fix: simplify external dependencies in vite.config.ts

Author: vtempest

apps/qwksearch-web/components/ResearchAgent/components/MessageComposer/ChatInputBox.tsx

@@ -103,6 +103,7 @@ const ChatInputBox = () => {
     const [suggestions, setSuggestions] = useState<string[]>([]);
     const [highlightedIndex, setHighlightedIndex] = useState(-1);
     const [suggestionsOpen, setSuggestionsOpen] = useState(false);
+    const [dropdownPosition, setDropdownPosition] = useState<'below' | 'above'>('below');
     const suppressNextFetchRef = useRef(false);
     const autocompleteAbortRef = useRef<AbortController | null>(null);
 
@@ -125,14 +126,32 @@ const ChatInputBox = () => {
             autocompleteAbortRef.current = controller;
             try {
                 const res = await fetch(
-                    `/api/agent/autocomplete?q=${encodeURIComponent(query)}`,
+                    `/api/agent/autocomplete?q=${encodeURIComponent(query)}&limit=8`,
                     { signal: controller.signal },
                 );
                 if (!res.ok) return;
                 const data = await res.json();
                 const list: string[] = Array.isArray(data?.suggestions) ? data.suggestions : [];
                 setSuggestions(list);
-                setSuggestionsOpen(list.length > 0);
+                if (list.length > 0) {
+                    // Calculate dropdown position based on viewport space
+                    if (wrapperRef.current) {
+                        const rect = wrapperRef.current.getBoundingClientRect();
+                        const spaceBelow = window.innerHeight - rect.bottom;
+                        const spaceAbove = rect.top;
+                        const dropdownHeight = Math.min(288, list.length * 48); // max-h-72 = 288px, ~48px per item
+
+                        // On mobile (or when not enough space below), show above if there's more space
+                        if (spaceBelow < dropdownHeight && spaceAbove > spaceBelow) {
+                            setDropdownPosition('above');
+                        } else {
+                            setDropdownPosition('below');
+                        }
+                    }
+                    setSuggestionsOpen(true);
+                } else {
+                    setSuggestionsOpen(false);
+                }
                 setHighlightedIndex(-1);
             } catch (err: any) {
                 if (err?.name !== "AbortError") console.error("Autocomplete fetch failed", err);
@@ -391,11 +410,15 @@ const ChatInputBox = () => {
                                 // no-op; rendered outside wrapper, handled by mousedown stopPropagation below
                             }
                         }}
-                        initial={{ opacity: 0, y: -4 }}
+                        initial={{ opacity: 0, y: dropdownPosition === 'above' ? 4 : -4 }}
                         animate={{ opacity: 1, y: 0 }}
-                        exit={{ opacity: 0, y: -4 }}
+                        exit={{ opacity: 0, y: dropdownPosition === 'above' ? 4 : -4 }}
                         transition={{ duration: 0.12 }}
-                        className="absolute left-2 right-2 md:left-0 md:right-0 top-full mt-2 z-20 rounded-2xl bg-gray-50 dark:bg-[#30302E] border border-bg-300 dark:border-transparent shadow-xl overflow-hidden"
+                        className={`absolute left-2 right-2 md:left-0 md:right-0 z-20 rounded-2xl bg-gray-50 dark:bg-[#30302E] border border-bg-300 dark:border-transparent shadow-xl overflow-hidden ${
+                            dropdownPosition === 'above'
+                                ? 'bottom-full mb-2'
+                                : 'top-full mt-2'
+                        }`}
                         onMouseDown={(e) => e.preventDefault()}
                     >
                         <ul className="max-h-72 overflow-y-auto custom-scrollbar py-1">
@@ -405,10 +428,10 @@ const ChatInputBox = () => {
                                         type="button"
                                         onMouseEnter={() => setHighlightedIndex(i)}
                                         onClick={() => selectSuggestion(s)}
-                                        className={`w-full text-left px-4 py-2 text-[15px] flex items-center gap-2 transition-colors ${
+                                        className={`w-full text-left px-4 py-2.5 text-[15px] flex items-center gap-3 transition-colors ${
                                             i === highlightedIndex
                                                 ? 'bg-bg-200 text-text-100'
-                                                : 'text-text-200 hover:bg-bg-200'
+                                                : 'text-text-200 hover:bg-bg-100 dark:hover:bg-[#3A3A38]'
                                         }`}
                                     >
                                         <Search className="w-4 h-4 text-text-400 shrink-0" />

apps/qwksearch-web/vite.config.ts

@@ -24,24 +24,20 @@ export default defineConfig(({ command }) => ({
   resolve: {
     alias: {
       "shadcn-app-dock": resolve(__dirname, "../../packages/shadcn-app-dock/src/index.ts"),
+      "extract-webpage": resolve(__dirname, "../../packages/extract-webpage/src"),
+      "chat-agent-toolkit": resolve(__dirname, "../../packages/agent-toolkit/src"),
+      "extract-pdf": resolve(__dirname, "../../packages/extract-pdf/src"),
+      "extract-youtube": resolve(__dirname, "../../packages/extract-youtube/src"),
+      "qwksearch-api-client": resolve(__dirname, "../../packages/qwksearch-api-client/src"),
+      "grab-url": resolve(__dirname, "../../node_modules/grab-url"),
     },
   },
   build: {
     rollupOptions: {
       // `fsevents` is an optional macOS-only native module that rollup/chokidar
       // require() lazily inside a try/catch; it has no place in the Worker
       // bundle and is never installed on Linux, so leave it external.
-      // Workspace packages with subpath imports must also be external since
-      // Rolldown cannot resolve them during bundling.
-      external: [
-        "fsevents",
-        /^extract-webpage/,
-        /^chat-agent-toolkit/,
-        /^extract-pdf/,
-        /^extract-youtube/,
-        /^qwksearch-api-client/,
-        /^grab-url/,
-      ],
+      external: ["fsevents"],
     },
   },
   plugins: [

packages/agent-toolkit/src/models/registry.ts

@@ -0,0 +1,4 @@
+/**
+ * @fileoverview Re-export ModelRegistry from config directory
+ */
+export { default } from "../config/model-registry";

packages/agent-toolkit/src/models/types.ts

@@ -0,0 +1,4 @@
+/**
+ * @fileoverview Re-export model types from config directory
+ */
+export type { Model, ConfigModelProvider } from "../config/config-types";

packages/agent-toolkit/src/suggest-next-words/autocomplete-ai.ts

@@ -0,0 +1,38 @@
+import { pipeline, type TextGenerationSingle } from "@huggingface/transformers";
+
+/**
+ * Generates the next words for a given prompt using a text generation model.
+ *
+ * The DistilGPT2 model is a distilled, smaller version of OpenAI's GPT-2, featuring
+ * around 82 million parameters (~80MB), and available in Hugging Face Transformers
+ * for efficient next word (next-token) prediction tasks in English text. It is
+ * well-suited for sequence generation and can be used as a next word prediction
+ * model with code similar to GPT2, but offers faster and lighter inference compared
+ * GPT-2 (124M parameter) model, preserving most capabilities but running
+ * significantly faster and requiring less memory.
+ * @see https://huggingface.co/Xenova/distilgpt2
+ * @param {string} prompt - The input prompt to complete.
+ * @param {Object} [options] - Generation options.
+ * @param {number} [options.maxTokens=16] - Maximum number of new tokens to generate.
+ * @param {string} [options.model='Xenova/distilgpt2'] - The model identifier to use.
+ * @returns {Promise<string>} - The generated text completions.
+ */
+export async function predictNextWordsWithSmallLocalModel(
+  prompt: string,
+  { model = "Xenova/distilgpt2", maxTokens = 16, modelParams = {} } = {}
+): Promise<string> {
+  if (!prompt) throw new Error("Prompt is required");
+  return (
+    await (
+      await pipeline("text-generation", model, {
+        dtype: "fp16",
+        device: "cpu",
+        ...modelParams,
+      })
+    )(prompt, { max_new_tokens: maxTokens })
+  )
+    .map((res) => (res as TextGenerationSingle).generated_text)
+    .join(" ")
+    .replace(prompt, "")
+    .trim();
+}