docs: added js lambda and onnx

docs/udfs/onnx.md

@@ -0,0 +1,56 @@
+# ONNX
+
+ONNX, or Open Neural Network Exchange, is an open-source format designed to represent machine learning models. It provides a standardized way to describe models so that they can be easily exchanged between different deep learning frameworks. ONNX is supported by various frameworks such as PyTorch, TensorFlow, Microsoft Cognitive Toolkit (CNTK), and others, allowing interoperability and flexibility in deploying models across different platforms.
+
+Dozer supports ONNX models and allows you to deploy them as APIs. This enables you to use your models in production without having to write any additional code. For instance, you can use a pre-trained model to predict probabilities of a particular event, such as a customer credit score, or other use cases.
+
+## Configuration
+
+Add the following block to your YAML file to register ONNX models.
+
+```yaml
+sql : |
+    SELECT torch_jit(col1, col2) INTO output FROM input;
+```
+
+```yaml
+udfs:
+    - name: torch_jit
+      config: !Onnx
+        path: ./model.onnx
+```
+
+`torch_jit` is the function which would run the ONNX model on `col1, col2` as input returning the output in output` column.
+
+### Parameters  
+
+| **Parameter Name** | **Type**             | **Description**                                                                                                                                                                                                                                                           |
+|--------------------|----------------------|-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
+| `path`             | String               | Path to the ONNX model.                                                                                                                                                                                    |
+## Running the ONNX Model
+
+### Pre-requisites
+
+- Enabling ONNX feature while building Dozer.
+  ```bash
+  cargo install --path dozer-cli --features onnx --locked
+  ```
+- Installing ONNX runtime.
+  ```bash
+    pip install onnxruntime
+    ```
+
+Run App to start ingesting data into Dozer.
+
+```bash
+dozer run app
+```
+### To use ONNX on Dozer Cloud
+
+```
+dozer cloud deploy -c dozer-config.yaml -c model.onnx
+```
+
+## Trying it out
+
+To test a ONNX sample, clone the `dozer-samples` GitHub repo and follow the steps described [here](https://github.com/getdozer/dozer-samples/tree/main/usecases/onnx)

sidebars.js

@@ -128,8 +128,18 @@ const sidebars = {
         'transforming-data/windowing'
       ]
     },
-
-
+    {
+      type: 'category',
+      label: 'User Defined Functions',
+      link: {
+        type: 'generated-index',
+        title: 'User Defined Functions',
+      },
+      items: [
+       'udfs/lambda-functions',
+        'udfs/onnx',
+      ]
+    },
     {
       type: 'category',
       label: 'Accessing Data',
@@ -145,18 +155,6 @@ const sidebars = {
         'accessing-data/authorization'
       ]
     },
-    //'lambda-functions',
-    // {
-    //   type: 'category',
-    //   label: 'Deployment',
-    //   link: {
-    //     type: 'doc',
-    //     id: 'deployment',
-    //   },
-    //   items: []
-    // }
-
-
   ],
 };