PG1204 commented on code in PR #5320: URL: https://github.com/apache/texera/pull/5320#discussion_r3365368550
########## common/workflow-operator/src/main/scala/org/apache/texera/amber/operator/huggingFace/codegen/ImageTaskCodegen.scala: ########## @@ -0,0 +1,146 @@ +/* + * 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 + +/** + * Codegen for the Hugging Face image-pipeline task family. + * + * Splits into two sub-families: + * - "image-only" tasks send raw image bytes as the request body and don't + * consume the prompt column: image-classification, object-detection, + * image-segmentation, image-to-text. + * - "image + prompt" tasks bundle a base64 image and a text prompt in a + * JSON payload: visual-question-answering, document-question-answering, + * zero-shot-image-classification, image-text-to-text, image-to-image. + * + * Per-row `current_image_bytes` is resolved upstream in + * [[PythonCodegenBase]]'s `process_table` (either from the operator's + * uploaded image or from `INPUT_IMAGE_COLUMN`). The image helpers + * (`_read_image_input`, `_compress_image_bytes`, `_image_input_as_base64`, + * `_read_binary_value`, `_looks_like_html`, `_html_to_image_bytes`, + * `_extract_json_arg`) live in PythonCodegenBase alongside the per-task + * tuples (`image_only_tasks`, `image_prompt_tasks`, `image_tasks`). + */ +object ImageTaskCodegen extends TaskCodegen { + + /** Primary key for registration; the dispatcher maps every task in + * [[tasks]] to this codegen. + */ + override val task: String = "image-classification" + + /** All HF tasks routed through this codegen. */ + override val tasks: Set[String] = Set( + // image-only + "image-classification", + "object-detection", + "image-segmentation", + "image-to-text", + // image + prompt + "visual-question-answering", + "document-question-answering", + "zero-shot-image-classification", + "image-text-to-text", + "image-to-image" + ) + + override def payloadPython(ctx: CodegenContext): String = + """ if task in image_only_tasks: + | payload = current_image_bytes + | use_raw_binary_body = True + | raw_binary_headers = image_headers + | elif task in ("visual-question-answering", "document-question-answering"): + | payload = { + | "inputs": { + | "image": self._image_input_as_base64(current_image_bytes), + | "question": prompt_value, + | } + | } + | elif task == "image-text-to-text": + | img_b64 = self._image_input_as_base64(current_image_bytes) + | payload = { + | "model": self.MODEL_ID, + | "messages": [{ + | "role": "user", + | "content": [ + | {"type": "image_url", "image_url": {"url": f"data:image/png;base64,{img_b64}"}}, + | {"type": "text", "text": prompt_value if prompt_value else "Describe this image."}, + | ], + | }], + | "max_tokens": self.MAX_NEW_TOKENS, + | } + | elif task == "image-to-image": + | payload = current_image_bytes + | use_raw_binary_body = True + | raw_binary_headers = image_headers + | elif task == "zero-shot-image-classification": + | labels = [] Review Comment: Applied your suggestion: `labels = [s.strip() for s in prompt_value.split(",") if s.strip()]`, which reads the prompt column as a comma-separated label list. The task is now shippable end-to-end (verified that a row like `cat,dog,car` returns a usable prediction from a `clip-vit-base-patch32`-style model). -- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. To unsubscribe, e-mail: [email protected] For queries about this service, please contact Infrastructure at: [email protected]
