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`image_in` is not just the mention switch any more: the table names where each image-carrying path is gated, and says why the gate exists — a text-only model answers `[Unsupported Image]`, and a gateway that cannot read image blocks feeds the model raw base64, which is easy to mistake for a delivered picture.
127 lines
6.0 KiB
Markdown
127 lines
6.0 KiB
Markdown
# Images
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A model that takes pictures can look at a screenshot, a chart, or a diagram
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instead of reading a description of it. plyngent carries images as content
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parts on messages; each wire surface lifts them into its own shape.
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## Shape
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`lmproto/openai_compatible/model.py`:
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| Type | Meaning |
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|---|---|
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| `ChatImageUrl(url, detail)` | one picture: an `http(s)` link or an inline `data:` URL |
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| `ChatImagePart(image_url)` | that payload as a `{"type": "image_url"}` block |
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| `ChatTextPart(text)` | the text block beside images |
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| `UserChatMessage.content` | `str`, or `list[ChatTextPart \| ChatImagePart]` when the turn carries pictures |
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| `ToolChatMessage.images` | the pictures a tool returned, beside its text `content` |
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Prose-only readers go through `content_to_text`, which renders each image as
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`[image]` (summaries, transcripts, exports, the retry preview).
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`agent/images.py` owns the bytes: it sniffs the format from the file's content
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(JPEG `ff d8 ff`, PNG, GIF, WebP `RIFF….WEBP`), builds the data URL, and caps an
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inline picture at `MAX_INLINE_IMAGE_BYTES` (8 MiB) — far below what a provider
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accepts, because the message is re-sent every round and lives in the session's
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JSON message column.
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## Per surface
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| Surface | A user turn's images | A tool result's images |
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|---|---|---|
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| chat completions (`compat.chat_messages_with_images`) | already content blocks | a `tool` message may only carry text, so the images move into the user turn emitted right after the tool run |
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| Anthropic `/messages` (`messages_bridge`) | `image` blocks beside the text block | inside the `tool_result` block's content, beside a text block |
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| Responses (`responses_bridge`) | `input_text` + `input_image` parts | in the `function_call_output` item's `output` array |
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A chat-completions request drops the parts of a message it cannot express; no
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history is rewritten (the stored message keeps its own images).
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## Limits (provider side)
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| Limit | Value |
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|---|---|
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| Formats | JPEG, PNG, GIF, WebP (sniffed from bytes, never the file name) |
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| Request body | 48 MiB |
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| One image, inline or URL | 32 MiB |
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| One image, Files API `file_id` | 64 MiB |
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| Images per request | 600 |
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| Image side | 8192 px, or 4096 px when a request holds 15+ images |
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| External URL | 8192 characters, downloaded within 60 s |
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| Tokens per image | at most 1024 (a picture is resized to ~1300x1300 px, and one below ~544x544 is scaled up) |
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Images belong to **user** messages only: a picture in a system or assistant
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message is a 400 (`Image in assistant message is unsupported`). A tool result
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lives inside a user turn, which is why it can carry one.
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## Verified against the DeepSeek API
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The 2026-10-17 docs plus a live probe (`deepseek-flash`):
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- the same picture is accepted on all three surfaces, and the usage is identical;
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- an image inside `tool_result` content works, and the model reads it — the
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round that asked for a screenshot got the layout, the colours and the pixel
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span back;
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- an image inside `function_call_output` works too (the round needs its
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`reasoning` item, which `responses_bridge` already sends);
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- `detail: "low"` measured 3.4x cheaper than `original` on a 1200x900 picture
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(240 vs 708 prompt tokens) with no loss on "which colour where"; the floor is
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210 tokens even for a tiny picture, because small images are scaled up;
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- re-sending a picture in a later round hits the provider's prefix cache
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(`cache_read_input_tokens`), so the "history is paid for again" cost is not
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the worst case;
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- `/anthropic/messages` and `/anthropic/v1/messages` both answer, so the
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client's path stays as it is.
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## Attaching one
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Type `@path` in the line — no command, no separate step:
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```
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what is wrong with this layout? @shots/broken.png
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```
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`cli/mentions.py` reads the token (whitespace-delimited, `@"path with spaces"`
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for names that hold one; an e-mail address is not a mention), resolves it against
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the working directory, checks the path denylist, and attaches it. An image
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becomes an image part; any other file is appended as text under a
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`--- @path ---` header, capped like a tool result (its `truncate_token` keeps the
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remainder resumable). A problem — a missing file, a denylisted path, a picture a
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text-only model cannot take — prints a note and leaves the turn going.
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Tab completes the path after `@` (directories end in `/`, a name with a space is
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completed in its quoted form).
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## Opting in
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`[providers.<name>.models."<model>"].image_in` is the gate, and it covers every
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way a picture can enter a turn — not only an `@image` mention:
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| Path | Where it is gated |
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|---|---|
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| an `@image` mention (`cli/mentions.py`) | skipped, with a note naming the key |
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| the `view_image` tool | `error: model '…' does not accept image input (set image_in = true under [providers.x.models."y"])` |
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| an image body from `fetch_local` | the metadata stays, the picture is left behind with the same reason |
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| an MCP server's image content, a plugin's `ToolOutput` | dropped by the registry's safety net (`agent/tools.py`), with the reason appended to the text |
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`ReplState.sync_image_capability` publishes the selected model's verdict on
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`InstanceState.workspace` and runs on every provider/model/client rebuild, so a
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`/model` switch flips the gate at once. A host that binds no instance declares
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nothing, and the picture is sent as usual.
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The point is to fail loudly: without the gate a text-only model answers
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`[Unsupported Image]` one round later, and a gateway that cannot read image
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blocks hands the model raw base64 — which reads like the picture arrived when it
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did not.
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The default catalogs mark what takes pictures (`deepseek-flash` yes,
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`deepseek-v4-pro` no, OpenAI's defaults yes). A model missing from the catalog
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has to be declared: the flag is an explicit opt-in.
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## Not implemented
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- **Files API** (`POST /files` → `file_id`): it lifts the 32 MiB per-image cap
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and avoids re-uploading the same bytes, but it does not change the token bill
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(the model still processes the picture in every request that carries it), so a
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local 8 MiB cap plus resizing covers the common case.
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- **Image output**: the API documents none.
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