add(vision): add new documentation for vision

Author: hahuyhoang411

docs/docs/features/vision.md

@@ -0,0 +1,65 @@
+---
+title: Vision
+description: Inference engine for vision, the same as OpenAI's
+keywords: [Nitro, Jan, fast inference, inference server, local AI, large language model, OpenAI compatible, open source, llava, bakllava, vision]
+---
+
+## Load model
+Just like loading the Chat model, for the vision model, you need two specific types:
+- the `GGUF model`
+- the `mmproj model`.
+
+You can load the model using:
+
+```bash title="Load Model" {3,4}
+curl -X POST 'http://127.0.0.1:3928/inferences/llamacpp/loadmodel' -H 'Content-Type: application/json' -d '{
+   "llama_model_path": "/path/to/gguf/model/",
+   "mmproj": "/path/to/mmproj/model/",
+   "ctx_len": 2048,
+   "ngl": 100,
+   "cont_batching": false,
+   "embedding": false,
+   "system_prompt": "",
+   "user_prompt": "\n### Instruction:\n",
+   "ai_prompt": "\n### Response:\n"
+ }'
+```
+
+Download the models here:
+- [Llava Model](https://huggingface.co/jartine/llava-v1.5-7B-GGUF/tree/main): Large Language and Vision Assistant achieves SoTA on 11 benchmarks.
+- [Bakllava Model](https://huggingface.co/mys/ggml_bakllava-1/tree/main) is a Mistral 7B base augmented with the LLaVA architecture.
+
+## Inference
+
+Nitro currently only works with images converted to base64 format. Use this [base64 converter](https://www.base64-image.de/) to prepare your images.
+
+To get the model's understanding of an image, do the following:
+
+```bash title="Inference"
+curl http://127.0.0.1:3928/v1/chat/completions \
+  -H "Content-Type: application/json" \
+  -H "Authorization: Bearer $OPENAI_API_KEY" \
+  -d '{
+    "model": "gpt-4-vision-preview",
+    "messages": [
+      {
+        "role": "user",
+        "content": [
+          {
+            "type": "text",
+            "text": "What’s in this image?"
+          },
+          {
+            "type": "image_url",
+            "image_url": {
+              "url": "<base64>"
+            }
+          }
+        ]
+      }
+    ],
+    "max_tokens": 300
+  }'
+```
+
+If the base64 string is too long and causes errors, consider using [Postman](https://www.postman.com/) as an alternative.

docs/sidebars.js

@@ -39,6 +39,7 @@ const sidebars = {
       items: [
         "features/chat",
         "features/embed",
+        "features/vision"
       ],
     },
     {