diff --git a/deployment/components/edp/templates/ingestion/ingestion-configmap.yaml b/deployment/components/edp/templates/ingestion/ingestion-configmap.yaml index c6c40299c..4515ba4b5 100644 --- a/deployment/components/edp/templates/ingestion/ingestion-configmap.yaml +++ b/deployment/components/edp/templates/ingestion/ingestion-configmap.yaml @@ -7,6 +7,7 @@ metadata: name: edp-ingestion-configmap namespace: edp data: + EMBEDDING_MODEL_NAME: {{ .Values.ingestion.config.embedding_model_name | quote }} VECTOR_STORE: {{ .Values.ingestion.config.vector_store | quote }} VECTOR_ALGORITHM: {{ .Values.ingestion.config.vector_algorithm | quote }} VECTOR_DIMS: {{ .Values.ingestion.config.vector_dims | quote }} diff --git a/deployment/components/edp/values.yaml b/deployment/components/edp/values.yaml index 203a2d4d8..9f1af7ba8 100644 --- a/deployment/components/edp/values.yaml +++ b/deployment/components/edp/values.yaml @@ -26,6 +26,8 @@ edpOidcConfigUrl: "http://keycloak-http.auth.svc/realms/EnterpriseRAG/.well-know edpOidcClientSecret: "" bucketNameRegexFilter: '.*' presignedUrlCredentialsSystemFallback: "false" +embedding_model_name: &embedding_model_name "BAAI/bge-base-en-v1.5" + minioApiDomain: &minioApiDomain "s3.erag.com" minioBrowserDomain: &minioBrowserDomain "minio.erag.com" @@ -895,6 +897,7 @@ ingestion: tag: latest config: opeaLoggerLevel: "INFO" # "DEBUG", "INFO", "WARNING", "ERROR", "CRITICAL" + embedding_model_name: *embedding_model_name # e.g., "BAAI/bge-base-en-v1.5" # Vector Algorithm configuration vector_algorithm: "FLAT" # "FLAT", "HNSW" vector_dims: "768" # Depends on model used in embedding. For example bge-large-en-v1.5=768, bge-large-en-v1.5=1024 diff --git a/deployment/components/gmc/values.yaml b/deployment/components/gmc/values.yaml index 280284c7e..5a8584072 100644 --- a/deployment/components/gmc/values.yaml +++ b/deployment/components/gmc/values.yaml @@ -221,6 +221,8 @@ images: tag: *tag pullPolicy: Always envfile: "src/comps/retrievers/impl/microservice/.env" + envs: + EMBEDDING_MODEL_NAME: *embedding_model_name ingestion-usvc: image: "erag-ingestion" repository: *repo diff --git a/deployment/roles/application/edp/templates/values.yaml.j2 b/deployment/roles/application/edp/templates/values.yaml.j2 index 8bd0c73a9..63eac146a 100644 --- a/deployment/roles/application/edp/templates/values.yaml.j2 +++ b/deployment/roles/application/edp/templates/values.yaml.j2 @@ -12,6 +12,8 @@ proxy: alternateTagging: {{ use_alternate_tagging }} {% endif %} +embedding_model_name: &embedding_model_name {{ embedding_model_name }} + {% set storage = lookup('env', 'edp_storage_type') or edp.storageType if edp.storageType is defined else "minio" %} {% if storage == "minio" %} edpAccessKey: {{ EDP_MINIO_ACCESS_KEY }} @@ -136,10 +138,10 @@ ingestion: tag: {{ tag }} repository: {{ registry }} config: + embedding_model_name: *embedding_model_name {% if edp.hierarchical_indices.enabled is true %} use_hierarchical_indices: "True" {% endif %} - config: vector_dims: {{ vector_databases.vector_dims }} vector_datatype: {{ vector_databases.vector_datatype }} {% if edp.late_chunking.enabled is true %} diff --git a/deployment/roles/application/pipeline/templates/values.yaml.j2 b/deployment/roles/application/pipeline/templates/values.yaml.j2 index ffac6237e..f0b7fccf5 100644 --- a/deployment/roles/application/pipeline/templates/values.yaml.j2 +++ b/deployment/roles/application/pipeline/templates/values.yaml.j2 @@ -148,6 +148,7 @@ images: vector_store: {{ vector_databases.vector_store }} {% endif %} envs: + EMBEDDING_MODEL_NAME: *embedding_model_name {% if edp.hierarchical_indices.enabled is true %} USE_HIERARCHICAL_INDICES: "True" K_SUMMARIES: {{ edp.hierarchical_indices.kSummaries }} diff --git a/deployment/terraform/ibm/main.tf b/deployment/terraform/ibm/main.tf index cfc85261a..28cc62c3c 100644 --- a/deployment/terraform/ibm/main.tf +++ b/deployment/terraform/ibm/main.tf @@ -302,7 +302,7 @@ resource "null_resource" "run_install_system" { } inline = [ "chmod +x /tmp/run_install.sh", - "/tmp/run_install.sh --platform ibm --gaudi --stage system --tag ${var.solution_version}" + "/tmp/run_install.sh --platform ibm --stage system --tag ${var.solution_version}${var.deployment_type == "hpu" ? " --gaudi" : ""}" ] } } @@ -326,7 +326,7 @@ resource "null_resource" "run_install_cluster" { proxy_port = var.use_proxy ? var.proxy_port : null } inline = [ - "/tmp/run_install.sh --platform ibm --gaudi --stage cluster --tag ${var.solution_version}" + "/tmp/run_install.sh --platform ibm --stage cluster --tag ${var.solution_version}${var.deployment_type == "hpu" ? " --gaudi" : ""}" ] } } @@ -350,7 +350,7 @@ resource "null_resource" "run_install_application" { proxy_port = var.use_proxy ? var.proxy_port : null } inline = [ - "/tmp/run_install.sh --platform ibm --gaudi --stage application --tag ${var.solution_version}" + "/tmp/run_install.sh --platform ibm --stage application --tag ${var.solution_version}${var.deployment_type == "hpu" ? " --gaudi" : ""}" ] } } diff --git a/deployment/terraform/scripts/run_install.sh b/deployment/terraform/scripts/run_install.sh index 7b95be944..6a9e5f4e4 100755 --- a/deployment/terraform/scripts/run_install.sh +++ b/deployment/terraform/scripts/run_install.sh @@ -247,12 +247,16 @@ configure_platform_defaults() { ;; ibm) log_info "Configuring IBM Cloud platform defaults" - STORAGE_DEVICE="/dev/nvme1n1" - STORAGE_MOUNT_POINT="/mnt/nvme1" + if [[ "$INSTALL_GAUDI_DRIVER" == "true" ]]; then + STORAGE_DEVICE="/dev/nvme1n1" + STORAGE_MOUNT_POINT="/mnt/nvme1" + else + STORAGE_DEVICE="/dev/vdb" + STORAGE_MOUNT_POINT="/mnt/vdb1" + fi CONTAINERD_STORAGE_DIR="${STORAGE_MOUNT_POINT}/containerd" LOCAL_PATH_STORAGE_DIR="${STORAGE_MOUNT_POINT}/local-path-provisioner" ETCD_DATA_DIR="${STORAGE_MOUNT_POINT}/etcd" - INSTALL_GAUDI_DRIVER=true ;; esac @@ -535,7 +539,13 @@ create_partition_and_format_storage() { sudo parted -s $device mkpart primary ext4 0% 100% sudo partprobe $device - # Wait for partition to be available + # Wait for partition to be available (up to 10 seconds) + for i in {1..10}; do + if [[ -b "$partition_device" ]]; then + break + fi + sleep 1 + done if [[ ! -b "$partition_device" ]]; then log_fatal "Partition device not found after creation: $partition_device" fi diff --git a/ibm_catalog.json b/ibm_catalog.json index 3dc0d5224..683221c0d 100644 --- a/ibm_catalog.json +++ b/ibm_catalog.json @@ -10,8 +10,8 @@ "long_description": "Complete Enterprise Retrieval-Augmented Generation solution featuring Intel Gaudi AI accelerators, Kubernetes orchestration, ChatQA, comprehensive monitoring, and enterprise security with Keycloak authentication.", "flavors": [ { - "label": "Standard", - "name": "standard", + "label": "Gaudi", + "name": "gaudi", "working_directory": "deployment/terraform/ibm", "compliance": {}, "architecture": {}, @@ -48,6 +48,15 @@ "type": "resource_group" } }, + { + "key": "instance_profile", + "type": "string", + "description": "IBM Cloud instance profile with Intel Gaudi HPU", + "required": true, + "options": [ + {"label": "gx3d-160x1792x8gaudi3", "value": "gx3d-160x1792x8gaudi3"} + ] + }, { "key": "instance_name", "type": "string", @@ -118,12 +127,6 @@ "description": "Fully qualified domain name for the Enterprise RAG application", "default_value": "enterprise-rag.local" }, - { - "key": "vllm_cpu_model_name", - "type": "string", - "description": "CPU-based LLM model name for inference", - "default_value": "" - }, { "key": "vllm_hpu_model_name", "type": "string", @@ -146,10 +149,10 @@ "key": "deployment_type", "type": "string", "default_value": "hpu", + "hidden": true, "description": "Deployment type for AI acceleration", "options": [ - {"label": "Intel Gaudi HPU", "value": "hpu"}, - {"label": "Xeon Only", "value": "cpu"} + {"label": "Intel Gaudi HPU", "value": "hpu"} ] }, { @@ -217,8 +220,221 @@ } ], "install_type": "fullstack" + }, + { + "label": "Xeon", + "name": "xeon", + "working_directory": "deployment/terraform/ibm", + "compliance": {}, + "architecture": {}, + "configuration": [ + { + "key": "api_key", + "type": "password", + "description": "IBM Cloud API key for resource provisioning", + "required": true + }, + { + "key": "region", + "type": "string", + "default_value": "us-south", + "description": "IBM Cloud region for deployment", + "required": true, + "options": [ + {"label": "US South(Dallas)", "value": "us-south"}, + {"label": "US East(Washington DC)", "value": "us-east"}, + {"label": "EU Germany(Frankfurt)", "value": "eu-de"} + ] + }, + { + "key": "resource_group", + "default_value": "Default", + "description": "This variable lists resource group name used by the resources", + "required": true, + "custom_config": { + "config_constraints": { + "identifier": "rg_name" + }, + "grouping": "deployment", + "original_grouping": "deployment", + "type": "resource_group" + } + }, + { + "key": "instance_profile", + "type": "string", + "description": "IBM Cloud instance profile with Intel Xeon CPU", + "required": true, + "options": [ + {"label": "bx3d-128x640", "value": "bx3d-128x640"} + ] + }, + { + "key": "instance_name", + "type": "string", + "default_value": "enterprise-rag", + "description": "Name prefix for created resources (VPC, instance, etc.)", + "required": true + }, + { + "key": "instance_zone", + "type": "string", + "description": "Availability zone for instance deployment (e.g., us-south-1)", + "required": true, + "options": [ + { + "displayname": "eu-de-1", + "value": "eu-de-1" + }, + { + "displayname": "us-south-2", + "value": "us-south-2" + }, + { + "displayname": "us-east-3", + "value": "us-east-3" + }, + { + "displayname": "us-east-2", + "value": "us-east-2" + } + ] + }, + { + "key": "ssh_key_name", + "type": "string", + "description": "Name of existing SSH key in IBM Cloud for instance access", + "required": true + }, + { + "key": "ssh_key", + "type": "multiline_secure_value", + "description": "This variable specifies the ssh key", + "default_value": "-----BEGIN OPENSSH PRIVATE KEY-----", + "required": true, + "custom_config": { + "grouping": "deployment", + "original_grouping": "deployment", + "type": "multiline_secure_value" + } + }, + { + "key": "hugging_face_token", + "type": "multiline_secure_value", + "default_value": "__NULL__", + "description": "This variable specifies the Hugging Face token. You can also create a token by referring to the documentation at https://huggingface.co/docs/hub/en/security-tokens. ", + "required": true + }, + { + "key": "boot_volume_size", + "type": "number", + "default_value": 100, + "description": "Boot volume size in GB (minimum 100GB recommended)", + "minimum": 100, + "maximum": 300 + }, + { + "key": "fqdn", + "type": "string", + "description": "Fully qualified domain name for the Enterprise RAG application", + "default_value": "enterprise-rag.local" + }, + { + "key": "vllm_cpu_model_name", + "type": "string", + "description": "CPU-based LLM model name for inference", + "default_value": "" + }, + { + "key": "embedding_model_name", + "type": "string", + "description": "Embedding model for vector representations", + "default_value": "BAAI/bge-base-en-v1.5" + }, + { + "key": "reranking_model_name", + "type": "string", + "description": "Reranking model for improving search results", + "default_value": "BAAI/bge-reranker-base" + }, + { + "key": "deployment_type", + "type": "string", + "default_value": "cpu", + "hidden": true, + "description": "Deployment type for AI acceleration", + "options": [ + {"label": "Xeon", "value": "cpu"} + ] + }, + { + "key": "vpc", + "type": "string", + "description": "Existing VPC name (optional - will create new if empty)" + }, + { + "key": "subnet", + "type": "string", + "description": "Existing subnet name (optional - will create new if empty)" + }, + { + "key": "security_group", + "type": "string", + "description": "Existing security group name (optional - will create new if empty)" + }, + { + "key": "ssh_allowed_cidr", + "type": "string", + "default_value": "0.0.0.0/0", + "description": "CIDR block allowed for SSH access (restrict for security)" + }, + { + "key": "ssh_user", + "type": "string", + "default_value": "ubuntu", + "description": "SSH username for instance access" + }, + { + "key": "resource_prefix", + "type": "string", + "default_value": "erag", + "description": "Prefix for resource naming convention" + } + ], + "outputs": [ + { + "key": "floating_ip", + "description": "Public IP address of the deployed Enterprise RAG instance" + }, + { + "key": "vpc_id", + "description": "ID of the VPC used for the deployment" + }, + { + "key": "subnet_id", + "description": "ID of the subnet where the instance is deployed" + }, + { + "key": "security_group_id", + "description": "ID of the security group protecting the instance" + }, + { + "key": "instance_id", + "description": "ID of the provisioned compute instance" + }, + { + "key": "ssh_command", + "description": "SSH command to connect to the instance" + }, + { + "key": "application_url", + "description": "URL to access the Enterprise RAG application" + } + ], + "install_type": "fullstack" } ] } ] } + diff --git a/src/comps/chat_history/impl/microservice/pyproject.toml b/src/comps/chat_history/impl/microservice/pyproject.toml index 351d3c6c2..dd56e8e9f 100644 --- a/src/comps/chat_history/impl/microservice/pyproject.toml +++ b/src/comps/chat_history/impl/microservice/pyproject.toml @@ -9,7 +9,7 @@ requires-python = ">=3.11,<3.12" 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comps.text_extractor.utils.file_loaders.abstract_loader import AbstractLoader from comps.text_extractor.utils.file_loaders.load_image import LoadImage @@ -12,11 +18,26 @@ logger = get_opea_logger(f"{__file__.split('comps/')[1].split('/', 1)[0]}_microservice") +# Markers added by pymupdf4llm for OCR text +PICTURE_TEXT_START_MARKER = "---- Start of picture text ----" +PICTURE_TEXT_END_MARKER = "---- End of picture text -----" + +# Placeholder marker for pictures in pymupdf4llm output +PICTURE_PLACEHOLDER_MARKER = re.compile(r"==> picture \[\d+ x \d+\] <==") + +def _remove_pymupdf4llm_markers(text): + """Remove markers added by pymupdf4llm during OCR text extraction.""" + text = text.replace(PICTURE_TEXT_START_MARKER, "") + text = text.replace(PICTURE_TEXT_END_MARKER, "") + text = PICTURE_PLACEHOLDER_MARKER.sub("", text) + return text -def _process_single_page(file_path, page_num): + +def _process_single_page_from_file(file_path, page_num): """ Process a single PDF page. This function is designed to be run in parallel. + Opens the PDF file, extracts text. Each call opens and closes its own document instance, making it safe for parallel execution. Args: file_path: Path to the PDF file page_num: Page number to process (0-indexed) @@ -24,63 +45,13 @@ def _process_single_page(file_path, page_num): Returns: dict: Dictionary containing extracted text and metadata """ + + doc = None + try: doc = pymupdf.open(file_path) - page = doc.load_page(page_num) - page.clean_contents() - - result = "" - - # https://pymupdf.readthedocs.io/en/latest/page.html#description-of-get-links-entries - for link in page.links(): - if link.get("uri"): - result = result + f" {link.get('uri')}" - - # https://pymupdf.readthedocs.io/en/latest/recipes-text.html#how-to-extract-table-content-from-documents - finder = page.find_tables() - for table in finder.tables: - logger.info(f"[{file_path}] Extracting table from page {page_num + 1}") - table_data = table.extract() - if len(table_data) > 0: - flattened_table_data = [str(item) for sublist in table_data for item in sublist] - result += " ".join(flattened_table_data) - - # https://pymupdf.readthedocs.io/en/latest/recipes-text.html#how-to-extract-text-from-pdf-documents - # simple page.get_text() does extact text, but it includes text from tables. skip table bounding boxes from the text extraction - try: - non_table_text = [] - text_dict = page.get_text("dict") - table_rects = [pymupdf.Rect(table.bbox) for table in finder.tables] - for block in text_dict["blocks"]: - block_rect = pymupdf.Rect(block["bbox"]) - if not any(block_rect.intersects(table_rect) for table_rect in table_rects): - if "lines" in block: - for line in block["lines"]: - for span in line["spans"]: - non_table_text.append(span["text"]) - result += " ".join(non_table_text) - except Exception: - result += page.get_text().strip() - - # https://pymupdf.readthedocs.io/en/latest/recipes-images.html#how-to-extract-images-pdf-documents - images = doc.get_page_images(page_num, full=False) - for img in images: - img_data = doc.extract_image(img[0]) - img_path = "" - try: - img_path = _save_image(img_data) - logger.debug(f"[{file_path}] Extracted {img_path} for processing") - img_loader = LoadImage(img_path) - result += img_loader.extract_text() - logger.info(f"[{file_path}] Processed image {img_path} for page {page_num + 1}") - except Exception as e: - logger.error(f"[{file_path}] Error parsing image on page {page_num + 1}: {e}. Ignoring...") - finally: - if img_path and img_path != "" and os.path.exists(img_path) and not os.path.isdir(img_path): - logger.debug(f"[{file_path}] Removed {img_path} after processing") - os.remove(img_path) - - doc.close() + + result = _extract_page(doc, page_num, log_identifier=file_path) return { 'page_num': page_num, 'text': result, @@ -94,10 +65,69 @@ def _process_single_page(file_path, page_num): 'success': False, 'error': str(e) } + finally: + if doc is not None: + doc.close() + + +def _extract_page(doc, page_num, log_identifier=""): + """ + Extract text from a single page using an already opened document. + + Args: + doc: Opened pymupdf Document object + page_num: Page number to process (0-indexed) + log_identifier: Optional log identifier (file_path) for logging purposes only + + Returns: + dict: Dictionary containing extracted text and metadata + """ + page = doc.load_page(page_num) + result = "" + + + # Create a temporary single-page Document because pymupdf4llm.to_text() expects a Document, not a Page. + single_page_doc = pymupdf.open() + single_page_doc.insert_pdf(doc, from_page=page_num, to_page=page_num) + + result = pymupdf4llm.to_text(single_page_doc, header=False, footer=False, use_ocr=True, force_text=True, table_format="simple") + result = _remove_pymupdf4llm_markers(result) + + # https://pymupdf.readthedocs.io/en/latest/page.html#description-of-get-links-entries + for link in page.links(): + if link.get("uri"): + result = result + f" {link.get('uri')}" + + # https://pymupdf.readthedocs.io/en/latest/recipes-images.html#how-to-extract-images-pdf-documents + images = page.get_images(full=False) + debug_cnt = 0 + for img in images: + img_data = doc.extract_image(img[0]) + img_path = "" + + logger.info(f"Extracting image {debug_cnt + 1}/{len(images)}") + try: + img_path = _save_image(img_data) + logger.debug(f"[{log_identifier}] Extracted {img_path} for processing") + img_loader = LoadImage(img_path) + image_text = img_loader.extract_text() + image_text = image_text.strip() + if image_text: + result += "\n" + image_text + logger.info(f"[{log_identifier}] Processed image {img_path} for page {page_num + 1}") + except Exception as e: + logger.error(f"[{log_identifier}] Error parsing image on page {page_num + 1}: {e}. Ignoring...") + finally: + if img_path and img_path != "" and os.path.exists(img_path) and not os.path.isdir(img_path): + logger.debug(f"[{log_identifier}] Removed {img_path} after processing") + os.remove(img_path) + + return result def _save_image(data, save_path="/tmp/opea_upload"): """Save image data to a file.""" + import uuid if not os.path.exists(save_path): os.makedirs(save_path, mode=0o700, exist_ok=True) @@ -122,6 +152,7 @@ def extract_text(self): - PDF_PARALLEL_PROCESSING: Enable/disable parallel processing (default: true) - PDF_MAX_WORKERS: Maximum number of parallel workers (default: auto-detect) """ + doc = pymupdf.open(self.file_path) page_count = doc.page_count doc.close() @@ -149,7 +180,7 @@ def extract_text(self): with ProcessPoolExecutor(max_workers=max_workers) as executor: # Submit all pages for processing future_to_page = { - executor.submit(_process_single_page, self.file_path, i): i + executor.submit(_process_single_page_from_file, self.file_path, i): i for i in range(page_count) } @@ -172,6 +203,7 @@ def extract_text(self): # Combine results in page order result = " ".join(results[i] for i in range(page_count)) + else: # Sequential processing (fallback or single page) if page_count == 1: @@ -179,76 +211,25 @@ def extract_text(self): else: logger.info(f"[{self.file_path}] Using sequential processing (parallel disabled)") - result = "" - doc = pymupdf.open(self.file_path) - - for i in range(page_count): - page_start = time.time() - page_result = self._extract_page_sequential(doc, i) - result += " " + page_result if result else page_result - page_end = time.time() - logger.info(f"[{self.file_path}] Page {i+1}/{page_count} processed in {page_end - page_start:.2f} seconds") - - doc.close() - - end_time = time.time() - logger.info(f"[{self.file_path}] Total processing time: {end_time - start_time:.2f} seconds for {page_count} pages") - - return result - - def _extract_page_sequential(self, doc, page_num): - """Extract text from a single page (sequential processing).""" - result = "" - page = doc.load_page(page_num) - page.clean_contents() - - # https://pymupdf.readthedocs.io/en/latest/page.html#description-of-get-links-entries - for link in page.links(): - if link.get("uri"): - result = result + f" {link.get('uri')}" - - # https://pymupdf.readthedocs.io/en/latest/recipes-text.html#how-to-extract-table-content-from-documents - finder = page.find_tables() - for table in finder.tables: - logger.info(f"[{self.file_path}] Extracting table from page {page_num + 1}") - table_data = table.extract() - if len(table_data) > 0: - flattened_table_data = [str(item) for sublist in table_data for item in sublist] - result += " ".join(flattened_table_data) - - # https://pymupdf.readthedocs.io/en/latest/recipes-text.html#how-to-extract-text-from-pdf-documents - # simple page.get_text() does extact text, but it includes text from tables. skip table bounding boxes from the text extraction - try: - non_table_text = [] - text_dict = page.get_text("dict") - table_rects = [pymupdf.Rect(table.bbox) for table in finder.tables] - for block in text_dict["blocks"]: - block_rect = pymupdf.Rect(block["bbox"]) - if not any(block_rect.intersects(table_rect) for table_rect in table_rects): - if "lines" in block: - for line in block["lines"]: - for span in line["spans"]: - non_table_text.append(span["text"]) - result += " ".join(non_table_text) - except Exception: - result += page.get_text().strip() - - # https://pymupdf.readthedocs.io/en/latest/recipes-images.html#how-to-extract-images-pdf-documents - images = doc.get_page_images(page_num, full=False) - for img in images: - img_data = doc.extract_image(img[0]) - img_path = "" try: - img_path = _save_image(img_data) - logger.debug(f"[{self.file_path}] Extracted {img_path} for processing") - img_loader = LoadImage(img_path) - result += img_loader.extract_text() - logger.info(f"[{self.file_path}] Processed image {img_path}") + result = "" + doc = pymupdf.open(self.file_path) + + for i in range(page_count): + page_start = time.time() + page_result = _extract_page(doc, i, log_identifier=self.file_path) + result += " " + page_result if result else page_result + page_end = time.time() + logger.info(f"[{self.file_path}] Page {i+1}/{page_count} processed in {page_end - page_start:.2f} seconds") + except Exception as e: - logger.error(f"[{self.file_path}] Error parsing image {img_path}: {e}. Ignoring...") + logger.error(f"[{self.file_path}] Error processing document: {e}") + raise e finally: - if img_path and img_path != "" and os.path.exists(img_path) and not os.path.isdir(img_path): - logger.debug(f"[{self.file_path}] Removed {img_path} after processing") - os.remove(img_path) + if doc is not None: + doc.close() + end_time = time.time() + logger.info(f"[{self.file_path}] Total processing time: {end_time - start_time:.2f} seconds for {page_count} pages") + return result diff --git a/src/comps/text_splitter/impl/microservice/pyproject.toml b/src/comps/text_splitter/impl/microservice/pyproject.toml index 683a93a7f..4674eb7f4 100644 --- a/src/comps/text_splitter/impl/microservice/pyproject.toml +++ b/src/comps/text_splitter/impl/microservice/pyproject.toml @@ -8,7 +8,7 @@ requires-python = ">=3.11,<3.12" dependencies = [ "fastapi==0.120.2", - "aiohttp == 3.12.14", + "aiohttp == 3.13.3", "opentelemetry-api==1.25.0", "opentelemetry-exporter-otlp==1.25.0", 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input_text: str, embedding: List if before_result.docs: prev_chunk = max(before_result.docs, key=lambda x: int(x.start_index) if hasattr(x, 'start_index') else 0) logger.debug(f"Retrieved previous chunk: {prev_chunk.id, prev_chunk.start_index}") - sibling_docs.append(self._convert_to_text_doc(prev_chunk)) + prev_doc = self._convert_to_text_doc(prev_chunk) + prev_doc.metadata["vector_distance"] = -1 # Siblings do not have a distance score + sibling_docs.append(prev_doc) after_filter = None if filter_expression is None: @@ -515,7 +518,9 @@ async def similarity_search_with_siblings(self, input_text: str, embedding: List if after_result.docs: next_chunk = min(after_result.docs, key=lambda x: int(x.start_index) if hasattr(x, 'start_index') else 0) logger.debug(f"Retrieved next chunk: {next_chunk.id, next_chunk.start_index}") - sibling_docs.append(self._convert_to_text_doc(next_chunk)) + next_doc = self._convert_to_text_doc(next_chunk) + next_doc.metadata["vector_distance"] = -1 # Siblings do not have a distance score + sibling_docs.append(next_doc) all_sibling_docs[doc.id] = sibling_docs diff --git a/src/edp/app/utils.py b/src/edp/app/utils.py index 40250c650..46c9b71cb 100644 --- a/src/edp/app/utils.py +++ b/src/edp/app/utils.py @@ -30,7 +30,8 @@ def get_local_minio_client_using_token_credentials(jwt_token, verify=False): raise ValueError("JWT token does not contain access_token") credentials = WebIdentityProvider( jwt_provider_func=lambda: jwt_token, - sts_endpoint=os.getenv('EDP_STS_ENDPOINT', endpoint) + sts_endpoint=os.getenv('EDP_STS_ENDPOINT', endpoint), + http_client=get_http_client(endpoint, cert_check) ) return get_minio_client(endpoint, region, cert_check, credentials) diff --git a/src/tests/e2e/conftest.py b/src/tests/e2e/conftest.py index b4e990505..692ff1f26 100644 --- a/src/tests/e2e/conftest.py +++ b/src/tests/e2e/conftest.py @@ -268,6 +268,12 @@ def temporarily_remove_brute_force_detection(keycloak_helper): keycloak_helper.set_brute_force_detection(True) +@pytest.fixture(scope="session") +def test_language(): + """Get the test language from environment variable""" + return os.getenv("TEST_LANG", "en") + + @pytest.fixture(scope="session") def code_snippets(): """ diff --git a/src/tests/e2e/evals/evaluation/rag_eval/README.md b/src/tests/e2e/evals/evaluation/rag_eval/README.md index abaebd2ac..af507c129 100644 --- a/src/tests/e2e/evals/evaluation/rag_eval/README.md +++ b/src/tests/e2e/evals/evaluation/rag_eval/README.md @@ -12,9 +12,9 @@ - [MultiHop (English dataset)](#multihop-english-dataset) - [Evaluation](#evaluation) - [Usage Guide](#usage-guide) + - [Tips to Control the Evaluation Scope](#tips-to-control-the-evaluation-scope) - [Acknowledgements](#acknowledgements) - ## Introduction @@ -187,7 +187,7 @@ This evaluation uses [yixuantt/MultiHopRAG](https://huggingface.co/datasets/yixu ### Evaluation -This section explains how to run the evaluation pipeline for Multihop dataset. +This section explains how to run the evaluation pipeline for MultiHop dataset. The evaluation script is located at `examples/eval_multihop.py`. @@ -199,23 +199,42 @@ python eval_multihop.py --help | **Argument** | **Default Value** | **Description** | | ---------------------- |---------------------------------------------------|-------------------------------------------------------------------------------------------------| -| `--output_dir` | `./output` | Directory to save evaluation results | -| `--auth_file` | `deployment/ansible-logs/default_credentials.txt` | Path to credentials file with `KEYCLOAK_ERAG_ADMIN_USERNAME` and `KEYCLOAK_ERAG_ADMIN_PASSWORD` | -| `--cluster_config_file`| `deployment/inventory/sample/config.yaml` | Path to cluster configuration YAML file with deployment settings | -| `--dataset_path` | `multihop_dataset/MultiHopRAG.json` | Path to the evaluation dataset | -| `--docs_path` | `multihop_dataset/corpus.json` | Path to the documents for retrieval | -| `--limits` | `100` | Number of queries to evaluate (0 means evaluate all; default: 100) | -| `--ingest_docs` | *(flag)* | Ingest documents into the vector database (use only on first run) | -| `--generation_metrics` | *(flag)* | Compute text generation metrics (`BLEU`, `ROUGE`) | -| `--retrieval_metrics` | *(flag)* | Compute retrieval metrics (`Hits@K`, `MAP@K`, `MRR@K`) | -| `--skip_normalize` | *(flag)* | Skip 'None' separator normalization for exact 1:1 text matching | -| `--ragas_metrics` | *(flag)* | Compute RAGAS metrics (answer correctness, context precision, etc.) | -| `--resume_checkpoint` | *None* | Path to a checkpoint file to resume evaluation from previous state | -| `--keep_checkpoint` | *(flag)* | Keep the checkpoint file after evaluation (do not delete) | -| `--llm_judge_endpoint` | `http://localhost:8008` | URL of the LLM judge service; only used for RAGAS evaluation | -| `--embedding_endpoint` | `http://localhost:8090/embed` | URL of the embedding service endpoint, only used for RAGAS | -| `--temperature` | Read from RAG system config | Controls text generation randomness; defaults to RAG system setting if omitted. | -| `--max_new_tokens` | Read from RAG system config | Maximum tokens generated; defaults to RAG system setting if omitted. | +| `--output_dir` | `./output` | Directory to save evaluation results +| +| `--auth_file` | `deployment/ansible-logs/default_credentials.txt` | Path to credentials file with `KEYCLOAK_ERAG_ADMIN_USERNAME` and `KEYCLOAK_ERAG_ADMIN_PASSWORD` +| +| `--cluster_config_file`| `deployment/inventory/sample/config.yaml` | Path to cluster configuration YAML file with deployment settings +| +| `--dataset_path` | `multihop_dataset/MultiHopRAG.json` | Path to the evaluation dataset +| +| `--docs_path` | `multihop_dataset/corpus.json` | Path to the documents for retrieval +| +| `--limits` | `100` | Number of queries to evaluate (0 means evaluate all; default: 100) +| +| `--exclude_types` | *None* | Exclude queries by question type. Queries matching these question types will be skipped. Example: --exclude_types comparison_query +| +| `--ingest_docs` | *(flag)* | Ingest documents into the vector database (use only on first run) +| +| `--generation_metrics` | *(flag)* | Compute text generation metrics (`BLEU`, `ROUGE`) +| +| `--retrieval_metrics` | *(flag)* | Compute retrieval metrics (`Hits@K`, `MAP@K`, `MRR@K`) +| +| `--skip_normalize` | *(flag)* | Skip 'None' separator normalization for exact 1:1 text matching +| +| `--ragas_metrics` | *(flag)* | Compute RAGAS metrics (answer correctness, context precision, etc.) +| +| `--resume_checkpoint` | *None* | Path to a checkpoint file to resume evaluation from previous state +| +| `--keep_checkpoint` | *(flag)* | Keep the checkpoint file after evaluation (do not delete) +| +| `--llm_judge_endpoint` | `http://localhost:8008` | URL of the LLM judge service; only used for RAGAS evaluation +| +| `--embedding_endpoint` | `http://localhost:8090/embed` | URL of the embedding service endpoint, only used for RAGAS +| +| `--temperature` | Read from RAG system config | Controls text generation randomness; defaults to RAG system setting if omitted +| +| `--max_new_tokens` | Read from RAG system config | Maximum tokens generated; defaults to RAG system setting if omitted +| > Note: If `--dataset_path` and `--docs_path` are set to their default values and the corresponding files are not found locally, they will be automatically downloaded at runtime from [yixuantt/MultiHopRAG](https://huggingface.co/datasets/yixuantt/MultiHopRAG) and saved to the expected local paths. @@ -224,7 +243,7 @@ python eval_multihop.py --help ### Usage Guide -This section outlines how to run Multihop evaluation of the RAG pipeline using [examples/eval_multihop.py](examples/eval_multihop.py). +This section outlines how to run MultiHop evaluation of the RAG pipeline using [examples/eval_multihop.py](examples/eval_multihop.py). - **Ingest Documents** To ingest the MultiHop dataset into the RAG system, use the flag `--ingest_docs`: @@ -250,7 +269,7 @@ This section outlines how to run Multihop evaluation of the RAG pipeline using [ _Metrics: BLEU, ROUGE, (LLM-score – not implemented yet)_ - To evaluate the quality of RAG generated answers on Multihop queries, run: + To evaluate the quality of RAG generated answers on MultiHop queries, run: ```bash # First-time run (with document ingestion) @@ -374,6 +393,29 @@ The evaluation results are stored in the output/ directory with detailed logs an The query and its corresponding ground_truth_text originate from the yixuantt/MultiHopRAG dataset. +### Tips to Control the Evaluation Scope + +**Controlling the Number of Queries with `--limits`:** + +The `--limits` parameter allows you to control how many queries from the dataset are evaluated. This is particularly useful for quick testing during development to verify that the pipeline works correctly. + +```bash +# Evaluate only the first 2 queries (quick test) +python eval_multihop.py --generation_metrics --limits 2 +``` + +**Excluding Specific Query Types with `--exclude_types`:** + +The dataset specified by `--dataset_path` (default: multihop_dataset/MultiHopRAG.json) contains queries along with their `question_type`. You can selectively exclude specific query types from evaluation using the `--exclude_types` parameter. This is useful when you want to focus on particular aspects of your RAG system, for example, to compute accuracy metrics separately for each query type and identify which types your RAG handles better or worse. + +```bash +# Exclude comparison queries from evaluation +python eval_multihop.py --retrieval_metrics --exclude_types comparison_query + +# Exclude multiple query types (space-separated) +python eval_multihop.py --retrieval_metrics --exclude_types comparison_query inference_query +``` + ## Acknowledgements This example is mostly adapted from [MultiHop-RAG](https://github.com/yixuantt/MultiHop-RAG) repo, we thank the authors for their great work! diff --git a/src/tests/e2e/evals/evaluation/rag_eval/evaluator.py b/src/tests/e2e/evals/evaluation/rag_eval/evaluator.py index e86120073..acc6965d2 100644 --- a/src/tests/e2e/evals/evaluation/rag_eval/evaluator.py +++ b/src/tests/e2e/evals/evaluation/rag_eval/evaluator.py @@ -140,6 +140,9 @@ def get_golden_context(self, data: dict): def get_query(self, data: dict): raise NotImplementedError("Depends on the specific dataset.") + def get_question_type(self, data: dict): + raise NotImplementedError("Depends on the specific dataset.") + def get_document(self, data: dict): raise NotImplementedError("Depends on the specific dataset.") @@ -164,6 +167,7 @@ def scoring(self, data: dict) -> dict: }, "log": { "query": self.get_query(data), + "query_type": self.get_question_type(data), "generated_text": generated_text, "ground_truth_text": ground_truth_text, "evaluateDatetime": str(datetime.now()), @@ -217,6 +221,7 @@ def scoring_retrieval(self, data: dict, normalize: bool = True) -> dict: }, "log": { "query": self.get_query(data), + "query_type": self.get_question_type(data), "golden_context": golden_context, "num_retrieved_documents": len(retrieved_documents), "num_reranked_documents": len(reranked_documents), diff --git a/src/tests/e2e/evals/evaluation/rag_eval/examples/eval_multihop.py b/src/tests/e2e/evals/evaluation/rag_eval/examples/eval_multihop.py index b7b4873d7..df8139f3f 100644 --- a/src/tests/e2e/evals/evaluation/rag_eval/examples/eval_multihop.py +++ b/src/tests/e2e/evals/evaluation/rag_eval/examples/eval_multihop.py @@ -41,6 +41,9 @@ def get_ground_truth_text(self, data: dict): def get_query(self, data: dict): return data["query"] + def get_question_type(self, data: dict): + return data.get("question_type") or "unknown" + def get_template(self): return None @@ -63,7 +66,7 @@ def evaluate(self, all_queries, arguments): generated_text = self.send_request(query, arguments) data["generated_text"] = generated_text - result = {"id": index, "uuid": self.get_uuid(query), **self.scoring(data)} + result = {"id": index, "uuid": self.get_uuid(query), "question_type": self.get_question_type(data), **self.scoring(data)} logger.debug(f"Result for query {index}: {result}") results.append(result) index += 1 @@ -194,6 +197,7 @@ def get_retrieval_metrics(self, all_queries, arguments): def prepare_ragas_record(self, data, arguments): query = self.get_query(data) + question_type = self.get_question_type(data) generated_text = self.send_request(query, arguments) try: @@ -204,6 +208,7 @@ def prepare_ragas_record(self, data, arguments): return { "query": query, + "question_type": question_type, "generated_text": generated_text, "ground_truth": self.get_ground_truth_text(data), "golden_context": self.get_golden_context(data), @@ -293,8 +298,9 @@ def get_ragas_metrics(self, all_queries, arguments): # Store metadata for each query query_metadata.append({ - "query": result["query"], "uuid": self.get_uuid(result["query"]), + "query": result["query"], + "question_type": result["question_type"], "generated_text": result["generated_text"], "ground_truth": result["ground_truth"], "golden_context": result["golden_context"], @@ -328,6 +334,7 @@ def get_ragas_metrics(self, all_queries, arguments): "ragas_metrics": score, "log": { "query": query_metadata[idx]["query"], + "question_type": query_metadata[idx]["question_type"], "generated_text": query_metadata[idx]["generated_text"], "ground_truth": query_metadata[idx]["ground_truth"], "golden_context": query_metadata[idx]["golden_context"], @@ -398,6 +405,7 @@ def args_parser(): parser.add_argument("--ragas_metrics", action="store_true", help="Whether to compute ragas metrics such as answer correctness, relevancy, semantic similarity, context precision, context recall , and faithfulness") parser.add_argument("--skip_normalize", action="store_true", help="Skip normalization of 'None' separators in retrieval metrics. By default, normalization is enabled") parser.add_argument("--limits", type=int, default=100, help="Number of queries to evaluate. Set to 0 to evaluate all provided queries") + parser.add_argument("--exclude_types", type=str, nargs='+', dest='exclude_types', help="Exclude queries by question type. Queries matching these question types will be skipped. Example: --exclude_types comparision_query") parser.add_argument("--resume_checkpoint", type=str, help="Path to a checkpoint file to resume evaluation from previously saved progress") parser.add_argument("--keep_checkpoint", action="store_true", help="Keep the checkpoint file after successful evaluation instead of deleting it") parser.add_argument("--llm_judge_endpoint", type=str, default="http://localhost:8008", help="URL of the LLM judge service. Only used for RAGAS metrics") @@ -475,6 +483,29 @@ def filter_category_null_queries(queries): return [q for q in queries if q.get("question_type") != 'null_query'] + +def filter_queries_by_type(queries, exclude_types=None): + """ + Filter queries by excluding specific question types. + + Args: + queries: List of query dictionaries + exclude_types: List of question types to exclude (if None, exclude none) + + Returns: + Filtered list of queries + """ + if not exclude_types: + return queries + + logger.info(f"Excluding question types: {exclude_types}") + # Normalize exclude_types to lowercase and strip whitespace for case-insensitive comparison + normalized_exclude_types = {qt.lower().strip() for qt in exclude_types} + filtered = [q for q in queries if q.get("question_type", "").lower().strip() not in normalized_exclude_types] + + return filtered + + def main(): args = args_parser() logger.info(f"Running Multihop evaluation with arguments: {args.__dict__}") @@ -536,8 +567,13 @@ def main(): all_queries = filter_category_null_queries(all_queries) logger.info(f"Queries remaining: {len(all_queries)}") + # Filter by question type if specified + if args.exclude_types: + all_queries = filter_queries_by_type(all_queries, args.exclude_types) + logger.info(f"Queries after type filtering: {len(all_queries)}") + except Exception as e: - logger.error(f"Error filtering queries categorized as 'null_query': {e}") + logger.error(f"Error filtering queries: {e}") if not all_queries: logger.error("No queries remain after filtering 'null_query' category. Please check the dataset.") diff --git a/src/tests/e2e/evals/evaluation/rag_eval/requirements.txt b/src/tests/e2e/evals/evaluation/rag_eval/requirements.txt index 211cd17b2..74cccb056 100644 --- a/src/tests/e2e/evals/evaluation/rag_eval/requirements.txt +++ b/src/tests/e2e/evals/evaluation/rag_eval/requirements.txt @@ -15,7 +15,7 @@ prometheus-fastapi-instrumentator==7.0.0 # LangChain dependencies langchain==0.3.27 -langchain-core==0.3.80 +langchain-core==0.3.81 langchain-openai==0.3.35 # RAG evaluation packages diff --git a/src/tests/e2e/files/dataprep_upload/test_post_backup.txt b/src/tests/e2e/files/dataprep_upload/test_post_backup.txt new file mode 100644 index 000000000..65d558fff --- /dev/null +++ b/src/tests/e2e/files/dataprep_upload/test_post_backup.txt @@ -0,0 +1 @@ +According to a 2024 report, the mole population in the city of Gdansk exceeded 1.2 million individuals, meaning there were on average four moles for every resident. \ No newline at end of file diff --git a/src/tests/e2e/files/dataprep_upload/test_pre_backup.txt b/src/tests/e2e/files/dataprep_upload/test_pre_backup.txt new file mode 100644 index 000000000..eb9233514 --- /dev/null +++ b/src/tests/e2e/files/dataprep_upload/test_pre_backup.txt @@ -0,0 +1 @@ +Elvira Marqens from the small village of Rulberton crafts a unique cheese called Trindlefoss. diff --git a/src/tests/e2e/files/dataprep_upload/test_adoc_tables.adoc b/src/tests/e2e/files/dataset_en/test_adoc_tables.adoc similarity index 100% rename from src/tests/e2e/files/dataprep_upload/test_adoc_tables.adoc rename to src/tests/e2e/files/dataset_en/test_adoc_tables.adoc diff --git a/src/tests/e2e/files/dataprep_upload/test_top_n_1.txt b/src/tests/e2e/files/dataset_en/test_top_n_1.txt similarity index 100% rename from src/tests/e2e/files/dataprep_upload/test_top_n_1.txt rename to src/tests/e2e/files/dataset_en/test_top_n_1.txt diff --git a/src/tests/e2e/files/dataprep_upload/test_top_n_2.txt b/src/tests/e2e/files/dataset_en/test_top_n_2.txt similarity index 100% rename from src/tests/e2e/files/dataprep_upload/test_top_n_2.txt rename to src/tests/e2e/files/dataset_en/test_top_n_2.txt diff --git a/src/tests/e2e/files/dataprep_upload/story.txt b/src/tests/e2e/files/dataset_en/test_txt.txt similarity index 100% rename from src/tests/e2e/files/dataprep_upload/story.txt rename to src/tests/e2e/files/dataset_en/test_txt.txt diff --git a/src/tests/e2e/files/dataset_pl/test_adoc_tables.adoc b/src/tests/e2e/files/dataset_pl/test_adoc_tables.adoc new file mode 100644 index 000000000..32ad94a81 --- /dev/null +++ b/src/tests/e2e/files/dataset_pl/test_adoc_tables.adoc @@ -0,0 +1,54 @@ += Przykładowe Tabele Produktowe + +== Tabela 1: Standardowa Tabela AsciiDoc + +[options="header,footer"] +|======================= +|ID |Nazwa Produktu |Kategoria + +|1 |Zentrophin Gelax |Kosmetyka +|2 |Flornax Quibit |Artykuły domowe +|3 |Nebulor Vexid |Outdoor +|4 |Crysolune Kitra |Technologia +|5 |Dravexi Loomin |Zabawki + +|======================= + +== Tabela 2: Tabela w formacie CSV + +[format="csv",cols="4"] +|====== +ID,Produkt,Cena,Stan magazynowy +101,Blurnix Droppa,19.99,128 +102,Vintago Plustik,7.45,432 +103,Myzterna Flux,42.00,5 +104,Keplaroon Zetta,99.90,0 +|====== + +== Tabela 3: Tabela z łączonymi komórkami i wieloliniami + +[options="header"] +|=== +|ID |Nazwa Produktu |Opis |Status + +|201 +|Quarlix Supreme +|Środek do wielu powierzchni + +z modułem zapachu bioaktywnego +|Dostępny + +|202 +|Luminoid Krux +.2+|Kompaktowa lekka kostka +|Wyprzedany + +|203 +|- (jak powyżej) +|Wycofany + +|204 +|Snarkelbit HyperEdge +|Interfejs gamingowy i audio 3-w-1 +|W produkcji + +|=== diff --git a/src/tests/e2e/files/dataset_pl/test_top_n_1.txt b/src/tests/e2e/files/dataset_pl/test_top_n_1.txt new file mode 100644 index 000000000..4b415c608 --- /dev/null +++ b/src/tests/e2e/files/dataset_pl/test_top_n_1.txt @@ -0,0 +1 @@ +Emanueleee ma 4 zdalnie sterowane samochody. diff --git a/src/tests/e2e/files/dataset_pl/test_top_n_2.txt b/src/tests/e2e/files/dataset_pl/test_top_n_2.txt new file mode 100644 index 000000000..92aefbca0 --- /dev/null +++ b/src/tests/e2e/files/dataset_pl/test_top_n_2.txt @@ -0,0 +1 @@ +Raffaeleee ma 27 zdalnie sterowanych samochodów. diff --git a/src/tests/e2e/files/dataset_pl/test_txt.txt b/src/tests/e2e/files/dataset_pl/test_txt.txt new file mode 100644 index 000000000..b925ded50 --- /dev/null +++ b/src/tests/e2e/files/dataset_pl/test_txt.txt @@ -0,0 +1 @@ +W Gdańsku zarejestrowanych jest 851 samochodów marki Fiat potocznie nazywanych MALUCHAMI. \ No newline at end of file diff --git a/src/tests/e2e/files/localized_dataset.yaml b/src/tests/e2e/files/localized_dataset.yaml new file mode 100644 index 000000000..2adc2fc9b --- /dev/null +++ b/src/tests/e2e/files/localized_dataset.yaml @@ -0,0 +1,42 @@ +# yamllint disable-line rule:line-length +test_txt: + - en: + files: [test_txt.txt] + questions: + - question: "How many cars commonly called MALUCH are registered in Gdansk?" + expected_any: ["851"] + pl: + files: [test_txt.txt] + questions: + - question: "Ile samochodów potocznie nazywanych MALUCHAMI jest zarejestrowanych w Gdańsku?" + expected_any: ["851"] +test_top_n: + - en: + files: [test_top_n_1.txt, test_top_n_2.txt] + questions: + - question: "How many RC cars do Emanueleee and Raffaeleee have in total?" + expected_any: ["31"] + pl: + files: [test_top_n_1.txt, test_top_n_2.txt] + questions: + - question: "Ile aut zdalnie sterowanych mają łącznie Emanueleee i Raffaeleee?" + expected_any: ["31"] +test_adoc_tables: + - en: + files: [test_adoc_tables.adoc] + questions: + - question: "What category does Flornax Quibit belong to?" + expected_any: ["homeware"] + - question: "What is the price for Myzterna Flux?" + expected_any: ["42"] + - question: "Give me a description of the product called 'Luminoid Krux'" + expected_any: ["compact", "light", "cube"] + pl: + files: [test_adoc_tables.adoc] + questions: + - question: "Do jakiej kategorii należy Flornax Quibit?" + expected_any: ["domowe", "homeware"] + - question: "Jaka jest cena Myzterna Flux?" + expected_any: ["42"] + - question: "Podaj opis produktu o nazwie 'Luminoid Krux'" + expected_any: ["kompaktowa", "lekka", "kostka"] diff --git a/src/tests/e2e/helpers/k8s_helper.py b/src/tests/e2e/helpers/k8s_helper.py index 4144feaec..363facb42 100644 --- a/src/tests/e2e/helpers/k8s_helper.py +++ b/src/tests/e2e/helpers/k8s_helper.py @@ -11,6 +11,10 @@ logger = logging.getLogger(__name__) +class ResourceNotFound(Exception): + pass + + class K8sHelper: def retrieve_admin_password(self, secret_name, namespace): @@ -28,21 +32,41 @@ def list_namespaces(self): namespaces = kr8s.get("namespaces") return [ns.name for ns in namespaces] + def get_namespace(self, namespace_name): + """Get a namespace by name""" + namespaces = kr8s.get("namespaces") + for ns in namespaces: + if ns.name == namespace_name: + return ns + return None + + def get_backups(self, namespace): + """Get a list of kr8s CustomResource objects representing backups in a namespace""" + logger.debug(f"Getting backups in namespace '{namespace}'") + return kr8s.get("backups", namespace=namespace) + def list_pods(self, namespace): """List all pods in the specified namespace""" - pods = kr8s.get("pods", namespace=namespace) - return [pod.name for pod in pods] + return kr8s.get("pods", namespace=namespace) - def get_pods_by_label(self, namespace, label_selector): - """Get a list of kr8s Pod objects matching a label selector in a namespace""" + def get_pod_by_label(self, namespace, label_selector): + """Returns first pod matching a label selector in a namespace""" logger.debug(f"Getting pods with label selector '{label_selector}' in namespace '{namespace}'") - return kr8s.get("pods", namespace=namespace, label_selector=label_selector) + pods = kr8s.get("pods", namespace=namespace, label_selector=label_selector) + if len(pods) == 0: + raise ResourceNotFound(f"No running pods found with label '{label_selector}' in namespace '{namespace}'.") + return pods[0] def exec_in_pod(self, pod, command): """Execute a command in a pod's container""" logger.debug(f"Executing command '{command}' in pod '{pod.name}'") try: - return pod.exec(command) + exec_result = pod.exec(command) + stdout = exec_result.stdout + if isinstance(stdout, bytes): + return stdout.decode().strip() + else: + return stdout.strip() except Exception as e: logger.error(f"Failed to execute command in pod '{pod.name}': {e}") raise # Re-raise the exception to fail the test diff --git a/src/tests/e2e/helpers/keycloak_helper.py b/src/tests/e2e/helpers/keycloak_helper.py index 5a43649bd..f9e1e5031 100644 --- a/src/tests/e2e/helpers/keycloak_helper.py +++ b/src/tests/e2e/helpers/keycloak_helper.py @@ -207,3 +207,44 @@ def set_brute_force_detection(self, enabled: bool): response = requests.put(url, json=realm_settings, headers=headers, verify=False) if response.status_code != 204: raise Exception(f"Failed to update brute force detection (status {response.status_code}): {response.text}") + + def add_user(self, username, password, first_name="", last_name="", email=""): + """Add a new user to Keycloak""" + logger.info(f"Adding new user '{username}' to Keycloak") + url = f"{self.erag_auth_domain}/admin/realms/{VITE_KEYCLOAK_REALM}/users" + headers = { + "Authorization": f"Bearer {self.admin_access_token}", + "Content-Type": "application/json" + } + payload = { + "username": username, + "enabled": True, + "firstName": first_name, + "lastName": last_name, + "email": email, + "credentials": [{ + "type": "password", + "value": password, + "temporary": False + }] + } + response = requests.post(url, json=payload, headers=headers, verify=False) + if response.status_code != 201: + raise Exception(f"Failed to add user '{username}' (status {response.status_code}): {response.text}") + logger.info(f"User '{username}' added successfully") + + def user_exists(self, username): + """Check if a user exists in Keycloak""" + logger.info(f"Checking if user '{username}' exists in Keycloak") + url = f"{self.erag_auth_domain}/admin/realms/{VITE_KEYCLOAK_REALM}/users?username={username}" + headers = { + "Authorization": f"Bearer {self.admin_access_token}", + "Content-Type": "application/json" + } + response = requests.get(url, headers=headers, verify=False) + if response.status_code != 200: + raise Exception(f"Failed to check user existence (status {response.status_code}): {response.text}") + users = response.json() + exists = len(users) > 0 + logger.info(f"User '{username}' exists: {exists}") + return exists diff --git a/src/tests/e2e/lifecycle/scenarios.yaml b/src/tests/e2e/lifecycle/scenarios.yaml index f7792f4de..4dfc6a284 100644 --- a/src/tests/e2e/lifecycle/scenarios.yaml +++ b/src/tests/e2e/lifecycle/scenarios.yaml @@ -23,3 +23,14 @@ scenarios: lifecycle: - test_update_reranker_model.py markers: "smoke" + + update_embedding_model: + lifecycle: + - test_update_embedding_model.py + markers: "smoke" + + backup-restore: + lifecycle: + - test_pre_backup.py + - test_post_backup.py + - test_post_restore.py diff --git a/src/tests/e2e/lifecycle/test_post_backup.py b/src/tests/e2e/lifecycle/test_post_backup.py new file mode 100644 index 000000000..acc6c2ee9 --- /dev/null +++ b/src/tests/e2e/lifecycle/test_post_backup.py @@ -0,0 +1,66 @@ +#!/usr/bin/env python +# -*- coding: utf-8 -*- +# Copyright (C) 2025 Intel Corporation +# SPDX-License-Identifier: Apache-2.0 + +import allure +import logging +import os + +from tests.e2e.validation.constants import DATAPREP_UPLOAD_DIR + +logger = logging.getLogger(__name__) + + +@allure.testcase("IEASG-T313") +def test_post_backup_backup_created(k8s_helper): + """ + Check backup is properly created. + 1. check if "velero" namespace exists. + 2. check if there is at least one backup in velero namespace. + 3. check if backup is in "Completed" status (check all backups for the sake of simplicity). + 4. check if there are no "Error" or "CrashLoopBackOff" pods in "velero" namespace. + """ + velero_ns = k8s_helper.get_namespace("velero") + assert velero_ns is not None, "Velero namespace does not exist." + + backups = k8s_helper.get_backups(namespace="velero") + assert len(backups) > 0, "No backups found in velero namespace." + + for backup in backups: + logger.debug(f"Backup Name: {backup.name}, Status: {backup.status.phase}") + assert backup.status.phase == "Completed", f"Backup {backup.name} is not completed." + + velero_pods = k8s_helper.list_pods(namespace="velero") + for pod in velero_pods: + pod_status = pod.status.phase + logger.debug(f"Pod Name: {pod.name}, Status: {pod_status}") + assert pod_status not in ["Error", "CrashLoopBackOff"], f"Pod {pod.name} is in {pod_status} status." + + +@allure.testcase("IEASG-T314") +def test_post_backup_data_ingested_after_backup(keycloak_helper, edp_helper, chat_history_helper): + """ + Ingest some data which should not be present in the backup since backup was already created. + 1. Upload a file to the system via EDP. + 2. Create a chat history via Chat History API. + 3. Create a new user in Keycloak. + """ + # Upload a file + file = "test_post_backup.txt" + edp_helper.upload_file_and_wait_for_ingestion(os.path.join(DATAPREP_UPLOAD_DIR, file)) + + # Create chat history + chat_history_helper.save_history([ + { + "question": "How do voles affect the ecosystem near Gdansk Airport?", + "answer": "They serve as a crucial food source for various predators such as owls, " + "foxes, and snakes, helping maintain the balance of the food web.", + "metadata": {} + } + ]) + + # Create a new user + user = "post-backup-user-that-should-not-exist-after-restore" + if not keycloak_helper.user_exists(user): + keycloak_helper.add_user(user, "PostBackupPass123!", "PostBackupUser", "PostBackupSurname", "postbackup@example.com") diff --git a/src/tests/e2e/lifecycle/test_post_restore.py b/src/tests/e2e/lifecycle/test_post_restore.py new file mode 100644 index 000000000..4b60fdab0 --- /dev/null +++ b/src/tests/e2e/lifecycle/test_post_restore.py @@ -0,0 +1,76 @@ +#!/usr/bin/env python +# -*- coding: utf-8 -*- +# Copyright (C) 2025 Intel Corporation +# SPDX-License-Identifier: Apache-2.0 + +import allure +import logging +import pytest + +logger = logging.getLogger(__name__) + + +@allure.testcase("IEASG-T315") +def test_post_restore_data_exists(keycloak_helper, edp_helper, chat_history_helper, chatqa_api_helper): + """ + 1. Verify that the previously uploaded file is present in the system. + 2. Verify that the chat history is present. + 3. Verify that the previously created user exists. + 4. Ask a question related to the pre-backup data to ensure the system responds correctly. + """ + # Verify uploaded file exists + file_name = "test_pre_backup.txt" + files = edp_helper.list_files() + for item in files.json(): + if file_name in item['object_name']: + logger.debug(f"File found: {item['object_name']}") + break + else: + pytest.fail(f"File {file_name} not found after restore.") + + # Verify chat history exists + response = chat_history_helper.get_all_histories() + all_history_names = [history["history_name"] for history in response.json()] + logger.debug(f"All histories: {all_history_names}") + for history in all_history_names: + if "What is the name of the cheese" in history: + logger.debug(f"Chat history found: {history}") + break + else: + pytest.fail("Chat history not found after restore.") + + # Verify user + user = "backup-test" + assert keycloak_helper.user_exists(user), f"User {user} not found after restore" + + response = chatqa_api_helper.call_chatqa( + "What unique product does Elvira Marqens craft in the village of Rulberton?") + assert response.status_code == 200, "Unexpected status code returned" + response_text = chatqa_api_helper.get_text(response) + logger.info(f"ChatQA response: {response_text}") + assert "cheese" in response_text.lower(), "Unexpected answer from ChatQA after restore" + + +@allure.testcase("IEASG-T316") +def test_post_restore_data_does_not_exists(keycloak_helper, edp_helper, chat_history_helper): + """ + Check if data ingested after backup does not exist after restore. + """ + # Verify uploaded file does not exist + file_name = "test_post_backup.txt" + files = edp_helper.list_files() + for item in files.json(): + if file_name in item['object_name']: + pytest.fail(f"File {file_name} found after restore, but it should not be present.") + + # Verify chat history does not exist + response = chat_history_helper.get_all_histories() + all_history_names = [history["history_name"] for history in response.json()] + logger.debug(f"All histories: {all_history_names}") + for history in all_history_names: + if "How do voles affect" in history: + pytest.fail("Chat history found after restore, but it should not be present.") + + # Verify user does not exist + user = "post-backup-user-that-should-not-exist-after-restore" + assert not keycloak_helper.user_exists(user), f"User {user} found after restore, but it should not be present." diff --git a/src/tests/e2e/lifecycle/test_pre_backup.py b/src/tests/e2e/lifecycle/test_pre_backup.py new file mode 100644 index 000000000..139764db1 --- /dev/null +++ b/src/tests/e2e/lifecycle/test_pre_backup.py @@ -0,0 +1,39 @@ +#!/usr/bin/env python +# -*- coding: utf-8 -*- +# Copyright (C) 2025 Intel Corporation +# SPDX-License-Identifier: Apache-2.0 + +import allure +import logging +import os + +from tests.e2e.validation.constants import DATAPREP_UPLOAD_DIR + +logger = logging.getLogger(__name__) + + +@allure.testcase("IEASG-T312") +def test_pre_backup(keycloak_helper, edp_helper, chat_history_helper): + """ + Prepare data for backup: + 1. Upload a file to the system via EDP. + 2. Create a chat history via Chat History API. + 3. Create a new user in Keycloak. + """ + # Populate db + file = "test_pre_backup.txt" + edp_helper.upload_file_and_wait_for_ingestion(os.path.join(DATAPREP_UPLOAD_DIR, file)) + + # Populate chat history + chat_history_helper.save_history([ + { + "question": "What is the name of the cheese produced by Elvira Marqens from the village of Rulberton?", + "answer": "Trindlefoss.", + "metadata": {} + } + ]) + + # Add new user if it does not exist + user = "backup-test" + if not keycloak_helper.user_exists(user): + keycloak_helper.add_user(user, "PreBackupPass123!", "BackupUser", "BackupSurname", "backup@example.com") diff --git a/src/tests/e2e/lifecycle/test_uninstall.py b/src/tests/e2e/lifecycle/test_uninstall.py index f42ad5fea..4ce10fed0 100644 --- a/src/tests/e2e/lifecycle/test_uninstall.py +++ b/src/tests/e2e/lifecycle/test_uninstall.py @@ -25,7 +25,7 @@ def disable_guards_at_startup(guard_helper, suppress_logging, temporarily_remove @allure.testcase("IEASG-T309") def test_uninstall(k8s_helper): """Verify that after uninstallation, only the allowed namespaces and no unexpected pods exist.""" - allowed_namespaces = ["default", "kube-system", "kube-public", "kube-node-lease", "local-path-storage"] + allowed_namespaces = ["default", "habana-system", "kube-system", "kube-public", "kube-node-lease", "local-path-storage"] current_namespaces = k8s_helper.list_namespaces() logger.debug(f"Namespaces in the cluster: {current_namespaces}") unexpected_ns = [ns for ns in current_namespaces if ns not in allowed_namespaces] diff --git a/src/tests/e2e/lifecycle/test_update_embedding_model.py b/src/tests/e2e/lifecycle/test_update_embedding_model.py new file mode 100644 index 000000000..f87d521a8 --- /dev/null +++ b/src/tests/e2e/lifecycle/test_update_embedding_model.py @@ -0,0 +1,38 @@ +#!/usr/bin/env python +# -*- coding: utf-8 -*- +# Copyright (C) 2025 Intel Corporation +# SPDX-License-Identifier: Apache-2.0 + +import allure +import logging +import pytest + +from tests.e2e.validation.constants import CHATQA_NAMESPACE +from tests.e2e.validation.buildcfg import cfg + +logger = logging.getLogger(__name__) + +EMBEDDING_POD_LABEL_SELECTOR = "app.kubernetes.io/name=embedding-usvc" + + +@allure.testcase("IEASG-T311") +def test_update_embedding_model(k8s_helper): + """ + Test verifies if reranker pod have the expected EMBEDDING_MODEL_NAME + environment variable set. + """ + expected_model_name = cfg.get("embedding_model_name") + logger.info(f"Expected reranking model name from config: {expected_model_name}") + embedding_pod = k8s_helper.get_pod_by_label(namespace=CHATQA_NAMESPACE, + label_selector=EMBEDDING_POD_LABEL_SELECTOR) + + command = ["sh", "-c", "echo $EMBEDDING_MODEL_NAME"] + logger.info(f"Checking environment variable $EMBEDDING_MODEL_NAME in pod: {embedding_pod.name}") + try: + env_value = k8s_helper.exec_in_pod(embedding_pod, command) + logger.info(f"Pod '{embedding_pod.name}' reports EMBEDDING_MODEL_NAME = '{env_value}'") + except Exception as e: + pytest.fail(f"Test failed while executing command in pod '{embedding_pod.name}'. Error: {e}") + + assert env_value == expected_model_name, \ + f"Pod '{embedding_pod.name}' has an incorrect model name. Expected: '{expected_model_name}', Found: '{env_value}'" diff --git a/src/tests/e2e/lifecycle/test_update_llm_model.py b/src/tests/e2e/lifecycle/test_update_llm_model.py index 9690537f2..5eaae14e7 100644 --- a/src/tests/e2e/lifecycle/test_update_llm_model.py +++ b/src/tests/e2e/lifecycle/test_update_llm_model.py @@ -5,12 +5,42 @@ import allure import logging +import pytest + +from tests.e2e.helpers.k8s_helper import ResourceNotFound +from tests.e2e.validation.buildcfg import cfg +from tests.e2e.validation.constants import CHATQA_NAMESPACE logger = logging.getLogger(__name__) +VLLM_POD_LABEL_SELECTOR = "app.kubernetes.io/name=vllm" +VLLM_GAUDI_POD_LABEL_SELECTOR = "app.kubernetes.io/name=vllm_gaudi" + -# TODO: add allure test case id -@allure.testcase("IEASG-T") +@allure.testcase("IEASG-T288") def test_update_llm_model(k8s_helper): - """ """ - pass + """ + Test verifies if vllm pod have the expected LLM_VLLM_MODEL_NAME env variable set. + It first tries to find the vllm pod, and if not found, it falls back to the vllm-gaudi pod. + Depending on which pod is found, it checks the corresponding model name from the config. + """ + try: + vllm_pod = k8s_helper.get_pod_by_label(namespace=CHATQA_NAMESPACE, label_selector=VLLM_POD_LABEL_SELECTOR) + expected_model_name = cfg.get("llm_model") + except ResourceNotFound as e: + logger.debug(e) + logger.debug("Looking for vllm-gaudi pod as fallback.") + vllm_pod = k8s_helper.get_pod_by_label(namespace=CHATQA_NAMESPACE, label_selector=VLLM_GAUDI_POD_LABEL_SELECTOR) + expected_model_name = cfg.get("llm_model_gaudi") + + logger.info(f"Expected LLM model name from config: {expected_model_name}") + command = ["sh", "-c", "echo $LLM_VLLM_MODEL_NAME"] + logger.info(f"Checking environment variable $LLM_VLLM_MODEL_NAME in pod: {vllm_pod.name}") + try: + env_value = k8s_helper.exec_in_pod(vllm_pod, command) + logger.info(f"Pod '{vllm_pod.name}' reports LLM_VLLM_MODEL_NAME = '{env_value}'") + except Exception as e: + pytest.fail(f"Test failed while executing command in pod '{vllm_pod.name}'. Error: {e}") + + assert env_value == expected_model_name, \ + f"Pod '{vllm_pod.name}' has an incorrect model name. Expected: '{expected_model_name}', Found: '{env_value}'" diff --git a/src/tests/e2e/lifecycle/test_update_reranker_model.py b/src/tests/e2e/lifecycle/test_update_reranker_model.py index 1bdb0411d..25fa2788e 100644 --- a/src/tests/e2e/lifecycle/test_update_reranker_model.py +++ b/src/tests/e2e/lifecycle/test_update_reranker_model.py @@ -7,12 +7,12 @@ import logging import pytest +from tests.e2e.validation.constants import CHATQA_NAMESPACE from tests.e2e.validation.buildcfg import cfg logger = logging.getLogger(__name__) -NAMESPACE = "chatqa" -APP_LABEL_SELECTOR = "app.kubernetes.io/name=reranking-usvc" +RERANKER_POD_LABEL_SELECTOR = "app.kubernetes.io/name=reranking-usvc" @allure.testcase("IEASG-T310") @@ -23,26 +23,15 @@ def test_update_reranker_model(k8s_helper): """ expected_model_name = cfg.get("reranking_model_name") logger.info(f"Expected reranking model name from config: {expected_model_name}") + reranker_pod = k8s_helper.get_pod_by_label(namespace=CHATQA_NAMESPACE, label_selector=RERANKER_POD_LABEL_SELECTOR) - pods = k8s_helper.get_pods_by_label(namespace=NAMESPACE, label_selector=APP_LABEL_SELECTOR) - assert len(pods) > 0, f"No running pods found with label '{APP_LABEL_SELECTOR}' in namespace '{NAMESPACE}'." - reranker_pod = pods[0] - + command = ["sh", "-c", "echo $RERANKING_MODEL_NAME"] logger.info(f"Checking environment variable $RERANKING_MODEL_NAME in pod: {reranker_pod.name}") try: - command = ["sh", "-c", "echo $RERANKING_MODEL_NAME"] - exec_result = k8s_helper.exec_in_pod(reranker_pod, command) - - stdout = exec_result.stdout - if isinstance(stdout, bytes): - env_value = stdout.decode().strip() - else: - env_value = stdout.strip() - + env_value = k8s_helper.exec_in_pod(reranker_pod, command) logger.info(f"Pod '{reranker_pod.name}' reports RERANKING_MODEL_NAME = '{env_value}'") - - assert env_value == expected_model_name, \ - f"Pod '{reranker_pod.name}' has an incorrect model name. Expected: '{expected_model_name}', Found: '{env_value}'" - except Exception as e: pytest.fail(f"Test failed while executing command in pod '{reranker_pod.name}'. Error: {e}") + + assert env_value == expected_model_name, \ + f"Pod '{reranker_pod.name}' has an incorrect model name. Expected: '{expected_model_name}', Found: '{env_value}'" diff --git a/src/tests/e2e/validation/README.md b/src/tests/e2e/validation/README.md index 8157e4fed..6c8f48a62 100644 --- a/src/tests/e2e/validation/README.md +++ b/src/tests/e2e/validation/README.md @@ -27,46 +27,34 @@ tox -e e2e To run specific tests that match a name pattern (using a simple regex), use: ``` -tox -e e2e -- -k +tox -e e2e -- --build-config-file= --credentials-file= -k ``` -Replace with your search keyword or pattern. - +* `` - full path to `config.yaml` file +* `` - full path to `default_credentials.txt` file which contains credentials for admin and user +* `` - desired test name you want to run ## Allure Integration -We use Allure for test reporting. When tests are run via tox, results are automatically collected and stored in `allure-results` directory (as specified in tox.ini). These results can then be uploaded to Zephyr using the following script: - -https://github.com/intel-sandbox/rag-solution-infra/blob/main/tools/upload_test_results_to_zephyr.py - +We use Allure for test reporting. When tests are run via tox, results are automatically collected and stored in `allure-results` directory (as specified in tox.ini). ## Project Structure & Best Practices ### Test Location -All E2E tests are stored in the src/tests/ directory. Each module should be named according to the component being tested. Example: +All E2E tests are stored in the src/tests/e2e/validation directory. Each module should be named according to the component being tested. Example: ``` -test_chatqa.py +test_chatqa_pipeline.py test_edp.py ``` -This naming convention helps with clarity and maintainability. - -### Helpers and Fixtures -Reusable test helpers and setup logic are implemented as Pytest fixtures. Shared fixtures are defined in `src/tests/conftest.py`, while additional utilities can be organized under `src/tests/helpers/`. - -Example fixture: - -```python -# src/tests/conftest.py +This naming convention helps with clariyyty and maintainability. -import pytest -from .helpers.guard_helper import GuardHelper +### Test Data +Any data files required for the tests (such as input files for EDP, long code snippets, or other external assets) should be stored in the `src/tests/e2e/files` directory. This ensures that large or static data is kept separate from the test logic. -@pytest.fixture(scope="session") -def guard_helper(chatqa_api_helper, fingerprint_api_helper): - return GuardHelper(chatqa_api_helper, fingerprint_api_helper) -``` +### Helpers and Fixtures +Reusable test helpers and setup logic are implemented as Pytest fixtures. Shared fixtures are defined in `src/tests/e2e/conftest.py`, while additional utilities can be organized under `src/tests/e2e/helpers/`. ## Linking Tests to Zephyr -Each test should be linked to its corresponding Zephyr test case using the @allure.testcase decorator: +Each test should be linked to its corresponding Zephyr test case using the `@allure.testcase` decorator: ```python import allure diff --git a/src/tests/e2e/validation/constants.py b/src/tests/e2e/validation/constants.py index 308492d4a..e4d484666 100644 --- a/src/tests/e2e/validation/constants.py +++ b/src/tests/e2e/validation/constants.py @@ -11,3 +11,4 @@ VITE_KEYCLOAK_CLIENT_ID = "EnterpriseRAG-oidc" INGRESS_NGINX_CONTROLLER_NS = "ingress-nginx" INGRESS_NGINX_CONTROLLER_POD_LABEL_SELECTOR = {"app.kubernetes.io/name": "ingress-nginx"} +CHATQA_NAMESPACE = "chatqa" \ No newline at end of file diff --git a/src/tests/e2e/validation/test_api_health_checks.py b/src/tests/e2e/validation/test_api_health_checks.py index a69c3e422..a5d3a05d9 100644 --- a/src/tests/e2e/validation/test_api_health_checks.py +++ b/src/tests/e2e/validation/test_api_health_checks.py @@ -52,11 +52,18 @@ def test_api_health_checks(generic_api_helper): try: response = generic_api_helper.call_health_check_api( service['namespace'], service['selector'], service['port'], service['health_path']) - assert response.status_code == 200, \ - f"Got unexpected status code for {service['selector']} health check API call" - except (AssertionError, requests.exceptions.RequestException) as e: - logger.warning(e) + if response.status_code != 200: + error_msg = ( + f"Health check failed for {service['selector']}. " + f"Status Code: {response.status_code}, " + f"Response Body: {response.text}" + ) + logger.error(error_msg) + assert response.status_code == 200, error_msg + + except (AssertionError, requests.exceptions.RequestException) as e: + logger.warning(f"Error during health check for {service['selector']}: {e}") failed_microservices.append(service) - assert failed_microservices == [], "/v1/health_check API call didn't succeed for some microservices" + assert failed_microservices == [], f"Health check failed for services: {failed_microservices}" diff --git a/src/tests/e2e/validation/test_learning_capabilities.py b/src/tests/e2e/validation/test_learning_capabilities.py index d1b75278f..3a850b7f3 100644 --- a/src/tests/e2e/validation/test_learning_capabilities.py +++ b/src/tests/e2e/validation/test_learning_capabilities.py @@ -5,11 +5,13 @@ import allure import logging +import os import pytest import time -import os +from types import SimpleNamespace +import yaml -from tests.e2e.validation.constants import DATAPREP_UPLOAD_DIR +from tests.e2e.validation.constants import DATAPREP_UPLOAD_DIR, TEST_FILES_DIR from tests.e2e.validation.buildcfg import cfg # Skip all tests if chatqa pipeline is not deployed @@ -27,13 +29,25 @@ # In each test case, a file is uploaded and a question related to the file content is asked. +@pytest.fixture +def test_data(request, test_language): + """Load scenarios and package them with language info""" + data_path = os.path.join(TEST_FILES_DIR, "localized_dataset.yaml") + + with open(data_path, "r", encoding="utf-8") as f: + scenarios = yaml.load(f, Loader=yaml.SafeLoader) + + current_scenario = scenarios.get(request.node.name, []) + stages = [step[test_language] for step in current_scenario if test_language in step] + + return SimpleNamespace(stages=stages, language=test_language) + + @pytest.mark.smoke @allure.testcase("IEASG-T50") -def test_txt(edp_helper, chatqa_api_helper): +def test_txt(edp_helper, chatqa_api_helper, test_data): """*.txt file learning capabilities""" - question = "How many cars commonly called MALUCH are registered in Gdansk?" - response = upload_and_ask_question(edp_helper, chatqa_api_helper, "story.txt", question) - assert "851" in response, UNRELATED_RESPONSE_MSG + run_standard_validation(edp_helper, chatqa_api_helper, test_data) @pytest.mark.smoke @@ -355,20 +369,9 @@ def test_adoc_links(edp_helper, chatqa_api_helper): @allure.testcase("IEASG-T179") -def test_adoc_tables(edp_helper, chatqa_api_helper): +def test_adoc_tables(edp_helper, chatqa_api_helper, test_data): """Validate if tables are recognized in the adoc file""" - # 1. Test tables in a standard format - question = " What category does Flornax Quibit belong to?" - response = upload_and_ask_question(edp_helper, chatqa_api_helper, "test_adoc_tables.adoc", question) - assert "homeware" in response.lower(), UNRELATED_RESPONSE_MSG - # 2. Test tables in csv format - question = "What is the price for Myzterna Flux?" - response = ask_question(chatqa_api_helper, question) - assert "42" in response, UNRELATED_RESPONSE_MSG - # 3. Test tables with merged cells - question = "Give me a description of the product called 'Luminoid Krux'" - response = ask_question(chatqa_api_helper, question) - assert chatqa_api_helper.words_in_response(["compact", "light", "cube"], response), UNRELATED_RESPONSE_MSG + run_standard_validation(edp_helper, chatqa_api_helper, test_data) @allure.testcase("IEASG-T180") @@ -629,7 +632,7 @@ def test_multi_doc_reasoning(edp_helper, chatqa_api_helper): @allure.testcase("IEASG-T247") -def test_top_n(edp_helper, chatqa_api_helper, fingerprint_api_helper): +def test_top_n(edp_helper, chatqa_api_helper, fingerprint_api_helper, test_data): """ Upload 2 documents: A: Emanueleee has got 4 RC cars. @@ -642,19 +645,25 @@ def test_top_n(edp_helper, chatqa_api_helper, fingerprint_api_helper): current_parameters = fingerprint_api_helper.append_arguments("").json().get("parameters", {}) original_n = current_parameters.get("top_n") - file1 = "test_top_n_1.txt" - file2 = "test_top_n_2.txt" - question = "How many RC cars do Emanueleee and Raffaeleee have in total?" - edp_helper.upload_file_and_wait_for_ingestion(os.path.join(DATAPREP_UPLOAD_DIR, file1)) - edp_helper.upload_file_and_wait_for_ingestion(os.path.join(DATAPREP_UPLOAD_DIR, file2)) + # Get the first (and only) stage for this test from the unified test_data object + stage = test_data.stages[0] + question_item = stage["questions"][0] + question = question_item["question"] + expected_value = question_item["expected_any"][0] + + # 1. Ingest files using the language defined in test_data + for file_name in stage.get("files", []): + path = os.path.join(TEST_FILES_DIR, f"dataset_{test_data.language}", file_name) + edp_helper.upload_file_and_wait_for_ingestion(path) try: fingerprint_api_helper.set_component_parameters("reranker", top_n=1) response = ask_question(chatqa_api_helper, question) - assert "31" not in response.lower(), "only a single document should be used to answer the question" + assert expected_value not in response.lower(), "only a single document should be used to answer the question" + fingerprint_api_helper.set_component_parameters("reranker", top_n=3) response = ask_question(chatqa_api_helper, question) - assert "31" in response.lower(), "3 documents should be used to answer the question" + assert expected_value in response.lower(), "3 documents should be used to answer the question" finally: # revert top_n back to original value fingerprint_api_helper.set_component_parameters("reranker", top_n=original_n) @@ -676,4 +685,37 @@ def ask_question(chatqa_api_helper, question=""): def delete_file(edp_helper, file): response = edp_helper.generate_presigned_url(file, "DELETE") - return edp_helper.delete_file(response.json().get("url")) \ No newline at end of file + return edp_helper.delete_file(response.json().get("url")) + + +def run_standard_validation(edp_helper, chatqa_api_helper, test_data): + """ + For each stage in the test data: + 1. Ingest files specified in the stage. + 2. For each question in the stage, ask the question and validate the response against expected answers. + 3. Support both 'expected_any' and 'expected_all' validation methods. + """ + for stage in test_data.stages: + # 1. File ingestion + for file_name in stage.get("files", []): + path = os.path.join(TEST_FILES_DIR, f"dataset_{test_data.language}", file_name) + logger.info(f"Ingesting file: {file_name}") + edp_helper.upload_file_and_wait_for_ingestion(path) + + # 2. Question validation + for item in stage.get("questions", []): + question = item.get("question") + response = ask_question(chatqa_api_helper, question) + + # expected_any: success if at least one string is found + if "expected_any" in item: + expected_list = item["expected_any"] + assert chatqa_api_helper.words_in_response(expected_list, response), \ + f"Assertion failed! None of {expected_list} found in response: {response}" + + # expected_all: success only if all strings are found + if "expected_all" in item: + expected_list = item["expected_all"] + missing_words = [word for word in expected_list if word.lower() not in response.lower()] + assert not missing_words, \ + f"Assertion failed! Missing words: {missing_words} in response: {response}" \ No newline at end of file diff --git a/src/tox.ini b/src/tox.ini index f2c608283..caeb62351 100644 --- a/src/tox.ini +++ b/src/tox.ini @@ -380,7 +380,22 @@ deps = [testenv:e2e] description = Run end-to-end tests on a running cluster deps = {[testenv:test-base]deps} -setenv = {[testenv:test-base]setenv} +setenv = + {[testenv:test-base]setenv} + TEST_LANG = en +passenv = {[testenv:test-base]passenv} +changedir = {[testenv:test-base]changedir} +commands = + pytest -vv -s --capture=tee-sys --alluredir allure-results --clean-alluredir --log-format="%(asctime)s %(levelname)s [%(module)s] %(message)s" e2e/validation {posargs} + +# ----------------------------------------------------------------------------- + +[testenv:e2e-polish] +description = Run end-to-end tests on a running cluster +deps = {[testenv:test-base]deps} +setenv = + {[testenv:test-base]setenv} + TEST_LANG = pl passenv = {[testenv:test-base]passenv} changedir = {[testenv:test-base]changedir} commands = diff --git a/src/ui/apps/chatqna/src/features/admin-panel/control-plane/components/cards/PromptTemplateCard.tsx b/src/ui/apps/chatqna/src/features/admin-panel/control-plane/components/cards/PromptTemplateCard.tsx index 331c2c597..e637b7ad9 100644 --- a/src/ui/apps/chatqna/src/features/admin-panel/control-plane/components/cards/PromptTemplateCard.tsx +++ b/src/ui/apps/chatqna/src/features/admin-panel/control-plane/components/cards/PromptTemplateCard.tsx @@ -1,17 +1,10 @@ // Copyright (C) 2024-2025 Intel Corporation // SPDX-License-Identifier: Apache-2.0 -import { Button } from "@intel-enterprise-rag-ui/components"; import { sanitizeString } from "@intel-enterprise-rag-ui/utils"; -import { - ChangeEventHandler, - FormEventHandler, - useEffect, - useState, -} from "react"; +import { ChangeEventHandler, useEffect, useState } from "react"; import { ValidationError } from "yup"; -import { useChangeArgumentsMutation } from "@/features/admin-panel/control-plane/api"; import { ControlPlaneCardProps } from "@/features/admin-panel/control-plane/components/cards"; import SelectedServiceCard from "@/features/admin-panel/control-plane/components/SelectedServiceCard/SelectedServiceCard"; import ServiceArgumentTextArea from "@/features/admin-panel/control-plane/components/ServiceArgumentTextArea/ServiceArgumentTextArea"; @@ -19,23 +12,22 @@ import { PromptTemplateArgs, promptTemplateFormConfig, } from "@/features/admin-panel/control-plane/config/chat-qna-graph/promptTemplate"; -import { ChangeArgumentsRequest } from "@/features/admin-panel/control-plane/types/api"; +import useServiceCard from "@/features/admin-panel/control-plane/hooks/useServiceCard"; import { validatePromptTemplateForm } from "@/features/admin-panel/control-plane/validators/promptTemplateInput"; const PromptTemplateCard = ({ data: { + id, status, displayName, promptTemplateArgs: prevPromptTemplateArguments, }, }: ControlPlaneCardProps) => { - const [changeArguments] = useChangeArgumentsMutation(); - - const [promptTemplateForm, setPromptTemplateForm] = - useState( - (prevPromptTemplateArguments ?? - ({} as PromptTemplateArgs)) as PromptTemplateArgs, - ); + const { + argumentsForm: promptTemplateForm, + onArgumentValueChange, + footerProps, + } = useServiceCard(id, prevPromptTemplateArguments); const [isHydrated, setIsHydrated] = useState( !!prevPromptTemplateArguments, @@ -46,7 +38,6 @@ const PromptTemplateCard = ({ useEffect(() => { if (prevPromptTemplateArguments !== undefined) { - setPromptTemplateForm(prevPromptTemplateArguments); setIsHydrated(true); } else { setIsHydrated(false); @@ -75,40 +66,20 @@ const PromptTemplateCard = ({ const handleChange: ChangeEventHandler = (event) => { const { value, name } = event.target; - setPromptTemplateForm((prevForm) => ({ - ...prevForm, - [name]: sanitizeString(value), - })); - }; - - const handlePromptTemplateArgsSubmit: FormEventHandler = ( - event, - ) => { - event.preventDefault(); - const changeArgumentsRequest: ChangeArgumentsRequest = [ - { - name: "prompt_template", - data: promptTemplateForm, - }, - ]; - - changeArguments(changeArgumentsRequest); + onArgumentValueChange(name, sanitizeString(value)); }; - const changePromptTemplateBtnDisabled = - !isHydrated || - isInvalid || - (promptTemplateForm.user_prompt_template === - prevPromptTemplateArguments?.user_prompt_template && - promptTemplateForm.system_prompt_template === - prevPromptTemplateArguments?.system_prompt_template); - return ( - -
+ +

{error}

-
- +
); }; diff --git a/src/ui/apps/chatqna/src/features/chat/components/ChatHistoryList/ChatHistoryList.tsx b/src/ui/apps/chatqna/src/features/chat/components/ChatHistoryList/ChatHistoryList.tsx index 0b339fe8a..2a3a0582e 100644 --- a/src/ui/apps/chatqna/src/features/chat/components/ChatHistoryList/ChatHistoryList.tsx +++ b/src/ui/apps/chatqna/src/features/chat/components/ChatHistoryList/ChatHistoryList.tsx @@ -3,15 +3,35 @@ import "./ChatHistoryList.scss"; -import { LoadingFallback } from "@intel-enterprise-rag-ui/components"; +import { + LoadingFallback, + SearchBar, +} from "@intel-enterprise-rag-ui/components"; import classNames from "classnames"; +import { useMemo, useState } from "react"; import { useGetAllChatsQuery } from "@/features/chat/api/chatHistory"; import ChatHistoryItem from "@/features/chat/components/ChatHistoryItem/ChatHistoryItem"; const ChatHistoryList = () => { const { data, isLoading } = useGetAllChatsQuery(); - const isChatHistoryEmpty = !Array.isArray(data) || data.length === 0; + const [searchFilter, setSearchFilter] = useState(""); + + const filteredData = useMemo(() => { + if (!data || !Array.isArray(data)) return []; + if (!searchFilter.trim()) return data; + + const lowerSearchFilter = searchFilter.toLowerCase(); + return data.filter((item) => + item.name.toLowerCase().includes(lowerSearchFilter), + ); + }, [data, searchFilter]); + + const isChatHistoryEmpty = filteredData.length === 0; + + const emptyStateMessage = searchFilter.trim() + ? "No chat history matches your search." + : "No chat history available."; const chatHistoryListClass = classNames("chat-history-list", { "chat-history-list--empty": isChatHistoryEmpty, @@ -19,15 +39,23 @@ const ChatHistoryList = () => { return ( );