Merge pull request #450 from Kiln-AI/main

Update docs

Author: scosman

app/desktop/pyproject.toml

@@ -1,3 +1,7 @@
+[build-system]
+requires = ["hatchling"]
+build-backend = "hatchling.build"
+
 [project]
 name = "kiln-studio-desktop"
 version = "0.1.0"
@@ -11,6 +15,9 @@ dependencies = [
     "scipy>=1.15.2",
 ]
 
+# We don't really want to build a wheel for desktop, it's a pyinstaller project. This is a minimal build to take care of errors.
+[tool.hatch.build.targets.wheel]
+only-include = ["__init__.py"]
 
 [tool.uv.sources]
 kiln-server = { workspace = true }

app/web_ui/src/routes/(app)/evals/[project_id]/[task_id]/create_evaluator/select_eval_template.svelte

@@ -412,7 +412,7 @@
     <FormElement
       label="Failure Example - Recommended"
       description="An example of model output that should fail the eval."
-      info_description="Including an example helps the judge model understand the issue."
+      info_description="Examples help the judge model understand the issue. The format is flexible (plain text); you can include the entire input/output or just the relevant portion. You can include a description or multiple examples if needed."
       inputType="textarea"
       id="failure_example"
       optional={true}
@@ -421,7 +421,7 @@
     <FormElement
       label="Passing Example"
       description="An example of model output that should pass the eval."
-      info_description="Including an example helps the judge model understand the issue."
+      info_description="Examples help the judge model understand the issue. The format is flexible (plain text); you can include the entire input/output or just the relevant portion. You can include a description or multiple examples if needed."
       inputType="textarea"
       id="pass_example"
       optional={true}

libs/core/README.md

@@ -32,6 +32,7 @@ The library has a [comprehensive set of docs](https://kiln-ai.github.io/Kiln/kil
 
 ## Table of Contents
 
+- [Connecting AI Providers](#connecting-ai-providers-openai-openrouter-ollama-etc)
 - [Using the Kiln Data Model](#using-the-kiln-data-model)
   - [Understanding the Kiln Data Model](#understanding-the-kiln-data-model)
   - [Datamodel Overview](#datamodel-overview)
@@ -40,6 +41,7 @@ The library has a [comprehensive set of docs](https://kiln-ai.github.io/Kiln/kil
   - [Using your Kiln Dataset in a Notebook or Project](#using-your-kiln-dataset-in-a-notebook-or-project)
   - [Using Kiln Dataset in Pandas](#using-kiln-dataset-in-pandas)
   - [Building and Running a Kiln Task from Code](#building-and-running-a-kiln-task-from-code)
+  - [Tagging Task Runs Programmatically](#tagging-task-runs-programmatically)
   - [Adding Custom Model or AI Provider from Code](#adding-custom-model-or-ai-provider-from-code)
 - [Full API Reference](#full-api-reference)
 
@@ -49,6 +51,12 @@ The library has a [comprehensive set of docs](https://kiln-ai.github.io/Kiln/kil
 pip install kiln-ai
 ```
 
+## Connecting AI Providers (OpenAI, OpenRouter, Ollama, etc)
+
+The easiest way to connect AI providers is to use the Kiln app UI. Once connected in the UI, credentials will be stored to `~/.kiln_ai/settings.yml`, which will be available to the library.
+
+For configuring credentials from code or connecting custom servers/model, see [Adding Custom Model or AI Provider from Code](#adding-custom-model-or-ai-provider-from-code).
+
 ## Using the Kiln Data Model
 
 ### Understanding the Kiln Data Model
@@ -146,7 +154,10 @@ item = kiln_ai.datamodel.TaskRun(
             type=kiln_ai.datamodel.DataSourceType.human,
             properties={"created_by": "Jane Doe"},
         ),
-        rating=kiln_ai.datamodel.TaskOutputRating(score=5,type="five_star"),
+        rating=kiln_ai.datamodel.TaskOutputRating(
+            value=5,
+            type=kiln_ai.datamodel.datamodel_enums.five_star,
+        ),
     ),
 )
 item.save_to_file()
@@ -237,6 +248,25 @@ for run in task.runs():
 
 ```
 
+## Tagging Task Runs Programmatically
+
+You can also tag your Kiln Task runs programmatically:
+
+```py
+# Load your Kiln Task from disk
+task_path = "/Users/youruser/Kiln Projects/test project/tasks/632780983478 - Joke Generator/task.kiln"
+task = kiln_ai.datamodel.Task.load_from_file(task_path)
+
+for run in task.runs():
+    # Parse the task output from JSON
+    output = json.loads(run.output.output)
+
+    # Add a tag if the punchline is unusually short
+    if len(output["punchline"]) < 100:
+        run.tags.append("very_short")
+        run.save_to_file()  # Persist the updated tags
+```
+
 ### Adding Custom Model or AI Provider from Code
 
 You can add additional AI models and providers to Kiln.