Merge branch 'master' into feat/presidio-entity-guardrail

.github/workflows/test.yaml

@@ -276,6 +276,11 @@ jobs:
           --health-start-period=10s
       weave_clickhouse:
         image: clickhouse/clickhouse-server
+        env:
+          CLICKHOUSE_DEFAULT_ACCESS_MANAGEMENT: 1
+          CLICKHOUSE_USER: default
+          CLICKHOUSE_PASSWORD: ""
+          CLICKHOUSE_DB: default
         ports:
           - "8123:8123"
         options: --health-cmd "wget -nv -O- 'http://localhost:8123/ping' || exit 1" --health-interval=5s --health-timeout=3s

README.md

@@ -104,3 +104,4 @@ We're in the process of 🧹 cleaning up 🧹. This codebase contains a large am
 The Weave Tracing code is mostly in: `weave/trace` and `weave/trace_server`.
 
 The Weave Evaluations code is mostly in `weave/flow`.
+

docs/docs/guides/core-types/datasets.md

@@ -3,15 +3,24 @@ import TabItem from '@theme/TabItem';
 
 # Datasets
 
-`Dataset`s enable you to collect examples for evaluation and automatically track versions for accurate comparisons. Use this to download the latest version locally with a simple API.
+Weave `Dataset`s help you to organize, collect, track, and version examples for LLM application evaluation for easy comparison. You can create and interact with `Dataset`s programmatically and via the UI. 
 
-This guide will show you how to:
+This page describes:
 
-- Publish `Dataset`s to W&B
-- Download the latest version
-- Iterate over examples
+- Basic `Dataset` operations in Python and TypeScript and how to get started  
+- How to create a `Dataset` in Python and TypeScript from objects such as Weave [calls](../tracking/tracing.mdx)
+- Available operations on a `Dataset` in the UI
 
-## Quickstart
+## `Dataset` quickstart
+
+The following code samples demonstrate how to perform fundamental `Dataset` operations using Python and TypeScript. Using the SDKs, you can:
+
+- Create a `Dataset`
+- Publish the `Dataset`
+- Retrieve the `Dataset`
+- Access a specific example in the `Dataset`
+
+Select a tab to see Python and TypeScript-specific code. 
 
 <Tabs groupId="programming-language" queryString>
   <TabItem value="python" label="Python" default>
@@ -69,55 +78,114 @@ This guide will show you how to:
   </TabItem>
 </Tabs>
 
-## Alternate constructors
+## Create a `Dataset` from other objects
 
 <Tabs groupId="programming-language" queryString>
   <TabItem value="python" label="Python" default>
-  Datasets can also be constructed from common Weave objects like `Call`s, and popular python objects like `pandas.DataFrame`s.
-  <Tabs groupId="use-case">
-    <TabItem value="from-calls" label="From Calls">
-    This can be useful if you want to create an example from specific examples.
+  In Python, `Dataset`s can also be constructed from common Weave objects like [calls](../tracking/tracing.mdx), and Python objects like `pandas.DataFrame`s. This feature is useful if you want to create an example `Dataset` from specific examples.
 
-    ```python
-    @weave.op
-    def model(task: str) -> str:
-        return f"Now working on {task}"
+  ### Weave call
 
-    res1, call1 = model.call(task="fetch")
-    res2, call2 = model.call(task="parse")
+  To create a `Dataset` from one or more Weave calls, retrieve the call object(s), and add them to a list in the `from_calls` method.
 
-    dataset = Dataset.from_calls([call1, call2])
-    # Now you can use the dataset to evaluate the model, etc.
-    ```
-    </TabItem>
+  ```python
+  @weave.op
+  def model(task: str) -> str:
+      return f"Now working on {task}"
 
-    <TabItem value="from-pandas" label="From Pandas">
-    You can also freely convert between `Dataset`s and `pandas.DataFrame`s.
+  res1, call1 = model.call(task="fetch")
+  res2, call2 = model.call(task="parse")
 
-    ```python
-    import pandas as pd
+  dataset = Dataset.from_calls([call1, call2])
+  # Now you can use the dataset to evaluate the model, etc.
+  ```
 
-    df = pd.DataFrame([
-        {'id': '0', 'sentence': "He no likes ice cream.", 'correction': "He doesn't like ice cream."},
-        {'id': '1', 'sentence': "She goed to the store.", 'correction': "She went to the store."},
-        {'id': '2', 'sentence': "They plays video games all day.", 'correction': "They play video games all day."}
-    ])
-    dataset = Dataset.from_pandas(df)
-    df2 = dataset.to_pandas()
+  ### Pandas DataFrame
 
-    assert df.equals(df2)
-    ```
+  To create a `Dataset` from a Pandas `DataFrame` object, use the `from_pandas` method. 
 
-    </TabItem>
+  To convert the `Dataset` back, use `to_pandas`.
 
-  </Tabs>
+  ```python
+  import pandas as pd
 
-  </TabItem>
-  <TabItem value="typescript" label="TypeScript">
+  df = pd.DataFrame([
+      {'id': '0', 'sentence': "He no likes ice cream.", 'correction': "He doesn't like ice cream."},
+      {'id': '1', 'sentence': "She goed to the store.", 'correction': "She went to the store."},
+      {'id': '2', 'sentence': "They plays video games all day.", 'correction': "They play video games all day."}
+  ])
+  dataset = Dataset.from_pandas(df)
+  df2 = dataset.to_pandas()
 
-```typescript
-This feature is not available in TypeScript yet.  Stay tuned!
-```
+  assert df.equals(df2)
+  ```
 
   </TabItem>
+  <TabItem value="typescript" label="TypeScript">
+   This feature is not currently available in TypeScript.  Stay tuned!
+  </TabItem>
 </Tabs>
+
+## Edit and delete a `Dataset` in the UI
+
+:::tip
+To follow along with the example screenshots shown in this section, run the code shown in the [`Dataset` quickstart](#dataset-quickstart) and navigate to the **Datasets** tab in the Weave UI.
+:::
+
+You can edit and delete existing `Dataset`s from the **Datasets** tab in the UI. To create a `Dataset`, [use one of the SDKs](#dataset-quickstart). 
+
+### Edit a `Dataset` 
+
+1. Navigate to the Weave project containing the `Dataset` you want to edit.
+2. From the sidebar, select **Datasets**. Your available `Dataset`s display.
+
+   ![Dataset UI](./imgs/datasetui.png)
+
+3. In the **Object** column, click the name and version of the `Dataset` you want to edit. A pop-out modal showing `Dataset` information like name, version, author, and `Dataset` rows displays.
+
+   ![View `Dataset` information](./imgs/datasetui-popout.png)
+
+4. In the upper right-hand corner of the modal, click the **Edit dataset** button (the pencil icon). An **+ Add row** button displays at the bottom of the modal.
+
+    ![`Dataset` UI- Add row icon](./imgs/datasetui-popout-edit.png)
+
+5. Click **+ Add row**. A green row displays at the top of your existing `Dataset` rows, indicating that you can add a new row to the `Dataset`. 
+
+    ![`Dataset` UI](./imgs/datasetui-popout-edit-green.png)
+
+6. To add data to a new row, click the desired column within that row. The default **id** column in a `Dataset` row cannot be edited, as Weave assigns it automatically upon creation. An editing modal appears with **Text**, **Code**, and **Diff** options for formatting.
+
+    ![`Dataset` UI - Add data to a column and format.](./imgs/datasetui-popout-edit-addcol.png)
+
+7. Repeat step 6 for each column that you want to add data to in the new row. 
+
+    ![`Dataset` UI - Add data to all columns.](./imgs/datasetui-popout-edit-colsadded.png)
+
+8. Repeat step 5 for each row that you want to add to the `Dataset`.
+
+9. Once you're done editing, publish your `Dataset` by clicking **Publish** in the upper right-hand corner of the modal. Alternatively, if you don't want to publish your changes, click **Cancel**. 
+
+    ![`Dataset` UI - Publish or cancel.](./imgs/datasetui-popout-edit-publish.png)
+
+   Once published, the new version of the `Dataset` with updated rows is available in the UI. 
+
+     ![`Dataset` UI - Published metadata.](./imgs/datasetui-popout-edit-published-meta.png)
+     ![`Dataset` UI - Published rows.](./imgs/datasetui-popout-edit-published-rows.png)
+
+### Delete a `Dataset`
+
+1. Navigate to the Weave project containing the `Dataset` you want to edit.
+2. From the sidebar, select **Datasets**. Your available `Dataset`s display.
+3. In the **Object** column, click the name and version of the `Dataset` you want to delete. A pop-out modal showing `Dataset` information like name, version, author, and `Dataset` rows displays.
+
+4. In the upper right-hand corner of the modal, click the trash can icon. 
+
+   ![`Dataset` UI - Delete a `Dataset` icon.](./imgs/dataset-trashcan.png)
+
+   A pop-up modal prompting you to confirm `Dataset` deletion displays. 
+
+   ![`Dataset` UI - Confirm deletion modal.](./imgs/datasetui-delete-modal.png)
+
+5. In the pop-up modal, click the red **Delete** button to delete the `Dataset`. Alternatively, click **Cancel** if you don't want to delete the `Dataset`. 
+
+   Now, the `Dataset` is deleted, and no longer visible in the **Datasets** tab in your Weave dashboard.