Add phi3 v tutorial

docs/genai/tutorials/phi3-python.md

@@ -4,7 +4,7 @@ description: Small but mighty. Run Phi-3 with ONNX Runtime in 3 easy steps.
 has_children: false
 parent: Tutorials
 grand_parent: Generate API (Preview)
-nav_order: 1
+nav_order: 2
 ---
 
 # Run Phi-3 language models with the ONNX Runtime generate() API

docs/genai/tutorials/phi3-v.md

@@ -0,0 +1,143 @@
+---
+title: Phi-3 vision tutorial
+description: Small and mighty useful. Run Phi-3 vision with ONNX Runtime.
+has_children: false
+parent: Tutorials
+grand_parent: Generate API (Preview)
+nav_order: 1
+image: /images/coffee.png
+---
+
+# Run the Phi-3 vision model with the ONNX Runtime generate() API
+{: .no_toc }
+
+The Phi-3 vision model is a small, but powerful multi modal model that allows you to use both image and text to output text. It is used in scenarios such as describing the content of images in detail.
+
+The Phi-3 vision model is supported by versions of onnxruntime-genai 0.3.0-rc2 and later.
+
+You can download the models here:
+
+* [https://microsoft/Phi-3-vision-128k-instruct-onnx-cpu](https://microsoft/Phi-3-vision-128k-instruct-onnx-cpu)
+* [https://microsoft/Phi-3-vision-128k-instruct-onnx-cuda](https://microsoft/Phi-3-vision-128k-instruct-onnx-cuda)
+
+Support for DirectML is coming soon!
+
+* TOC placeholder
+{:toc}
+
+## Setup
+
+1. Install the git large file system extension
+
+   HuggingFace uses `git` for version control. To download the ONNX models you need `git lfs` to be installed, if you do not already have it.
+
+   * Windows: `winget install -e --id GitHub.GitLFS` (If you don't have winget, download and run the `exe` from the [official source](https://docs.github.com/en/repositories/working-with-files/managing-large-files/installing-git-large-file-storage?platform=windows))
+   * Linux: `apt-get install git-lfs`
+   * MacOS: `brew install git-lfs`
+
+   Then run `git lfs install`
+
+2. Install the HuggingFace CLI
+
+   ```bash
+   pip install huggingface-hub[cli]
+   ```
+
+## Choose your platform
+
+If you have an NVIDIA GPU, that will give the best performance right now.
+
+The models will also run on CPU, but they will be slower.
+
+Support for Windows machines with GPUs other than NVIDIA is coming soon!
+
+**Note: Only one package and model is required based on your hardware. That is, only execute the steps for one of the following sections**
+
+## Run with NVIDIA CUDA
+
+1. Download the model
+
+   ```bash
+   huggingface-cli download microsoft/Phi-3-vision-128k-instruct-onnx-cuda --include cuda-int4-rtn-block-32/* --local-dir .
+   ```
+   This command downloads the model into a folder called `cuda-int4-rtn-block-32`.
+
+2. Install the generate() API
+
+   ```
+   pip install numpy
+   pip install --pre onnxruntime-genai-cuda --index-url=https://aiinfra.pkgs.visualstudio.com/PublicPackages/_packaging/onnxruntime-genai/pypi/simple/
+   ```
+
+3. Setup your CUDA environment
+
+   Please follow the steps [here](../howto/setup-cuda-env.md) to setup the CUDA environment.
+
+
+4. Run the model
+
+   Run the model with [phi3v.py](https://github.com/microsoft/onnxruntime-genai/blob/main/examples/python/phi3v.py).
+
+   ```bash
+   curl https://raw.githubusercontent.com/microsoft/onnxruntime-genai/main/examples/python/phi3v.py -o phi3v.py
+   python phi3v.py -m cuda-int4-rtn-block-32 
+   ```
+
+   Enter the path to an image file and a prompt, and the model uses the image and prompt to give you an answer.
+
+   For example: `Describe the image`
+
+   ![coffee](../../../images/coffee.png)
+
+   ```
+   The image shows a cup of coffee with a latte art design on top. The coffee is a light brown color,
+   and the art is white with a leaf-like pattern. The cup is white and has a handle on one side.</s>
+   ```
+
+## Run on CPU
+
+1. Download the model
+
+   ```bash
+   huggingface-cli download microsoft/Phi-3-vision-128k-instruct-onnx-cpu --include cpu-int4-rtn-block-32-acc-level-4/* --local-dir .
+   ```
+
+   This command downloads the model into a folder called `cpu-int4-rtn-block-32-acc-level-4`
+
+2. Install the generate() API for CPU
+
+   ```
+   pip install numpy
+   pip install --pre onnxruntime-genai
+   ```
+
+3. Run the model
+
+   Run the model with [phi3v.py](https://github.com/microsoft/onnxruntime-genai/blob/main/examples/python/phi3v.py).
+
+   ```bash
+   curl https://raw.githubusercontent.com/microsoft/onnxruntime-genai/main/examples/python/phi3v.py -o phi3v.py
+   python phi3v.py -m cpu-int4-rtn-block-32-acc-level-4
+   ```
+
+   Enter the path to an image file and a prompt, and the model uses the image and prompt to give you an answer.
+
+   For example: `Convert this image to markdown format`
+
+   ![Excel table with cookie sales figures](../../../images/table.png)
+
+   ```
+   | Product             | Qtr 1      | Qtr 2      | Grand Total |
+   |---------------------|------------|------------|-------------|
+   | Chocolade           | $744.60    | $162.56    | $907.16     |
+   | Gummibarchen        | $5,079.60  | $1,249.20  | $6,328.80   |
+   | Scottish Longbreads | $1,267.50  | $1,062.50  | $2,330.00   |
+   | Sir Rodney's Scones | $1,418.00  | $756.00    | $2,174.00   |
+   | Tarte au sucre      | $4,728.00  | $4,547.92  | $9,275.92   |
+   | Chocolate Biscuits  | $943.89    | $349.60    | $1,293.49   |
+   | Total               | $14,181.59 | $8,127.78  | $22,309.37  |
+
+   The table lists various products along with their sales figures for Qtr 1, Qtr 2, and the Grand Total.
+   The products include Chocolade, Gummibarchen, Scottish Longbreads, Sir Rodney's Scones, Tarte au sucre,
+   and Chocolate Biscuits. The Grand Total column sums up the sales for each product across the two quarters.</s>
+   ```

src/routes/components/generative-ai-hero.svelte

@@ -15,7 +15,7 @@
 				and more.
 			</p>
 			<br />
-			<!-- a href="./generative-ai" class="btn btn-primary">Learn more about ORT & Generative AI →</a -->
+			<a href="https://onnxruntime.ai/docs/genai" class="btn btn-primary">Learn more about ONNX Runtime & Generative AI →</a>
 		</div>
 		<div class="m-auto overflow:hidden">
 			<Ortgenerativeai />