Add image upload in conversation

This commit is contained in:
Xin Wang
2026-06-02 08:24:53 +08:00
parent f22df60873
commit 21f6c17388
11 changed files with 622 additions and 8 deletions

View File

@@ -70,7 +70,8 @@
"app_id": "6a153aed53e3f8d9f2744905",
"variables": {},
"detail": false,
"timeout_sec": 60.0
"timeout_sec": 60.0,
"image_input_mode": "base64"
},
"tts": {
"provider": "xfyun",

View File

@@ -148,6 +148,8 @@ class LLMConfig:
variables: dict[str, str] = field(default_factory=dict)
detail: bool = False
timeout_sec: float = 60.0
# FastGPT image input mode: "base64" (inline data URL) or "upload" (presigned upload).
image_input_mode: str = "base64"
@property
def is_fastgpt(self) -> bool:
@@ -257,6 +259,15 @@ def config_from_dict(data: dict) -> EngineConfig:
llm["app_id"] = None
if not isinstance(llm.get("variables"), dict):
llm["variables"] = {}
image_input_mode = str(
llm.get("image_input_mode", LLMConfig().image_input_mode)
).strip().lower()
if image_input_mode not in {"base64", "upload"}:
raise ValueError(
"services.llm.image_input_mode must be 'base64' or 'upload', "
f"got {llm.get('image_input_mode')!r}"
)
llm["image_input_mode"] = image_input_mode
if agent.get("greeting_mode") == "fastgpt_opener" and llm["provider"] != "fastgpt":
raise ValueError(
"agent.greeting_mode='fastgpt_opener' requires services.llm.provider='fastgpt'"

View File

@@ -1,7 +1,11 @@
from __future__ import annotations
import asyncio
import base64
import binascii
import json
import os
import tempfile
import uuid
from dataclasses import dataclass, field
from typing import Any
@@ -73,6 +77,50 @@ def _message_text(message: dict[str, Any]) -> str:
return ""
IMAGE_INPUT_MODE_BASE64 = "base64"
IMAGE_INPUT_MODE_UPLOAD = "upload"
SUPPORTED_IMAGE_INPUT_MODES = frozenset({IMAGE_INPUT_MODE_BASE64, IMAGE_INPUT_MODE_UPLOAD})
_MIME_TO_EXT = {
"image/jpeg": ".jpg",
"image/png": ".png",
"image/webp": ".webp",
}
def _message_has_image(message: dict[str, Any]) -> bool:
content = message.get("content")
if not isinstance(content, list):
return False
return any(
isinstance(part, dict) and part.get("type") == "image_url"
for part in content
)
def _redact_messages_for_log(messages: list[dict[str, Any]]) -> list[dict[str, Any]]:
"""Replace base64 image data URLs with a short placeholder for logging."""
redacted: list[dict[str, Any]] = []
for message in messages:
content = message.get("content")
if not isinstance(content, list):
redacted.append(message)
continue
parts: list[Any] = []
for part in content:
if (
isinstance(part, dict)
and part.get("type") == "image_url"
and isinstance(part.get("image_url"), dict)
):
url = str(part["image_url"].get("url") or "")
parts.append({"type": "image_url", "image_url": {"url": f"<{len(url)} chars>"}})
else:
parts.append(part)
redacted.append({**message, "content": parts})
return redacted
def _first_nonempty_text(*values: Any) -> str:
for value in values:
if isinstance(value, str):
@@ -172,6 +220,7 @@ class FastGPTLLMService(LLMService):
app_id: str | None = None,
greeting_prompt: str | None = None,
timeout: float = 60.0,
image_input_mode: str = IMAGE_INPUT_MODE_BASE64,
settings: FastGPTLLMSettings | None = None,
**kwargs,
) -> None:
@@ -183,6 +232,20 @@ class FastGPTLLMService(LLMService):
self._chat_id = chat_id or f"voice_{uuid.uuid4().hex[:16]}"
self._app_id = (app_id or "").strip()
self._greeting_prompt = (greeting_prompt or "你好").strip() or "你好"
mode = (image_input_mode or IMAGE_INPUT_MODE_BASE64).strip().lower()
if mode not in SUPPORTED_IMAGE_INPUT_MODES:
raise ValueError(
f"Unsupported image_input_mode {image_input_mode!r}; "
f"expected one of {sorted(SUPPORTED_IMAGE_INPUT_MODES)}"
)
if mode == IMAGE_INPUT_MODE_UPLOAD and not self._app_id:
logger.warning(
"FastGPT image_input_mode='upload' requires app_id; "
"falling back to inline base64"
)
mode = IMAGE_INPUT_MODE_BASE64
self._image_input_mode = mode
self._client = AsyncChatClient(
api_key=api_key,
base_url=base_url,
@@ -310,26 +373,114 @@ class FastGPTLLMService(LLMService):
if response is not None:
await response.aclose()
def _build_fastgpt_messages(self, context: LLMContext) -> list[dict[str, str]]:
def _build_fastgpt_messages(self, context: LLMContext) -> list[dict[str, Any]]:
raw_messages = context.get_messages()
for message in reversed(raw_messages):
if not isinstance(message, dict) or message.get("role") != "user":
continue
if _message_has_image(message):
# Multimodal turn: forward the OpenAI-style content list as-is
# (text parts + image_url with a base64 data URL). FastGPT's
# /chat/completions accepts this directly.
return [{"role": "user", "content": message["content"]}]
text = _message_text(message)
if text:
return [{"role": "user", "content": text}]
return [{"role": "user", "content": self._greeting_prompt}]
async def _resolve_image_inputs(
self, messages: list[dict[str, Any]]
) -> list[dict[str, Any]]:
"""In ``upload`` mode, replace inline base64 image data URLs with uploaded URLs.
In ``base64`` mode the messages are returned untouched (inline data URLs).
New message/content objects are built so the shared ``LLMContext`` messages
are never mutated.
"""
if self._image_input_mode != IMAGE_INPUT_MODE_UPLOAD:
return messages
resolved: list[dict[str, Any]] = []
for message in messages:
content = message.get("content")
if not isinstance(content, list):
resolved.append(message)
continue
new_content: list[Any] = []
for part in content:
url = (
part.get("image_url", {}).get("url")
if isinstance(part, dict) and part.get("type") == "image_url"
else None
)
if isinstance(url, str) and url.startswith("data:image/"):
uploaded = await self._upload_data_url(url)
new_content.append(
{"type": "image_url", "image_url": {"url": uploaded}}
)
else:
new_content.append(part)
resolved.append({**message, "content": new_content})
return resolved
async def _upload_data_url(self, data_url: str) -> str:
"""Upload a ``data:image/...;base64,...`` URL via FastGPT and return its URL.
Falls back to the original data URL if parsing or upload fails so the turn
still proceeds with inline base64.
"""
header, _, payload = data_url.partition(",")
mime_type = header[len("data:") :].split(";", 1)[0].strip() or "image/jpeg"
try:
raw = base64.b64decode(payload, validate=True)
except (binascii.Error, ValueError) as exc:
logger.warning(f"FastGPT image upload skipped; invalid base64: {exc}")
return data_url
suffix = _MIME_TO_EXT.get(mime_type, ".jpg")
tmp_path: str | None = None
try:
with tempfile.NamedTemporaryFile(suffix=suffix, delete=False) as tmp:
tmp.write(raw)
tmp_path = tmp.name
result = await self._client.upload_chat_image(
appId=self._app_id,
chatId=self._chat_id,
file_path=tmp_path,
)
url = result.get("url") if isinstance(result, dict) else None
if isinstance(url, str) and url:
logger.info(
f"FastGPT image uploaded chatId={self._chat_id} "
f"bytes={len(raw)} url={url}"
)
return url
logger.warning("FastGPT image upload returned no url; using inline base64")
return data_url
except Exception as exc:
logger.warning(f"FastGPT image upload failed; using inline base64: {exc}")
return data_url
finally:
if tmp_path is not None:
try:
os.unlink(tmp_path)
except OSError:
pass
async def _process_context(self, context: LLMContext) -> None:
messages = self._build_fastgpt_messages(context)
messages = await self._resolve_image_inputs(messages)
variables = self._settings.variables or None
logger.info(
"FastGPT chat completion "
f"chatId={self._chat_id} appId={self._app_id or '-'} "
f"variables={sorted((variables or {}).keys())} messages={messages!r}"
f"variables={sorted((variables or {}).keys())} "
f"messages={_redact_messages_for_log(messages)!r}"
)
await self.start_ttfb_metrics()

View File

@@ -65,6 +65,7 @@ def create_llm_service(
app_id=config.app_id,
greeting_prompt=greeting_prompt,
timeout=config.timeout_sec,
image_input_mode=config.image_input_mode,
settings=FastGPTLLMSettings(
model=config.model or "fastgpt",
variables=variables,

View File

@@ -24,6 +24,17 @@ const WS_LOG_GROUP_KEYS = {
AUDIO_SEND: "send:input.audio",
};
const CAMERA_DONE_TEXT = "【拍摄完成】";
// Sample images shown as thumbnails under the camera preview. Same-origin files
// so they can be drawn to a canvas (for base64 + dimensions) without tainting.
const SAMPLE_IMAGES = [
{ src: "./samples/front-damage.jpg", label: "车辆前部" },
{ src: "./samples/plate.jpg", label: "车牌" },
{ src: "./samples/license.jpg", label: "驾驶证" },
{ src: "./samples/scene.jpg", label: "事故现场" },
];
// Cap the longer edge before JPEG-encoding so payloads stay small.
const IMAGE_MAX_DIM = 1280;
const IMAGE_JPEG_QUALITY = 0.85;
const CAMERA_STATE_PROMPTS = {
2000: "请对准车辆碰撞部位拍摄照片。",
2001: "请对准车辆碰撞部位拍摄照片。",
@@ -62,6 +73,14 @@ const els = {
cameraState: document.getElementById("camera-state"),
cameraQuestion: document.getElementById("camera-question"),
cameraDoneBtn: document.getElementById("camera-done-btn"),
cameraPreview: document.getElementById("camera-preview"),
cameraVideo: document.getElementById("camera-video"),
cameraPhoto: document.getElementById("camera-photo"),
cameraCanvas: document.getElementById("camera-canvas"),
cameraStartBtn: document.getElementById("camera-start-btn"),
cameraFlipBtn: document.getElementById("camera-flip-btn"),
cameraUpload: document.getElementById("camera-upload"),
cameraSamples: document.getElementById("camera-samples"),
clearBtn: document.getElementById("clear-btn"),
clearWsLogBtn: document.getElementById("clear-ws-log-btn"),
wsLog: document.getElementById("ws-log"),
@@ -125,6 +144,13 @@ const state = {
assistantState: "",
cameraState: "",
// Camera / image input.
cameraStream: null,
cameraActive: false,
cameraFacing: "environment",
pendingImage: null,
samplesRendered: false,
// VU meter smoothing.
meterLevel: 0,
@@ -211,14 +237,16 @@ function setAssistantState(value) {
function setCameraButtonEnabled() {
if (!els.cameraDoneBtn) return;
els.cameraDoneBtn.disabled =
!state.connected || !state.cameraState ||
!state.ws || state.ws.readyState !== WebSocket.OPEN;
const wsReady =
state.connected && state.ws && state.ws.readyState === WebSocket.OPEN;
const hasImageSource = state.cameraActive || Boolean(state.pendingImage);
els.cameraDoneBtn.disabled = !wsReady || !state.cameraState || !hasImageSource;
}
function syncCameraDrawer(value) {
const prompt = CAMERA_STATE_PROMPTS[value];
const open = Boolean(prompt);
const wasOpen = Boolean(state.cameraState);
state.cameraState = open ? value : "";
els.cameraDrawer.classList.toggle("is-open", open);
els.conversation.classList.toggle("has-camera", open);
@@ -226,9 +254,11 @@ function syncCameraDrawer(value) {
if (open) {
els.cameraState.textContent = `State ${value}`;
els.cameraQuestion.textContent = prompt;
renderSampleThumbnails();
} else {
els.cameraState.textContent = "State -";
els.cameraQuestion.textContent = "";
if (wasOpen) resetCameraInput();
}
setCameraButtonEnabled();
}
@@ -260,6 +290,35 @@ function addBubble(role, text) {
return bubble;
}
// Render a single chat bubble holding an image and (optionally) text together.
function addImageBubble(role, imageUrl, text) {
if (els.chatLog.querySelector(".chat__empty")) {
els.chatLog.innerHTML = "";
}
const bubble = document.createElement("div");
bubble.className = `bubble bubble--${role}`;
if (role !== "system") {
const tag = document.createElement("span");
tag.className = "bubble__role";
tag.textContent = role === "user" ? "You" : "Assistant";
bubble.appendChild(tag);
}
const img = document.createElement("img");
img.className = "bubble__image";
img.src = imageUrl;
img.alt = text || "image";
bubble.appendChild(img);
const body = document.createElement("span");
body.className = "bubble__text";
body.textContent = text || "";
bubble.appendChild(body);
els.chatLog.appendChild(bubble);
scrollChatToBottom();
return bubble;
}
function appendToBubble(bubble, text) {
const body = bubble.querySelector(".bubble__text");
body.textContent += text;
@@ -499,6 +558,9 @@ function compactWsPayload(payload) {
if (typeof compact.audio === "string") {
compact.audio = `<base64 ${compact.audio.length} chars>`;
}
if (typeof compact.image === "string") {
compact.image = `<base64 ${compact.image.length} chars>`;
}
if (typeof compact.data === "string" && compact.data.length > 160) {
compact.data = `<string ${compact.data.length} chars>`;
}
@@ -807,6 +869,219 @@ function resetPlaybackClock() {
}
}
/* ------------------------------------------------------ Camera / image */
function setPreviewMode(mode) {
// mode: "camera" | "photo" | "idle"
els.cameraPreview.classList.toggle("is-camera", mode === "camera");
els.cameraPreview.classList.toggle("is-photo", mode === "photo");
}
// Draw an <img>/<video> source to the canvas and return a normalized payload
// (JPEG data URL + dimensions) suitable for an `input.image` message.
function mediaToPayload(source) {
const srcW = source.videoWidth || source.naturalWidth || source.width;
const srcH = source.videoHeight || source.naturalHeight || source.height;
if (!srcW || !srcH) return null;
let w = srcW;
let h = srcH;
const longest = Math.max(w, h);
if (longest > IMAGE_MAX_DIM) {
const scale = IMAGE_MAX_DIM / longest;
w = Math.round(w * scale);
h = Math.round(h * scale);
}
const canvas = els.cameraCanvas;
canvas.width = w;
canvas.height = h;
const ctx = canvas.getContext("2d");
ctx.drawImage(source, 0, 0, w, h);
let dataUrl;
try {
dataUrl = canvas.toDataURL("image/jpeg", IMAGE_JPEG_QUALITY);
} catch (err) {
addWsLog("system", `image encode failed: ${err.message || err}`);
return null;
}
return { dataUrl, mime: "image/jpeg", width: w, height: h };
}
function setPendingImage(payload) {
state.pendingImage = payload;
if (payload) {
els.cameraPhoto.src = payload.dataUrl;
setPreviewMode("photo");
}
setCameraButtonEnabled();
}
async function startCamera() {
if (!navigator.mediaDevices || !navigator.mediaDevices.getUserMedia) {
addWsLog("system", "getUserMedia not available in this browser");
return;
}
stopCameraStream();
try {
state.cameraStream = await navigator.mediaDevices.getUserMedia({
video: { facingMode: state.cameraFacing },
audio: false,
});
} catch (err) {
addWsLog("system", `camera error: ${err.message || err}`);
return;
}
els.cameraVideo.srcObject = state.cameraStream;
try {
await els.cameraVideo.play();
} catch (_) {
/* autoplay may resolve later */
}
state.cameraActive = true;
state.pendingImage = null;
setPreviewMode("camera");
els.cameraStartBtn.classList.add("is-active");
els.cameraStartBtn.textContent = "重新拍摄";
els.cameraFlipBtn.hidden = false;
clearSampleSelection();
setCameraButtonEnabled();
}
function stopCameraStream() {
if (state.cameraStream) {
state.cameraStream.getTracks().forEach((track) => track.stop());
state.cameraStream = null;
}
els.cameraVideo.srcObject = null;
state.cameraActive = false;
els.cameraStartBtn.classList.remove("is-active");
els.cameraStartBtn.textContent = "使用摄像头";
els.cameraFlipBtn.hidden = true;
}
function captureFromCamera() {
const payload = mediaToPayload(els.cameraVideo);
if (!payload) return null;
stopCameraStream();
setPendingImage(payload);
return payload;
}
// Load a same-origin/object URL into an <img> and resolve once decoded.
function loadImage(src) {
return new Promise((resolve, reject) => {
const img = new Image();
img.onload = () => resolve(img);
img.onerror = () => reject(new Error(`failed to load image: ${src}`));
img.src = src;
});
}
async function selectFileImage(file) {
if (!file) return;
const objectUrl = URL.createObjectURL(file);
try {
const img = await loadImage(objectUrl);
const payload = mediaToPayload(img);
if (!payload) return;
stopCameraStream();
clearSampleSelection();
setPendingImage(payload);
} catch (err) {
addWsLog("system", `upload error: ${err.message || err}`);
} finally {
URL.revokeObjectURL(objectUrl);
}
}
async function selectSampleImage(src, buttonEl) {
try {
const img = await loadImage(src);
const payload = mediaToPayload(img);
if (!payload) return;
stopCameraStream();
clearSampleSelection();
if (buttonEl) buttonEl.classList.add("is-selected");
setPendingImage(payload);
} catch (err) {
addWsLog("system", `sample error: ${err.message || err}`);
}
}
function clearSampleSelection() {
els.cameraSamples
.querySelectorAll(".camera-drawer__sample.is-selected")
.forEach((el) => el.classList.remove("is-selected"));
}
function renderSampleThumbnails() {
if (state.samplesRendered) return;
state.samplesRendered = true;
els.cameraSamples.innerHTML = "";
for (const sample of SAMPLE_IMAGES) {
const btn = document.createElement("button");
btn.type = "button";
btn.className = "camera-drawer__sample";
btn.title = sample.label;
const img = document.createElement("img");
img.src = sample.src;
img.alt = sample.label;
btn.appendChild(img);
btn.addEventListener("click", () => selectSampleImage(sample.src, btn));
els.cameraSamples.appendChild(btn);
}
}
function resetCameraInput() {
stopCameraStream();
state.pendingImage = null;
clearSampleSelection();
els.cameraPhoto.removeAttribute("src");
setPreviewMode("idle");
setCameraButtonEnabled();
}
function sendImage(payload, text) {
if (!payload) return false;
if (!state.ws || state.ws.readyState !== WebSocket.OPEN) return false;
const message = {
type: "input.image",
image: payload.dataUrl,
mime_type: payload.mime,
width: payload.width,
height: payload.height,
text: text || CAMERA_DONE_TEXT,
interrupt: true,
};
wsSend(JSON.stringify(message));
// Mirror the text-input path: interrupt in-flight bot audio and render the
// user's image + text together as one local bubble (the engine does not echo
// image input back as a transcript event).
stopPlaybackQueue();
state.currentAssistantBubble = null;
addImageBubble("user", payload.dataUrl, text || CAMERA_DONE_TEXT);
return true;
}
function submitCameraImage() {
// If the live camera is on, grab the current frame first; otherwise use the
// already-selected (uploaded / sample / captured) image.
let payload = state.pendingImage;
if (state.cameraActive) {
payload = captureFromCamera() || payload;
}
if (!payload) return;
// Keep the existing workflow contract: the accompanying text stays the
// "【拍摄完成】" marker that advances the FastGPT camera step; the image is
// the new multimodal attachment.
if (!sendImage(payload, CAMERA_DONE_TEXT)) return;
resetCameraInput();
}
/* --------------------------------------------------------- Chat updates */
function handleUserTranscript(text) {
@@ -1139,7 +1414,23 @@ els.clearWsLogBtn.addEventListener("click", () => {
els.cameraDoneBtn.addEventListener("click", () => {
if (!state.cameraState) return;
sendText(CAMERA_DONE_TEXT);
submitCameraImage();
});
els.cameraStartBtn.addEventListener("click", () => {
startCamera();
});
els.cameraFlipBtn.addEventListener("click", () => {
state.cameraFacing =
state.cameraFacing === "environment" ? "user" : "environment";
if (state.cameraActive) startCamera();
});
els.cameraUpload.addEventListener("change", (event) => {
const file = event.target.files && event.target.files[0];
selectFileImage(file);
event.target.value = "";
});
function autosizeTextarea() {
@@ -1174,6 +1465,7 @@ els.textInput.addEventListener("keydown", (event) => {
});
window.addEventListener("beforeunload", () => {
stopCameraStream();
if (state.ws) {
try {
state.ws.close();

View File

@@ -82,16 +82,65 @@
<span id="camera-state" class="camera-drawer__state">State -</span>
</div>
<div class="camera-drawer__preview" aria-hidden="true">
<div id="camera-preview" class="camera-drawer__preview">
<video
id="camera-video"
class="camera-drawer__video"
playsinline
muted
autoplay
></video>
<img
id="camera-photo"
class="camera-drawer__photo"
alt="Selected image preview"
/>
<span class="camera-drawer__corner camera-drawer__corner--tl"></span>
<span class="camera-drawer__corner camera-drawer__corner--tr"></span>
<span class="camera-drawer__corner camera-drawer__corner--bl"></span>
<span class="camera-drawer__corner camera-drawer__corner--br"></span>
<span class="camera-drawer__lens"></span>
<span class="camera-drawer__scan"></span>
<span id="camera-placeholder" class="camera-drawer__placeholder">
打开摄像头实时拍摄,或从下方选择 / 上传图片
</span>
</div>
<p id="camera-question" class="camera-drawer__question"></p>
<div class="camera-drawer__sources">
<button
id="camera-start-btn"
class="btn btn--ghost camera-drawer__source"
type="button"
>
使用摄像头
</button>
<button
id="camera-flip-btn"
class="btn btn--ghost camera-drawer__source"
type="button"
hidden
>
切换摄像头
</button>
<label class="btn btn--ghost camera-drawer__source">
上传图片
<input
id="camera-upload"
type="file"
accept="image/*"
hidden
/>
</label>
</div>
<div
id="camera-samples"
class="camera-drawer__samples"
aria-label="示例图片,点击选择"
></div>
<button
id="camera-done-btn"
class="btn btn--primary camera-drawer__button"
@@ -100,6 +149,7 @@
>
拍摄完成
</button>
<canvas id="camera-canvas" hidden></canvas>
</div>
</aside>

Binary file not shown.

After

Width:  |  Height:  |  Size: 18 KiB

Binary file not shown.

After

Width:  |  Height:  |  Size: 17 KiB

Binary file not shown.

After

Width:  |  Height:  |  Size: 17 KiB

Binary file not shown.

After

Width:  |  Height:  |  Size: 17 KiB

View File

@@ -148,6 +148,45 @@ body {
background-size: 34px 34px, 34px 34px, auto, auto;
}
.camera-drawer__video,
.camera-drawer__photo {
position: absolute;
inset: 0;
width: 100%;
height: 100%;
object-fit: cover;
display: none;
z-index: 1;
}
.camera-drawer__preview.is-camera .camera-drawer__video {
display: block;
}
.camera-drawer__preview.is-photo .camera-drawer__photo {
display: block;
}
/* Hide the decorative lens/scan/placeholder once real media is showing. */
.camera-drawer__preview.is-camera .camera-drawer__lens,
.camera-drawer__preview.is-photo .camera-drawer__lens,
.camera-drawer__preview.is-camera .camera-drawer__scan,
.camera-drawer__preview.is-photo .camera-drawer__scan,
.camera-drawer__preview.is-camera .camera-drawer__placeholder,
.camera-drawer__preview.is-photo .camera-drawer__placeholder {
display: none;
}
.camera-drawer__placeholder {
position: absolute;
inset: auto 18px 16px;
z-index: 2;
color: rgba(214, 220, 235, 0.78);
font-size: 12px;
line-height: 1.5;
text-align: center;
}
.camera-drawer__lens {
position: absolute;
top: 50%;
@@ -174,6 +213,7 @@ body {
.camera-drawer__corner {
position: absolute;
z-index: 2;
width: 28px;
height: 28px;
border-color: rgba(255, 255, 255, 0.7);
@@ -229,6 +269,62 @@ body {
cursor: not-allowed;
}
.camera-drawer__sources {
display: flex;
flex-wrap: wrap;
gap: 8px;
}
.camera-drawer__source {
flex: 1 1 auto;
min-height: 38px;
font-size: 13px;
font-weight: 600;
cursor: pointer;
}
.camera-drawer__source.is-active {
border-color: var(--success);
color: var(--success);
}
.camera-drawer__samples {
display: grid;
grid-template-columns: repeat(4, 1fr);
gap: 8px;
}
.camera-drawer__samples:empty {
display: none;
}
.camera-drawer__sample {
position: relative;
aspect-ratio: 4 / 3;
padding: 0;
border: 2px solid transparent;
border-radius: 10px;
overflow: hidden;
cursor: pointer;
background: #0f141f;
}
.camera-drawer__sample img {
width: 100%;
height: 100%;
object-fit: cover;
display: block;
}
.camera-drawer__sample:hover {
border-color: rgba(149, 160, 187, 0.6);
}
.camera-drawer__sample.is-selected {
border-color: var(--success);
box-shadow: 0 0 0 1px var(--success);
}
.app__body {
display: grid;
grid-template-columns: minmax(0, 1fr) clamp(300px, 32vw, 420px);
@@ -511,6 +607,18 @@ body {
margin-bottom: 4px;
}
.bubble__image {
display: block;
max-width: 240px;
width: 100%;
border-radius: 10px;
margin-bottom: 6px;
}
.bubble__image + .bubble__text:empty {
display: none;
}
/* WebSocket log --------------------------------------------------------- */
.ws-log {