# Plan: Vision — Image Understanding Capability

**Goal:** Maven can "see" — accept images (from mavweb upload, Telegram, or filesystem paths), run vision inference via a local or remote multimodal model, and answer questions about the image content or extract structured information.

**Done when:**
- Vision model backend is configurable: local multimodal LLM (e.g., LLaVA, Qwen-VL via `llama-server` mmproj) or remote API
- `internal/vision/` package handles image preprocessing, model inference, result parsing
- Voice/text commands like "что на картинке?" or "прочитай текст с экрана" route to the vision handler
- Extracted information can be written as facts/notes through `ipc.CoreAPI`
- Telegram image messages are processed through the same pipeline

**Scope:**
- New `internal/vision/` package — image loader (Go stdlib `image` + `golang.org/x/image`), inference client
- New config block: `voice.vision` in `config.Config` — `{enabled, provider, model_path, mmproj_path, remote_url}`
- Router intent extension: new `IntentVision` or reuse `IntentQuery` with a vision flag
- Reuses `internal/llm.Client` for API-compatible backends (OpenAI-compatible vision API)
- Reuses `internal/ipc.CoreAPI` for writing extracted data

**Steps:**
1. Create `internal/vision/provider.go` — `Provider` interface with `Describe(image []byte, prompt string) (string, error)` and `ExtractText(image []byte) (string, error)`
2. Implement `LocalProvider` — spawns `llama-server` with mmproj, sends multimodal chat completion requests
3. Implement `RemoteProvider` — calls an OpenAI-compatible vision API endpoint, reuses `internal/llm.Client`
4. Create `internal/vision/processor.go` — image preprocessing (resize, format conversion to JPEG/PNG, base64 encoding)
5. Wire vision into `cmd/mavend/voice.go:reactiveHandler` — detect vision intent from router (new `IntentVision` or a `Slots.HasImage` flag)
6. Add IPC method `MethodDescribeImage` for programmatic access (mavweb upload, telegram bot)
7. Add vision config block to `config.Config` and wire in `cmd/mavend/main.go`
8. Test with a local multimodal model: send an image via mavweb, verify description and text extraction