update

README.md

@@ -244,6 +244,40 @@ xinfer.serve_model(
 )
 ```
 
+You can now query the endpoint with an image and prompt.
+
+```bash
+curl -X 'POST' \
+  'http://127.0.0.1:8000/infer' \
+  -H 'accept: application/json' \
+  -H 'Content-Type: application/json' \
+  -d '{
+  "image": "https://raw.githubusercontent.com/dnth/x.infer/refs/heads/main/assets/demo/00aa2580828a9009.jpg",
+  "infer_kwargs": {"prompt": "Caption this image"}
+}'
+```
+
+Or in Python:
+
+```python
+import requests
+
+url = "http://127.0.0.1:8000/infer"
+headers = {
+    "accept": "application/json",
+    "Content-Type": "application/json"
+}
+payload = {
+    "image": "https://raw.githubusercontent.com/dnth/x.infer/refs/heads/main/assets/demo/00aa2580828a9009.jpg",
+    "infer_kwargs": {
+        "prompt": "Caption this image"
+    }
+}
+
+response = requests.post(url, headers=headers, json=payload)
+print(response.json())
+```
+
 ### Add Your Own Model
 
 + **Step 1:** Create a new model class that implements the `BaseModel` interface.

nbs/query.ipynb

@@ -0,0 +1,64 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'response': 'A parade with a marching band and a flag-bearing figure passes through a town, with spectators lining the street and a church steeple visible in the background.'}\n"
+     ]
+    }
+   ],
+   "source": [
+    "import requests\n",
+    "\n",
+    "url = \"http://127.0.0.1:8000/infer\"\n",
+    "headers = {\n",
+    "    \"accept\": \"application/json\",\n",
+    "    \"Content-Type\": \"application/json\"\n",
+    "}\n",
+    "payload = {\n",
+    "    \"image\": \"https://raw.githubusercontent.com/dnth/x.infer/refs/heads/main/assets/demo/00aa2580828a9009.jpg\",\n",
+    "    \"infer_kwargs\": {\n",
+    "        \"prompt\": \"Caption this image\"\n",
+    "    }\n",
+    "}\n",
+    "\n",
+    "response = requests.post(url, headers=headers, json=payload)\n",
+    "print(response.json())"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "xinfer",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.10.15"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}