Merge branch 'pr/1082'

fix: guard against non-array searching queries in research steps

src/components/AssistantSteps.tsx

@@ -37,7 +37,8 @@ const getStepTitle = (
   if (step.type === 'reasoning') {
     return isStreaming && !step.reasoning ? 'Thinking...' : 'Thinking';
   } else if (step.type === 'searching') {
-    return `Searching ${step.searching.length} ${step.searching.length === 1 ? 'query' : 'queries'}`;
+    const queries = Array.isArray(step.searching) ? step.searching : [];
+    return `Searching ${queries.length} ${queries.length === 1 ? 'query' : 'queries'}`;
   } else if (step.type === 'search_results') {
     return `Found ${step.reading.length} ${step.reading.length === 1 ? 'result' : 'results'}`;
   } else if (step.type === 'reading') {
@@ -160,6 +161,7 @@ const AssistantSteps = ({
                       )}
 
                       {step.type === 'searching' &&
+                        Array.isArray(step.searching) &&
                         step.searching.length > 0 && (
                           <div className="flex flex-wrap gap-1.5 mt-1.5">
                             {step.searching.map((query, idx) => (

src/components/MessageInputActions/Attach.tsx

@@ -18,6 +18,7 @@ import { Fragment, useRef, useState } from 'react';
 import { useChat } from '@/lib/hooks/useChat';
 import { AnimatePresence } from 'motion/react';
 import { motion } from 'framer-motion';
+import { toast } from 'sonner';
 
 const Attach = () => {
   const { files, setFiles, setFileIds, fileIds } = useChat();
@@ -26,31 +27,59 @@ const Attach = () => {
   const fileInputRef = useRef<any>();
 
   const handleChange = async (e: React.ChangeEvent<HTMLInputElement>) => {
-    setLoading(true);
-    const data = new FormData();
+    const selectedFiles = e.target.files;
 
-    for (let i = 0; i < e.target.files!.length; i++) {
-      data.append('files', e.target.files![i]);
+    if (!selectedFiles?.length) {
+      return;
     }
 
-    const embeddingModelProvider = localStorage.getItem(
-      'embeddingModelProviderId',
-    );
-    const embeddingModel = localStorage.getItem('embeddingModelKey');
+    setLoading(true);
 
-    data.append('embedding_model_provider_id', embeddingModelProvider!);
-    data.append('embedding_model_key', embeddingModel!);
+    try {
+      const data = new FormData();
 
-    const res = await fetch(`/api/uploads`, {
-      method: 'POST',
-      body: data,
-    });
+      for (let i = 0; i < selectedFiles.length; i++) {
+        data.append('files', selectedFiles[i]);
+      }
 
-    const resData = await res.json();
+      const embeddingModelProvider = localStorage.getItem(
+        'embeddingModelProviderId',
+      );
+      const embeddingModel = localStorage.getItem('embeddingModelKey');
 
-    setFiles([...files, ...resData.files]);
-    setFileIds([...fileIds, ...resData.files.map((file: any) => file.fileId)]);
-    setLoading(false);
+      if (!embeddingModelProvider || !embeddingModel) {
+        throw new Error('Please select an embedding model before uploading.');
+      }
+
+      data.append('embedding_model_provider_id', embeddingModelProvider);
+      data.append('embedding_model_key', embeddingModel);
+
+      const res = await fetch(`/api/uploads`, {
+        method: 'POST',
+        body: data,
+      });
+
+      const resData = await res.json().catch(() => ({}));
+
+      if (!res.ok) {
+        throw new Error(resData.message || 'Failed to upload file(s).');
+      }
+
+      if (!Array.isArray(resData.files)) {
+        throw new Error('Invalid upload response from server.');
+      }
+
+      setFiles([...files, ...resData.files]);
+      setFileIds([
+        ...fileIds,
+        ...resData.files.map((file: any) => file.fileId),
+      ]);
+    } catch (err: any) {
+      toast(err?.message || 'Failed to upload file(s).');
+    } finally {
+      setLoading(false);
+      e.target.value = '';
+    }
   };
 
   return loading ? (

src/components/MessageInputActions/AttachSmall.tsx

@@ -9,6 +9,7 @@ import { Fragment, useRef, useState } from 'react';
 import { useChat } from '@/lib/hooks/useChat';
 import { AnimatePresence } from 'motion/react';
 import { motion } from 'framer-motion';
+import { toast } from 'sonner';
 
 const AttachSmall = () => {
   const { files, setFiles, setFileIds, fileIds } = useChat();
@@ -17,31 +18,59 @@ const AttachSmall = () => {
   const fileInputRef = useRef<any>();
 
   const handleChange = async (e: React.ChangeEvent<HTMLInputElement>) => {
-    setLoading(true);
-    const data = new FormData();
+    const selectedFiles = e.target.files;
 
-    for (let i = 0; i < e.target.files!.length; i++) {
-      data.append('files', e.target.files![i]);
+    if (!selectedFiles?.length) {
+      return;
     }
 
-    const embeddingModelProvider = localStorage.getItem(
-      'embeddingModelProviderId',
-    );
-    const embeddingModel = localStorage.getItem('embeddingModelKey');
+    setLoading(true);
 
-    data.append('embedding_model_provider_id', embeddingModelProvider!);
-    data.append('embedding_model_key', embeddingModel!);
+    try {
+      const data = new FormData();
 
-    const res = await fetch(`/api/uploads`, {
-      method: 'POST',
-      body: data,
-    });
+      for (let i = 0; i < selectedFiles.length; i++) {
+        data.append('files', selectedFiles[i]);
+      }
 
-    const resData = await res.json();
+      const embeddingModelProvider = localStorage.getItem(
+        'embeddingModelProviderId',
+      );
+      const embeddingModel = localStorage.getItem('embeddingModelKey');
 
-    setFiles([...files, ...resData.files]);
-    setFileIds([...fileIds, ...resData.files.map((file: any) => file.fileId)]);
-    setLoading(false);
+      if (!embeddingModelProvider || !embeddingModel) {
+        throw new Error('Please select an embedding model before uploading.');
+      }
+
+      data.append('embedding_model_provider_id', embeddingModelProvider);
+      data.append('embedding_model_key', embeddingModel);
+
+      const res = await fetch(`/api/uploads`, {
+        method: 'POST',
+        body: data,
+      });
+
+      const resData = await res.json().catch(() => ({}));
+
+      if (!res.ok) {
+        throw new Error(resData.message || 'Failed to upload file(s).');
+      }
+
+      if (!Array.isArray(resData.files)) {
+        throw new Error('Invalid upload response from server.');
+      }
+
+      setFiles([...files, ...resData.files]);
+      setFileIds([
+        ...fileIds,
+        ...resData.files.map((file: any) => file.fileId),
+      ]);
+    } catch (err: any) {
+      toast(err?.message || 'Failed to upload file(s).');
+    } finally {
+      setLoading(false);
+      e.target.value = '';
+    }
   };
 
   return loading ? (

src/components/WeatherWidget.tsx

@@ -1,5 +1,8 @@
-import { Cloud, Sun, CloudRain, CloudSnow, Wind } from 'lucide-react';
+'use client';
+
+import { Wind } from 'lucide-react';
 import { useEffect, useState } from 'react';
+import { getApproxLocation } from '@/lib/actions';
 
 const WeatherWidget = () => {
   const [data, setData] = useState({
@@ -15,17 +18,6 @@ const WeatherWidget = () => {
 
   const [loading, setLoading] = useState(true);
 
-  const getApproxLocation = async () => {
-    const res = await fetch('https://ipwhois.app/json/');
-    const data = await res.json();
-
-    return {
-      latitude: data.latitude,
-      longitude: data.longitude,
-      city: data.city,
-    };
-  };
-
   const getLocation = async (
     callback: (location: {
       latitude: number;

src/lib/actions.ts

@@ -20,3 +20,17 @@ export const getSuggestions = async (chatHistory: [string, string][]) => {
 
   return data.suggestions;
 };
+
+export const getApproxLocation = async () => {
+  const res = await fetch('https://free.freeipapi.com/api/json', {
+    method: 'GET',
+  });
+
+  const data = await res.json();
+
+  return {
+    latitude: data.latitude,
+    longitude: data.longitude,
+    city: data.cityName,
+  };
+};

src/lib/agents/search/researcher/actions/academicSearch.ts

@@ -30,7 +30,9 @@ const academicSearchAction: ResearchAction<typeof schema> = {
     config.classification.classification.skipSearch === false &&
     config.classification.classification.academicSearch === true,
   execute: async (input, additionalConfig) => {
-    input.queries = input.queries.slice(0, 3);
+    input.queries = (
+      Array.isArray(input.queries) ? input.queries : [input.queries]
+    ).slice(0, 3);
 
     const researchBlock = additionalConfig.session.getBlock(
       additionalConfig.researchBlockId,

src/lib/agents/search/researcher/actions/socialSearch.ts

@@ -30,7 +30,9 @@ const socialSearchAction: ResearchAction<typeof schema> = {
     config.classification.classification.skipSearch === false &&
     config.classification.classification.discussionSearch === true,
   execute: async (input, additionalConfig) => {
-    input.queries = input.queries.slice(0, 3);
+    input.queries = (
+      Array.isArray(input.queries) ? input.queries : [input.queries]
+    ).slice(0, 3);
 
     const researchBlock = additionalConfig.session.getBlock(
       additionalConfig.researchBlockId,

src/lib/agents/search/researcher/actions/webSearch.ts

@@ -85,7 +85,9 @@ const webSearchAction: ResearchAction<typeof actionSchema> = {
     config.sources.includes('web') &&
     config.classification.classification.skipSearch === false,
   execute: async (input, additionalConfig) => {
-    input.queries = input.queries.slice(0, 3);
+    input.queries = (
+      Array.isArray(input.queries) ? input.queries : [input.queries]
+    ).slice(0, 3);
 
     const researchBlock = additionalConfig.session.getBlock(
       additionalConfig.researchBlockId,

src/lib/config/index.ts

@@ -1,7 +1,7 @@
 import path from 'node:path';
 import fs from 'fs';
 import { Config, ConfigModelProvider, UIConfigSections } from './types';
-import { hashObj } from '../serverUtils';
+import { hashObj } from '../utils/hash';
 import { getModelProvidersUIConfigSection } from '../models/providers';
 
 class ConfigManager {

src/lib/models/providers/ollama/ollamaLLM.ts

@@ -25,7 +25,9 @@ const reasoningModels = [
   'qwen3',
   'deepseek-v3.1',
   'magistral',
-  'nemotron-3-nano',
+  'nemotron-3',
+  'nemotron-cascade-2',
+  'glm-4.7-flash',
 ];
 
 class OllamaLLM extends BaseLLM<OllamaConfig> {

src/lib/serverActions.ts

@@ -0,0 +1 @@
+'use server';

src/lib/uploads/store.ts

@@ -2,8 +2,7 @@ import BaseEmbedding from "../models/base/embedding";
 import UploadManager from "./manager";
 import computeSimilarity from "../utils/computeSimilarity";
 import { Chunk } from "../types";
-import { hashObj } from "../serverUtils";
-import fs from 'fs';
+import { hashObj } from '../utils/hash';
 
 type UploadStoreParams = {
     embeddingModel: BaseEmbedding<any>;