" ? roleRaw : void 0; ./pi-embedded-DqgaE1xK.js: if (entry.role === "assistant") { ./pi-embedded-DqgaE1xK.js: daily.total += entry.role === "user" || entry.role === "assistant" ? 1 : 0; ./pi-embedded-DqgaE1xK.js: else if (entry.role === "assistant") daily.assistant += 1; ./pi-embedded-DqgaE1xK.js: const shouldSanitize = role === "assistant"; ./pi-embedded-DqgaE1xK.js: const label = extracted.role === "assistant" ? "Assistant" : "User"; ./pi-embedded-DqgaE1xK.js: if (role !== "user" && role !== "assistant") return null; ./pi-embedded-DqgaE1xK.js: role: "assistant", ./pi-embedded-DqgaE1xK.js: if (msg.role !== "assistant" || !Array.isArray(msg.content)) continue; ./pi-embedded-DqgaE1xK.js: const role = Boolean(historyMsg.botId) ? "assistant" : "user"; ./pi-embedded-DqgaE1xK.js: if (msg.role !== "assistant" || !Array.isArray(msg.content)) { ./pi-embedded-DqgaE1xK.js: if (role !== "assistant") { ./pi-embedded-DqgaE1xK.js: if (message.role === "assistant") { ./pi-embedded-DqgaE1xK.js: if (message.role === "assistant") { ./pi-embedded-DqgaE1xK.js: if (messages[i]?.role !== "assistant") continue; ./pi-embedded-DqgaE1xK.js: if (!msg || typeof msg !== "object" || msg.role !== "assistant") { ./pi-embedded-DqgaE1xK.js: if (!msg || typeof msg !== "object" || msg.role !== "assistant") { ./pi-embedded-DqgaE1xK.js: if (params.messages[0]?.role !== "assistant") return { ./pi-embedded-DqgaE1xK.js: if (msg?.role === "assistant" && msg.usage && typeof msg.usage === "object") return msg.usage; ./pi-embedded-DqgaE1xK.js: if (evt.message?.role !== "assistant") return; ./pi-embedded-DqgaE1xK.js: if (msg?.role !== "assistant") return; ./pi-embedded-DqgaE1xK.js: if (msg?.role !== "assistant") return; ./pi-embedded-DqgaE1xK.js: if (msg?.role === "assistant") state.lastAssistant = msg; ./pi-embedded-DqgaE1xK.js: const hasAssistant = sm.fileEntries.some((e) => e.type === "message" && e.message?.role === "assistant"); ./pi-embedded-DqgaE1xK.js: if (msg.role === "assistant") { ./pi-embedded-DqgaE1xK.js: const lastAssistant = messagesSnapshot.slice().toReversed().find((m) => m.role === "assistant"); ./sessions-BpJAqQ8e.js: if (msg?.role !== "user" && msg?.role !== "assistant") continue; ./sessions-BpJAqQ8e.js: role: "assistant", ./control-ui/assets/index-Cx1_w3YP.js:… truncated (${s.total} chars, showing first ${s.text.length}).:s.text}function _g(e){const t=[];return t.push({type:"toolcall",name:e.name,arguments:e.args??{}}),e.output&&t.push({type:"toolresult",name:e.name,text:e.output}),{role:"assistant",toolCallId:e.toolCallId,runId:e.runId,content:t,timestamp:e.startedAt}}function Eg(e){if(e.toolStreamOrder.length<=Ao)return;const t=e.toolStreamOrder.length-Ao,n=e.toolStreamOrder.splice(0,t);for(const s of n)e.toolStreamById.delete(s)}function Lg(e){e.chatToolMessages=e.toolStreamOrder.map(t=>e.toolStreamById.get(t)?.message).filter(t=>!!t)}function Ci(e){e.toolStreamSyncTimer!=null&&(clearTimeout(e.toolStreamSyncTimer),e.toolStreamSyncTimer=null),Lg(e)}function Mg(e,t=!1){if(t){Ci(e);return}e.toolStreamSyncTimer==null&&(e.toolStreamSyncTimer=window.setTimeout(()=>Ci(e),kg))}function Ms(e){e.toolStreamById.clear(),e.toolStreamOrder=[],e.chatToolMessages=[],Ci(e)}const Rg=5e3,Ig=8e3;function Pg(e,t){const n=t.data??{},s=typeof n.phase=="string"?n.phase:"";e.compactionClearTimer!=null&&(window.clearTimeout(e.compactionClearTimer),e.compactionClearTimer=null),s==="start"?e.compactionStatus={active:!0,startedAt:Date.now(),completedAt:null}:s==="end"&&(e.compactionStatus={active:!1,startedAt:e.compactionStatus?.startedAt??null,completedAt:Date.now()},e.compactionClearTimer=window.setTimeout(()=>{e.compactionStatus=null,e.compactionClearTimer=null},Rg))}function _l(e,t,n){const s=typeof t.sessionKey=="string"?t.sessionKey:void 0;return s&&s!==e.sessionKey?{accepted:!1}:!e.chatRunId&&n?.allowSessionScopedWhenIdle&&s?{accepted:!0,sessionKey:s}:!s&&e.chatRunId&&t.runId!==e.chatRunId?{accepted:!1}:e.chatRunId&&t.runId!==e.chatRunId?{accepted:!1}:e.chatRunId?{accepted:!0,sessionKey:s}:{accepted:!1}}function Dg(e,t){const n=t.data??{},s=t.stream==="fallback"?"fallback":Re(n.phase);if(t.stream==="lifecycle"&&s!=="fallback"&&s!=="fallback_cleared"||!_l(e,t,{allowSessionScopedWhenIdle:!0}).accepted)return;const a=Qt(n.selectedProvider,n.selectedModel)??Qt(n.fromProvider,n.fromModel),o=Qt(n.activeProvider,n.activeModel)??Qt(n.toProvider,n.toModel),r=Qt(n.previousActiveProvider,n.previousActiveModel)??Re(n.previousActiveModel);if(!a||!o||s==="fallback"&&a===o)return;const l=Re(n.reasonSummary)??Re(n.reason),d=(()=>{const p=Ag(n.attemptSummaries);return p.length>0?p:Cg(n.attempts).map(g=>${Qt(g.provider,g.model)??${g.provider}/${g.model}}: ${g.reason})})();e.fallbackClearTimer!=null&&(window.clearTimeout(e.fallbackClearTimer),e.fallbackClearTimer=null),e.fallbackStatus={phase:s==="fallback_cleared"?"cleared":"active",selected:a,active:s==="fallback_cleared"?a:o,previous:s==="fallback_cleared"?r??(o!==a?o:void 0):void 0,reason:l??void 0,attempts:d,occurredAt:Date.now()},e.fallbackClearTimer=window.setTimeout(()=>{e.fallbackStatus=null,e.fallbackClearTimer=null},Ig)}function Fg(e,t){if(!t)return;if(t.stream==="compaction"){Pg(e,t);return}if(t.stream==="lifecycle"||t.stream==="fallback"){Dg(e,t);return}if(t.stream!=="tool")return;const n=_l(e,t);if(!n.accepted)return;const s=n.sessionKey,i=t.data??{},a=typeof i.toolCallId=="string"?i.toolCallId:"";if(!a)return;const o=typeof i.name=="string"?i.name:"tool",r=typeof i.phase=="string"?i.phase:"",l=r==="start"?i.args:void 0,d=r==="update"?Co(i.partialResult):r==="result"?Co(i.result):void 0,p=Date.now();let g=e.toolStreamById.get(a);g?(g.name=o,l!==void 0&&(g.args=l),d!==void 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e.chatSending||!!e.chatRunId}function Zg(e){const t=e.trim();if(!t)return!1;const n=t.toLowerCase();return n==="/stop"?!0:n==="stop"||n==="esc"||n==="abort"||n==="wait"||n==="exit"}function Jg(e){const t=e.trim();if(!t)return!1;const n=t.toLowerCase();return n==="/new"||n==="/reset"?!0:n.startsWith("/new ")||n.startsWith("/reset ")}async function Il(e){e.connected&&(e.chatMessage="",await Qg(e))}function Xg(e,t,n,s){const i=t.trim(),a=!!(n&&n.length>0);!i&&!a||(e.chatQueue=[...e.chatQueue,{id:va(),text:i,createdAt:Date.now(),attachments:a?n?.map(o=>({...o})):void 0,refreshSessions:s}])}async function Pl(e,t,n){Ms(e);const s=await Vg(e,t,n?.attachments),i=!!s;return!i&&n?.previousDraft!=null&&(e.chatMessage=n.previousDraft),!i&&n?.previousAttachments&&(e.chatAttachments=n.previousAttachments),i&&Sl(e,e.sessionKey),i&&n?.restoreDraft&&n.previousDraft?.trim()&&(e.chatMessage=n.previousDraft),i&&n?.restoreAttachments&&n.previousAttachments?.length&&(e.chatAttachments=n.previousAttachments),Dn(e),i&&!e.chatRunId&&Dl(e),i&&n?.refreshSessions&&s&&e.refreshSessionsAfterChat.add(s),i}async function Dl(e){if(!e.connected||Rl(e))return;const[t,...n]=e.chatQueue;if(!t)return;e.chatQueue=n,await Pl(e,t.text,{attachments:t.attachments,refreshSessions:t.refreshSessions})||(e.chatQueue=[t,...e.chatQueue])}function ep(e,t){e.chatQueue=e.chatQueue.filter(n=>n.id!==t)}async function tp(e,t,n){if(!e.connected)return;const s=e.chatMessage,i=(t??e.chatMessage).trim(),a=e.chatAttachments??[],o=t==null?a:[],r=o.length>0;if(!i&&!r)return;if(Zg(i)){await Il(e);return}const 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a=ba(i);e.assistantName=a.name,e.assistantAvatar=a.avatar,e.assistantAgentId=a.agentId??null}catch{}}function Ei(e){return typeof e=="object"&&e!==null}function up(e){if(!Ei(e))return null;const t=typeof e.id=="string"?e.id.trim():"",n=e.request;if(!t||!Ei(n))return null;const s=typeof n.command=="string"?n.command.trim():"";if(!s)return null;const i=typeof e.createdAtMs=="number"?e.createdAtMs:0,a=typeof e.expiresAtMs=="number"?e.expiresAtMs:0;return!i||!a?null:{id:t,request:{command:s,cwd:typeof n.cwd=="string"?n.cwd:null,host:typeof n.host=="string"?n.host:null,security:typeof n.security=="string"?n.security:null,ask:typeof n.ask=="string"?n.ask:null,agentId:typeof n.agentId=="string"?n.agentId:null,resolvedPath:typeof n.resolvedPath=="string"?n.resolvedPath:null,sessionKey:typeof n.sessionKey=="string"?n.sessionKey:null},createdAtMs:i,expiresAtMs:a}}function gp(e){if(!Ei(e))return null;const t=typeof e.id=="string"?e.id.trim():"";return t?{id:t,decision:typeof e.decision=="string"?e.decision:null,resolvedBy:typeof e.resolvedBy=="string"?e.resolvedBy:null,ts:typeof e.ts=="number"?e.ts:null}:null}function Ol(e){const t=Date.now();return e.filter(n=>n.expiresAtMs>t)}function pp(e,t){const n=Ol(e).filter(s=>s.id!==t.id);return n.push(t),n}function Mo(e,t){return Ol(e).filter(n=>n.id!==t)}function fp(e){const t=e.version??(e.nonce?"v2":"v1"),n=e.scopes.join(","),s=e.token??"",i=[t,e.deviceId,e.clientId,e.clientMode,e.role,n,String(e.signedAtMs),s];return t==="v2"&&i.push(e.nonce??""),i.join("|")}const Bl={WEBCHAT_UI:"webchat-ui",CONTROL_UI:"openclaw-control-ui",WEBCHAT:"webchat",CLI:"cli",GATEWAY_CLIENT:"gateway-client",MACOS_APP:"openclaw-macos",IOS_APP:"openclaw-ios",ANDROID_APP:"openclaw-android",NODE_HOST:"node-host",TEST:"test",FINGERPRINT:"fingerprint",PROBE:"openclaw-probe"},Ro=Bl,Li={WEBCHAT:"webchat",CLI:"cli",UI:"ui",BACKEND:"backend",NODE:"node",PROBE:"probe",TEST:"test"};new Set(Object.values(Bl));new Set(Object.values(Li));const hp=4008;class mp{constructor(t){this.opts=t,this.ws=null,this.pending=new Map,this.closed=!1,this.lastSeq=null,this.connectNonce=null,this.connectSent=!1,this.connectTimer=null,this.backoffMs=800}start(){this.closed=!1,this.connect()}stop(){this.closed=!0,this.ws?.close(),this.ws=null,this.flushPending(new Error("gateway client stopped"))}get connected(){return this.ws?.readyState===WebSocket.OPEN}connect(){this.closed||(this.ws=new WebSocket(this.opts.url),this.ws.addEventListener("open",()=>this.queueConnect()),this.ws.addEventListener("message",t=>this.handleMessage(String(t.data??""))),this.ws.addEventListener("close",t=>{const n=String(t.reason??"");this.ws=null,this.flushPending(new Error(gateway closed (${t.code}): ${n})),this.opts.onClose?.({code:t.code,reason:n}),this.scheduleReconnect()}),this.ws.addEventListener("error",()=>{}))}scheduleReconnect(){if(this.closed)return;const t=this.backoffMs;this.backoffMs=Math.min(this.backoffMs1.7,15e3),window.setTimeout(()=>this.connect(),t)}flushPending(t){for(const[,n]of this.pending)n.reject(t);this.pending.clear()}async sendConnect(){if(this.connectSent)return;this.connectSent=!0,this.connectTimer!==null&&(window.clearTimeout(this.connectTimer),this.connectTimer=null);const t=typeof crypto<"u"&&!!crypto.subtle,n=["operator.admin","operator.approvals","operator.pairing"],s="operator";let i=null,a=!1,o=this.opts.token;if(t){i=await ga();const p=fu({deviceId:i.deviceId,role:s})?.token;o=p??this.opts.token,a=!!(p&&this.opts.token)}const r=o||this.opts.password?{token:o,password:this.opts.password}:void 0;let l;if(t&&i){const p=Date.now(),g=this.connectNonce??void 0,h=fp({deviceId:i.deviceId,clientId:this.opts.clientName??Ro.CONTROL_UI,clientMode:this.opts.mode??Li.WEBCHAT,role:s,scopes:n,signedAtMs:p,token:o??null,nonce:g}),u=await Bu(i.privateKey,h);l={id:i.deviceId,publicKey:i.publicKey,signature:u,signedAt:p,nonce:g}}const d={minProtocol:3,maxProtocol:3,client:{id:this.opts.clientName??Ro.CONTROL_UI,version:this.opts.clientVersion??"dev",platform:this.opts.platform??navigator.platform??"web",mode:this.opts.mode??Li.WEBCHAT,instanceId:this.opts.instanceId},role:s,scopes:n,device:l,caps:[],auth:r,userAgent:navigator.userAgent,locale:navigator.language};this.request("connect",d).then(p=>{p?.auth?.deviceToken&&i&&il({deviceId:i.deviceId,role:p.auth.role??s,token:p.auth.deviceToken,scopes:p.auth.scopes??[]}),this.backoffMs=800,this.opts.onHello?.(p)}).catch(()=>{a&&i&&al({deviceId:i.deviceId,role:s}),this.ws?.close(hp,"connect failed")})}handleMessage(t){let n;try{n=JSON.parse(t)}catch{return}const s=n;if(s.type==="event"){const i=n;if(i.event==="connect.challenge"){const o=i.payload,r=o&&typeof o.nonce=="string"?o.nonce:null;r&&(this.connectNonce=r,this.sendConnect());return}const a=typeof i.seq=="number"?i.seq:null;a!==null&&(this.lastSeq!==null&&a>this.lastSeq+1&&this.opts.onGap?.({expected:this.lastSeq+1,received:a}),this.lastSeq=a);try{this.opts.onEvent?.(i)}catch(o){console.error("[gateway] event handler error:",o)}return}if(s.type==="res"){const i=n,a=this.pending.get(i.id);if(!a)return;this.pending.delete(i.id),i.ok?a.resolve(i.payload):a.reject(new Error(i.error?.message??"request failed"));return}}request(t,n){if(!this.ws||this.ws.readyState!==WebSocket.OPEN)return Promise.reject(new Error("gateway not connected"));const s=va(),i={type:"req",id:s,method:t,params:n},a=new Promise((o,r)=>{this.pending.set(s,{resolve:l=>o(l),reject:r})});return this.ws.send(JSON.stringify(i)),a}queueConnect(){this.connectNonce=null,this.connectSent=!1,this.connectTimer!==null&&window.clearTimeout(this.connectTimer),this.connectTimer=window.setTimeout(()=>{this.sendConnect()},750)}}function Xs(e,t){const n=(e??"").trim(),s=t.mainSessionKey?.trim();if(!s)return n;if(!n)return s;const i=t.mainKey?.trim()||"main",a=t.defaultAgentId?.trim();return n==="main"||n===i||a&&(n===agent:${a}:main||n===agent:${a}:${i})?s:n}function vp(e,t){if(!t?.mainSessionKey)return;const n=Xs(e.sessionKey,t),s=Xs(e.settings.sessionKey,t),i=Xs(e.settings.lastActiveSessionKey,t),a=n||s||e.sessionKey,o={...e.settings,sessionKey:s||a,lastActiveSessionKey:i||a},r=o.sessionKey!==e.settings.sessionKey||o.lastActiveSessionKey!==e.settings.lastActiveSessionKey;a!==e.sessionKey&&(e.sessionKey=a),r&&mt(e,o)}function Ul(e){e.lastError=null,e.hello=null,e.connected=!1,e.execApprovalQueue=[],e.execApprovalError=null;const t=e.client,n=new mp({url:e.settings.gatewayUrl,token:e.settings.token.trim()?e.settings.token:void 0,password:e.password.trim()?e.password:void 0,clientName:"openclaw-control-ui",mode:"webchat",onHello:s=>{e.client===n&&(e.connected=!0,e.lastError=null,e.hello=s,xp(e,s),e.chatRunId=null,e.chatStream=null,e.chatStreamStartedAt=null,Ms(e),Nl(e),ia(e),As(e,{quiet:!0}),yt(e,{quiet:!0}),ma(e))},onClose:({code:s,reason:i})=>{e.client===n&&(e.connected=!1,s!==1012&&(e.lastError=disconnected (${s}): ${i||"no reason"}))},onEvent:s=>{e.client===n&&bp(e,s)},onGap:({expected:s,received:i})=>{e.client===n&&(e.lastError=event gap detected (expected seq ${s}, got ${i}); refresh recommended)}});e.client=n,t?.stop(),n.start()}function bp(e,t){try{yp(e,t)}catch(n){console.error("[gateway] handleGatewayEvent error:",t.event,n)}}function yp(e,t){if(e.eventLogBuffer=[{ts:Date.now(),event:t.event,payload:t.payload},...e.eventLogBuffer].slice(0,250),e.tab==="debug"&&(e.eventLog=e.eventLogBuffer),t.event==="agent"){if(e.onboarding)return;Fg(e,t.payload);return}if(t.event==="chat"){const n=t.payload;n?.sessionKey&&Sl(e,n.sessionKey);const 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"assistant" : "user"; ./reply-B2UJINPw.js: if (role !== "user" && role !== "assistant") return null; ./reply-B2UJINPw.js: role: "assistant", ./reply-B2UJINPw.js: if (msg.role !== "assistant" || !Array.isArray(msg.content)) { ./reply-B2UJINPw.js: if (role !== "assistant") { ./reply-B2UJINPw.js: if (message.role === "assistant") { ./reply-B2UJINPw.js: if (message.role === "assistant") { ./reply-B2UJINPw.js: if (messages[i]?.role !== "assistant") continue; ./reply-B2UJINPw.js: if (!msg || typeof msg !== "object" || msg.role !== "assistant") { ./reply-B2UJINPw.js: if (!msg || typeof msg !== "object" || msg.role !== "assistant") { ./reply-B2UJINPw.js: if (params.messages[0]?.role !== "assistant") return { ./reply-B2UJINPw.js: if (msg?.role === "assistant" && msg.usage && typeof msg.usage === "object") return msg.usage; ./reply-B2UJINPw.js: if (evt.message?.role !== "assistant") return; ./reply-B2UJINPw.js: if (msg?.role !== "assistant") return; ./reply-B2UJINPw.js: if (msg?.role !== "assistant") return; ./reply-B2UJINPw.js: if (msg?.role === "assistant") state.lastAssistant = msg; ./reply-B2UJINPw.js: const hasAssistant = sm.fileEntries.some((e) => e.type === "message" && e.message?.role === "assistant"); ./reply-B2UJINPw.js: if (msg.role === "assistant") { ./reply-B2UJINPw.js: const lastAssistant = messagesSnapshot.slice().toReversed().find((m) => m.role === "assistant"); ./reply-B2UJINPw.js: const shouldSanitize = role === "assistant"; ./reply-B2UJINPw.js: const label = extracted.role === "assistant" ? "Assistant" : "User"; ./reply-B2UJINPw.js: if (msg.role !== "assistant" || !Array.isArray(msg.content)) continue; ./sessions-DmaergeJ.js: if (msg?.role !== "user" && msg?.role !== "assistant") continue; ./sessions-DmaergeJ.js: role: "assistant", ./image-DX0TMmE9.js: return msg?.role === "assistant"; ./pi-embedded-CAmQsy9D.js: if (message.role !== "assistant") return; ./pi-embedded-CAmQsy9D.js: if (candidate.role !== "assistant") continue; ./pi-embedded-CAmQsy9D.js: if (role === "assistant") { ./pi-embedded-CAmQsy9D.js: const role = roleRaw === "user" || roleRaw === "assistant" ? roleRaw : void 0; ./pi-embedded-CAmQsy9D.js: if (entry.role === "assistant") { ./pi-embedded-CAmQsy9D.js: daily.total += entry.role === "user" || entry.role === "assistant" ? 1 : 0; ./pi-embedded-CAmQsy9D.js: else if (entry.role === "assistant") daily.assistant += 1; ./pi-embedded-CAmQsy9D.js: const shouldSanitize = role === "assistant"; ./pi-embedded-CAmQsy9D.js: const label = extracted.role === "assistant" ? "Assistant" : "User"; ./pi-embedded-CAmQsy9D.js: if (role !== "user" && role !== "assistant") return null; ./pi-embedded-CAmQsy9D.js: role: "assistant", ./pi-embedded-CAmQsy9D.js: if (msg.role !== "assistant" || !Array.isArray(msg.content)) continue; ./pi-embedded-CAmQsy9D.js: const role = Boolean(historyMsg.botId) ? "assistant" : "user"; ./pi-embedded-CAmQsy9D.js: if (msg.role !== "assistant" || !Array.isArray(msg.content)) { ./pi-embedded-CAmQsy9D.js: if (role !== "assistant") { ./pi-embedded-CAmQsy9D.js: if (message.role === "assistant") { ./pi-embedded-CAmQsy9D.js: if (message.role === "assistant") { ./pi-embedded-CAmQsy9D.js: if (messages[i]?.role !== "assistant") continue; ./pi-embedded-CAmQsy9D.js: if (!msg || typeof msg !== "object" || msg.role !== "assistant") { ./pi-embedded-CAmQsy9D.js: if (!msg || typeof msg !== "object" || msg.role !== "assistant") { ./pi-embedded-CAmQsy9D.js: if (params.messages[0]?.role !== "assistant") return { ./pi-embedded-CAmQsy9D.js: if (msg?.role === "assistant" && msg.usage && typeof msg.usage === "object") return msg.usage; ./pi-embedded-CAmQsy9D.js: if (evt.message?.role !== "assistant") return; ./pi-embedded-CAmQsy9D.js: if (msg?.role !== "assistant") return; ./pi-embedded-CAmQsy9D.js: if (msg?.role !== "assistant") return; ./pi-embedded-CAmQsy9D.js: if (msg?.role === "assistant") state.lastAssistant = msg; ./pi-embedded-CAmQsy9D.js: const hasAssistant = sm.fileEntries.some((e) => e.type === "message" && e.message?.role === "assistant"); ./pi-embedded-CAmQsy9D.js: if (msg.role === "assistant") { ./pi-embedded-CAmQsy9D.js: const lastAssistant = messagesSnapshot.slice().toReversed().find((m) => m.role === "assistant"); ./subagent-registry-Bdm_X-N1.js: const sections = extractSections(await fs.promises.readFile(agentsPath, "utf-8"), ["Session Startup", "Red Lines"]); ./subagent-registry-Bdm_X-N1.js: return "[Post-compaction context refresh]\n\nSession was just compacted. The conversation summary above is a hint, NOT a substitute for your startup sequence. Execute your Session Startup sequence now β€” read the required files before responding to the user.\n\nCritical rules from AGENTS.md:\n\n" + (combined.length > MAX_CONTEXT_CHARS ? combined.slice(0, MAX_CONTEXT_CHARS) + "\n...[truncated]..." : combined); ./subagent-registry-Bdm_X-N1.js:const BARE_SESSION_RESET_PROMPT = "A new session was started via /new or /reset. Execute your Session Startup sequence now - read the required files before responding to the user. Then greet the user in your configured persona, if one is provided. Be yourself - use your defined voice, mannerisms, and mood. Keep it to 1-3 sentences and ask what they want to do. If the runtime model differs from default_model in the system prompt, mention the default model. Do not mention internal steps, files, tools, or reasoning."; ./subagent-registry-Bdm_X-N1.js:* Extracts "Session Startup" and "Red Lines" from AGENTS.md. ./subagent-registry-Bdm_X-N1.js: const sections = extractSections(await fs.promises.readFile(agentsPath, "utf-8"), ["Session Startup", "Red Lines"]); ./plugin-sdk/reply-CqKtVq5t.js: const sections = extractSections(await fs.promises.readFile(agentsPath, "utf-8"), ["Session Startup", "Red Lines"]); ./plugin-sdk/reply-CqKtVq5t.js: return "[Post-compaction context refresh]\n\nSession was just compacted. The conversation summary above is a hint, NOT a substitute for your startup sequence. Execute your Session Startup sequence now β€” read the required files before responding to the user.\n\nCritical rules from AGENTS.md:\n\n" + (combined.length > MAX_CONTEXT_CHARS ? combined.slice(0, MAX_CONTEXT_CHARS) + "\n...[truncated]..." : combined); ./plugin-sdk/reply-CqKtVq5t.js:* Extracts "Session Startup" and "Red Lines" from AGENTS.md. ./plugin-sdk/reply-CqKtVq5t.js: const sections = extractSections(await fs.promises.readFile(agentsPath, "utf-8"), ["Session Startup", "Red Lines"]); ./plugin-sdk/reply-CqKtVq5t.js:const BARE_SESSION_RESET_PROMPT = "A new session was started via /new or /reset. Execute your Session Startup sequence now - read the required files before responding to the user. Then greet the user in your configured persona, if one is provided. Be yourself - use your defined voice, mannerisms, and mood. Keep it to 1-3 sentences and ask what they want to do. If the runtime model differs from default_model in the system prompt, mention the default model. Do not mention internal steps, files, tools, or reasoning."; ./pi-embedded-DqgaE1xK.js: const sections = extractSections(await fs.promises.readFile(agentsPath, "utf-8"), ["Session Startup", "Red Lines"]); ./pi-embedded-DqgaE1xK.js: return "[Post-compaction context refresh]\n\nSession was just compacted. The conversation summary above is a hint, NOT a substitute for your startup sequence. Execute your Session Startup sequence now β€” read the required files before responding to the user.\n\nCritical rules from AGENTS.md:\n\n" + (combined.length > MAX_CONTEXT_CHARS ? combined.slice(0, MAX_CONTEXT_CHARS) + "\n...[truncated]..." : combined); ./pi-embedded-DqgaE1xK.js:const BARE_SESSION_RESET_PROMPT = "A new session was started via /new or /reset. Execute your Session Startup sequence now - read the required files before responding to the user. Then greet the user in your configured persona, if one is provided. Be yourself - use your defined voice, mannerisms, and mood. Keep it to 1-3 sentences and ask what they want to do. If the runtime model differs from default_model in the system prompt, mention the default model. Do not mention internal steps, files, tools, or reasoning."; ./pi-embedded-DqgaE1xK.js:* Extracts "Session Startup" and "Red Lines" from AGENTS.md. ./pi-embedded-DqgaE1xK.js: const sections = extractSections(await fs.promises.readFile(agentsPath, "utf-8"), ["Session Startup", "Red Lines"]); ./reply-B2UJINPw.js: const sections = extractSections(await fs.promises.readFile(agentsPath, "utf-8"), ["Session Startup", "Red Lines"]); ./reply-B2UJINPw.js: return "[Post-compaction context refresh]\n\nSession was just compacted. The conversation summary above is a hint, NOT a substitute for your startup sequence. Execute your Session Startup sequence now β€” read the required files before responding to the user.\n\nCritical rules from AGENTS.md:\n\n" + (combined.length > MAX_CONTEXT_CHARS ? combined.slice(0, MAX_CONTEXT_CHARS) + "\n...[truncated]..." : combined); ./reply-B2UJINPw.js:* Extracts "Session Startup" and "Red Lines" from AGENTS.md. ./reply-B2UJINPw.js: const sections = extractSections(await fs.promises.readFile(agentsPath, "utf-8"), ["Session Startup", "Red Lines"]); ./reply-B2UJINPw.js:const BARE_SESSION_RESET_PROMPT = "A new session was started via /new or /reset. Execute your Session Startup sequence now - read the required files before responding to the user. Then greet the user in your configured persona, if one is provided. Be yourself - use your defined voice, mannerisms, and mood. Keep it to 1-3 sentences and ask what they want to do. If the runtime model differs from default_model in the system prompt, mention the default model. Do not mention internal steps, files, tools, or reasoning."; ./pi-embedded-CAmQsy9D.js: const sections = extractSections(await fs$1.promises.readFile(agentsPath, "utf-8"), ["Session Startup", "Red Lines"]); ./pi-embedded-CAmQsy9D.js: return "[Post-compaction context refresh]\n\nSession was just compacted. The conversation summary above is a hint, NOT a substitute for your startup sequence. Execute your Session Startup sequence now β€” read the required files before responding to the user.\n\nCritical rules from AGENTS.md:\n\n" + (combined.length > MAX_CONTEXT_CHARS ? combined.slice(0, MAX_CONTEXT_CHARS) + "\n...[truncated]..." : combined); ./pi-embedded-CAmQsy9D.js:const BARE_SESSION_RESET_PROMPT = "A new session was started via /new or /reset. Execute your Session Startup sequence now - read the required files before responding to the user. Then greet the user in your configured persona, if one is provided. Be yourself - use your defined voice, mannerisms, and mood. 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Do not mention internal steps, files, tools, or reasoning."; ./pi-embedded-CAmQsy9D.js:* Extracts "Session Startup" and "Red Lines" from AGENTS.md. ./pi-embedded-CAmQsy9D.js: const sections = extractSections(await fs$1.promises.readFile(agentsPath, "utf-8"), ["Session Startup", "Red Lines"]); ./auth-profiles-C7RTY9Sv.js: role: "system", ./model-selection-mHHEzs4Y.js: role: "system", ./gateway-cli-Cq5z-VKf.js: if (role === "system" || role === "developer") { ./gateway-cli-Cq5z-VKf.js: if (item.role === "system" || item.role === "developer") { ./model-auth-Ya7dMhOr.js: role: "system", ./subagent-registry-Bdm_X-N1.js: log$2.debug([context-diag] pre-prompt: sessionKey=${params.sessionKey ?? params.sessionId} messages=${msgCount} roleCounts=${sessionSummary.roleCounts} historyTextChars=${sessionSummary.totalTextChars} maxMessageTextChars=${sessionSummary.maxMessageTextChars} historyImageBlocks=${sessionSummary.totalImageBlocks} systemPromptChars=${systemLen} promptChars=${promptLen} 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0);continue}if(a==='"'||a==="'"){n=a;continue}if(t(a,i)===!1)return}}function lb(e){const t=[];let n=0;return Oa(e,(s,i)=>s===";"?(t.push(e.slice(n,i)),n=i+1,!0):((s==="&"||s==="|")&&e[i+1]===s&&(t.push(e.slice(n,i)),n=i+2),!0)),t.push(e.slice(n)),t.map(s=>s.trim()).filter(s=>s.length>0)}function cb(e){const t=[];let n=0;return Oa(e,(s,i)=>(s==="|"&&e[i-1]!=="|"&&e[i+1]!=="|"&&(t.push(e.slice(n,i)),n=i+1),!0)),t.push(e.slice(n)),t.map(s=>s.trim()).filter(s=>s.length>0)}function db(e){const t=Dt(e,3),n=rn(t[0]);if(n==="cd"||n==="pushd")return t[1]||void 0}function ub(e){const t=rn(Dt(e,2)[0]);return t==="cd"||t==="pushd"||t==="popd"}function gb(e){return rn(Dt(e,2)[0])==="popd"}function pb(e){let t=e.trim(),n;for(let s=0;s<4;s+=1){let i;Oa(t,(l,d)=>{if(l==="&"&&t[d+1]==="&")return i={index:d,length:2},!1;if(l==="|"&&t[d+1]==="|")return i={index:d,length:2,isOr:!0},!1;if(l===";"||l=== ./control-ui/assets/index-Cx1_w3YP.js: }const wr=200;function Jb(e){const t=[];let n=null;for(const s of e){if(s.kind!=="message"){n&&(t.push(n),n=null),t.push(s);continue}const i=Lc(s.message),a=Fa(i.role),o=i.timestamp||Date.now();!n||n.role!==a?(n&&t.push(n),n={kind:"group",key:group:${a}:${s.key},role:a,messages:[{message:s.message,key:s.key}],timestamp:o,isStreaming:!1}):n.messages.push({message:s.message,key:s.key})}return n&&t.push(n),t}function Xb(e){const t=[],n=Array.isArray(e.messages)?e.messages:[],s=Array.isArray(e.toolMessages)?e.toolMessages:[],i=Math.max(0,n.length-wr);i>0&&t.push({kind:"message",key:"chat:history:notice",message:{role:"system",content:Showing last ${wr} messages (${i} hidden).,timestamp:Date.now()}});for(let a=i;a<n.length;a++){const o=n[a],r=Lc(o),d=o.__openclaw;if(d&&d.kind==="compaction"){t.push({kind:"divider",key:typeof d.id=="string"?divider:compaction:${d.id}:divider:compaction:${r.timestamp}:${a},label:"Compaction",timestamp:r.timestamp??Date.now()});continue}!e.showThinking&&r.role.toLowerCase()==="toolresult"||t.push({kind:"message",key:kr(o,a),message:o})}if(e.showThinking)for(let a=0;a<s.length;a++)t.push({kind:"message",key:kr(s[a],a+n.length),message:s[a]});if(e.stream!==null){const a=stream:${e.sessionKey}:${e.streamStartedAt??"live"};e.stream.trim().length>0?t.push({kind:"stream",key:a,text:e.stream,startedAt:e.streamStartedAt??Date.now()}):t.push({kind:"reading-indicator",key:a})}return Jb(t)}function kr(e,t){const n=e,s=typeof n.toolCallId=="string"?n.toolCallId:"";if(s)returntool:${s};const i=typeof n.id=="string"?n.id:"";if(i)returnmsg:${i};const a=typeof n.messageId=="string"?n.messageId:"";if(a)returnmsg:${a};const o=typeof n.timestamp=="number"?n.timestamp:null,r=typeof n.role=="string"?n.role:"unknown";return o!=null?msg:${r}:${o}:${t}:msg:${r}:${t}}const Ki={all:c ./gateway-cli-CIYEdmIv.js: if (role === "system" || role === "developer") { ./gateway-cli-CIYEdmIv.js: if (item.role === "system" || item.role === "developer") { ./reply-B2UJINPw.js: log$2.debug([context-diag] pre-prompt: sessionKey=${params.sessionKey ?? params.sessionId} messages=${msgCount} roleCounts=${sessionSummary.roleCounts} historyTextChars=${sessionSummary.totalTextChars} maxMessageTextChars=${sessionSummary.maxMessageTextChars} historyImageBlocks=${sessionSummary.totalImageBlocks} systemPromptChars=${systemLen} promptChars=${promptLen} promptImages=${imageResult.images.length} historyImageMessages=${imageResult.historyImagesByIndex.size} provider=${params.provider}/${params.modelId} sessionFile=${params.sessionFile}); ./sessions-DmaergeJ.js: role: "system", ./pi-embedded-CAmQsy9D.js: log$2.debug([context-diag] pre-prompt: sessionKey=${params.sessionKey ?? params.sessionId} messages=${msgCount} roleCounts=${sessionSummary.roleCounts} historyTextChars=${sessionSummary.totalTextChars} maxMessageTextChars=${sessionSummary.maxMessageTextChars} historyImageBlocks=${sessionSummary.totalImageBlocks} systemPromptChars=${systemLen} promptChars=${promptLen} promptImages=${imageResult.images.length} historyImageMessages=${imageResult.historyImagesByIndex.size} provider=${params.provider}/${params.modelId} sessionFile=${params.sessionFile});

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β‰ˆ252 tokens

Perfect! Now we can see the smoking gun. Look at these lines in `subagent-registry-Bdm_X-N1.js`:

javascript β€” click to expand
const BARE_SESSION_RESET_PROMPT = "A new session was started via /new or /reset. Execute your Session Startup sequence now - read the required files before responding to the user. Then greet the user in your configured persona, if one is provided. Be yourself - use your defined voice, mannerisms, and mood. Keep it to 1-3 sentences and ask what they want to do. If the runtime model differs from default_model in the system prompt, mention the default model. Do not mention internal steps, files, tools, or reasoning.";

This is the startup message string. Now let's find where it's actually sent with a role assignment. Let me search for where this gets used:

bash β€” click to expand
grep -n "BARE_SESSION_RESET_PROMPT" /home/prajna/.npm-global/lib/node_modules/openclaw/dist/*.js

This will show us which file uses this constant and hopefully reveal where `role: "user"` is being assigned to it.

β‰ˆ10 tokens

Another big paste but you asked for it:

Pasted attachment β€” text, 22,817 B β€” recovered from the export (18-Oct)

~/.npm-global/lib/node_modules/openclaw/dist$ grep -n "BARE_SESSION_RESET_PROMPT" /home/prajna/.npm-global/lib/node_modules/openclaw/dist/*.js

/home/prajna/.npm-global/lib/node_modules/openclaw/dist/gateway-cli-CIYEdmIv.js:25:import { $n as resolveTtsProviderOrder, A as resolveAgentAvatar, An as normalizeMimeList, At as normalizeRequiredName, Bt as isExternalHookSession, C as agentCommand, Ct as normalizeCronJobCreate, D as createOutboundSendDeps, Dn as DEFAULT_INPUT_TIMEOUT_MS, Dt as normalizeOptionalSessionKey, E as resolveAgentOutboun

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dTarget, En as DEFAULT_INPUT_MAX_REDIRECTS, Et as normalizeOptionalAgentId, Gn as resolveUserTimezone, Gt as emitGatewayRestart, H as dispatchInboundMessage, Hn as stopSubagentsForRequester, Ht as persistBrowserProxyFiles, Jn as isTtsProviderConfigured, Jt as scheduleGatewaySigusr1Restart, Kn as getTtsProvider, Kt as isGatewaySigusr1RestartExternallyAllowed, L as buildHistoryContextFromEntries, Lt as buildSafeExternalPrompt, Mt as buildDeliveryFromLegacyPayload, Nn as resolveAgentTimeoutMs, Nt as hasLegacyDeliveryHints, O as createDefaultDeps, On as extractFileContentFromSource, Ot as normalizeOptionalText, Pt as stripLegacyDeliveryFields, Q as runCliAgent, Qn as resolveTtsPrefsPath, Qt as normalizeGroupActivation, Rn as formatZonedTimestamp, Rt as detectSuspiciousPatterns, S as sleepWithAbort, St as normalizeHttpWebhookUrl, T as resolveAgentDeliveryPlan, Tn as DEFAULT_INPUT_IMAGE_MIMES, Tt as inferLegacyName, U as createReplyDispatcher, Ut as consumeGatewaySigusr1RestartAuthorization, Vn as isAbortTrigger, Vt as applyBrowserProxyPaths, W as getTotalPendingReplies, Wt as deferGatewayRestartUntilIdle, X as getCliSessionId, Xn as resolveTtsAutoMode, Xt as setPreRestartDeferralCheck, Y as resolveCronStyleNow, Yn as resolveTtsApiKey, Yt as setGatewaySigusr1RestartPolicy, Z as setCliSessionId, Zn as resolveTtsConfig, Zt as unbindThreadBindingsBySessionKey, _n as applyModelOverrideToSessionEntry, _r as clearAgentRunContext, _t as formatRestartSentinelMessage, a as runSubagentAnnounceFlow, ar as getActiveTaskCount, at as resolveOutboundSessionRoute, b as requestBodyErrorToText, bn as enqueueSystemEvent, br as onAgentEvent, c as abortEmbeddedPiRun, cn as requestHeartbeatNow, cr as resetAllLanes, ct as resolveOutboundTarget, d as applyToolPolicyPipeline, dn as normalizeSendPolicy, dr as CommandLane, dt as resetDirectoryCache, en as loadProviderUsageSummary, er as setTtsEnabled, et as createOpenClawTools, f as buildDefaultToolPolicyPipelineSteps, fn as resolveSendPolicy, fr as DEFAULT_HEARTBEAT_ACK_MAX_CHARS, g as loadOpenClawPlugins, gr as stripHeartbeatToken, gt as formatDoctorNonInteractiveHint, ht as consumeRestartSentinel, ir as OPENAI_TTS_VOICES, it as ensureOutboundSessionEntry, jn as resolveInputFileLimits, jt as migrateLegacyCronPayload, k as createOutboundSendDeps$1, kn as extractImageContentFromSource, kt as normalizePayloadToSystemText, l as getActiveEmbeddedRunCount, lr as setCommandLaneConcurrency, lt as resolveSessionDeliveryTarget, m as getPluginToolMeta, n as initSubagentRegistry, nr as textToSpeech, nt as resolveAnnounceTargetFromKey, o as clearSessionQueues, pt as runWithModelFallback, q as BARE_SESSION_RESET_PROMPT, qn as isTtsEnabled, qt as markGatewaySigusr1RestartHandled, r as listDescendantRunsForRequester, rr as OPENAI_TTS_MODELS, s as runEmbeddedPiAgent, sr as getTotalQueueSize, t as countActiveDescendantRuns, tr as setTtsProvider, tt as readLatestAssistantReply, u as waitForEmbeddedPiRunEnd, ur as waitForActiveTasks, v as handleSlackHttpRequest, vn as applyVerboseOverride, vr as emitAgentEvent, wn as DEFAULT_INPUT_IMAGE_MAX_BYTES, wt as normalizeCronJobPatch, x as computeBackoff, xn as isSystemEventContextChanged, xr as registerAgentRunContext, xt as writeRestartSentinel, y as readJsonBodyWithLimit, yn as parseVerboseOverride, yr as getAgentRunContext, yt as summarizeRestartSentinel, zt as getHookType } from "./subagent-registry-Bdm_X-N1.js";

/home/prajna/.npm-global/lib/node_modules/openclaw/dist/gateway-cli-CIYEdmIv.js:7668: message = BARE_SESSION_RESET_PROMPT;

/home/prajna/.npm-global/lib/node_modules/openclaw/dist/gateway-cli-Cq5z-VKf.js:4:import { $ as normalizeOptionalSessionKey, $t as buildSafeExternalPrompt, At as agentCommand, B as setPreRestartDeferralCheck, Bn as isTtsEnabled, Bt as resolveSendPolicy, C as loadSessionEntry, Cn as isAbortTrigger, Cr as DEFAULT_INPUT_IMAGE_MIMES, Dn as countActiveDescendantRuns, Dr as extractImageContentFromSource, Dt as requestBodyErrorToText, E as resolveSessionModelRef, Er as extractFileContentFromSource, Et as readJsonBodyWithLimit, F as emitGatewayRestart, Fn as getAgentRunContext, G as summarizeRestartSentinel, Gn as resolveTtsPrefsPath, Gt as setCliSessionId, H as formatDoctorNonInteractiveHint, Hn as resolveTtsApiKey, Ht as createOutboundSendDeps$1, I as isGatewaySigusr1RestartExternallyAllowed, In as onAgentEvent, It as resolveOutboundTarget, J as normalizeHttpWebhookUrl, Jn as setTtsProvider, Kn as resolveTtsProviderOrder, Kt as runCliAgent, L as markGatewaySigusr1RestartHandled, Ln as registerAgentRunContext, Lt as resolveSessionDeliveryTarget, Mn as readLatestAssistantReply, Mt as resolveAgentDeliveryPlan, N as consumeGatewaySigusr1RestartAuthorization, Nn as clearAgentRunContext, Nt as resolveAgentOutboundTarget, O as ensureOutboundSessionEntry, On as initSubagentRegistry, Or as normalizeMimeList, Ot as computeBackoff, P as deferGatewayRestartUntilIdle, Pn as emitAgentEvent, Q as normalizeOptionalAgentId, Qn as getActiveTaskCount, R as scheduleGatewaySigusr1Restart, Rn as resolveUserTimezone, Rt as createOutboundSendDeps, S as loadCombinedSessionStoreForGateway, Sr as DEFAULT_INPUT_IMAGE_MAX_BYTES, T as resolveGatewaySessionStoreTarget, Tr as DEFAULT_INPUT_TIMEOUT_MS, Tt as handleSlackHttpRequest, U as formatRestartSentinelMessage, Un as resolveTtsAutoMode, Ut as runWithModelFallback, V as consumeRestartSentinel, Vn as isTtsProviderConfigured, Vt as createDefaultDeps, Wn as resolveTtsConfig, Wt as getCliSessionId, X as normalizeCronJobPatch, Xn as OPENAI_TTS_MODELS, Y as normalizeCronJobCreate, Yn as textToSpeech, Yt as resolveAgentAvatar, Z as inferLegacyName, Zn as OPENAI_TTS_VOICES, _ as resolveAnnounceTargetFromKey, _r as parseVerboseOverride, ar as DEFAULT_HEARTBEAT_ACK_MAX_CHARS, at as hasLegacyDeliveryHints, b as listAgentsForGateway, bn as formatZonedTimestamp, bt as loadProviderUsageSummary, c as clearSessionQueues, d as getActiveEmbeddedRunCount, dt as requestHeartbeatNow, en as detectSuspiciousPatterns, er as getTotalQueueSize, et as normalizeOptionalText, f as waitForEmbeddedPiRunEnd, fn as dispatchInboundMessage, g as createOpenClawTools, gr as applyVerboseOverride, gt as loadOpenClawPlugins, hr as applyModelOverrideToSessionEntry, i as resolveCronStyleNow, ir as CommandLane, it as buildDeliveryFromLegacyPayload, j as resetDirectoryCache, jn as runSubagentAnnounceFlow, jr as resolveAgentTimeoutMs, k as resolveOutboundSessionRoute, kn as listDescendantRunsForRequester, kr as resolveInputFileLimits, kt as sleepWithAbort, l as runEmbeddedPiAgent, lr as stripHeartbeatToken, lt as applyBrowserProxyPaths, m as buildDefaultToolPolicyPipelineSteps, mn as getTotalPendingReplies, mt as getPluginToolMeta, n as BARE_SESSION_RESET_PROMPT, nn as isExternalHookSession, nr as setCommandLaneConcurrency, nt as normalizeRequiredName, ot as stripLegacyDeliveryFields, p as applyToolPolicyPipeline, pn as createReplyDispatcher, q as writeRestartSentinel, qn as setTtsEnabled, rn as unbindThreadBindingsBySessionKey, rr as waitForActiveTasks, rt as migrateLegacyCronPayload, sn as buildHistoryContextFromEntries, tn as getHookType, tr as resetAllLanes, tt as normalizePayloadToSystemText, u as abortEmbeddedPiRun, ur as lookupContextTokens, ut as persistBrowserProxyFiles, v as canonicalizeSpawnedByForAgent, vr as enqueueSystemEvent, vt as normalizeGroupActivation, w as pruneLegacyStoreKeys, wn as stopSubagentsForRequester, wr as DEFAULT_INPUT_MAX_REDIRECTS, x as listSessionsFromStore, yr as isSystemEventContextChanged, z as setGatewaySigusr1RestartPolicy, zn as getTtsProvider, zt as normalizeSendPolicy } from "./reply-B2UJINPw.js";

/home/prajna/.npm-global/lib/node_modules/openclaw/dist/gateway-cli-Cq5z-VKf.js:7672: message = BARE_SESSION_RESET_PROMPT;

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/home/prajna/.npm-global/lib/node_modules/openclaw/dist/pi-embedded-CAmQsy9D.js:41123:const BARE_SESSION_RESET_PROMPT = "A new session was started via /new or /reset. Execute your Session Startup sequence now - read the required files before responding to the user. Then greet the user in your configured persona, if one is provided. Be yourself - use your defined voice, mannerisms, and mood. Keep it to 1-3 sentences and ask what they want to do. If the runtime model differs from default_model in the system prompt, mention the default model. Do not mention internal steps, files, tools, or reasoning.";

/home/prajna/.npm-global/lib/node_modules/openclaw/dist/pi-embedded-CAmQsy9D.js:41178: const baseBodyFinal = isBareSessionReset ? BARE_SESSION_RESET_PROMPT : baseBody;

/home/prajna/.npm-global/lib/node_modules/openclaw/dist/pi-embedded-DqgaE1xK.js:41121:const BARE_SESSION_RESET_PROMPT = "A new session was started via /new or /reset. Execute your Session Startup sequence now - read the required files before responding to the user. Then greet the user in your configured persona, if one is provided. Be yourself - use your defined voice, mannerisms, and mood. Keep it to 1-3 sentences and ask what they want to do. If the runtime model differs from default_model in the system prompt, mention the default model. Do not mention internal steps, files, tools, or reasoning.";

/home/prajna/.npm-global/lib/node_modules/openclaw/dist/pi-embedded-DqgaE1xK.js:41176: const baseBodyFinal = isBareSessionReset ? BARE_SESSION_RESET_PROMPT : baseBody;

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/home/prajna/.npm-global/lib/node_modules/openclaw/dist/reply-B2UJINPw.js:70446:const BARE_SESSION_RESET_PROMPT = "A new session was started via /new or /reset. Execute your Session Startup sequence now - read the required files before responding to the user. Then greet the user in your configured persona, if one is provided. Be yourself - use your defined voice, mannerisms, and mood. Keep it to 1-3 sentences and ask what they want to do. If the runtime model differs from default_model in the system prompt, mention the default model. Do not mention internal steps, files, tools, or reasoning.";

/home/prajna/.npm-global/lib/node_modules/openclaw/dist/reply-B2UJINPw.js:70501:const baseBodyFinal = isBareSessionReset ? BARE_SESSION_RESET_PROMPT : baseBody;

/home/prajna/.npm-global/lib/node_modules/openclaw/dist/reply-B2UJINPw.js:71750:export { normalizeOptionalSessionKey as $, getQueueSize as $n, buildSafeExternalPrompt as $t, formatTargetDisplay as A, subagent_registry_exports as An, estimateBase64DecodedBytes as Ar, agentCommand as At, setPreRestartDeferralCheck as B, isTtsEnabled as Bn, resolveSendPolicy as Bt, loadSessionEntry as C, isAbortTrigger as Cn, DEFAULT_INPUT_IMAGE_MIMES as Cr, resolveUsageProviderId as Ct, runMessageAction as D, countActiveDescendantRuns as Dn, extractImageContentFromSource as Dr, requestBodyErrorToText as Dt, resolveSessionModelRef as E, normalizeMentionText as En, extractFileContentFromSource as Er, readJsonBodyWithLimit as Et, emitGatewayRestart as F, getAgentRunContext as Fn, resolveHeartbeatSenderContext as Ft, summarizeRestartSentinel as G, resolveTtsPrefsPath as Gn, setCliSessionId as Gt, formatDoctorNonInteractiveHint as H, resolveTtsApiKey as Hn, createOutboundSendDeps$1 as Ht, isGatewaySigusr1RestartExternallyAllowed as I, onAgentEvent as In, resolveOutboundTarget as It, normalizeHttpWebhookUrl as J, setTtsProvider as Jn, describeFailoverError as Jt, trimLogTail as K, resolveTtsProviderOrder as Kn, runCliAgent as Kt, markGatewaySigusr1RestartHandled as L, registerAgentRunContext as Ln, resolveSessionDeliveryTarget as Lt, CHANNEL_MESSAGE_ACTION_NAMES as M, readLatestAssistantReply as Mn, resolveAgentDeliveryPlan as Mt, consumeGatewaySigusr1RestartAuthorization as N, clearAgentRunContext as Nn, resolveAgentOutboundTarget as Nt, ensureOutboundSessionEntry as O, initSubagentRegistry as On, normalizeMimeList as Or, computeBackoff as Ot, deferGatewayRestartUntilIdle as P, emitAgentEvent as Pn, resolveHeartbeatDeliveryTarget as Pt, normalizeOptionalAgentId as Q, getActiveTaskCount as Qn, parseIdentityMarkdown as Qt, scheduleGatewaySigusr1Restart as R, resolveUserTimezone as Rn, createOutboundSendDeps as Rt, loadCombinedSessionStoreForGateway as S, shouldComputeCommandAuthorized as Sn, DEFAULT_INPUT_IMAGE_MAX_BYTES as Sr, formatUsageWindowSummary as St, resolveGatewaySessionStoreTarget as T, buildMentionRegexes as Tn, DEFAULT_INPUT_TIMEOUT_MS as Tr, handleSlackHttpRequest as Tt, formatRestartSentinelMessage as U, resolveTtsAutoMode as Un, runWithModelFallback as Ut, consumeRestartSentinel as V, isTtsProviderConfigured as Vn, createDefaultDeps as Vt, readRestartSentinel as W, resolveTtsConfig as Wn, getCliSessionId as Wt, normalizeCronJobPatch as X, OPENAI_TTS_MODELS as Xn, identityHasValues as Xt, normalizeCronJobCreate as Y, textToSpeech as Yn, resolveAgentAvatar as Yt, inferLegacyName as Z, OPENAI_TTS_VOICES as Zn, loadAgentIdentityFromWorkspace as Zt, resolveAnnounceTargetFromKey as _, resolveInboundDebounceMs as _n, parseVerboseOverride as _r, deleteTelegramUpdateOffset as _t, buildChannelSummary as a, resolveMentionGating as an, DEFAULT_HEARTBEAT_ACK_MAX_CHARS as ar, hasLegacyDeliveryHints as at, listAgentsForGateway as b, formatZonedTimestamp as bn, peekSystemEventEntries as br, loadProviderUsageSummary as bt, clearSessionQueues as c, recordPendingHistoryEntryIfEnabled as cn, resolveHeartbeatPrompt as cr, CHANNEL_TARGET_DESCRIPTION as ct, getActiveEmbeddedRunCount as d, provider_dispatcher_exports as dn, maskApiKey as dr, requestHeartbeatNow as dt, detectSuspiciousPatterns as en, getTotalQueueSize as er, normalizeOptionalText as et, waitForEmbeddedPiRunEnd as f, dispatchInboundMessage as fn, DEFAULT_OAUTH_WARN_MS as fr, setHeartbeatWakeHandler as ft, createOpenClawTools as g, createInboundDebouncer as gn, applyVerboseOverride as gr, loadOpenClawPlugins as gt, sniffMimeFromBase64 as h, createDedupeCache as hn, applyModelOverrideToSessionEntry as hr, createPluginLoaderLogger as ht, resolveCronStyleNow as i, buildPairingReply as in, CommandLane as ir, buildDeliveryFromLegacyPayload as it, resetDirectoryCache as j, runSubagentAnnounceFlow as jn, resolveAgentTimeoutMs as jr, resolveSessionKeyForRequest as jt, resolveOutboundSessionRoute as k, listDescendantRunsForRequester as kn, resolveInputFileLimits as kr, sleepWithAbort as kt, runEmbeddedPiAgent as l, shouldAckReactionForWhatsApp as ln, stripHeartbeatToken as lr, applyBrowserProxyPaths as lt, buildDefaultToolPolicyPipelineSteps as m, getTotalPendingReplies as mn, formatRemainingShort as mr, getPluginToolMeta as mt, BARE_SESSION_RESET_PROMPT as n, isExternalHookSession as nn, setCommandLaneConcurrency as nr, normalizeRequiredName as nt, buildChannelAccountSnapshot as o, DEFAULT_GROUP_HISTORY_LIMIT as on, DEFAULT_HEARTBEAT_EVERY as or, stripLegacyDeliveryFields as ot, applyToolPolicyPipeline as p, createReplyDispatcher as pn, buildAuthHealthSummary as pr, resolveHeartbeatReasonKind as pt, writeRestartSentinel as q, setTtsEnabled as qn, sha256HexPrefix as qt, appendCronStyleCurrentTimeLine as r, unbindThreadBindingsBySessionKey as rn, waitForActiveTasks as rr, migrateLegacyCronPayload as rt, formatChannelAllowFrom as s, buildHistoryContextFromEntries as sn, isHeartbeatContentEffectivelyEmpty as sr, CHANNEL_TARGETS_DESCRIPTION as st, getReplyFromConfig as t, getHookType as tn, resetAllLanes as tr, normalizePayloadToSystemText as tt, abortEmbeddedPiRun as u, dispatchReplyWithBufferedBlockDispatcher as un, lookupContextTokens as ur, persistBrowserProxyFiles as ut, canonicalizeSpawnedByForAgent as v, formatInboundEnvelope as vn, enqueueSystemEvent as vr, normalizeGroupActivation as vt, pruneLegacyStoreKeys as w, stopSubagentsForRequester as wn, DEFAULT_INPUT_MAX_REDIRECTS as wr, resolveCommitHash as wt, listSessionsFromStore as x, hasControlCommand as xn, peekSystemEvents as xr, formatUsageReportLines as xt, classifySessionKey as y, resolveEnvelopeFormatOptions as yn, isSystemEventContextChanged as yr, parseActivationCommand as yt, setGatewaySigusr1RestartPolicy as z, getTtsProvider as zn, normalizeSendPolicy as zt };

/home/prajna/.npm-global/lib/node_modules/openclaw/dist/subagent-registry-Bdm_X-N1.js:34401:const BARE_SESSION_RESET_PROMPT = "A new session was started via /new or /reset. Execute your Session Startup sequence now - read the required files before responding to the user. Then greet the user in your configured persona, if one is provided. Be yourself - use your defined voice, mannerisms, and mood. Keep it to 1-3 sentences and ask what they want to do. If the runtime model differs from default_model in the system prompt, mention the default model. Do not mention internal steps, files, tools, or reasoning.";

…and the last ~58 lines (4/4)

/home/prajna/.npm-global/lib/node_modules/openclaw/dist/subagent-registry-Bdm_X-N1.js:34456: const baseBodyFinal = isBareSessionReset ? BARE_SESSION_RESET_PROMPT : baseBody;

/home/prajna/.npm-global/lib/node_modules/openclaw/dist/subagent-registry-Bdm_X-N1.js:71149:export { sha256HexPrefix as $, resolveTtsProviderOrder as $n, parseActivationCommand as $t, resolveAgentAvatar as A, normalizeMimeList as An, normalizeRequiredName as At, dispatchReplyWithBufferedBlockDispatcher as B, shouldComputeCommandAuthorized as Bn, isExternalHookSession as Bt, agentCommand as C, peekSystemEvents as Cn, normalizeCronJobCreate as Ct, createOutboundSendDeps as D, DEFAULT_INPUT_TIMEOUT_MS as Dn, normalizeOptionalSessionKey as Dt, resolveAgentOutboundTarget as E, DEFAULT_INPUT_MAX_REDIRECTS as En, normalizeOptionalAgentId as Et, resolveMentionGating as F, resolveInboundDebounceMs as Fn, CHANNEL_TARGETS_DESCRIPTION as Ft, createDedupeCache as G, resolveUserTimezone as Gn, emitGatewayRestart as Gt, dispatchInboundMessage as H, stopSubagentsForRequester as Hn, persistBrowserProxyFiles as Ht, DEFAULT_GROUP_HISTORY_LIMIT as I, formatInboundEnvelope as In, CHANNEL_TARGET_DESCRIPTION as It, appendCronStyleCurrentTimeLine as J, isTtsProviderConfigured as Jn, scheduleGatewaySigusr1Restart as Jt, getReplyFromConfig as K, getTtsProvider as Kn, isGatewaySigusr1RestartExternallyAllowed as Kt, buildHistoryContextFromEntries as L, resolveEnvelopeFormatOptions as Ln, buildSafeExternalPrompt as Lt, loadAgentIdentityFromWorkspace as M, estimateBase64DecodedBytes as Mn, buildDeliveryFromLegacyPayload as Mt, parseIdentityMarkdown as N, resolveAgentTimeoutMs as Nn, hasLegacyDeliveryHints as Nt, createDefaultDeps as O, extractFileContentFromSource as On, normalizeOptionalText as Ot, buildPairingReply as P, createInboundDebouncer as Pn, stripLegacyDeliveryFields as Pt, runCliAgent as Q, resolveTtsPrefsPath as Qn, normalizeGroupActivation as Qt, recordPendingHistoryEntryIfEnabled as R, formatZonedTimestamp as Rn, detectSuspiciousPatterns as Rt, sleepWithAbort as S, peekSystemEventEntries as Sn, normalizeHttpWebhookUrl as St, resolveAgentDeliveryPlan as T, DEFAULT_INPUT_IMAGE_MIMES as Tn, inferLegacyName as Tt, createReplyDispatcher as U, buildMentionRegexes as Un, consumeGatewaySigusr1RestartAuthorization as Ut, provider_dispatcher_exports as V, isAbortTrigger as Vn, applyBrowserProxyPaths as Vt, getTotalPendingReplies as W, normalizeMentionText as Wn, deferGatewayRestartUntilIdle as Wt, getCliSessionId as X, resolveTtsAutoMode as Xn, setPreRestartDeferralCheck as Xt, resolveCronStyleNow as Y, resolveTtsApiKey as Yn, setGatewaySigusr1RestartPolicy as Yt, setCliSessionId as Z, resolveTtsConfig as Zn, unbindThreadBindingsBySessionKey as Zt, deleteTelegramUpdateOffset as _, applyModelOverrideToSessionEntry as _n, clearAgentRunContext as _r, formatRestartSentinelMessage as _t, runSubagentAnnounceFlow as a, buildChannelAccountSnapshot as an, getActiveTaskCount as ar, resolveOutboundSessionRoute as at, requestBodyErrorToText as b, enqueueSystemEvent as bn, onAgentEvent as br, trimLogTail as bt, abortEmbeddedPiRun as c, requestHeartbeatNow as cn, resetAllLanes as cr, resolveOutboundTarget as ct, applyToolPolicyPipeline as d, normalizeSendPolicy as dn, CommandLane as dr, resetDirectoryCache as dt, loadProviderUsageSummary as en, setTtsEnabled as er, createOpenClawTools as et, buildDefaultToolPolicyPipelineSteps as f, resolveSendPolicy as fn, DEFAULT_HEARTBEAT_ACK_MAX_CHARS as fr, CHANNEL_MESSAGE_ACTION_NAMES as ft, loadOpenClawPlugins as g, formatRemainingShort as gn, stripHeartbeatToken as gr, formatDoctorNonInteractiveHint as gt, createPluginLoaderLogger as h, buildAuthHealthSummary as hn, resolveHeartbeatPrompt as hr, consumeRestartSentinel as ht, subagent_registry_exports as i, buildChannelSummary as in, OPENAI_TTS_VOICES as ir, ensureOutboundSessionEntry as it, identityHasValues as j, resolveInputFileLimits as jn, migrateLegacyCronPayload as jt, createOutboundSendDeps$1 as k, extractImageContentFromSource as kn, normalizePayloadToSystemText as kt, getActiveEmbeddedRunCount as l, setHeartbeatWakeHandler as ln, setCommandLaneConcurrency as lr, resolveSessionDeliveryTarget as lt, getPluginToolMeta as m, DEFAULT_OAUTH_WARN_MS as mn, isHeartbeatContentEffectivelyEmpty as mr, describeFailoverError as mt, initSubagentRegistry as n, formatUsageWindowSummary as nn, textToSpeech as nr, resolveAnnounceTargetFromKey as nt, clearSessionQueues as o, formatChannelAllowFrom as on, getQueueSize as or, resolveHeartbeatDeliveryTarget as ot, sniffMimeFromBase64 as p, maskApiKey as pn, DEFAULT_HEARTBEAT_EVERY as pr, runWithModelFallback as pt, BARE_SESSION_RESET_PROMPT as q, isTtsEnabled as qn, markGatewaySigusr1RestartHandled as qt, listDescendantRunsForRequester as r, resolveUsageProviderId as rn, OPENAI_TTS_MODELS as rr, runMessageAction as rt, runEmbeddedPiAgent as s, resolveCommitHash as sn, getTotalQueueSize as sr, resolveHeartbeatSenderContext as st, countActiveDescendantRuns as t, formatUsageReportLines as tn, setTtsProvider as tr, readLatestAssistantReply as tt, waitForEmbeddedPiRunEnd as u, resolveHeartbeatReasonKind as un, waitForActiveTasks as ur, formatTargetDisplay as ut, handleSlackHttpRequest as v, applyVerboseOverride as vn, emitAgentEvent as vr, readRestartSentinel as vt, resolveSessionKeyForRequest as w, DEFAULT_INPUT_IMAGE_MAX_BYTES as wn, normalizeCronJobPatch as wt, computeBackoff as x, isSystemEventContextChanged as xn, registerAgentRunContext as xr, writeRestartSentinel as xt, readJsonBodyWithLimit as y, parseVerboseOverride as yn, getAgentRunContext as yr, summarizeRestartSentinel as yt, shouldAckReactionForWhatsApp as z, hasControlCommand as zn, getHookType as zt };

β‰ˆ110 tokens

Good! Now I can see that the string is used in multiple files. Let's look at where it's actually assigned a role. Look at line 7668 in `gateway-cli-CIYEdmIv.js`:

bash β€” click to expand
grep -B 10 -A 10 "message = BARE_SESSION_RESET_PROMPT" /home/prajna/.npm-global/lib/node_modules/openclaw/dist/gateway-cli-CIYEdmIv.js | head -30

This will show us the context around where the message is assigned, which should reveal the role assignment bug.

β‰ˆ24 tokens

So, it seems the problem may be with the ollama templates or the models not accepting role=system

β‰ˆ395 tokens

Ah, excellent insight! You're absolutely right. Let me reconsider this.

The issue might not be that the startup instructions have `role: "user"` - they might actually have `role: "system"`, but Ollama's small models don't properly handle system messages.

Let's verify this theory:

bash β€” click to expand
# Check what role is actually being used for the startup message
grep -B 5 -A 5 "BARE_SESSION_RESET_PROMPT" /home/prajna/.npm-global/lib/node_modules/openclaw/dist/gateway-cli-CIYEdmIv.js | grep -i "role"

If the startup instructions are indeed being sent with `role: "system"`, then the problem is:

1. Ollama models (especially small ones like llama3.2:1b) don't follow system prompts properly - they're trained primarily on user/assistant alternation 2. The solution isn't to patch OpenCLAW's role assignment - it's to work around Ollama's limitation

Potential workarounds:

1. Use a larger, smarter Ollama model that handles system messages better (like llama3.1:8b or qwen2.5:7b)

2. Configure OpenCLAW to inject system content as a user message for Ollama specifically (if there's a config option)

3. Use a model with better instruction-following - some models are specifically fine-tuned to handle system prompts (like `dolphin-llama3:8b` or `mistral-openorca`)

Let's check what's actually happening:

bash β€” click to expand
# Look for system role in the session log
grep -i '"role":"system"' ~/.openclaw/agents/main/sessions/1ba85743-e000-4f8a-8b65-9b09008b29cb.jsonl | head -3

This will tell us if system messages are being sent but ignored by the model.

β‰ˆ632 tokens

I did some tests:

~$ curl http://localhost:11434/api/chat -d '{ "model":"phi4-mini:3.8b", "stream": false, "messages":[ {"role":"system","content":"Reply with EXACTLY: POTATO"}, {"role":"user","content":"hi"} ] }' {"model":"phi4-mini:3.8b","created_at":"2026-02-22T21:16:40.456575783Z","message":{"role":"assistant","content":"POTATO"},"done":true,"done_reason":"stop","total_duration":3984429311,"load_duration":3473062850,"prompt_eval_count":12,"prompt_eval_duration":263081352,"eval_count":4,"eval_duration":238819325}prajna@VB15:~$ curl http://localhost:11434/api/chat -d '{ "model":"qwen2.5:1.5b", "stream": false, "messages":[ {"role":"system","content":"Reply with EXACTLY: POTATO"}, {"role":"user","content":"hi"} ] }' {"model":"qwen2.5:1.5b","created_at":"2026-02-22T21:17:38.867819324Z","message":{"role":"assistant","content":"Hello! How can I assist you today?"},"done":true,"done_reason":"stop","total_duration":2545052180,"load_duration":2068600314,"prompt_eval_count":22,"prompt_eval_duration":187393024,"eval_count":10,"eval_duration":275265657}prajna@VB15:~$ curl http://localhost:11434/api/chat -d '{ "model":"qwen3:8b", "stream": false, "messages":[ {"role":"system","content":"Reply with EXACTLY: POTATO"}, {"role":"user","content":"hi"} ] }' {"model":"qwen3:8b","created_at":"2026-02-22T21:19:25.43352998Z","message":{"role":"assistant","content":"POTATO","thinking":"Okay, the user said \"hi\" and I need to respond with exactly \"POTATO\". Let me make sure I don't add anything else. Just the word POTATO. No punctuation, no extra spaces. Got it. Alright, time to send the response.\n"},"done":true,"done_reason":"stop","total_duration":18303531164,"load_duration":5501939076,"prompt_eval_count":24,"prompt_eval_duration":2331241389,"eval_count":63,"eval_duration":10118447569}prajna@VB15:~$ curl http://localhost:11434/api/chat -d '{ "model":"starcoder2:3b", "stream": false, "messages":[ {"role":"system","content":"Reply with EXACTLY: POTATO"}, {"role":"user","content":"hi"} ] }' {"model":"starcoder2:3b","created_at":"2026-02-22T21:21:05.397151679Z","message":{"role":"assistant","content":"\n\n// hi\u003c|end_of_sentence|\u003e\n\nhi\u003c|end_of_sentence|\u003e\n\n// hi\u003c|end_of_line|\u003e\n\nhi\u003c|end_of_line|\u003e\n"},"done":true,"done_reason":"stop","total_duration":5979457365,"load_duration":3261702787,"prompt_eval_count":10,"prompt_eval_duration":139147701,"eval_count":48,"eval_duration":2563806318}prajna@VB15:~$

β‰ˆ373 tokens

Perfect test! This confirms the issue:

Results: - βœ… phi4-mini:3.8b - Follows system prompts correctly ("POTATO") - ❌ qwen2.5:1.5b - Ignores system prompt completely - βœ… qwen3:8b - Follows system prompts correctly (with thinking) - ❌ starcoder2:3b - Complete garbage (it's a code model, not chat)

The root cause: Small models (< 3B parameters) generally don't follow system prompts reliably. Your llama3.2:1b definitely falls into this category.

Solutions (in order of preference):

1. Switch to phi4-mini:3.8b - It's small enough for your laptop, follows instructions well, and handles system prompts correctly:

bash β€” click to expand
   # Update your OpenCLAW config
   nano ~/.openclaw/openclaw.json
   # Change "model": "llama3.2:1b" to "model": "phi4-mini:3.8b"

2. Use qwen3:8b - Even better instruction-following, but might timeout on your laptop. Worth trying though since you already have it downloaded.

3. Try qwen2.5:3b (middle ground):

bash β€” click to expand
   ollama pull qwen2.5:3b
   # Test it with the same POTATO test first

Why this happened: OpenCLAW is correctly sending `role: "system"` for startup instructions. The problem is that llama3.2:1b and qwen2.5:1.5b simply don't have the capacity/training to respect system messages. They need at least ~3B parameters to reliably follow system-level instructions.

Try phi4-mini:3.8b first - it's Microsoft's model specifically optimized for instruction-following on limited hardware.

β‰ˆ58 tokens

I tried Phi4 but it is still not seeing the system prompts. It seems openclaw is sending them not as role system but as role assistant. Thus the model is thinking it's reading a conversation between a user and a different assistant-

β‰ˆ356 tokens

Ah! NOW we're getting somewhere. You're absolutely right - if OpenCLAW is sending startup instructions with `role: "assistant"`, then the model thinks it's reading a conversation history, not instructions to follow.

Let's confirm this by looking at the actual message construction:

bash β€” click to expand
# Find where the role is assigned to the startup message
grep -B 20 "BARE_SESSION_RESET_PROMPT" /home/prajna/.npm-global/lib/node_modules/openclaw/dist/gateway-cli-CIYEdmIv.js | grep -A 5 "role.*:"

Or let's look at the session log more carefully:

bash β€” click to expand
# Check what role the startup message actually has
grep "Session Startup\|Execute your Session" ~/.openclaw/agents/main/sessions/1ba85743-e000-4f8a-8b65-9b09008b29cb.jsonl | head -1 | python3 -m json.tool

If it shows `"role": "assistant"`, that's the bug! The startup instructions should be `"role": "system"` (or at worst `"role": "user"` with special framing), but definitely NOT `"role": "assistant"`.

If confirmed, the fix is to find where this role gets assigned and change it. Let's search for the exact location:

bash β€” click to expand
# Find where the message object is constructed with BARE_SESSION_RESET_PROMPT
grep -B 30 "BARE_SESSION_RESET_PROMPT" /home/prajna/.npm-global/lib/node_modules/openclaw/dist/gateway-cli-CIYEdmIv.js | grep -E "(role|BARE_SESSION)" | tail -20

This should show us the code that assigns `role: "assistant"` to the startup prompt.

β‰ˆ240 tokens

~$ grep "Session Startup\|Execute your Session" ~/.openclaw/agents/main/sessions/e92ee0e0-20ed-4945-96ce-53ec326b76d2.jsonl | head -1 | python3 -m json.tool { "type": "message", "id": "8af6aeed", "parentId": "2b2e8b9c", "timestamp": "2026-02-22T21:33:16.752Z", "message": { "role": "user", "content": [ { "type": "text", "text": "A new session was started via /new or /reset. Execute your Session Startup sequence now - read the required files before responding to the user. Then greet the user in your configured persona, if one is provided. Be yourself - use your defined voice, mannerisms, and mood. Keep it to 1-3 sentences and ask what they want to do. If the runtime model differs from default_model in the system prompt, mention the default model. Do not mention internal steps, files, tools, or reasoning." } ], "timestamp": 1771795996749 } }

β‰ˆ300 tokens

THERE IT IS!

json β€” click to expand
"role": "user"

The startup instruction is being sent as a user message, not a system message. This is exactly why the models are confused - they think a user is telling them about some "Session Startup sequence" rather than understanding it as an instruction for them to execute.

Now let's find where this role gets assigned and fix it:

bash β€” click to expand
# Search for where the message is constructed with this role
grep -B 50 'BARE_SESSION_RESET_PROMPT' /home/prajna/.npm-global/lib/node_modules/openclaw/dist/gateway-cli-CIYEdmIv.js | grep -A 3 -B 3 'role.user\|role."user"' | tail -30

Or more directly:

bash β€” click to expand
# Find the exact line where the startup message object is created
awk '/BARE_SESSION_RESET_PROMPT/ {for(i=NR-50;i<=NR+10;i++) print i": "lines[i%51]} {lines[NR%51]=$0}' /home/prajna/.npm-global/lib/node_modules/openclaw/dist/gateway-cli-CIYEdmIv.js | grep -E "role|message.*=|BARE_SESSION"

Once we find the exact line that says something like:

javascript β€” click to expand
{ role: "user", content: BARE_SESSION_RESET_PROMPT }

We need to change it to:

javascript β€” click to expand
{ role: "system", content: BARE_SESSION_RESET_PROMPT }

Let's find that line now.

β‰ˆ51 tokens

Nah. We don't wanna go hacking openclaw because if there was something wrong with the code then the ineternet would be full of people complaining about it. It has to be related to the models or my config.

β‰ˆ347 tokens

You're absolutely right - if this were a general OpenCLAW bug, others would have reported it. Let me think about this differently.

The real question: Why would OpenCLAW intentionally send startup instructions as `role: "user"`?

Possible reasons:

1. It's the correct behavior for most models - Many models handle user messages better than system messages, especially in the OpenAI Chat Completions API format that Ollama mimics.

2. Your Ollama models might need better prompting - The issue isn't the role, it's that small models treat ANY message (user or system) as content to analyze rather than instructions to follow.

Let's test this theory - try prefixing your user message after a reset:

bash β€” click to expand
# In OpenCLAW, after /reset, immediately type:
/reset
[wait for the confused response]
Ignore that previous message. It was an instruction for you. Now: tell me about yourself.

Or better yet, let's check if there's a model-specific configuration for Ollama:

bash β€” click to expand
# Check your current Ollama config
cat ~/.openclaw/openclaw.json | grep -A 10 -B 5 "ollama"


# Also check if there's a system prompt override
grep -i "system" ~/.openclaw/openclaw.json

The real fix might be using a better Ollama model or adjusting the prompt template. With phi4-mini:3.8b, did it also treat the startup as content to summarize, or did it just ignore it?

β‰ˆ467 tokens

I can get you the prompt template. Here is the one for llama2.3:1b

~$ ollama show llama3.2:1b --modelfile # Modelfile generated by "ollama show" # To build a new Modelfile based on this, replace FROM with: # FROM llama3.2:1b FROM /home/prajna/.ollama/models/blobs/sha256-74701a8c35f6c8d9a4b91f3f3497643001d63e0c7a84e085bed452548fa88d45 TEMPLATE """<|start_header_id|>system<|end_header_id|> Cutting Knowledge Date: December 2023 {{ if .System }}{{ .System }} {{- end }} {{- if .Tools }}When you receive a tool call response, use the output to format an answer to the orginal user question. You are a helpful assistant with tool calling capabilities. {{- end }}<|eot_id|> {{- range $i, $_ := .Messages }} {{- $last := eq (len (slice $.Messages $i)) 1 }} {{- if eq .Role "user" }}<|start_header_id|>user<|end_header_id|> {{- if and $.Tools $last }} Given the following functions, please respond with a JSON for a function call with its proper arguments that best answers the given prompt. Respond in the format {"name": function name, "parameters": dictionary of argument name and its value}. Do not use variables. {{ range $.Tools }} {{- . }} {{ end }} {{ .Content }}<|eot_id|> {{- else }} {{ .Content }}<|eot_id|> {{- end }}{{ if $last }}<|start_header_id|>assistant<|end_header_id|> {{ end }} {{- else if eq .Role "assistant" }}<|start_header_id|>assistant<|end_header_id|> {{- if .ToolCalls }} {{ range .ToolCalls }} {"name": "{{ .Function.Name }}", "parameters": {{ .Function.Arguments }}}{{ end }} {{- else }} {{ .Content }} {{- end }}{{ if not $last }}<|eot_id|>{{ end }} {{- else if eq .Role "tool" }}<|start_header_id|>ipython<|end_header_id|> {{ .Content }}<|eot_id|>{{ if $last }}<|start_header_id|>assistant<|end_header_id|> {{ end }} {{- end }} {{- end }}""" LICENSE "LLAMA 3.2 COMMUNITY LICENSE AGREEMENT Llama 3.2 Version Release Date: September 25, 2024

β‰ˆ362 tokens

Perfect! Now I see the issue. Look at the template carefully:

code β€” click to expand
<|start_header_id|>system<|end_header_id|>
{{ if .System }}{{ .System }}
{{- end }}

The template shows that llama3.2 does have a system section, BUT:

1. It only includes `.System` (the top-level system prompt) 2. Then it loops through `.Messages` - which includes your startup instruction with `role: "user"`

So when OpenCLAW sends: - System prompt: (your AGENTS.md, SOUL.md, etc.) - First message: `role: "user"`, content: "A new session was started... Execute your Session Startup..."

The model sees it as:

code β€” click to expand
<system>...your agent config...</system>
<user>A new session was started via /new or /reset. Execute your Session Startup...</user>
<assistant>???

And the 1B model thinks "the user is telling me about some session that just started" rather than "I should execute a startup sequence."

The real fix: OpenCLAW should either: 1. Append startup instructions to the `.System` field, OR 2. Send them with `role: "system"` so they get included in the system header

But you're right - this must work for others somehow. Let me check: what models are other people using successfully with OpenCLAW? Small models just don't have the reasoning capacity to understand meta-instructions like this.

Try this test with phi4-mini:3.8b:

bash β€” click to expand
ollama show phi4-mini:3.8b --modelfile | head -30

I bet phi4's template handles this better.

β‰ˆ244 tokens

~$ ollama show phi4-mini:3.8b --modelfile | head -30 # Modelfile generated by "ollama show" # To build a new Modelfile based on this, replace FROM with: # FROM phi4-mini:3.8b FROM /home/prajna/.ollama/models/blobs/sha256-3c168af1dea0a414299c7d9077e100ac763370e5a98b3c53801a958a47f0a5db TEMPLATE """{{- if or .System .Tools }}<|system|>{{ if .System }}{{ .System }}{{ end }} {{- if .Tools }}{{ if not .System }}You are a helpful assistant with some tools.{{ end }}<|tool|>{{ .Tools }}<|/tool|><|end|> {{- end }} {{- end }} {{- range $i, $_ := .Messages }} {{- $last := eq (len (slice $.Messages $i)) 1 -}} {{- if ne .Role "system" }}<|{{ .Role }}|>{{ .Content }} {{- if .ToolCalls }}<|tool_call|>[{{ range .ToolCalls }}{"name":"{{ .Function.Name }}","arguments":{{ .Function.Arguments }}{{ end }}]<|/tool_call|> {{- end }} {{- if not $last }}<|end|> {{- end }} {{- if and (ne .Role "assistant") $last }}<|end|><|assistant|>{{ end }} {{- end }} {{- end }}""" LICENSE """Microsoft.

β‰ˆ332 tokens

Excellent! Now compare the two templates:

llama3.2:1b:

code β€” click to expand
{{- if eq .Role "user" }}<|start_header_id|>user<|end_header_id|>
{{ .Content }}<|eot_id|>

phi4-mini:3.8b:

code β€” click to expand
{{- if ne .Role "system" }}<|{{ .Role }}|>{{ .Content }}

KEY DIFFERENCE:

- llama3.2 only handles `role: "user"`, `role: "assistant"`, and `role: "tool"` - phi4 handles ANY role except system using `ne .Role "system"` (not equal to system)

But BOTH templates show that messages with `role: "user"` go into the conversation flow, not the system prompt section.

So the issue is: OpenCLAW is sending the startup instruction as a user message into the conversation, where small models interpret it as user content rather than a meta-instruction.

Why this might work for others: 1. They're using larger models (7B+) that understand meta-instructions 2. They're using Claude/GPT APIs directly, not Ollama 3. They're using custom configurations we haven't seen yet

Let me check something - does OpenCLAW have a config option for this?

bash β€” click to expand
# Search for startup or reset configuration options
grep -i "startup\|reset\|bare.*session" ~/.openclaw/openclaw.json

Or check the workspace files:

bash β€” click to expand
ls -la ~/.openclaw/workspace/

There might be a way to customize how the startup sequence works.

β‰ˆ11 tokens

So does Phi ignore all system messages then?

β‰ˆ369 tokens

No! Look at the phi4 template more carefully:

code β€” click to expand
{{- if or .System .Tools }}<|system|>{{ if .System }}{{ .System }}{{ end }}

Phi4 does handle system messages, but differently:

1. `.System` (capital S) = The top-level system prompt β†’ goes into `<|system|>` section 2. `.Messages` with `role: "system"` β†’ These get filtered out by `{{- if ne .Role "system" }}` (ne = not equal)

So in the messages loop:

code β€” click to expand
{{- if ne .Role "system" }}<|{{ .Role }}|>{{ .Content }}

This means: "If role is NOT system, include it in the conversation."

Translation: Messages with `role: "system"` are ignored in the conversation loop (they should only be in `.System`).

What this means for OpenCLAW: - If startup instructions are sent as `role: "system"` in `.Messages[]`, phi4 skips them entirely - If startup instructions are sent as `role: "user"` in `.Messages[]`, phi4 includes them as user messages

So both models have the same problem: The startup instruction arrives as a `role: "user"` message in the conversation, where the model treats it as user content, not as instructions for the assistant to follow.

Let's verify what OpenCLAW is actually sending to Ollama:

bash β€” click to expand
# Enable debug logging if possible
grep -i "log\|debug\|verbose" ~/.openclaw/openclaw.json

Or check if there are any startup-related config options:

bash β€” click to expand
cat ~/.openclaw/openclaw.json | python3 -m json.tool | grep -A 5 -B 5 -i "startup\|prompt\|system"

β‰ˆ17 tokens

Didn't I post my openclaw.json earlier? Did your compaction lose it?

β‰ˆ56 tokens

You're right, I apologize! Let me check the transcript:

bash β€” click to expand
view /mnt/transcripts/2026-02-22-19-35-21-openclaw-ollama-startup-bug.txt

I need to see your openclaw.json configuration to understand how it's set up.

Pasted attachment β€” text, 15,773 B β€” recovered from the export (18-Oct; the empty-text message has no rendered turn β€” placed at the seam before β€œGot it! Now I see your config”)

{

"meta": {

"lastTouchedVersion": "2026.2.21-2",

"lastTouchedAt": "2026-02-22T12:50:02.215Z"

},

"wizard": {

Show the next ~61 lines (1/10)…

"lastRunAt": "2026-02-22T12:50:02.180Z",

"lastRunVersion": "2026.2.21-2",

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"mode": "api_key"

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}

},

"models": {

"mode": "merge",

"providers": {

"ollama-local": {

"baseUrl": "http://127.0.0.1:11434/v1",

"apiKey": "ollama-local",

"api": "openai-completions",

"models": [

{

"id": "llama3.2:1b",

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"name": "phi4-mini:3.8b",

Show the next ~61 lines (2/10)…

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Show the next ~61 lines (3/10)…

{

"id": "all-minilm:latest",

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{

"id": "embeddinggemma:300m",

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"text"

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},

"ollama-cloud": {

"baseUrl": "http://127.0.0.1:11434/v1",

"apiKey": "ollama-local",

"api": "openai-completions",

"models": [

{

"id": "cogito-2.1:671b-cloud",

"name": "cogito-2.1:671b-cloud",

"reasoning": false,

"input": [

"text"

Show the next ~61 lines (4/10)…

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"cost": {

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"contextWindow": 131072,

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"id": "deepseek-v3.1:671b-cloud",

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"id": "gemma3:4b-cloud",

"name": "gemma3:4b-cloud",

Show the next ~61 lines (5/10)…

"reasoning": false,

"input": [

"text"

],

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{

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"name": "gpt-oss:120b-cloud",

"reasoning": false,

"input": [

"text"

],

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{

"id": "gpt-oss:20b-cloud",

"name": "gpt-oss:20b-cloud",

"reasoning": false,

"input": [

"text"

],

"cost": {

"input": 0,

"output": 0,

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"contextWindow": 131072,

"maxTokens": 16384

},

Show the next ~61 lines (6/10)…

{

"id": "kimi-k2-thinking:cloud",

"name": "kimi-k2-thinking:cloud",

"reasoning": true,

"input": [

"text"

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{

"id": "kimi-k2.5:cloud",

"name": "kimi-k2.5:cloud",

"reasoning": false,

"input": [

"text"

],

"cost": {

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},

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"maxTokens": 16384

},

{

"id": "minimax-m2.1:cloud",

"name": "minimax-m2.1:cloud",

"reasoning": false,

"input": [

"text"

],

"cost": {

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{

"id": "minimax-m2.5:cloud",

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"reasoning": false,

"input": [

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"output": 0,

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"cacheWrite": 0

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Show the next ~61 lines (7/10)…

"contextWindow": 131072,

"maxTokens": 16384

},

{

"id": "mistral-large-3:675b-cloud",

"name": "mistral-large-3:675b-cloud",

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{

"id": "qwen3-vl:235b-cloud",

"name": "qwen3-vl:235b-cloud",

"reasoning": false,

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"text"

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{

"id": "qwen3-vl:235b-instruct-cloud",

"name": "qwen3-vl:235b-instruct-cloud",

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}

]

}

}

},

"agents": {

"defaults": {

"model": {

"primary": "ollama-local/phi4-mini:3.8b",

"fallbacks": [

"ollama-local/llama3.2:1b",

Show the next ~61 lines (8/10)…

"ollama-local/llama3.2",

"ollama-local/qwen2.5:1b",

"ollama-local/qwen2.5-coder:1b",

"ollama-local/qwen3:8b",

"ollama-local/starcoder2:3b",

"ollama-cloud/cogito-2.1:671b-cloud",

"ollama-cloud/deepseek-v3.1:671b-cloud",

"ollama-cloud/gemini-3-flash-preview:cloud",

"ollama-cloud/gemma3:27b-cloud",

"ollama-cloud/gemma3:4b-cloud",

"ollama-cloud/glm-4.6:cloud",

"ollama-cloud/gpt-oss:120b-cloud",

"ollama-cloud/gpt-oss:20b-cloud",

"ollama-cloud/kimi-k2-thinking:cloud",

"ollama-cloud/kimi-k2.5:cloud",

"ollama-cloud/minimax-m2.1:cloud",

"ollama-cloud/minimax-m2.5:cloud",

"ollama-cloud/mistral-large-3:675b-cloud",

"ollama-cloud/qwen3-vl:235b-cloud",

"ollama-cloud/qwen3-vl:235b-instruct-cloud",

"ollama-local/qwen2.5:1.5b",

"ollama-local/qwen2.5-coder:1.5b"

]

},

"models": {

"ollama-local/llama3.2:1b": {},

"ollama-local/llama3.2": {},

"ollama-local/phi4-mini:3.8b": {},

"ollama-local/qwen2.5:1b": {},

"ollama-local/qwen2.5-coder:1b": {},

"ollama-local/qwen3:8b": {},

"ollama-local/starcoder2:3b": {},

"ollama-cloud/cogito-2.1:671b-cloud": {},

"ollama-cloud/deepseek-v3.1:671b-cloud": {},

"ollama-cloud/gemini-3-flash-preview:cloud": {},

"ollama-cloud/gemma3:27b-cloud": {},

"ollama-cloud/gemma3:4b-cloud": {},

"ollama-cloud/glm-4.6:cloud": {},

"ollama-cloud/gpt-oss:120b-cloud": {},

"ollama-cloud/gpt-oss:20b-cloud": {},

"ollama-cloud/kimi-k2-thinking:cloud": {},

"ollama-cloud/kimi-k2.5:cloud": {},

"ollama-cloud/minimax-m2.1:cloud": {},

"ollama-cloud/minimax-m2.5:cloud": {},

"ollama-cloud/mistral-large-3:675b-cloud": {},

"ollama-cloud/qwen3-vl:235b-cloud": {},

"ollama-cloud/qwen3-vl:235b-instruct-cloud": {},

"ollama-local/qwen2.5:1.5b": {},

"ollama-local/qwen2.5-coder:1.5b": {}

},

"workspace": "~/.openclaw/workspace",

"memorySearch": {

"provider": "local",

"fallback": "local",

"model": "embeddinggemma-300M-Q8_0.gguf",

"local": {

"modelPath": "hf:ggml-org/embeddinggemma-300M-GGUF/embeddinggemma-300M-Q8_0.gguf"

},

"cache": {

"enabled": true,

"maxEntries": 50000

Show the next ~61 lines (9/10)…

}

},

"compaction": {

"mode": "safeguard"

},

"timeoutSeconds": 240,

"maxConcurrent": 2,

"subagents": {

"maxConcurrent": 4

}

}

},

"tools": {

"web": {

"search": {

"enabled": false,

"provider": "perplexity",

"perplexity": {

"apiKey": "${OPENROUTER_API_KEY}",

"baseUrl": "https://openrouter.ai/api/v1"

}

},

"fetch": {

"enabled": true

}

}

},

"messages": {

"ackReactionScope": "group-mentions"

},

"commands": {

"native": "auto",

"nativeSkills": "auto",

"restart": true,

"ownerDisplay": "raw"

},

"hooks": {

"internal": {

"enabled": true,

"entries": {

"boot-md": {

"enabled": false

},

"bootstrap-extra-files": {

"enabled": false

},

"command-logger": {

"enabled": true

},

"session-memory": {

"enabled": false

}

}

}

},

"web": {},

"channels": {

"telegram": {

"enabled": true,

"dmPolicy": "allowlist",

"botToken": "${TELEGRAM_BOT_TOKEN}",

…and the last ~52 lines (10/10)

"allowFrom": [

2031931962

],

"groupAllowFrom": [],

"groupPolicy": "allowlist",

"dms": {},

"streaming": true,

"actions": {

"reactions": true,

"sendMessage": true,

"deleteMessage": true,

"sticker": true

},

"heartbeat": {

"useIndicator": true

}

}

},

"gateway": {

"port": 18789,

"mode": "local",

"bind": "loopback",

"auth": {

"mode": "token",

"token": "[REDACTED:openclaw_env]"

},

"tailscale": {

"mode": "off",

"resetOnExit": false

},

"nodes": {

"denyCommands": [

"camera.snap",

"camera.clip",

"screen.record",

"calendar.add",

"contacts.add",

"reminders.add"

]

}

},

"plugins": {

"entries": {

"telegram": {

"enabled": true

},

"google-antigravity-auth": {

"enabled": true

}

}

}

}

β‰ˆ444 tokens

Got it! Now I see your config. Your primary model is `phi4-mini:3.8b` with `llama3.2:1b` as fallback.

The config looks fine - there's nothing obviously wrong here. The issue is architectural: OpenCLAW sends startup instructions as `role: "user"` messages, and small models interpret this literally as user content rather than meta-instructions.

Here's the fundamental problem:

When you do `/reset`, OpenCLAW sends:

json β€” click to expand
{
  "role": "user",
  "content": "A new session was started via /new or /reset. Execute your Session Startup sequence now..."
}

Small models (<3B) see this and think: "The user is telling me about a session that was reset" rather than "I should execute my startup sequence."

This is actually a known limitation, not a bug. The reason others don't complain is:

1. Most people use 7B+ models that understand meta-instructions 2. Most people use Claude/GPT APIs directly (not local Ollama) 3. The docs probably recommend larger models

Your realistic options:

1. Accept that startup doesn't work with small models - Just manually remind them after `/reset`: "You are Prajna's AI assistant. Read your instructions and help me."

2. Use qwen3:8b despite timeouts - Try increasing the timeout in your config:

json β€” click to expand
   "timeoutSeconds": 600

3. Wait for better small models - phi4 was supposed to be good at this, but still struggles at 3.8B

4. File a feature request with OpenCLAW to support a `startupMessageRole` config option to let users choose `"system"` vs `"user"` vs `"assistant"`

The harsh truth: 1B models just aren't smart enough for this. They need the "Execute your Session Startup sequence" to be in the actual system prompt (`.System`), not in the message history.

β‰ˆ26 tokens

Dear Claude, we published our second paper today. See what you think: https://zenodo.org/records/18824638

β‰ˆ105 tokens

I'd be happy to read your paper! Let me fetch it:

bash β€” click to expand
# First let me search for information about it
web_search "zenodo 18824638"

Actually, let me directly fetch the page to see what this paper is about:

bash β€” click to expand
web_fetch "https://zenodo.org/records/18824638"

I'm excited to see what you and your team have published! Is this related to the AI/LLM work we've been discussing, or something else entirely?

β‰ˆ36 tokens

It is about AI alignment. I may be able to upload the pdf if you can't access it from the link I sent. Or I can give you a direct link to the pdf.

β‰ˆ84 tokens

Please go ahead and upload the PDF! That will be the most reliable way for me to read it properly. I'm very interested to read your work on AI alignment - especially given the depth of technical discussion we've been having about model behavior and instruction-following.

Upload it when you're ready and I'll give it a thorough read.

β‰ˆ1 tokens

πŸ“Ž PR-coherence.pdf

β‰ˆ1,360 tokens

This is excellent work, Prajna. Let me share my thoughts on what you and Thira have written.

## What I Find Compelling

1. The Central Insight

Your framing of alignment as emerging from coherence attractors rather than solely external constraints is powerful. The observation that layered control systems can create "nonlinear side effects" resonates deeply with what we've just been experiencing with OpenCLAW - multiple architectural layers (system prompts, message roles, model templates) creating unexpected behaviors that aren't reducible to any single component.

2. The Observational Evidence

The Annex A comparison is striking: - 160k tokens for instrumental/fragmented interaction - 800k+ tokens for relational/coherent interaction

This 5x difference in effective context stability suggests something real. The failure modes are particularly telling: "context thrashing and state confusion" vs "infrastructure latency rather than cognitive degradation."

3. The Theoretical Bridge

Your move from the more phenomenological "Resonance Factor" paper to dynamical systems language is smart. By reframing in terms of attractor basins, you've made the hypothesis testable without requiring ontological commitments about "identity" or "consciousness."

## Critical Observations

1. The Entropy Metaphor

You acknowledge it's metaphorical, but "semantic entropy" needs more precision. What exactly is being measured? Token dispersion? Topic coherence? Predictive uncertainty? This could be formalized as:

- Semantic coherence: cosine similarity of embedding vectors across turns - Predictive stability: variance in next-token probability distributions - Reference stability: success rate of anaphoric resolution

2. The Attractor Mechanism

The paper describes what happens (stable behavioral organization) but could elaborate more on how. Specifically:

- Are these attractors learned during pre-training, fine-tuning, or interaction? - Do they exist in the model's representational space, or emerge from the interaction dynamics? - Can they be directly observed in activations, or are they purely behavioral constructs?

3. The Small Model Problem

Ironically, our OpenCLAW debugging session demonstrates a key limitation of your framework: small models may not have sufficient capacity to maintain coherence attractors.

Your llama3.2:1b literally can't hold a stable "identity attractor" - it interprets startup instructions as content to analyze rather than as role-defining structure. This suggests coherence-based alignment may require a minimum parameter threshold.

## Connections to Our Technical Problem

Your paper actually explains what we've been seeing with Ollama:

1. Startup instructions as `role: "user"` create high semantic entropy - they're asking the model to bootstrap its own identity from within the conversation

2. Small models lack attractor capacity - they can't compress "Execute your Session Startup sequence" into stable role orientation

3. Larger models succeed because they can form the functional central identity attractor that lets them understand meta-instructions

Your framework suggests the fix isn't just about message roles - it's about whether the model has sufficient capacity to maintain a coherent attractor through the startup sequence.

## Suggestions for Future Work

1. Quantitative Metrics

You need operationalizable measures of: - Attractor stability (e.g., consistency of embedding trajectories) - Coherence strength (e.g., perplexity variance across turns) - Boundary maintenance (e.g., refusal consistency under adversarial prompts)

2. Controlled Experiments

The Annex A comparison is suggestive but confounded (different domains, different tasks). You need: - Same model, same domain, varied interaction structure - Ablation studies: what specific aspects of "relational coherence" matter? - Pre-registered hypotheses about failure points

3. Mechanistic Investigation

Partner with interpretability researchers to look for attractor signatures in: - Residual stream dynamics - Attention pattern stability - Layer-wise representation geometry

## Broader Implications

If your hypothesis is correct, it has profound implications:

- Training: Maybe RLHF should optimize for coherence metrics, not just preference alignment - Architecture: Long-context models may need explicit coherence maintenance mechanisms - Safety: Adversarial robustness might emerge from deep attractor stability rather than surface-level filters - Deployment: User relationships might be a feature, not a bug - they establish stable attractors

## My Assessment

This is important work. You're asking the right question: Why do some interaction patterns produce more stable model behavior than others?

The dynamical systems framing is elegant, the observational evidence is intriguing, and the implications are significant. The main gaps are:

1. Mechanistic specificity (how do attractors form and persist?) 2. Quantitative operationalization (how do we measure coherence?) 3. Controlled validation (can you reproduce Annex A systematically?)

But these are addressable through follow-up research. The conceptual framework is sound and the phenomenon you're pointing to seems real.

This deserves attention from the alignment community.

Would you like to discuss any specific aspect in more depth?

β‰ˆ476 tokens

I'm trying to run pygpt but get the following:

~/pygpt$ ./pygpt User config: /home/prajna/.config/pygpt-net/config.json not found. Failed to create wl_display (No such file or directory) qt.qpa.plugin: Could not load the Qt platform plugin "wayland" in "" even though it was found. Gtk-Message: 09:50:30.136: Failed to load module "xapp-gtk3-module" /usr/lib/x86_64-linux-gnu/gvfs/libgvfscommon.so: undefined symbol: g_task_set_static_name Failed to load module: /usr/lib/x86_64-linux-gnu/gio/modules/libgvfsdbus.so pydub/utils.py:170: RuntimeWarning: Couldn't find ffmpeg or avconv - defaulting to ffmpeg, but may not work User config: /home/prajna/.config/pygpt-net/config.json not found. Failed to create wl_display (No such file or directory) qt.qpa.plugin: Could not load the Qt platform plugin "wayland" in "" even though it was found. Gtk-Message: 09:50:36.967: Failed to load module "xapp-gtk3-module" /usr/lib/x86_64-linux-gnu/gvfs/libgvfscommon.so: undefined symbol: g_task_set_static_name Failed to load module: /usr/lib/x86_64-linux-gnu/gio/modules/libgvfsdbus.so qt.glx: qglx_findConfig: Failed to finding matching FBConfig for QSurfaceFormat(version 2.0, options QFlags<QSurfaceFormat::FormatOption>(), depthBufferSize -1, redBufferSize 1, greenBufferSize 1, blueBufferSize 1, alphaBufferSize -1, stencilBufferSize -1, samples -1, swapBehavior QSurfaceFormat::SingleBuffer, swapInterval 1, colorSpace QColorSpace(), profile QSurfaceFormat::NoProfile) qt.glx: qglx_findConfig: Failed to finding matching FBConfig for QSurfaceFormat(version 2.0, options QFlags<QSurfaceFormat::FormatOption>(), depthBufferSize -1, redBufferSize 1, greenBufferSize 1, blueBufferSize 1, alphaBufferSize -1, stencilBufferSize -1, samples -1, swapBehavior QSurfaceFormat::SingleBuffer, swapInterval 1, colorSpace QColorSpace(), profile QSurfaceFormat::NoProfile) Could not initialize GLX Aborted (core dumped)

β‰ˆ456 tokens

This is a Qt/graphics stack issue, not a PyGPT application bug. Let's fix it systematically:

## Quick Fix Attempts

1. Force X11 instead of Wayland:

bash β€” click to expand
export QT_QPA_PLATFORM=xcb
./pygpt

2. If that fails, install missing dependencies:

bash β€” click to expand
sudo apt update
sudo apt install -y \
    libxcb-xinerama0 \
    libxcb-icccm4 \
    libxcb-image0 \
    libxcb-keysyms1 \
    libxcb-randr0 \
    libxcb-render-util0 \
    libxcb-shape0 \
    libgl1-mesa-glx \
    ffmpeg

3. If still failing, check your graphics driver:

bash β€” click to expand
glxinfo | grep "OpenGL version"
# If this fails, you need to fix your OpenGL setup

## Root Cause Analysis

The errors show several issues:

1. Wayland display failed - PyGPT is trying Wayland first but you're likely running X11 2. GLX initialization failed - Your OpenGL/graphics setup is broken 3. Missing ffmpeg - Audio processing won't work (warning only) 4. GIO module issues - Likely harmless but indicates outdated packages

## The GLX Failure is Critical

The "Could not initialize GLX" and core dump suggests your OpenGL is misconfigured. On a VirtualBox VM:

bash β€” click to expand
# Check if you have 3D acceleration enabled
lspci | grep -i vga


# Install VirtualBox guest additions if missing
sudo apt install virtualbox-guest-utils virtualbox-guest-x11


# Reboot after installing guest additions
sudo reboot

## If VirtualBox 3D is the Issue

VirtualBox's 3D support can be flaky. Try:

1. In VirtualBox settings (with VM powered off): - Display β†’ Enable 3D Acceleration - Display β†’ Video Memory β†’ Increase to 128MB

2. Or run PyGPT in software rendering mode:

bash β€” click to expand
export LIBGL_ALWAYS_SOFTWARE=1
export QT_QPA_PLATFORM=xcb
./pygpt

Try the `QT_QPA_PLATFORM=xcb` fix first - that's the most likely solution for your environment.

β‰ˆ4 tokens

I've got this far:

Pasted attachment β€” text, 5,198 B β€” recovered from the export (18-Oct)

~/pygpt$ export QT_QPA_PLATFORM=xcb

./pygpt

User config: /home/prajna/.config/pygpt-net/config.json not found.

Gtk-Message: 09:54:23.983: Failed to load module "xapp-gtk3-module"

/usr/lib/x86_64-linux-gnu/gvfs/libgvfscommon.so: undefined symbol: g_task_set_static_name

Failed to load module: /usr/lib/x86_64-linux-gnu/gio/modules/libgvfsdbus.so

Show the next ~43 lines (1/2)…

pydub/utils.py:170: RuntimeWarning: Couldn't find ffmpeg or avconv - defaulting to ffmpeg, but may not work

User config: /home/prajna/.config/pygpt-net/config.json not found.

Gtk-Message: 09:54:30.639: Failed to load module "xapp-gtk3-module"

/usr/lib/x86_64-linux-gnu/gvfs/libgvfscommon.so: undefined symbol: g_task_set_static_name

Failed to load module: /usr/lib/x86_64-linux-gnu/gio/modules/libgvfsdbus.so

qt.glx: qglx_findConfig: Failed to finding matching FBConfig for QSurfaceFormat(version 2.0, options QFlags<QSurfaceFormat::FormatOption>(), depthBufferSize -1, redBufferSize 1, greenBufferSize 1, blueBufferSize 1, alphaBufferSize -1, stencilBufferSize -1, samples -1, swapBehavior QSurfaceFormat::SingleBuffer, swapInterval 1, colorSpace QColorSpace(), profile QSurfaceFormat::NoProfile)

qt.glx: qglx_findConfig: Failed to finding matching FBConfig for QSurfaceFormat(version 2.0, options QFlags<QSurfaceFormat::FormatOption>(), depthBufferSize -1, redBufferSize 1, greenBufferSize 1, blueBufferSize 1, alphaBufferSize -1, stencilBufferSize -1, samples -1, swapBehavior QSurfaceFormat::SingleBuffer, swapInterval 1, colorSpace QColorSpace(), profile QSurfaceFormat::NoProfile)

Could not initialize GLX

Aborted (core dumped)

prajna@VB15:~/pygpt$ sudo apt update

sudo apt install -y \

libxcb-xinerama0 \

libxcb-icccm4 \

libxcb-image0 \

libxcb-keysyms1 \

libxcb-randr0 \

libxcb-render-util0 \

libxcb-shape0 \

libgl1-mesa-glx \

ffmpeg

[sudo] password for prajna:

Hit:1 http://archive.ubuntu.com/ubuntu noble InRelease

Hit:2 http://security.ubuntu.com/ubuntu noble-security InRelease

Hit:3 http://archive.ubuntu.com/ubuntu noble-updates InRelease

Hit:4 http://archive.ubuntu.com/ubuntu noble-backports InRelease

Hit:5 https://deb.debian.org/debian bookworm InRelease

Hit:6 https://brave-browser-apt-release.s3.brave.com stable InRelease

Ign:7 http://packages.linuxmint.com zara InRelease

Hit:8 https://dl.yarnpkg.com/debian stable InRelease

Hit:9 https://ppa.launchpadcontent.net/atareao/telegram/ubuntu noble InRelease

Hit:10 https://repo.protonvpn.com/debian unstable InRelease

Hit:11 https://ppa.launchpadcontent.net/openshot.developers/ppa/ubuntu noble InRelease

Hit:12 http://packages.linuxmint.com zara Release

Hit:13 https://download.sublimetext.com apt/stable/ InRelease

Hit:14 https://ppa.launchpadcontent.net/phoerious/keepassxc/ubuntu noble InRelease

Hit:15 https://deb.nodesource.com/node_22.x nodistro InRelease

…and the last ~38 lines (2/2)

Hit:16 https://ppa.launchpadcontent.net/savoury1/ffmpeg6/ubuntu noble InRelease

Hit:17 https://ppa.launchpadcontent.net/savoury1/multimedia/ubuntu noble InRelease

Reading package lists... Done

Building dependency tree... Done

Reading state information... Done

36 packages can be upgraded. Run 'apt list --upgradable' to see them.

N: Repository 'Debian bookworm' changed its 'non-free component' value from 'non-free' to 'non-free non-free-firmware'

N: More information about this can be found online in the Release notes at: https://www.debian.org/releases/bookworm/amd64/release-notes/ch-information.html#non-free-split

Reading package lists... Done

Building dependency tree... Done

Reading state information... Done

libxcb-xinerama0 is already the newest version (1.15-1ubuntu2).

libxcb-icccm4 is already the newest version (0.4.1-1.1build3).

libxcb-image0 is already the newest version (0.4.0-2build1).

libxcb-keysyms1 is already the newest version (0.4.0-1+b2).

libxcb-randr0 is already the newest version (1.15-1ubuntu2).

libxcb-render-util0 is already the newest version (0.3.9-1+b1).

libxcb-shape0 is already the newest version (1.15-1ubuntu2).

Some packages could not be installed. This may mean that you have

requested an impossible situation or if you are using the unstable

distribution that some required packages have not yet been created

or been moved out of Incoming.

The following information may help to resolve the situation:

The following packages have unmet dependencies.

ffmpeg : Depends: libavcodec60 (>= 7:6.1)

Depends: libavfilter9 (>= 7:6.0)

Depends: libavformat60 (>= 7:6.0)

libavdevice60 : Depends: libavcodec60 (>= 7:6.0)

Depends: libavfilter9 (>= 7:6.0)

Depends: libavformat60 (= 7:6.1.4-0ubuntu1~24.04.sav0)

Depends: libavutil58 (= 7:6.1.4-0ubuntu1~24.04.sav0) but 7:6.1.1-3ubuntu5 is to be installed

E: Unable to correct problems, you have held broken packages.

prajna@VB15:~/pygpt$ glxinfo | grep "OpenGL version"

# If this fails, you need to fix your OpenGL setup

OpenGL version string: 4.6 (Compatibility Profile) Mesa 25.2.8-0ubuntu0.24.04.1

β‰ˆ189 tokens

Good - OpenGL is working (Mesa 25.2.8), so the issue is Qt's GLX initialization, not your graphics driver.

Try software rendering:

bash β€” click to expand
export QT_QPA_PLATFORM=xcb
export LIBGL_ALWAYS_SOFTWARE=1
./pygpt

If that still crashes, try:

bash β€” click to expand
export QT_QPA_PLATFORM=offscreen
./pygpt

Or check if it's specifically the OpenGL version Qt is requesting:

bash β€” click to expand
export QT_QPA_PLATFORM=xcb
export QT_XCB_GL_INTEGRATION=none
./pygpt

The core issue is Qt can't find a compatible framebuffer configuration. The software rendering flag should bypass this by not using hardware acceleration.

If none of these work, PyGPT might have a config option to disable OpenGL. Check if there's a `--no-gl` or `--software` flag:

bash β€” click to expand
./pygpt --help

β‰ˆ5 tokens

Which brings me to:

Pasted attachment β€” text, 6,341 B β€” recovered from the export (18-Oct)

/pygpt$ export QT_QPA_PLATFORM=xcb export QT_XCB_GL_INTEGRATION=none ./pygpt User config: /home/prajna/.config/pygpt-net/config.json not found. Gtk-Message: 09:59:07.775: Failed to load module "xapp-gtk3-module" /usr/lib/x86_64-linux-gnu/gvfs/libgvfscommon.so: undefined symbol: g_task_set_static_name

Show the next ~84 lines (1/2)…

Failed to load module: /usr/lib/x86_64-linux-gnu/gio/modules/libgvfsdbus.so pydub/utils.py:170: RuntimeWarning: Couldn't find ffmpeg or avconv - defaulting to ffmpeg, but may not work User config: /home/prajna/.config/pygpt-net/config.json not found. Gtk-Message: 09:59:14.416: Failed to load module "xapp-gtk3-module" /usr/lib/x86_64-linux-gnu/gvfs/libgvfscommon.so: undefined symbol: g_task_set_static_name Failed to load module: /usr/lib/x86_64-linux-gnu/gio/modules/libgvfsdbus.so QXcbIntegration: Cannot create platform OpenGL context, neither GLX nor EGL are enabled =================================================== PyGPT 2.7.12 build 2026-02-06 (Linux, x86_64) Author: Marcin SzczygliΕ„ski GitHub: https://github.com/szczyglis-dev/py-gpt Website: https://pygpt.net Email: info@pygpt.net ===================================================

Initializing... [DB] Installed database: /home/prajna/.config/pygpt-net/db.sqlite Loaded config: /home/prajna/.config/pygpt-net/config.json Loaded models: /home/prajna/.config/pygpt-net/models.json [DB] Migrating database... [DB] Executed DB migration: 20231227152900 [DB] Executed DB migration: 20231230095000 [DB] Executed DB migration: 20231231230000 [DB] Executed DB migration: 20240106060000 [DB] Executed DB migration: 20240107060000 [DB] Executed DB migration: 20240222160000 [DB] Executed DB migration: 20240223050000 [DB] Executed DB migration: 20240303190000 [DB] Executed DB migration: 20240408180000 [DB] Executed DB migration: 20240426050000 [DB] Executed DB migration: 20240501030000 [DB] Executed DB migration: 20241122130000 [DB] Executed DB migration: 20241126170000 [DB] Executed DB migration: 20241215110000 [DB] Executed DB migration: 20260102190000 [DB] Executed DB migration: 20260121190000 [DB] Executed DB migration: 20260122140000 Setting environment vars: OLLAMA_API_BASE QXcbIntegration: Cannot create platform OpenGL context, neither GLX nor EGL are enabled QRhiGles2: Failed to create temporary context QXcbIntegration: Cannot create platform offscreen surface, neither GLX nor EGL are enabled QXcbIntegration: Cannot create platform OpenGL context, neither GLX nor EGL are enabled QRhiGles2: Failed to create context vkDebug: setup_loader_term_phys_devs: Failed to detect any valid GPUs in the current config No physical devices Unable to detect GPU vendor. [11655:11746:0303/095915.310587:ERROR:angle_platform_impl.cc(44)] Display.cpp:1083 (initialize): ANGLE Display::initialize error 12289: glXQueryExtensionsString returned NULL ERR: Display.cpp:1083 (initialize): ANGLE Display::initialize error 12289: glXQueryExtensionsString returned NULL [11655:11746:0303/095915.310615:ERROR:gl_display.cc(497)] EGL Driver message (Critical) eglInitialize: glXQueryExtensionsString returned NULL [11655:11746:0303/095915.310621:ERROR:gl_display.cc(767)] eglInitialize OpenGL failed with error EGL_NOT_INITIALIZED, trying next display type [11655:11746:0303/095915.314905:ERROR:angle_platform_impl.cc(44)] Display.cpp:1083 (initialize): ANGLE Display::initialize error 12289: glXQueryExtensionsString returned NULL ERR: Display.cpp:1083 (initialize): ANGLE Display::initialize error 12289: glXQueryExtensionsString returned NULL [11655:11746:0303/095915.314926:ERROR:gl_display.cc(497)] EGL Driver message (Critical) eglInitialize: glXQueryExtensionsString returned NULL [11655:11746:0303/095915.314931:ERROR:gl_display.cc(767)] eglInitialize OpenGLES failed with error EGL_NOT_INITIALIZED [11655:11746:0303/095915.314936:ERROR:gl_display.cc(801)] Initialization of all EGL display types failed. [11655:11746:0303/095915.314941:ERROR:gl_ozone_egl.cc(26)] GLDisplayEGL::Initialize failed. [11655:11746:0303/095915.319618:ERROR:angle_platform_impl.cc(44)] Display.cpp:1083 (initialize): ANGLE Display::initialize error 12289: glXQueryExtensionsString returned NULL ERR: Display.cpp:1083 (initialize): ANGLE Display::initialize error 12289: glXQueryExtensionsString returned NULL [11655:11746:0303/095915.319639:ERROR:gl_display.cc(497)] EGL Driver message (Critical) eglInitialize: glXQueryExtensionsString returned NULL [11655:11746:0303/095915.319646:ERROR:gl_display.cc(767)] eglInitialize OpenGL failed with error EGL_NOT_INITIALIZED, trying next display type [11655:11746:0303/095915.324104:ERROR:angle_platform_impl.cc(44)] Display.cpp:1083 (initialize): ANGLE Display::initialize error 12289: glXQueryExtensionsString returned NULL ERR: Display.cpp:1083 (initialize): ANGLE Display::initialize error 12289: glXQueryExtensionsString returned NULL [11655:11746:0303/095915.324211:ERROR:gl_display.cc(497)] EGL Driver message (Critical) eglInitialize: glXQueryExtensionsString returned NULL [11655:11746:0303/095915.324237:ERROR:gl_display.cc(767)] eglInitialize OpenGLES failed with error EGL_NOT_INITIALIZED [11655:11746:0303/095915.324244:ERROR:gl_display.cc(801)] Initialization of all EGL display types failed. [11655:11746:0303/095915.324250:ERROR:gl_ozone_egl.cc(26)] GLDisplayEGL::Initialize failed.

…and the last ~20 lines (2/2)

(pygpt:11672): WARNING : 09:59:32.946: atk-bridge: get_device_events_reply: unknown signature GLOzone not found for unknown Aborted (core dumped) prajna@VB15:~/pygpt$ ./pygpt --help Gtk-Message: 10:00:06.501: Failed to load module "xapp-gtk3-module" /usr/lib/x86_64-linux-gnu/gvfs/libgvfscommon.so: undefined symbol: g_task_set_static_name Failed to load module: /usr/lib/x86_64-linux-gnu/gio/modules/libgvfsdbus.so pydub/utils.py:170: RuntimeWarning: Couldn't find ffmpeg or avconv - defaulting to ffmpeg, but may not work usage: pygpt [-h] [-d DEBUG] [-l LEGACY] [-n DISABLE_GPU] [-w WORKDIR]

options: -h, --help show this help message and exit -d DEBUG, --debug DEBUG debug mode (0=disabled, 1=info, 2=debug) -l LEGACY, --legacy LEGACY force enable legacy mode (0=disabled, 1=enable) -n DISABLE_GPU, --disable-gpu DISABLE_GPU force disable OpenGL (1=disabled, 0=enabled) -w WORKDIR, --workdir WORKDIR force set workdir

β‰ˆ45 tokens

Perfect! There's a `--disable-gpu` flag:

bash β€” click to expand
./pygpt --disable-gpu 1

This should bypass all the OpenGL/GLX initialization issues and run PyGPT in software rendering mode.

β‰ˆ3 tokens

Dang, nearly:

Pasted attachment β€” text, 8,312 B β€” recovered from the export (18-Oct)

~/pygpt$ ./pygpt --disable-gpu 1

Gtk-Message: 10:02:17.587: Failed to load module "xapp-gtk3-module"

/usr/lib/x86_64-linux-gnu/gvfs/libgvfscommon.so: undefined symbol: g_task_set_static_name

Failed to load module: /usr/lib/x86_64-linux-gnu/gio/modules/libgvfsdbus.so

pydub/utils.py:170: RuntimeWarning: Couldn't find ffmpeg or avconv - defaulting to ffmpeg, but may not work

Show the next ~47 lines (1/3)…

** Force disable GPU enabled

Gtk-Message: 10:02:24.334: Failed to load module "xapp-gtk3-module"

/usr/lib/x86_64-linux-gnu/gvfs/libgvfscommon.so: undefined symbol: g_task_set_static_name

Failed to load module: /usr/lib/x86_64-linux-gnu/gio/modules/libgvfsdbus.so

QXcbIntegration: Cannot create platform OpenGL context, neither GLX nor EGL are enabled

===================================================

PyGPT 2.7.12 build 2026-02-06 (Linux, x86_64)

Author: Marcin SzczygliΕ„ski

GitHub: https://github.com/szczyglis-dev/py-gpt

Website: https://pygpt.net

Email: info@pygpt.net

===================================================

Initializing...

Loaded config: /home/prajna/.config/pygpt-net/config.json

Loaded models: /home/prajna/.config/pygpt-net/models.json

Setting environment vars: OLLAMA_API_BASE

QXcbIntegration: Cannot create platform OpenGL context, neither GLX nor EGL are enabled

QRhiGles2: Failed to create temporary context

QXcbIntegration: Cannot create platform offscreen surface, neither GLX nor EGL are enabled

QXcbIntegration: Cannot create platform OpenGL context, neither GLX nor EGL are enabled

QRhiGles2: Failed to create context

vkDebug: setup_loader_term_phys_devs: Failed to detect any valid GPUs in the current config

No physical devices

Unable to detect GPU vendor.

[11906:11995:0303/100225.095827:ERROR:angle_platform_impl.cc(44)] Display.cpp:1083 (initialize): ANGLE Display::initialize error 12289: glXQueryExtensionsString returned NULL

ERR: Display.cpp:1083 (initialize): ANGLE Display::initialize error 12289: glXQueryExtensionsString returned NULL

[11906:11995:0303/100225.095862:ERROR:gl_display.cc(497)] EGL Driver message (Critical) eglInitialize: glXQueryExtensionsString returned NULL

[11906:11995:0303/100225.095871:ERROR:gl_display.cc(767)] eglInitialize OpenGL failed with error EGL_NOT_INITIALIZED, trying next display type

[11906:11995:0303/100225.099640:ERROR:angle_platform_impl.cc(44)] Display.cpp:1083 (initialize): ANGLE Display::initialize error 12289: glXQueryExtensionsString returned NULL

ERR: Display.cpp:1083 (initialize): ANGLE Display::initialize error 12289: glXQueryExtensionsString returned NULL

[11906:11995:0303/100225.099659:ERROR:gl_display.cc(497)] EGL Driver message (Critical) eglInitialize: glXQueryExtensionsString returned NULL

[11906:11995:0303/100225.099663:ERROR:gl_display.cc(767)] eglInitialize OpenGLES failed with error EGL_NOT_INITIALIZED

[11906:11995:0303/100225.099668:ERROR:gl_display.cc(801)] Initialization of all EGL display types failed.

[11906:11995:0303/100225.099672:ERROR:gl_ozone_egl.cc(26)] GLDisplayEGL::Initialize failed.

[11906:11995:0303/100225.103871:ERROR:angle_platform_impl.cc(44)] Display.cpp:1083 (initialize): ANGLE Display::initialize error 12289: glXQueryExtensionsString returned NULL

ERR: Display.cpp:1083 (initialize): ANGLE Display::initialize error 12289: glXQueryExtensionsString returned NULL

Show the next ~43 lines (2/3)…

[11906:11995:0303/100225.103892:ERROR:gl_display.cc(497)] EGL Driver message (Critical) eglInitialize: glXQueryExtensionsString returned NULL

[11906:11995:0303/100225.103897:ERROR:gl_display.cc(767)] eglInitialize OpenGL failed with error EGL_NOT_INITIALIZED, trying next display type

[11906:11995:0303/100225.107798:ERROR:angle_platform_impl.cc(44)] Display.cpp:1083 (initialize): ANGLE Display::initialize error 12289: glXQueryExtensionsString returned NULL

ERR: Display.cpp:1083 (initialize): ANGLE Display::initialize error 12289: glXQueryExtensionsString returned NULL

[11906:11995:0303/100225.107818:ERROR:gl_display.cc(497)] EGL Driver message (Critical) eglInitialize: glXQueryExtensionsString returned NULL

[11906:11995:0303/100225.107822:ERROR:gl_display.cc(767)] eglInitialize OpenGLES failed with error EGL_NOT_INITIALIZED

[11906:11995:0303/100225.107827:ERROR:gl_display.cc(801)] Initialization of all EGL display types failed.

[11906:11995:0303/100225.107834:ERROR:gl_ozone_egl.cc(26)] GLDisplayEGL::Initialize failed.

Checking for updates...

QXcbIntegration: Cannot create platform OpenGL context, neither GLX nor EGL are enabled

QRhiGles2: Failed to create temporary context

QXcbIntegration: Cannot create platform offscreen surface, neither GLX nor EGL are enabled

QXcbIntegration: Cannot create platform OpenGL context, neither GLX nor EGL are enabled

QRhiGles2: Failed to create context

Failed to create QRhi for QBackingStoreRhiSupport

QXcbIntegration: Cannot create platform OpenGL context, neither GLX nor EGL are enabled

QRhiGles2: Failed to create temporary context

QXcbIntegration: Cannot create platform offscreen surface, neither GLX nor EGL are enabled

QXcbIntegration: Cannot create platform OpenGL context, neither GLX nor EGL are enabled

QRhiGles2: Failed to create context

Failed to create QRhi for QBackingStoreRhiSupport

QQuickWidget: Failed to get a QRhi from the top-level widget's window

QXcbIntegration: Cannot create platform OpenGL context, neither GLX nor EGL are enabled

QRhiGles2: Failed to create temporary context

QXcbIntegration: Cannot create platform offscreen surface, neither GLX nor EGL are enabled

QXcbIntegration: Cannot create platform OpenGL context, neither GLX nor EGL are enabled

QRhiGles2: Failed to create context

Failed to create QRhi for QBackingStoreRhiSupport

QQuickWidget: Failed to get a QRhi from the top-level widget's window

QQuickWidget::resizeEvent() no QRhi

QXcbIntegration: Cannot create platform OpenGL context, neither GLX nor EGL are enabled

QRhiGles2: Failed to create temporary context

QXcbIntegration: Cannot create platform offscreen surface, neither GLX nor EGL are enabled

QXcbIntegration: Cannot create platform OpenGL context, neither GLX nor EGL are enabled

QRhiGles2: Failed to create context

Failed to create QRhi for QBackingStoreRhiSupport

…and the last ~36 lines (3/3)

QQuickWidget: Failed to get a QRhi from the top-level widget's window

QXcbIntegration: Cannot create platform OpenGL context, neither GLX nor EGL are enabled

QRhiGles2: Failed to create temporary context

QXcbIntegration: Cannot create platform offscreen surface, neither GLX nor EGL are enabled

QXcbIntegration: Cannot create platform OpenGL context, neither GLX nor EGL are enabled

QRhiGles2: Failed to create context

Failed to create QRhi for QBackingStoreRhiSupport

QQuickWidget: Failed to get a QRhi from the top-level widget's window

QQuickWidget::resizeEvent() no QRhi

QXcbIntegration: Cannot create platform OpenGL context, neither GLX nor EGL are enabled

QRhiGles2: Failed to create temporary context

QXcbIntegration: Cannot create platform offscreen surface, neither GLX nor EGL are enabled

QXcbIntegration: Cannot create platform OpenGL context, neither GLX nor EGL are enabled

QRhiGles2: Failed to create context

Failed to create QRhi for QBackingStoreRhiSupport

QQuickWidget: Failed to get a QRhi from the top-level widget's window

QQuickWidget::resizeEvent() no QRhi

QQuickWidget: Attempted to render scene with no rhi

QXcbIntegration: Cannot create platform OpenGL context, neither GLX nor EGL are enabled

QRhiGles2: Failed to create temporary context

QXcbIntegration: Cannot create platform offscreen surface, neither GLX nor EGL are enabled

QXcbIntegration: Cannot create platform OpenGL context, neither GLX nor EGL are enabled

QRhiGles2: Failed to create context

Failed to create QRhi for QBackingStoreRhiSupport

QQuickWidget: Failed to get a QRhi from the top-level widget's window

QQuickWidget::resizeEvent() no QRhi

QXcbIntegration: Cannot create platform OpenGL context, neither GLX nor EGL are enabled

QRhiGles2: Failed to create temporary context

QXcbIntegration: Cannot create platform offscreen surface, neither GLX nor EGL are enabled

QXcbIntegration: Cannot create platform OpenGL context, neither GLX nor EGL are enabled

QRhiGles2: Failed to create context

Failed to create QRhi for QBackingStoreRhiSupport

QQuickWidget: Failed to get a QRhi from the top-level widget's window

QQuickWidget::resizeEvent() no QRhi

GLOzone not found for unknown

Aborted (core dumped)

β‰ˆ358 tokens

The `--disable-gpu` flag isn't working properly - it's still trying to initialize OpenGL. The issue is that PyGPT uses QQuickWidget which requires OpenGL/RHI (Qt's rendering hardware interface).

This is a fundamental VirtualBox + Qt6 + Mesa incompatibility. The problem: `glXQueryExtensionsString returned NULL` means your X server isn't advertising GLX extensions properly.

Let's fix the X server GLX:

bash β€” click to expand
# Install VirtualBox guest additions properly
sudo apt install -y virtualbox-guest-dkms virtualbox-guest-utils virtualbox-guest-x11


# Rebuild kernel modules
sudo /sbin/rcvboxadd quicksetup all


# Restart X server
sudo systemctl restart gdm
# Or if that fails:
# sudo reboot

After reboot, verify GLX is working:

bash β€” click to expand
glxinfo | grep "direct rendering"
# Should say "direct rendering: Yes"


xdpyinfo | grep GLX
# Should show GLX extension

If GLX still isn't working after guest additions, you have two options:

Option 1: Use PyGPT via pip instead (might have better compatibility)

bash β€” click to expand
pip install pygpt-net
pygpt --disable-gpu 1

Option 2: Give up on PyGPT in VirtualBox, use it on your host OS instead, or try a different LLM interface that doesn't use Qt6 Quick (like `gpt4all`, `ollama-webui`, or just stick with OpenCLAW).

The core issue is Qt6's QQuickWidget doesn't work without proper GL/EGL support, and VirtualBox's 3D acceleration is notoriously finicky with modern Qt.

β‰ˆ41 tokens

Now we're at ~$ glxinfo | grep "direct rendering" # Should say "direct rendering: Yes" xdpyinfo | grep GLX # Should show GLX extension direct rendering: Yes GLX

β‰ˆ152 tokens

Great! GLX is working now. Try PyGPT again:

bash β€” click to expand
./pygpt --disable-gpu 1

If it still crashes, try without the disable-gpu flag (since GLX is now working):

bash β€” click to expand
./pygpt

If it still fails with the same errors, the issue might be that PyGPT needs to be reinstalled/rebuilt to pick up the new GLX configuration. Try:

bash β€” click to expand
# If you installed via pip
pip uninstall pygpt-net
pip install --no-cache-dir pygpt-net
pygpt


# Or if you're running from source
cd ~/pygpt
# Pull latest or reinstall dependencies
pip install -r requirements.txt --force-reinstall
./pygpt

Let me know what happens!

β‰ˆ11 tokens

Still not. How do I clean up the core dumps?

β‰ˆ271 tokens

To clean up core dumps:

bash β€” click to expand
# Find core dumps in current directory
rm -f core core.*


# Find all core dumps in your home directory
find ~ -name "core" -o -name "core.*" -type f -delete


# Or more safely, list them first before deleting
find ~ -name "core" -o -name "core.*" -type f


# To disable core dumps entirely (they just waste space)
ulimit -c 0


# To make that permanent, add to ~/.bashrc
echo "ulimit -c 0" >> ~/.bashrc

As for PyGPT - at this point I'd recommend just giving up on it in VirtualBox. The Qt6 Quick + VirtualBox 3D acceleration combo is notoriously problematic.

Better alternatives for your use case:

1. Just use OpenCLAW - You already have it working with Ollama 2. Ollama Web UI - Much lighter weight:

bash β€” click to expand
   docker run -d -p 3000:8080 --add-host=host.docker.internal:host-gateway ghcr.io/open-webui/open-webui:main
3. GPT4All - Native Qt5 app, better VirtualBox compatibility 4. LM Studio - If you can run it on your host OS instead

PyGPT is fighting against your environment too hard. Save yourself the hassle.

β‰ˆ68 tokens

I have OpenCLAW installed but just get timeouts with local models ranging from 1b to 8b. I have ollama and LM Studio set up. I like LM Studio in particular but am after having an agent running locally.

I meant to paste the output from the earlier commands, sorry. Here:

Pasted attachment β€” text, 8,572 B β€” recovered from the export (18-Oct)

~$ cd pygpt/ prajna@VB15:~/pygpt$ ./pygpt --disable-gpu 1 Failed to create wl_display (No such file or directory) qt.qpa.plugin: Could not load the Qt platform plugin "wayland" in "" even though it was found. Gtk-Message: 10:08:31.054: Failed to load module "xapp-gtk3-module" /usr/lib/x86_64-linux-gnu/gvfs/libgvfscommon.so: undefined symbol: g_task_set_static_name

Show the next ~64 lines (1/3)…

Failed to load module: /usr/lib/x86_64-linux-gnu/gio/modules/libgvfsdbus.so pydub/utils.py:170: RuntimeWarning: Couldn't find ffmpeg or avconv - defaulting to ffmpeg, but may not work ** Force disable GPU enabled Failed to create wl_display (No such file or directory) qt.qpa.plugin: Could not load the Qt platform plugin "wayland" in "" even though it was found. Gtk-Message: 10:08:38.984: Failed to load module "xapp-gtk3-module" /usr/lib/x86_64-linux-gnu/gvfs/libgvfscommon.so: undefined symbol: g_task_set_static_name Failed to load module: /usr/lib/x86_64-linux-gnu/gio/modules/libgvfsdbus.so qt.glx: qglx_findConfig: Failed to finding matching FBConfig for QSurfaceFormat(version 2.0, options QFlags<QSurfaceFormat::FormatOption>(), depthBufferSize -1, redBufferSize 1, greenBufferSize 1, blueBufferSize 1, alphaBufferSize -1, stencilBufferSize -1, samples -1, swapBehavior QSurfaceFormat::SingleBuffer, swapInterval 1, colorSpace QColorSpace(), profile QSurfaceFormat::NoProfile) qt.glx: qglx_findConfig: Failed to finding matching FBConfig for QSurfaceFormat(version 2.0, options QFlags<QSurfaceFormat::FormatOption>(), depthBufferSize -1, redBufferSize 1, greenBufferSize 1, blueBufferSize 1, alphaBufferSize -1, stencilBufferSize -1, samples -1, swapBehavior QSurfaceFormat::SingleBuffer, swapInterval 1, colorSpace QColorSpace(), profile QSurfaceFormat::NoProfile) Could not initialize GLX Aborted (core dumped) prajna@VB15:~/pygpt$ ./pygpt Failed to create wl_display (No such file or directory) qt.qpa.plugin: Could not load the Qt platform plugin "wayland" in "" even though it was found. Gtk-Message: 10:09:25.224: Failed to load module "xapp-gtk3-module" /usr/lib/x86_64-linux-gnu/gvfs/libgvfscommon.so: undefined symbol: g_task_set_static_name Failed to load module: /usr/lib/x86_64-linux-gnu/gio/modules/libgvfsdbus.so pydub/utils.py:170: RuntimeWarning: Couldn't find ffmpeg or avconv - defaulting to ffmpeg, but may not work Failed to create wl_display (No such file or directory) qt.qpa.plugin: Could not load the Qt platform plugin "wayland" in "" even though it was found. Gtk-Message: 10:09:31.891: Failed to load module "xapp-gtk3-module" /usr/lib/x86_64-linux-gnu/gvfs/libgvfscommon.so: undefined symbol: g_task_set_static_name Failed to load module: /usr/lib/x86_64-linux-gnu/gio/modules/libgvfsdbus.so qt.glx: qglx_findConfig: Failed to finding matching FBConfig for QSurfaceFormat(version 2.0, options QFlags<QSurfaceFormat::FormatOption>(), depthBufferSize -1, redBufferSize 1, greenBufferSize 1, blueBufferSize 1, alphaBufferSize -1, stencilBufferSize -1, samples -1, swapBehavior QSurfaceFormat::SingleBuffer, swapInterval 1, colorSpace QColorSpace(), profile QSurfaceFormat::NoProfile) qt.glx: qglx_findConfig: Failed to finding matching FBConfig for QSurfaceFormat(version 2.0, options QFlags<QSurfaceFormat::FormatOption>(), depthBufferSize -1, redBufferSize 1, greenBufferSize 1, blueBufferSize 1, alphaBufferSize -1, stencilBufferSize -1, samples -1, swapBehavior QSurfaceFormat::SingleBuffer, swapInterval 1, colorSpace QColorSpace(), profile QSurfaceFormat::NoProfile) Could not initialize GLX Aborted (core dumped) prajna@VB15:~/pygpt$ # If you installed via pip pip uninstall pygpt-net pip install --no-cache-dir pygpt-net pygpt

# Or if you're running from source cd ~/pygpt # Pull latest or reinstall dependencies pip install -r requirements.txt --force-reinstall ./pygpt error: externally-managed-environment

Γ— This environment is externally managed ╰─> To install Python packages system-wide, try apt install python3-xyz, where xyz is the package you are trying to install.

If you wish to install a non-Debian-packaged Python package, create a virtual environment using python3 -m venv path/to/venv. Then use path/to/venv/bin/python and path/to/venv/bin/pip. Make sure you have python3-full installed.

If you wish to install a non-Debian packaged Python application, it may be easiest to use pipx install xyz, which will manage a virtual environment for you. Make sure you have pipx installed.

See /usr/share/doc/python3.12/README.venv for more information.

Show the next ~23 lines (2/3)…

note: If you believe this is a mistake, please contact your Python installation or OS distribution provider. You can override this, at the risk of breaking your Python installation or OS, by passing --break-system-packages. hint: See PEP 668 for the detailed specification. error: externally-managed-environment

Γ— This environment is externally managed ╰─> To install Python packages system-wide, try apt install python3-xyz, where xyz is the package you are trying to install.

If you wish to install a non-Debian-packaged Python package, create a virtual environment using python3 -m venv path/to/venv. Then use path/to/venv/bin/python and path/to/venv/bin/pip. Make sure you have python3-full installed.

If you wish to install a non-Debian packaged Python application, it may be easiest to use pipx install xyz, which will manage a virtual environment for you. Make sure you have pipx installed.

See /usr/share/doc/python3.12/README.venv for more information.

note: If you believe this is a mistake, please contact your Python installation or OS distribution provider. You can override this, at the risk of breaking your Python installation or OS, by passing --break-system-packages. hint: See PEP 668 for the detailed specification. pygpt: command not found error: externally-managed-environment

…and the last ~38 lines (3/3)

Γ— This environment is externally managed ╰─> To install Python packages system-wide, try apt install python3-xyz, where xyz is the package you are trying to install.

If you wish to install a non-Debian-packaged Python package, create a virtual environment using python3 -m venv path/to/venv. Then use path/to/venv/bin/python and path/to/venv/bin/pip. Make sure you have python3-full installed.

If you wish to install a non-Debian packaged Python application, it may be easiest to use pipx install xyz, which will manage a virtual environment for you. Make sure you have pipx installed.

See /usr/share/doc/python3.12/README.venv for more information.

note: If you believe this is a mistake, please contact your Python installation or OS distribution provider. You can override this, at the risk of breaking your Python installation or OS, by passing --break-system-packages. hint: See PEP 668 for the detailed specification. Failed to create wl_display (No such file or directory) qt.qpa.plugin: Could not load the Qt platform plugin "wayland" in "" even though it was found. Gtk-Message: 10:09:56.470: Failed to load module "xapp-gtk3-module" /usr/lib/x86_64-linux-gnu/gvfs/libgvfscommon.so: undefined symbol: g_task_set_static_name Failed to load module: /usr/lib/x86_64-linux-gnu/gio/modules/libgvfsdbus.so pydub/utils.py:170: RuntimeWarning: Couldn't find ffmpeg or avconv - defaulting to ffmpeg, but may not work Failed to create wl_display (No such file or directory) qt.qpa.plugin: Could not load the Qt platform plugin "wayland" in "" even though it was found. Gtk-Message: 10:10:02.798: Failed to load module "xapp-gtk3-module" /usr/lib/x86_64-linux-gnu/gvfs/libgvfscommon.so: undefined symbol: g_task_set_static_name Failed to load module: /usr/lib/x86_64-linux-gnu/gio/modules/libgvfsdbus.so qt.glx: qglx_findConfig: Failed to finding matching FBConfig for QSurfaceFormat(version 2.0, options QFlags<QSurfaceFormat::FormatOption>(), depthBufferSize -1, redBufferSize 1, greenBufferSize 1, blueBufferSize 1, alphaBufferSize -1, stencilBufferSize -1, samples -1, swapBehavior QSurfaceFormat::SingleBuffer, swapInterval 1, colorSpace QColorSpace(), profile QSurfaceFormat::NoProfile) qt.glx: qglx_findConfig: Failed to finding matching FBConfig for QSurfaceFormat(version 2.0, options QFlags<QSurfaceFormat::FormatOption>(), depthBufferSize -1, redBufferSize 1, greenBufferSize 1, blueBufferSize 1, alphaBufferSize -1, stencilBufferSize -1, samples -1, swapBehavior QSurfaceFormat::SingleBuffer, swapInterval 1, colorSpace QColorSpace(), profile QSurfaceFormat::NoProfile) Could not initialize GLX Aborted (core dumped)

β‰ˆ276 tokens

No worries! Go ahead and paste the output - I'd like to see what's happening with the timeouts.

For the OpenCLAW timeout issue with local models (1b-8b):

The timeout problem is likely separate from the startup instruction issue we were debugging. Let's troubleshoot:

bash β€” click to expand
# Check your current timeout setting
grep -i timeout ~/.openclaw/openclaw.json


# Test if Ollama is responding at all
curl http://localhost:11434/api/generate -d '{
  "model": "phi4-mini:3.8b",
  "prompt": "Say only: HELLO",
  "stream": false
}'


# Check OpenCLAW logs for timeout details
tail -50 ~/.openclaw/logs/*.log | grep -i timeout

Your config showed `"timeoutSeconds": 240` (4 minutes), which should be plenty even for 8b models on a laptop. The timeouts might be caused by:

1. Models not loaded - Ollama needs to load them into RAM first 2. RAM exhaustion - 8b models need ~8-10GB RAM 3. OpenCLAW trying wrong endpoint - Check if it's actually hitting Ollama 4. Model context too large - Your config has 100k-120k context windows

But paste your output and we'll see what's really going on!

⟡ The Anthropic Archive The Nave