chore: update ji local changes
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@@ -213,7 +213,7 @@ export function RecentChatList() {
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className="block w-full whitespace-nowrap group-hover/side-menu-item:overflow-hidden"
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className="block w-full whitespace-nowrap group-hover/side-menu-item:overflow-hidden"
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href={pathOfThread(thread)}
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href={pathOfThread(thread)}
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>
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>
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{desensitize(titleOfThread(thread))}
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{desensitize(titleOfThread(thread, t.pages.newChat))}
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</Link>
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</Link>
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</SidebarMenuButton>
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</SidebarMenuButton>
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{env.NEXT_PUBLIC_STATIC_WEBSITE_ONLY !== "true" && (
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{env.NEXT_PUBLIC_STATIC_WEBSITE_ONLY !== "true" && (
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@@ -236,7 +236,7 @@ export function RecentChatList() {
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onSelect={() =>
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onSelect={() =>
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handleRenameClick(
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handleRenameClick(
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thread.thread_id,
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thread.thread_id,
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titleOfThread(thread),
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titleOfThread(thread, t.pages.newChat),
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)
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)
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}
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}
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>
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>
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@@ -64,24 +64,50 @@ export async function loginByUsername(
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return response.json() as Promise<LoginByUsernameResponse>;
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return response.json() as Promise<LoginByUsernameResponse>;
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}
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}
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// The upstream token issuer and the verifier (token_info_url) run on separate
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// servers whose clocks can drift ~3-4s apart. A token verified right after it
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// is issued can look "not yet valid / expired" to the verifier, which surfaces
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// as a 401 here. That window closes on its own once real time advances past the
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// skew, so we silently retry the exchange a couple of times before giving up —
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// the LoginPage keeps showing its loading state, so the user never notices.
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const TOKEN_LOGIN_MAX_ATTEMPTS = 3; // initial try + 2 retries → covers up to ~6s skew
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const TOKEN_LOGIN_RETRY_DELAY_MS = 3000;
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const wait = (ms: number) => new Promise<void>((resolve) => setTimeout(resolve, ms));
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export async function loginByToken(
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export async function loginByToken(
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token: string,
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token: string,
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): Promise<LoginByUsernameResponse> {
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): Promise<LoginByUsernameResponse> {
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// Token-exchange login: the gateway resolves the upstream token to a username
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// Token-exchange login: the gateway resolves the upstream token to a username
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// and signs the matching local account in.
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// and signs the matching local account in.
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const response = await apiFetch(
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const url = `${getBackendBaseURL()}/api/v1/auth/login/token?token=${encodeURIComponent(token)}`;
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`${getBackendBaseURL()}/api/v1/auth/login/token?token=${encodeURIComponent(token)}`,
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let lastError = "Login failed.";
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{
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for (let attempt = 1; attempt <= TOKEN_LOGIN_MAX_ATTEMPTS; attempt += 1) {
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const response = await apiFetch(url, {
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method: "POST",
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method: "POST",
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headers: {
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headers: {
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"Content-Type": "application/json",
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"Content-Type": "application/json",
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},
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},
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},
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});
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);
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if (response.ok) {
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if (!response.ok) {
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return response.json() as Promise<LoginByUsernameResponse>;
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}
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const error = await response.json().catch(() => null);
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const error = await response.json().catch(() => null);
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throw new Error(extractErrorMessage(error));
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lastError = extractErrorMessage(error);
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// Only 401 is plausibly the transient clock-skew case and worth waiting on.
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// 403 (disabled), 429 (rate-limited), 500 (misconfigured) won't self-heal,
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// so fail fast instead of stalling the user.
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const isTransient = response.status === 401;
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if (!isTransient || attempt === TOKEN_LOGIN_MAX_ATTEMPTS) {
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throw new Error(lastError);
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}
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await wait(TOKEN_LOGIN_RETRY_DELAY_MS);
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}
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}
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return response.json() as Promise<LoginByUsernameResponse>;
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// Unreachable: the loop either returns or throws above.
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throw new Error(lastError);
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}
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}
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@@ -62,6 +62,21 @@ export function textOfMessage(message: Message) {
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return null;
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return null;
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}
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}
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export function titleOfThread(thread: AgentThread) {
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export function titleOfThread(thread: AgentThread, fallback = "Untitled") {
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return thread.values?.title ?? "Untitled";
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const title = thread.values?.title;
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if (title) return title;
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// No title yet (e.g. the very first turn is still streaming, or the backend
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// title pass hasn't finished). Derive a sensible display title from the first
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// user message so the user never sees a bare "Untitled" placeholder.
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const messages = thread.values?.messages;
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if (Array.isArray(messages)) {
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const firstHuman = messages.find((m) => m.type === "human");
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const text = firstHuman ? textOfMessage(firstHuman)?.trim() : null;
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if (text) {
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return text.length > 50 ? `${text.slice(0, 50).trimEnd()}…` : text;
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}
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}
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return fallback;
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}
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}
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@@ -71,7 +71,7 @@ export default function ChatsPage() {
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<Link key={thread.thread_id} href={pathOfThread(thread)}>
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<Link key={thread.thread_id} href={pathOfThread(thread)}>
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<div className="flex flex-col gap-2 border-b p-4">
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<div className="flex flex-col gap-2 border-b p-4">
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<div>
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<div>
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<div>{desensitize(titleOfThread(thread))}</div>
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<div>{desensitize(titleOfThread(thread, t.pages.newChat))}</div>
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</div>
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</div>
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{thread.updated_at && (
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{thread.updated_at && (
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<div className="text-muted-foreground text-sm">
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<div className="text-muted-foreground text-sm">
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@@ -166,7 +166,7 @@ Lead-agent middlewares are assembled in strict append order across `packages/har
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9. **SummarizationMiddleware** - Context reduction when approaching token limits (optional, if enabled)
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9. **SummarizationMiddleware** - Context reduction when approaching token limits (optional, if enabled)
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10. **TodoListMiddleware** - Task tracking with `write_todos` tool (optional, if plan_mode)
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10. **TodoListMiddleware** - Task tracking with `write_todos` tool (optional, if plan_mode)
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11. **TokenUsageMiddleware** - Records token usage metrics when token tracking is enabled (optional)
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11. **TokenUsageMiddleware** - Records token usage metrics when token tracking is enabled (optional)
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12. **TitleMiddleware** - Auto-generates thread title after first complete exchange and normalizes structured message content before prompting the title model
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12. **TitleMiddleware** - Two-phase auto-title (never shows "untitled"): `before_model` sets an instant question-derived *provisional* title the moment the first user message arrives (no LLM, zero latency), then `after_model` asynchronously generates the final LLM title and replaces it (tracked via the `title_provisional` state flag). Normalizes structured message content before prompting the title model
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13. **MemoryMiddleware** - Memory V2: `wrap_model_call` injects Hindsight recall transiently; `after_agent` auto-retains the turn to Hindsight
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13. **MemoryMiddleware** - Memory V2: `wrap_model_call` injects Hindsight recall transiently; `after_agent` auto-retains the turn to Hindsight
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14. **ViewImageMiddleware** - Injects base64 image data before LLM call (conditional on vision support)
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14. **ViewImageMiddleware** - Injects base64 image data before LLM call (conditional on vision support)
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15. **DeferredToolFilterMiddleware** - Hides deferred tool schemas from the bound model until tool search is enabled (optional)
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15. **DeferredToolFilterMiddleware** - Hides deferred tool schemas from the bound model until tool search is enabled (optional)
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@@ -178,7 +178,7 @@ Lead-agent middlewares are assembled in strict append order across `packages/har
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10. **SummarizationMiddleware** - Context reduction when approaching token limits (optional, if enabled)
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10. **SummarizationMiddleware** - Context reduction when approaching token limits (optional, if enabled)
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11. **TodoListMiddleware** - Task tracking with `write_todos` tool (optional, if plan_mode)
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11. **TodoListMiddleware** - Task tracking with `write_todos` tool (optional, if plan_mode)
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12. **TokenUsageMiddleware** - Records token usage metrics when token tracking is enabled (optional)
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12. **TokenUsageMiddleware** - Records token usage metrics when token tracking is enabled (optional)
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13. **TitleMiddleware** - Auto-generates thread title after first complete exchange and normalizes structured message content before prompting the title model
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13. **TitleMiddleware** - Two-phase auto-title (never shows "untitled"): `before_model` sets an instant question-derived *provisional* title the moment the first user message arrives (no LLM, zero latency), then `after_model` asynchronously generates the final LLM title and replaces it (tracked via the `title_provisional` state flag). Normalizes structured message content before prompting the title model
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14. **MemoryMiddleware** - Queues conversations for async memory update (filters to user + final AI responses)
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14. **MemoryMiddleware** - Queues conversations for async memory update (filters to user + final AI responses)
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15. **ViewImageMiddleware** - Injects base64 image data before LLM call (conditional on vision support)
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15. **ViewImageMiddleware** - Injects base64 image data before LLM call (conditional on vision support)
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16. **DeferredToolFilterMiddleware** - Hides deferred tool schemas from the bound model until tool search is enabled (optional)
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16. **DeferredToolFilterMiddleware** - Hides deferred tool schemas from the bound model until tool search is enabled (optional)
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+50
-6
@@ -23,6 +23,7 @@ class TitleMiddlewareState(AgentState):
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"""Compatible with the `ThreadState` schema."""
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"""Compatible with the `ThreadState` schema."""
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title: NotRequired[str | None]
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title: NotRequired[str | None]
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title_provisional: NotRequired[bool]
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class TitleMiddleware(AgentMiddleware[TitleMiddlewareState]):
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class TitleMiddleware(AgentMiddleware[TitleMiddlewareState]):
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@@ -61,16 +62,37 @@ class TitleMiddleware(AgentMiddleware[TitleMiddlewareState]):
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return ""
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return ""
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def _should_generate_title(self, state: TitleMiddlewareState) -> bool:
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def _should_set_provisional_title(self, state: TitleMiddlewareState) -> bool:
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"""Check if we should generate a title for this thread."""
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"""Check if we should set an instant, question-derived placeholder title.
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Runs in ``before_model`` so the thread shows a sensible title the moment
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the user sends their first message — eliminating the "untitled" window
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while the (possibly long) first answer streams. No LLM call, no latency.
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"""
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config = self._get_title_config()
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config = self._get_title_config()
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if not config.enabled:
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if not config.enabled:
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return False
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return False
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# Check if thread already has a title in state
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# Already has a title (provisional or final) — nothing to do.
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if state.get("title"):
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if state.get("title"):
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return False
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return False
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# Only on the very first turn, as soon as the user message arrives.
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messages = state.get("messages", [])
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user_messages = [m for m in messages if m.type == "human"]
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return len(user_messages) == 1
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def _should_generate_title(self, state: TitleMiddlewareState) -> bool:
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"""Check if we should generate the final LLM title for this thread."""
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config = self._get_title_config()
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if not config.enabled:
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return False
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# Skip only if we already have a *finalized* title. A provisional
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# placeholder set in before_model should still be upgraded by the LLM.
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if state.get("title") and not state.get("title_provisional"):
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return False
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# Check if this is the first turn (has at least one user message and one assistant response)
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# Check if this is the first turn (has at least one user message and one assistant response)
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messages = state.get("messages", [])
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messages = state.get("messages", [])
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if len(messages) < 2:
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if len(messages) < 2:
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@@ -146,13 +168,27 @@ class TitleMiddleware(AgentMiddleware[TitleMiddlewareState]):
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config["tags"] = [*(config.get("tags") or []), "middleware:title"]
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config["tags"] = [*(config.get("tags") or []), "middleware:title"]
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return config
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return config
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def _provisional_title_result(self, state: TitleMiddlewareState) -> dict | None:
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"""Set an instant placeholder title from the first user message (no LLM)."""
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if not self._should_set_provisional_title(state):
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return None
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messages = state.get("messages", [])
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user_msg_content = next((m.content for m in messages if m.type == "human"), "")
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user_msg = self._normalize_content(user_msg_content)
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if not user_msg.strip():
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return None
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title = self._fallback_title(user_msg)
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logger.debug("TitleMiddleware: set provisional title %r before first model call", title)
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return {"title": title, "title_provisional": True}
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def _generate_title_result(self, state: TitleMiddlewareState) -> dict | None:
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def _generate_title_result(self, state: TitleMiddlewareState) -> dict | None:
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"""Generate a local fallback title without blocking on an LLM call."""
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"""Generate a local fallback title without blocking on an LLM call."""
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if not self._should_generate_title(state):
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if not self._should_generate_title(state):
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return None
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return None
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_, user_msg = self._build_title_prompt(state)
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_, user_msg = self._build_title_prompt(state)
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return {"title": self._fallback_title(user_msg)}
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return {"title": self._fallback_title(user_msg), "title_provisional": False}
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def _force_disable_thinking(self, model: object) -> None:
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def _force_disable_thinking(self, model: object) -> None:
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"""Force-disable thinking on the title model via `extra_body` overrides.
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"""Force-disable thinking on the title model via `extra_body` overrides.
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@@ -204,10 +240,18 @@ class TitleMiddleware(AgentMiddleware[TitleMiddlewareState]):
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response = await model.ainvoke(prompt, config=self._get_runnable_config())
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response = await model.ainvoke(prompt, config=self._get_runnable_config())
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title = self._parse_title(response.content)
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title = self._parse_title(response.content)
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if title:
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if title:
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return {"title": title}
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return {"title": title, "title_provisional": False}
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except Exception:
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except Exception:
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logger.debug("Failed to generate async title; falling back to local title", exc_info=True)
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logger.debug("Failed to generate async title; falling back to local title", exc_info=True)
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return {"title": self._fallback_title(user_msg)}
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return {"title": self._fallback_title(user_msg), "title_provisional": False}
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@override
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def before_model(self, state: TitleMiddlewareState, runtime: Runtime) -> dict | None:
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return self._provisional_title_result(state)
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@override
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async def abefore_model(self, state: TitleMiddlewareState, runtime: Runtime) -> dict | None:
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return self._provisional_title_result(state)
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@override
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@override
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def after_model(self, state: TitleMiddlewareState, runtime: Runtime) -> dict | None:
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def after_model(self, state: TitleMiddlewareState, runtime: Runtime) -> dict | None:
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@@ -69,6 +69,10 @@ class ThreadState(AgentState):
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sandbox: NotRequired[SandboxState | None]
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sandbox: NotRequired[SandboxState | None]
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thread_data: NotRequired[ThreadDataState | None]
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thread_data: NotRequired[ThreadDataState | None]
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title: NotRequired[str | None]
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title: NotRequired[str | None]
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# True while `title` is a provisional, question-derived placeholder that the
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# async LLM pass has not yet finalized. Lets TitleMiddleware show a title
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# instantly (no "untitled" window) and upgrade it once the answer is ready.
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title_provisional: NotRequired[bool]
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artifacts: Annotated[list[str], merge_artifacts]
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artifacts: Annotated[list[str], merge_artifacts]
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todos: NotRequired[list | None]
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todos: NotRequired[list | None]
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uploaded_files: NotRequired[list[dict] | None]
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uploaded_files: NotRequired[list[dict] | None]
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+61
-12
@@ -128,6 +128,45 @@ def extract_json_object(text: str | None) -> dict[str, Any] | None:
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return None
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return None
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def recover_html_document(text: str | None) -> str | None:
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"""Slice a complete HTML document out of a model reply.
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Used as a fallback when the JSON wrapper around the ``html`` field can't be
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parsed — the model commonly emits *literal* newlines and *unescaped* quotes
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(``"zh-CN"``) inside the value, which is invalid JSON, so
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:func:`extract_json_object` returns ``None``. Without this, the caller would
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archive the whole ``{"title": ..., "html": "<!doctype html>…"}`` blob as the
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page. We locate the ``<!doctype html>`` / ``<html …>`` start and the final
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``</html>`` and return just that span, dropping the surrounding JSON
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scaffolding. Also accepts a reply that is already bare HTML. Returns
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``None`` when no HTML document can be found.
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"""
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if not text or not isinstance(text, str):
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return None
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lowered = text.lower()
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start = lowered.find("<!doctype html")
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if start == -1:
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start = lowered.find("<html")
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if start == -1:
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return None
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end = lowered.rfind("</html>")
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candidate = text[start:] if end == -1 else text[start : end + len("</html>")]
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candidate = candidate.strip()
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# If the html had been a properly-escaped JSON string value (the JSON failed
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# to parse for some *other* reason), unescape the common sequences so they
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# don't survive into the rendered page. Only triggers when escapes exist, so
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# genuinely-literal HTML (the usual broken-JSON case) is left untouched.
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if "\\n" in candidate or '\\"' in candidate or "\\/" in candidate or "\\t" in candidate:
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candidate = (
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candidate.replace('\\"', '"')
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.replace("\\n", "\n")
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.replace("\\r", "\r")
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.replace("\\t", "\t")
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.replace("\\/", "/")
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)
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return candidate or None
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def sanitize_html(html: str) -> tuple[str, list[str]]:
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def sanitize_html(html: str) -> tuple[str, list[str]]:
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"""Remove script-execution vectors from ``html``.
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"""Remove script-execution vectors from ``html``.
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@@ -242,11 +281,7 @@ _GENERATION_TEMPLATE = """你是一个内网页面生成助手。请根据输入
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|
||||||
用户页面要求:
|
用户页面要求:
|
||||||
{page_prompt}
|
{page_prompt}
|
||||||
|
{constraint_block}本次数据:
|
||||||
限制条件:
|
|
||||||
{negative_prompt}
|
|
||||||
|
|
||||||
本次数据:
|
|
||||||
{data}
|
{data}
|
||||||
|
|
||||||
参考页面风格:
|
参考页面风格:
|
||||||
@@ -258,11 +293,12 @@ _GENERATION_TEMPLATE = """你是一个内网页面生成助手。请根据输入
|
|||||||
要求:
|
要求:
|
||||||
1. 只输出 JSON,不要输出 Markdown,不要输出多余解释。
|
1. 只输出 JSON,不要输出 Markdown,不要输出多余解释。
|
||||||
2. JSON 字段必须包含 title、html、style_summary、layout_summary。
|
2. JSON 字段必须包含 title、html、style_summary、layout_summary。
|
||||||
3. html 必须是完整 HTML 文档,包含 <!doctype html>、html、head、body。
|
3. html 字段的值必须是合法 JSON 字符串:其中所有换行必须写成 \\n、所有双引号必须转义为 \\",不要在字符串里直接换行或使用未转义的引号。
|
||||||
4. 所有 CSS 写在 <style> 标签内,不要引用外部 CDN 或外链样式表。
|
4. html 必须是完整 HTML 文档,包含 <!doctype html>、html、head、body。
|
||||||
5. 不要包含 <script>、外链脚本、iframe、表单提交、on* 事件属性。
|
5. 所有 CSS 写在 <style> 标签内,不要引用外部 CDN 或外链样式表。
|
||||||
6. 参考页面只用于风格和布局,页面内容必须来自“本次数据”,不要复用参考页旧数据。
|
6. 不要包含 <script>、外链脚本、iframe、表单提交、on* 事件属性。
|
||||||
7. 页面使用中文,排版适合在浏览器中直接预览。
|
7. 参考页面只用于风格和布局,页面内容必须来自“本次数据”,不要复用参考页旧数据。
|
||||||
|
8. 页面使用中文,排版适合在浏览器中直接预览。
|
||||||
"""
|
"""
|
||||||
|
|
||||||
_REPAIR_TEMPLATE = """你是一个 HTML 修复助手。下面的 HTML 存在问题,请修复后重新输出完整页面。
|
_REPAIR_TEMPLATE = """你是一个 HTML 修复助手。下面的 HTML 存在问题,请修复后重新输出完整页面。
|
||||||
@@ -312,14 +348,27 @@ def build_generation_prompt(
|
|||||||
reference_layout: str | None,
|
reference_layout: str | None,
|
||||||
skill_instructions: str | None = None,
|
skill_instructions: str | None = None,
|
||||||
data_limit: int = 16000,
|
data_limit: int = 16000,
|
||||||
skill_limit: int = 16000,
|
skill_limit: int = 30000,
|
||||||
) -> str:
|
) -> str:
|
||||||
skill_block = ""
|
skill_block = ""
|
||||||
if skill_instructions and skill_instructions.strip():
|
if skill_instructions and skill_instructions.strip():
|
||||||
skill_block = "\n可用页面生成技能规范(请严格遵循):\n" + _clip(skill_instructions.strip(), skill_limit) + "\n"
|
skill_block = "\n可用页面生成技能规范(请严格遵循):\n" + _clip(skill_instructions.strip(), skill_limit) + "\n"
|
||||||
|
# The constraint block is only emitted when the user actually supplied one,
|
||||||
|
# and is framed as a top-priority hard rule that overrides the page
|
||||||
|
# requirements / reference page / data on conflict — otherwise the model
|
||||||
|
# tends to treat "限制条件" as a soft hint and ignore it.
|
||||||
|
constraint_block = ""
|
||||||
|
neg = (negative_prompt or "").strip()
|
||||||
|
if neg:
|
||||||
|
constraint_block = (
|
||||||
|
"\n限制条件(最高优先级的硬性约束,必须逐条严格遵守;"
|
||||||
|
"若与上面的页面要求、参考页面或本次数据发生冲突,一律以这里的限制条件为准):\n"
|
||||||
|
+ neg
|
||||||
|
+ "\n\n"
|
||||||
|
)
|
||||||
return _GENERATION_TEMPLATE.format(
|
return _GENERATION_TEMPLATE.format(
|
||||||
page_prompt=(page_prompt or "(未提供,使用通用看板风格)").strip(),
|
page_prompt=(page_prompt or "(未提供,使用通用看板风格)").strip(),
|
||||||
negative_prompt=(negative_prompt or "无").strip(),
|
constraint_block=constraint_block,
|
||||||
data=_clip(data, data_limit),
|
data=_clip(data, data_limit),
|
||||||
reference_style=(reference_style or "无").strip(),
|
reference_style=(reference_style or "无").strip(),
|
||||||
reference_layout=(reference_layout or "无").strip(),
|
reference_layout=(reference_layout or "无").strip(),
|
||||||
|
|||||||
+14
-5
@@ -966,6 +966,7 @@ class ScheduledTaskService:
|
|||||||
"""
|
"""
|
||||||
cfg = self._html_config(task)
|
cfg = self._html_config(task)
|
||||||
page_prompt = str(cfg.get("page_prompt") or "").strip()
|
page_prompt = str(cfg.get("page_prompt") or "").strip()
|
||||||
|
negative_prompt = str(cfg.get("negative_prompt") or "").strip()
|
||||||
gather_instruction = (
|
gather_instruction = (
|
||||||
"请运用你自身的检索/搜索等技能,围绕下述页面需求获取最新、真实的资料,"
|
"请运用你自身的检索/搜索等技能,围绕下述页面需求获取最新、真实的资料,"
|
||||||
"并整理成结构化的中文要点(可用列表/小标题),供后续生成 HTML 页面使用,本步骤不要生成 HTML:\n"
|
"并整理成结构化的中文要点(可用列表/小标题),供后续生成 HTML 页面使用,本步骤不要生成 HTML:\n"
|
||||||
@@ -976,6 +977,11 @@ class ScheduledTaskService:
|
|||||||
base_prompt = str(task.get("prompt") or "").strip()
|
base_prompt = str(task.get("prompt") or "").strip()
|
||||||
if base_prompt:
|
if base_prompt:
|
||||||
parts.append(f"补充说明:{base_prompt}")
|
parts.append(f"补充说明:{base_prompt}")
|
||||||
|
# Apply the user's constraints to data gathering too, not just rendering
|
||||||
|
# — a "限制条件" like "只要最近 24 小时的新闻" or "排除某主题" must shape
|
||||||
|
# which sources/data the agent collects, otherwise it silently leaks in.
|
||||||
|
if negative_prompt:
|
||||||
|
parts.append(f"限制条件(最高优先级,必须严格遵守):{negative_prompt}")
|
||||||
gather_task = {**task, "prompt": "\n".join(parts)}
|
gather_task = {**task, "prompt": "\n".join(parts)}
|
||||||
# Never apply the markdown gate to the gather pass.
|
# Never apply the markdown gate to the gather pass.
|
||||||
gather_ctx = dict(task.get("execution_context") or {})
|
gather_ctx = dict(task.get("execution_context") or {})
|
||||||
@@ -1100,11 +1106,14 @@ class ScheduledTaskService:
|
|||||||
title = str(parsed.get("title") or task.get("name") or "生成页面").strip()
|
title = str(parsed.get("title") or task.get("name") or "生成页面").strip()
|
||||||
html = parsed.get("html")
|
html = parsed.get("html")
|
||||||
if not isinstance(html, str) or "<" not in html:
|
if not isinstance(html, str) or "<" not in html:
|
||||||
# GLM5 may have replied with bare HTML instead of JSON — accept it.
|
# The JSON wrapper couldn't be parsed (the model emitted literal
|
||||||
if isinstance(raw, str) and ("<html" in raw.lower() or "<!doctype" in raw.lower()):
|
# newlines / unescaped quotes inside the "html" value), or it replied
|
||||||
html = raw
|
# with bare HTML. Either way, recover just the HTML document so we
|
||||||
else:
|
# never archive the {"title":...,"html":"..."} JSON blob as the page.
|
||||||
raise ValueError("GLM5 未返回有效的 HTML(JSON 解析失败)")
|
recovered = html_page_utils.recover_html_document(raw)
|
||||||
|
if recovered is None:
|
||||||
|
raise ValueError("模型未返回有效的 HTML(JSON 解析失败)")
|
||||||
|
html = recovered
|
||||||
style_summary = str(parsed.get("style_summary") or "").strip() or None
|
style_summary = str(parsed.get("style_summary") or "").strip() or None
|
||||||
layout_summary = str(parsed.get("layout_summary") or "").strip() or None
|
layout_summary = str(parsed.get("layout_summary") or "").strip() or None
|
||||||
|
|
||||||
|
|||||||
Reference in new issue
Block a user