Merge pull request #677 from roboflow/nick/docs/schema-api-and-notebo…

…ok-fix

Add workflow schema api docs

docs/notebooks/inference_pipeline_rtsp.ipynb

@@ -7,7 +7,7 @@
     "# InferencePipeline on RTSP Stream\n",
     "\n",
     "---\n",
-    "[![Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://github.com/roboflow/notebooks/blob/main/notebooks/inferencePipeline.ipynb)\n",
+    "[![Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/roboflow/inference/blob/main/docs/notebooks/inference_pipeline_rtsp.ipynb)\n",
     "\n",
     "The Roboflow Inference Pipeline is a drop-in replacement for the Hosted Inference API that can be deployed on your own hardware. The Inference Pipeline interface is made for streaming and is likely the best route to go for real time use cases. It is an asynchronous interface that can consume many different video sources including local devices (like webcams), RTSP video streams, video files, etc. With this interface, you define the source of a video stream and sinks.\n",
     "\n",

docs/notebooks/rgb_anomaly_detection.ipynb

@@ -8,7 +8,7 @@
     "# RGB Anomaly Detection\n",
     "\n",
     "---\n",
-    "[![Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://github.com/roboflow/notebooks/blob/main/notebooks/rgb_anomalyDetection.ipynb)\n",
+    "[![Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/roboflow/inference/blob/main/docs/notebooks/rgb_anomaly_detection.ipynb)\n",
     "\n",
     "In this cookbook, we identify color / RGB anomalies for segmented items. Capture a base image to extract your ground truth RGB with Roboflow and compare to neew data collected. In this scenario, we are assessing variations in logo color.\n",
     "\n",

docs/workflows/schema_api.md

@@ -0,0 +1,64 @@
+# Workflows Schema API
+
+The Workflows Schema API provides developers with a clear, programmatic understanding of a workflow's structure, inputs, and outputs. It addresses the challenge of programmatically determining a workflow's input requirements and output types.
+
+## Purpose and Benefits
+
+The API offers structured access to:
+
+1. **Input Parameters**: Required workflow inputs.
+2. **Output Structure**: Details of the returned data.
+3. **Type Hints**: Expected data types for inputs and outputs.
+4. **Schemas of Kinds**: Detailed schemas for complex data types.
+
+This enables developers to:
+
+- Validate inputs programmatically
+- Understand output data structures
+- Integrate workflows into larger systems
+- Generate documentation or UIs based on workflow requirements
+
+## Using the API
+[![Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/roboflow/inference/blob/main/docs/notebooks/workflow_schema_api.ipynb)
+
+```python
+import requests
+
+WORKSPACE_NAME = "workspace-name"
+WORKFLOW_ID = "workflow-id"
+INFERENCE_SERVER_URL = "https://detect.roboflow.com"
+
+WORKFLOW_SCHEMA_ENDPOINT = f"{INFERENCE_SERVER_URL}/{WORKSPACE_NAME}/workflows/{WORKFLOW_ID}/describe_interface"
+ROBOFLOW_API_KEY = "Your Roboflow API Key"
+
+headers = {
+    "Content-Type": "application/json",
+}
+
+data = {
+    "api_key": ROBOFLOW_API_KEY,
+}
+
+res = requests.post(WORKFLOW_SCHEMA_ENDPOINT, headers=headers, json=data)
+
+schema = res.json()
+
+inputs = schema["inputs"]
+outputs = schema["outputs"]
+kinds_schemas = schema["kinds_schemas"]
+typing_hints = schema["typing_hints"]
+```
+
+## Inputs and Outputs
+
+The `inputs` and `outputs` keys show all of the inputs and outputs the workflow expects to run and return.
+
+## Typing Hints
+
+The `typing_hints` key shows the data types of the inputs and outputs.
+
+## Kinds Schemas
+
+The `kinds_schemas` key returns an OpenAPI specification with more detailed information about the data 
+types being returned and how to parse them. For example, the `object_detection_prediction` contains 
+information about the nested data that will be present.

mkdocs.yml

@@ -89,6 +89,7 @@ nav:
         - Dynamic Python Blocks: workflows/custom_python_code_blocks.md
         - Versioning: workflows/versioning.md
         - Testing: workflows/testing.md
+        - Schema API: workflows/schema_api.md
   - Reference:
       - Inference Pipeline: using_inference/inference_pipeline.md
       - Active Learning: