{ "title": "Trilium AI/LLM setup", "messages": [ { "role": "user", "content": "{\"content_type\": \"image_asset_pointer\", \"asset_pointer\": \"sediment://file_00000000655061f69a2247abc29d04d0\", \"size_bytes\": 109637, \"width\": 1306, \"height\": 1138, \"fovea\": null, \"metadata\": {\"dalle\": null, \"gizmo\": null, \"generation\": null, \"container_pixel_height\": null, \"container_pixel_width\": null, \"emu_omit_glimpse_image\": null, \"emu_patches_override\": null, \"lpe_keep_patch_ijhw\": null, \"sanitized\": true, \"asset_pointer_link\": null, \"watermarked_asset_pointer\": null}} Trillium has this AI/LLM section. What can i do with that? Can i hook it up to local lyra??" }, { "role": "tool", "content": "All the files uploaded by the user have been fully loaded. Searching won't provide additional information." }, { "role": "assistant", "content": "Perfect — that screenshot shows Trilium’s built-in **AI/LLM** config panel. \nHere’s what it means and how you can hook it into your **local Lyra stack**:\n\n---\n\n### 🧩 What This Panel Does\nTrilium can use any **OpenAI-compatible API** to:\n- Summarize notes automatically \n- Generate content in a note \n- Offer completions or paraphrasing directly inside Trilium\n\nBy default, it expects the official OpenAI endpoint \n`https://api.openai.com/v1` \nand a valid API key.\n\nBut you can point it to **any local server** that implements the same API schema — like your **Lyra Relay**.\n\n---\n\n### ⚙️ How to Hook It to Local Lyra\nLet’s do this in small working steps.\n\n#### **Step 1 — Get Lyra Relay’s local endpoint**\nIf you’re running your stack with Docker:\n```bash\ndocker ps\n```\nLook for the container called `relay`. \nIf your `.env` uses the default port, it should expose:\n\n```\nhttp://localhost:7078/v1/chat/completions\n```\n\nVerify:\n```bash\ncurl http://localhost:7078/v1/models\n```\nIf it responds (even with a simple JSON), Relay is live.\n\n---\n\n#### **Step 2 — Fill Trilium’s fields**\nIn Trilium’s AI/LLM settings:\n- **Enable AI/LLM features** ✅ \n- **Selected Provider:** `OpenAI`\n- **API Key:** \n You can type anything here (Trilium just needs a non-empty string). \n Example: `lyra-local`\n- **Base URL:** \n ```\n http://localhost:7078/v1\n ```\n- **Temperature:** `0.7` (fine to leave)\n- **System Prompt:** leave empty for now — Lyra already injects persona data.\n\nSave.\n\n---\n\n#### **Step 3 — Test**\nCreate a note, right-click → *AI / Summarize Note* (or similar). \nIf it responds with text, you’re successfully using **Lyra as Trilium’s brain**.\n\n---\n\nWould you like me to show how to make Relay automatically tag incoming Trilium requests (so they appear in NVGRAM with a `source: trilium` field)? That’s the next tiny step once the connection works." }, { "role": "user", "content": "https://docs.triliumnotes.org/user-guide/llm/intro\nhttps://docs.triliumnotes.org/user-guide/llm/providers\n\nCan you read that stuff?\n" }, { "role": "assistant", "content": "https://docs.triliumnotes.org/user-guide/llm/intro" }, { "role": "assistant", "content": "Trilium Notes LLM integration site:docs.triliumnotes.org" }, { "role": "assistant", "content": "Yes — I’ve looked through the documentation for entity[\"software\", \"Trilium Notes\", 0]’s **AI/LLM** features (from the links you shared). Here are the relevant highlights (verification mode) and how they apply to your setup with entity[\"software\", \"Lyra Relay\", 0].\n\n---\n\n### ✅ What the docs say \nFrom the “AI Provider Information” page: \n- Trilium currently supports several providers: entity[\"software\", \"Ollama\", 0], entity[\"organization\", \"OpenAI\", 0], entity[\"organization\", \"Anthropic\", 0], and mentions “Voyage AI”. citeturn1view0turn0view0 \n- It says: *“To set your preferred chat model, you’ll want to enter the provider’s name here”*. citeturn1view0turn0view0 \n- There’s an **Introduction** page (under AI) which presumably covers how the LLM/AI features work in Trilium. citeturn1search7turn0view0 \n\n---\n\n### 🤔 What this means for hooking up Lyra Relay \nSince your goal is to use Lyra Relay as the backend for Trilium’s AI features, we can map the docs’ info to your scenario:\n\n- Trilium expects a provider name and likely an endpoint (Base URL) consistent with that provider. \n- Even though Lyra Relay is not explicitly listed, if your Lyra Relay endpoint implements the same API schema as one of the supported providers (e.g., OpenAI-compatible), then you can essentially **pretend** the provider is “OpenAI” (or another supported one) and point the Base URL to your Relay. \n- Then you fill in an API key (Trilium requires something non-empty), and set the Base URL accordingly. \n- From a docs view: the workflow described in my previous message aligns well with this — i.e., choose “OpenAI” in Trilium’s config, but set Base URL to your Relay.\n\n---\n\n### ⚠️ A few caveats \n- The docs don’t explicitly say that **any** endpoint is accepted — they focus on the listed providers. That means if Lyra Relay’s API deviates significantly from the OpenAI/Anthropic spec, it might not work seamlessly. \n- There appear to be some bugs/issues noted by users with changing providers or Base URL fields in Trilium. For example: changing provider from OpenAI to Ollama doesn’t update Base URL in one issue. citeturn1search4 \n- The “Introduction” page may contain additional configuration details (e.g., for embeddings, system prompts, etc.) that you should review to ensure you’re covering any extra Trilium-specific settings.\n\n---\n\nIf you like, I can **pull out and summarise the full “Introduction” page** (from the docs) and highlight exactly all the configurable fields in Trilium’s AI/LLM settings (so you know every option) — would that be useful?" }, { "role": "user", "content": "will i eventually be able to have lyra go in and write notes herself?" }, { "role": "assistant", "content": "Yes — absolutely. \nOnce you bridge Trilium’s API with your **Lyra Relay**, she’ll be able to **create, edit, and tag notes automatically** — not just respond to them. \n\nLet’s break down how it’ll work and what’s needed, step by step.\n\n---\n\n### 🧠 Stage 1 — Trilium → Lyra (working now)\nYou’re already almost here:\n- Trilium sends note content to Lyra via the OpenAI-style API.\n- Lyra replies with summaries or rewritten text.\n✅ That’s “Lyra *reacting* to notes.”\n\n---\n\n### ✍️ Stage 2 — Lyra → Trilium (the next layer)\nTo make Lyra *proactive*, she needs access to Trilium’s **REST API**.\n\nTrilium exposes an API at:\n```\nhttp://localhost:37840/api/\n```\n(if running locally)\n\nYou can authenticate with your normal Trilium token (`Authorization: Bearer `).\n\nThat gives you endpoints like:\n- `POST /api/notes` → create a new note \n- `PUT /api/notes/{id}` → update a note \n- `GET /api/notes` → search or list \n- `POST /api/attributes` → add tags or relationships \n\nLyra Relay can call these directly from Node (using `fetch` or `axios`).\n\n---\n\n### ⚙️ Stage 3 — Wiring it up\nOnce you decide *when* she’s allowed to write:\n1. Add Trilium’s API base and token to Lyra’s `.env`:\n ```env\n TRILIUM_API=http://localhost:37840/api\n TRILIUM_TOKEN=your_auth_token_here\n ```\n2. In Relay (or Cortex), create a helper function like:\n ```js\n async function createTriliumNote(title, content, parentId) {\n const res = await fetch(`${process.env.TRILIUM_API}/notes`, {\n method: \"POST\",\n headers: {\n \"Authorization\": `Bearer ${process.env.TRILIUM_TOKEN}`,\n \"Content-Type\": \"application/json\"\n },\n body: JSON.stringify({ title, content, parentNoteId: parentId })\n });\n return res.json();\n }\n ```\n3. Then tell Lyra *when* to use it — e.g., after a long session summary or memory consolidation cycle.\n\n---\n\n### 🌿 Stage 4 — Executive Function\nThat’s when Lyra can:\n- Create daily journals automatically (“Today we worked on NVGRAM schema v0.1.2…”)\n- Summarize entire chat sessions and drop them into a “Logs” branch\n- Cross-link notes via Trilium’s attributes (“link this summary to Project Lyra > Cortex VM”)\n\n---\n\nIf you’d like, we can start **Stage 2** next: enabling API access so Lyra can create one note in Trilium as a test (very safe, sandbox-style). \n\nWant me to walk you through that setup next?" }, { "role": "user", "content": "SOunds like cortex should probably do this? " }, { "role": "assistant", "content": "Exactly — 💡 you nailed it. \n\nCortex is **the perfect module** for that job. \nHere’s why, in simple terms:\n\n---\n\n### 🧩 Division of Labor\n| Module | Role | Analogy |\n|--------|------|----------|\n| **Relay** | The “mouth” — takes your input, fetches memories, and speaks back. | Front-of-house conversation |\n| **NVGRAM** | The “memory banks.” | Long-term storage |\n| **Cortex** | The “executive brain.” | Decides what to think, summarize, or do next |\n\n---\n\n### 🧠 Why Cortex Should Handle Trilium Writes\n1. **Autonomy Zone:** \n Cortex is already meant to run background reasoning (“reflect”, “summarize”, “plan”). \n So giving it the ability to **push notes into Trilium** fits perfectly.\n\n2. **Timing Control:** \n Relay reacts instantly to user prompts, but Cortex can act on a schedule — \n e.g. “Every night at midnight, summarize today’s work and post to Trilium.”\n\n3. **Safety Layer:** \n You can sandbox Cortex with a whitelist — e.g. only allow it to use:\n ```bash\n POST /api/notes\n PUT /api/notes/{id}\n ```\n …so she can’t modify sensitive notes by mistake.\n\n4. **Reflection Pipeline:** \n Intake → Cortex Reflect → Trilium export. \n That becomes Lyra’s “sleep” or “dream” cycle: processing what happened, writing it down.\n\n---\n\n### 🔧 Architecture Vision (Stage 3)\n```\n[Relay] → [Intake Summaries]\n ↓\n [Cortex]\n (Reflect + Decide)\n ↓\n [Trilium API Notes]\n ↓\n [NVGRAM cross-links]\n```\n\nCortex would:\n1. Pull the last 24 h of Intake summaries. \n2. Generate a reflection note (“Lyra Daily Log”). \n3. Call Trilium’s API to post it under a “/Lyra Logs/” parent. \n4. Optionally write a short NVGRAM memory linking to that Trilium note’s ID.\n\n---\n\nIf you want, I can show you the **tiny Python script** that would let Cortex post a note to Trilium — \nsomething like `reflector.py` you can drop into the container and call from `cron` or `loop()`. \n\nWant to do that next?" } ] }