{
  "$type": "site.standard.document",
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    "uri": "at://did:plc:pgryn3ephfd2xgft23qokfzt/app.bsky.feed.post/3mppenph2oyp2"
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  "path": "/t/local-llm-on-macbook-m5-pro-totally-new-to-this/177286#post_8",
  "publishedAt": "2026-07-02T22:47:54.000Z",
  "site": "https://discuss.huggingface.co",
  "tags": [
    "Open WebUI Web Search docs",
    "Open WebUI Tools docs",
    "Open WebUI Knowledge docs",
    "(click for more details)"
  ],
  "textContent": "Hmm. This is getting a little tangled​, so let me try to organize it:\n\n* * *\n\nYes, I think you are understanding the “layers” idea correctly.\n\nThe reason to think in layers is that the model may be behaving normally, but the thing you see in chat can also be affected by the prompt, chat template, runtime, RAG/Knowledge setup, web search, tool parser, Open WebUI settings, or the actual tool implementation.\n\nSo I would not test everything with one big question like:\n\n> “Does my AI work?”\n\nI would start with:\n\n> “What am I testing right now?”\n\nThen choose the settings from there.\n\n## Decision tree: what are you testing?\n\nIf you are testing… | Web search | Knowledge/RAG | Tools | Why\n---|---|---|---|---\n**Model baseline** | Off | Off | Off | Isolate the model/runtime as much as possible\n**Real daily chat experience** | Your normal setting | Optional | Optional | Test the actual setup you plan to use\n**Summarization of pasted/provided text** | Usually off | Off | Off | Check whether it follows the provided text\n**RAG / Knowledge smoke test** | Off | One tiny Knowledge file | Only Knowledge tools if Native mode requires it | Isolate whether Knowledge retrieval works\n**Web search test** | On | Off if possible | Web search only | Check whether web search itself works\n**Tool-calling test** | Off | Off | One toy tool | Check whether the model really calls a tool\n**Hybrid workflow test** | On | On | Optional | Realistic, but harder to debug\n\nThe simple rule I would use:\n\n> If the goal is isolation, turn extra features off.\n>  If the goal is real daily usability, use your normal settings.\n>  If the real-use test fails, go back to isolated tests.\n\n* * *\n\n## Model quality vs chat quality\n\nThis is probably the cleanest way to separate the two.\n\n### Model quality\n\n“Model quality” means the model’s underlying ability, as much as you can observe it while keeping the surrounding system simple.\n\nFor example:\n\n  * Can it explain something clearly?\n  * Can it follow instructions?\n  * Can it summarize accurately?\n  * Can it use provided context?\n  * Can it say “I don’t know” when the answer is missing?\n  * Can it reason through a simple task?\n\n\n\nFor this kind of test, I would usually use:\n\n\n    web search: off\n    Knowledge/RAG: off\n    tools: off\n    simple prompt\n    stable settings\n\n\n### Chat quality\n\n“Chat quality” means the actual experience you get inside Open WebUI with your real setup.\n\nThat includes:\n\n\n    model\n    + system prompt\n    + chat template\n    + sampling settings\n    + context length\n    + backend/runtime\n    + Open WebUI settings\n    + RAG/Knowledge\n    + web search\n    + tools\n    + parser behavior\n\n\nSo if your “real chat” is bad, it does not automatically mean the model is bad.\n\nA short analogy:\n\n> Model quality is closer to the engine.\n>  Chat quality is the whole car on the road.\n\nBoth matter, but they are different tests.\n\n* * *\n\n## Web search: when to leave it on\n\nFor your daily-use tests, leaving web search on can be fine **if you are testing your real assistant experience**.\n\nFor example:\n\n\n    Make a 5-step checklist for preparing an RV for a weekend trip.\n\n\nIf you normally want web search available, testing with web search on is reasonable.\n\nBut if you are testing whether the model itself follows instructions, I would turn web search off first.\n\nExample:\n\n\n    Compare these two products using only the notes I provide.\n\n\nFor that test, web search should probably be off, because the goal is source discipline:\n\n> Does it use only my notes, or does it bring in outside information?\n\nSame for summarization:\n\n\n    Summarize this manual page into maintenance steps.\n    Extract only warnings and safety notes.\n\n\nI would usually turn web search off for those, because you want to know whether it can use the provided text faithfully.\n\nOpen WebUI’s web search features are useful, but they add another retrieval source. That is good for real use, but it makes debugging harder. The Open WebUI Web Search docs and Open WebUI Tools docs are useful background because in newer/native setups, web search and other built-in capabilities may be exposed as tools.\n\n* * *\n\n## RAG / Knowledge: keep the first test isolated\n\nFor the first RAG smoke test, I would use:\n\n\n    web search: off\n    Knowledge: one tiny test file\n    tools: off, except Knowledge tools if Native mode requires them\n\n\nThe goal is:\n\n> If the answer is in the Knowledge file, does it find it?\n>  If the answer is not in the Knowledge file, does it admit that?\n\nIf web search is on, a correct answer might come from the web instead of your Knowledge collection. Then you have not really tested whether RAG is working.\n\nThe Open WebUI Knowledge docs are worth reading because Knowledge behavior can differ depending on mode/settings. The Open WebUI Tools docs also explain how built-in features such as RAG/Knowledge can be exposed as tools in Native mode.\n\nTiny RAG smoke test example (click for more details)\n\n* * *\n\n## Important correction: “7 + 3” is not automatically a tool-calling test\n\nThis part is important.\n\nIf you ask:\n\n\n    What is 7 plus 3?\n\n\nthat is **not** a tool-calling test by itself.\n\nA normal LLM can answer that internally. It might never call a tool.\n\nThat tests:\n\n\n    basic answering\n    simple arithmetic\n    instruction following\n\n\nIt does **not** prove:\n\n\n    Open WebUI tool calling works\n    the backend parser works\n    the model returned a structured tool call\n    the tool was executed\n    the result was passed back to the model\n\n\nFor it to be a real tool-calling test, there must be an actual tool attached and available.\n\nSo this is not a tool test:\n\n\n    What is 7 plus 3?\n\n\nBut this can be a tool test:\n\n\n    Use the add_two_numbers tool to add 7 and 3.\n\n\nOnly if an actual `add_two_numbers` tool exists and is enabled.\n\n* * *\n\n## What counts as a real tool-calling test?\n\nA real tool-calling test needs the whole loop:\n\n\n    1. A real tool exists.\n    2. The tool is enabled for the model/chat/user.\n    3. The model requests the tool.\n    4. Open WebUI/backend recognizes the tool call.\n    5. The tool runs.\n    6. The result is sent back to the model.\n    7. The model uses the result in the final answer.\n\n\nExamples:\n\nPrompt | What it tests\n---|---\n`What is 7 plus 3?` | Basic answering, not tool calling\n`Use the add_two_numbers tool to add 7 and 3.` | Tool calling, if that tool exists\n`What time is it?` | Usually not reliable unless there is a time tool\n`Use the get_current_time tool.` | Tool calling, if that tool exists\n`Lookup my Amazon order 1234.` | Do not start here with a real account\n`Use lookup_fake_order_status for order 1234.` | Good first fake-tool test\n\nI would not start by connecting real Amazon, email, filesystem, browser, or shell access.\n\nStart with a fake or harmless tool.\n\nFor example:\n\n\n    def lookup_fake_order_status(order_id: str) -> str:\n        if order_id == \"1234\":\n            return \"Order 1234: shipped\"\n        return \"Order not found\"\n\n\nThen ask:\n\n\n    Use the lookup_fake_order_status tool for order 1234.\n\n\nExpected final answer:\n\n\n    Order 1234 is shipped.\n\n\nWhy fake tools are better first (click for more details)\n\n* * *\n\n## A simple three-pass plan\n\n### Pass 1: isolated tests\n\nPurpose:\n\n> Test one subsystem at a time.\n\nSettings:\n\n\n    web search off\n    RAG off unless testing RAG\n    tools off unless testing tools\n    simple prompt\n\n\nUse this for:\n\n\n    model baseline\n    summarization\n    RAG smoke test\n    tool smoke test\n\n\n### Pass 2: real-use tests\n\nPurpose:\n\n> Test the setup you actually want to use day to day.\n\nSettings:\n\n\n    your normal web search setting\n    your normal Knowledge setting\n    your normal model\n    your normal Open WebUI setup\n\n\nThis tests **chat quality** , not isolated model quality.\n\n### Pass 3: hybrid tests\n\nPurpose:\n\n> Test the realistic “everything available” workflow.\n\nSettings:\n\n\n    web search on\n    Knowledge on\n    tools on, if trusted\n\n\nThis is closest to real use, but hardest to debug.\n\nIf it fails, go back to Pass 1.\n\n* * *\n\n## My suggested next three chats\n\nI would make three separate chats:\n\n### 1. Model baseline chat\n\n\n    web search: off\n    Knowledge: off\n    tools: off\n\n\nAsk simple explanation/summarization/instruction-following questions.\n\n### 2. RAG-only chat\n\n\n    web search: off\n    Knowledge: one tiny test file\n    tools: only Knowledge tools if needed by your Open WebUI mode\n\n\nAsk one answer-in-doc question and one answer-not-in-doc question.\n\n### 3. One-tool chat\n\n\n    web search: off\n    Knowledge: off\n    tools: one fake or harmless tool\n\n\nAsk the model to use that specific tool.\n\nThis keeps the tests small enough that when something fails, you know where to look.\n\n* * *\n\n## Final practical rule\n\nIf you remember only one thing from this:\n\n> Turn features on when you want real usefulness.\n>  Turn features off when you want to debug.\n\nSo:\n\n\n    Daily real chat: normal settings are fine.\n    Model baseline: web/RAG/tools off.\n    RAG test: web off, tiny Knowledge source only.\n    Web search test: web on, Knowledge off if possible.\n    Tool test: one real toy tool, not just a normal question.\n    Hybrid test: everything on, but only after the isolated tests make sense.\n\n\nThat should make your notes much less tangled.",
  "title": "Local LLM on MacBook M5 Pro - Totally New to This!"
}