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docs/services/individual/anythingllm.md

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+# AnythingLLM
+
+**Local RAG Document Assistant**
+
+## Service Overview
+
+| Property | Value |
+|----------|-------|
+| **Service Name** | anythingllm |
+| **Host** | atlantis |
+| **Category** | AI |
+| **Docker Image** | `mintplexlabs/anythingllm:latest` |
+| **Compose File** | `hosts/synology/atlantis/anythingllm/docker-compose.yml` |
+| **Port** | 3101 |
+| **URL** | `http://192.168.0.200:3101` |
+
+## Purpose
+
+AnythingLLM is a self-hosted, local-first document assistant powered by RAG (Retrieval-Augmented Generation). It indexes documents into a vector database, then uses a local LLM to answer questions with context from those documents.
+
+Primary use cases:
+- Semantic search across all Paperless-NGX documents (355 docs as of 2026-03-15)
+- Natural language Q&A over document library ("find my 2024 property tax assessment")
+- Document summarization ("summarize my medical records")
+
+## Architecture
+
+```
+AnythingLLM (atlantis:3101)
+├── Embedder: built-in all-MiniLM-L6-v2 (CPU, runs locally)
+├── Vector DB: built-in LanceDB (no external service)
+├── LLM: Olares qwen3-coder:latest (30B MoE, RTX 5090)
+│   └── Endpoint: https://a5be22681.vishinator.olares.com/v1
+└── Documents: Paperless-NGX archive (mounted read-only)
+```
+
+## Configuration
+
+Configuration is done through the web UI on first launch at `http://192.168.0.200:3101`.
+
+### LLM Provider Setup
+
+| Setting | Value |
+|---------|-------|
+| **Provider** | Generic OpenAI |
+| **Base URL** | `https://a5be22681.vishinator.olares.com/v1` |
+| **Model** | `qwen3-coder:latest` |
+| **Token Limit** | 65536 |
+| **API Key** | (leave blank or any string — Olares auth is bypassed for this endpoint) |
+
+### Embedding Setup
+
+| Setting | Value |
+|---------|-------|
+| **Provider** | AnythingLLM (built-in) |
+| **Model** | all-MiniLM-L6-v2 |
+
+No external embedding service needed. Runs on CPU inside the container.
+
+### Vector Database
+
+| Setting | Value |
+|---------|-------|
+| **Provider** | LanceDB (built-in) |
+
+No external vector DB service needed. Data stored in the container volume.
+
+## Volumes
+
+| Container Path | Host Path | Purpose |
+|----------------|-----------|---------|
+| `/app/server/storage` | `/volume2/metadata/docker/anythingllm/storage` | Config, vector DB, user data |
+| `/documents/paperless-archive` | `/volume1/archive/paperless/backup_2026-03-15/media/documents/archive` | OCR'd Paperless PDFs (read-only) |
+| `/documents/paperless-originals` | `/volume1/archive/paperless/backup_2026-03-15/media/documents/originals` | Original Paperless uploads (read-only) |
+
+## Document Import
+
+After initial setup via the UI:
+
+1. Create a workspace (e.g., "Documents")
+2. Open the workspace, click the upload/document icon
+3. Browse to `/documents/paperless-archive` — these are OCR'd PDFs with searchable text
+4. Select all files and embed them into the workspace
+5. AnythingLLM will chunk, embed, and index all documents
+
+The archive directory contains 339 OCR'd PDFs; originals has 355 files (includes non-PDF formats that Tika processed).
+
+## Paperless-NGX Backup
+
+The documents served to AnythingLLM come from a Paperless-NGX backup taken 2026-03-15:
+
+| Property | Value |
+|----------|-------|
+| **Source** | calypso `/volume1/docker/paperlessngx/` |
+| **Destination** | atlantis `/volume1/archive/paperless/backup_2026-03-15/` |
+| **Size** | 1.6 GB |
+| **Documents** | 355 total (339 with OCR archive) |
+| **Previous backup** | `/volume1/archive/paperless/paperless_backup_2025-12-03.tar.gz` |
+
+## Dependencies
+
+- **Olares** must be running with `qwen3-coder:latest` loaded. We standardized AnythingLLM and Perplexica on `qwen3-coder` to avoid VRAM swap cycles REDACTED_APP_PASSWORD use `qwen3:32b`. See [AI Integrations](../../admin/ai-integrations.md) for the migration history.
+- Olares endpoint must be accessible from atlantis LAN (192.168.0.145)
+- No dependency on atlantis Ollama (stopped — not needed)
+
+## Troubleshooting
+
+| Issue | Cause | Fix |
+|-------|-------|-----|
+| LLM responses fail | Olares `qwen3-coder:latest` not running | Check: `ssh olares "sudo kubectl get pods -n ollamaserver-shared"` and scale up if needed |
+| Slow embedding | Expected on CPU (Ryzen V1780B) | Initial 355-doc ingestion may take a while; subsequent queries are fast |
+| Empty search results | Documents not yet embedded | Check workspace → documents tab, ensure files are uploaded and embedded |
+| 502 from Olares endpoint | Model loading / pod restarting | Wait 2-3 min, check Olares pod status |