EmilySun621 opened a new pull request, #5119:
URL: https://github.com/apache/texera/pull/5119

   > Paste a URL. Drop a file. Open a SQLite database. Ask the AI agent. **Four 
new import paths, zero manual download.**
   
   ---
   
   ## What's New
   
   **🔗 URL Import** — Paste any CSV/JSON URL on the Datasets page, click 
Import. Server-side fetch, auto-format detection.
   
   **📁 Local File Drop** — Drag & drop CSV, JSON, XLSX, TSV, SQLite directly 
onto the Datasets page.
   
   **🗄️ SQLite Import** — Drop a .sqlite file → pick tables from a list → each 
table becomes a dataset. Uses Bun's built-in `bun:sqlite`, no external 
dependencies.
   
   **⚡ REST API Agent Tool** — `fetch_api_data` tool lets the AI agent fetch 
from any API endpoint. Auto-flattens nested JSON to tabular format.
   
   ---
   
   ## How It Works
   
   ```
   Frontend (Datasets page)          Agent Service (port 3001)         Texera
   ┌─────────────────────┐          ┌─────────────────────────┐      
┌──────────┐
   │ URL input ──────────┼────→     │ POST /fetch-url         │─────→│ Dataset  
│
   │ File drop zone ─────┼────→     │ POST /sqlite-tables     │      │ Creation 
│
   │ Agent chat ─────────┼────→     │ POST /sqlite-export     │      │ API      
│
   └─────────────────────┘          │ Tool: fetch_api_data    │      
└──────────┘
                                    └─────────────────────────┘
   ```
   
   ---
   
   ## Verified
   
   ```bash
   $ curl -X POST localhost:3001/api/data-source/fetch-url \
       -H "Content-Type: application/json" \
       -d 
'{"url":"https://archive.ics.uci.edu/ml/machine-learning-databases/iris/iris.data"}'
   
   → {"rows":150, "columns":["5.1","3.5","1.4","0.2","Iris-setosa"], 
"format":"csv"} ✅
   ```
   
   ---
   
   ## Files Changed
   
   **New:** `agent-service/src/api/data-source-api.ts` (3 endpoints), 
`data-source-tools.ts` (agent tool)
   
   **Modified:** `user-dataset.component.*` (URL input + drop zone), 
`dataset.service.ts` (fetch methods), `proxy.config.json`, 
`DatasetSearchQueryBuilder.scala` (fix: new datasets now appear in list 
immediately)


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