small fix

README.md

@@ -1,6 +1,6 @@
 # Groundlight Python SDK
 
-Groundlight makes it simple to build reliable visual applications. Read the [full documentation here](https://code.groundlight.ai/python-sdk/).
+Groundlight makes it simple to build reliable visual applications. Read the [full documentation here](https://code.groundlight.ai).
 
 ## Computer Vision powered by Natural Language
 
@@ -30,7 +30,7 @@ _Note: The SDK is currently in "beta" phase. Interfaces are subject to change in
 
 Some more resources you might like:
 
-- [Code Documentation](https://code.groundlight.ai/python-sdk/docs/getting-started)
+- [Code Documentation](https://code.groundlight.ai/docs/getting-started)
 - [Python SDK on PyPi](https://pypi.org/project/groundlight/) or [GitHub](https://github.com/groundlight/python-sdk)
 - [Company](https://www.groundlight.ai/)
 - [Login to Groundlight App](https://app.groundlight.ai/)

docs/README.md

@@ -15,7 +15,7 @@ cd ..
 make develop-docs-comprehensive
 ```
 
-and then open [http://localhost:3000/python-sdk](http://localhost:3000/python-sdk).
+and then open [http://localhost:3000](http://localhost:3000).
 
 
 ## Running docs tests

docs/docs/building-applications/6-async-queries.md

@@ -7,7 +7,7 @@ sidebar_position: 5
 Groundlight provides a simple interface for submitting asynchronous queries. This is useful for times in which the thread or process or machine submitting image queries is not the same thread or machine that will be retrieving and using the results. For example, you might have a forward deployed robot or camera that submits image queries to Groundlight, and a separate server that retrieves the results and takes action based on them. We will refer to these two machines as the **submitting machine** and the **retrieving machine**.
 
 ## Setup Submitting Machine
-On the **submitting machine**, you will need to install the Groundlight Python SDK. Then you can submit image queries asynchronously using the `ask_async` interface (read the full documentation [here](pathname:///python-sdk/api-reference-docs/#groundlight.client.Groundlight.ask_async)). `ask_async` submits your query and returns as soon as the query is submitted. It does not wait for an answer to be available prior to returning to minimize the time your program spends interacting with Groundlight. As a result, the `ImageQuery` object `ask_async` returns lacks a `result` (the `result` field will be `None`). This is acceptable for this use case as the **submitting machine** is not interested in the result. Instead, the **submitting machine** just needs to communicate the `ImageQuery.id`s to the **retrieving machine** - this might be done via a database, a message queue, or some other mechanism. For this example, we assume you are using a database where you save the `ImageQuery.id` to it via `db.save(image_query.id)`.
+On the **submitting machine**, you will need to install the Groundlight Python SDK. Then you can submit image queries asynchronously using the `ask_async` interface (read the full documentation [here](pathname:///api-reference-docs/#groundlight.client.Groundlight.ask_async)). `ask_async` submits your query and returns as soon as the query is submitted. It does not wait for an answer to be available prior to returning to minimize the time your program spends interacting with Groundlight. As a result, the `ImageQuery` object `ask_async` returns lacks a `result` (the `result` field will be `None`). This is acceptable for this use case as the **submitting machine** is not interested in the result. Instead, the **submitting machine** just needs to communicate the `ImageQuery.id`s to the **retrieving machine** - this might be done via a database, a message queue, or some other mechanism. For this example, we assume you are using a database where you save the `ImageQuery.id` to it via `db.save(image_query.id)`.
 
 ```python notest
 from groundlight import Groundlight
@@ -54,7 +54,7 @@ while image_query_id is not None:
 ```
 
 ## Important Considerations
-When you submit an image query asynchronously, ML prediction on your query is **not** instant. So attempting to retrieve the result immediately after submitting an async query will likely result in an `UNCLEAR` result as Groundlight is still processing your query. Instead, if your code needs a `result` synchronously we recommend using one of our methods with a polling mechanism to retrieve the result. You can see all of the interfaces available in the documentation [here](pathname:///python-sdk/api-reference-docs/#groundlight.client.Groundlight).
+When you submit an image query asynchronously, ML prediction on your query is **not** instant. So attempting to retrieve the result immediately after submitting an async query will likely result in an `UNCLEAR` result as Groundlight is still processing your query. Instead, if your code needs a `result` synchronously we recommend using one of our methods with a polling mechanism to retrieve the result. You can see all of the interfaces available in the documentation [here](pathname:///api-reference-docs/#groundlight.client.Groundlight).
 
 ```python notest
 from groundlight import Groundlight

docs/docusaurus.config.js

@@ -99,7 +99,7 @@ const config = {
             position: "left",
           },
           {
-            href: "pathname:///python-sdk/api-reference-docs/",
+            href: "pathname:///api-reference-docs/",
             label: "API Reference",
             position: "left",
           },