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new e08b7f336a test(workflow-operator): add unit tests for MediaGenCodegen
(#6438)
e08b7f336a is described below
commit e08b7f336af68ce1bcaca012589beb41c7aed132
Author: Prateek Ganigi <[email protected]>
AuthorDate: Thu Jul 16 13:47:58 2026 -0700
test(workflow-operator): add unit tests for MediaGenCodegen (#6438)
### What changes were proposed in this PR?
Adds dedicated unit test coverage for MediaGenCodegen, the TaskCodegen
object that generates the Python payload/parse snippets for Hugging Face
media-generation operators (text-to-image and text-to-video). This class
previously had no direct test coverage.
A new spec file, [MediaGenCodegenSpec.scala was created in the same test
package, mirroring the structure and patterns of TextGenCodegenSpec
(shared makeCtx helper; assertions on snippet structure/markers rather
than exact whitespace). It adds 9 tests covering:
- task equals "text-to-image"
- tasks equals exactly Set("text-to-image", "text-to-video")
- payloadPython emits the static {"inputs": prompt_value} payload
- parsePython branches on both media tasks, routes URL responses through
the shared _url_to_data_url helper, converts OpenAI b64_json payloads
into a data:image/png;base64, URL, and falls back to json.dumps(body)
- Snippets never inline raw CodegenContext string values (no sentinel
leakage)
- Context-independence: identical output across two unrelated
CodegenContext instances
### Any related issues, documentation, discussions?
Closes #6252
### How was this PR tested?
Added 9 unit tests in the new spec file, all passing via sbt:
sbt "WorkflowOperator/testOnly
org.apache.texera.amber.operator.huggingFace.codegen.MediaGenCodegenSpec"
[info] Tests: succeeded 9, failed 0, canceled 0, ignored 0, pending 0
[info] All tests passed.
### Was this PR authored or co-authored using generative AI tooling?
Co-authored with Claude Opus 4.8 in compliance with ASF
---
.../huggingFace/codegen/MediaGenCodegenSpec.scala | 140 +++++++++++++++++++++
1 file changed, 140 insertions(+)
diff --git
a/common/workflow-operator/src/test/scala/org/apache/texera/amber/operator/huggingFace/codegen/MediaGenCodegenSpec.scala
b/common/workflow-operator/src/test/scala/org/apache/texera/amber/operator/huggingFace/codegen/MediaGenCodegenSpec.scala
new file mode 100644
index 0000000000..02a4c2d607
--- /dev/null
+++
b/common/workflow-operator/src/test/scala/org/apache/texera/amber/operator/huggingFace/codegen/MediaGenCodegenSpec.scala
@@ -0,0 +1,140 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements. See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership. The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied. See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
+package org.apache.texera.amber.operator.huggingFace.codegen
+
+import org.apache.texera.amber.pybuilder.PyStringTypes.EncodableString
+import org.scalatest.flatspec.AnyFlatSpec
+import org.scalatest.matchers.should.Matchers
+
+class MediaGenCodegenSpec extends AnyFlatSpec with Matchers {
+
+ private def makeCtx(
+ hfApiToken: EncodableString = "token",
+ modelId: EncodableString = "stabilityai/stable-diffusion-2",
+ promptColumn: EncodableString = "prompt",
+ resultColumn: EncodableString = "hf_response",
+ task: EncodableString = "text-to-image",
+ systemPrompt: EncodableString = "You are a helpful assistant.",
+ safeMaxTokens: Int = 256,
+ safeTemp: Double = 0.7
+ ): CodegenContext =
+ CodegenContext(
+ hfApiToken = hfApiToken,
+ modelId = modelId,
+ promptColumn = promptColumn,
+ resultColumn = resultColumn,
+ task = task,
+ systemPrompt = systemPrompt,
+ safeMaxTokens = safeMaxTokens,
+ safeTemp = safeTemp
+ )
+
+ "MediaGenCodegen.task" should "be the canonical text-to-image string" in {
+ MediaGenCodegen.task shouldBe "text-to-image"
+ }
+
+ "MediaGenCodegen.tasks" should "cover exactly text-to-image and
text-to-video" in {
+ MediaGenCodegen.tasks shouldBe Set("text-to-image", "text-to-video")
+ }
+
+ "MediaGenCodegen.payloadPython" should "emit the static inputs payload
shape" in {
+ val out = MediaGenCodegen.payloadPython(makeCtx())
+ out should include("""payload = {"inputs": prompt_value}""")
+ }
+
+ "MediaGenCodegen.parsePython" should "branch on both media tasks" in {
+ val out = MediaGenCodegen.parsePython(makeCtx())
+ out should include("""if task == "text-to-image":""")
+ out should include("""elif task == "text-to-video":""")
+ }
+
+ it should "route URL responses through the _url_to_data_url helper" in {
+ val out = MediaGenCodegen.parsePython(makeCtx())
+ out should include("self._url_to_data_url(")
+ }
+
+ it should "convert OpenAI b64_json payloads into a data URL" in {
+ val out = MediaGenCodegen.parsePython(makeCtx())
+ out should include("b64_json")
+ out should include("data:image/png;base64,")
+ }
+
+ it should "fall back to json.dumps(body) when no known shape matches" in {
+ val out = MediaGenCodegen.parsePython(makeCtx())
+ out should include("json.dumps(body)")
+ }
+
+ "MediaGenCodegen snippets" should "never inline raw CodegenContext string
values" in {
+ // The snippets are static and reference only self.* attributes; the base
+ // class decodes user-supplied strings safely at runtime. Sentinel values
+ // are distinctive and non-overlapping with the static template text.
+ val ctx = makeCtx(
+ hfApiToken = "MARKER_TOKEN_zXyq42",
+ modelId = "MARKER_MODEL_zXyq42",
+ promptColumn = "MARKER_PROMPT_zXyq42",
+ resultColumn = "MARKER_RESULT_zXyq42",
+ task = "MARKER_TASK_zXyq42",
+ systemPrompt = "MARKER_SYSTEM_zXyq42"
+ )
+ val payload = MediaGenCodegen.payloadPython(ctx)
+ val parse = MediaGenCodegen.parsePython(ctx)
+
+ payload should not include "MARKER_TOKEN_zXyq42"
+ payload should not include "MARKER_MODEL_zXyq42"
+ payload should not include "MARKER_PROMPT_zXyq42"
+ payload should not include "MARKER_RESULT_zXyq42"
+ payload should not include "MARKER_TASK_zXyq42"
+ payload should not include "MARKER_SYSTEM_zXyq42"
+ parse should not include "MARKER_TOKEN_zXyq42"
+ parse should not include "MARKER_MODEL_zXyq42"
+ parse should not include "MARKER_PROMPT_zXyq42"
+ parse should not include "MARKER_RESULT_zXyq42"
+ parse should not include "MARKER_TASK_zXyq42"
+ parse should not include "MARKER_SYSTEM_zXyq42"
+ }
+
+ it should "produce identical output regardless of the CodegenContext
contents" in {
+ // media generation's payload/parse are static — they reference only
+ // self.* attributes, never ctx fields. Two unrelated contexts must
+ // serialise to byte-identical Python. A future refactor that
+ // accidentally consumes a ctx field will regress here.
+ val ctxA = makeCtx(
+ hfApiToken = "token-A",
+ modelId = "model-A",
+ promptColumn = "col-A",
+ resultColumn = "result-A",
+ systemPrompt = "system-A",
+ safeMaxTokens = 1,
+ safeTemp = 0.0
+ )
+ val ctxB = makeCtx(
+ hfApiToken = "token-B",
+ modelId = "model-B",
+ promptColumn = "col-B",
+ resultColumn = "result-B",
+ systemPrompt = "system-B",
+ safeMaxTokens = 4096,
+ safeTemp = 2.0
+ )
+
+ MediaGenCodegen.payloadPython(ctxA) shouldBe
MediaGenCodegen.payloadPython(ctxB)
+ MediaGenCodegen.parsePython(ctxA) shouldBe
MediaGenCodegen.parsePython(ctxB)
+ }
+}
