# Image API
This is an Actix-web server for serving images and videos from a filesystem.
Upon first run it will generate thumbnails for all images and videos at `BASE_PATH`.

## Features
- Automatic thumbnail generation for images and videos
- EXIF data extraction and storage for photos
- File watching with NFS support (polling-based)
- Video streaming with HLS
- Tag-based organization
- Memories API for browsing photos by date
- **Video Wall** - Auto-generated short preview clips for videos, served via a grid view
- **AI-Powered Photo Insights** - Generate contextual insights from photos using LLMs
- **RAG-based Context Retrieval** - Semantic search over daily conversation summaries
- **Automatic Daily Summaries** - LLM-generated summaries of daily conversations with embeddings

## External Dependencies

### ffmpeg (required)
`ffmpeg` must be on `PATH`. It is used for:
- **HLS video streaming** — transcoding/segmenting source videos into `.m3u8` + `.ts` playlists
- **Video thumbnails** — extracting a frame at the 3-second mark
- **Video preview clips** — short looping previews for the Video Wall
- **HEIC / HEIF thumbnails** — decoding Apple's HEIC format (your ffmpeg build must include
  `libheif`; most modern builds do)

Builds used in development: the `gyan.dev` full build on Windows, and distro `ffmpeg`
packages on Linux work fine. If HEIC thumbnails silently fail, check
`ffmpeg -formats | grep heif` to confirm HEIF support.

### RAW photo thumbnails
RAW formats (ARW, NEF, CR2, CR3, DNG, RAF, ORF, RW2, PEF, SRW, TIFF) are thumbnailed
by reading an embedded JPEG preview out of the TIFF container — no external RAW
decoder (libraw / dcraw) is involved. The pipeline tries two layers in order and
keeps the largest valid JPEG:

1. **Fast path (no extra dependency)** — `kamadak-exif` reads
   `JPEGInterchangeFormat` from IFD0 / IFD1 directly. Covers older bodies and
   most DNGs.
2. **`exiftool` fallback (recommended for RAW-heavy libraries)** — shells out
   to extract `PreviewImage` / `JpgFromRaw` / `OtherImage`, which reaches
   MakerNote and SubIFD-hosted previews kamadak-exif can't see (e.g. Nikon's
   `PreviewIFD`, where modern Nikon bodies stash the full-res review JPEG).
   If `exiftool` isn't on `PATH` this layer is skipped silently and only the
   fast-path result is used.

Install `exiftool` via your package manager:
- macOS: `brew install exiftool`
- Linux (Debian/Ubuntu): `apt install libimage-exiftool-perl`
- Windows: `winget install OliverBetz.ExifTool` or `choco install exiftool`

Files where neither layer produces a valid preview fall back to ffmpeg. Anything
that still can't be decoded is marked with a `<thumb>.unsupported` sentinel in
the thumbnail directory so we don't retry it every scan. Delete those sentinels
(and any cached black thumbnails) to force retries after a tooling upgrade.

## Environment
There are a handful of required environment variables to have the API run.
They should be defined where the binary is located or above it in an `.env` file.

- `DATABASE_URL` is a path or url to a database (currently only SQLite is tested)
- `BASE_PATH` is the root from which you want to serve images and videos
- `THUMBNAILS` is a path where generated thumbnails should be stored. Thumbnails
  mirror the source tree under `BASE_PATH` and keep the source's original
  extension (e.g. `foo.arw` or `bar.mp4`), though the file contents are always
  JPEG bytes — browsers content-sniff. Files that can't be thumbnailed by the
  `image` crate, ffmpeg, or an embedded RAW preview get a zero-byte
  `<thumb_path>.unsupported` sentinel in this directory so subsequent scans
  skip them. Delete the `*.unsupported` files to force retries (for example
  after upgrading ffmpeg or adding libheif)
- `VIDEO_PATH` is a path where HLS playlists and video parts should be stored
- `GIFS_DIRECTORY` is a path where generated video GIF thumbnails should be stored
- `BIND_URL` is the url and port to bind to (typically your own IP address)
- `SECRET_KEY` is the *hopefully* random string to sign Tokens with
- `RUST_LOG` is one of `off, error, warn, info, debug, trace`, from least to most noisy [error is default]
- `EXCLUDED_DIRS` is a comma separated list of directories to exclude from the Memories API
- `PREVIEW_CLIPS_DIRECTORY` (optional) is a path where generated video preview clips should be stored [default: `preview_clips`]
- `WATCH_QUICK_INTERVAL_SECONDS` (optional) is the interval in seconds for quick file scans [default: 60]
- `WATCH_FULL_INTERVAL_SECONDS` (optional) is the interval in seconds for full file scans [default: 3600]

### AI Insights Configuration (Optional)

The following environment variables configure AI-powered photo insights and daily conversation summaries:

#### Ollama Configuration
- `OLLAMA_PRIMARY_URL` - Primary Ollama server URL [default: `http://localhost:11434`]
  - Example: `http://desktop:11434` (your main/powerful server)
- `OLLAMA_FALLBACK_URL` - Fallback Ollama server URL (optional)
  - Example: `http://server:11434` (always-on backup server)
- `OLLAMA_PRIMARY_MODEL` - Model to use on primary server [default: `nemotron-3-nano:30b`]
  - Example: `nemotron-3-nano:30b`, `llama3.2:3b`, etc.
- `OLLAMA_FALLBACK_MODEL` - Model to use on fallback server (optional)
  - If not set, uses `OLLAMA_PRIMARY_MODEL` on fallback server

**Legacy Variables** (still supported):
- `OLLAMA_URL` - Used if `OLLAMA_PRIMARY_URL` not set
- `OLLAMA_MODEL` - Used if `OLLAMA_PRIMARY_MODEL` not set

#### OpenRouter Configuration (Hybrid Backend)
The hybrid agentic backend keeps embeddings + vision local (Ollama) while routing
chat + tool-calling to OpenRouter. Enabled per-request when the client sends
`backend=hybrid`.

- `OPENROUTER_API_KEY` - OpenRouter API key. Required to enable the hybrid backend.
- `OPENROUTER_DEFAULT_MODEL` - Model id used when the client doesn't specify one
  [default: `anthropic/claude-sonnet-4`]
  - Example: `openai/gpt-4o-mini`, `google/gemini-2.5-flash`
- `OPENROUTER_ALLOWED_MODELS` - Comma-separated curated allowlist exposed to
  clients via `GET /insights/openrouter/models`. The mobile picker shows only
  these. Empty/unset = no picker, server default is used.
  - Example: `openai/gpt-4o-mini,anthropic/claude-haiku-4-5,google/gemini-2.5-flash`
- `OPENROUTER_BASE_URL` - Override base URL [default: `https://openrouter.ai/api/v1`]
- `OPENROUTER_EMBEDDING_MODEL` - Embedding model for OpenRouter
  [default: `openai/text-embedding-3-small`]. Only used if/when embeddings are
  routed through OpenRouter (currently embeddings stay local).
- `OPENROUTER_HTTP_REFERER` - Optional `HTTP-Referer` for OpenRouter attribution
- `OPENROUTER_APP_TITLE` - Optional `X-Title` for OpenRouter attribution

Capability checks are skipped for the curated allowlist — bad model ids surface
as a 4xx from the chat call. Pick tool-capable models.

#### SMS API Configuration
- `SMS_API_URL` - URL to SMS message API [default: `http://localhost:8000`]
  - Used to fetch conversation data for context in insights
- `SMS_API_TOKEN` - Authentication token for SMS API (optional)

#### Agentic Insight Generation
- `AGENTIC_MAX_ITERATIONS` - Maximum tool-call iterations per agentic insight request [default: `10`]
  - Controls how many times the model can invoke tools before being forced to produce a final answer
  - Increase for more thorough context gathering; decrease to limit response time

#### Insight Chat Continuation
After an agentic insight is generated, the conversation can be continued. Endpoints:
- `POST /insights/chat` — single-turn reply (non-streaming)
- `POST /insights/chat/stream` — SSE variant with live `text` deltas and
  `tool_call` / `tool_result` events. Mobile client uses this.
- `GET /insights/chat/history?path=...&library=...` — rendered transcript;
  each assistant message carries a `tools: [{name, arguments, result}]` array
- `POST /insights/chat/rewind` — truncate transcript at a rendered index
  (drops that message + any preceding tool scaffolding + later turns). Used
  for "try again from here" flows. The initial user message is protected.

Amend mode (`amend: true` in the chat request body) regenerates the insight's
title and inserts a new row instead of appending to the existing transcript,
so you can rewrite the saved summary from within chat.

- `AGENTIC_CHAT_MAX_ITERATIONS` - Cap on tool-calling iterations per chat turn [default: `6`]
  - Per-request `max_iterations` (when sent by the client) is clamped to this cap

#### Fallback Behavior
- Primary server is tried first with 5-second connection timeout
- On failure, automatically falls back to secondary server (if configured)
- Total request timeout is 120 seconds to accommodate LLM inference
- Logs indicate which server/model was used and any failover attempts

#### Daily Summary Generation
Daily conversation summaries are generated automatically on server startup. Configure in `src/main.rs`:
- Date range for summary generation
- Contacts to process
- Model version used for embeddings: `nomic-embed-text:v1.5`

### Apollo + Face Recognition (Optional)

Apollo (sibling project) hosts both the Places API and the local insightface
inference service. Both integrations are optional and degrade gracefully when
unset.

- `APOLLO_API_BASE_URL` - Base URL of the sibling Apollo backend.
  - When set, photo-insight enrichment folds the user's personal place name
    (Home, Work, Cabin, ...) into the location string, and the agentic loop
    gains a `get_personal_place_at` tool. Unset = legacy Nominatim-only path.
- `APOLLO_FACE_API_BASE_URL` - Base URL for the face-detection service.
  - Falls back to `APOLLO_API_BASE_URL` when unset (typical single-Apollo
    deploy). Both unset = face feature disabled (file-watch hook and
    manual-face endpoints short-circuit silently).
- `FACE_AUTOBIND_MIN_COS` (Phase 3) - Cosine-sim floor for auto-binding a
  detected face to an existing same-named person via people-tag bootstrap
  [default: `0.4`].
- `FACE_DETECT_CONCURRENCY` (Phase 3) - Per-scan-tick concurrent detect
  calls fired by the file watcher [default: `8`]. Apollo serializes them
  via its single-worker GPU pool.
- `FACE_DETECT_TIMEOUT_SEC` - reqwest client timeout per detect call
  [default: `60`]. CPU inference on a backlog can take many seconds.