chore: Update dependencies and improve documentation examples

.github/workflows/test.yaml

@@ -54,8 +54,8 @@ jobs:
         run: |
           # Run a basic test to ensure the minimal package works
           uv run python -c "import wurzel; print('Minimal installation successful')"
-          # Run only core tests that don't require optional dependencies
-          uv run pytest tests/ -k "not (qdrant or milvus or docling or openai or transformers or tlsh or splitter)" -v --ignore=tests/splitter --ignore=tests/splitter_test.py
+          # Core tests only (no optional deps); skip doc examples (run in full install)
+          uv run pytest tests/ -k "not (qdrant or milvus or docling or openai or transformers or tlsh or splitter)" -v --ignore=tests/splitter --ignore=tests/splitter_test.py --ignore=tests/test_doc_examples.py
 
 
       - name: Test full installation

README.md

@@ -47,12 +47,19 @@ wurzel inspect wurzel.<step_path>
 ### 2. Programmatic Execution (Python)
 Run a step using the snippet below:
 ```python
-from wurzel.steps import step
+import os
 from pathlib import Path
+
 from wurzel.step_executor import BaseStepExecutor
+from wurzel.steps.manual_markdown import ManualMarkdownStep
 
+# Create input dir and set folder (required by ManualMarkdownStep)
+input_dir = Path("./input")
+input_dir.mkdir(exist_ok=True)
+abs_input = input_dir.resolve()
+os.environ["MANUALMARKDOWNSTEP__FOLDER_PATH"] = str(abs_input)
 with BaseStepExecutor() as ex:
-    ex(step, set(Path("./input")), Path("./output"))
+    ex(ManualMarkdownStep, {abs_input}, Path("./output"))
 ```
 
 ### Building your one step

docs/backends/argoworkflows.md

@@ -364,7 +364,6 @@ container:
 Use the Argo backend directly in Python:
 
 ```python
-from pathlib import Path
 from wurzel.backend.backend_argo import ArgoBackend
 from wurzel.steps.embedding import EmbeddingStep
 from wurzel.steps.manual_markdown import ManualMarkdownStep
@@ -375,17 +374,16 @@ from wurzel.utils import WZ
 source = WZ(ManualMarkdownStep)
 embedding = WZ(EmbeddingStep)
 step = WZ(QdrantConnectorStep)
-
 source >> embedding >> step
 pipeline = step
 
-# Generate Argo Workflows configuration from values file
-backend = ArgoBackend.from_values(
-    files=[Path("values.yaml")],
-    workflow_name="pipelinedemo"
-)
+# Generate Argo Workflows configuration (default config, no values file)
+backend = ArgoBackend()
 argo_yaml = backend.generate_artifact(pipeline)
-print(argo_yaml)
+
+# Or from values file (YAML must contain workflows.pipelinedemo):
+# from pathlib import Path
+# backend = ArgoBackend.from_values(files=[Path("values.yaml")], workflow_name="pipelinedemo")
 ```
 
 ## Deploying Argo Workflows

docs/backends/dvc.md

@@ -98,7 +98,6 @@ dvc repro
 Use the DVC backend directly in Python:
 
 ```python
-from pathlib import Path
 from wurzel.backend.backend_dvc import DvcBackend
 from wurzel.steps.embedding import EmbeddingStep
 from wurzel.steps.manual_markdown import ManualMarkdownStep
@@ -109,21 +108,17 @@ from wurzel.utils import WZ
 source = WZ(ManualMarkdownStep)
 embedding = WZ(EmbeddingStep)
 step = WZ(QdrantConnectorStep)
-
 source >> embedding >> step
 pipeline = step
 
-# Option 1: Generate DVC configuration from values file
-backend = DvcBackend.from_values(
-    files=[Path("values.yaml")],
-    workflow_name="pipelinedemo"
-)
-dvc_yaml = backend.generate_artifact(pipeline)
-print(dvc_yaml)
-
-# Option 2: Generate with default settings
+# Option 1: Generate with default settings (no values file)
 dvc_yaml = DvcBackend().generate_artifact(pipeline)
-print(dvc_yaml)
+
+# Option 2: Generate from values file (YAML must contain dvc.pipelinedemo)
+# from pathlib import Path
+# values_file = Path("values.yaml")
+# backend = DvcBackend.from_values(files=[values_file], workflow_name="pipelinedemo")
+# dvc_yaml = backend.generate_artifact(pipeline)
 ```
 
 ## Running DVC Pipelines