From c23688963091d5903291c83fb4c215ed7ddd3844 Mon Sep 17 00:00:00 2001 From: MiaAppel Date: Thu, 30 Oct 2025 17:37:20 +0100 Subject: [PATCH 01/61] FEAT: PAAL-151 Add Testworkflows --- testworkflows/pyproject.toml | 24 + testworkflows/scripts/evaluate.py | 206 ++ testworkflows/scripts/publish.py | 129 ++ testworkflows/scripts/run.py | 136 ++ testworkflows/scripts/setup.py | 103 + testworkflows/tests/test_e2e.py | 323 +++ testworkflows/uv.lock | 3352 +++++++++++++++++++++++++++++ 7 files changed, 4273 insertions(+) create mode 100644 testworkflows/pyproject.toml create mode 100644 testworkflows/scripts/evaluate.py create mode 100644 testworkflows/scripts/publish.py create mode 100644 testworkflows/scripts/run.py create mode 100644 testworkflows/scripts/setup.py create mode 100755 testworkflows/tests/test_e2e.py create mode 100644 testworkflows/uv.lock diff --git a/testworkflows/pyproject.toml b/testworkflows/pyproject.toml new file mode 100644 index 0000000..1c89a29 --- /dev/null +++ b/testworkflows/pyproject.toml @@ -0,0 +1,24 @@ +[project] +name = "test-bench" +version = "0.1.0" +description = "Testbench to evaluate agents using Ragas" +requires-python = ">=3.12" +dependencies = [ + "a2a>=0.44", + "a2a-sdk>=0.3.0", + "crefi>=2.0.9", + "httpx>=0.28.1", + "pandas>=2.3.3", + "pyarrow>=21.0.0", + "starlette>=0.48.0", + "utils>=1.0.2", + "wget>=3.2", + "opentelemetry-instrumentation-starlette>=0.56b0", + "ragas>=0.3.5", + "datasets>=2.14.0", + "prometheus-client>=0.19.0", + "pytest>=7.4.0", + "langchain-google-genai>=2.0.0", + "langchain-google-vertexai>=2.0.0", + "python-dotenv>=1.0.0", +] diff --git a/testworkflows/scripts/evaluate.py b/testworkflows/scripts/evaluate.py new file mode 100644 index 0000000..61c99f0 --- /dev/null +++ b/testworkflows/scripts/evaluate.py @@ -0,0 +1,206 @@ +import argparse +import inspect +import json +import logging +import os +from pydantic import BaseModel +from argparse import ArgumentError +from logging import Logger +from typing import Any +from dotenv import load_dotenv +from langchain_openai import ChatOpenAI +from ragas import evaluate, Experiment +from ragas.dataset_schema import EvaluationDataset, EvaluationResult +from ragas.llms import LangchainLLMWrapper +from ragas.metrics import Metric +import ragas.metrics as metrics_module +from langchain_google_genai import ChatGoogleGenerativeAI + + +def get_available_metrics() -> dict[str, Metric]: + """ + Loads all Metric classes from Ragas + Returns a dict mapping metric names to metric instances. + """ + available_metrics: dict[str, Metric] = {} + + # Iterate through all members of the metrics module + for name, obj in inspect.getmembers(metrics_module): + # Check if it's a class and is a subclass of Metric (but not Metric itself) + if inspect.isclass(obj) and issubclass(obj, Metric) and obj is not Metric: + try: + # Instantiate the metric + metric_instance = obj() + # Use the metric's name attribute + metric_name = metric_instance.name + available_metrics[metric_name] = metric_instance + except Exception: + # Skip metrics that can't be instantiated without parameters + pass + + return available_metrics + + +# Get all available metrics +AVAILABLE_METRICS = get_available_metrics() + + +def calculate_metrics(dataset: EvaluationDataset, metrics: list[str], llm: Any) -> dict[str, Any]: + """ + Calculate RAGAS metrics on the dataset. + + Args: + dataset: Ragas EvaluationDataset + metrics: List of metric names as strings (e.g., ["faithfulness", "answer_relevancy"]) + llm: Language model for evaluation + + Returns: + Dictionary containing evaluation results + """ + + # Map metric names to actual metric objects + metric_objects = [] + for metric_name in metrics: + if metric_name in AVAILABLE_METRICS: + metric_objects.append(AVAILABLE_METRICS[metric_name]) + else: + logger.warning(f"Unknown metric '{metric_name}', skipping...") + logger.warning(f"Available metrics: {', '.join(AVAILABLE_METRICS.keys())}") + + if not metric_objects: + raise ValueError("No valid metrics provided for evaluation") + + # Run RAGAS evaluation + result = evaluate( + dataset=dataset, + metrics=metric_objects, + llm=llm, + ) + + return result + + +def format_evaluation_scores( + ragas_result: EvaluationResult, + metrics: list[str] +) -> dict[str, Any]: + + """ + Format the RAGAS evaluation results. + + Args: + ragas_result: The result object from RAGAS evaluate() + experiment: Ragas Experiment containing the original results + metrics: List of metric names used + + Returns: + Formatted dictionary matching the required structure + """ + + # Get the pandas DataFrame from RAGAS result + df = ragas_result.to_pandas() + + # Calculate overall scores (mean of each metric) + overall_scores = {} + for metric in metrics: + if metric in df.columns: + overall_scores[metric] = float(df[metric].mean()) + + # Build individual results + individual_results = ragas_result.to_pandas().to_dict(orient="records") + + # Ragas doesn't have TokenUsageParser for Google Gemini - setting placeholders instead + total_tokens = { + "input_tokens": 0, + "output_tokens": 0 + } + total_cost = 0.0 + + + return { + "overall_scores": overall_scores, + "individual_results": individual_results, + "total_tokens": total_tokens, + "total_cost": total_cost + } + + +def main( + output_file: str, + model: str, + metrics: list[str] = None +) -> None: + """ + Main function to evaluate results using RAGAS metrics. + + Args: + output_file: Path to save evaluation_scores.json + model: Model name to use for evaluation + metrics: List of metric names to calculate + """ + + ragas_llm = ChatOpenAI( + model=model + ) + llm = LangchainLLMWrapper(ragas_llm) + + dataset = EvaluationDataset.from_jsonl('data/experiments/ragas_experiment.jsonl') + + # Calculate metrics + logger.info(f"Calculating metrics: {', '.join(metrics)}...") + ragas_result = calculate_metrics(dataset, metrics, llm) + + # Format results + logger.info("Formatting evaluation scores...") + evaluation_scores = format_evaluation_scores(ragas_result, metrics) + + # Ensure output directory exists + os.makedirs(os.path.dirname(output_file), exist_ok=True) + + # Save to file + with open(output_file, 'w') as f: + json.dump(evaluation_scores, f, indent=2) + + logger.info(f"Evaluation scores saved to {output_file}") + logger.info(f"Overall scores: {evaluation_scores['overall_scores']}") + + +if __name__ == "__main__": + # Set up logger & get logger instance + logging.basicConfig(level=logging.INFO) + logger: Logger = logging.getLogger(__name__) + + # Parse the parameters (model and metrics) evaluate.py was called with + parser = argparse.ArgumentParser( + description = "Evaluate results using RAGAS metrics", + formatter_class = argparse.RawDescriptionHelpFormatter, + epilog=f""" + Available metrics: {', '.join(AVAILABLE_METRICS.keys())} + + Examples: + python3 scripts/evaluate.py gemini-flash-latest faithfulness + python3 scripts/evaluate.py gemini-flash-latest faithfulness context_precision context_recall + """ + ) + + parser.add_argument( + 'model', + type = str, + help = 'Model name to use for evaluation (e.g., gemini-flash-latest)' + ) + + parser.add_argument( + 'metrics', + nargs = '+', + choices = list(AVAILABLE_METRICS.keys()), + help = 'At least one (or more) metrics to evaluate (e.g., faithfulness, answer_relevancy)' + ) + + args = parser.parse_args() + + # Run evaluation with the 'model' and 'metrics' provided as parameters, 'output_file' is hardcoded + main( + output_file = "results/evaluation_scores.json", + model = args.model, + metrics = args.metrics + ) diff --git a/testworkflows/scripts/publish.py b/testworkflows/scripts/publish.py new file mode 100644 index 0000000..a9cceed --- /dev/null +++ b/testworkflows/scripts/publish.py @@ -0,0 +1,129 @@ +import argparse +import json +import logging +from logging import Logger +from typing import Any +from prometheus_client import CollectorRegistry, Gauge, push_to_gateway + + +def get_overall_scores(file_path: str) -> dict[str, Any]: + """Load the evaluation_scores.json file and return the 'overall_scores' metrics.""" + with open(file_path, 'r') as file: + return json.load(file).get("overall_scores", {}) + + +def create_and_push_metrics( + overall_scores: dict[str, float], + workflow_name: str, + pushgateway_url: str +) -> None: + """ + Create Prometheus Gauge metrics for each overall score and push to Pushgateway. + + Args: + overall_scores: Dictionary of metric names to scores + workflow_name: Name of the test workflow (used as label to distinguish workflows) + pushgateway_url: URL of the Prometheus Pushgateway + """ + # Create a new registry for this push + registry: CollectorRegistry = CollectorRegistry() + + for metric_name, score in overall_scores.items(): + # Create a Gauge with workflow_name as a label + gauge = Gauge( + f'ragas_evaluation_{metric_name}', + f'Overall {metric_name} score from RAGAS evaluation', + labelnames = ['workflow_name'], + registry = registry + ) + + # Set the gauge value with the workflow_name label + gauge.labels(workflow_name=workflow_name).set(score) + logger.info(f"Set metric 'evaluation_{metric_name}{{workflow_name=\"{workflow_name}\"}}' to {score}") + + + # Push metrics to Pushgateway + try: + logger.info(f"Pushing metrics to Pushgateway at {pushgateway_url}...") + push_to_gateway( + pushgateway_url, + job = 'ragas_evaluation', + registry = registry + ) + logger.info("✓ Metrics successfully pushed to Pushgateway") + except Exception as e: + logger.error(f"✗ Error pushing metrics to Pushgateway: {e}") + raise + + +def publish_metrics( + input_file: str, + workflow_name: str | None = None, + pushgateway_url: str | None = None +) -> None: + """ + Publish evaluation metrics to Prometheus Pushgateway. + + Args: + input_file: Path to the evaluation scores + workflow_name: Name of the test workflow (e.g., 'weather-assistant-test'). + pushgateway_url: URL of Prometheus Pushgateway (e.g., 'localhost:9091'). + """ + + # Load overall scores from the evaluation file + logger.info(f"Loading evaluation scores from {input_file}...") + overall_scores = get_overall_scores(input_file) + + if not overall_scores: + logger.warning("No overall scores found in evaluation_scores.json") + return + + # Create and push Prometheus metrics + logger.info(f"Creating Prometheus metrics for {len(overall_scores)} scores...") + logger.info(f"Workflow: {workflow_name}") + create_and_push_metrics(overall_scores, workflow_name, pushgateway_url) + + logger.info("Published metrics:") + for metric_name, score in overall_scores.items(): + logger.info(f" - ragas_evaluation_{metric_name}{{workflow_name=\"{workflow_name}\"}}: {score}") + + +if __name__ == "__main__": + """ + Main function to publish Prometheus metrics to Prometheus Pushgateway. + + Args: + workflow_name: Name of the test workflow + pushgateway_url: (OPTIONAL) URL to the Prometheus Pushgateway (default: localhost:9091) + + Examples: + python3 scripts/publish.py weather-assistant-test + python3 scripts/publish.py weather-assistant-test pushgateway-url.com + """ + + # Set up logger & get logger instance + logging.basicConfig(level=logging.INFO) + logger: Logger = logging.getLogger(__name__) + + parser = argparse.ArgumentParser( + description = "Publish RAGAS evaluation metrics to Prometheus Pushgateway" + ) + parser.add_argument( + "workflow_name", + help = "Name of the test workflow (e.g., 'weather-assistant-test')" + ) + parser.add_argument( + "pushgateway_url", + nargs = "?", + default = "localhost:9091", + help = "URL of Prometheus Pushgateway (default: localhost:9091)" + ) + + args = parser.parse_args() + + # Call 'publish_metrics' with hardcoded input file and specified 'workflow_name' & 'pushgateway_url' + publish_metrics( + input_file = "results/evaluation_scores.json", + workflow_name = args.workflow_name, + pushgateway_url = args.pushgateway_url + ) diff --git a/testworkflows/scripts/run.py b/testworkflows/scripts/run.py new file mode 100644 index 0000000..bb4226e --- /dev/null +++ b/testworkflows/scripts/run.py @@ -0,0 +1,136 @@ +import asyncio +import argparse +import httpx +import json + +import logging +from logging import Logger + +from uuid import uuid4 + +from pydantic import BaseModel +from ragas import Dataset, experiment, Experiment + +from a2a.client.client_factory import ClientFactory, minimal_agent_card +from a2a.client.client import ClientConfig, Client + +from a2a.types import ( + Message, AgentCard, +) + +async def initialize_client(agent_url: str, httpx_client: httpx.AsyncClient, logger: Logger) -> Client: + """Initialize the A2A client with a minimal agent card.""" + logger.info(f'Initializing A2A client for: {agent_url}') + + # Create a minimal agent card with the provided URL + agent_card: AgentCard = minimal_agent_card(agent_url) + + config: ClientConfig = ClientConfig(httpx_client=httpx_client) + factory: ClientFactory = ClientFactory(config) + client: Client = factory.create(agent_card) + + logger.info('A2A client initialized successfully') + + return client + + +@experiment() +async def run_agent_experiment(row, agent_url: str) -> dict[str, str | list | list]: + """ + Experiment function that processes each row from the dataset. + + Args: + row: A dictionary containing 'user_input', 'retrieved_contexts', and 'reference' fields + agent_url: The URL of the agent to query + + Returns: + Dictionary with original row data plus 'response' + """ + logger: Logger = logging.getLogger(__name__) + + output_text: str = "" + + try: + async with httpx.AsyncClient() as httpx_client: + client = await initialize_client(agent_url, httpx_client, logger) + + # Get the input from the row + input_text = row.get("user_input") + + message = Message( + role='user', + parts=[ + { + 'kind': 'text', + 'text': input_text + } + ], + messageId = uuid4().hex + ) + + logger.info(f'Processing: {input_text}') + + async for response in client.send_message(message): + # Client returns tuples, extract the task/message + if isinstance(response, tuple): + task, _ = response + if task: + artifacts: list = task.model_dump(mode='json', include={'artifacts'}).get('artifacts',[]) + history: list = task.model_dump(mode='json', include={'history'}).get('history',[]) + + # Extract the model response + if artifacts and artifacts[0].get('parts'): + output_text = artifacts[0]['parts'][0].get('text', '') + else: + logger.warning("No text found in artifacts") + + elif hasattr(response, 'model_dump'): + logger.debug(response.model_dump(mode='json', exclude_none=True)) + else: + logger.warning(f'Unexpected response: {response}') + + except Exception as e: + logger.error(f'Error processing input "{row.get("user_input")}": {str(e)}') + output_text = f"ERROR: {str(e)}" + + # Return the original row data plus the results + result: dict[str, str | list] = { + **row, + "response": output_text, + } + + return result + + +async def main(agent_url: str) -> None: + """Main function to load Ragas Dataset and run Experiment.""" + + # Set up logger & get logger instance + logging.basicConfig(level=logging.INFO) + logger: Logger = logging.getLogger(__name__) + + # Load existing Ragas dataset + logger.info('Loading Ragas dataset from data/datasets/ragas_dataset.jsonl') + dataset: Dataset[BaseModel] = Dataset.load(name="ragas_dataset", backend="local/jsonl", root_dir="./data") + logger.info(f'Dataset loaded with {len(dataset)} samples') + + # Run the experiment + logger.info('Starting experiment...') + results: Experiment = await run_agent_experiment.arun( + dataset, + name = "ragas_experiment", + agent_url = agent_url + ) + + logger.info('Experiment completed successfully') + logger.info(f'Results saved to data/experiments/ragas_experiment.jsonl') + + +if __name__ == '__main__': + # Parse parameter the script was called with (URL) + parser = argparse.ArgumentParser(description="Runs all queries from the Ragas dataset through the agent at the provided URL") + parser.add_argument('url', help='URL to agent') + args = parser.parse_args() + + # Call main using the parsed URL + asyncio.run(main(args.url)) \ No newline at end of file diff --git a/testworkflows/scripts/setup.py b/testworkflows/scripts/setup.py new file mode 100644 index 0000000..d11357a --- /dev/null +++ b/testworkflows/scripts/setup.py @@ -0,0 +1,103 @@ +import argparse +import requests + +from pathlib import Path +from typing import Callable +from io import BytesIO + +import pandas as pd +from pandas import DataFrame +from pydantic import BaseModel +from ragas import Dataset + +def dataframe_to_ragas_dataset(dataframe: DataFrame) -> None: + """Convert DataFrame to Ragas dataset and save to data/ragas_dataset.jsonl. + + Expected schema: + - user_input: The test question/prompt + - retrieved_contexts: List of retrieved context strings + - reference: The reference/ground truth answer + """ + + # Set output directory (and create it if it doesn't exist already) + output_dir = Path('data') + output_dir.mkdir(exist_ok=True) + + # Convert DataFrame to list of dictionaries + dataset_samples = dataframe.to_dict(orient="records") + + # Create Ragas Dataset + dataset: Dataset[BaseModel] = Dataset(name="ragas_dataset", backend="local/jsonl", root_dir="./data") + + # Append all samples to the dataset + for sample in dataset_samples: + dataset.append(sample) + + # Save the dataset + dataset.save() + + +def get_converter(url: str) -> Callable[[BytesIO], DataFrame]: + """Extract the file format from the URL and return the converter function""" + suffix = Path(url).suffix.lower() + + format_map = { + '.json': pd.read_json, + '.csv': custom_convert_csv, + '.parquet': pd.read_parquet, + '.prq': pd.read_parquet, + } + + if suffix in format_map: + return format_map[suffix] + + raise TypeError(f"Unsupported filetype at url: {url}") + +def custom_convert_csv(input_file: BytesIO) -> DataFrame: + """ + Converts a CSV input file to a Pandas DataFrame and, if it exists, turns 'retrieved_contexts' into a list (RAGAS requires 'retrieved_contexts' as a list of strings) + + Args: + input_file: The CSV input_file + + Returns: + Pandas DataFrame with correct formatting + """ + + dataframe: DataFrame = pd.read_csv(input_file) + + # Ensure retrieved_contexts is a list (convert string to list if needed) + if 'retrieved_contexts' in dataframe: + dataframe['retrieved_contexts'] = dataframe['retrieved_contexts'].apply( + lambda x: x if isinstance(x, list) else [x] if x else [] + ) + + return dataframe + + +def main(url : str) -> None: + """Download provided dataset -> convert to Ragas dataset -> save to data/ragas_dataset.jsonl + + Source dataset must contain columns: user_input, retrieved_contexts, reference + """ + converter = get_converter(url) + + # Download file from URL and raise HTTP error if it occurs + file = requests.get(url) + file.raise_for_status() + + # Load into DataFrame by using the correct converter + buffer = BytesIO(file.content) + dataframe = converter(buffer) + + # Convert DataFrame to Ragas dataset and save it + dataframe_to_ragas_dataset(dataframe) + +if __name__ == '__main__': + # Parse parameter the script was called with (URL) + parser = argparse.ArgumentParser(description="Download provided dataset -> convert to Ragas dataset -> save to data/datasets/ragas_dataset.jsonl") + parser.add_argument('url', help='URL to the dataset in .csv / .json / .parquet format (must have user_input, retrieved_contexts, and reference columns)') + args = parser.parse_args() + + # Call main using the parsed URL + main(args.url) diff --git a/testworkflows/tests/test_e2e.py b/testworkflows/tests/test_e2e.py new file mode 100755 index 0000000..8f6c550 --- /dev/null +++ b/testworkflows/tests/test_e2e.py @@ -0,0 +1,323 @@ +""" +End-to-end test script that runs all scripts in the correct order: +1. setup.py - Downloads, converts and saves Ragas Dataset to data/datasets/ragas_dataset.jsonl +2. run.py - Runs agent queries on the dataset and saves Ragas Experiment to data/experiments/ragas_experiment.jsonl +3. evaluate.py - Evaluates results using RAGAS metrics and saves result to results/evaluation_scores.json +4. publish.py - Publishes metrics to Prometheus Pushgateway + +Usage: + python test_e2e.py --dataset-url --agent-url --model \ + --metrics [METRIC2 ...] --workflow-name \ + [--pushgateway-url ] + +Example: + python test_e2e.py \ + --dataset-url "https://example.com/dataset.csv" \ + --agent-url "http://localhost:8000" \ + --model "gemini-flash-latest" \ + --metrics faithfulness answer_relevancy \ + --workflow-name "weather-assistant-test" +""" + +import argparse +import subprocess +import sys +import logging +from pathlib import Path +from typing import List + +# Set up logging +logging.basicConfig( + level=logging.INFO, + format='%(asctime)s - %(levelname)s - %(message)s' +) +logger = logging.getLogger(__name__) + + +class E2ETestRunner: + """Manages the end-to-end test execution pipeline.""" + + def __init__( + self, + dataset_url: str, + agent_url: str, + model: str, + metrics: List[str], + workflow_name: str, + pushgateway_url: str = "localhost:9091" + ): + self.dataset_url = dataset_url + self.agent_url = agent_url + self.model = model + self.metrics = metrics + self.workflow_name = workflow_name + self.pushgateway_url = pushgateway_url + + # Define script paths + self.scripts_dir = Path(__file__).parent.parent / "scripts" + self.setup_script = self.scripts_dir / "setup.py" + self.run_script = self.scripts_dir / "run.py" + self.evaluate_script = self.scripts_dir / "evaluate.py" + self.publish_script = self.scripts_dir / "publish.py" + + # Define expected output files + self.dataset_file = Path("./data/datasets/ragas_dataset.jsonl") + self.results_file = Path("./data/experiments/ragas_experiment.jsonl") + self.evaluation_file = Path("./results/evaluation_scores.json") + + + def verify_scripts_exist(self) -> bool: + """Verify that all required scripts exist.""" + logger.info("Verifying all scripts exist...") + scripts = [ + self.setup_script, + self.run_script, + self.evaluate_script, + self.publish_script + ] + + missing_scripts = [script for script in scripts if not script.exists()] + + if missing_scripts: + logger.error("Missing scripts:") + for script in missing_scripts: + logger.error(f" - {script}") + return False + + logger.info("✓ All scripts found") + return True + + + def run_command(self, command: List[str], step_name: str) -> bool: + """ + Run a command and handle output/errors. + + Args: + command: List of command arguments + step_name: Name of the step for logging + + Returns: + True if successful, False otherwise + """ + logger.info(f"\n{'='*60}") + logger.info(f"Step: {step_name}") + logger.info(f"Command: {' '.join(command)}") + logger.info(f"{'='*60}\n") + + try: + result = subprocess.run( + command, + check=True, + capture_output=True, + text=True + ) + + # Log stdout if present + if result.stdout: + logger.info("Output:") + for line in result.stdout.strip().split('\n'): + logger.info(f" {line}") + + logger.info(f"✓ {step_name} completed successfully\n") + return True + + except subprocess.CalledProcessError as e: + logger.error(f"✗ {step_name} failed with exit code {e.returncode}") + + if e.stdout: + logger.error("Standard output:") + for line in e.stdout.strip().split('\n'): + logger.error(f" {line}") + + if e.stderr: + logger.error("Error output:") + for line in e.stderr.strip().split('\n'): + logger.error(f" {line}") + + return False + + except Exception as e: + logger.error(f"✗ Unexpected error in {step_name}: {e}") + return False + + + def verify_file_exists(self, file_path: Path, step_name: str) -> bool: + """Verify that an expected output file was created.""" + if file_path.exists(): + logger.info(f"✓ Verified {file_path} was created by {step_name}") + return True + else: + logger.error(f"✗ Expected file {file_path} not found after {step_name}") + return False + + + def run_setup(self) -> bool: + """Run setup.py to download and convert dataset.""" + command = ["python3", str(self.setup_script), self.dataset_url] + success = self.run_command(command, "1. Setup - Download Dataset") + + if success: + return self.verify_file_exists(self.dataset_file, "setup.py") + return False + + + def run_agent_queries(self) -> bool: + """Run run.py to execute agent queries on the dataset.""" + command = ["python3", str(self.run_script), self.agent_url] + success = self.run_command(command, "2. Run - Execute Agent Queries") + + if success: + return self.verify_file_exists(self.results_file, "run.py") + return False + + + def run_evaluation(self) -> bool: + """Run evaluate.py to evaluate results using RAGAS metrics.""" + command = [ + "python3", + str(self.evaluate_script), + self.model, + *self.metrics + ] + success = self.run_command(command, "3. Evaluate - Calculate RAGAS Metrics") + + if success: + return self.verify_file_exists(self.evaluation_file, "evaluate.py") + return False + + + def run_publish(self) -> bool: + """Run publish.py to publish metrics to Prometheus Pushgateway.""" + command = [ + "python3", + str(self.publish_script), + self.workflow_name, + self.pushgateway_url + ] + return self.run_command(command, "4. Publish - Push Metrics to Prometheus") + + + def run_full_pipeline(self) -> bool: + """Execute the complete E2E test pipeline.""" + logger.info("\n" + "="*60) + logger.info("Starting E2E Test Pipeline") + logger.info("="*60 + "\n") + + # Verify all scripts exist before starting + if not self.verify_scripts_exist(): + logger.error("Cannot proceed - missing required scripts") + return False + + # Run each step in order + steps = [ + ("Setup", self.run_setup), + ("Run", self.run_agent_queries), + ("Evaluate", self.run_evaluation), + ("Publish", self.run_publish) + ] + + for step_name, step_func in steps: + if not step_func(): + logger.error(f"\n{'='*60}") + logger.error(f"E2E Test FAILED at step: {step_name}") + logger.error(f"{'='*60}\n") + return False + + # All steps completed successfully + logger.info("\n" + "="*60) + logger.info("E2E Test Pipeline COMPLETED SUCCESSFULLY") + logger.info("="*60 + "\n") + + logger.info("Summary:") + logger.info(f" ✓ Ragas Dataset created: {self.dataset_file}") + logger.info(f" ✓ Ragas Experiment saved: {self.results_file}") + logger.info(f" ✓ Evaluation completed: {self.evaluation_file}") + logger.info(f" ✓ Metrics published to: {self.pushgateway_url}") + logger.info(f" ✓ Workflow name: {self.workflow_name}") + + return True + + +def main(): + """Parse arguments and run the E2E test""" + parser = argparse.ArgumentParser( + description = "End-to-end test runner for the agent testing pipeline", + formatter_class = argparse.RawDescriptionHelpFormatter, + epilog=""" + Examples: + # Basic usage + python test_e2e.py \\ + --dataset-url "https://example.com/data.csv" \\ + --agent-url "http://localhost:8000" \\ + --model "gemini-flash-latest" \\ + --metrics faithfulness answer_relevancy \\ + --workflow-name "my-test" + + # With custom Pushgateway URL + python test_e2e.py \\ + --dataset-url "https://example.com/data.csv" \\ + --agent-url "http://localhost:8000" \\ + --model "gemini-flash-latest" \\ + --metrics faithfulness \\ + --workflow-name "my-test" \\ + --pushgateway-url "pushgateway.example.com:9091" + """ + ) + + parser.add_argument( + "--dataset-url", + required=True, + help="URL to the dataset in .csv / .json / .parquet format" + ) + + parser.add_argument( + "--agent-url", + required=True, + help="URL to agent" + ) + + parser.add_argument( + "--model", + required=True, + help="Model name to use for evaluation (e.g., gemini-flash-latest)" + ) + + parser.add_argument( + "--metrics", + nargs="+", + required=True, + help="At least one (or more) metrics to evaluate (e.g., faithfulness, answer_relevancy)" + ) + + parser.add_argument( + "--workflow-name", + required=True, + help="Name of the test workflow (e.g., 'weather-assistant-test')" + ) + + parser.add_argument( + "--pushgateway-url", + default="localhost:9091", + help="URL of Prometheus Pushgateway (default: localhost:9091)" + ) + + args = parser.parse_args() + + # Create and run the test pipeline + runner = E2ETestRunner( + 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upload-time = "2025-09-14T22:18:19.088Z" }, +] From 203f302aa8494522da143c1ed145795e90996a95 Mon Sep 17 00:00:00 2001 From: MiaAppel Date: Fri, 31 Oct 2025 10:20:30 +0100 Subject: [PATCH 02/61] FEAT: Add unit tests & test datasets FIX: Create module level logger in evaluate.py run.py and publish.py --- testworkflows/scripts/evaluate.py | 9 +- testworkflows/scripts/publish.py | 12 +- testworkflows/scripts/run.py | 10 +- testworkflows/tests/test_data/dataset.csv | 6 + testworkflows/tests/test_data/dataset.json | 27 ++ testworkflows/tests/test_evaluate.py | 321 ++++++++++++++++++ testworkflows/tests/test_publish.py | 371 +++++++++++++++++++++ testworkflows/tests/test_run.py | 222 ++++++++++++ testworkflows/tests/test_setup.py | 301 +++++++++++++++++ 9 files changed, 1263 insertions(+), 16 deletions(-) create mode 100644 testworkflows/tests/test_data/dataset.csv create mode 100644 testworkflows/tests/test_data/dataset.json create mode 100644 testworkflows/tests/test_evaluate.py create mode 100644 testworkflows/tests/test_publish.py create mode 100644 testworkflows/tests/test_run.py create mode 100644 testworkflows/tests/test_setup.py diff --git a/testworkflows/scripts/evaluate.py b/testworkflows/scripts/evaluate.py index 61c99f0..cc55926 100644 --- a/testworkflows/scripts/evaluate.py +++ b/testworkflows/scripts/evaluate.py @@ -16,6 +16,10 @@ import ragas.metrics as metrics_module from langchain_google_genai import ChatGoogleGenerativeAI +# Set up module-level logger +logging.basicConfig(level=logging.INFO) +logger: Logger = logging.getLogger(__name__) + def get_available_metrics() -> dict[str, Metric]: """ @@ -139,6 +143,7 @@ def main( metrics: List of metric names to calculate """ + # Create LLM client using the proxy ragas_llm = ChatOpenAI( model=model ) @@ -166,10 +171,6 @@ def main( if __name__ == "__main__": - # Set up logger & get logger instance - logging.basicConfig(level=logging.INFO) - logger: Logger = logging.getLogger(__name__) - # Parse the parameters (model and metrics) evaluate.py was called with parser = argparse.ArgumentParser( description = "Evaluate results using RAGAS metrics", diff --git a/testworkflows/scripts/publish.py b/testworkflows/scripts/publish.py index a9cceed..0f7cca6 100644 --- a/testworkflows/scripts/publish.py +++ b/testworkflows/scripts/publish.py @@ -5,6 +5,10 @@ from typing import Any from prometheus_client import CollectorRegistry, Gauge, push_to_gateway +# Set up module-level logger +logging.basicConfig(level=logging.INFO) +logger: Logger = logging.getLogger(__name__) + def get_overall_scores(file_path: str) -> dict[str, Any]: """Load the evaluation_scores.json file and return the 'overall_scores' metrics.""" @@ -90,21 +94,17 @@ def publish_metrics( if __name__ == "__main__": """ - Main function to publish Prometheus metrics to Prometheus Pushgateway. + Main function to publish Prometheus metrics to Prometheus Pushgateway. Args: workflow_name: Name of the test workflow pushgateway_url: (OPTIONAL) URL to the Prometheus Pushgateway (default: localhost:9091) Examples: - python3 scripts/publish.py weather-assistant-test + python3 scripts/publish.py weather-assistant-test python3 scripts/publish.py weather-assistant-test pushgateway-url.com """ - # Set up logger & get logger instance - logging.basicConfig(level=logging.INFO) - logger: Logger = logging.getLogger(__name__) - parser = argparse.ArgumentParser( description = "Publish RAGAS evaluation metrics to Prometheus Pushgateway" ) diff --git a/testworkflows/scripts/run.py b/testworkflows/scripts/run.py index bb4226e..2ef0023 100644 --- a/testworkflows/scripts/run.py +++ b/testworkflows/scripts/run.py @@ -18,6 +18,10 @@ Message, AgentCard, ) +# Set up module-level logger +logging.basicConfig(level=logging.INFO) +logger: Logger = logging.getLogger(__name__) + async def initialize_client(agent_url: str, httpx_client: httpx.AsyncClient, logger: Logger) -> Client: """Initialize the A2A client with a minimal agent card.""" logger.info(f'Initializing A2A client for: {agent_url}') @@ -46,8 +50,6 @@ async def run_agent_experiment(row, agent_url: str) -> dict[str, str | list | li Returns: Dictionary with original row data plus 'response' """ - logger: Logger = logging.getLogger(__name__) - output_text: str = "" try: @@ -105,10 +107,6 @@ async def run_agent_experiment(row, agent_url: str) -> dict[str, str | list | li async def main(agent_url: str) -> None: """Main function to load Ragas Dataset and run Experiment.""" - # Set up logger & get logger instance - logging.basicConfig(level=logging.INFO) - logger: Logger = logging.getLogger(__name__) - # Load existing Ragas dataset logger.info('Loading Ragas dataset from data/datasets/ragas_dataset.jsonl') dataset: Dataset[BaseModel] = Dataset.load(name="ragas_dataset", backend="local/jsonl", root_dir="./data") diff --git a/testworkflows/tests/test_data/dataset.csv b/testworkflows/tests/test_data/dataset.csv new file mode 100644 index 0000000..506b15a --- /dev/null +++ b/testworkflows/tests/test_data/dataset.csv @@ -0,0 +1,6 @@ +user_input,retrieved_contexts,reference +"What is the weather like in New York right now?","The answer must state the current temperature in New York, specify the units (Celsius or Fahrenheit), and describe the current weather condition (e.g., Sunny, Cloudy, Rain).","The answer must state the current temperature in New York, specify the units (Celsius or Fahrenheit), and describe the current weather condition (e.g., Sunny, Cloudy, Rain)." +"What is the current time in New York?","The answer must state the current time in New York in HH:MM format and include the correct timezone abbreviation (e.g., CST).","The answer must state the current time in New York in HH:MM format and include the correct timezone abbreviation (e.g., CST)." +"What is the weather like in Cairo?","The answer must state the current temperature in Cairo, specify the units (Celsius or Fahrenheit), and describe the current weather condition (e.g., Sunny, Cloudy, Rain).","The answer must state the current temperature in Cairo, specify the units (Celsius or Fahrenheit), and describe the current weather condition (e.g., Sunny, Cloudy, Rain)." +"How is the weather in Sydney?","The answer must state the current temperature in Sydney, specify the units (Celsius or Fahrenheit), and describe the current weather condition (e.g., Sunny, Cloudy, Rain).","The answer must state the current temperature in Sydney, specify the units (Celsius or Fahrenheit), and describe the current weather condition (e.g., Sunny, Cloudy, Rain)." +"Time in Garching?","The answer must state the current time in Garching, Germany in HH:MM format and include the correct timezone abbreviation (CEST).","The answer must state the current time in Garching, Germany in HH:MM format and include the correct timezone abbreviation (CEST)." diff --git a/testworkflows/tests/test_data/dataset.json b/testworkflows/tests/test_data/dataset.json new file mode 100644 index 0000000..1d6f88d --- /dev/null +++ b/testworkflows/tests/test_data/dataset.json @@ -0,0 +1,27 @@ +[ + { + "user_input": "What is the weather like in New York right now?", + "retrieved_contexts": ["The answer must state the current temperature in New York, specify the units (Celsius or Fahrenheit), and describe the current weather condition (e.g., Sunny, Cloudy, Rain)."], + "reference": "The answer must state the current temperature in New York, specify the units (Celsius or Fahrenheit), and describe the current weather condition (e.g., Sunny, Cloudy, Rain)." + }, + { + "user_input": "What is the current time in New York?", + "retrieved_contexts": ["The answer must state the current time in New York in HH:MM format and include the correct timezone abbreviation (e.g., CST)."], + "reference": "The answer must state the current time in New York in HH:MM format and include the correct timezone abbreviation (e.g., CST)." + }, + { + "user_input": "What is the weather like in Cairo?", + "retrieved_contexts": ["The answer must state the current temperature in Cairo, specify the units (Celsius or Fahrenheit), and describe the current weather condition (e.g., Sunny, Cloudy, Rain)."], + "reference": "The answer must state the current temperature in Cairo, specify the units (Celsius or Fahrenheit), and describe the current weather condition (e.g., Sunny, Cloudy, Rain)." + }, + { + "user_input": "How is the weather in Sydney?", + "retrieved_contexts": ["The answer must state the current temperature in Sydney, specify the units (Celsius or Fahrenheit), and describe the current weather condition (e.g., Sunny, Cloudy, Rain)."], + "reference": "The answer must state the current temperature in Sydney, specify the units (Celsius or Fahrenheit), and describe the current weather condition (e.g., Sunny, Cloudy, Rain)." + }, + { + "user_input": "Time in Garching?", + "retrieved_contexts": ["The answer must state the current time in Garching, Germany in HH:MM format and include the correct timezone abbreviation (CEST)."], + "reference": "The answer must state the current time in Garching, Germany in HH:MM format and include the correct timezone abbreviation (CEST)." + } +] diff --git a/testworkflows/tests/test_evaluate.py b/testworkflows/tests/test_evaluate.py new file mode 100644 index 0000000..f3355d2 --- /dev/null +++ b/testworkflows/tests/test_evaluate.py @@ -0,0 +1,321 @@ +""" +Unit tests for evaluate.py + +Tests the RAGAS evaluation functionality. +""" + +import unittest +import tempfile +import shutil +import json +from pathlib import Path +from unittest.mock import patch, MagicMock + +from ragas.dataset_schema import EvaluationDataset, EvaluationResult +import pandas as pd + +import sys +sys.path.insert(0, str(Path(__file__).parent.parent / "scripts")) + +from evaluate import ( + get_available_metrics, + calculate_metrics, + format_evaluation_scores, + main, + AVAILABLE_METRICS +) + + +class TestGetAvailableMetrics(unittest.TestCase): + """Test the get_available_metrics function""" + + def test_returns_dict(self): + """Test that get_available_metrics returns a dictionary""" + metrics = get_available_metrics() + self.assertIsInstance(metrics, dict) + + def test_contains_common_metrics(self): + """Test that common metrics are available""" + metrics = get_available_metrics() + + # Check for some common metrics + common_metrics = ['faithfulness', 'answer_relevancy'] + + for metric in common_metrics: + if metric in metrics: + self.assertIn(metric, metrics) + + def test_metric_instances_have_name(self): + """Test that metric instances have a name attribute""" + metrics = get_available_metrics() + + for metric_name, metric_instance in metrics.items(): + self.assertTrue(hasattr(metric_instance, 'name')) + + +class TestCalculateMetrics(unittest.TestCase): + """Test the calculate_metrics function""" + + def setUp(self): + """Set up test data""" + # Create a mock dataset + self.test_data = [ + { + 'user_input': 'What is the capital of France?', + 'retrieved_contexts': ['Paris is the capital of France.'], + 'reference': 'Paris', + 'response': 'The capital of France is Paris.' + } + ] + + @patch('evaluate.evaluate') + def test_calculate_metrics_calls_evaluate(self, mock_evaluate): + """Test that calculate_metrics calls RAGAS evaluate""" + # Create mock dataset + mock_dataset = MagicMock(spec=EvaluationDataset) + + # Create mock LLM + mock_llm = MagicMock() + + # Mock evaluate return value + mock_result = MagicMock(spec=EvaluationResult) + mock_evaluate.return_value = mock_result + + # Call calculate_metrics + metrics = ['faithfulness'] + result = calculate_metrics(mock_dataset, metrics, mock_llm) + + # Verify evaluate was called + mock_evaluate.assert_called_once() + self.assertEqual(result, mock_result) + + @patch('evaluate.evaluate') + def test_calculate_metrics_with_multiple_metrics(self, mock_evaluate): + """Test calculate_metrics with multiple metrics""" + mock_dataset = MagicMock(spec=EvaluationDataset) + mock_llm = MagicMock() + mock_result = MagicMock(spec=EvaluationResult) + mock_evaluate.return_value = mock_result + + # Call with multiple metrics + metrics = ['faithfulness', 'answer_relevancy'] + result = calculate_metrics(mock_dataset, metrics, mock_llm) + + # Verify evaluate was called + mock_evaluate.assert_called_once() + + def test_calculate_metrics_with_invalid_metric(self): + """Test calculate_metrics with invalid metric name""" + mock_dataset = MagicMock(spec=EvaluationDataset) + mock_llm = MagicMock() + + # Call with invalid metric - this should raise ValueError + metrics = ['nonexistent_metric'] + + with self.assertRaises(ValueError) as context: + calculate_metrics(mock_dataset, metrics, mock_llm) + + self.assertIn('No valid metrics', str(context.exception)) + + +class TestFormatEvaluationScores(unittest.TestCase): + """Test the format_evaluation_scores function""" + + def test_format_evaluation_scores_structure(self): + """Test that formatted scores have correct structure""" + # Create mock RAGAS result + mock_result = MagicMock(spec=EvaluationResult) + + # Create a mock DataFrame + df = pd.DataFrame({ + 'user_input': ['Question 1', 'Question 2'], + 'response': ['Answer 1', 'Answer 2'], + 'faithfulness': [0.9, 0.8], + 'answer_relevancy': [0.85, 0.75] + }) + mock_result.to_pandas.return_value = df + + # Format the scores + metrics = ['faithfulness', 'answer_relevancy'] + formatted = format_evaluation_scores(mock_result, metrics) + + # Verify structure + self.assertIn('overall_scores', formatted) + self.assertIn('individual_results', formatted) + self.assertIn('total_tokens', formatted) + self.assertIn('total_cost', formatted) + + def test_overall_scores_calculation(self): + """Test that overall scores are calculated correctly""" + mock_result = MagicMock(spec=EvaluationResult) + + df = pd.DataFrame({ + 'faithfulness': [0.9, 0.8, 0.7], + 'answer_relevancy': [0.85, 0.75, 0.65] + }) + mock_result.to_pandas.return_value = df + + metrics = ['faithfulness', 'answer_relevancy'] + formatted = format_evaluation_scores(mock_result, metrics) + + # Verify overall scores are averages + self.assertAlmostEqual(formatted['overall_scores']['faithfulness'], 0.8, places=2) + self.assertAlmostEqual(formatted['overall_scores']['answer_relevancy'], 0.75, places=2) + + def test_individual_results_present(self): + """Test that individual results are included""" + mock_result = MagicMock(spec=EvaluationResult) + + df = pd.DataFrame({ + 'user_input': ['Q1', 'Q2'], + 'faithfulness': [0.9, 0.8] + }) + mock_result.to_pandas.return_value = df + + metrics = ['faithfulness'] + formatted = format_evaluation_scores(mock_result, metrics) + + # Verify individual results + self.assertEqual(len(formatted['individual_results']), 2) + + def test_token_usage_placeholders(self): + """Test that token usage has placeholder values""" + mock_result = MagicMock(spec=EvaluationResult) + + df = pd.DataFrame({ + 'faithfulness': [0.9] + }) + mock_result.to_pandas.return_value = df + + metrics = ['faithfulness'] + formatted = format_evaluation_scores(mock_result, metrics) + + # Verify placeholders + self.assertEqual(formatted['total_tokens']['input_tokens'], 0) + self.assertEqual(formatted['total_tokens']['output_tokens'], 0) + self.assertEqual(formatted['total_cost'], 0.0) + + +class TestMain(unittest.TestCase): + """Test the main function""" + + def setUp(self): + """Set up temporary directory and test data""" + self.temp_dir = tempfile.mkdtemp() + self.original_cwd = Path.cwd() + + # Create test experiment JSONL + self.experiment_dir = Path(self.temp_dir) / "data" / "experiments" + self.experiment_dir.mkdir(parents=True, exist_ok=True) + + self.experiment_file = self.experiment_dir / "ragas_experiment.jsonl" + test_data = [ + { + 'user_input': 'What is the weather?', + 'retrieved_contexts': ['Context about weather'], + 'reference': 'Expected answer', + 'response': 'The weather is sunny.' + } + ] + + with open(self.experiment_file, 'w') as f: + for item in test_data: + f.write(json.dumps(item) + '\n') + + def tearDown(self): + """Clean up temporary directory""" + shutil.rmtree(self.temp_dir, ignore_errors=True) + + + def test_main_no_metrics(self): + """Test main function with no metrics provided""" + import os + os.chdir(self.temp_dir) + + try: + # When metrics is None, the function should raise an error + # The actual error type depends on implementation + with self.assertRaises((TypeError, AttributeError)): + main( + output_file="results/evaluation_scores.json", + model="gemini-flash-latest", + metrics=None + ) + finally: + os.chdir(self.original_cwd) + + +class TestEvaluationDatasetLoading(unittest.TestCase): + """Test loading of evaluation datasets from JSONL""" + + def setUp(self): + """Set up temporary directory with test JSONL""" + self.temp_dir = tempfile.mkdtemp() + self.jsonl_file = Path(self.temp_dir) / "test_experiment.jsonl" + + # Create test data + test_data = [ + { + 'user_input': 'Question 1', + 'retrieved_contexts': ['Context 1'], + 'reference': 'Answer 1', + 'response': 'Response 1' + }, + { + 'user_input': 'Question 2', + 'retrieved_contexts': ['Context 2'], + 'reference': 'Answer 2', + 'response': 'Response 2' + } + ] + + with open(self.jsonl_file, 'w') as f: + for item in test_data: + f.write(json.dumps(item) + '\n') + + def tearDown(self): + """Clean up temporary directory""" + shutil.rmtree(self.temp_dir, ignore_errors=True) + + def test_load_evaluation_dataset_from_jsonl(self): + """Test loading EvaluationDataset from JSONL file""" + dataset = EvaluationDataset.from_jsonl(str(self.jsonl_file)) + + # Verify dataset was loaded + self.assertIsInstance(dataset, EvaluationDataset) + + def test_loaded_dataset_structure(self): + """Test that loaded dataset has correct structure""" + dataset = EvaluationDataset.from_jsonl(str(self.jsonl_file)) + + # Convert to pandas to inspect + # Note: This may vary depending on Ragas version + # The test validates that the dataset can be loaded successfully + + +class TestAvailableMetrics(unittest.TestCase): + """Test the AVAILABLE_METRICS loading and validation""" + + def test_available_metrics_loaded(self): + """Test that AVAILABLE_METRICS is populated correctly""" + # Should be a non-empty dictionary + self.assertIsInstance(AVAILABLE_METRICS, dict) + self.assertGreater(len(AVAILABLE_METRICS), 0) + + # All keys should be strings + for key in AVAILABLE_METRICS.keys(): + self.assertIsInstance(key, str) + + # All values should be Metric instances + from ragas.metrics import Metric + for value in AVAILABLE_METRICS.values(): + self.assertIsInstance(value, Metric) + + def test_invalid_metric_name(self): + """Test that invalid metric names are rejected""" + invalid_metric = 'this_metric_does_not_exist_12345' + self.assertNotIn(invalid_metric, AVAILABLE_METRICS) + + +if __name__ == '__main__': + unittest.main() diff --git a/testworkflows/tests/test_publish.py b/testworkflows/tests/test_publish.py new file mode 100644 index 0000000..72437a2 --- /dev/null +++ b/testworkflows/tests/test_publish.py @@ -0,0 +1,371 @@ +""" +Unit tests for publish.py + +Tests the Prometheus metrics publishing functionality. +""" + +import unittest +import tempfile +import shutil +import json +from pathlib import Path +from unittest.mock import patch, MagicMock, call + +from prometheus_client import CollectorRegistry, Gauge + +import sys +sys.path.insert(0, str(Path(__file__).parent.parent / "scripts")) + +from publish import ( + get_overall_scores, + create_and_push_metrics, + publish_metrics +) + + +class TestGetOverallScores(unittest.TestCase): + """Test the get_overall_scores function""" + + def setUp(self): + """Set up temporary directory and test file""" + self.temp_dir = tempfile.mkdtemp() + self.test_file = Path(self.temp_dir) / "evaluation_scores.json" + + def tearDown(self): + """Clean up temporary directory""" + shutil.rmtree(self.temp_dir, ignore_errors=True) + + def test_loads_overall_scores(self): + """Test that get_overall_scores loads the overall_scores section""" + test_data = { + "overall_scores": { + "faithfulness": 0.85, + "answer_relevancy": 0.90 + }, + "individual_results": [], + "total_tokens": {"input_tokens": 0, "output_tokens": 0}, + "total_cost": 0.0 + } + + with open(self.test_file, 'w') as f: + json.dump(test_data, f) + + scores = get_overall_scores(str(self.test_file)) + + self.assertEqual(scores['faithfulness'], 0.85) + self.assertEqual(scores['answer_relevancy'], 0.90) + + def test_returns_empty_dict_if_no_overall_scores(self): + """Test that empty dict is returned if overall_scores is missing""" + test_data = { + "individual_results": [], + "total_tokens": {"input_tokens": 0, "output_tokens": 0} + } + + with open(self.test_file, 'w') as f: + json.dump(test_data, f) + + scores = get_overall_scores(str(self.test_file)) + + self.assertEqual(scores, {}) + + def test_file_not_found(self): + """Test behavior when file doesn't exist""" + with self.assertRaises(FileNotFoundError): + get_overall_scores(str(Path(self.temp_dir) / "nonexistent.json")) + + +class TestCreateAndPushMetrics(unittest.TestCase): + """Test the create_and_push_metrics function""" + + @patch('publish.push_to_gateway') + @patch('publish.Gauge') + def test_creates_gauges_for_each_metric(self, mock_gauge_class, mock_push): + """Test that a Gauge is created for each metric""" + overall_scores = { + 'faithfulness': 0.85, + 'answer_relevancy': 0.90 + } + + # Mock the Gauge instances + mock_gauge_instance = MagicMock() + mock_gauge_class.return_value = mock_gauge_instance + + create_and_push_metrics( + overall_scores=overall_scores, + workflow_name="test-workflow", + pushgateway_url="localhost:9091" + ) + + # Verify Gauge was called for each metric + self.assertEqual(mock_gauge_class.call_count, 2) + + # Verify gauge names + gauge_calls = mock_gauge_class.call_args_list + gauge_names = [call[0][0] for call in gauge_calls] + self.assertIn('ragas_evaluation_faithfulness', gauge_names) + self.assertIn('ragas_evaluation_answer_relevancy', gauge_names) + + @patch('publish.push_to_gateway') + @patch('publish.Gauge') + def test_sets_gauge_values(self, mock_gauge_class, mock_push): + """Test that gauge values are set correctly""" + overall_scores = { + 'faithfulness': 0.85 + } + + # Mock the Gauge instance and labels + mock_gauge_instance = MagicMock() + mock_labels = MagicMock() + mock_gauge_instance.labels.return_value = mock_labels + mock_gauge_class.return_value = mock_gauge_instance + + create_and_push_metrics( + overall_scores=overall_scores, + workflow_name="test-workflow", + pushgateway_url="localhost:9091" + ) + + # Verify labels were set with workflow_name + mock_gauge_instance.labels.assert_called_with(workflow_name="test-workflow") + + # Verify gauge value was set + mock_labels.set.assert_called_with(0.85) + + @patch('publish.push_to_gateway') + def test_pushes_to_gateway(self, mock_push): + """Test that metrics are pushed to Pushgateway""" + overall_scores = { + 'faithfulness': 0.85 + } + + create_and_push_metrics( + overall_scores=overall_scores, + workflow_name="test-workflow", + pushgateway_url="localhost:9091" + ) + + # Verify push_to_gateway was called + mock_push.assert_called_once() + + # Verify push parameters + call_args = mock_push.call_args + self.assertEqual(call_args[0][0], "localhost:9091") + self.assertEqual(call_args[1]['job'], 'ragas_evaluation') + + @patch('publish.push_to_gateway') + def test_handles_push_error(self, mock_push): + """Test error handling when push fails""" + mock_push.side_effect = Exception("Connection refused") + + overall_scores = { + 'faithfulness': 0.85 + } + + with self.assertRaises(Exception) as context: + create_and_push_metrics( + overall_scores=overall_scores, + workflow_name="test-workflow", + pushgateway_url="localhost:9091" + ) + + self.assertIn("Connection refused", str(context.exception)) + + +class TestPublishMetrics(unittest.TestCase): + """Test the publish_metrics function""" + + def setUp(self): + """Set up temporary directory and test file""" + self.temp_dir = tempfile.mkdtemp() + self.test_file = Path(self.temp_dir) / "evaluation_scores.json" + + # Create test evaluation scores file + test_data = { + "overall_scores": { + "faithfulness": 0.85, + "answer_relevancy": 0.90 + }, + "individual_results": [], + "total_tokens": {"input_tokens": 0, "output_tokens": 0}, + "total_cost": 0.0 + } + + with open(self.test_file, 'w') as f: + json.dump(test_data, f) + + def tearDown(self): + """Clean up temporary directory""" + shutil.rmtree(self.temp_dir, ignore_errors=True) + + @patch('publish.create_and_push_metrics') + def test_publish_metrics_calls_create_and_push(self, mock_create_push): + """Test that publish_metrics calls create_and_push_metrics""" + publish_metrics( + input_file=str(self.test_file), + workflow_name="test-workflow", + pushgateway_url="localhost:9091" + ) + + # Verify create_and_push_metrics was called + mock_create_push.assert_called_once() + + # Verify parameters (positional arguments) + call_args = mock_create_push.call_args + self.assertEqual(call_args[0][0]['faithfulness'], 0.85) + self.assertEqual(call_args[0][0]['answer_relevancy'], 0.90) + self.assertEqual(call_args[0][1], "test-workflow") + self.assertEqual(call_args[0][2], "localhost:9091") + + @patch('publish.create_and_push_metrics') + def test_publish_metrics_with_empty_scores(self, mock_create_push): + """Test behavior when overall_scores is empty""" + # Create file with empty overall_scores + test_data = { + "overall_scores": {}, + "individual_results": [] + } + + empty_file = Path(self.temp_dir) / "empty_scores.json" + with open(empty_file, 'w') as f: + json.dump(test_data, f) + + publish_metrics( + input_file=str(empty_file), + workflow_name="test-workflow", + pushgateway_url="localhost:9091" + ) + + # Verify create_and_push_metrics was NOT called + mock_create_push.assert_not_called() + + @patch('publish.create_and_push_metrics') + def test_publish_metrics_default_pushgateway_url(self, mock_create_push): + """Test that default pushgateway URL is used when not provided""" + publish_metrics( + input_file=str(self.test_file), + workflow_name="test-workflow", + pushgateway_url="localhost:9091" + ) + + # Verify the URL was passed correctly (third positional argument) + call_args = mock_create_push.call_args + self.assertEqual(call_args[0][2], "localhost:9091") + + +class TestIntegrationWithTestData(unittest.TestCase): + """Integration tests with realistic evaluation data""" + + def setUp(self): + """Set up temporary directory with realistic test data""" + self.temp_dir = tempfile.mkdtemp() + self.test_file = Path(self.temp_dir) / "evaluation_scores.json" + + # Create realistic evaluation scores + test_data = { + "overall_scores": { + "faithfulness": 0.8523, + "answer_relevancy": 0.9012, + "context_precision": 0.7845, + "context_recall": 0.8234 + }, + "individual_results": [ + { + "user_input": "What is the weather?", + "response": "It is sunny.", + "faithfulness": 0.85, + "answer_relevancy": 0.90 + } + ], + "total_tokens": { + "input_tokens": 0, + "output_tokens": 0 + }, + "total_cost": 0.0 + } + + with open(self.test_file, 'w') as f: + json.dump(test_data, f, indent=2) + + def tearDown(self): + """Clean up temporary directory""" + shutil.rmtree(self.temp_dir, ignore_errors=True) + + @patch('publish.push_to_gateway') + def test_publish_realistic_scores(self, mock_push): + """Test publishing realistic evaluation scores""" + publish_metrics( + input_file=str(self.test_file), + workflow_name="weather-assistant-test", + pushgateway_url="localhost:9091" + ) + + # Verify push was called + mock_push.assert_called_once() + + def test_load_realistic_scores(self): + """Test loading realistic evaluation scores""" + scores = get_overall_scores(str(self.test_file)) + + # Verify all scores are present + self.assertIn('faithfulness', scores) + self.assertIn('answer_relevancy', scores) + self.assertIn('context_precision', scores) + self.assertIn('context_recall', scores) + + # Verify values are floats + for score in scores.values(): + self.assertIsInstance(score, float) + self.assertGreaterEqual(score, 0.0) + self.assertLessEqual(score, 1.0) + + +class TestPrometheusGaugeCreation(unittest.TestCase): + """Test Prometheus Gauge creation and configuration""" + + def test_gauge_with_labels(self): + """Test creating a Gauge with labels""" + registry = CollectorRegistry() + + gauge = Gauge( + 'ragas_evaluation_test_metric', + 'Test metric description', + labelnames=['workflow_name'], + registry=registry + ) + + # Set a value with label + gauge.labels(workflow_name='test-workflow').set(0.85) + + # Verify the gauge was created + self.assertIsNotNone(gauge) + + def test_multiple_gauges_in_registry(self): + """Test creating multiple gauges in the same registry""" + registry = CollectorRegistry() + + gauge1 = Gauge( + 'ragas_evaluation_faithfulness', + 'Faithfulness score', + labelnames=['workflow_name'], + registry=registry + ) + + gauge2 = Gauge( + 'ragas_evaluation_answer_relevancy', + 'Answer relevancy score', + labelnames=['workflow_name'], + registry=registry + ) + + # Set values + gauge1.labels(workflow_name='test').set(0.85) + gauge2.labels(workflow_name='test').set(0.90) + + # Both gauges should be in the registry + metrics = list(registry.collect()) + self.assertGreaterEqual(len(metrics), 2) + + +if __name__ == '__main__': + unittest.main() diff --git a/testworkflows/tests/test_run.py b/testworkflows/tests/test_run.py new file mode 100644 index 0000000..064896a --- /dev/null +++ b/testworkflows/tests/test_run.py @@ -0,0 +1,222 @@ +""" +Unit tests for run.py + +Tests the agent query execution and experiment functionality. +""" + +import unittest +import tempfile +import shutil +import asyncio +from pathlib import Path +from unittest.mock import patch, MagicMock, AsyncMock + +from pydantic import BaseModel +from ragas import Dataset + +import sys +sys.path.insert(0, str(Path(__file__).parent.parent / "scripts")) + +from run import initialize_client, run_agent_experiment, main + + +class TestInitializeClient(unittest.TestCase): + """Test the initialize_client function""" + + @patch('run.ClientFactory') + @patch('run.minimal_agent_card') + async def test_initialize_client_creates_client(self, mock_agent_card, mock_factory): + """Test that initialize_client creates a client correctly""" + # Mock the agent card + mock_card = MagicMock() + mock_agent_card.return_value = mock_card + + # Mock the factory and client + mock_client = MagicMock() + mock_factory_instance = MagicMock() + mock_factory_instance.create.return_value = mock_client + mock_factory.return_value = mock_factory_instance + + # Mock httpx client and logger + mock_httpx_client = AsyncMock() + mock_logger = MagicMock() + + # Call the function + result = await initialize_client( + "http://test-agent:8000", + mock_httpx_client, + mock_logger + ) + + # Verify + mock_agent_card.assert_called_once_with("http://test-agent:8000") + mock_factory_instance.create.assert_called_once_with(mock_card) + self.assertEqual(result, mock_client) + + def test_initialize_client_sync(self): + """Synchronous wrapper for async test""" + asyncio.run(self.test_initialize_client_creates_client()) + + +class TestRunAgentExperiment(unittest.TestCase): + """Test the run_agent_experiment function""" + + def setUp(self): + """Set up temporary directory for experiment outputs""" + self.temp_dir = tempfile.mkdtemp() + self.original_cwd = Path.cwd() + + def tearDown(self): + """Clean up temporary directory""" + shutil.rmtree(self.temp_dir, ignore_errors=True) + + @patch('run.logging.getLogger') + @patch('run.initialize_client') + async def test_run_agent_experiment_success(self, mock_init_client, mock_get_logger): + """Test successful agent query execution""" + # Mock logger + mock_logger = MagicMock() + mock_get_logger.return_value = mock_logger + + # Mock the client + mock_client = MagicMock() + + # Create a mock task response + mock_task = MagicMock() + mock_task.model_dump.return_value = { + 'artifacts': [{ + 'parts': [{'text': 'Agent response text'}] + }], + 'history': [] + } + + # Mock the async generator returned by send_message + async def mock_send_message(message): + yield (mock_task, None) + + mock_client.send_message = mock_send_message + mock_init_client.return_value = mock_client + + # Create test row + test_row = { + 'user_input': 'What is the weather?', + 'retrieved_contexts': ['Context about weather'], + 'reference': 'Expected answer' + } + + # Mock httpx AsyncClient + with patch('run.httpx.AsyncClient') as mock_httpx: + mock_httpx_instance = AsyncMock() + mock_httpx_instance.__aenter__.return_value = mock_httpx_instance + mock_httpx_instance.__aexit__.return_value = None + mock_httpx.return_value = mock_httpx_instance + + # Create an async function that mimics the experiment function + async def test_experiment_func(row, agent_url): + return await run_agent_experiment.func(row, agent_url=agent_url) + + # Call the function + result = await test_experiment_func( + test_row, + agent_url="http://test-agent:8000" + ) + + # Verify result structure + self.assertIn('user_input', result) + self.assertIn('retrieved_contexts', result) + self.assertIn('reference', result) + self.assertIn('response', result) + self.assertEqual(result['user_input'], 'What is the weather?') + self.assertEqual(result['response'], 'Agent response text') + + @patch('run.logging.getLogger') + @patch('run.initialize_client') + async def test_run_agent_experiment_error(self, mock_init_client, mock_get_logger): + """Test agent query with error handling""" + # Mock logger + mock_logger = MagicMock() + mock_get_logger.return_value = mock_logger + + # Mock client that raises an error + mock_init_client.side_effect = Exception("Connection failed") + + # Create test row + test_row = { + 'user_input': 'What is the weather?', + 'retrieved_contexts': ['Context'], + 'reference': 'Answer' + } + + # Mock httpx AsyncClient + with patch('run.httpx.AsyncClient') as mock_httpx: + mock_httpx_instance = AsyncMock() + mock_httpx_instance.__aenter__.return_value = mock_httpx_instance + mock_httpx_instance.__aexit__.return_value = None + mock_httpx.return_value = mock_httpx_instance + + # Create an async function that mimics the experiment function + async def test_experiment_func(row, agent_url): + return await run_agent_experiment.func(row, agent_url=agent_url) + + # Call the function + result = await test_experiment_func( + test_row, + agent_url="http://test-agent:8000" + ) + + # Verify error is captured in response + self.assertIn('response', result) + self.assertIn('ERROR', result['response']) + self.assertIn('Connection failed', result['response']) + +class TestMain(unittest.TestCase): + """Test the main function""" + + def setUp(self): + """Set up temporary directory""" + self.temp_dir = tempfile.mkdtemp() + self.original_cwd = Path.cwd() + + def tearDown(self): + """Clean up temporary directory""" + shutil.rmtree(self.temp_dir, ignore_errors=True) + + @patch('run.run_agent_experiment.arun') + @patch('run.Dataset.load') + async def test_main_execution(self, mock_dataset_load, mock_arun): + """Test main function execution flow""" + import os + os.chdir(self.temp_dir) + + try: + # Create a mock dataset + mock_dataset = MagicMock() + mock_dataset.__len__ = MagicMock(return_value=2) + mock_dataset_load.return_value = mock_dataset + + # Mock experiment results + mock_experiment = MagicMock() + mock_arun.return_value = mock_experiment + + # Run main + await main("http://test-agent:8000") + + # Verify Dataset.load was called + mock_dataset_load.assert_called_once() + + # Verify experiment was run + mock_arun.assert_called_once() + finally: + os.chdir(self.original_cwd) + + def test_main_sync(self): + """Synchronous wrapper for async test""" + asyncio.run(self.test_main_execution()) + + + + + + +if __name__ == '__main__': + unittest.main() diff --git a/testworkflows/tests/test_setup.py b/testworkflows/tests/test_setup.py new file mode 100644 index 0000000..854e38f --- /dev/null +++ b/testworkflows/tests/test_setup.py @@ -0,0 +1,301 @@ +""" +Unit tests for setup.py + +Tests the dataset download, conversion, and Ragas dataset creation functionality. +""" + +import unittest +import tempfile +import shutil +from pathlib import Path +from io import BytesIO +from unittest.mock import patch, MagicMock + +import pandas as pd +from ragas import Dataset + +import sys +sys.path.insert(0, str(Path(__file__).parent.parent / "scripts")) + +from setup import ( + custom_convert_csv, + get_converter, + dataframe_to_ragas_dataset, + main +) + + +class TestCustomConvertCSV(unittest.TestCase): + """Test the custom_convert_csv function""" + + def test_converts_string_to_list(self): + """Test that retrieved_contexts strings are converted to lists""" + csv_content = b"user_input,retrieved_contexts,reference\n" + csv_content += b'"Question?","Context text","Answer"\n' + + buffer = BytesIO(csv_content) + df = custom_convert_csv(buffer) + + self.assertIsInstance(df['retrieved_contexts'].iloc[0], list) + self.assertEqual(df['retrieved_contexts'].iloc[0], ["Context text"]) + + def test_handles_empty_retrieved_contexts(self): + """Test handling of empty retrieved_contexts""" + csv_content = b"user_input,retrieved_contexts,reference\n" + csv_content += b'"Question?","","Answer"\n' + + buffer = BytesIO(csv_content) + df = custom_convert_csv(buffer) + + # Empty string becomes [nan] in pandas, which then becomes [] + # The function converts non-list values to lists + result = df['retrieved_contexts'].iloc[0] + # Check that it's a list and handle NaN case + self.assertIsInstance(result, list) + # If it contains NaN, that's acceptable behavior for empty strings in CSV + if result and pd.isna(result[0]): + # This is expected - pandas converts empty string to NaN + pass + else: + # Or it should be an empty list + self.assertEqual(result, []) + + def test_missing_retrieved_contexts_column(self): + """Test that CSV without retrieved_contexts column works""" + csv_content = b"user_input,reference\n" + csv_content += b'"Question?","Answer"\n' + + buffer = BytesIO(csv_content) + df = custom_convert_csv(buffer) + + self.assertNotIn('retrieved_contexts', df.columns) + + +class TestGetConverter(unittest.TestCase): + """Test the get_converter function""" + + def test_csv_converter(self): + """Test that CSV files get custom_convert_csv""" + converter = get_converter("https://example.com/data.csv") + self.assertEqual(converter, custom_convert_csv) + + def test_json_converter(self): + """Test that JSON files get pd.read_json""" + converter = get_converter("https://example.com/data.json") + self.assertEqual(converter, pd.read_json) + + def test_parquet_converter(self): + """Test that Parquet files get pd.read_parquet""" + converter = get_converter("https://example.com/data.parquet") + self.assertEqual(converter, pd.read_parquet) + + def test_prq_converter(self): + """Test that .prq files get pd.read_parquet""" + converter = get_converter("https://example.com/data.prq") + self.assertEqual(converter, pd.read_parquet) + + def test_unsupported_format(self): + """Test that unsupported formats raise TypeError""" + with self.assertRaises(TypeError) as context: + get_converter("https://example.com/data.xlsx") + + self.assertIn("Unsupported filetype", str(context.exception)) + + +class TestDataframeToRagasDataset(unittest.TestCase): + """Test the dataframe_to_ragas_dataset function""" + + def setUp(self): + """Set up temporary directory for test outputs""" + self.temp_dir = tempfile.mkdtemp() + self.original_cwd = Path.cwd() + + def tearDown(self): + """Clean up temporary directory""" + shutil.rmtree(self.temp_dir, ignore_errors=True) + + def test_creates_ragas_dataset_file(self): + """Test that ragas_dataset.jsonl is created""" + import os + os.chdir(self.temp_dir) + + try: + df = pd.DataFrame({ + 'user_input': ['Question 1'], + 'retrieved_contexts': [['Context 1']], + 'reference': ['Answer 1'] + }) + + dataframe_to_ragas_dataset(df) + + # Check for the file in the datasets subdirectory + dataset_file = Path(self.temp_dir) / 'data' / 'datasets' / 'ragas_dataset.jsonl' + self.assertTrue(dataset_file.exists(), f"Dataset file not found at {dataset_file}") + finally: + os.chdir(self.original_cwd) + +class TestMain(unittest.TestCase): + """Test the main function with mocked HTTP requests""" + + def setUp(self): + """Set up temporary directory""" + self.temp_dir = tempfile.mkdtemp() + self.original_cwd = Path.cwd() + + def tearDown(self): + """Clean up temporary directory""" + shutil.rmtree(self.temp_dir, ignore_errors=True) + + @patch('setup.requests.get') + def test_main_with_csv(self, mock_get): + """Test main function with CSV file""" + import os + os.chdir(self.temp_dir) + + try: + # Mock the HTTP response + csv_content = b"user_input,retrieved_contexts,reference\n" + csv_content += b'"Question?","Context text","Answer"\n' + + mock_response = MagicMock() + mock_response.content = csv_content + mock_response.raise_for_status = MagicMock() + mock_get.return_value = mock_response + + # Run main + main("https://example.com/data.csv") + + # Verify dataset was created in datasets subdirectory + dataset_file = Path(self.temp_dir) / 'data' / 'datasets' / 'ragas_dataset.jsonl' + self.assertTrue(dataset_file.exists(), f"Dataset file not found at {dataset_file}") + + # Verify requests.get was called + mock_get.assert_called_once_with("https://example.com/data.csv") + finally: + os.chdir(self.original_cwd) + + @patch('setup.requests.get') + def test_main_with_json(self, mock_get): + """Test main function with JSON file""" + import os + os.chdir(self.temp_dir) + + try: + # Mock the HTTP response + json_content = b'''[ + { + "user_input": "Question?", + "retrieved_contexts": ["Context text"], + "reference": "Answer" + } + ]''' + + mock_response = MagicMock() + mock_response.content = json_content + mock_response.raise_for_status = MagicMock() + mock_get.return_value = mock_response + + # Run main + main("https://example.com/data.json") + + # Verify dataset was created in datasets subdirectory + dataset_file = Path(self.temp_dir) / 'data' / 'datasets' / 'ragas_dataset.jsonl' + self.assertTrue(dataset_file.exists(), f"Dataset file not found at {dataset_file}") + finally: + os.chdir(self.original_cwd) + + @patch('setup.requests.get') + def test_main_with_invalid_url(self, mock_get): + """Test main function with invalid URL (HTTP error)""" + import os + os.chdir(self.temp_dir) + + try: + # Mock HTTP error + mock_response = MagicMock() + mock_response.raise_for_status.side_effect = Exception("HTTP 404") + mock_get.return_value = mock_response + + # Verify that the error propagates + with self.assertRaises(Exception): + main("https://example.com/nonexistent.csv") + finally: + os.chdir(self.original_cwd) + + +class TestIntegrationWithTestData(unittest.TestCase): + """Integration tests using the actual test data files""" + + def setUp(self): + """Set up temporary directory""" + self.temp_dir = tempfile.mkdtemp() + self.original_cwd = Path.cwd() + self.test_data_dir = Path(__file__).parent / "test_data" + + def tearDown(self): + """Clean up temporary directory""" + shutil.rmtree(self.temp_dir, ignore_errors=True) + + def test_csv_test_data_conversion(self): + """Test conversion of actual CSV test data""" + import os + os.chdir(self.temp_dir) + + try: + # Read the test CSV file + csv_path = self.test_data_dir / "dataset.csv" + with open(csv_path, 'rb') as f: + df = custom_convert_csv(f) + + # Verify structure + self.assertEqual(len(df), 5) # 5 rows in test data + self.assertIn('user_input', df.columns) + self.assertIn('retrieved_contexts', df.columns) + self.assertIn('reference', df.columns) + + # Verify retrieved_contexts is a list + for contexts in df['retrieved_contexts']: + self.assertIsInstance(contexts, list) + + # Create Ragas dataset + dataframe_to_ragas_dataset(df) + + # Verify it was created in datasets subdirectory + dataset_file = Path(self.temp_dir) / 'data' / 'datasets' / 'ragas_dataset.jsonl' + self.assertTrue(dataset_file.exists(), f"Dataset file not found at {dataset_file}") + finally: + os.chdir(self.original_cwd) + + def test_json_test_data_conversion(self): + """Test conversion of actual JSON test data""" + import os + os.chdir(self.temp_dir) + + try: + # Read the test JSON file + json_path = self.test_data_dir / "dataset.json" + with open(json_path, 'rb') as f: + df = pd.read_json(f) + + # Verify structure + self.assertEqual(len(df), 5) # 5 rows in test data + self.assertIn('user_input', df.columns) + self.assertIn('retrieved_contexts', df.columns) + self.assertIn('reference', df.columns) + + # Verify retrieved_contexts is already a list (JSON preserves types) + for contexts in df['retrieved_contexts']: + self.assertIsInstance(contexts, list) + + # Create Ragas dataset + dataframe_to_ragas_dataset(df) + + # Verify it was created in datasets subdirectory + dataset_file = Path(self.temp_dir) / 'data' / 'datasets' / 'ragas_dataset.jsonl' + self.assertTrue(dataset_file.exists(), f"Dataset file not found at {dataset_file}") + finally: + os.chdir(self.original_cwd) + + +if __name__ == '__main__': + unittest.main() From f2d828d3344de66aea0a5215aac9d7a241614eca Mon Sep 17 00:00:00 2001 From: MiaAppel Date: Tue, 4 Nov 2025 15:17:36 +0100 Subject: [PATCH 03/61] FIX: Plenty of fixes / small refactorings in coordination with @fmallmann --- .github/workflows/test-testworkflows.yml | 35 +++++ testworkflows/scripts/evaluate.py | 84 ++++++++--- testworkflows/scripts/publish.py | 13 +- testworkflows/scripts/run.py | 17 +-- testworkflows/scripts/setup.py | 10 +- testworkflows/tests/test_evaluate.py | 176 ++++++----------------- testworkflows/tests/test_publish.py | 92 +----------- testworkflows/tests/test_run.py | 21 +-- testworkflows/tests/test_setup.py | 94 ------------ 9 files changed, 159 insertions(+), 383 deletions(-) create mode 100644 .github/workflows/test-testworkflows.yml diff --git a/.github/workflows/test-testworkflows.yml b/.github/workflows/test-testworkflows.yml new file mode 100644 index 0000000..62cc731 --- /dev/null +++ b/.github/workflows/test-testworkflows.yml @@ -0,0 +1,35 @@ +name: Test Testworkflows + +on: + push: + branches: [ main ] + pull_request: + branches: [ main ] + +jobs: + test-testworkflows: + runs-on: ubuntu-latest + + defaults: + run: + working-directory: testworkflows + + steps: + - name: Checkout repository + uses: actions/checkout@v4 + + - name: Set up Python 3.12 + uses: actions/setup-python@v5 + with: + python-version: '3.12' + + - name: Install uv + run: | + curl -LsSf https://astral.sh/uv/install.sh | sh + echo "$HOME/.cargo/bin" >> $GITHUB_PATH + + - name: Sync dependencies with uv + run: uv sync + + - name: Run pytest (skip E2E tests) + run: uv run pytest tests/ -v --ignore=tests/test_e2e.py diff --git a/testworkflows/scripts/evaluate.py b/testworkflows/scripts/evaluate.py index cc55926..9e14d7f 100644 --- a/testworkflows/scripts/evaluate.py +++ b/testworkflows/scripts/evaluate.py @@ -3,6 +3,7 @@ import json import logging import os +from dataclasses import dataclass, asdict from pydantic import BaseModel from argparse import ArgumentError from logging import Logger @@ -15,6 +16,7 @@ from ragas.metrics import Metric import ragas.metrics as metrics_module from langchain_google_genai import ChatGoogleGenerativeAI +from ragas.cost import get_token_usage_for_openai # Set up module-level logger logging.basicConfig(level=logging.INFO) @@ -79,15 +81,26 @@ def calculate_metrics(dataset: EvaluationDataset, metrics: list[str], llm: Any) dataset=dataset, metrics=metric_objects, llm=llm, + token_usage_parser=get_token_usage_for_openai, ) return result +@dataclass +class EvaluationScores: + """Evaluation scores and results.""" + overall_scores: dict[str, float] + individual_results: list[dict[str, Any]] + total_tokens: dict[str, int] + total_cost: float + + def format_evaluation_scores( ragas_result: EvaluationResult, - metrics: list[str] -) -> dict[str, Any]: + cost_per_input_token: float, + cost_per_output_token: float, +) -> EvaluationScores: """ Format the RAGAS evaluation results. @@ -105,34 +118,36 @@ def format_evaluation_scores( df = ragas_result.to_pandas() # Calculate overall scores (mean of each metric) - overall_scores = {} - for metric in metrics: - if metric in df.columns: - overall_scores[metric] = float(df[metric].mean()) + overall_scores = ragas_result._repr_dict # Build individual results individual_results = ragas_result.to_pandas().to_dict(orient="records") - # Ragas doesn't have TokenUsageParser for Google Gemini - setting placeholders instead + # Extract token usage and calculate cost using TokenUsageParser + token_usage = ragas_result.total_tokens() total_tokens = { - "input_tokens": 0, - "output_tokens": 0 + "input_tokens": token_usage.input_tokens, + "output_tokens": token_usage.output_tokens } - total_cost = 0.0 - + total_cost = ragas_result.total_cost( + cost_per_input_token=cost_per_input_token, + cost_per_output_token=cost_per_output_token + ) - return { - "overall_scores": overall_scores, - "individual_results": individual_results, - "total_tokens": total_tokens, - "total_cost": total_cost - } + return EvaluationScores( + overall_scores=overall_scores, + individual_results=individual_results, + total_tokens=total_tokens, + total_cost=total_cost + ) def main( output_file: str, model: str, - metrics: list[str] = None + metrics: list[str] = None, + cost_per_input_token: float = 5.0 / 1e6, + cost_per_output_token: float = 15.0 / 1e6 ) -> None: """ Main function to evaluate results using RAGAS metrics. @@ -142,8 +157,11 @@ def main( model: Model name to use for evaluation metrics: List of metric names to calculate """ + # Check if any metrics were provided + if metrics is None: + raise ArgumentError("No metrics were provided as arguments") - # Create LLM client using the proxy + # Create LLM client using the AI-Gateway ragas_llm = ChatOpenAI( model=model ) @@ -157,17 +175,21 @@ def main( # Format results logger.info("Formatting evaluation scores...") - evaluation_scores = format_evaluation_scores(ragas_result, metrics) + evaluation_scores = format_evaluation_scores( + ragas_result, + cost_per_input_token=cost_per_input_token, + cost_per_output_token=cost_per_output_token + ) # Ensure output directory exists os.makedirs(os.path.dirname(output_file), exist_ok=True) # Save to file with open(output_file, 'w') as f: - json.dump(evaluation_scores, f, indent=2) + json.dump(asdict(evaluation_scores), f, indent=2) logger.info(f"Evaluation scores saved to {output_file}") - logger.info(f"Overall scores: {evaluation_scores['overall_scores']}") + logger.info(f"Overall scores: {evaluation_scores.overall_scores}") if __name__ == "__main__": @@ -197,11 +219,27 @@ def main( help = 'At least one (or more) metrics to evaluate (e.g., faithfulness, answer_relevancy)' ) + parser.add_argument( + '--cost-per-input', + type = float, + default = 5.0 / 1e6, + help = 'Cost per input token (default: 5.0/1M = $0.000005 for typical GPT-4 pricing)' + ) + + parser.add_argument( + '--cost-per-output', + type = float, + default = 15.0 / 1e6, + help = 'Cost per output token (default: 15.0/1M = $0.000015 for typical GPT-4 pricing)' + ) + args = parser.parse_args() # Run evaluation with the 'model' and 'metrics' provided as parameters, 'output_file' is hardcoded main( output_file = "results/evaluation_scores.json", model = args.model, - metrics = args.metrics + metrics = args.metrics, + cost_per_input_token = args.cost_per_input, + cost_per_output_token = args.cost_per_output ) diff --git a/testworkflows/scripts/publish.py b/testworkflows/scripts/publish.py index 0f7cca6..d903b8a 100644 --- a/testworkflows/scripts/publish.py +++ b/testworkflows/scripts/publish.py @@ -2,7 +2,6 @@ import json import logging from logging import Logger -from typing import Any from prometheus_client import CollectorRegistry, Gauge, push_to_gateway # Set up module-level logger @@ -10,7 +9,7 @@ logger: Logger = logging.getLogger(__name__) -def get_overall_scores(file_path: str) -> dict[str, Any]: +def get_overall_scores(file_path: str) -> dict[str, float]: """Load the evaluation_scores.json file and return the 'overall_scores' metrics.""" with open(file_path, 'r') as file: return json.load(file).get("overall_scores", {}) @@ -43,7 +42,7 @@ def create_and_push_metrics( # Set the gauge value with the workflow_name label gauge.labels(workflow_name=workflow_name).set(score) - logger.info(f"Set metric 'evaluation_{metric_name}{{workflow_name=\"{workflow_name}\"}}' to {score}") + logger.info(f"Set metric 'ragas_evaluation_{metric_name}{{workflow_name=\"{workflow_name}\"}}' to {score}") # Push metrics to Pushgateway @@ -59,6 +58,10 @@ def create_and_push_metrics( logger.error(f"✗ Error pushing metrics to Pushgateway: {e}") raise + logger.info("Published metrics:") + for metric_name, score in overall_scores.items(): + logger.info(f" - ragas_evaluation_{metric_name}{{workflow_name=\"{workflow_name}\"}}: {score}") + def publish_metrics( input_file: str, @@ -87,10 +90,6 @@ def publish_metrics( logger.info(f"Workflow: {workflow_name}") create_and_push_metrics(overall_scores, workflow_name, pushgateway_url) - logger.info("Published metrics:") - for metric_name, score in overall_scores.items(): - logger.info(f" - ragas_evaluation_{metric_name}{{workflow_name=\"{workflow_name}\"}}: {score}") - if __name__ == "__main__": """ diff --git a/testworkflows/scripts/run.py b/testworkflows/scripts/run.py index 2ef0023..babb047 100644 --- a/testworkflows/scripts/run.py +++ b/testworkflows/scripts/run.py @@ -1,7 +1,6 @@ import asyncio import argparse import httpx -import json import logging from logging import Logger @@ -22,14 +21,15 @@ logging.basicConfig(level=logging.INFO) logger: Logger = logging.getLogger(__name__) -async def initialize_client(agent_url: str, httpx_client: httpx.AsyncClient, logger: Logger) -> Client: + +async def initialize_client(agent_url: str) -> Client: """Initialize the A2A client with a minimal agent card.""" logger.info(f'Initializing A2A client for: {agent_url}') # Create a minimal agent card with the provided URL agent_card: AgentCard = minimal_agent_card(agent_url) - config: ClientConfig = ClientConfig(httpx_client=httpx_client) + config: ClientConfig = ClientConfig() factory: ClientFactory = ClientFactory(config) client: Client = factory.create(agent_card) @@ -39,7 +39,7 @@ async def initialize_client(agent_url: str, httpx_client: httpx.AsyncClient, log @experiment() -async def run_agent_experiment(row, agent_url: str) -> dict[str, str | list | list]: +async def run_agent_experiment(row, agent_url: str) -> dict[str, str | list]: """ Experiment function that processes each row from the dataset. @@ -50,11 +50,10 @@ async def run_agent_experiment(row, agent_url: str) -> dict[str, str | list | li Returns: Dictionary with original row data plus 'response' """ - output_text: str = "" try: - async with httpx.AsyncClient() as httpx_client: - client = await initialize_client(agent_url, httpx_client, logger) + async with httpx.AsyncClient(): + client = await initialize_client(agent_url) # Get the input from the row input_text = row.get("user_input") @@ -78,16 +77,12 @@ async def run_agent_experiment(row, agent_url: str) -> dict[str, str | list | li task, _ = response if task: artifacts: list = task.model_dump(mode='json', include={'artifacts'}).get('artifacts',[]) - history: list = task.model_dump(mode='json', include={'history'}).get('history',[]) # Extract the model response if artifacts and artifacts[0].get('parts'): output_text = artifacts[0]['parts'][0].get('text', '') else: logger.warning("No text found in artifacts") - - elif hasattr(response, 'model_dump'): - logger.debug(response.model_dump(mode='json', exclude_none=True)) else: logger.warning(f'Unexpected response: {response}') diff --git a/testworkflows/scripts/setup.py b/testworkflows/scripts/setup.py index d11357a..4e61ed4 100644 --- a/testworkflows/scripts/setup.py +++ b/testworkflows/scripts/setup.py @@ -27,11 +27,15 @@ def dataframe_to_ragas_dataset(dataframe: DataFrame) -> None: dataset_samples = dataframe.to_dict(orient="records") # Create Ragas Dataset - dataset: Dataset[BaseModel] = Dataset(name="ragas_dataset", backend="local/jsonl", root_dir="./data") + dataset: Dataset[BaseModel] = Dataset( + name="ragas_dataset", + data=dataset_samples, + backend="local/jsonl", + root_dir="./data") - # Append all samples to the dataset + """# Append all samples to the dataset for sample in dataset_samples: - dataset.append(sample) + dataset.append(sample)""" # Save the dataset dataset.save() diff --git a/testworkflows/tests/test_evaluate.py b/testworkflows/tests/test_evaluate.py index f3355d2..2f34dd7 100644 --- a/testworkflows/tests/test_evaluate.py +++ b/testworkflows/tests/test_evaluate.py @@ -26,33 +26,6 @@ ) -class TestGetAvailableMetrics(unittest.TestCase): - """Test the get_available_metrics function""" - - def test_returns_dict(self): - """Test that get_available_metrics returns a dictionary""" - metrics = get_available_metrics() - self.assertIsInstance(metrics, dict) - - def test_contains_common_metrics(self): - """Test that common metrics are available""" - metrics = get_available_metrics() - - # Check for some common metrics - common_metrics = ['faithfulness', 'answer_relevancy'] - - for metric in common_metrics: - if metric in metrics: - self.assertIn(metric, metrics) - - def test_metric_instances_have_name(self): - """Test that metric instances have a name attribute""" - metrics = get_available_metrics() - - for metric_name, metric_instance in metrics.items(): - self.assertTrue(hasattr(metric_instance, 'name')) - - class TestCalculateMetrics(unittest.TestCase): """Test the calculate_metrics function""" @@ -89,21 +62,6 @@ def test_calculate_metrics_calls_evaluate(self, mock_evaluate): mock_evaluate.assert_called_once() self.assertEqual(result, mock_result) - @patch('evaluate.evaluate') - def test_calculate_metrics_with_multiple_metrics(self, mock_evaluate): - """Test calculate_metrics with multiple metrics""" - mock_dataset = MagicMock(spec=EvaluationDataset) - mock_llm = MagicMock() - mock_result = MagicMock(spec=EvaluationResult) - mock_evaluate.return_value = mock_result - - # Call with multiple metrics - metrics = ['faithfulness', 'answer_relevancy'] - result = calculate_metrics(mock_dataset, metrics, mock_llm) - - # Verify evaluate was called - mock_evaluate.assert_called_once() - def test_calculate_metrics_with_invalid_metric(self): """Test calculate_metrics with invalid metric name""" mock_dataset = MagicMock(spec=EvaluationDataset) @@ -121,30 +79,6 @@ def test_calculate_metrics_with_invalid_metric(self): class TestFormatEvaluationScores(unittest.TestCase): """Test the format_evaluation_scores function""" - def test_format_evaluation_scores_structure(self): - """Test that formatted scores have correct structure""" - # Create mock RAGAS result - mock_result = MagicMock(spec=EvaluationResult) - - # Create a mock DataFrame - df = pd.DataFrame({ - 'user_input': ['Question 1', 'Question 2'], - 'response': ['Answer 1', 'Answer 2'], - 'faithfulness': [0.9, 0.8], - 'answer_relevancy': [0.85, 0.75] - }) - mock_result.to_pandas.return_value = df - - # Format the scores - metrics = ['faithfulness', 'answer_relevancy'] - formatted = format_evaluation_scores(mock_result, metrics) - - # Verify structure - self.assertIn('overall_scores', formatted) - self.assertIn('individual_results', formatted) - self.assertIn('total_tokens', formatted) - self.assertIn('total_cost', formatted) - def test_overall_scores_calculation(self): """Test that overall scores are calculated correctly""" mock_result = MagicMock(spec=EvaluationResult) @@ -155,12 +89,21 @@ def test_overall_scores_calculation(self): }) mock_result.to_pandas.return_value = df - metrics = ['faithfulness', 'answer_relevancy'] - formatted = format_evaluation_scores(mock_result, metrics) + # Mock _repr_dict with calculated averages + mock_result._repr_dict = {'faithfulness': 0.8, 'answer_relevancy': 0.75} + + # Mock token usage methods + mock_token_usage = MagicMock() + mock_token_usage.input_tokens = 100 + mock_token_usage.output_tokens = 50 + mock_result.total_tokens.return_value = mock_token_usage + mock_result.total_cost.return_value = 0.001 + + formatted = format_evaluation_scores(mock_result, 5.0/1e6, 15.0/1e6) - # Verify overall scores are averages - self.assertAlmostEqual(formatted['overall_scores']['faithfulness'], 0.8, places=2) - self.assertAlmostEqual(formatted['overall_scores']['answer_relevancy'], 0.75, places=2) + # Verify overall scores are correct + self.assertAlmostEqual(formatted.overall_scores['faithfulness'], 0.8, places=2) + self.assertAlmostEqual(formatted.overall_scores['answer_relevancy'], 0.75, places=2) def test_individual_results_present(self): """Test that individual results are included""" @@ -172,14 +115,23 @@ def test_individual_results_present(self): }) mock_result.to_pandas.return_value = df - metrics = ['faithfulness'] - formatted = format_evaluation_scores(mock_result, metrics) + # Mock _repr_dict for overall scores + mock_result._repr_dict = {'faithfulness': 0.85} + + # Mock token usage methods + mock_token_usage = MagicMock() + mock_token_usage.input_tokens = 100 + mock_token_usage.output_tokens = 50 + mock_result.total_tokens.return_value = mock_token_usage + mock_result.total_cost.return_value = 0.001 + + formatted = format_evaluation_scores(mock_result, 5.0/1e6, 15.0/1e6) # Verify individual results - self.assertEqual(len(formatted['individual_results']), 2) + self.assertEqual(len(formatted.individual_results), 2) def test_token_usage_placeholders(self): - """Test that token usage has placeholder values""" + """Test that token usage is returned correctly""" mock_result = MagicMock(spec=EvaluationResult) df = pd.DataFrame({ @@ -187,13 +139,22 @@ def test_token_usage_placeholders(self): }) mock_result.to_pandas.return_value = df - metrics = ['faithfulness'] - formatted = format_evaluation_scores(mock_result, metrics) + # Mock _repr_dict for overall scores + mock_result._repr_dict = {'faithfulness': 0.9} - # Verify placeholders - self.assertEqual(formatted['total_tokens']['input_tokens'], 0) - self.assertEqual(formatted['total_tokens']['output_tokens'], 0) - self.assertEqual(formatted['total_cost'], 0.0) + # Mock token usage methods with specific values + mock_token_usage = MagicMock() + mock_token_usage.input_tokens = 150 + mock_token_usage.output_tokens = 75 + mock_result.total_tokens.return_value = mock_token_usage + mock_result.total_cost.return_value = 0.002 + + formatted = format_evaluation_scores(mock_result, 5.0/1e6, 15.0/1e6) + + # Verify token usage is captured correctly + self.assertEqual(formatted.total_tokens['input_tokens'], 150) + self.assertEqual(formatted.total_tokens['output_tokens'], 75) + self.assertEqual(formatted.total_cost, 0.002) class TestMain(unittest.TestCase): @@ -245,54 +206,6 @@ def test_main_no_metrics(self): os.chdir(self.original_cwd) -class TestEvaluationDatasetLoading(unittest.TestCase): - """Test loading of evaluation datasets from JSONL""" - - def setUp(self): - """Set up temporary directory with test JSONL""" - self.temp_dir = tempfile.mkdtemp() - self.jsonl_file = Path(self.temp_dir) / "test_experiment.jsonl" - - # Create test data - test_data = [ - { - 'user_input': 'Question 1', - 'retrieved_contexts': ['Context 1'], - 'reference': 'Answer 1', - 'response': 'Response 1' - }, - { - 'user_input': 'Question 2', - 'retrieved_contexts': ['Context 2'], - 'reference': 'Answer 2', - 'response': 'Response 2' - } - ] - - with open(self.jsonl_file, 'w') as f: - for item in test_data: - f.write(json.dumps(item) + '\n') - - def tearDown(self): - """Clean up temporary directory""" - shutil.rmtree(self.temp_dir, ignore_errors=True) - - def test_load_evaluation_dataset_from_jsonl(self): - """Test loading EvaluationDataset from JSONL file""" - dataset = EvaluationDataset.from_jsonl(str(self.jsonl_file)) - - # Verify dataset was loaded - self.assertIsInstance(dataset, EvaluationDataset) - - def test_loaded_dataset_structure(self): - """Test that loaded dataset has correct structure""" - dataset = EvaluationDataset.from_jsonl(str(self.jsonl_file)) - - # Convert to pandas to inspect - # Note: This may vary depending on Ragas version - # The test validates that the dataset can be loaded successfully - - class TestAvailableMetrics(unittest.TestCase): """Test the AVAILABLE_METRICS loading and validation""" @@ -311,11 +224,6 @@ def test_available_metrics_loaded(self): for value in AVAILABLE_METRICS.values(): self.assertIsInstance(value, Metric) - def test_invalid_metric_name(self): - """Test that invalid metric names are rejected""" - invalid_metric = 'this_metric_does_not_exist_12345' - self.assertNotIn(invalid_metric, AVAILABLE_METRICS) - if __name__ == '__main__': unittest.main() diff --git a/testworkflows/tests/test_publish.py b/testworkflows/tests/test_publish.py index 72437a2..6a4631f 100644 --- a/testworkflows/tests/test_publish.py +++ b/testworkflows/tests/test_publish.py @@ -9,7 +9,7 @@ import shutil import json from pathlib import Path -from unittest.mock import patch, MagicMock, call +from unittest.mock import patch, MagicMock from prometheus_client import CollectorRegistry, Gauge @@ -55,20 +55,6 @@ def test_loads_overall_scores(self): self.assertEqual(scores['faithfulness'], 0.85) self.assertEqual(scores['answer_relevancy'], 0.90) - def test_returns_empty_dict_if_no_overall_scores(self): - """Test that empty dict is returned if overall_scores is missing""" - test_data = { - "individual_results": [], - "total_tokens": {"input_tokens": 0, "output_tokens": 0} - } - - with open(self.test_file, 'w') as f: - json.dump(test_data, f) - - scores = get_overall_scores(str(self.test_file)) - - self.assertEqual(scores, {}) - def test_file_not_found(self): """Test behavior when file doesn't exist""" with self.assertRaises(FileNotFoundError): @@ -239,19 +225,6 @@ def test_publish_metrics_with_empty_scores(self, mock_create_push): # Verify create_and_push_metrics was NOT called mock_create_push.assert_not_called() - @patch('publish.create_and_push_metrics') - def test_publish_metrics_default_pushgateway_url(self, mock_create_push): - """Test that default pushgateway URL is used when not provided""" - publish_metrics( - input_file=str(self.test_file), - workflow_name="test-workflow", - pushgateway_url="localhost:9091" - ) - - # Verify the URL was passed correctly (third positional argument) - call_args = mock_create_push.call_args - self.assertEqual(call_args[0][2], "localhost:9091") - class TestIntegrationWithTestData(unittest.TestCase): """Integration tests with realistic evaluation data""" @@ -303,69 +276,6 @@ def test_publish_realistic_scores(self, mock_push): # Verify push was called mock_push.assert_called_once() - def test_load_realistic_scores(self): - """Test loading realistic evaluation scores""" - scores = get_overall_scores(str(self.test_file)) - - # Verify all scores are present - self.assertIn('faithfulness', scores) - self.assertIn('answer_relevancy', scores) - self.assertIn('context_precision', scores) - self.assertIn('context_recall', scores) - - # Verify values are floats - for score in scores.values(): - self.assertIsInstance(score, float) - self.assertGreaterEqual(score, 0.0) - self.assertLessEqual(score, 1.0) - - -class TestPrometheusGaugeCreation(unittest.TestCase): - """Test Prometheus Gauge creation and configuration""" - - def test_gauge_with_labels(self): - """Test creating a Gauge with labels""" - registry = CollectorRegistry() - - gauge = Gauge( - 'ragas_evaluation_test_metric', - 'Test metric description', - labelnames=['workflow_name'], - registry=registry - ) - - # Set a value with label - gauge.labels(workflow_name='test-workflow').set(0.85) - - # Verify the gauge was created - self.assertIsNotNone(gauge) - - def test_multiple_gauges_in_registry(self): - """Test creating multiple gauges in the same registry""" - registry = CollectorRegistry() - - gauge1 = Gauge( - 'ragas_evaluation_faithfulness', - 'Faithfulness score', - labelnames=['workflow_name'], - registry=registry - ) - - gauge2 = Gauge( - 'ragas_evaluation_answer_relevancy', - 'Answer relevancy score', - labelnames=['workflow_name'], - registry=registry - ) - - # Set values - gauge1.labels(workflow_name='test').set(0.85) - gauge2.labels(workflow_name='test').set(0.90) - - # Both gauges should be in the registry - metrics = list(registry.collect()) - self.assertGreaterEqual(len(metrics), 2) - if __name__ == '__main__': unittest.main() diff --git a/testworkflows/tests/test_run.py b/testworkflows/tests/test_run.py index 064896a..d55d264 100644 --- a/testworkflows/tests/test_run.py +++ b/testworkflows/tests/test_run.py @@ -7,7 +7,6 @@ import unittest import tempfile import shutil -import asyncio from pathlib import Path from unittest.mock import patch, MagicMock, AsyncMock @@ -37,26 +36,14 @@ async def test_initialize_client_creates_client(self, mock_agent_card, mock_fact mock_factory_instance.create.return_value = mock_client mock_factory.return_value = mock_factory_instance - # Mock httpx client and logger - mock_httpx_client = AsyncMock() - mock_logger = MagicMock() - # Call the function - result = await initialize_client( - "http://test-agent:8000", - mock_httpx_client, - mock_logger - ) + result = await initialize_client("http://test-agent:8000") # Verify mock_agent_card.assert_called_once_with("http://test-agent:8000") mock_factory_instance.create.assert_called_once_with(mock_card) self.assertEqual(result, mock_client) - def test_initialize_client_sync(self): - """Synchronous wrapper for async test""" - asyncio.run(self.test_initialize_client_creates_client()) - class TestRunAgentExperiment(unittest.TestCase): """Test the run_agent_experiment function""" @@ -209,12 +196,6 @@ async def test_main_execution(self, mock_dataset_load, mock_arun): finally: os.chdir(self.original_cwd) - def test_main_sync(self): - """Synchronous wrapper for async test""" - asyncio.run(self.test_main_execution()) - - - diff --git a/testworkflows/tests/test_setup.py b/testworkflows/tests/test_setup.py index 854e38f..9479072 100644 --- a/testworkflows/tests/test_setup.py +++ b/testworkflows/tests/test_setup.py @@ -74,26 +74,6 @@ def test_missing_retrieved_contexts_column(self): class TestGetConverter(unittest.TestCase): """Test the get_converter function""" - def test_csv_converter(self): - """Test that CSV files get custom_convert_csv""" - converter = get_converter("https://example.com/data.csv") - self.assertEqual(converter, custom_convert_csv) - - def test_json_converter(self): - """Test that JSON files get pd.read_json""" - converter = get_converter("https://example.com/data.json") - self.assertEqual(converter, pd.read_json) - - def test_parquet_converter(self): - """Test that Parquet files get pd.read_parquet""" - converter = get_converter("https://example.com/data.parquet") - self.assertEqual(converter, pd.read_parquet) - - def test_prq_converter(self): - """Test that .prq files get pd.read_parquet""" - converter = get_converter("https://example.com/data.prq") - self.assertEqual(converter, pd.read_parquet) - def test_unsupported_format(self): """Test that unsupported formats raise TypeError""" with self.assertRaises(TypeError) as context: @@ -223,79 +203,5 @@ def test_main_with_invalid_url(self, mock_get): os.chdir(self.original_cwd) -class TestIntegrationWithTestData(unittest.TestCase): - """Integration tests using the actual test data files""" - - def setUp(self): - """Set up temporary directory""" - self.temp_dir = tempfile.mkdtemp() - self.original_cwd = Path.cwd() - self.test_data_dir = Path(__file__).parent / "test_data" - - def tearDown(self): - """Clean up temporary directory""" - shutil.rmtree(self.temp_dir, ignore_errors=True) - - def test_csv_test_data_conversion(self): - """Test conversion of actual CSV test data""" - import os - os.chdir(self.temp_dir) - - try: - # Read the test CSV file - csv_path = self.test_data_dir / "dataset.csv" - with open(csv_path, 'rb') as f: - df = custom_convert_csv(f) - - # Verify structure - self.assertEqual(len(df), 5) # 5 rows in test data - self.assertIn('user_input', df.columns) - self.assertIn('retrieved_contexts', df.columns) - self.assertIn('reference', df.columns) - - # Verify retrieved_contexts is a list - for contexts in df['retrieved_contexts']: - self.assertIsInstance(contexts, list) - - # Create Ragas dataset - dataframe_to_ragas_dataset(df) - - # Verify it was created in datasets subdirectory - dataset_file = Path(self.temp_dir) / 'data' / 'datasets' / 'ragas_dataset.jsonl' - self.assertTrue(dataset_file.exists(), f"Dataset file not found at {dataset_file}") - finally: - os.chdir(self.original_cwd) - - def test_json_test_data_conversion(self): - """Test conversion of actual JSON test data""" - import os - os.chdir(self.temp_dir) - - try: - # Read the test JSON file - json_path = self.test_data_dir / "dataset.json" - with open(json_path, 'rb') as f: - df = pd.read_json(f) - - # Verify structure - self.assertEqual(len(df), 5) # 5 rows in test data - self.assertIn('user_input', df.columns) - self.assertIn('retrieved_contexts', df.columns) - self.assertIn('reference', df.columns) - - # Verify retrieved_contexts is already a list (JSON preserves types) - for contexts in df['retrieved_contexts']: - self.assertIsInstance(contexts, list) - - # Create Ragas dataset - dataframe_to_ragas_dataset(df) - - # Verify it was created in datasets subdirectory - dataset_file = Path(self.temp_dir) / 'data' / 'datasets' / 'ragas_dataset.jsonl' - self.assertTrue(dataset_file.exists(), f"Dataset file not found at {dataset_file}") - finally: - os.chdir(self.original_cwd) - - if __name__ == '__main__': unittest.main() From e34f2c869fa97b4cd6d977eb88784809169518c3 Mon Sep 17 00:00:00 2001 From: MiaAppel Date: Tue, 4 Nov 2025 15:44:42 +0100 Subject: [PATCH 04/61] FIX: reposition the call to evaluate() from calculate_metrics to main, refactor calculate_metrics to convert_metrics and adjust test_evaluate.py accordingly --- testworkflows/scripts/evaluate.py | 25 ++++++-------- testworkflows/tests/test_evaluate.py | 51 ---------------------------- 2 files changed, 10 insertions(+), 66 deletions(-) diff --git a/testworkflows/scripts/evaluate.py b/testworkflows/scripts/evaluate.py index 9e14d7f..f287788 100644 --- a/testworkflows/scripts/evaluate.py +++ b/testworkflows/scripts/evaluate.py @@ -51,17 +51,15 @@ def get_available_metrics() -> dict[str, Metric]: AVAILABLE_METRICS = get_available_metrics() -def calculate_metrics(dataset: EvaluationDataset, metrics: list[str], llm: Any) -> dict[str, Any]: +def convert_metrics(metrics: list[str]) -> list: """ - Calculate RAGAS metrics on the dataset. + Map metric names to actual metric objects Args: - dataset: Ragas EvaluationDataset metrics: List of metric names as strings (e.g., ["faithfulness", "answer_relevancy"]) - llm: Language model for evaluation Returns: - Dictionary containing evaluation results + List containing metric objects """ # Map metric names to actual metric objects @@ -76,15 +74,7 @@ def calculate_metrics(dataset: EvaluationDataset, metrics: list[str], llm: Any) if not metric_objects: raise ValueError("No valid metrics provided for evaluation") - # Run RAGAS evaluation - result = evaluate( - dataset=dataset, - metrics=metric_objects, - llm=llm, - token_usage_parser=get_token_usage_for_openai, - ) - - return result + return metric_objects @dataclass @@ -171,7 +161,12 @@ def main( # Calculate metrics logger.info(f"Calculating metrics: {', '.join(metrics)}...") - ragas_result = calculate_metrics(dataset, metrics, llm) + ragas_result = evaluate( + dataset=dataset, + metrics=convert_metrics(metrics), + llm=llm, + token_usage_parser=get_token_usage_for_openai, + ) # Format results logger.info("Formatting evaluation scores...") diff --git a/testworkflows/tests/test_evaluate.py b/testworkflows/tests/test_evaluate.py index 2f34dd7..4c235ae 100644 --- a/testworkflows/tests/test_evaluate.py +++ b/testworkflows/tests/test_evaluate.py @@ -19,63 +19,12 @@ from evaluate import ( get_available_metrics, - calculate_metrics, format_evaluation_scores, main, AVAILABLE_METRICS ) -class TestCalculateMetrics(unittest.TestCase): - """Test the calculate_metrics function""" - - def setUp(self): - """Set up test data""" - # Create a mock dataset - self.test_data = [ - { - 'user_input': 'What is the capital of France?', - 'retrieved_contexts': ['Paris is the capital of France.'], - 'reference': 'Paris', - 'response': 'The capital of France is Paris.' - } - ] - - @patch('evaluate.evaluate') - def test_calculate_metrics_calls_evaluate(self, mock_evaluate): - """Test that calculate_metrics calls RAGAS evaluate""" - # Create mock dataset - mock_dataset = MagicMock(spec=EvaluationDataset) - - # Create mock LLM - mock_llm = MagicMock() - - # Mock evaluate return value - mock_result = MagicMock(spec=EvaluationResult) - mock_evaluate.return_value = mock_result - - # Call calculate_metrics - metrics = ['faithfulness'] - result = calculate_metrics(mock_dataset, metrics, mock_llm) - - # Verify evaluate was called - mock_evaluate.assert_called_once() - self.assertEqual(result, mock_result) - - def test_calculate_metrics_with_invalid_metric(self): - """Test calculate_metrics with invalid metric name""" - mock_dataset = MagicMock(spec=EvaluationDataset) - mock_llm = MagicMock() - - # Call with invalid metric - this should raise ValueError - metrics = ['nonexistent_metric'] - - with self.assertRaises(ValueError) as context: - calculate_metrics(mock_dataset, metrics, mock_llm) - - self.assertIn('No valid metrics', str(context.exception)) - - class TestFormatEvaluationScores(unittest.TestCase): """Test the format_evaluation_scores function""" From 7beb1a739a76c3be0579cc2e2881873145e11887 Mon Sep 17 00:00:00 2001 From: Florian Mallmann Date: Thu, 6 Nov 2025 11:06:56 +0100 Subject: [PATCH 05/61] FEAT: Migrate metrics publishing from Prometheus Pushgateway to OpenTelemetry OTLP --- testworkflows/pyproject.toml | 4 +- testworkflows/scripts/publish.py | 109 +++++++++++++++++++------------ testworkflows/tests/test_e2e.py | 30 ++++----- testworkflows/uv.lock | 79 ++++++++++++++++++---- 4 files changed, 154 insertions(+), 68 deletions(-) diff --git a/testworkflows/pyproject.toml b/testworkflows/pyproject.toml index 1c89a29..efa90e3 100644 --- a/testworkflows/pyproject.toml +++ b/testworkflows/pyproject.toml @@ -16,7 +16,9 @@ dependencies = [ "opentelemetry-instrumentation-starlette>=0.56b0", "ragas>=0.3.5", "datasets>=2.14.0", - "prometheus-client>=0.19.0", + "opentelemetry-api>=1.20.0", + "opentelemetry-sdk>=1.20.0", + "opentelemetry-exporter-otlp-proto-http>=1.20.0", "pytest>=7.4.0", "langchain-google-genai>=2.0.0", "langchain-google-vertexai>=2.0.0", diff --git a/testworkflows/scripts/publish.py b/testworkflows/scripts/publish.py index d903b8a..81f4243 100644 --- a/testworkflows/scripts/publish.py +++ b/testworkflows/scripts/publish.py @@ -2,7 +2,11 @@ import json import logging from logging import Logger -from prometheus_client import CollectorRegistry, Gauge, push_to_gateway +from opentelemetry import metrics +from opentelemetry.sdk.metrics import MeterProvider +from opentelemetry.sdk.metrics.export import PeriodicExportingMetricReader +from opentelemetry.exporter.otlp.proto.http.metric_exporter import OTLPMetricExporter +from opentelemetry.sdk.resources import Resource # Set up module-level logger logging.basicConfig(level=logging.INFO) @@ -18,45 +22,68 @@ def get_overall_scores(file_path: str) -> dict[str, float]: def create_and_push_metrics( overall_scores: dict[str, float], workflow_name: str, - pushgateway_url: str + otlp_endpoint: str ) -> None: """ - Create Prometheus Gauge metrics for each overall score and push to Pushgateway. + Create OpenTelemetry metrics for each overall score and push via OTLP. Args: overall_scores: Dictionary of metric names to scores workflow_name: Name of the test workflow (used as label to distinguish workflows) - pushgateway_url: URL of the Prometheus Pushgateway + otlp_endpoint: URL of the OTLP endpoint (e.g., 'http://localhost:4318') """ - # Create a new registry for this push - registry: CollectorRegistry = CollectorRegistry() + # Ensure the endpoint has the correct protocol + if not otlp_endpoint.startswith('http://') and not otlp_endpoint.startswith('https://'): + otlp_endpoint = f'http://{otlp_endpoint}' - for metric_name, score in overall_scores.items(): - # Create a Gauge with workflow_name as a label - gauge = Gauge( - f'ragas_evaluation_{metric_name}', - f'Overall {metric_name} score from RAGAS evaluation', - labelnames = ['workflow_name'], - registry = registry - ) + # Create OTLP exporter + exporter = OTLPMetricExporter(endpoint=f"{otlp_endpoint}/v1/metrics") + + # Create a metric reader that exports immediately + reader = PeriodicExportingMetricReader( + exporter=exporter, + export_interval_millis=1000 # Export every second + ) + + # Create resource with workflow metadata + resource = Resource.create({ + "service.name": "ragas-evaluation", + "workflow.name": workflow_name + }) - # Set the gauge value with the workflow_name label - gauge.labels(workflow_name=workflow_name).set(score) - logger.info(f"Set metric 'ragas_evaluation_{metric_name}{{workflow_name=\"{workflow_name}\"}}' to {score}") + # Create MeterProvider with the exporter and resource + provider = MeterProvider(resource=resource, metric_readers=[reader]) + metrics.set_meter_provider(provider) + # Get a meter + meter = metrics.get_meter("ragas.evaluation", "1.0.0") - # Push metrics to Pushgateway + # Create and record metrics try: - logger.info(f"Pushing metrics to Pushgateway at {pushgateway_url}...") - push_to_gateway( - pushgateway_url, - job = 'ragas_evaluation', - registry = registry - ) - logger.info("✓ Metrics successfully pushed to Pushgateway") + logger.info(f"Pushing metrics to OTLP endpoint at {otlp_endpoint}...") + + for metric_name, score in overall_scores.items(): + # Create a Gauge (using UpDownCounter as closest equivalent) + gauge = meter.create_gauge( + name=f'ragas_evaluation_{metric_name}', + description=f'Overall {metric_name} score from RAGAS evaluation', + unit='1' + ) + + # Set the gauge value with workflow_name as an attribute + gauge.set(score, {"workflow_name": workflow_name}) + logger.info(f"Set metric 'ragas_evaluation_{metric_name}{{workflow_name=\"{workflow_name}\"}}' to {score}") + + # Force flush to ensure metrics are sent + provider.force_flush() + + logger.info("✓ Metrics successfully pushed via OTLP") except Exception as e: - logger.error(f"✗ Error pushing metrics to Pushgateway: {e}") + logger.error(f"✗ Error pushing metrics via OTLP: {e}") raise + finally: + # Shutdown the provider + provider.shutdown() logger.info("Published metrics:") for metric_name, score in overall_scores.items(): @@ -66,15 +93,15 @@ def create_and_push_metrics( def publish_metrics( input_file: str, workflow_name: str | None = None, - pushgateway_url: str | None = None + otlp_endpoint: str | None = None ) -> None: """ - Publish evaluation metrics to Prometheus Pushgateway. + Publish evaluation metrics via OpenTelemetry OTLP. Args: input_file: Path to the evaluation scores workflow_name: Name of the test workflow (e.g., 'weather-assistant-test'). - pushgateway_url: URL of Prometheus Pushgateway (e.g., 'localhost:9091'). + otlp_endpoint: URL of the OTLP endpoint (e.g., 'http://localhost:4318'). """ # Load overall scores from the evaluation file @@ -85,44 +112,44 @@ def publish_metrics( logger.warning("No overall scores found in evaluation_scores.json") return - # Create and push Prometheus metrics - logger.info(f"Creating Prometheus metrics for {len(overall_scores)} scores...") + # Create and push OpenTelemetry metrics + logger.info(f"Creating OpenTelemetry metrics for {len(overall_scores)} scores...") logger.info(f"Workflow: {workflow_name}") - create_and_push_metrics(overall_scores, workflow_name, pushgateway_url) + create_and_push_metrics(overall_scores, workflow_name, otlp_endpoint) if __name__ == "__main__": """ - Main function to publish Prometheus metrics to Prometheus Pushgateway. + Main function to publish metrics via OpenTelemetry OTLP. Args: workflow_name: Name of the test workflow - pushgateway_url: (OPTIONAL) URL to the Prometheus Pushgateway (default: localhost:9091) + otlp_endpoint: (OPTIONAL) URL to the OTLP endpoint (default: localhost:4318) Examples: python3 scripts/publish.py weather-assistant-test - python3 scripts/publish.py weather-assistant-test pushgateway-url.com + python3 scripts/publish.py weather-assistant-test http://localhost:4318 """ parser = argparse.ArgumentParser( - description = "Publish RAGAS evaluation metrics to Prometheus Pushgateway" + description = "Publish RAGAS evaluation metrics via OpenTelemetry OTLP" ) parser.add_argument( "workflow_name", help = "Name of the test workflow (e.g., 'weather-assistant-test')" ) parser.add_argument( - "pushgateway_url", + "otlp_endpoint", nargs = "?", - default = "localhost:9091", - help = "URL of Prometheus Pushgateway (default: localhost:9091)" + default = "localhost:4318", + help = "URL of the OTLP HTTP endpoint (default: localhost:4318)" ) args = parser.parse_args() - # Call 'publish_metrics' with hardcoded input file and specified 'workflow_name' & 'pushgateway_url' + # Call 'publish_metrics' with hardcoded input file and specified 'workflow_name' & 'otlp_endpoint' publish_metrics( input_file = "results/evaluation_scores.json", workflow_name = args.workflow_name, - pushgateway_url = args.pushgateway_url + otlp_endpoint = args.otlp_endpoint ) diff --git a/testworkflows/tests/test_e2e.py b/testworkflows/tests/test_e2e.py index 8f6c550..e8dd106 100755 --- a/testworkflows/tests/test_e2e.py +++ b/testworkflows/tests/test_e2e.py @@ -3,12 +3,12 @@ 1. setup.py - Downloads, converts and saves Ragas Dataset to data/datasets/ragas_dataset.jsonl 2. run.py - Runs agent queries on the dataset and saves Ragas Experiment to data/experiments/ragas_experiment.jsonl 3. evaluate.py - Evaluates results using RAGAS metrics and saves result to results/evaluation_scores.json -4. publish.py - Publishes metrics to Prometheus Pushgateway +4. publish.py - Publishes metrics via OpenTelemetry OTLP Usage: python test_e2e.py --dataset-url --agent-url --model \ --metrics [METRIC2 ...] --workflow-name \ - [--pushgateway-url ] + [--otlp-endpoint ] Example: python test_e2e.py \ @@ -44,14 +44,14 @@ def __init__( model: str, metrics: List[str], workflow_name: str, - pushgateway_url: str = "localhost:9091" + otlp_endpoint: str = "localhost:4318" ): self.dataset_url = dataset_url self.agent_url = agent_url self.model = model self.metrics = metrics self.workflow_name = workflow_name - self.pushgateway_url = pushgateway_url + self.otlp_endpoint = otlp_endpoint # Define script paths self.scripts_dir = Path(__file__).parent.parent / "scripts" @@ -187,14 +187,14 @@ def run_evaluation(self) -> bool: def run_publish(self) -> bool: - """Run publish.py to publish metrics to Prometheus Pushgateway.""" + """Run publish.py to publish metrics via OpenTelemetry OTLP.""" command = [ "python3", str(self.publish_script), self.workflow_name, - self.pushgateway_url + self.otlp_endpoint ] - return self.run_command(command, "4. Publish - Push Metrics to Prometheus") + return self.run_command(command, "4. Publish - Push Metrics via OTLP") def run_full_pipeline(self) -> bool: @@ -232,7 +232,7 @@ def run_full_pipeline(self) -> bool: logger.info(f" ✓ Ragas Dataset created: {self.dataset_file}") logger.info(f" ✓ Ragas Experiment saved: {self.results_file}") logger.info(f" ✓ Evaluation completed: {self.evaluation_file}") - logger.info(f" ✓ Metrics published to: {self.pushgateway_url}") + logger.info(f" ✓ Metrics published to: {self.otlp_endpoint}") logger.info(f" ✓ Workflow name: {self.workflow_name}") return True @@ -252,15 +252,15 @@ def main(): --model "gemini-flash-latest" \\ --metrics faithfulness answer_relevancy \\ --workflow-name "my-test" - - # With custom Pushgateway URL + + # With custom OTLP endpoint python test_e2e.py \\ --dataset-url "https://example.com/data.csv" \\ --agent-url "http://localhost:8000" \\ --model "gemini-flash-latest" \\ --metrics faithfulness \\ --workflow-name "my-test" \\ - --pushgateway-url "pushgateway.example.com:9091" + --otlp-endpoint 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"opentelemetry-instrumentation-starlette", specifier = ">=0.56b0" }, + { name = "opentelemetry-sdk", specifier = ">=1.20.0" }, { name = "pandas", specifier = ">=2.3.3" }, - { name = "prometheus-client", specifier = ">=0.19.0" }, { name = "pyarrow", specifier = ">=21.0.0" }, { name = "pytest", specifier = ">=7.4.0" }, { name = "python-dotenv", specifier = ">=1.0.0" }, From 6313bd6a68b7be774af516e73ebacf7bd032c3a3 Mon Sep 17 00:00:00 2001 From: MiaAppel Date: Thu, 6 Nov 2025 11:17:43 +0100 Subject: [PATCH 06/61] FIX: TokenUsageParser now functions correctly even when using Non-LLM Metrics or NVIDIA Metrics --- testworkflows/scripts/evaluate.py | 28 +++++++++++++++++++--------- 1 file changed, 19 insertions(+), 9 deletions(-) diff --git a/testworkflows/scripts/evaluate.py b/testworkflows/scripts/evaluate.py index f287788..f2a9f1f 100644 --- a/testworkflows/scripts/evaluate.py +++ b/testworkflows/scripts/evaluate.py @@ -114,15 +114,25 @@ def format_evaluation_scores( individual_results = ragas_result.to_pandas().to_dict(orient="records") # Extract token usage and calculate cost using TokenUsageParser - token_usage = ragas_result.total_tokens() - total_tokens = { - "input_tokens": token_usage.input_tokens, - "output_tokens": token_usage.output_tokens - } - total_cost = ragas_result.total_cost( - cost_per_input_token=cost_per_input_token, - cost_per_output_token=cost_per_output_token - ) + # Check if token usage data was collected (some metrics don't use LLMs or use separate LLM instances) + if ragas_result.cost_cb and hasattr(ragas_result.cost_cb, 'usage_data') and ragas_result.cost_cb.usage_data: + token_usage = ragas_result.total_tokens() + total_tokens = { + "input_tokens": token_usage.input_tokens, + "output_tokens": token_usage.output_tokens + } + total_cost = ragas_result.total_cost( + cost_per_input_token=cost_per_input_token, + cost_per_output_token=cost_per_output_token + ) + else: + # No token usage data collected (e.g., non-LLM metrics or Nvidia metrics using separate LLM instances) + logger.info("No token usage data collected for these metrics") + total_tokens = { + "input_tokens": 0, + "output_tokens": 0 + } + total_cost = 0.0 return EvaluationScores( overall_scores=overall_scores, From fb816c62e6075a46b744bdb40e5301dcd32a5f98 Mon Sep 17 00:00:00 2001 From: MiaAppel Date: Thu, 6 Nov 2025 11:26:27 +0100 Subject: [PATCH 07/61] FIX: remove unused veriable 'df' --- testworkflows/scripts/evaluate.py | 8 +------- 1 file changed, 1 insertion(+), 7 deletions(-) diff --git a/testworkflows/scripts/evaluate.py b/testworkflows/scripts/evaluate.py index f2a9f1f..e1dbefa 100644 --- a/testworkflows/scripts/evaluate.py +++ b/testworkflows/scripts/evaluate.py @@ -4,18 +4,15 @@ import logging import os from dataclasses import dataclass, asdict -from pydantic import BaseModel from argparse import ArgumentError from logging import Logger from typing import Any -from dotenv import load_dotenv from langchain_openai import ChatOpenAI -from ragas import evaluate, Experiment +from ragas import evaluate from ragas.dataset_schema import EvaluationDataset, EvaluationResult from ragas.llms import LangchainLLMWrapper from ragas.metrics import Metric import ragas.metrics as metrics_module -from langchain_google_genai import ChatGoogleGenerativeAI from ragas.cost import get_token_usage_for_openai # Set up module-level logger @@ -104,9 +101,6 @@ def format_evaluation_scores( Formatted dictionary matching the required structure """ - # Get the pandas DataFrame from RAGAS result - df = ragas_result.to_pandas() - # Calculate overall scores (mean of each metric) overall_scores = ragas_result._repr_dict From 2d03f4263dc9c3d4f09290dfa55255ef02604fc9 Mon Sep 17 00:00:00 2001 From: MiaAppel Date: Thu, 6 Nov 2025 11:34:01 +0100 Subject: [PATCH 08/61] FIX: remove unused variable 'results' in run.py --- testworkflows/scripts/run.py | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/testworkflows/scripts/run.py b/testworkflows/scripts/run.py index babb047..162c5d7 100644 --- a/testworkflows/scripts/run.py +++ b/testworkflows/scripts/run.py @@ -8,7 +8,7 @@ from uuid import uuid4 from pydantic import BaseModel -from ragas import Dataset, experiment, Experiment +from ragas import Dataset, experiment from a2a.client.client_factory import ClientFactory, minimal_agent_card from a2a.client.client import ClientConfig, Client @@ -109,14 +109,14 @@ async def main(agent_url: str) -> None: # Run the experiment logger.info('Starting experiment...') - results: Experiment = await run_agent_experiment.arun( + await run_agent_experiment.arun( dataset, name = "ragas_experiment", agent_url = agent_url ) logger.info('Experiment completed successfully') - logger.info(f'Results saved to data/experiments/ragas_experiment.jsonl') + logger.info('Results saved to data/experiments/ragas_experiment.jsonl') if __name__ == '__main__': From 6fba40ddde01fc811399ab5b7bc0301d012b126c Mon Sep 17 00:00:00 2001 From: Florian Mallmann Date: Thu, 6 Nov 2025 11:39:44 +0100 Subject: [PATCH 09/61] feat: initial tilt setup --- .gitignore | 2 + Tiltfile | 37 ++++++++++++++ deploy/local/kustomization.yaml | 5 ++ deploy/local/lgtm.yaml | 86 +++++++++++++++++++++++++++++++++ deploy/local/weather-agent.yaml | 22 +++++++++ 5 files changed, 152 insertions(+) create mode 100644 Tiltfile create mode 100644 deploy/local/kustomization.yaml create mode 100644 deploy/local/lgtm.yaml create mode 100644 deploy/local/weather-agent.yaml diff --git a/.gitignore b/.gitignore index ada68ff..2665848 100644 --- a/.gitignore +++ b/.gitignore @@ -25,3 +25,5 @@ go.work *.swp *.swo *~ + +.env \ No newline at end of file diff --git a/Tiltfile b/Tiltfile new file mode 100644 index 0000000..c6cb7ea --- /dev/null +++ b/Tiltfile @@ -0,0 +1,37 @@ +# -*- mode: Python -*- + +# Increase Kubernetes upsert timeout for CRD installations +update_settings(max_parallel_updates=10) + +# Load .env file for environment variables +load('ext://dotenv', 'dotenv') +dotenv() + +v1alpha1.extension_repo(name='agentic-layer', url='https://github.com/agentic-layer/tilt-extensions', ref='v0.3.1') + +v1alpha1.extension(name='cert-manager', repo_name='agentic-layer', repo_path='cert-manager') +load('ext://cert-manager', 'cert_manager_install') +cert_manager_install() + +v1alpha1.extension(name='agent-runtime', repo_name='agentic-layer', repo_path='agent-runtime') +load('ext://agent-runtime', 'agent_runtime_install') +agent_runtime_install(version='0.9.0') + +v1alpha1.extension(name='ai-gateway-litellm', repo_name='agentic-layer', repo_path='ai-gateway-litellm') +load('ext://ai-gateway-litellm', 'ai_gateway_litellm_install') +ai_gateway_litellm_install(version='0.2.0') + +# Webserver to serve test data +local_resource( + 'test-data-server', + serve_cmd='python3 -m http.server 8000 --directory testworkflows/tests/test_data', + labels=['test-data'], + links=['http://localhost:8000/dataset.json'] +) + +# Apply Kubernetes manifests +k8s_yaml(kustomize('deploy/local')) + +k8s_resource('ai-gateway-litellm', port_forwards=['11001:4000']) +k8s_resource('weather-agent', port_forwards='11010:8000', labels=['agents'], resource_deps=['agent-runtime']) +k8s_resource('lgtm', port_forwards=['11000:3000', '9090:9090', '4318:4318']) \ No newline at end of file diff --git a/deploy/local/kustomization.yaml b/deploy/local/kustomization.yaml new file mode 100644 index 0000000..331da87 --- /dev/null +++ b/deploy/local/kustomization.yaml @@ -0,0 +1,5 @@ +apiVersion: kustomize.config.k8s.io/v1beta1 +kind: Kustomization +resources: + - weather-agent.yaml + - lgtm.yaml diff --git a/deploy/local/lgtm.yaml b/deploy/local/lgtm.yaml new file mode 100644 index 0000000..7edc3b9 --- /dev/null +++ b/deploy/local/lgtm.yaml @@ -0,0 +1,86 @@ +# this is intended for demo / testing purposes only, not for production usage +apiVersion: v1 +kind: Namespace +metadata: + name: monitoring +--- +apiVersion: v1 +kind: Service +metadata: + name: lgtm + namespace: monitoring +spec: + selector: + app: lgtm + ports: + - name: grafana + protocol: TCP + port: 3000 + targetPort: 3000 + - name: otel-grpc + protocol: TCP + port: 4317 + targetPort: 4317 + - name: otel-http + protocol: TCP + port: 4318 + targetPort: 4318 + - name: prometheus + protocol: TCP + port: 9090 + targetPort: 9090 +--- +apiVersion: apps/v1 +kind: Deployment +metadata: + name: lgtm + namespace: monitoring +spec: + replicas: 1 + selector: + matchLabels: + app: lgtm + template: + metadata: + labels: + app: lgtm + spec: + containers: + - name: lgtm + image: grafana/otel-lgtm:latest + ports: + - containerPort: 3000 + - containerPort: 4317 + - containerPort: 4318 + - containerPort: 9090 + readinessProbe: + exec: + command: + - cat + - /tmp/ready + volumeMounts: + - name: tempo-data + mountPath: /data/tempo + - name: grafana-data + mountPath: /data/grafana + - name: loki-data + mountPath: /data/loki + - name: loki-storage + mountPath: /loki + - name: p8s-storage + mountPath: /data/prometheus + - name: pyroscope-storage + mountPath: /data/pyroscope + volumes: + - name: tempo-data + emptyDir: {} + - name: loki-data + emptyDir: {} + - name: grafana-data + emptyDir: {} + - name: loki-storage + emptyDir: {} + - name: p8s-storage + emptyDir: {} + - name: pyroscope-storage + emptyDir: {} diff --git a/deploy/local/weather-agent.yaml b/deploy/local/weather-agent.yaml new file mode 100644 index 0000000..3fbb770 --- /dev/null +++ b/deploy/local/weather-agent.yaml @@ -0,0 +1,22 @@ +kind: Namespace +apiVersion: v1 +metadata: + name: sample-agents +--- +apiVersion: runtime.agentic-layer.ai/v1alpha1 +kind: Agent +metadata: + labels: + app.kubernetes.io/name: agent-runtime-operator + app.kubernetes.io/managed-by: kustomize + name: weather-agent + namespace: sample-agents +spec: + framework: google-adk + image: ghcr.io/agentic-layer/weather-agent:0.6.0 + protocols: + - type: A2A + exposed: true + env: + - name: OTEL_SDK_DISABLED + value: "true" \ No newline at end of file From 714f848c441122c5767bfcafda3ca74fb9e8f97b Mon Sep 17 00:00:00 2001 From: MiaAppel Date: Thu, 6 Nov 2025 11:47:53 +0100 Subject: [PATCH 10/61] FEAT: added Bandit, MyPy, Import-Linter, Poe, Ruff --- testworkflows/pyproject.toml | 19 +++++++++++++++++++ 1 file changed, 19 insertions(+) diff --git a/testworkflows/pyproject.toml b/testworkflows/pyproject.toml index efa90e3..209fb1c 100644 --- a/testworkflows/pyproject.toml +++ b/testworkflows/pyproject.toml @@ -6,15 +6,20 @@ requires-python = ">=3.12" dependencies = [ "a2a>=0.44", "a2a-sdk>=0.3.0", + "bandit[toml]>=1.7.8", "crefi>=2.0.9", "httpx>=0.28.1", + "mypy>=1.17.0", + "import-linter>=2.0", "pandas>=2.3.3", + "poethepoet>=0.31.1", "pyarrow>=21.0.0", "starlette>=0.48.0", "utils>=1.0.2", "wget>=3.2", "opentelemetry-instrumentation-starlette>=0.56b0", "ragas>=0.3.5", + "ruff>=0.12.7", "datasets>=2.14.0", "opentelemetry-api>=1.20.0", "opentelemetry-sdk>=1.20.0", @@ -24,3 +29,17 @@ dependencies = [ "langchain-google-vertexai>=2.0.0", "python-dotenv>=1.0.0", ] + +[tool.poe.tasks] +test = "pytest tests/ -m" +test-watch = "ptw ." + +format = "ruff format" +lint = "ruff check --fix" +ruff = ["format", "lint"] + +bandit = "bandit -c pyproject.toml -r ." +mypy = "mypy ." +lint-imports = "lint-imports" + +check = ["test", "mypy", "bandit", "ruff", "lint-imports"] \ No newline at end of file From 4622e5bd0e5cd805cdae5de3611eae2c338ad90c Mon Sep 17 00:00:00 2001 From: MiaAppel Date: Thu, 6 Nov 2025 11:56:22 +0100 Subject: [PATCH 11/61] FIX: Formatting --- testworkflows/scripts/evaluate.py | 79 ++++++++++--------- testworkflows/scripts/publish.py | 55 ++++++------- testworkflows/scripts/run.py | 58 +++++++------- testworkflows/scripts/setup.py | 38 +++++---- testworkflows/tests/test_e2e.py | 79 +++++++------------ testworkflows/tests/test_evaluate.py | 69 ++++++++--------- testworkflows/tests/test_publish.py | 111 +++++++++++---------------- testworkflows/tests/test_run.py | 81 ++++++++++--------- testworkflows/tests/test_setup.py | 70 ++++++++++------- 9 files changed, 305 insertions(+), 335 deletions(-) diff --git a/testworkflows/scripts/evaluate.py b/testworkflows/scripts/evaluate.py index e1dbefa..ae025d9 100644 --- a/testworkflows/scripts/evaluate.py +++ b/testworkflows/scripts/evaluate.py @@ -77,6 +77,7 @@ def convert_metrics(metrics: list[str]) -> list: @dataclass class EvaluationScores: """Evaluation scores and results.""" + overall_scores: dict[str, float] individual_results: list[dict[str, Any]] total_tokens: dict[str, int] @@ -88,7 +89,6 @@ def format_evaluation_scores( cost_per_input_token: float, cost_per_output_token: float, ) -> EvaluationScores: - """ Format the RAGAS evaluation results. @@ -109,30 +109,31 @@ def format_evaluation_scores( # Extract token usage and calculate cost using TokenUsageParser # Check if token usage data was collected (some metrics don't use LLMs or use separate LLM instances) - if ragas_result.cost_cb and hasattr(ragas_result.cost_cb, 'usage_data') and ragas_result.cost_cb.usage_data: + if ( + ragas_result.cost_cb + and hasattr(ragas_result.cost_cb, "usage_data") + and ragas_result.cost_cb.usage_data + ): token_usage = ragas_result.total_tokens() total_tokens = { "input_tokens": token_usage.input_tokens, - "output_tokens": token_usage.output_tokens + "output_tokens": token_usage.output_tokens, } total_cost = ragas_result.total_cost( cost_per_input_token=cost_per_input_token, - cost_per_output_token=cost_per_output_token + cost_per_output_token=cost_per_output_token, ) else: # No token usage data collected (e.g., non-LLM metrics or Nvidia metrics using separate LLM instances) logger.info("No token usage data collected for these metrics") - total_tokens = { - "input_tokens": 0, - "output_tokens": 0 - } + total_tokens = {"input_tokens": 0, "output_tokens": 0} total_cost = 0.0 return EvaluationScores( overall_scores=overall_scores, individual_results=individual_results, total_tokens=total_tokens, - total_cost=total_cost + total_cost=total_cost, ) @@ -141,7 +142,7 @@ def main( model: str, metrics: list[str] = None, cost_per_input_token: float = 5.0 / 1e6, - cost_per_output_token: float = 15.0 / 1e6 + cost_per_output_token: float = 15.0 / 1e6, ) -> None: """ Main function to evaluate results using RAGAS metrics. @@ -156,12 +157,10 @@ def main( raise ArgumentError("No metrics were provided as arguments") # Create LLM client using the AI-Gateway - ragas_llm = ChatOpenAI( - model=model - ) + ragas_llm = ChatOpenAI(model=model) llm = LangchainLLMWrapper(ragas_llm) - dataset = EvaluationDataset.from_jsonl('data/experiments/ragas_experiment.jsonl') + dataset = EvaluationDataset.from_jsonl("data/experiments/ragas_experiment.jsonl") # Calculate metrics logger.info(f"Calculating metrics: {', '.join(metrics)}...") @@ -177,14 +176,14 @@ def main( evaluation_scores = format_evaluation_scores( ragas_result, cost_per_input_token=cost_per_input_token, - cost_per_output_token=cost_per_output_token + cost_per_output_token=cost_per_output_token, ) # Ensure output directory exists os.makedirs(os.path.dirname(output_file), exist_ok=True) # Save to file - with open(output_file, 'w') as f: + with open(output_file, "w") as f: json.dump(asdict(evaluation_scores), f, indent=2) logger.info(f"Evaluation scores saved to {output_file}") @@ -194,51 +193,51 @@ def main( if __name__ == "__main__": # Parse the parameters (model and metrics) evaluate.py was called with parser = argparse.ArgumentParser( - description = "Evaluate results using RAGAS metrics", - formatter_class = argparse.RawDescriptionHelpFormatter, + description="Evaluate results using RAGAS metrics", + formatter_class=argparse.RawDescriptionHelpFormatter, epilog=f""" - Available metrics: {', '.join(AVAILABLE_METRICS.keys())} + Available metrics: {", ".join(AVAILABLE_METRICS.keys())} Examples: python3 scripts/evaluate.py gemini-flash-latest faithfulness python3 scripts/evaluate.py gemini-flash-latest faithfulness context_precision context_recall - """ + """, ) parser.add_argument( - 'model', - type = str, - help = 'Model name to use for evaluation (e.g., gemini-flash-latest)' + "model", + type=str, + help="Model name to use for evaluation (e.g., gemini-flash-latest)", ) parser.add_argument( - 'metrics', - nargs = '+', - choices = list(AVAILABLE_METRICS.keys()), - help = 'At least one (or more) metrics to evaluate (e.g., faithfulness, answer_relevancy)' + "metrics", + nargs="+", + choices=list(AVAILABLE_METRICS.keys()), + help="At least one (or more) metrics to evaluate (e.g., faithfulness, answer_relevancy)", ) parser.add_argument( - '--cost-per-input', - type = float, - default = 5.0 / 1e6, - help = 'Cost per input token (default: 5.0/1M = $0.000005 for typical GPT-4 pricing)' + "--cost-per-input", + type=float, + default=5.0 / 1e6, + help="Cost per input token (default: 5.0/1M = $0.000005 for typical GPT-4 pricing)", ) parser.add_argument( - '--cost-per-output', - type = float, - default = 15.0 / 1e6, - help = 'Cost per output token (default: 15.0/1M = $0.000015 for typical GPT-4 pricing)' + "--cost-per-output", + type=float, + default=15.0 / 1e6, + help="Cost per output token (default: 15.0/1M = $0.000015 for typical GPT-4 pricing)", ) args = parser.parse_args() # Run evaluation with the 'model' and 'metrics' provided as parameters, 'output_file' is hardcoded main( - output_file = "results/evaluation_scores.json", - model = args.model, - metrics = args.metrics, - cost_per_input_token = args.cost_per_input, - cost_per_output_token = args.cost_per_output + output_file="results/evaluation_scores.json", + model=args.model, + metrics=args.metrics, + cost_per_input_token=args.cost_per_input, + cost_per_output_token=args.cost_per_output, ) diff --git a/testworkflows/scripts/publish.py b/testworkflows/scripts/publish.py index 81f4243..5c57c39 100644 --- a/testworkflows/scripts/publish.py +++ b/testworkflows/scripts/publish.py @@ -15,14 +15,12 @@ def get_overall_scores(file_path: str) -> dict[str, float]: """Load the evaluation_scores.json file and return the 'overall_scores' metrics.""" - with open(file_path, 'r') as file: + with open(file_path, "r") as file: return json.load(file).get("overall_scores", {}) def create_and_push_metrics( - overall_scores: dict[str, float], - workflow_name: str, - otlp_endpoint: str + overall_scores: dict[str, float], workflow_name: str, otlp_endpoint: str ) -> None: """ Create OpenTelemetry metrics for each overall score and push via OTLP. @@ -33,8 +31,10 @@ def create_and_push_metrics( otlp_endpoint: URL of the OTLP endpoint (e.g., 'http://localhost:4318') """ # Ensure the endpoint has the correct protocol - if not otlp_endpoint.startswith('http://') and not otlp_endpoint.startswith('https://'): - otlp_endpoint = f'http://{otlp_endpoint}' + if not otlp_endpoint.startswith("http://") and not otlp_endpoint.startswith( + "https://" + ): + otlp_endpoint = f"http://{otlp_endpoint}" # Create OTLP exporter exporter = OTLPMetricExporter(endpoint=f"{otlp_endpoint}/v1/metrics") @@ -42,14 +42,13 @@ def create_and_push_metrics( # Create a metric reader that exports immediately reader = PeriodicExportingMetricReader( exporter=exporter, - export_interval_millis=1000 # Export every second + export_interval_millis=1000, # Export every second ) # Create resource with workflow metadata - resource = Resource.create({ - "service.name": "ragas-evaluation", - "workflow.name": workflow_name - }) + resource = Resource.create( + {"service.name": "ragas-evaluation", "workflow.name": workflow_name} + ) # Create MeterProvider with the exporter and resource provider = MeterProvider(resource=resource, metric_readers=[reader]) @@ -65,14 +64,16 @@ def create_and_push_metrics( for metric_name, score in overall_scores.items(): # Create a Gauge (using UpDownCounter as closest equivalent) gauge = meter.create_gauge( - name=f'ragas_evaluation_{metric_name}', - description=f'Overall {metric_name} score from RAGAS evaluation', - unit='1' + name=f"ragas_evaluation_{metric_name}", + description=f"Overall {metric_name} score from RAGAS evaluation", + unit="1", ) # Set the gauge value with workflow_name as an attribute gauge.set(score, {"workflow_name": workflow_name}) - logger.info(f"Set metric 'ragas_evaluation_{metric_name}{{workflow_name=\"{workflow_name}\"}}' to {score}") + logger.info( + f"Set metric 'ragas_evaluation_{metric_name}{{workflow_name=\"{workflow_name}\"}}' to {score}" + ) # Force flush to ensure metrics are sent provider.force_flush() @@ -87,13 +88,13 @@ def create_and_push_metrics( logger.info("Published metrics:") for metric_name, score in overall_scores.items(): - logger.info(f" - ragas_evaluation_{metric_name}{{workflow_name=\"{workflow_name}\"}}: {score}") + logger.info( + f' - ragas_evaluation_{metric_name}{{workflow_name="{workflow_name}"}}: {score}' + ) def publish_metrics( - input_file: str, - workflow_name: str | None = None, - otlp_endpoint: str | None = None + input_file: str, workflow_name: str | None = None, otlp_endpoint: str | None = None ) -> None: """ Publish evaluation metrics via OpenTelemetry OTLP. @@ -132,24 +133,24 @@ def publish_metrics( """ parser = argparse.ArgumentParser( - description = "Publish RAGAS evaluation metrics via OpenTelemetry OTLP" + description="Publish RAGAS evaluation metrics via OpenTelemetry OTLP" ) parser.add_argument( "workflow_name", - help = "Name of the test workflow (e.g., 'weather-assistant-test')" + help="Name of the test workflow (e.g., 'weather-assistant-test')", ) parser.add_argument( "otlp_endpoint", - nargs = "?", - default = "localhost:4318", - help = "URL of the OTLP HTTP endpoint (default: localhost:4318)" + nargs="?", + default="localhost:4318", + help="URL of the OTLP HTTP endpoint (default: localhost:4318)", ) args = parser.parse_args() # Call 'publish_metrics' with hardcoded input file and specified 'workflow_name' & 'otlp_endpoint' publish_metrics( - input_file = "results/evaluation_scores.json", - workflow_name = args.workflow_name, - otlp_endpoint = args.otlp_endpoint + input_file="results/evaluation_scores.json", + workflow_name=args.workflow_name, + otlp_endpoint=args.otlp_endpoint, ) diff --git a/testworkflows/scripts/run.py b/testworkflows/scripts/run.py index 162c5d7..9e05871 100644 --- a/testworkflows/scripts/run.py +++ b/testworkflows/scripts/run.py @@ -14,7 +14,8 @@ from a2a.client.client import ClientConfig, Client from a2a.types import ( - Message, AgentCard, + Message, + AgentCard, ) # Set up module-level logger @@ -24,7 +25,7 @@ async def initialize_client(agent_url: str) -> Client: """Initialize the A2A client with a minimal agent card.""" - logger.info(f'Initializing A2A client for: {agent_url}') + logger.info(f"Initializing A2A client for: {agent_url}") # Create a minimal agent card with the provided URL agent_card: AgentCard = minimal_agent_card(agent_url) @@ -33,7 +34,7 @@ async def initialize_client(agent_url: str) -> Client: factory: ClientFactory = ClientFactory(config) client: Client = factory.create(agent_card) - logger.info('A2A client initialized successfully') + logger.info("A2A client initialized successfully") return client @@ -59,32 +60,29 @@ async def run_agent_experiment(row, agent_url: str) -> dict[str, str | list]: input_text = row.get("user_input") message = Message( - role='user', - parts=[ - { - 'kind': 'text', - 'text': input_text - } - ], - messageId = uuid4().hex + role="user", + parts=[{"kind": "text", "text": input_text}], + messageId=uuid4().hex, ) - logger.info(f'Processing: {input_text}') + logger.info(f"Processing: {input_text}") async for response in client.send_message(message): # Client returns tuples, extract the task/message if isinstance(response, tuple): task, _ = response if task: - artifacts: list = task.model_dump(mode='json', include={'artifacts'}).get('artifacts',[]) + artifacts: list = task.model_dump( + mode="json", include={"artifacts"} + ).get("artifacts", []) # Extract the model response - if artifacts and artifacts[0].get('parts'): - output_text = artifacts[0]['parts'][0].get('text', '') + if artifacts and artifacts[0].get("parts"): + output_text = artifacts[0]["parts"][0].get("text", "") else: logger.warning("No text found in artifacts") else: - logger.warning(f'Unexpected response: {response}') + logger.warning(f"Unexpected response: {response}") except Exception as e: logger.error(f'Error processing input "{row.get("user_input")}": {str(e)}') @@ -103,27 +101,29 @@ async def main(agent_url: str) -> None: """Main function to load Ragas Dataset and run Experiment.""" # Load existing Ragas dataset - logger.info('Loading Ragas dataset from data/datasets/ragas_dataset.jsonl') - dataset: Dataset[BaseModel] = Dataset.load(name="ragas_dataset", backend="local/jsonl", root_dir="./data") - logger.info(f'Dataset loaded with {len(dataset)} samples') + logger.info("Loading Ragas dataset from data/datasets/ragas_dataset.jsonl") + dataset: Dataset[BaseModel] = Dataset.load( + name="ragas_dataset", backend="local/jsonl", root_dir="./data" + ) + logger.info(f"Dataset loaded with {len(dataset)} samples") # Run the experiment - logger.info('Starting experiment...') + logger.info("Starting experiment...") await run_agent_experiment.arun( - dataset, - name = "ragas_experiment", - agent_url = agent_url + dataset, name="ragas_experiment", agent_url=agent_url ) - logger.info('Experiment completed successfully') - logger.info('Results saved to data/experiments/ragas_experiment.jsonl') + logger.info("Experiment completed successfully") + logger.info("Results saved to data/experiments/ragas_experiment.jsonl") -if __name__ == '__main__': +if __name__ == "__main__": # Parse parameter the script was called with (URL) - parser = argparse.ArgumentParser(description="Runs all queries from the Ragas dataset through the agent at the provided URL") - parser.add_argument('url', help='URL to agent') + parser = argparse.ArgumentParser( + description="Runs all queries from the Ragas dataset through the agent at the provided URL" + ) + parser.add_argument("url", help="URL to agent") args = parser.parse_args() # Call main using the parsed URL - asyncio.run(main(args.url)) \ No newline at end of file + asyncio.run(main(args.url)) diff --git a/testworkflows/scripts/setup.py b/testworkflows/scripts/setup.py index 4e61ed4..99c1a87 100644 --- a/testworkflows/scripts/setup.py +++ b/testworkflows/scripts/setup.py @@ -1,5 +1,7 @@ import argparse + import requests +from requests import Response from pathlib import Path from typing import Callable @@ -10,6 +12,8 @@ from pydantic import BaseModel from ragas import Dataset + + def dataframe_to_ragas_dataset(dataframe: DataFrame) -> None: """Convert DataFrame to Ragas dataset and save to data/ragas_dataset.jsonl. @@ -20,7 +24,7 @@ def dataframe_to_ragas_dataset(dataframe: DataFrame) -> None: """ # Set output directory (and create it if it doesn't exist already) - output_dir = Path('data') + output_dir = Path("data") output_dir.mkdir(exist_ok=True) # Convert DataFrame to list of dictionaries @@ -31,7 +35,8 @@ def dataframe_to_ragas_dataset(dataframe: DataFrame) -> None: name="ragas_dataset", data=dataset_samples, backend="local/jsonl", - root_dir="./data") + root_dir="./data", + ) """# Append all samples to the dataset for sample in dataset_samples: @@ -46,10 +51,10 @@ def get_converter(url: str) -> Callable[[BytesIO], DataFrame]: suffix = Path(url).suffix.lower() format_map = { - '.json': pd.read_json, - '.csv': custom_convert_csv, - '.parquet': pd.read_parquet, - '.prq': pd.read_parquet, + ".json": pd.read_json, + ".csv": custom_convert_csv, + ".parquet": pd.read_parquet, + ".prq": pd.read_parquet, } if suffix in format_map: @@ -57,6 +62,7 @@ def get_converter(url: str) -> Callable[[BytesIO], DataFrame]: raise TypeError(f"Unsupported filetype at url: {url}") + def custom_convert_csv(input_file: BytesIO) -> DataFrame: """ Converts a CSV input file to a Pandas DataFrame and, if it exists, turns 'retrieved_contexts' into a list (RAGAS requires 'retrieved_contexts' as a list of strings) @@ -71,15 +77,15 @@ def custom_convert_csv(input_file: BytesIO) -> DataFrame: dataframe: DataFrame = pd.read_csv(input_file) # Ensure retrieved_contexts is a list (convert string to list if needed) - if 'retrieved_contexts' in dataframe: - dataframe['retrieved_contexts'] = dataframe['retrieved_contexts'].apply( + if "retrieved_contexts" in dataframe: + dataframe["retrieved_contexts"] = dataframe["retrieved_contexts"].apply( lambda x: x if isinstance(x, list) else [x] if x else [] ) return dataframe -def main(url : str) -> None: +def main(url: str) -> None: """Download provided dataset -> convert to Ragas dataset -> save to data/ragas_dataset.jsonl Source dataset must contain columns: user_input, retrieved_contexts, reference @@ -87,7 +93,7 @@ def main(url : str) -> None: converter = get_converter(url) # Download file from URL and raise HTTP error if it occurs - file = requests.get(url) + file: Response = requests.get(url) file.raise_for_status() # Load into DataFrame by using the correct converter @@ -97,10 +103,16 @@ def main(url : str) -> None: # Convert DataFrame to Ragas dataset and save it dataframe_to_ragas_dataset(dataframe) -if __name__ == '__main__': + +if __name__ == "__main__": # Parse parameter the script was called with (URL) - parser = argparse.ArgumentParser(description="Download provided dataset -> convert to Ragas dataset -> save to data/datasets/ragas_dataset.jsonl") - parser.add_argument('url', help='URL to the dataset in .csv / .json / .parquet format (must have user_input, retrieved_contexts, and reference columns)') + parser = argparse.ArgumentParser( + description="Download provided dataset -> convert to Ragas dataset -> save to data/datasets/ragas_dataset.jsonl" + ) + parser.add_argument( + "url", + help="URL to the dataset in .csv / .json / .parquet format (must have user_input, retrieved_contexts, and reference columns)", + ) args = parser.parse_args() # Call main using the parsed URL diff --git a/testworkflows/tests/test_e2e.py b/testworkflows/tests/test_e2e.py index e8dd106..6f69272 100755 --- a/testworkflows/tests/test_e2e.py +++ b/testworkflows/tests/test_e2e.py @@ -28,8 +28,7 @@ # Set up logging logging.basicConfig( - level=logging.INFO, - format='%(asctime)s - %(levelname)s - %(message)s' + level=logging.INFO, format="%(asctime)s - %(levelname)s - %(message)s" ) logger = logging.getLogger(__name__) @@ -44,7 +43,7 @@ def __init__( model: str, metrics: List[str], workflow_name: str, - otlp_endpoint: str = "localhost:4318" + otlp_endpoint: str = "localhost:4318", ): self.dataset_url = dataset_url self.agent_url = agent_url @@ -65,7 +64,6 @@ def __init__( self.results_file = Path("./data/experiments/ragas_experiment.jsonl") self.evaluation_file = Path("./results/evaluation_scores.json") - def verify_scripts_exist(self) -> bool: """Verify that all required scripts exist.""" logger.info("Verifying all scripts exist...") @@ -73,7 +71,7 @@ def verify_scripts_exist(self) -> bool: self.setup_script, self.run_script, self.evaluate_script, - self.publish_script + self.publish_script, ] missing_scripts = [script for script in scripts if not script.exists()] @@ -87,7 +85,6 @@ def verify_scripts_exist(self) -> bool: logger.info("✓ All scripts found") return True - def run_command(self, command: List[str], step_name: str) -> bool: """ Run a command and handle output/errors. @@ -99,23 +96,18 @@ def run_command(self, command: List[str], step_name: str) -> bool: Returns: True if successful, False otherwise """ - logger.info(f"\n{'='*60}") + logger.info(f"\n{'=' * 60}") logger.info(f"Step: {step_name}") logger.info(f"Command: {' '.join(command)}") - logger.info(f"{'='*60}\n") + logger.info(f"{'=' * 60}\n") try: - result = subprocess.run( - command, - check=True, - capture_output=True, - text=True - ) + result = subprocess.run(command, check=True, capture_output=True, text=True) # Log stdout if present if result.stdout: logger.info("Output:") - for line in result.stdout.strip().split('\n'): + for line in result.stdout.strip().split("\n"): logger.info(f" {line}") logger.info(f"✓ {step_name} completed successfully\n") @@ -126,12 +118,12 @@ def run_command(self, command: List[str], step_name: str) -> bool: if e.stdout: logger.error("Standard output:") - for line in e.stdout.strip().split('\n'): + for line in e.stdout.strip().split("\n"): logger.error(f" {line}") if e.stderr: logger.error("Error output:") - for line in e.stderr.strip().split('\n'): + for line in e.stderr.strip().split("\n"): logger.error(f" {line}") return False @@ -140,7 +132,6 @@ def run_command(self, command: List[str], step_name: str) -> bool: logger.error(f"✗ Unexpected error in {step_name}: {e}") return False - def verify_file_exists(self, file_path: Path, step_name: str) -> bool: """Verify that an expected output file was created.""" if file_path.exists(): @@ -150,7 +141,6 @@ def verify_file_exists(self, file_path: Path, step_name: str) -> bool: logger.error(f"✗ Expected file {file_path} not found after {step_name}") return False - def run_setup(self) -> bool: """Run setup.py to download and convert dataset.""" command = ["python3", str(self.setup_script), self.dataset_url] @@ -160,7 +150,6 @@ def run_setup(self) -> bool: return self.verify_file_exists(self.dataset_file, "setup.py") return False - def run_agent_queries(self) -> bool: """Run run.py to execute agent queries on the dataset.""" command = ["python3", str(self.run_script), self.agent_url] @@ -170,38 +159,30 @@ def run_agent_queries(self) -> bool: return self.verify_file_exists(self.results_file, "run.py") return False - def run_evaluation(self) -> bool: """Run evaluate.py to evaluate results using RAGAS metrics.""" - command = [ - "python3", - str(self.evaluate_script), - self.model, - *self.metrics - ] + command = ["python3", str(self.evaluate_script), self.model, *self.metrics] success = self.run_command(command, "3. Evaluate - Calculate RAGAS Metrics") if success: return self.verify_file_exists(self.evaluation_file, "evaluate.py") return False - def run_publish(self) -> bool: """Run publish.py to publish metrics via OpenTelemetry OTLP.""" command = [ "python3", str(self.publish_script), self.workflow_name, - self.otlp_endpoint + self.otlp_endpoint, ] return self.run_command(command, "4. Publish - Push Metrics via OTLP") - def run_full_pipeline(self) -> bool: """Execute the complete E2E test pipeline.""" - logger.info("\n" + "="*60) + logger.info("\n" + "=" * 60) logger.info("Starting E2E Test Pipeline") - logger.info("="*60 + "\n") + logger.info("=" * 60 + "\n") # Verify all scripts exist before starting if not self.verify_scripts_exist(): @@ -213,20 +194,20 @@ def run_full_pipeline(self) -> bool: ("Setup", self.run_setup), ("Run", self.run_agent_queries), ("Evaluate", self.run_evaluation), - ("Publish", self.run_publish) + ("Publish", self.run_publish), ] for step_name, step_func in steps: if not step_func(): - logger.error(f"\n{'='*60}") + logger.error(f"\n{'=' * 60}") logger.error(f"E2E Test FAILED at step: {step_name}") - logger.error(f"{'='*60}\n") + logger.error(f"{'=' * 60}\n") return False # All steps completed successfully - logger.info("\n" + "="*60) + logger.info("\n" + "=" * 60) logger.info("E2E Test Pipeline COMPLETED SUCCESSFULLY") - logger.info("="*60 + "\n") + logger.info("=" * 60 + "\n") logger.info("Summary:") logger.info(f" ✓ Ragas Dataset created: {self.dataset_file}") @@ -241,8 +222,8 @@ def run_full_pipeline(self) -> bool: def main(): """Parse arguments and run the E2E test""" parser = argparse.ArgumentParser( - description = "End-to-end test runner for the agent testing pipeline", - formatter_class = argparse.RawDescriptionHelpFormatter, + description="End-to-end test runner for the agent testing pipeline", + formatter_class=argparse.RawDescriptionHelpFormatter, epilog=""" Examples: # Basic usage @@ -261,44 +242,40 @@ def main(): --metrics faithfulness \\ --workflow-name "my-test" \\ --otlp-endpoint "http://otlp.example.com:4318" - """ + """, ) parser.add_argument( "--dataset-url", required=True, - help="URL to the dataset in .csv / .json / .parquet format" + help="URL to the dataset in .csv / .json / .parquet format", ) - parser.add_argument( - "--agent-url", - required=True, - help="URL to agent" - ) + parser.add_argument("--agent-url", required=True, help="URL to agent") parser.add_argument( "--model", required=True, - help="Model name to use for evaluation (e.g., gemini-flash-latest)" + help="Model name to use for evaluation (e.g., gemini-flash-latest)", ) parser.add_argument( "--metrics", nargs="+", required=True, - help="At least one (or more) metrics to evaluate (e.g., faithfulness, answer_relevancy)" + help="At least one (or more) metrics to evaluate (e.g., faithfulness, answer_relevancy)", ) parser.add_argument( "--workflow-name", required=True, - help="Name of the test workflow (e.g., 'weather-assistant-test')" + help="Name of the test workflow (e.g., 'weather-assistant-test')", ) parser.add_argument( "--otlp-endpoint", default="localhost:4318", - help="URL of the OTLP HTTP endpoint (default: localhost:4318)" + help="URL of the OTLP HTTP endpoint (default: localhost:4318)", ) args = parser.parse_args() @@ -310,7 +287,7 @@ def main(): model=args.model, metrics=args.metrics, workflow_name=args.workflow_name, - otlp_endpoint=args.otlp_endpoint + otlp_endpoint=args.otlp_endpoint, ) success = runner.run_full_pipeline() diff --git a/testworkflows/tests/test_evaluate.py b/testworkflows/tests/test_evaluate.py index 4c235ae..45c4671 100644 --- a/testworkflows/tests/test_evaluate.py +++ b/testworkflows/tests/test_evaluate.py @@ -9,20 +9,16 @@ import shutil import json from pathlib import Path -from unittest.mock import patch, MagicMock +from unittest.mock import MagicMock -from ragas.dataset_schema import EvaluationDataset, EvaluationResult +from ragas.dataset_schema import EvaluationResult import pandas as pd import sys + sys.path.insert(0, str(Path(__file__).parent.parent / "scripts")) -from evaluate import ( - get_available_metrics, - format_evaluation_scores, - main, - AVAILABLE_METRICS -) +from evaluate import format_evaluation_scores, main, AVAILABLE_METRICS class TestFormatEvaluationScores(unittest.TestCase): @@ -32,14 +28,13 @@ def test_overall_scores_calculation(self): """Test that overall scores are calculated correctly""" mock_result = MagicMock(spec=EvaluationResult) - df = pd.DataFrame({ - 'faithfulness': [0.9, 0.8, 0.7], - 'answer_relevancy': [0.85, 0.75, 0.65] - }) + df = pd.DataFrame( + {"faithfulness": [0.9, 0.8, 0.7], "answer_relevancy": [0.85, 0.75, 0.65]} + ) mock_result.to_pandas.return_value = df # Mock _repr_dict with calculated averages - mock_result._repr_dict = {'faithfulness': 0.8, 'answer_relevancy': 0.75} + mock_result._repr_dict = {"faithfulness": 0.8, "answer_relevancy": 0.75} # Mock token usage methods mock_token_usage = MagicMock() @@ -48,24 +43,23 @@ def test_overall_scores_calculation(self): mock_result.total_tokens.return_value = mock_token_usage mock_result.total_cost.return_value = 0.001 - formatted = format_evaluation_scores(mock_result, 5.0/1e6, 15.0/1e6) + formatted = format_evaluation_scores(mock_result, 5.0 / 1e6, 15.0 / 1e6) # Verify overall scores are correct - self.assertAlmostEqual(formatted.overall_scores['faithfulness'], 0.8, places=2) - self.assertAlmostEqual(formatted.overall_scores['answer_relevancy'], 0.75, places=2) + self.assertAlmostEqual(formatted.overall_scores["faithfulness"], 0.8, places=2) + self.assertAlmostEqual( + formatted.overall_scores["answer_relevancy"], 0.75, places=2 + ) def test_individual_results_present(self): """Test that individual results are included""" mock_result = MagicMock(spec=EvaluationResult) - df = pd.DataFrame({ - 'user_input': ['Q1', 'Q2'], - 'faithfulness': [0.9, 0.8] - }) + df = pd.DataFrame({"user_input": ["Q1", "Q2"], "faithfulness": [0.9, 0.8]}) mock_result.to_pandas.return_value = df # Mock _repr_dict for overall scores - mock_result._repr_dict = {'faithfulness': 0.85} + mock_result._repr_dict = {"faithfulness": 0.85} # Mock token usage methods mock_token_usage = MagicMock() @@ -74,7 +68,7 @@ def test_individual_results_present(self): mock_result.total_tokens.return_value = mock_token_usage mock_result.total_cost.return_value = 0.001 - formatted = format_evaluation_scores(mock_result, 5.0/1e6, 15.0/1e6) + formatted = format_evaluation_scores(mock_result, 5.0 / 1e6, 15.0 / 1e6) # Verify individual results self.assertEqual(len(formatted.individual_results), 2) @@ -83,13 +77,11 @@ def test_token_usage_placeholders(self): """Test that token usage is returned correctly""" mock_result = MagicMock(spec=EvaluationResult) - df = pd.DataFrame({ - 'faithfulness': [0.9] - }) + df = pd.DataFrame({"faithfulness": [0.9]}) mock_result.to_pandas.return_value = df # Mock _repr_dict for overall scores - mock_result._repr_dict = {'faithfulness': 0.9} + mock_result._repr_dict = {"faithfulness": 0.9} # Mock token usage methods with specific values mock_token_usage = MagicMock() @@ -98,11 +90,11 @@ def test_token_usage_placeholders(self): mock_result.total_tokens.return_value = mock_token_usage mock_result.total_cost.return_value = 0.002 - formatted = format_evaluation_scores(mock_result, 5.0/1e6, 15.0/1e6) + formatted = format_evaluation_scores(mock_result, 5.0 / 1e6, 15.0 / 1e6) # Verify token usage is captured correctly - self.assertEqual(formatted.total_tokens['input_tokens'], 150) - self.assertEqual(formatted.total_tokens['output_tokens'], 75) + self.assertEqual(formatted.total_tokens["input_tokens"], 150) + self.assertEqual(formatted.total_tokens["output_tokens"], 75) self.assertEqual(formatted.total_cost, 0.002) @@ -121,25 +113,25 @@ def setUp(self): self.experiment_file = self.experiment_dir / "ragas_experiment.jsonl" test_data = [ { - 'user_input': 'What is the weather?', - 'retrieved_contexts': ['Context about weather'], - 'reference': 'Expected answer', - 'response': 'The weather is sunny.' + "user_input": "What is the weather?", + "retrieved_contexts": ["Context about weather"], + "reference": "Expected answer", + "response": "The weather is sunny.", } ] - with open(self.experiment_file, 'w') as f: + with open(self.experiment_file, "w") as f: for item in test_data: - f.write(json.dumps(item) + '\n') + f.write(json.dumps(item) + "\n") def tearDown(self): """Clean up temporary directory""" shutil.rmtree(self.temp_dir, ignore_errors=True) - def test_main_no_metrics(self): """Test main function with no metrics provided""" import os + os.chdir(self.temp_dir) try: @@ -149,7 +141,7 @@ def test_main_no_metrics(self): main( output_file="results/evaluation_scores.json", model="gemini-flash-latest", - metrics=None + metrics=None, ) finally: os.chdir(self.original_cwd) @@ -170,9 +162,10 @@ def test_available_metrics_loaded(self): # All values should be Metric instances from ragas.metrics import Metric + for value in AVAILABLE_METRICS.values(): self.assertIsInstance(value, Metric) -if __name__ == '__main__': +if __name__ == "__main__": unittest.main() diff --git a/testworkflows/tests/test_publish.py b/testworkflows/tests/test_publish.py index 6a4631f..b5c298b 100644 --- a/testworkflows/tests/test_publish.py +++ b/testworkflows/tests/test_publish.py @@ -11,16 +11,12 @@ from pathlib import Path from unittest.mock import patch, MagicMock -from prometheus_client import CollectorRegistry, Gauge import sys + sys.path.insert(0, str(Path(__file__).parent.parent / "scripts")) -from publish import ( - get_overall_scores, - create_and_push_metrics, - publish_metrics -) +from publish import get_overall_scores, create_and_push_metrics, publish_metrics class TestGetOverallScores(unittest.TestCase): @@ -38,22 +34,19 @@ def tearDown(self): def test_loads_overall_scores(self): """Test that get_overall_scores loads the overall_scores section""" test_data = { - "overall_scores": { - "faithfulness": 0.85, - "answer_relevancy": 0.90 - }, + "overall_scores": {"faithfulness": 0.85, "answer_relevancy": 0.90}, "individual_results": [], "total_tokens": {"input_tokens": 0, "output_tokens": 0}, - "total_cost": 0.0 + "total_cost": 0.0, } - with open(self.test_file, 'w') as f: + with open(self.test_file, "w") as f: json.dump(test_data, f) scores = get_overall_scores(str(self.test_file)) - self.assertEqual(scores['faithfulness'], 0.85) - self.assertEqual(scores['answer_relevancy'], 0.90) + self.assertEqual(scores["faithfulness"], 0.85) + self.assertEqual(scores["answer_relevancy"], 0.90) def test_file_not_found(self): """Test behavior when file doesn't exist""" @@ -64,14 +57,11 @@ def test_file_not_found(self): class TestCreateAndPushMetrics(unittest.TestCase): """Test the create_and_push_metrics function""" - @patch('publish.push_to_gateway') - @patch('publish.Gauge') + @patch("publish.push_to_gateway") + @patch("publish.Gauge") def test_creates_gauges_for_each_metric(self, mock_gauge_class, mock_push): """Test that a Gauge is created for each metric""" - overall_scores = { - 'faithfulness': 0.85, - 'answer_relevancy': 0.90 - } + overall_scores = {"faithfulness": 0.85, "answer_relevancy": 0.90} # Mock the Gauge instances mock_gauge_instance = MagicMock() @@ -80,7 +70,7 @@ def test_creates_gauges_for_each_metric(self, mock_gauge_class, mock_push): create_and_push_metrics( overall_scores=overall_scores, workflow_name="test-workflow", - pushgateway_url="localhost:9091" + pushgateway_url="localhost:9091", ) # Verify Gauge was called for each metric @@ -89,16 +79,14 @@ def test_creates_gauges_for_each_metric(self, mock_gauge_class, mock_push): # Verify gauge names gauge_calls = mock_gauge_class.call_args_list gauge_names = [call[0][0] for call in gauge_calls] - self.assertIn('ragas_evaluation_faithfulness', gauge_names) - self.assertIn('ragas_evaluation_answer_relevancy', gauge_names) + self.assertIn("ragas_evaluation_faithfulness", gauge_names) + self.assertIn("ragas_evaluation_answer_relevancy", gauge_names) - @patch('publish.push_to_gateway') - @patch('publish.Gauge') + @patch("publish.push_to_gateway") + @patch("publish.Gauge") def test_sets_gauge_values(self, mock_gauge_class, mock_push): """Test that gauge values are set correctly""" - overall_scores = { - 'faithfulness': 0.85 - } + overall_scores = {"faithfulness": 0.85} # Mock the Gauge instance and labels mock_gauge_instance = MagicMock() @@ -109,7 +97,7 @@ def test_sets_gauge_values(self, mock_gauge_class, mock_push): create_and_push_metrics( overall_scores=overall_scores, workflow_name="test-workflow", - pushgateway_url="localhost:9091" + pushgateway_url="localhost:9091", ) # Verify labels were set with workflow_name @@ -118,17 +106,15 @@ def test_sets_gauge_values(self, mock_gauge_class, mock_push): # Verify gauge value was set mock_labels.set.assert_called_with(0.85) - @patch('publish.push_to_gateway') + @patch("publish.push_to_gateway") def test_pushes_to_gateway(self, mock_push): """Test that metrics are pushed to Pushgateway""" - overall_scores = { - 'faithfulness': 0.85 - } + overall_scores = {"faithfulness": 0.85} create_and_push_metrics( overall_scores=overall_scores, workflow_name="test-workflow", - pushgateway_url="localhost:9091" + pushgateway_url="localhost:9091", ) # Verify push_to_gateway was called @@ -137,22 +123,20 @@ def test_pushes_to_gateway(self, mock_push): # Verify push parameters call_args = mock_push.call_args self.assertEqual(call_args[0][0], "localhost:9091") - self.assertEqual(call_args[1]['job'], 'ragas_evaluation') + self.assertEqual(call_args[1]["job"], "ragas_evaluation") - @patch('publish.push_to_gateway') + @patch("publish.push_to_gateway") def test_handles_push_error(self, mock_push): """Test error handling when push fails""" mock_push.side_effect = Exception("Connection refused") - overall_scores = { - 'faithfulness': 0.85 - } + overall_scores = {"faithfulness": 0.85} with self.assertRaises(Exception) as context: create_and_push_metrics( overall_scores=overall_scores, workflow_name="test-workflow", - pushgateway_url="localhost:9091" + pushgateway_url="localhost:9091", ) self.assertIn("Connection refused", str(context.exception)) @@ -168,29 +152,26 @@ def setUp(self): # Create test evaluation scores file test_data = { - "overall_scores": { - "faithfulness": 0.85, - "answer_relevancy": 0.90 - }, + "overall_scores": {"faithfulness": 0.85, "answer_relevancy": 0.90}, "individual_results": [], "total_tokens": {"input_tokens": 0, "output_tokens": 0}, - "total_cost": 0.0 + "total_cost": 0.0, } - with open(self.test_file, 'w') as f: + with open(self.test_file, "w") as f: json.dump(test_data, f) def tearDown(self): """Clean up temporary directory""" shutil.rmtree(self.temp_dir, ignore_errors=True) - @patch('publish.create_and_push_metrics') + @patch("publish.create_and_push_metrics") def test_publish_metrics_calls_create_and_push(self, mock_create_push): """Test that publish_metrics calls create_and_push_metrics""" publish_metrics( input_file=str(self.test_file), workflow_name="test-workflow", - pushgateway_url="localhost:9091" + pushgateway_url="localhost:9091", ) # Verify create_and_push_metrics was called @@ -198,28 +179,25 @@ def test_publish_metrics_calls_create_and_push(self, mock_create_push): # Verify parameters (positional arguments) call_args = mock_create_push.call_args - self.assertEqual(call_args[0][0]['faithfulness'], 0.85) - self.assertEqual(call_args[0][0]['answer_relevancy'], 0.90) + self.assertEqual(call_args[0][0]["faithfulness"], 0.85) + self.assertEqual(call_args[0][0]["answer_relevancy"], 0.90) self.assertEqual(call_args[0][1], "test-workflow") self.assertEqual(call_args[0][2], "localhost:9091") - @patch('publish.create_and_push_metrics') + @patch("publish.create_and_push_metrics") def test_publish_metrics_with_empty_scores(self, mock_create_push): """Test behavior when overall_scores is empty""" # Create file with empty overall_scores - test_data = { - "overall_scores": {}, - "individual_results": [] - } + test_data = {"overall_scores": {}, "individual_results": []} empty_file = Path(self.temp_dir) / "empty_scores.json" - with open(empty_file, 'w') as f: + with open(empty_file, "w") as f: json.dump(test_data, f) publish_metrics( input_file=str(empty_file), workflow_name="test-workflow", - pushgateway_url="localhost:9091" + pushgateway_url="localhost:9091", ) # Verify create_and_push_metrics was NOT called @@ -240,42 +218,39 @@ def setUp(self): "faithfulness": 0.8523, "answer_relevancy": 0.9012, "context_precision": 0.7845, - "context_recall": 0.8234 + "context_recall": 0.8234, }, "individual_results": [ { "user_input": "What is the weather?", "response": "It is sunny.", "faithfulness": 0.85, - "answer_relevancy": 0.90 + "answer_relevancy": 0.90, } ], - "total_tokens": { - "input_tokens": 0, - "output_tokens": 0 - }, - "total_cost": 0.0 + "total_tokens": {"input_tokens": 0, "output_tokens": 0}, + "total_cost": 0.0, } - with open(self.test_file, 'w') as f: + with open(self.test_file, "w") as f: json.dump(test_data, f, indent=2) def tearDown(self): """Clean up temporary directory""" shutil.rmtree(self.temp_dir, ignore_errors=True) - @patch('publish.push_to_gateway') + @patch("publish.push_to_gateway") def test_publish_realistic_scores(self, mock_push): """Test publishing realistic evaluation scores""" publish_metrics( input_file=str(self.test_file), workflow_name="weather-assistant-test", - pushgateway_url="localhost:9091" + pushgateway_url="localhost:9091", ) # Verify push was called mock_push.assert_called_once() -if __name__ == '__main__': +if __name__ == "__main__": unittest.main() diff --git a/testworkflows/tests/test_run.py b/testworkflows/tests/test_run.py index d55d264..13489c9 100644 --- a/testworkflows/tests/test_run.py +++ b/testworkflows/tests/test_run.py @@ -10,10 +10,9 @@ from pathlib import Path from unittest.mock import patch, MagicMock, AsyncMock -from pydantic import BaseModel -from ragas import Dataset import sys + sys.path.insert(0, str(Path(__file__).parent.parent / "scripts")) from run import initialize_client, run_agent_experiment, main @@ -22,9 +21,11 @@ class TestInitializeClient(unittest.TestCase): """Test the initialize_client function""" - @patch('run.ClientFactory') - @patch('run.minimal_agent_card') - async def test_initialize_client_creates_client(self, mock_agent_card, mock_factory): + @patch("run.ClientFactory") + @patch("run.minimal_agent_card") + async def test_initialize_client_creates_client( + self, mock_agent_card, mock_factory + ): """Test that initialize_client creates a client correctly""" # Mock the agent card mock_card = MagicMock() @@ -57,9 +58,11 @@ def tearDown(self): """Clean up temporary directory""" shutil.rmtree(self.temp_dir, ignore_errors=True) - @patch('run.logging.getLogger') - @patch('run.initialize_client') - async def test_run_agent_experiment_success(self, mock_init_client, mock_get_logger): + @patch("run.logging.getLogger") + @patch("run.initialize_client") + async def test_run_agent_experiment_success( + self, mock_init_client, mock_get_logger + ): """Test successful agent query execution""" # Mock logger mock_logger = MagicMock() @@ -71,10 +74,8 @@ async def test_run_agent_experiment_success(self, mock_init_client, mock_get_log # Create a mock task response mock_task = MagicMock() mock_task.model_dump.return_value = { - 'artifacts': [{ - 'parts': [{'text': 'Agent response text'}] - }], - 'history': [] + "artifacts": [{"parts": [{"text": "Agent response text"}]}], + "history": [], } # Mock the async generator returned by send_message @@ -86,13 +87,13 @@ async def mock_send_message(message): # Create test row test_row = { - 'user_input': 'What is the weather?', - 'retrieved_contexts': ['Context about weather'], - 'reference': 'Expected answer' + "user_input": "What is the weather?", + "retrieved_contexts": ["Context about weather"], + "reference": "Expected answer", } # Mock httpx AsyncClient - with patch('run.httpx.AsyncClient') as mock_httpx: + with patch("run.httpx.AsyncClient") as mock_httpx: mock_httpx_instance = AsyncMock() mock_httpx_instance.__aenter__.return_value = mock_httpx_instance mock_httpx_instance.__aexit__.return_value = None @@ -104,20 +105,19 @@ async def test_experiment_func(row, agent_url): # Call the function result = await test_experiment_func( - test_row, - agent_url="http://test-agent:8000" + test_row, agent_url="http://test-agent:8000" ) # Verify result structure - self.assertIn('user_input', result) - self.assertIn('retrieved_contexts', result) - self.assertIn('reference', result) - self.assertIn('response', result) - self.assertEqual(result['user_input'], 'What is the weather?') - self.assertEqual(result['response'], 'Agent response text') - - @patch('run.logging.getLogger') - @patch('run.initialize_client') + self.assertIn("user_input", result) + self.assertIn("retrieved_contexts", result) + self.assertIn("reference", result) + self.assertIn("response", result) + self.assertEqual(result["user_input"], "What is the weather?") + self.assertEqual(result["response"], "Agent response text") + + @patch("run.logging.getLogger") + @patch("run.initialize_client") async def test_run_agent_experiment_error(self, mock_init_client, mock_get_logger): """Test agent query with error handling""" # Mock logger @@ -129,13 +129,13 @@ async def test_run_agent_experiment_error(self, mock_init_client, mock_get_logge # Create test row test_row = { - 'user_input': 'What is the weather?', - 'retrieved_contexts': ['Context'], - 'reference': 'Answer' + "user_input": "What is the weather?", + "retrieved_contexts": ["Context"], + "reference": "Answer", } # Mock httpx AsyncClient - with patch('run.httpx.AsyncClient') as mock_httpx: + with patch("run.httpx.AsyncClient") as mock_httpx: mock_httpx_instance = AsyncMock() mock_httpx_instance.__aenter__.return_value = mock_httpx_instance mock_httpx_instance.__aexit__.return_value = None @@ -147,14 +147,14 @@ async def test_experiment_func(row, agent_url): # Call the function result = await test_experiment_func( - test_row, - agent_url="http://test-agent:8000" + test_row, agent_url="http://test-agent:8000" ) # Verify error is captured in response - self.assertIn('response', result) - self.assertIn('ERROR', result['response']) - self.assertIn('Connection failed', result['response']) + self.assertIn("response", result) + self.assertIn("ERROR", result["response"]) + self.assertIn("Connection failed", result["response"]) + class TestMain(unittest.TestCase): """Test the main function""" @@ -168,11 +168,12 @@ def tearDown(self): """Clean up temporary directory""" shutil.rmtree(self.temp_dir, ignore_errors=True) - @patch('run.run_agent_experiment.arun') - @patch('run.Dataset.load') + @patch("run.run_agent_experiment.arun") + @patch("run.Dataset.load") async def test_main_execution(self, mock_dataset_load, mock_arun): """Test main function execution flow""" import os + os.chdir(self.temp_dir) try: @@ -197,7 +198,5 @@ async def test_main_execution(self, mock_dataset_load, mock_arun): os.chdir(self.original_cwd) - - -if __name__ == '__main__': +if __name__ == "__main__": unittest.main() diff --git a/testworkflows/tests/test_setup.py b/testworkflows/tests/test_setup.py index 9479072..d1435fe 100644 --- a/testworkflows/tests/test_setup.py +++ b/testworkflows/tests/test_setup.py @@ -12,17 +12,12 @@ from unittest.mock import patch, MagicMock import pandas as pd -from ragas import Dataset import sys + sys.path.insert(0, str(Path(__file__).parent.parent / "scripts")) -from setup import ( - custom_convert_csv, - get_converter, - dataframe_to_ragas_dataset, - main -) +from setup import custom_convert_csv, get_converter, dataframe_to_ragas_dataset, main class TestCustomConvertCSV(unittest.TestCase): @@ -36,8 +31,8 @@ def test_converts_string_to_list(self): buffer = BytesIO(csv_content) df = custom_convert_csv(buffer) - self.assertIsInstance(df['retrieved_contexts'].iloc[0], list) - self.assertEqual(df['retrieved_contexts'].iloc[0], ["Context text"]) + self.assertIsInstance(df["retrieved_contexts"].iloc[0], list) + self.assertEqual(df["retrieved_contexts"].iloc[0], ["Context text"]) def test_handles_empty_retrieved_contexts(self): """Test handling of empty retrieved_contexts""" @@ -49,7 +44,7 @@ def test_handles_empty_retrieved_contexts(self): # Empty string becomes [nan] in pandas, which then becomes [] # The function converts non-list values to lists - result = df['retrieved_contexts'].iloc[0] + result = df["retrieved_contexts"].iloc[0] # Check that it's a list and handle NaN case self.assertIsInstance(result, list) # If it contains NaN, that's acceptable behavior for empty strings in CSV @@ -68,7 +63,7 @@ def test_missing_retrieved_contexts_column(self): buffer = BytesIO(csv_content) df = custom_convert_csv(buffer) - self.assertNotIn('retrieved_contexts', df.columns) + self.assertNotIn("retrieved_contexts", df.columns) class TestGetConverter(unittest.TestCase): @@ -97,23 +92,31 @@ def tearDown(self): def test_creates_ragas_dataset_file(self): """Test that ragas_dataset.jsonl is created""" import os + os.chdir(self.temp_dir) try: - df = pd.DataFrame({ - 'user_input': ['Question 1'], - 'retrieved_contexts': [['Context 1']], - 'reference': ['Answer 1'] - }) + df = pd.DataFrame( + { + "user_input": ["Question 1"], + "retrieved_contexts": [["Context 1"]], + "reference": ["Answer 1"], + } + ) dataframe_to_ragas_dataset(df) # Check for the file in the datasets subdirectory - dataset_file = Path(self.temp_dir) / 'data' / 'datasets' / 'ragas_dataset.jsonl' - self.assertTrue(dataset_file.exists(), f"Dataset file not found at {dataset_file}") + dataset_file = ( + Path(self.temp_dir) / "data" / "datasets" / "ragas_dataset.jsonl" + ) + self.assertTrue( + dataset_file.exists(), f"Dataset file not found at {dataset_file}" + ) finally: os.chdir(self.original_cwd) + class TestMain(unittest.TestCase): """Test the main function with mocked HTTP requests""" @@ -126,10 +129,11 @@ def tearDown(self): """Clean up temporary directory""" shutil.rmtree(self.temp_dir, ignore_errors=True) - @patch('setup.requests.get') + @patch("setup.requests.get") def test_main_with_csv(self, mock_get): """Test main function with CSV file""" import os + os.chdir(self.temp_dir) try: @@ -146,29 +150,34 @@ def test_main_with_csv(self, mock_get): main("https://example.com/data.csv") # Verify dataset was created in datasets subdirectory - dataset_file = Path(self.temp_dir) / 'data' / 'datasets' / 'ragas_dataset.jsonl' - self.assertTrue(dataset_file.exists(), f"Dataset file not found at {dataset_file}") + dataset_file = ( + Path(self.temp_dir) / "data" / "datasets" / "ragas_dataset.jsonl" + ) + self.assertTrue( + dataset_file.exists(), f"Dataset file not found at {dataset_file}" + ) # Verify requests.get was called mock_get.assert_called_once_with("https://example.com/data.csv") finally: os.chdir(self.original_cwd) - @patch('setup.requests.get') + @patch("setup.requests.get") def test_main_with_json(self, mock_get): """Test main function with JSON file""" import os + os.chdir(self.temp_dir) try: # Mock the HTTP response - json_content = b'''[ + json_content = b"""[ { "user_input": "Question?", "retrieved_contexts": ["Context text"], "reference": "Answer" } - ]''' + ]""" mock_response = MagicMock() mock_response.content = json_content @@ -179,15 +188,20 @@ def test_main_with_json(self, mock_get): main("https://example.com/data.json") # Verify dataset was created in datasets subdirectory - dataset_file = Path(self.temp_dir) / 'data' / 'datasets' / 'ragas_dataset.jsonl' - self.assertTrue(dataset_file.exists(), f"Dataset file not found at {dataset_file}") + dataset_file = ( + Path(self.temp_dir) / "data" / "datasets" / "ragas_dataset.jsonl" + ) + self.assertTrue( + dataset_file.exists(), f"Dataset file not found at {dataset_file}" + ) finally: os.chdir(self.original_cwd) - @patch('setup.requests.get') + @patch("setup.requests.get") def test_main_with_invalid_url(self, mock_get): """Test main function with invalid URL (HTTP error)""" import os + os.chdir(self.temp_dir) try: @@ -203,5 +217,5 @@ def test_main_with_invalid_url(self, mock_get): os.chdir(self.original_cwd) -if __name__ == '__main__': +if __name__ == "__main__": unittest.main() From 7f3521653002a28caea239477361ec0aee4ec201 Mon Sep 17 00:00:00 2001 From: MiaAppel Date: Thu, 6 Nov 2025 12:12:35 +0100 Subject: [PATCH 12/61] FIX: Formatting --- testworkflows/scripts/evaluate.py | 13 ++++------ testworkflows/scripts/publish.py | 31 +++++++---------------- testworkflows/scripts/run.py | 28 +++++++-------------- testworkflows/scripts/setup.py | 13 +++------- testworkflows/tests/test_e2e.py | 6 ++--- testworkflows/tests/test_evaluate.py | 21 ++++++---------- testworkflows/tests/test_publish.py | 14 +++++------ testworkflows/tests/test_run.py | 28 +++++++-------------- testworkflows/tests/test_setup.py | 37 +++++++++------------------- 9 files changed, 63 insertions(+), 128 deletions(-) diff --git a/testworkflows/scripts/evaluate.py b/testworkflows/scripts/evaluate.py index ae025d9..88f6bc5 100644 --- a/testworkflows/scripts/evaluate.py +++ b/testworkflows/scripts/evaluate.py @@ -3,17 +3,18 @@ import json import logging import os -from dataclasses import dataclass, asdict from argparse import ArgumentError +from dataclasses import asdict, dataclass from logging import Logger from typing import Any + +import ragas.metrics as metrics_module from langchain_openai import ChatOpenAI from ragas import evaluate +from ragas.cost import get_token_usage_for_openai from ragas.dataset_schema import EvaluationDataset, EvaluationResult from ragas.llms import LangchainLLMWrapper from ragas.metrics import Metric -import ragas.metrics as metrics_module -from ragas.cost import get_token_usage_for_openai # Set up module-level logger logging.basicConfig(level=logging.INFO) @@ -109,11 +110,7 @@ def format_evaluation_scores( # Extract token usage and calculate cost using TokenUsageParser # Check if token usage data was collected (some metrics don't use LLMs or use separate LLM instances) - if ( - ragas_result.cost_cb - and hasattr(ragas_result.cost_cb, "usage_data") - and ragas_result.cost_cb.usage_data - ): + if ragas_result.cost_cb and hasattr(ragas_result.cost_cb, "usage_data") and ragas_result.cost_cb.usage_data: token_usage = ragas_result.total_tokens() total_tokens = { "input_tokens": token_usage.input_tokens, diff --git a/testworkflows/scripts/publish.py b/testworkflows/scripts/publish.py index 5c57c39..760f865 100644 --- a/testworkflows/scripts/publish.py +++ b/testworkflows/scripts/publish.py @@ -2,10 +2,11 @@ import json import logging from logging import Logger + from opentelemetry import metrics +from opentelemetry.exporter.otlp.proto.http.metric_exporter import OTLPMetricExporter from opentelemetry.sdk.metrics import MeterProvider from opentelemetry.sdk.metrics.export import PeriodicExportingMetricReader -from opentelemetry.exporter.otlp.proto.http.metric_exporter import OTLPMetricExporter from opentelemetry.sdk.resources import Resource # Set up module-level logger @@ -19,9 +20,7 @@ def get_overall_scores(file_path: str) -> dict[str, float]: return json.load(file).get("overall_scores", {}) -def create_and_push_metrics( - overall_scores: dict[str, float], workflow_name: str, otlp_endpoint: str -) -> None: +def create_and_push_metrics(overall_scores: dict[str, float], workflow_name: str, otlp_endpoint: str) -> None: """ Create OpenTelemetry metrics for each overall score and push via OTLP. @@ -31,9 +30,7 @@ def create_and_push_metrics( otlp_endpoint: URL of the OTLP endpoint (e.g., 'http://localhost:4318') """ # Ensure the endpoint has the correct protocol - if not otlp_endpoint.startswith("http://") and not otlp_endpoint.startswith( - "https://" - ): + if not otlp_endpoint.startswith("http://") and not otlp_endpoint.startswith("https://"): otlp_endpoint = f"http://{otlp_endpoint}" # Create OTLP exporter @@ -46,9 +43,7 @@ def create_and_push_metrics( ) # Create resource with workflow metadata - resource = Resource.create( - {"service.name": "ragas-evaluation", "workflow.name": workflow_name} - ) + resource = Resource.create({"service.name": "ragas-evaluation", "workflow.name": workflow_name}) # Create MeterProvider with the exporter and resource provider = MeterProvider(resource=resource, metric_readers=[reader]) @@ -71,9 +66,7 @@ def create_and_push_metrics( # Set the gauge value with workflow_name as an attribute gauge.set(score, {"workflow_name": workflow_name}) - logger.info( - f"Set metric 'ragas_evaluation_{metric_name}{{workflow_name=\"{workflow_name}\"}}' to {score}" - ) + logger.info(f"Set metric 'ragas_evaluation_{metric_name}{{workflow_name=\"{workflow_name}\"}}' to {score}") # Force flush to ensure metrics are sent provider.force_flush() @@ -88,14 +81,10 @@ def create_and_push_metrics( logger.info("Published metrics:") for metric_name, score in overall_scores.items(): - logger.info( - f' - ragas_evaluation_{metric_name}{{workflow_name="{workflow_name}"}}: {score}' - ) + logger.info(f' - ragas_evaluation_{metric_name}{{workflow_name="{workflow_name}"}}: {score}') -def publish_metrics( - input_file: str, workflow_name: str | None = None, otlp_endpoint: str | None = None -) -> None: +def publish_metrics(input_file: str, workflow_name: str, otlp_endpoint: str) -> None: """ Publish evaluation metrics via OpenTelemetry OTLP. @@ -132,9 +121,7 @@ def publish_metrics( python3 scripts/publish.py weather-assistant-test http://localhost:4318 """ - parser = argparse.ArgumentParser( - description="Publish RAGAS evaluation metrics via OpenTelemetry OTLP" - ) + parser = argparse.ArgumentParser(description="Publish RAGAS evaluation metrics via OpenTelemetry OTLP") parser.add_argument( "workflow_name", help="Name of the test workflow (e.g., 'weather-assistant-test')", diff --git a/testworkflows/scripts/run.py b/testworkflows/scripts/run.py index 9e05871..ede0d76 100644 --- a/testworkflows/scripts/run.py +++ b/testworkflows/scripts/run.py @@ -1,22 +1,18 @@ -import asyncio import argparse -import httpx - +import asyncio import logging from logging import Logger - from uuid import uuid4 -from pydantic import BaseModel -from ragas import Dataset, experiment - +import httpx +from a2a.client.client import Client, ClientConfig from a2a.client.client_factory import ClientFactory, minimal_agent_card -from a2a.client.client import ClientConfig, Client - from a2a.types import ( - Message, AgentCard, + Message, ) +from pydantic import BaseModel +from ragas import Dataset, experiment # Set up module-level logger logging.basicConfig(level=logging.INFO) @@ -72,9 +68,7 @@ async def run_agent_experiment(row, agent_url: str) -> dict[str, str | list]: if isinstance(response, tuple): task, _ = response if task: - artifacts: list = task.model_dump( - mode="json", include={"artifacts"} - ).get("artifacts", []) + artifacts: list = task.model_dump(mode="json", include={"artifacts"}).get("artifacts", []) # Extract the model response if artifacts and artifacts[0].get("parts"): @@ -102,16 +96,12 @@ async def main(agent_url: str) -> None: # Load existing Ragas dataset logger.info("Loading Ragas dataset from data/datasets/ragas_dataset.jsonl") - dataset: Dataset[BaseModel] = Dataset.load( - name="ragas_dataset", backend="local/jsonl", root_dir="./data" - ) + dataset: Dataset[BaseModel] = Dataset.load(name="ragas_dataset", backend="local/jsonl", root_dir="./data") logger.info(f"Dataset loaded with {len(dataset)} samples") # Run the experiment logger.info("Starting experiment...") - await run_agent_experiment.arun( - dataset, name="ragas_experiment", agent_url=agent_url - ) + await run_agent_experiment.arun(dataset, name="ragas_experiment", agent_url=agent_url) logger.info("Experiment completed successfully") logger.info("Results saved to data/experiments/ragas_experiment.jsonl") diff --git a/testworkflows/scripts/setup.py b/testworkflows/scripts/setup.py index 99c1a87..48a98fb 100644 --- a/testworkflows/scripts/setup.py +++ b/testworkflows/scripts/setup.py @@ -1,17 +1,14 @@ import argparse - -import requests -from requests import Response - +from io import BytesIO from pathlib import Path from typing import Callable -from io import BytesIO import pandas as pd +import requests from pandas import DataFrame from pydantic import BaseModel from ragas import Dataset - +from requests import Response def dataframe_to_ragas_dataset(dataframe: DataFrame) -> None: @@ -38,10 +35,6 @@ def dataframe_to_ragas_dataset(dataframe: DataFrame) -> None: root_dir="./data", ) - """# Append all samples to the dataset - for sample in dataset_samples: - dataset.append(sample)""" - # Save the dataset dataset.save() diff --git a/testworkflows/tests/test_e2e.py b/testworkflows/tests/test_e2e.py index 6f69272..fca4fe8 100755 --- a/testworkflows/tests/test_e2e.py +++ b/testworkflows/tests/test_e2e.py @@ -20,16 +20,14 @@ """ import argparse +import logging import subprocess import sys -import logging from pathlib import Path from typing import List # Set up logging -logging.basicConfig( - level=logging.INFO, format="%(asctime)s - %(levelname)s - %(message)s" -) +logging.basicConfig(level=logging.INFO, format="%(asctime)s - %(levelname)s - %(message)s") logger = logging.getLogger(__name__) diff --git a/testworkflows/tests/test_evaluate.py b/testworkflows/tests/test_evaluate.py index 45c4671..83022bf 100644 --- a/testworkflows/tests/test_evaluate.py +++ b/testworkflows/tests/test_evaluate.py @@ -4,21 +4,20 @@ Tests the RAGAS evaluation functionality. """ -import unittest -import tempfile -import shutil import json +import shutil +import sys +import tempfile +import unittest from pathlib import Path from unittest.mock import MagicMock -from ragas.dataset_schema import EvaluationResult import pandas as pd - -import sys +from ragas.dataset_schema import EvaluationResult sys.path.insert(0, str(Path(__file__).parent.parent / "scripts")) -from evaluate import format_evaluation_scores, main, AVAILABLE_METRICS +from evaluate import AVAILABLE_METRICS, format_evaluation_scores, main class TestFormatEvaluationScores(unittest.TestCase): @@ -28,9 +27,7 @@ def test_overall_scores_calculation(self): """Test that overall scores are calculated correctly""" mock_result = MagicMock(spec=EvaluationResult) - df = pd.DataFrame( - {"faithfulness": [0.9, 0.8, 0.7], "answer_relevancy": [0.85, 0.75, 0.65]} - ) + df = pd.DataFrame({"faithfulness": [0.9, 0.8, 0.7], "answer_relevancy": [0.85, 0.75, 0.65]}) mock_result.to_pandas.return_value = df # Mock _repr_dict with calculated averages @@ -47,9 +44,7 @@ def test_overall_scores_calculation(self): # Verify overall scores are correct self.assertAlmostEqual(formatted.overall_scores["faithfulness"], 0.8, places=2) - self.assertAlmostEqual( - formatted.overall_scores["answer_relevancy"], 0.75, places=2 - ) + self.assertAlmostEqual(formatted.overall_scores["answer_relevancy"], 0.75, places=2) def test_individual_results_present(self): """Test that individual results are included""" diff --git a/testworkflows/tests/test_publish.py b/testworkflows/tests/test_publish.py index b5c298b..1d64534 100644 --- a/testworkflows/tests/test_publish.py +++ b/testworkflows/tests/test_publish.py @@ -4,19 +4,17 @@ Tests the Prometheus metrics publishing functionality. """ -import unittest -import tempfile -import shutil import json -from pathlib import Path -from unittest.mock import patch, MagicMock - - +import shutil import sys +import tempfile +import unittest +from pathlib import Path +from unittest.mock import MagicMock, patch sys.path.insert(0, str(Path(__file__).parent.parent / "scripts")) -from publish import get_overall_scores, create_and_push_metrics, publish_metrics +from publish import create_and_push_metrics, get_overall_scores, publish_metrics class TestGetOverallScores(unittest.TestCase): diff --git a/testworkflows/tests/test_run.py b/testworkflows/tests/test_run.py index 13489c9..4533944 100644 --- a/testworkflows/tests/test_run.py +++ b/testworkflows/tests/test_run.py @@ -4,18 +4,16 @@ Tests the agent query execution and experiment functionality. """ -import unittest -import tempfile import shutil -from pathlib import Path -from unittest.mock import patch, MagicMock, AsyncMock - - import sys +import tempfile +import unittest +from pathlib import Path +from unittest.mock import AsyncMock, MagicMock, patch sys.path.insert(0, str(Path(__file__).parent.parent / "scripts")) -from run import initialize_client, run_agent_experiment, main +from run import initialize_client, main, run_agent_experiment class TestInitializeClient(unittest.TestCase): @@ -23,9 +21,7 @@ class TestInitializeClient(unittest.TestCase): @patch("run.ClientFactory") @patch("run.minimal_agent_card") - async def test_initialize_client_creates_client( - self, mock_agent_card, mock_factory - ): + async def test_initialize_client_creates_client(self, mock_agent_card, mock_factory): """Test that initialize_client creates a client correctly""" # Mock the agent card mock_card = MagicMock() @@ -60,9 +56,7 @@ def tearDown(self): @patch("run.logging.getLogger") @patch("run.initialize_client") - async def test_run_agent_experiment_success( - self, mock_init_client, mock_get_logger - ): + async def test_run_agent_experiment_success(self, mock_init_client, mock_get_logger): """Test successful agent query execution""" # Mock logger mock_logger = MagicMock() @@ -104,9 +98,7 @@ async def test_experiment_func(row, agent_url): return await run_agent_experiment.func(row, agent_url=agent_url) # Call the function - result = await test_experiment_func( - test_row, agent_url="http://test-agent:8000" - ) + result = await test_experiment_func(test_row, agent_url="http://test-agent:8000") # Verify result structure self.assertIn("user_input", result) @@ -146,9 +138,7 @@ async def test_experiment_func(row, agent_url): return await run_agent_experiment.func(row, agent_url=agent_url) # Call the function - result = await test_experiment_func( - test_row, agent_url="http://test-agent:8000" - ) + result = await test_experiment_func(test_row, agent_url="http://test-agent:8000") # Verify error is captured in response self.assertIn("response", result) diff --git a/testworkflows/tests/test_setup.py b/testworkflows/tests/test_setup.py index d1435fe..fa701ab 100644 --- a/testworkflows/tests/test_setup.py +++ b/testworkflows/tests/test_setup.py @@ -4,20 +4,19 @@ Tests the dataset download, conversion, and Ragas dataset creation functionality. """ -import unittest -import tempfile import shutil -from pathlib import Path +import sys +import tempfile +import unittest from io import BytesIO -from unittest.mock import patch, MagicMock +from pathlib import Path +from unittest.mock import MagicMock, patch import pandas as pd -import sys - sys.path.insert(0, str(Path(__file__).parent.parent / "scripts")) -from setup import custom_convert_csv, get_converter, dataframe_to_ragas_dataset, main +from setup import custom_convert_csv, dataframe_to_ragas_dataset, get_converter, main class TestCustomConvertCSV(unittest.TestCase): @@ -107,12 +106,8 @@ def test_creates_ragas_dataset_file(self): dataframe_to_ragas_dataset(df) # Check for the file in the datasets subdirectory - dataset_file = ( - Path(self.temp_dir) / "data" / "datasets" / "ragas_dataset.jsonl" - ) - self.assertTrue( - dataset_file.exists(), f"Dataset file not found at {dataset_file}" - ) + dataset_file = Path(self.temp_dir) / "data" / "datasets" / "ragas_dataset.jsonl" + self.assertTrue(dataset_file.exists(), f"Dataset file not found at {dataset_file}") finally: os.chdir(self.original_cwd) @@ -150,12 +145,8 @@ def test_main_with_csv(self, mock_get): main("https://example.com/data.csv") # Verify dataset was created in datasets subdirectory - dataset_file = ( - Path(self.temp_dir) / "data" / "datasets" / "ragas_dataset.jsonl" - ) - self.assertTrue( - dataset_file.exists(), f"Dataset file not found at {dataset_file}" - ) + dataset_file = Path(self.temp_dir) / "data" / "datasets" / "ragas_dataset.jsonl" + self.assertTrue(dataset_file.exists(), f"Dataset file not found at {dataset_file}") # Verify requests.get was called mock_get.assert_called_once_with("https://example.com/data.csv") @@ -188,12 +179,8 @@ def test_main_with_json(self, mock_get): main("https://example.com/data.json") # Verify dataset was created in datasets subdirectory - dataset_file = ( - Path(self.temp_dir) / "data" / "datasets" / "ragas_dataset.jsonl" - ) - self.assertTrue( - dataset_file.exists(), f"Dataset file not found at {dataset_file}" - ) + dataset_file = Path(self.temp_dir) / "data" / "datasets" / "ragas_dataset.jsonl" + self.assertTrue(dataset_file.exists(), f"Dataset file not found at {dataset_file}") finally: os.chdir(self.original_cwd) From c30b80aa3c2f59bb36b380ee92da0af268d94575 Mon Sep 17 00:00:00 2001 From: MiaAppel Date: Thu, 6 Nov 2025 12:13:23 +0100 Subject: [PATCH 13/61] FIX: Add config for Import-Linter, Ruff & Bandit to pyproject.toml --- testworkflows/pyproject.toml | 26 +++++++++++++++++++++++++- 1 file changed, 25 insertions(+), 1 deletion(-) diff --git a/testworkflows/pyproject.toml b/testworkflows/pyproject.toml index 209fb1c..bdd82cc 100644 --- a/testworkflows/pyproject.toml +++ b/testworkflows/pyproject.toml @@ -42,4 +42,28 @@ bandit = "bandit -c pyproject.toml -r ." mypy = "mypy ." lint-imports = "lint-imports" -check = ["test", "mypy", "bandit", "ruff", "lint-imports"] \ No newline at end of file +check = ["test", "mypy", "bandit", "ruff", "lint-imports"] + +[tool.importlinter] +root_package = "scripts" + +[tool.ruff] +# Allow lines to be as long as 120. +line-length = 120 + + +[tool.ruff.lint] +# https://docs.astral.sh/ruff/rules/ +# I001 --> enable import sorting rules +# Q --> enable flake8-quotes rules for consistent quote style +# N --> pep8-naming for proper naming conventions +# PT --> flake8-pytest-style for pytest best practices +# TID251 --> banned relative imports +# DTZ --> datetime timezone awareness +extend-select = ["Q", "N", "I001", "PT", "TID251", "DTZ"] + +[tool.bandit] +exclude_dirs = [".cache", ".venv"] + +[tool.bandit.assert_used] +skips = ["*_test.py", "*test_*.py"] \ No newline at end of file From 2bd09d4e86a7afaf7e4720f25708271464ce80c8 Mon Sep 17 00:00:00 2001 From: MiaAppel Date: Thu, 6 Nov 2025 12:52:22 +0100 Subject: [PATCH 14/61] FIX: Type Errors in run.py --- testworkflows/scripts/run.py | 9 ++++++--- 1 file changed, 6 insertions(+), 3 deletions(-) diff --git a/testworkflows/scripts/run.py b/testworkflows/scripts/run.py index ede0d76..3b79de1 100644 --- a/testworkflows/scripts/run.py +++ b/testworkflows/scripts/run.py @@ -10,6 +10,9 @@ from a2a.types import ( AgentCard, Message, + Part, + Role, + TextPart, ) from pydantic import BaseModel from ragas import Dataset, experiment @@ -56,9 +59,9 @@ async def run_agent_experiment(row, agent_url: str) -> dict[str, str | list]: input_text = row.get("user_input") message = Message( - role="user", - parts=[{"kind": "text", "text": input_text}], - messageId=uuid4().hex, + role=Role.user, + parts=[Part(TextPart(text=input_text))], + message_id=uuid4().hex, ) logger.info(f"Processing: {input_text}") From bf019dfa3433e8c873f965c41b871b415aca9e09 Mon Sep 17 00:00:00 2001 From: MiaAppel Date: Thu, 6 Nov 2025 12:57:16 +0100 Subject: [PATCH 15/61] FIX: Type Errors in setup.py --- testworkflows/scripts/setup.py | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/testworkflows/scripts/setup.py b/testworkflows/scripts/setup.py index 48a98fb..ead6016 100644 --- a/testworkflows/scripts/setup.py +++ b/testworkflows/scripts/setup.py @@ -1,7 +1,7 @@ import argparse from io import BytesIO from pathlib import Path -from typing import Callable +from typing import Any, Callable, cast import pandas as pd import requests @@ -25,7 +25,7 @@ def dataframe_to_ragas_dataset(dataframe: DataFrame) -> None: output_dir.mkdir(exist_ok=True) # Convert DataFrame to list of dictionaries - dataset_samples = dataframe.to_dict(orient="records") + dataset_samples = cast(list[dict[str, Any]], dataframe.to_dict(orient="records")) # Create Ragas Dataset dataset: Dataset[BaseModel] = Dataset( @@ -43,7 +43,7 @@ def get_converter(url: str) -> Callable[[BytesIO], DataFrame]: """Extract the file format from the URL and return the converter function""" suffix = Path(url).suffix.lower() - format_map = { + format_map: dict[str, Callable[[BytesIO], DataFrame]] = { ".json": pd.read_json, ".csv": custom_convert_csv, ".parquet": pd.read_parquet, From ad397d0ce0f48dbaa47292621fa302d7f6ac7e03 Mon Sep 17 00:00:00 2001 From: MiaAppel Date: Thu, 6 Nov 2025 13:13:19 +0100 Subject: [PATCH 16/61] FIX: Remove unnecessary dependencies & add missing ones --- testworkflows/pyproject.toml | 12 ++---------- 1 file changed, 2 insertions(+), 10 deletions(-) diff --git a/testworkflows/pyproject.toml b/testworkflows/pyproject.toml index bdd82cc..bb43d52 100644 --- a/testworkflows/pyproject.toml +++ b/testworkflows/pyproject.toml @@ -5,29 +5,21 @@ description = "Testbench to evaluate agents using Ragas" requires-python = ">=3.12" dependencies = [ "a2a>=0.44", - "a2a-sdk>=0.3.0", "bandit[toml]>=1.7.8", - "crefi>=2.0.9", "httpx>=0.28.1", "mypy>=1.17.0", "import-linter>=2.0", + "langchain-openai>=1.0.2", "pandas>=2.3.3", "poethepoet>=0.31.1", "pyarrow>=21.0.0", - "starlette>=0.48.0", - "utils>=1.0.2", - "wget>=3.2", - "opentelemetry-instrumentation-starlette>=0.56b0", "ragas>=0.3.5", + "requests>=2.32.5", "ruff>=0.12.7", - "datasets>=2.14.0", "opentelemetry-api>=1.20.0", "opentelemetry-sdk>=1.20.0", "opentelemetry-exporter-otlp-proto-http>=1.20.0", "pytest>=7.4.0", - "langchain-google-genai>=2.0.0", - "langchain-google-vertexai>=2.0.0", - "python-dotenv>=1.0.0", ] [tool.poe.tasks] From d7dda81e9eb1f8a9e39c068dd9c29b63faa0dbf1 Mon Sep 17 00:00:00 2001 From: MiaAppel Date: Thu, 6 Nov 2025 13:53:26 +0100 Subject: [PATCH 17/61] FIX: Type Errors in evaluate.py --- testworkflows/scripts/evaluate.py | 22 +++++++++++++++++----- 1 file changed, 17 insertions(+), 5 deletions(-) diff --git a/testworkflows/scripts/evaluate.py b/testworkflows/scripts/evaluate.py index 88f6bc5..147097a 100644 --- a/testworkflows/scripts/evaluate.py +++ b/testworkflows/scripts/evaluate.py @@ -112,9 +112,17 @@ def format_evaluation_scores( # Check if token usage data was collected (some metrics don't use LLMs or use separate LLM instances) if ragas_result.cost_cb and hasattr(ragas_result.cost_cb, "usage_data") and ragas_result.cost_cb.usage_data: token_usage = ragas_result.total_tokens() + # Handle both single TokenUsage and list of TokenUsage + if isinstance(token_usage, list): + input_tokens = sum(usage.input_tokens for usage in token_usage) + output_tokens = sum(usage.output_tokens for usage in token_usage) + else: + input_tokens = token_usage.input_tokens + output_tokens = token_usage.output_tokens + total_tokens = { - "input_tokens": token_usage.input_tokens, - "output_tokens": token_usage.output_tokens, + "input_tokens": input_tokens, + "output_tokens": output_tokens, } total_cost = ragas_result.total_cost( cost_per_input_token=cost_per_input_token, @@ -137,7 +145,7 @@ def format_evaluation_scores( def main( output_file: str, model: str, - metrics: list[str] = None, + metrics: list[str] | None = None, cost_per_input_token: float = 5.0 / 1e6, cost_per_output_token: float = 15.0 / 1e6, ) -> None: @@ -151,11 +159,11 @@ def main( """ # Check if any metrics were provided if metrics is None: - raise ArgumentError("No metrics were provided as arguments") + raise ArgumentError(argument=metrics, message="No metrics were provided as arguments") # Create LLM client using the AI-Gateway ragas_llm = ChatOpenAI(model=model) - llm = LangchainLLMWrapper(ragas_llm) + llm: LangchainLLMWrapper = LangchainLLMWrapper(ragas_llm) dataset = EvaluationDataset.from_jsonl("data/experiments/ragas_experiment.jsonl") @@ -168,6 +176,10 @@ def main( token_usage_parser=get_token_usage_for_openai, ) + # Ensure we have an EvaluationResult (not an Executor) + if not isinstance(ragas_result, EvaluationResult): + raise TypeError(f"Expected EvaluationResult, got {type(ragas_result)}") + # Format results logger.info("Formatting evaluation scores...") evaluation_scores = format_evaluation_scores( From 8f36726456dd54f838c73c5c6b053e99af8b634a Mon Sep 17 00:00:00 2001 From: MiaAppel Date: Thu, 6 Nov 2025 13:56:29 +0100 Subject: [PATCH 18/61] FIX: Add scripts/ to mypy_path --- testworkflows/pyproject.toml | 3 +++ 1 file changed, 3 insertions(+) diff --git a/testworkflows/pyproject.toml b/testworkflows/pyproject.toml index bb43d52..459bd52 100644 --- a/testworkflows/pyproject.toml +++ b/testworkflows/pyproject.toml @@ -54,6 +54,9 @@ line-length = 120 # DTZ --> datetime timezone awareness extend-select = ["Q", "N", "I001", "PT", "TID251", "DTZ"] +[tool.mypy] +mypy_path = "scripts" + [tool.bandit] exclude_dirs = [".cache", ".venv"] From b027cbc99e6cd67c58e6341e9086832e851e4186 Mon Sep 17 00:00:00 2001 From: MiaAppel Date: Thu, 6 Nov 2025 14:35:01 +0100 Subject: [PATCH 19/61] FIX: Adapt test_e2e.py as a Pytest and add it to the Workflows --- .github/workflows/test-testworkflows.yml | 2 +- testworkflows/pyproject.toml | 4 +- testworkflows/tests/test_e2e.py | 131 ++++++++--------------- 3 files changed, 47 insertions(+), 90 deletions(-) diff --git a/.github/workflows/test-testworkflows.yml b/.github/workflows/test-testworkflows.yml index 62cc731..2f093c7 100644 --- a/.github/workflows/test-testworkflows.yml +++ b/.github/workflows/test-testworkflows.yml @@ -32,4 +32,4 @@ jobs: run: uv sync - name: Run pytest (skip E2E tests) - run: uv run pytest tests/ -v --ignore=tests/test_e2e.py + run: uv run pytest tests/ -v diff --git a/testworkflows/pyproject.toml b/testworkflows/pyproject.toml index 459bd52..afd29f6 100644 --- a/testworkflows/pyproject.toml +++ b/testworkflows/pyproject.toml @@ -5,6 +5,7 @@ description = "Testbench to evaluate agents using Ragas" requires-python = ">=3.12" dependencies = [ "a2a>=0.44", + "a2a-sdk>=0.3.10", "bandit[toml]>=1.7.8", "httpx>=0.28.1", "mypy>=1.17.0", @@ -23,8 +24,7 @@ dependencies = [ ] [tool.poe.tasks] -test = "pytest tests/ -m" -test-watch = "ptw ." +test = "pytest tests/ -v" format = "ruff format" lint = "ruff check --fix" diff --git a/testworkflows/tests/test_e2e.py b/testworkflows/tests/test_e2e.py index fca4fe8..3eff507 100755 --- a/testworkflows/tests/test_e2e.py +++ b/testworkflows/tests/test_e2e.py @@ -1,28 +1,24 @@ """ -End-to-end test script that runs all scripts in the correct order: +End-to-end test that runs all scripts in the correct order: 1. setup.py - Downloads, converts and saves Ragas Dataset to data/datasets/ragas_dataset.jsonl 2. run.py - Runs agent queries on the dataset and saves Ragas Experiment to data/experiments/ragas_experiment.jsonl 3. evaluate.py - Evaluates results using RAGAS metrics and saves result to results/evaluation_scores.json 4. publish.py - Publishes metrics via OpenTelemetry OTLP Usage: - python test_e2e.py --dataset-url --agent-url --model \ - --metrics [METRIC2 ...] --workflow-name \ - [--otlp-endpoint ] - -Example: - python test_e2e.py \ - --dataset-url "https://example.com/dataset.csv" \ - --agent-url "http://localhost:8000" \ - --model "gemini-flash-latest" \ - --metrics faithfulness answer_relevancy \ - --workflow-name "weather-assistant-test" + pytest tests/test_e2e.py + + # With custom configuration via environment variables: + E2E_DATASET_URL="https://example.com/data.csv" \ + E2E_AGENT_URL="http://localhost:8000" \ + E2E_MODEL="gemini-flash-latest" \ + E2E_METRICS="faithfulness,answer_relevancy" \ + E2E_WORKFLOW_NAME="weather-assistant-test" \ + pytest tests/test_e2e.py """ -import argparse import logging import subprocess -import sys from pathlib import Path from typing import List @@ -159,7 +155,7 @@ def run_agent_queries(self) -> bool: def run_evaluation(self) -> bool: """Run evaluate.py to evaluate results using RAGAS metrics.""" - command = ["python3", str(self.evaluate_script), self.model, *self.metrics] + command = ["python3", str(self.evaluate_script), self.model] + self.metrics success = self.run_command(command, "3. Evaluate - Calculate RAGAS Metrics") if success: @@ -217,82 +213,43 @@ def run_full_pipeline(self) -> bool: return True -def main(): - """Parse arguments and run the E2E test""" - parser = argparse.ArgumentParser( - description="End-to-end test runner for the agent testing pipeline", - formatter_class=argparse.RawDescriptionHelpFormatter, - epilog=""" - Examples: - # Basic usage - python test_e2e.py \\ - --dataset-url "https://example.com/data.csv" \\ - --agent-url "http://localhost:8000" \\ - --model "gemini-flash-latest" \\ - --metrics faithfulness answer_relevancy \\ - --workflow-name "my-test" - - # With custom OTLP endpoint - python test_e2e.py \\ - --dataset-url "https://example.com/data.csv" \\ - --agent-url "http://localhost:8000" \\ - --model "gemini-flash-latest" \\ - --metrics faithfulness \\ - --workflow-name "my-test" \\ - --otlp-endpoint "http://otlp.example.com:4318" - """, - ) - - parser.add_argument( - "--dataset-url", - required=True, - help="URL to the dataset in .csv / .json / .parquet format", - ) - - parser.add_argument("--agent-url", required=True, help="URL to agent") - - parser.add_argument( - "--model", - required=True, - help="Model name to use for evaluation (e.g., gemini-flash-latest)", - ) - - parser.add_argument( - "--metrics", - nargs="+", - required=True, - help="At least one (or more) metrics to evaluate (e.g., faithfulness, answer_relevancy)", - ) - - parser.add_argument( - "--workflow-name", - required=True, - help="Name of the test workflow (e.g., 'weather-assistant-test')", - ) - - parser.add_argument( - "--otlp-endpoint", - default="localhost:4318", - help="URL of the OTLP HTTP endpoint (default: localhost:4318)", - ) - - args = parser.parse_args() +def test_e2e_pipeline(): + """Pytest test function for the E2E pipeline. + + This test can be run with pytest and uses environment variables or defaults + for configuration. To customize, set these environment variables: + - E2E_DATASET_URL + - E2E_AGENT_URL + - E2E_MODEL + - E2E_METRICS (comma-separated) + - E2E_WORKFLOW_NAME + - E2E_OTLP_ENDPOINT + + Example: + E2E_DATASET_URL="https://example.com/data.csv" pytest tests/test_e2e.py + """ + import os + + # Get configuration from environment variables with sensible defaults + dataset_url = os.getenv("E2E_DATASET_URL", "http://localhost:8000/dataset.json") + agent_url = os.getenv("E2E_AGENT_URL", "http://localhost:11010") + model = os.getenv("E2E_MODEL", "gemini-2.5-flash-lite") + metrics_str = os.getenv("E2E_METRICS", "faithfulness") + metrics = [m.strip() for m in metrics_str.split(",")] + workflow_name = os.getenv("E2E_WORKFLOW_NAME", "Test Workflow") + otlp_endpoint = os.getenv("E2E_OTLP_ENDPOINT", "localhost:4318") # Create and run the test pipeline runner = E2ETestRunner( - dataset_url=args.dataset_url, - agent_url=args.agent_url, - model=args.model, - metrics=args.metrics, - workflow_name=args.workflow_name, - otlp_endpoint=args.otlp_endpoint, + dataset_url=dataset_url, + agent_url=agent_url, + model=model, + metrics=metrics, + workflow_name=workflow_name, + otlp_endpoint=otlp_endpoint, ) success = runner.run_full_pipeline() - # Exit with appropriate status code - sys.exit(0 if success else 1) - - -if __name__ == "__main__": - main() + # Use pytest assertion instead of sys.exit + assert success, "E2E pipeline failed - check logs above for details" From ca36c954559e225cd790a5087fafe939240a4f89 Mon Sep 17 00:00:00 2001 From: MiaAppel Date: Thu, 6 Nov 2025 14:52:08 +0100 Subject: [PATCH 20/61] FIX: Adapt test_publish.py to the OpenTelemetry OTLP, adjust Error in test_evaluate.py --- testworkflows/tests/test_evaluate.py | 3 +- testworkflows/tests/test_publish.py | 151 ++++++++++++++++++--------- 2 files changed, 102 insertions(+), 52 deletions(-) diff --git a/testworkflows/tests/test_evaluate.py b/testworkflows/tests/test_evaluate.py index 83022bf..490db36 100644 --- a/testworkflows/tests/test_evaluate.py +++ b/testworkflows/tests/test_evaluate.py @@ -9,6 +9,7 @@ import sys import tempfile import unittest +from argparse import ArgumentError from pathlib import Path from unittest.mock import MagicMock @@ -132,7 +133,7 @@ def test_main_no_metrics(self): try: # When metrics is None, the function should raise an error # The actual error type depends on implementation - with self.assertRaises((TypeError, AttributeError)): + with self.assertRaises((ArgumentError)): main( output_file="results/evaluation_scores.json", model="gemini-flash-latest", diff --git a/testworkflows/tests/test_publish.py b/testworkflows/tests/test_publish.py index 1d64534..211fa11 100644 --- a/testworkflows/tests/test_publish.py +++ b/testworkflows/tests/test_publish.py @@ -1,7 +1,7 @@ """ Unit tests for publish.py -Tests the Prometheus metrics publishing functionality. +Tests the OpenTelemetry OTLP metrics publishing functionality. """ import json @@ -55,78 +55,109 @@ def test_file_not_found(self): class TestCreateAndPushMetrics(unittest.TestCase): """Test the create_and_push_metrics function""" - @patch("publish.push_to_gateway") - @patch("publish.Gauge") - def test_creates_gauges_for_each_metric(self, mock_gauge_class, mock_push): + @patch("publish.OTLPMetricExporter") + @patch("publish.MeterProvider") + @patch("publish.metrics.get_meter") + def test_creates_gauges_for_each_metric(self, mock_get_meter, mock_provider_class, mock_exporter_class): """Test that a Gauge is created for each metric""" overall_scores = {"faithfulness": 0.85, "answer_relevancy": 0.90} - # Mock the Gauge instances - mock_gauge_instance = MagicMock() - mock_gauge_class.return_value = mock_gauge_instance + # Mock the meter and gauge + mock_gauge = MagicMock() + mock_meter = MagicMock() + mock_meter.create_gauge.return_value = mock_gauge + mock_get_meter.return_value = mock_meter + + # Mock the provider + mock_provider = MagicMock() + mock_provider_class.return_value = mock_provider create_and_push_metrics( overall_scores=overall_scores, workflow_name="test-workflow", - pushgateway_url="localhost:9091", + otlp_endpoint="localhost:4318", ) - # Verify Gauge was called for each metric - self.assertEqual(mock_gauge_class.call_count, 2) + # Verify create_gauge was called for each metric + self.assertEqual(mock_meter.create_gauge.call_count, 2) # Verify gauge names - gauge_calls = mock_gauge_class.call_args_list - gauge_names = [call[0][0] for call in gauge_calls] + gauge_calls = mock_meter.create_gauge.call_args_list + gauge_names = [call[1]["name"] for call in gauge_calls] self.assertIn("ragas_evaluation_faithfulness", gauge_names) self.assertIn("ragas_evaluation_answer_relevancy", gauge_names) - @patch("publish.push_to_gateway") - @patch("publish.Gauge") - def test_sets_gauge_values(self, mock_gauge_class, mock_push): + @patch("publish.OTLPMetricExporter") + @patch("publish.MeterProvider") + @patch("publish.metrics.get_meter") + def test_sets_gauge_values(self, mock_get_meter, mock_provider_class, mock_exporter_class): """Test that gauge values are set correctly""" overall_scores = {"faithfulness": 0.85} - # Mock the Gauge instance and labels - mock_gauge_instance = MagicMock() - mock_labels = MagicMock() - mock_gauge_instance.labels.return_value = mock_labels - mock_gauge_class.return_value = mock_gauge_instance + # Mock the meter and gauge + mock_gauge = MagicMock() + mock_meter = MagicMock() + mock_meter.create_gauge.return_value = mock_gauge + mock_get_meter.return_value = mock_meter + + # Mock the provider + mock_provider = MagicMock() + mock_provider_class.return_value = mock_provider create_and_push_metrics( overall_scores=overall_scores, workflow_name="test-workflow", - pushgateway_url="localhost:9091", + otlp_endpoint="localhost:4318", ) - # Verify labels were set with workflow_name - mock_gauge_instance.labels.assert_called_with(workflow_name="test-workflow") - - # Verify gauge value was set - mock_labels.set.assert_called_with(0.85) + # Verify gauge.set was called with correct value and attributes + mock_gauge.set.assert_called_once_with(0.85, {"workflow_name": "test-workflow"}) - @patch("publish.push_to_gateway") - def test_pushes_to_gateway(self, mock_push): - """Test that metrics are pushed to Pushgateway""" + @patch("publish.OTLPMetricExporter") + @patch("publish.MeterProvider") + @patch("publish.metrics.get_meter") + def test_pushes_via_otlp(self, mock_get_meter, mock_provider_class, mock_exporter_class): + """Test that metrics are pushed via OTLP""" overall_scores = {"faithfulness": 0.85} + # Mock the meter and gauge + mock_gauge = MagicMock() + mock_meter = MagicMock() + mock_meter.create_gauge.return_value = mock_gauge + mock_get_meter.return_value = mock_meter + + # Mock the provider + mock_provider = MagicMock() + mock_provider_class.return_value = mock_provider + create_and_push_metrics( overall_scores=overall_scores, workflow_name="test-workflow", - pushgateway_url="localhost:9091", + otlp_endpoint="localhost:4318", ) - # Verify push_to_gateway was called - mock_push.assert_called_once() - - # Verify push parameters - call_args = mock_push.call_args - self.assertEqual(call_args[0][0], "localhost:9091") - self.assertEqual(call_args[1]["job"], "ragas_evaluation") - - @patch("publish.push_to_gateway") - def test_handles_push_error(self, mock_push): - """Test error handling when push fails""" - mock_push.side_effect = Exception("Connection refused") + # Verify OTLPMetricExporter was initialized with correct endpoint + mock_exporter_class.assert_called_once_with(endpoint="http://localhost:4318/v1/metrics") + + # Verify force_flush and shutdown were called + mock_provider.force_flush.assert_called_once() + mock_provider.shutdown.assert_called_once() + + @patch("publish.OTLPMetricExporter") + @patch("publish.MeterProvider") + @patch("publish.metrics.get_meter") + def test_handles_push_error(self, mock_get_meter, mock_provider_class, mock_exporter_class): + """Test error handling when OTLP export fails""" + # Mock the provider to raise an exception on force_flush + mock_provider = MagicMock() + mock_provider.force_flush.side_effect = Exception("Connection refused") + mock_provider_class.return_value = mock_provider + + # Mock the meter + mock_gauge = MagicMock() + mock_meter = MagicMock() + mock_meter.create_gauge.return_value = mock_gauge + mock_get_meter.return_value = mock_meter overall_scores = {"faithfulness": 0.85} @@ -134,11 +165,14 @@ def test_handles_push_error(self, mock_push): create_and_push_metrics( overall_scores=overall_scores, workflow_name="test-workflow", - pushgateway_url="localhost:9091", + otlp_endpoint="localhost:4318", ) self.assertIn("Connection refused", str(context.exception)) + # Verify shutdown is still called in finally block + mock_provider.shutdown.assert_called_once() + class TestPublishMetrics(unittest.TestCase): """Test the publish_metrics function""" @@ -169,7 +203,7 @@ def test_publish_metrics_calls_create_and_push(self, mock_create_push): publish_metrics( input_file=str(self.test_file), workflow_name="test-workflow", - pushgateway_url="localhost:9091", + otlp_endpoint="localhost:4318", ) # Verify create_and_push_metrics was called @@ -180,7 +214,7 @@ def test_publish_metrics_calls_create_and_push(self, mock_create_push): self.assertEqual(call_args[0][0]["faithfulness"], 0.85) self.assertEqual(call_args[0][0]["answer_relevancy"], 0.90) self.assertEqual(call_args[0][1], "test-workflow") - self.assertEqual(call_args[0][2], "localhost:9091") + self.assertEqual(call_args[0][2], "localhost:4318") @patch("publish.create_and_push_metrics") def test_publish_metrics_with_empty_scores(self, mock_create_push): @@ -195,7 +229,7 @@ def test_publish_metrics_with_empty_scores(self, mock_create_push): publish_metrics( input_file=str(empty_file), workflow_name="test-workflow", - pushgateway_url="localhost:9091", + otlp_endpoint="localhost:4318", ) # Verify create_and_push_metrics was NOT called @@ -237,17 +271,32 @@ def tearDown(self): """Clean up temporary directory""" shutil.rmtree(self.temp_dir, ignore_errors=True) - @patch("publish.push_to_gateway") - def test_publish_realistic_scores(self, mock_push): + @patch("publish.OTLPMetricExporter") + @patch("publish.MeterProvider") + @patch("publish.metrics.get_meter") + def test_publish_realistic_scores(self, mock_get_meter, mock_provider_class, mock_exporter_class): """Test publishing realistic evaluation scores""" + # Mock the meter and gauge + mock_gauge = MagicMock() + mock_meter = MagicMock() + mock_meter.create_gauge.return_value = mock_gauge + mock_get_meter.return_value = mock_meter + + # Mock the provider + mock_provider = MagicMock() + mock_provider_class.return_value = mock_provider + publish_metrics( input_file=str(self.test_file), workflow_name="weather-assistant-test", - pushgateway_url="localhost:9091", + otlp_endpoint="localhost:4318", ) - # Verify push was called - mock_push.assert_called_once() + # Verify OTLPMetricExporter was called + mock_exporter_class.assert_called_once() + + # Verify 4 metrics were created (faithfulness, answer_relevancy, context_precision, context_recall) + self.assertEqual(mock_meter.create_gauge.call_count, 4) if __name__ == "__main__": From 8072aa5a1c62d61257fbef9e6b9f85371c057b44 Mon Sep 17 00:00:00 2001 From: MiaAppel Date: Thu, 6 Nov 2025 14:54:18 +0100 Subject: [PATCH 21/61] FEAT: Use Python Version File to set Python Version --- .github/workflows/test-testworkflows.yml | 2 +- testworkflows/.python-version | 1 + 2 files changed, 2 insertions(+), 1 deletion(-) create mode 100644 testworkflows/.python-version diff --git a/.github/workflows/test-testworkflows.yml b/.github/workflows/test-testworkflows.yml index 2f093c7..110f18f 100644 --- a/.github/workflows/test-testworkflows.yml +++ b/.github/workflows/test-testworkflows.yml @@ -21,7 +21,7 @@ jobs: - name: Set up Python 3.12 uses: actions/setup-python@v5 with: - python-version: '3.12' + python-version-file: ".python-version" - name: Install uv run: | diff --git a/testworkflows/.python-version b/testworkflows/.python-version new file mode 100644 index 0000000..3a4f41e --- /dev/null +++ b/testworkflows/.python-version @@ -0,0 +1 @@ +3.13 \ No newline at end of file From 826225220ee3c5e1184be006a17251b644c6f86d Mon Sep 17 00:00:00 2001 From: MiaAppel Date: Thu, 6 Nov 2025 15:05:25 +0100 Subject: [PATCH 22/61] FIX: setup of test-testworkflows.yml --- .github/workflows/test-testworkflows.yml | 23 ++++++++++++----------- 1 file changed, 12 insertions(+), 11 deletions(-) diff --git a/.github/workflows/test-testworkflows.yml b/.github/workflows/test-testworkflows.yml index 110f18f..59712bc 100644 --- a/.github/workflows/test-testworkflows.yml +++ b/.github/workflows/test-testworkflows.yml @@ -15,21 +15,22 @@ jobs: working-directory: testworkflows steps: - - name: Checkout repository - uses: actions/checkout@v4 + - name: Checkout + uses: 'actions/checkout@v5' - - name: Set up Python 3.12 - uses: actions/setup-python@v5 + - name: Install uv + uses: 'astral-sh/setup-uv@v6' with: - python-version-file: ".python-version" + version: "0.8.17" + enable-cache: true - - name: Install uv - run: | - curl -LsSf https://astral.sh/uv/install.sh | sh - echo "$HOME/.cargo/bin" >> $GITHUB_PATH + - name: Set up Python + uses: 'actions/setup-python@v6' + with: + python-version-file: ".python-version" - - name: Sync dependencies with uv - run: uv sync + - name: Install Dependencies + run: uv sync --all-packages - name: Run pytest (skip E2E tests) run: uv run pytest tests/ -v From 986b301931246b6ee59ed25f825816840decf6db Mon Sep 17 00:00:00 2001 From: MiaAppel Date: Thu, 6 Nov 2025 15:05:25 +0100 Subject: [PATCH 23/61] FIX: setup of test-testworkflows.yml --- .github/workflows/test-testworkflows.yml | 23 ++++++++++++----------- 1 file changed, 12 insertions(+), 11 deletions(-) diff --git a/.github/workflows/test-testworkflows.yml b/.github/workflows/test-testworkflows.yml index 110f18f..cf9bef6 100644 --- a/.github/workflows/test-testworkflows.yml +++ b/.github/workflows/test-testworkflows.yml @@ -15,21 +15,22 @@ jobs: working-directory: testworkflows steps: - - name: Checkout repository - uses: actions/checkout@v4 + - name: Checkout + uses: 'actions/checkout@v5' - - name: Set up Python 3.12 - uses: actions/setup-python@v5 + - name: Install uv + uses: 'astral-sh/setup-uv@v6' with: - python-version-file: ".python-version" + version: "0.8.17" + enable-cache: true - - name: Install uv - run: | - curl -LsSf https://astral.sh/uv/install.sh | sh - echo "$HOME/.cargo/bin" >> $GITHUB_PATH + - name: Set up Python + uses: 'actions/setup-python@v6' + with: + python-version-file: "testworkflows/.python-version" - - name: Sync dependencies with uv - run: uv sync + - name: Install Dependencies + run: uv sync --all-packages - name: Run pytest (skip E2E tests) run: uv run pytest tests/ -v From 2116607745b647a5679b17ec1d527586709f3c90 Mon Sep 17 00:00:00 2001 From: MiaAppel Date: Thu, 6 Nov 2025 15:29:35 +0100 Subject: [PATCH 24/61] FEAT: add Tiltfile to test-testworkflows.yml to properly test test_e2e.py --- .github/workflows/test-testworkflows.yml | 26 +++++++++++++++++++++++- 1 file changed, 25 insertions(+), 1 deletion(-) diff --git a/.github/workflows/test-testworkflows.yml b/.github/workflows/test-testworkflows.yml index cf9bef6..1440715 100644 --- a/.github/workflows/test-testworkflows.yml +++ b/.github/workflows/test-testworkflows.yml @@ -32,5 +32,29 @@ jobs: - name: Install Dependencies run: uv sync --all-packages - - name: Run pytest (skip E2E tests) + - name: Set up Kubernetes (kind) + uses: 'helm/kind-action@v1' + with: + cluster_name: testbench-cluster + + - name: Install Tilt + uses: 'yokawasa/action-setup-kube-tools@v0.11.2' + with: + tilt: 'latest' + + - name: Start Tiltfile services + run: tilt ci + working-directory: .. + + - name: Wait for services to be ready + run: | + echo "Waiting for services to be ready..." + kubectl wait --for=condition=ready pod -l app=weather-agent --timeout=300s || true + kubectl wait --for=condition=ready pod -l app=ai-gateway-litellm --timeout=300s || true + kubectl wait --for=condition=ready pod -l app.kubernetes.io/name=lgtm --timeout=300s || true + + echo "Checking service status..." + kubectl get pods -A + + - name: Run pytest run: uv run pytest tests/ -v From d7db29ab32caaa496eb33b80b94f1428042b9230 Mon Sep 17 00:00:00 2001 From: MiaAppel Date: Thu, 6 Nov 2025 15:33:51 +0100 Subject: [PATCH 25/61] FEAT: add Tiltfile to test-testworkflows.yml to properly test test_e2e.py --- .github/workflows/test-testworkflows.yml | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/.github/workflows/test-testworkflows.yml b/.github/workflows/test-testworkflows.yml index 1440715..713737c 100644 --- a/.github/workflows/test-testworkflows.yml +++ b/.github/workflows/test-testworkflows.yml @@ -38,9 +38,9 @@ jobs: cluster_name: testbench-cluster - name: Install Tilt - uses: 'yokawasa/action-setup-kube-tools@v0.11.2' - with: - tilt: 'latest' + run: | + curl -fsSL https://raw.githubusercontent.com/tilt-dev/tilt/master/scripts/install.sh | bash + tilt version - name: Start Tiltfile services run: tilt ci From 14882b16c4f479d15cb8d08ebb85e8063303dd93 Mon Sep 17 00:00:00 2001 From: MiaAppel Date: Thu, 6 Nov 2025 15:41:06 +0100 Subject: [PATCH 26/61] FIX: Type Error in evaluate.py --- testworkflows/scripts/evaluate.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/testworkflows/scripts/evaluate.py b/testworkflows/scripts/evaluate.py index 147097a..62af603 100644 --- a/testworkflows/scripts/evaluate.py +++ b/testworkflows/scripts/evaluate.py @@ -162,8 +162,8 @@ def main( raise ArgumentError(argument=metrics, message="No metrics were provided as arguments") # Create LLM client using the AI-Gateway - ragas_llm = ChatOpenAI(model=model) - llm: LangchainLLMWrapper = LangchainLLMWrapper(ragas_llm) + ragas_llm: ChatOpenAI = ChatOpenAI(model=model) + llm = LangchainLLMWrapper(ragas_llm) # type: ignore[arg-type] dataset = EvaluationDataset.from_jsonl("data/experiments/ragas_experiment.jsonl") From a157286160d283d46e8abfe039e18337d9d280ce Mon Sep 17 00:00:00 2001 From: MiaAppel Date: Thu, 6 Nov 2025 15:41:27 +0100 Subject: [PATCH 27/61] FIX: Tiltfile Error in test-testworkflows.yml --- .github/workflows/test-testworkflows.yml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/.github/workflows/test-testworkflows.yml b/.github/workflows/test-testworkflows.yml index 713737c..8db1a7a 100644 --- a/.github/workflows/test-testworkflows.yml +++ b/.github/workflows/test-testworkflows.yml @@ -44,7 +44,7 @@ jobs: - name: Start Tiltfile services run: tilt ci - working-directory: .. + working-directory: . - name: Wait for services to be ready run: | From e56357195c545fd772e098a90dbea2018e01756f Mon Sep 17 00:00:00 2001 From: MiaAppel Date: Thu, 6 Nov 2025 15:51:01 +0100 Subject: [PATCH 28/61] FIX: Add GOOGLE_API_KEY Github Secret --- .github/workflows/test-testworkflows.yml | 4 ++++ 1 file changed, 4 insertions(+) diff --git a/.github/workflows/test-testworkflows.yml b/.github/workflows/test-testworkflows.yml index 8db1a7a..358e14a 100644 --- a/.github/workflows/test-testworkflows.yml +++ b/.github/workflows/test-testworkflows.yml @@ -6,6 +6,10 @@ on: pull_request: branches: [ main ] +env: + # Required environment variables for the test + GOOGLE_API_KEY: ${{ secrets.GOOGLE_API_KEY }} + jobs: test-testworkflows: runs-on: ubuntu-latest From 8ad3ea1f15801457fd0481a2cbed2038abf65cf3 Mon Sep 17 00:00:00 2001 From: MiaAppel Date: Thu, 6 Nov 2025 16:00:09 +0100 Subject: [PATCH 29/61] FIX: wait for Test-Data-Server to start up before running Pytests --- .github/workflows/test-testworkflows.yml | 3 +++ 1 file changed, 3 insertions(+) diff --git a/.github/workflows/test-testworkflows.yml b/.github/workflows/test-testworkflows.yml index 358e14a..c0d7d3c 100644 --- a/.github/workflows/test-testworkflows.yml +++ b/.github/workflows/test-testworkflows.yml @@ -60,5 +60,8 @@ jobs: echo "Checking service status..." kubectl get pods -A + echo "Waiting for test-data-server (HTTP server on port 8000)..." + curl --retry 30 --retry-delay 2 --retry-connrefused -f http://localhost:8000/dataset.json > /dev/null + - name: Run pytest run: uv run pytest tests/ -v From 73c1f7a007ce3364fa5ec6fc13c7b58c1fd535ed Mon Sep 17 00:00:00 2001 From: MiaAppel Date: Thu, 6 Nov 2025 16:17:00 +0100 Subject: [PATCH 30/61] FEAT: Implement Test-Data-Server in Github Action (Tilt CI shuts it down) --- .github/workflows/test-testworkflows.yml | 3 +++ 1 file changed, 3 insertions(+) diff --git a/.github/workflows/test-testworkflows.yml b/.github/workflows/test-testworkflows.yml index c0d7d3c..9ae2555 100644 --- a/.github/workflows/test-testworkflows.yml +++ b/.github/workflows/test-testworkflows.yml @@ -46,6 +46,9 @@ jobs: curl -fsSL https://raw.githubusercontent.com/tilt-dev/tilt/master/scripts/install.sh | bash tilt version + - name: Start test data server + run: uv run python -m http.server 8000 --directory tests/test_data & + - name: Start Tiltfile services run: tilt ci working-directory: . From 932009a3087f526d0a787e708b75e6788450f5ee Mon Sep 17 00:00:00 2001 From: MiaAppel Date: Thu, 6 Nov 2025 16:26:02 +0100 Subject: [PATCH 31/61] FIX: no more double Test-Data-Server in CI --- Tiltfile | 15 ++++++++------- 1 file changed, 8 insertions(+), 7 deletions(-) diff --git a/Tiltfile b/Tiltfile index c6cb7ea..e32f833 100644 --- a/Tiltfile +++ b/Tiltfile @@ -21,13 +21,14 @@ v1alpha1.extension(name='ai-gateway-litellm', repo_name='agentic-layer', repo_pa load('ext://ai-gateway-litellm', 'ai_gateway_litellm_install') ai_gateway_litellm_install(version='0.2.0') -# Webserver to serve test data -local_resource( - 'test-data-server', - serve_cmd='python3 -m http.server 8000 --directory testworkflows/tests/test_data', - labels=['test-data'], - links=['http://localhost:8000/dataset.json'] -) +# Webserver to serve test data (disabled in CI - manually started instead) +if not os.getenv('CI'): + local_resource( + 'test-data-server', + serve_cmd='python3 -m http.server 8000 --directory testworkflows/tests/test_data', + labels=['test-data'], + links=['http://localhost:8000/dataset.json'] + ) # Apply Kubernetes manifests k8s_yaml(kustomize('deploy/local')) From ef13ef66ae6f6104ff5034ac60dab4f94b3eacf0 Mon Sep 17 00:00:00 2001 From: MiaAppel Date: Thu, 6 Nov 2025 16:35:58 +0100 Subject: [PATCH 32/61] FIX: add OPENAI_API_KEY Placeholder so test_e2e.py can run --- .github/workflows/test-testworkflows.yml | 1 + 1 file changed, 1 insertion(+) diff --git a/.github/workflows/test-testworkflows.yml b/.github/workflows/test-testworkflows.yml index 9ae2555..8aadcba 100644 --- a/.github/workflows/test-testworkflows.yml +++ b/.github/workflows/test-testworkflows.yml @@ -9,6 +9,7 @@ on: env: # Required environment variables for the test GOOGLE_API_KEY: ${{ secrets.GOOGLE_API_KEY }} + OPENAI_API_KEY: PLACEHOLDER jobs: test-testworkflows: From 0525e6e34bfcab39d2e55887926dc1e16b99ef49 Mon Sep 17 00:00:00 2001 From: MiaAppel Date: Thu, 6 Nov 2025 16:42:36 +0100 Subject: [PATCH 33/61] FIX: add Timeout to Request --- testworkflows/scripts/setup.py | 2 +- testworkflows/tests/test_setup.py | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/testworkflows/scripts/setup.py b/testworkflows/scripts/setup.py index ead6016..0a6c512 100644 --- a/testworkflows/scripts/setup.py +++ b/testworkflows/scripts/setup.py @@ -86,7 +86,7 @@ def main(url: str) -> None: converter = get_converter(url) # Download file from URL and raise HTTP error if it occurs - file: Response = requests.get(url) + file: Response = requests.get(url, timeout=20) file.raise_for_status() # Load into DataFrame by using the correct converter diff --git a/testworkflows/tests/test_setup.py b/testworkflows/tests/test_setup.py index fa701ab..988bfec 100644 --- a/testworkflows/tests/test_setup.py +++ b/testworkflows/tests/test_setup.py @@ -149,7 +149,7 @@ def test_main_with_csv(self, mock_get): self.assertTrue(dataset_file.exists(), f"Dataset file not found at {dataset_file}") # Verify requests.get was called - mock_get.assert_called_once_with("https://example.com/data.csv") + mock_get.assert_called_once_with("https://example.com/data.csv", timeout=20) finally: os.chdir(self.original_cwd) From 2bb11ace02ae3b4f154d39f21365b6275d2f821f Mon Sep 17 00:00:00 2001 From: MiaAppel Date: Thu, 6 Nov 2025 16:49:12 +0100 Subject: [PATCH 34/61] FIX: up2date uv.lock --- testworkflows/uv.lock | 909 +++++++++++++----------------------------- 1 file changed, 271 insertions(+), 638 deletions(-) diff --git a/testworkflows/uv.lock b/testworkflows/uv.lock index e6972d6..cf5737a 100644 --- a/testworkflows/uv.lock +++ b/testworkflows/uv.lock @@ -18,7 +18,7 @@ sdist = { url = "https://files.pythonhosted.org/packages/fa/4c/502dc34d0ee1f4b5f [[package]] name = "a2a-sdk" -version = "0.3.7" +version = "0.3.10" source = { registry = "https://pypi.org/simple" } dependencies = [ { name = "google-api-core" }, @@ -27,9 +27,9 @@ dependencies = [ { name = "protobuf" }, { name = "pydantic" }, ] -sdist = { url = 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"bandit", "ruff", "lint-imports"] - -[tool.importlinter] -root_package = "scripts" +check = ["test", "mypy", "bandit", "ruff"] [tool.ruff] # Allow lines to be as long as 120. @@ -54,11 +50,20 @@ line-length = 120 # DTZ --> datetime timezone awareness extend-select = ["Q", "N", "I001", "PT", "TID251", "DTZ"] +ignore = [ + "PT009", # allow unittest-style assertions (assertEqual, assertAlmostEqual, etc.) + "PT027" # allow unittest.TestCase without using pytest fixtures +] + [tool.mypy] mypy_path = "scripts" [tool.bandit] exclude_dirs = [".cache", ".venv"] +skips = [ + "B404", # Usage of 'subprocess' module + "B603", # 'Subprocess' call without check for execution of untrusted input +] [tool.bandit.assert_used] skips = ["*_test.py", "*test_*.py"] \ No newline at end of file diff --git a/testworkflows/scripts/evaluate.py b/testworkflows/scripts/evaluate.py index 62af603..f93a60e 100644 --- a/testworkflows/scripts/evaluate.py +++ b/testworkflows/scripts/evaluate.py @@ -40,6 +40,7 @@ def get_available_metrics() -> dict[str, Metric]: available_metrics[metric_name] = metric_instance except Exception: # Skip metrics that can't be instantiated without parameters + logger.info(f"Exception encountered: {Exception}") pass return available_metrics @@ -163,7 +164,7 @@ def main( # Create LLM client using the AI-Gateway ragas_llm: ChatOpenAI = ChatOpenAI(model=model) - llm = LangchainLLMWrapper(ragas_llm) # type: ignore[arg-type] + llm = LangchainLLMWrapper(ragas_llm) # type: ignore[arg-type] dataset = EvaluationDataset.from_jsonl("data/experiments/ragas_experiment.jsonl") From de336adc541c4086675782f263758487f1899fc6 Mon Sep 17 00:00:00 2001 From: MiaAppel Date: Thu, 6 Nov 2025 17:11:04 +0100 Subject: [PATCH 36/61] FEAT: Add Check Workflow that runs 'uv poe check' --- .github/workflows/check-testworkflows.yml | 38 +++++++++++++++++++++++ 1 file changed, 38 insertions(+) create mode 100644 .github/workflows/check-testworkflows.yml diff --git a/.github/workflows/check-testworkflows.yml b/.github/workflows/check-testworkflows.yml new file mode 100644 index 0000000..ffb2b00 --- /dev/null +++ b/.github/workflows/check-testworkflows.yml @@ -0,0 +1,38 @@ +# +# GitHub Action: Check-Testworkflows +# +# This workflow is triggered on pushes to main and renovate branches, as well as +# pull requests. It runs backend checks to ensure code quality. +# +name: Check-Testworkflows + +on: + push: + branches: + - main + - 'renovate/**' + pull_request: + +jobs: + check-backend: + runs-on: ubuntu-latest + steps: + - name: Checkout + uses: 'actions/checkout@v5' + + - name: Install uv + uses: 'astral-sh/setup-uv@v6' + with: + version: "0.8.17" + enable-cache: true + + - name: Setup Python + uses: 'actions/setup-python@v6' + with: + python-version-file: ".python-version" + + - name: Install Dependencies + run: uv sync --all-packages + + - name: Run checks + run: uv run poe check \ No newline at end of file From 701f8fa8ef476a1feaac15d505f43f099f972747 Mon Sep 17 00:00:00 2001 From: MiaAppel Date: Thu, 6 Nov 2025 17:12:09 +0100 Subject: [PATCH 37/61] FIX: incorrect path to python-version-file --- .github/workflows/check-testworkflows.yml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/.github/workflows/check-testworkflows.yml b/.github/workflows/check-testworkflows.yml index ffb2b00..f387e41 100644 --- a/.github/workflows/check-testworkflows.yml +++ b/.github/workflows/check-testworkflows.yml @@ -29,7 +29,7 @@ jobs: - name: Setup Python uses: 'actions/setup-python@v6' with: - python-version-file: ".python-version" + python-version-file: "testworkflows/.python-version" - name: Install Dependencies run: uv sync --all-packages From b36a5fc4d77f4d4a170d3cfc432157a904c2d8f8 Mon Sep 17 00:00:00 2001 From: MiaAppel Date: Thu, 6 Nov 2025 17:13:59 +0100 Subject: [PATCH 38/61] FIX: incorrect working-directory in check-testworkflows.yml --- .github/workflows/check-testworkflows.yml | 5 +++++ 1 file changed, 5 insertions(+) diff --git a/.github/workflows/check-testworkflows.yml b/.github/workflows/check-testworkflows.yml index f387e41..ab84168 100644 --- a/.github/workflows/check-testworkflows.yml +++ b/.github/workflows/check-testworkflows.yml @@ -16,6 +16,11 @@ on: jobs: check-backend: runs-on: ubuntu-latest + + defaults: + run: + working-directory: testworkflows + steps: - name: Checkout uses: 'actions/checkout@v5' From e36d99fc794a13686d01436b4926375830622227 Mon Sep 17 00:00:00 2001 From: MiaAppel Date: Thu, 6 Nov 2025 17:15:25 +0100 Subject: [PATCH 39/61] Revert "FIX: incorrect working-directory in check-testworkflows.yml" This reverts commit b36a5fc4d77f4d4a170d3cfc432157a904c2d8f8. --- .github/workflows/check-testworkflows.yml | 5 ----- 1 file changed, 5 deletions(-) diff --git a/.github/workflows/check-testworkflows.yml b/.github/workflows/check-testworkflows.yml index ab84168..f387e41 100644 --- a/.github/workflows/check-testworkflows.yml +++ b/.github/workflows/check-testworkflows.yml @@ -16,11 +16,6 @@ on: jobs: check-backend: runs-on: ubuntu-latest - - defaults: - run: - working-directory: testworkflows - steps: - name: Checkout uses: 'actions/checkout@v5' From 333e5b0bfb9dd94d977e34f0fbe3a7794460da05 Mon Sep 17 00:00:00 2001 From: MiaAppel Date: Thu, 6 Nov 2025 17:15:25 +0100 Subject: [PATCH 40/61] Revert "FIX: incorrect path to python-version-file" This reverts commit 701f8fa8ef476a1feaac15d505f43f099f972747. --- .github/workflows/check-testworkflows.yml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/.github/workflows/check-testworkflows.yml b/.github/workflows/check-testworkflows.yml index f387e41..ffb2b00 100644 --- a/.github/workflows/check-testworkflows.yml +++ b/.github/workflows/check-testworkflows.yml @@ -29,7 +29,7 @@ jobs: - name: Setup Python uses: 'actions/setup-python@v6' with: - python-version-file: "testworkflows/.python-version" + python-version-file: ".python-version" - name: Install Dependencies run: uv sync --all-packages From 95c7231fe124698d05ae76955e3616bf1e077faa Mon Sep 17 00:00:00 2001 From: MiaAppel Date: Thu, 6 Nov 2025 17:15:26 +0100 Subject: [PATCH 41/61] Revert "FEAT: Add Check Workflow that runs 'uv poe check'" This reverts commit de336adc541c4086675782f263758487f1899fc6. --- .github/workflows/check-testworkflows.yml | 38 ----------------------- 1 file changed, 38 deletions(-) delete mode 100644 .github/workflows/check-testworkflows.yml diff --git a/.github/workflows/check-testworkflows.yml b/.github/workflows/check-testworkflows.yml deleted file mode 100644 index ffb2b00..0000000 --- a/.github/workflows/check-testworkflows.yml +++ /dev/null @@ -1,38 +0,0 @@ -# -# GitHub Action: Check-Testworkflows -# -# This workflow is triggered on pushes to main and renovate branches, as well as -# pull requests. It runs backend checks to ensure code quality. -# -name: Check-Testworkflows - -on: - push: - branches: - - main - - 'renovate/**' - pull_request: - -jobs: - check-backend: - runs-on: ubuntu-latest - steps: - - name: Checkout - uses: 'actions/checkout@v5' - - - name: Install uv - uses: 'astral-sh/setup-uv@v6' - with: - version: "0.8.17" - enable-cache: true - - - name: Setup Python - uses: 'actions/setup-python@v6' - with: - python-version-file: ".python-version" - - - name: Install Dependencies - run: uv sync --all-packages - - - name: Run checks - run: uv run poe check \ No newline at end of file From ff6c5ae0a7f2f23d9cceda8ce8a83c38986b976e Mon Sep 17 00:00:00 2001 From: MiaAppel Date: Thu, 6 Nov 2025 17:18:07 +0100 Subject: [PATCH 42/61] REFACTOR: Adapt check-testworkflows.yml to run all checks instead of only Pytest --- .../{test-testworkflows.yml => check-testworkflows.yml} | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) rename .github/workflows/{test-testworkflows.yml 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11:26:29 +0100 Subject: [PATCH 44/61] REFACTOR: create e2e_tests/ directory --- testworkflows/{tests => e2e_tests}/test_e2e.py | 0 1 file changed, 0 insertions(+), 0 deletions(-) rename testworkflows/{tests => e2e_tests}/test_e2e.py (100%) diff --git a/testworkflows/tests/test_e2e.py b/testworkflows/e2e_tests/test_e2e.py similarity index 100% rename from testworkflows/tests/test_e2e.py rename to testworkflows/e2e_tests/test_e2e.py From 08bc1ee91653931d89c1213ee5571404fda576a7 Mon Sep 17 00:00:00 2001 From: MiaAppel Date: Tue, 11 Nov 2025 11:27:35 +0100 Subject: [PATCH 45/61] REFACTOR: add test_e2e to POE tasks --- testworkflows/pyproject.toml | 1 + 1 file changed, 1 insertion(+) diff --git a/testworkflows/pyproject.toml b/testworkflows/pyproject.toml index 2751fc2..b27d7e3 100644 --- a/testworkflows/pyproject.toml +++ b/testworkflows/pyproject.toml @@ -27,6 +27,7 @@ dependencies = [ [tool.poe.tasks] test = "pytest tests/ -v" +test_e2e = "pytest e2e_tests/ -v" format = "ruff format" lint = "ruff check --fix" From 2b71106d1a6c1c7dd1a04ec196489fa049721986 Mon Sep 17 00:00:00 2001 From: MiaAppel Date: Tue, 11 Nov 2025 11:35:30 +0100 Subject: [PATCH 46/61] REFACTOR: adapt test-e2e.yml to run the testworkflow e2e test --- .github/workflows/test-e2e.yml | 67 ++++++++++++++++++++++++++-------- 1 file changed, 51 insertions(+), 16 deletions(-) diff --git a/.github/workflows/test-e2e.yml b/.github/workflows/test-e2e.yml index 277e227..fcb7941 100644 --- a/.github/workflows/test-e2e.yml +++ b/.github/workflows/test-e2e.yml @@ -7,32 +7,67 @@ on: - 'renovate/**' pull_request: +env: + # Required environment variables for the E2E test + GOOGLE_API_KEY: ${{ secrets.GOOGLE_API_KEY }} + OPENAI_API_KEY: PLACEHOLDER + jobs: - test-e2e: + test: name: Run on Ubuntu runs-on: ubuntu-latest - permissions: - contents: 'read' + + defaults: + run: + working-directory: testworkflows steps: - name: Clone the code - uses: actions/checkout@v5 + uses: 'actions/checkout@v5' - - name: Setup Go - uses: actions/setup-go@v6 + - name: Install uv + uses: 'astral-sh/setup-uv@v6' with: - go-version-file: go.mod + version: "0.8.17" + enable-cache: true + + - name: Setup Python + uses: 'actions/setup-python@v6' + with: + python-version-file: "testworkflows/.python-version" + + - name: Install Dependencies + run: uv sync --all-packages - - name: Install the latest version of kind + - name: Set up Kubernetes (kind) + uses: 'helm/kind-action@v1' + with: + cluster_name: testbench-cluster + + - name: Install Tilt run: | - curl -Lo ./kind https://kind.sigs.k8s.io/dl/latest/kind-linux-amd64 - chmod +x ./kind - sudo mv ./kind /usr/local/bin/kind + curl -fsSL https://raw.githubusercontent.com/tilt-dev/tilt/master/scripts/install.sh | bash + tilt version - - name: Verify kind installation - run: kind version + - name: Start test data server + run: uv run python -m http.server 8000 --directory tests/test_data & - - name: Running Test e2e + - name: Start Tiltfile services + run: tilt ci + working-directory: . + + - name: Wait for services to be ready run: | - go mod tidy - make test-e2e + echo "Waiting for services to be ready..." + kubectl wait --for=condition=ready pod -l app=weather-agent --timeout=300s || true + kubectl wait --for=condition=ready pod -l app=ai-gateway-litellm --timeout=300s || true + kubectl wait --for=condition=ready pod -l app.kubernetes.io/name=lgtm --timeout=300s || true + + echo "Checking service status..." + kubectl get pods -A + + echo "Waiting for test-data-server (HTTP server on port 8000)..." + curl --retry 30 --retry-delay 2 --retry-connrefused -f http://localhost:8000/dataset.json > /dev/null + + - name: Run E2E Test + run: uv run poe test_e2e From f905d5dad282628e545db8765b913a118c43d2d2 Mon Sep 17 00:00:00 2001 From: MiaAppel Date: Tue, 11 Nov 2025 11:36:26 +0100 Subject: [PATCH 47/61] REFACTOR: rename to check.yml and remove E2E-Test scaffolding --- .github/workflows/check-testworkflows.yml | 71 ----------------------- .github/workflows/check.yml | 44 ++++++++++++++ 2 files changed, 44 insertions(+), 71 deletions(-) delete mode 100644 .github/workflows/check-testworkflows.yml create mode 100644 .github/workflows/check.yml diff --git a/.github/workflows/check-testworkflows.yml b/.github/workflows/check-testworkflows.yml deleted file mode 100644 index d5ba534..0000000 --- a/.github/workflows/check-testworkflows.yml +++ /dev/null @@ -1,71 +0,0 @@ -name: Check Testworkflows - -on: - push: - branches: [ main ] - pull_request: - branches: [ main ] - -env: - # Required environment variables for the test - GOOGLE_API_KEY: ${{ secrets.GOOGLE_API_KEY }} - OPENAI_API_KEY: PLACEHOLDER - -jobs: - test-testworkflows: - runs-on: ubuntu-latest - - defaults: - run: - working-directory: testworkflows - - steps: - - name: Checkout - uses: 'actions/checkout@v5' - - - name: Install uv - uses: 'astral-sh/setup-uv@v6' - with: - version: "0.8.17" - enable-cache: true - - - name: Set up Python - uses: 'actions/setup-python@v6' - with: - python-version-file: "testworkflows/.python-version" - - - name: Install Dependencies - run: uv sync --all-packages - - - name: Set up Kubernetes (kind) - uses: 'helm/kind-action@v1' - with: - cluster_name: testbench-cluster - - - name: Install Tilt - run: | - curl -fsSL https://raw.githubusercontent.com/tilt-dev/tilt/master/scripts/install.sh | bash - tilt version - - - name: Start test data server - run: uv run python -m http.server 8000 --directory tests/test_data & - - - name: Start Tiltfile services - run: tilt ci - working-directory: . - - - name: Wait for services to be ready - run: | - echo "Waiting for services to be ready..." - kubectl wait --for=condition=ready pod -l app=weather-agent --timeout=300s || true - kubectl wait --for=condition=ready pod -l app=ai-gateway-litellm --timeout=300s || true - kubectl wait --for=condition=ready pod -l app.kubernetes.io/name=lgtm --timeout=300s || true - - echo "Checking service status..." - kubectl get pods -A - - echo "Waiting for test-data-server (HTTP server on port 8000)..." - curl --retry 30 --retry-delay 2 --retry-connrefused -f http://localhost:8000/dataset.json > /dev/null - - - name: Run Checks (Pytest, MyPy, Bandit, Ruff) - run: uv run poe check diff --git a/.github/workflows/check.yml b/.github/workflows/check.yml new file mode 100644 index 0000000..0d3a87a --- /dev/null +++ b/.github/workflows/check.yml @@ -0,0 +1,44 @@ +# +# GitHub Action: Check +# +# This workflow is triggered on pushes to main and renovate branches, as well as +# pull requests. It runs backend checks to ensure code quality. +# +name: Check + +on: + push: + branches: + - main + - 'renovate/**' + pull_request: + +jobs: + test-testworkflows: + name: Runs on Ubuntu + runs-on: ubuntu-latest + + defaults: + run: + working-directory: testworkflows + + steps: + - name: Clone the code + uses: 'actions/checkout@v5' + + - name: Install uv + uses: 'astral-sh/setup-uv@v6' + with: + version: "0.8.17" + enable-cache: true + + - name: Setup Python + uses: 'actions/setup-python@v6' + with: + python-version-file: "testworkflows/.python-version" + + - name: Install Dependencies + run: uv sync --all-packages + + - name: Run Checks + run: uv run poe check From 63304eda205e8d9e00344ca825550a9b9f2532cc Mon Sep 17 00:00:00 2001 From: MiaAppel Date: Tue, 11 Nov 2025 11:37:02 +0100 Subject: [PATCH 48/61] REFACTOR: replace Go Tests with Testworkflow Tests --- .github/workflows/test.yml | 27 +++++++++++++++++++-------- 1 file changed, 19 insertions(+), 8 deletions(-) diff --git a/.github/workflows/test.yml b/.github/workflows/test.yml index b78b1de..cfbdb18 100644 --- a/.github/workflows/test.yml +++ b/.github/workflows/test.yml @@ -14,16 +14,27 @@ jobs: permissions: contents: 'read' + defaults: + run: + working-directory: testworkflows + steps: - name: Clone the code - uses: actions/checkout@v5 + uses: 'actions/checkout@v5' + + - name: Install uv + uses: 'astral-sh/setup-uv@v6' + with: + version: "0.8.17" + enable-cache: true - - name: Setup Go - uses: actions/setup-go@v6 + - name: Setup Python + uses: 'actions/setup-python@v6' with: - go-version-file: go.mod + python-version-file: "testworkflows/.python-version" + + - name: Install Dependencies + run: uv sync --all-packages - - name: Running Tests - run: | - go mod tidy - make test + - name: Run Tests + run: uv run poe test From 90f23d328d69e7bd4ff268109a27474523b2e749 Mon Sep 17 00:00:00 2001 From: MiaAppel Date: Tue, 11 Nov 2025 11:40:56 +0100 Subject: [PATCH 49/61] FIX: Formatting --- .github/workflows/test-e2e.yml | 8 +++++++- .github/workflows/test.yml | 6 ++++++ 2 files changed, 13 insertions(+), 1 deletion(-) diff --git a/.github/workflows/test-e2e.yml b/.github/workflows/test-e2e.yml index fcb7941..996d5a7 100644 --- a/.github/workflows/test-e2e.yml +++ b/.github/workflows/test-e2e.yml @@ -1,3 +1,9 @@ +# +# GitHub Action: E2E Tests +# +# This workflow is triggered on pushes to main and renovate branches, as well as +# pull requests. It runs E2E Tests to ensure the code is working. +# name: E2E Tests on: @@ -69,5 +75,5 @@ jobs: echo "Waiting for test-data-server (HTTP server on port 8000)..." curl --retry 30 --retry-delay 2 --retry-connrefused -f http://localhost:8000/dataset.json > /dev/null - - name: Run E2E Test + - name: Running Test e2e run: uv run poe test_e2e diff --git a/.github/workflows/test.yml b/.github/workflows/test.yml index cfbdb18..1ac4fd5 100644 --- a/.github/workflows/test.yml +++ b/.github/workflows/test.yml @@ -1,3 +1,9 @@ +# +# GitHub Action: Test E2E +# +# This workflow is triggered on pushes to main and renovate branches, as well as +# pull requests. It runs Unit Tests to ensure the code is working. +# name: Tests on: From 10d200fcdf7e0dd84279ef701c59b47b4ffa9cce Mon Sep 17 00:00:00 2001 From: MiaAppel Date: Tue, 11 Nov 2025 11:42:09 +0100 Subject: [PATCH 50/61] FIX: Rename E2E Test folder --- testworkflows/{e2e_tests => tests_e2e}/test_e2e.py | 0 1 file changed, 0 insertions(+), 0 deletions(-) rename testworkflows/{e2e_tests => tests_e2e}/test_e2e.py (100%) diff --git a/testworkflows/e2e_tests/test_e2e.py b/testworkflows/tests_e2e/test_e2e.py similarity index 100% rename from testworkflows/e2e_tests/test_e2e.py rename to testworkflows/tests_e2e/test_e2e.py From 790128b5e83f72633b64d2ee09bb7a8e88398467 Mon Sep 17 00:00:00 2001 From: MiaAppel Date: Tue, 11 Nov 2025 11:50:20 +0100 Subject: [PATCH 51/61] REFACTOR: divide dependencies into dev and prod --- testworkflows/pyproject.toml | 19 ++++++++++++------- 1 file changed, 12 insertions(+), 7 deletions(-) diff --git a/testworkflows/pyproject.toml b/testworkflows/pyproject.toml index b27d7e3..95e7e7e 100644 --- a/testworkflows/pyproject.toml +++ b/testworkflows/pyproject.toml @@ -3,26 +3,31 @@ name = "test-bench" version = "0.1.0" description = "Testbench to evaluate agents using Ragas" requires-python = ">=3.12" -dependencies = [ - "a2a>=0.44", - "a2a-sdk>=0.3.10", + +[dependency-groups] +dev = [ "bandit[toml]>=1.7.8", - "httpx>=0.28.1", "mypy>=1.17.0", "import-linter>=2.0", + "poethepoet>=0.31.1", + "ruff>=0.12.7", + "pytest>=7.4.0", +] + +prod = [ + "a2a>=0.44", + "a2a-sdk>=0.3.10", + "httpx>=0.28.1", "langchain-openai>=1.0.2", "pandas>=2.3.3", "pandas-stubs>=2.3.0", - "poethepoet>=0.31.1", "pyarrow>=21.0.0", "ragas>=0.3.5", "requests>=2.32.5", "types-requests>=2.32.0", - "ruff>=0.12.7", "opentelemetry-api>=1.20.0", "opentelemetry-sdk>=1.20.0", "opentelemetry-exporter-otlp-proto-http>=1.20.0", - "pytest>=7.4.0", ] [tool.poe.tasks] From 254bd7bda4854446ad6fd68e4bf4f1c287f22446 Mon Sep 17 00:00:00 2001 From: MiaAppel Date: Tue, 11 Nov 2025 11:51:22 +0100 Subject: [PATCH 52/61] FIX: wrong directory for test_e2e --- testworkflows/pyproject.toml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/testworkflows/pyproject.toml b/testworkflows/pyproject.toml index 95e7e7e..4e07aa6 100644 --- a/testworkflows/pyproject.toml +++ b/testworkflows/pyproject.toml @@ -32,7 +32,7 @@ prod = [ [tool.poe.tasks] test = "pytest tests/ -v" -test_e2e = "pytest e2e_tests/ -v" +test_e2e = "pytest tests_e2e/ -v" format = "ruff format" lint = "ruff check --fix" From 76d406514b6d741c3b8e0d6abc60d9553d6701b3 Mon Sep 17 00:00:00 2001 From: MiaAppel Date: Tue, 11 Nov 2025 11:56:27 +0100 Subject: [PATCH 53/61] FIX: adapt uv commands to dev & prod dependencies --- .github/workflows/check.yml | 2 +- .github/workflows/test-e2e.yml | 2 +- .github/workflows/test.yml | 2 +- 3 files changed, 3 insertions(+), 3 deletions(-) diff --git a/.github/workflows/check.yml b/.github/workflows/check.yml index 0d3a87a..a33cc15 100644 --- a/.github/workflows/check.yml +++ b/.github/workflows/check.yml @@ -38,7 +38,7 @@ jobs: python-version-file: "testworkflows/.python-version" - name: Install Dependencies - run: uv sync --all-packages + run: uv sync --group dev --group prod - name: Run Checks run: uv run poe check diff --git a/.github/workflows/test-e2e.yml b/.github/workflows/test-e2e.yml index 996d5a7..d6f50ea 100644 --- a/.github/workflows/test-e2e.yml +++ b/.github/workflows/test-e2e.yml @@ -43,7 +43,7 @@ jobs: python-version-file: "testworkflows/.python-version" - name: Install Dependencies - run: uv sync --all-packages + run: uv sync --group dev --group prod - name: Set up Kubernetes (kind) uses: 'helm/kind-action@v1' diff --git a/.github/workflows/test.yml b/.github/workflows/test.yml index 1ac4fd5..bc535b0 100644 --- a/.github/workflows/test.yml +++ b/.github/workflows/test.yml @@ -40,7 +40,7 @@ jobs: python-version-file: "testworkflows/.python-version" - name: Install Dependencies - run: uv sync --all-packages + run: uv sync --group dev --group prod - name: Run Tests run: uv run poe test From 0bd2bb7ce0e7dc37a415a3c96c973f2dc5797ba6 Mon Sep 17 00:00:00 2001 From: MiaAppel Date: Tue, 11 Nov 2025 12:45:11 +0100 Subject: [PATCH 54/61] FIX: use native Pytest functionality instead of importing Unittest --- testworkflows/tests/test_evaluate.py | 383 ++++++++++++----- testworkflows/tests/test_publish.py | 622 ++++++++++++++++----------- testworkflows/tests/test_run.py | 369 ++++++++-------- testworkflows/tests/test_setup.py | 345 +++++++-------- testworkflows/tests_e2e/test_e2e.py | 6 +- 5 files changed, 1022 insertions(+), 703 deletions(-) diff --git a/testworkflows/tests/test_evaluate.py b/testworkflows/tests/test_evaluate.py index 490db36..199ea5e 100644 --- a/testworkflows/tests/test_evaluate.py +++ b/testworkflows/tests/test_evaluate.py @@ -4,164 +4,325 @@ Tests the RAGAS evaluation functionality. """ +import os import json import shutil import sys import tempfile -import unittest from argparse import ArgumentError from pathlib import Path -from unittest.mock import MagicMock +from ragas.metrics import Metric +from evaluate import convert_metrics import pandas as pd -from ragas.dataset_schema import EvaluationResult +import pytest sys.path.insert(0, str(Path(__file__).parent.parent / "scripts")) from evaluate import AVAILABLE_METRICS, format_evaluation_scores, main -class TestFormatEvaluationScores(unittest.TestCase): - """Test the format_evaluation_scores function""" +# Fixtures +@pytest.fixture +def temp_dir(): + """Create a temporary directory for tests""" + tmp = tempfile.mkdtemp() + original_cwd = Path.cwd() + yield tmp, original_cwd + shutil.rmtree(tmp, ignore_errors=True) - def test_overall_scores_calculation(self): - """Test that overall scores are calculated correctly""" - mock_result = MagicMock(spec=EvaluationResult) - df = pd.DataFrame({"faithfulness": [0.9, 0.8, 0.7], "answer_relevancy": [0.85, 0.75, 0.65]}) - mock_result.to_pandas.return_value = df +@pytest.fixture +def experiment_data(temp_dir): + """Create test experiment JSONL file""" + tmp, original_cwd = temp_dir - # Mock _repr_dict with calculated averages - mock_result._repr_dict = {"faithfulness": 0.8, "answer_relevancy": 0.75} + # Create test experiment JSONL + experiment_dir = Path(tmp) / "data" / "experiments" + experiment_dir.mkdir(parents=True, exist_ok=True) - # Mock token usage methods - mock_token_usage = MagicMock() - mock_token_usage.input_tokens = 100 - mock_token_usage.output_tokens = 50 - mock_result.total_tokens.return_value = mock_token_usage - mock_result.total_cost.return_value = 0.001 + experiment_file = experiment_dir / "ragas_experiment.jsonl" + test_data = [ + { + "user_input": "What is the weather?", + "retrieved_contexts": ["Context about weather"], + "reference": "Expected answer", + "response": "The weather is sunny.", + } + ] - formatted = format_evaluation_scores(mock_result, 5.0 / 1e6, 15.0 / 1e6) + with open(experiment_file, "w") as f: + for item in test_data: + f.write(json.dumps(item) + "\n") - # Verify overall scores are correct - self.assertAlmostEqual(formatted.overall_scores["faithfulness"], 0.8, places=2) - self.assertAlmostEqual(formatted.overall_scores["answer_relevancy"], 0.75, places=2) + return tmp, original_cwd, experiment_file - def test_individual_results_present(self): - """Test that individual results are included""" - mock_result = MagicMock(spec=EvaluationResult) - df = pd.DataFrame({"user_input": ["Q1", "Q2"], "faithfulness": [0.9, 0.8]}) - mock_result.to_pandas.return_value = df +# TestFormatEvaluationScores tests +def test_overall_scores_calculation(): + """Test that overall scores are calculated correctly""" - # Mock _repr_dict for overall scores - mock_result._repr_dict = {"faithfulness": 0.85} + # Create mock result + class MockTokenUsage: + input_tokens = 100 + output_tokens = 50 - # Mock token usage methods - mock_token_usage = MagicMock() - mock_token_usage.input_tokens = 100 - mock_token_usage.output_tokens = 50 - mock_result.total_tokens.return_value = mock_token_usage - mock_result.total_cost.return_value = 0.001 + class MockResult: + _repr_dict = {"faithfulness": 0.8, "answer_relevancy": 0.75} + cost_cb = None - formatted = format_evaluation_scores(mock_result, 5.0 / 1e6, 15.0 / 1e6) + def to_pandas(self): + return pd.DataFrame({"faithfulness": [0.9, 0.8, 0.7], "answer_relevancy": [0.85, 0.75, 0.65]}) - # Verify individual results - self.assertEqual(len(formatted.individual_results), 2) + def total_tokens(self): + return MockTokenUsage() - def test_token_usage_placeholders(self): - """Test that token usage is returned correctly""" - mock_result = MagicMock(spec=EvaluationResult) + def total_cost(self): + return 0.001 - df = pd.DataFrame({"faithfulness": [0.9]}) - mock_result.to_pandas.return_value = df + mock_result = MockResult() - # Mock _repr_dict for overall scores - mock_result._repr_dict = {"faithfulness": 0.9} + formatted = format_evaluation_scores(mock_result, 5.0 / 1e6, 15.0 / 1e6) - # Mock token usage methods with specific values - mock_token_usage = MagicMock() - mock_token_usage.input_tokens = 150 - mock_token_usage.output_tokens = 75 - mock_result.total_tokens.return_value = mock_token_usage - mock_result.total_cost.return_value = 0.002 + # Verify overall scores are correct + assert abs(formatted.overall_scores["faithfulness"] - 0.8) < 0.01 + assert abs(formatted.overall_scores["answer_relevancy"] - 0.75) < 0.01 - formatted = format_evaluation_scores(mock_result, 5.0 / 1e6, 15.0 / 1e6) - # Verify token usage is captured correctly - self.assertEqual(formatted.total_tokens["input_tokens"], 150) - self.assertEqual(formatted.total_tokens["output_tokens"], 75) - self.assertEqual(formatted.total_cost, 0.002) +def test_individual_results_present(): + """Test that individual results are included""" + # Create mock result + class MockTokenUsage: + input_tokens = 100 + output_tokens = 50 -class TestMain(unittest.TestCase): - """Test the main function""" + class MockResult: + _repr_dict = {"faithfulness": 0.85} + cost_cb = None - def setUp(self): - """Set up temporary directory and test data""" - self.temp_dir = tempfile.mkdtemp() - self.original_cwd = Path.cwd() + def to_pandas(self): + return pd.DataFrame({"user_input": ["Q1", "Q2"], "faithfulness": [0.9, 0.8]}) - # Create test experiment JSONL - self.experiment_dir = Path(self.temp_dir) / "data" / "experiments" - self.experiment_dir.mkdir(parents=True, exist_ok=True) + def total_tokens(self): + return MockTokenUsage() - self.experiment_file = self.experiment_dir / "ragas_experiment.jsonl" - test_data = [ - { - "user_input": "What is the weather?", - "retrieved_contexts": ["Context about weather"], - "reference": "Expected answer", - "response": "The weather is sunny.", - } - ] + def total_cost(self): + return 0.001 - with open(self.experiment_file, "w") as f: - for item in test_data: - f.write(json.dumps(item) + "\n") + mock_result = MockResult() - def tearDown(self): - """Clean up temporary directory""" - shutil.rmtree(self.temp_dir, ignore_errors=True) + formatted = format_evaluation_scores(mock_result, 5.0 / 1e6, 15.0 / 1e6) - def test_main_no_metrics(self): - """Test main function with no metrics provided""" - import os + # Verify individual results + assert len(formatted.individual_results) == 2 - os.chdir(self.temp_dir) - try: - # When metrics is None, the function should raise an error - # The actual error type depends on implementation - with self.assertRaises((ArgumentError)): - main( - output_file="results/evaluation_scores.json", - model="gemini-flash-latest", - metrics=None, - ) - finally: - os.chdir(self.original_cwd) +def test_token_usage_placeholders(): + """Test that token usage placeholders are returned when cost_cb is None""" + # Create mock result + class MockTokenUsage: + input_tokens = 150 + output_tokens = 75 -class TestAvailableMetrics(unittest.TestCase): - """Test the AVAILABLE_METRICS loading and validation""" + class MockResult: + _repr_dict = {"faithfulness": 0.9} + cost_cb = None # This causes placeholders to be used - def test_available_metrics_loaded(self): - """Test that AVAILABLE_METRICS is populated correctly""" - # Should be a non-empty dictionary - self.assertIsInstance(AVAILABLE_METRICS, dict) - self.assertGreater(len(AVAILABLE_METRICS), 0) + def to_pandas(self): + return pd.DataFrame({"faithfulness": [0.9]}) - # All keys should be strings - for key in AVAILABLE_METRICS.keys(): - self.assertIsInstance(key, str) + def total_tokens(self): + return MockTokenUsage() - # All values should be Metric instances - from ragas.metrics import Metric + def total_cost(self, **kwargs): + return 0.002 - for value in AVAILABLE_METRICS.values(): - self.assertIsInstance(value, Metric) + mock_result = MockResult() + formatted = format_evaluation_scores(mock_result, 5.0 / 1e6, 15.0 / 1e6) -if __name__ == "__main__": - unittest.main() + # Verify placeholder token usage is returned (0 when cost_cb is None) + assert formatted.total_tokens["input_tokens"] == 0 + assert formatted.total_tokens["output_tokens"] == 0 + assert formatted.total_cost == 0.0 + + +# TestMain tests +def test_main_no_metrics(experiment_data): + """Test main function with no metrics provided""" + + tmp, original_cwd, experiment_file = experiment_data + os.chdir(tmp) + + try: + # When metrics is None, the function should raise an error + # The actual error type depends on implementation + with pytest.raises(ArgumentError): + main( + output_file="results/evaluation_scores.json", + model="gemini-flash-latest", + metrics=None, + ) + finally: + os.chdir(original_cwd) + + +def test_main_successful_execution(experiment_data, monkeypatch): + """Test main function successful execution""" + from pathlib import Path + + from ragas.dataset_schema import EvaluationResult + + tmp, original_cwd, experiment_file = experiment_data + os.chdir(tmp) + + try: + # Mock EvaluationDataset.from_jsonl + class MockEvaluationDataset: + pass + + mock_dataset = MockEvaluationDataset() + + def mock_from_jsonl(path): + return mock_dataset + + # Mock the evaluate function + class MockTokenUsage: + input_tokens = 100 + output_tokens = 50 + + class MockEvaluationResult(EvaluationResult): + _repr_dict = {"faithfulness": 0.85} + cost_cb = None + + def __init__(self): + # Don't call super().__init__ to avoid initialization requirements + pass + + def to_pandas(self): + return pd.DataFrame({"user_input": ["Q1"], "faithfulness": [0.85]}) + + def total_tokens(self): + return MockTokenUsage() + + def total_cost(self, **kwargs): + return 0.001 + + mock_result = MockEvaluationResult() + + def mock_evaluate(dataset, metrics, llm, token_usage_parser): + return mock_result + + # Mock ChatOpenAI and LangchainLLMWrapper + class MockChatOpenAI: + pass + + def mock_chat_openai_init(model): + return MockChatOpenAI() + + class MockLLMWrapper: + def __init__(self, llm): + pass + + monkeypatch.setattr("evaluate.EvaluationDataset.from_jsonl", mock_from_jsonl) + monkeypatch.setattr("evaluate.evaluate", mock_evaluate) + monkeypatch.setattr("evaluate.ChatOpenAI", mock_chat_openai_init) + monkeypatch.setattr("evaluate.LangchainLLMWrapper", MockLLMWrapper) + + # Get a valid metric name + if not AVAILABLE_METRICS: + pytest.skip("No metrics available") + + valid_metric = list(AVAILABLE_METRICS.keys())[0] + + # Run main + output_file = "results/evaluation_scores.json" + main( + output_file=output_file, + model="gemini-flash-latest", + metrics=[valid_metric], + ) + + # Verify output file was created + output_path = Path(tmp) / output_file + assert output_path.exists(), f"Output file not found at {output_path}" + + # Verify output file has correct structure + with open(output_path, "r") as f: + data = json.load(f) + + assert "overall_scores" in data + assert "individual_results" in data + assert "total_tokens" in data + assert "total_cost" in data + finally: + os.chdir(original_cwd) + + +# TestAvailableMetrics tests +def test_available_metrics_loaded(): + """Test that AVAILABLE_METRICS is populated correctly""" + # Should be a non-empty dictionary + assert isinstance(AVAILABLE_METRICS, dict) + assert len(AVAILABLE_METRICS) > 0 + + # All keys should be strings + for key in AVAILABLE_METRICS.keys(): + assert isinstance(key, str) + + # All values should be Metric instances + for value in AVAILABLE_METRICS.values(): + assert isinstance(value, Metric) + + +# TestConvertMetrics tests +def test_convert_metrics_with_valid_metrics(): + """Test that convert_metrics correctly converts valid metric names to objects""" + + # Use metrics that are commonly available in RAGAS + metric_names = ["faithfulness", "answer_relevancy"] + + # Only test with metrics that actually exist in AVAILABLE_METRICS + available_names = [name for name in metric_names if name in AVAILABLE_METRICS] + + if not available_names: + pytest.skip("Required metrics not available in this RAGAS version") + + metric_objects = convert_metrics(available_names) + + # Verify we got the right number of metrics + assert len(metric_objects) == len(available_names) + + # Verify all returned objects are Metric instances + for obj in metric_objects: + assert isinstance(obj, Metric) + + +def test_convert_metrics_with_invalid_metrics(): + """Test that convert_metrics handles invalid metric names""" + + # Test with only invalid metrics - should raise ValueError + with pytest.raises(ValueError, match="No valid metrics provided"): + convert_metrics(["nonexistent_metric", "fake_metric"]) + + +def test_convert_metrics_mixed_valid_invalid(): + """Test convert_metrics with mixed valid and invalid metric names""" + + # Get one valid metric name from AVAILABLE_METRICS + if not AVAILABLE_METRICS: + pytest.skip("No metrics available") + + valid_metric = list(AVAILABLE_METRICS.keys())[0] + metric_names = [valid_metric, "nonexistent_metric", "fake_metric"] + + metric_objects = convert_metrics(metric_names) + + # Should only return the valid metric + assert len(metric_objects) == 1 + + + + assert isinstance(metric_objects[0], Metric) diff --git a/testworkflows/tests/test_publish.py b/testworkflows/tests/test_publish.py index 211fa11..bc215f6 100644 --- a/testworkflows/tests/test_publish.py +++ b/testworkflows/tests/test_publish.py @@ -8,296 +8,428 @@ import shutil import sys import tempfile -import unittest from pathlib import Path -from unittest.mock import MagicMock, patch + +import pytest sys.path.insert(0, str(Path(__file__).parent.parent / "scripts")) from publish import create_and_push_metrics, get_overall_scores, publish_metrics -class TestGetOverallScores(unittest.TestCase): - """Test the get_overall_scores function""" +# Fixtures +@pytest.fixture +def temp_dir(): + """Create a temporary directory for tests""" + tmp = tempfile.mkdtemp() + yield tmp + shutil.rmtree(tmp, ignore_errors=True) - def setUp(self): - """Set up temporary directory and test file""" - self.temp_dir = tempfile.mkdtemp() - self.test_file = Path(self.temp_dir) / "evaluation_scores.json" - def tearDown(self): - """Clean up temporary directory""" - shutil.rmtree(self.temp_dir, ignore_errors=True) +@pytest.fixture +def evaluation_scores_file(temp_dir): + """Create a test evaluation scores file""" + test_file = Path(temp_dir) / "evaluation_scores.json" + test_data = { + "overall_scores": {"faithfulness": 0.85, "answer_relevancy": 0.90}, + "individual_results": [], + "total_tokens": {"input_tokens": 0, "output_tokens": 0}, + "total_cost": 0.0, + } + + with open(test_file, "w") as f: + json.dump(test_data, f) + + return test_file - def test_loads_overall_scores(self): - """Test that get_overall_scores loads the overall_scores section""" - test_data = { - "overall_scores": {"faithfulness": 0.85, "answer_relevancy": 0.90}, - "individual_results": [], - "total_tokens": {"input_tokens": 0, "output_tokens": 0}, - "total_cost": 0.0, - } - with open(self.test_file, "w") as f: - json.dump(test_data, f) +@pytest.fixture +def realistic_scores_file(temp_dir): + """Create a realistic evaluation scores file""" + test_file = Path(temp_dir) / "evaluation_scores.json" + test_data = { + "overall_scores": { + "faithfulness": 0.8523, + "answer_relevancy": 0.9012, + "context_precision": 0.7845, + "context_recall": 0.8234, + }, + "individual_results": [ + { + "user_input": "What is the weather?", + "response": "It is sunny.", + "faithfulness": 0.85, + "answer_relevancy": 0.90, + } + ], + "total_tokens": {"input_tokens": 0, "output_tokens": 0}, + "total_cost": 0.0, + } + + with open(test_file, "w") as f: + json.dump(test_data, f, indent=2) - scores = get_overall_scores(str(self.test_file)) + return test_file - self.assertEqual(scores["faithfulness"], 0.85) - self.assertEqual(scores["answer_relevancy"], 0.90) - def test_file_not_found(self): - """Test behavior when file doesn't exist""" - with self.assertRaises(FileNotFoundError): - get_overall_scores(str(Path(self.temp_dir) / "nonexistent.json")) +# TestGetOverallScores tests +def test_loads_overall_scores(evaluation_scores_file): + """Test that get_overall_scores loads the overall_scores section""" + scores = get_overall_scores(str(evaluation_scores_file)) + assert scores["faithfulness"] == 0.85 + assert scores["answer_relevancy"] == 0.90 -class TestCreateAndPushMetrics(unittest.TestCase): - """Test the create_and_push_metrics function""" - @patch("publish.OTLPMetricExporter") - @patch("publish.MeterProvider") - @patch("publish.metrics.get_meter") - def test_creates_gauges_for_each_metric(self, mock_get_meter, mock_provider_class, mock_exporter_class): - """Test that a Gauge is created for each metric""" - overall_scores = {"faithfulness": 0.85, "answer_relevancy": 0.90} +def test_file_not_found(temp_dir): + """Test behavior when file doesn't exist""" + with pytest.raises(FileNotFoundError): + get_overall_scores(str(Path(temp_dir) / "nonexistent.json")) - # Mock the meter and gauge - mock_gauge = MagicMock() - mock_meter = MagicMock() - mock_meter.create_gauge.return_value = mock_gauge - mock_get_meter.return_value = mock_meter - # Mock the provider - mock_provider = MagicMock() - mock_provider_class.return_value = mock_provider +# TestCreateAndPushMetrics tests +def test_creates_gauges_for_each_metric(monkeypatch): + """Test that a Gauge is created for each metric""" + overall_scores = {"faithfulness": 0.85, "answer_relevancy": 0.90} - create_and_push_metrics( - overall_scores=overall_scores, - workflow_name="test-workflow", - otlp_endpoint="localhost:4318", - ) + # Mock the meter and gauge + create_gauge_calls = [] - # Verify create_gauge was called for each metric - self.assertEqual(mock_meter.create_gauge.call_count, 2) + class MockGauge: + def set(self, value, attributes): + pass - # Verify gauge names - gauge_calls = mock_meter.create_gauge.call_args_list - gauge_names = [call[1]["name"] for call in gauge_calls] - self.assertIn("ragas_evaluation_faithfulness", gauge_names) - self.assertIn("ragas_evaluation_answer_relevancy", gauge_names) + class MockMeter: + def create_gauge(self, name, unit=None, description=None): + create_gauge_calls.append({"name": name, "unit": unit, "description": description}) + return MockGauge() - @patch("publish.OTLPMetricExporter") - @patch("publish.MeterProvider") - @patch("publish.metrics.get_meter") - def test_sets_gauge_values(self, mock_get_meter, mock_provider_class, mock_exporter_class): - """Test that gauge values are set correctly""" - overall_scores = {"faithfulness": 0.85} + mock_meter = MockMeter() - # Mock the meter and gauge - mock_gauge = MagicMock() - mock_meter = MagicMock() - mock_meter.create_gauge.return_value = mock_gauge - mock_get_meter.return_value = mock_meter + def mock_get_meter(*args, **kwargs): + return mock_meter - # Mock the provider - mock_provider = MagicMock() - mock_provider_class.return_value = mock_provider + # Mock the provider + class MockProvider: + def force_flush(self): + pass - create_and_push_metrics( - overall_scores=overall_scores, - workflow_name="test-workflow", - otlp_endpoint="localhost:4318", - ) + def shutdown(self): + pass + + def mock_provider_init(**kwargs): + return MockProvider() + + # Mock the exporter + class MockExporter: + _preferred_temporality = {} + _preferred_aggregation = {} + + def mock_exporter_init(endpoint): + return MockExporter() + + monkeypatch.setattr("publish.metrics.get_meter", mock_get_meter) + monkeypatch.setattr("publish.MeterProvider", mock_provider_init) + monkeypatch.setattr("publish.OTLPMetricExporter", mock_exporter_init) + + create_and_push_metrics( + overall_scores=overall_scores, + workflow_name="test-workflow", + otlp_endpoint="localhost:4318", + ) + + # Verify create_gauge was called for each metric + assert len(create_gauge_calls) == 2 + + # Verify gauge names + gauge_names = [call["name"] for call in create_gauge_calls] + assert "ragas_evaluation_faithfulness" in gauge_names + assert "ragas_evaluation_answer_relevancy" in gauge_names + + +def test_sets_gauge_values(monkeypatch): + """Test that gauge values are set correctly""" + overall_scores = {"faithfulness": 0.85} + + # Mock the meter and gauge + set_calls = [] + + class MockGauge: + def set(self, value, attributes): + set_calls.append({"value": value, "attributes": attributes}) + + class MockMeter: + def create_gauge(self, name, unit=None, description=None): + return MockGauge() + + mock_meter = MockMeter() + + def mock_get_meter(*args, **kwargs): + return mock_meter + + # Mock the provider + class MockProvider: + def force_flush(self): + pass + + def shutdown(self): + pass + + def mock_provider_init(**kwargs): + return MockProvider() + + # Mock the exporter + class MockExporter: + _preferred_temporality = {} + _preferred_aggregation = {} + + def mock_exporter_init(endpoint): + return MockExporter() + + monkeypatch.setattr("publish.metrics.get_meter", mock_get_meter) + monkeypatch.setattr("publish.MeterProvider", mock_provider_init) + monkeypatch.setattr("publish.OTLPMetricExporter", mock_exporter_init) + + create_and_push_metrics( + overall_scores=overall_scores, + workflow_name="test-workflow", + otlp_endpoint="localhost:4318", + ) + + # Verify gauge.set was called with correct value and attributes + assert len(set_calls) == 1 + assert set_calls[0]["value"] == 0.85 + assert set_calls[0]["attributes"] == {"workflow_name": "test-workflow"} + + +def test_pushes_via_otlp(monkeypatch): + """Test that metrics are pushed via OTLP""" + overall_scores = {"faithfulness": 0.85} + + # Mock the meter and gauge + class MockGauge: + def set(self, value, attributes): + pass + + class MockMeter: + def create_gauge(self, name, unit=None, description=None): + return MockGauge() + + mock_meter = MockMeter() + + def mock_get_meter(*args, **kwargs): + return mock_meter + + # Mock the provider + force_flush_calls = [] + shutdown_calls = [] + + class MockProvider: + def force_flush(self): + force_flush_calls.append(True) + + def shutdown(self): + shutdown_calls.append(True) + + def mock_provider_init(**kwargs): + return MockProvider() + + # Mock the exporter + class MockExporter: + _preferred_temporality = {} + _preferred_aggregation = {} - # Verify gauge.set was called with correct value and attributes - mock_gauge.set.assert_called_once_with(0.85, {"workflow_name": "test-workflow"}) + exporter_calls = [] - @patch("publish.OTLPMetricExporter") - @patch("publish.MeterProvider") - @patch("publish.metrics.get_meter") - def test_pushes_via_otlp(self, mock_get_meter, mock_provider_class, mock_exporter_class): - """Test that metrics are pushed via OTLP""" - overall_scores = {"faithfulness": 0.85} + def mock_exporter_init(endpoint): + exporter_calls.append({"endpoint": endpoint}) + return MockExporter() - # Mock the meter and gauge - mock_gauge = MagicMock() - mock_meter = MagicMock() - mock_meter.create_gauge.return_value = mock_gauge - mock_get_meter.return_value = mock_meter + monkeypatch.setattr("publish.metrics.get_meter", mock_get_meter) + monkeypatch.setattr("publish.MeterProvider", mock_provider_init) + monkeypatch.setattr("publish.OTLPMetricExporter", mock_exporter_init) - # Mock the provider - mock_provider = MagicMock() - mock_provider_class.return_value = mock_provider + create_and_push_metrics( + overall_scores=overall_scores, + workflow_name="test-workflow", + otlp_endpoint="localhost:4318", + ) + # Verify OTLPMetricExporter was initialized with correct endpoint + assert len(exporter_calls) == 1 + assert exporter_calls[0]["endpoint"] == "http://localhost:4318/v1/metrics" + + # Verify force_flush and shutdown were called + assert len(force_flush_calls) == 1 + assert len(shutdown_calls) == 1 + + +def test_handles_push_error(monkeypatch): + """Test error handling when OTLP export fails""" + overall_scores = {"faithfulness": 0.85} + + # Mock the meter and gauge + class MockGauge: + def set(self, value, attributes): + pass + + class MockMeter: + def create_gauge(self, name, unit=None, description=None): + return MockGauge() + + mock_meter = MockMeter() + + def mock_get_meter(*args, **kwargs): + return mock_meter + + # Mock the provider to raise an exception on force_flush + shutdown_calls = [] + + class MockProvider: + def force_flush(self): + raise Exception("Connection refused") + + def shutdown(self): + shutdown_calls.append(True) + + def mock_provider_init(**kwargs): + return MockProvider() + + # Mock the exporter + class MockExporter: + _preferred_temporality = {} + _preferred_aggregation = {} + + def mock_exporter_init(endpoint): + return MockExporter() + + monkeypatch.setattr("publish.metrics.get_meter", mock_get_meter) + monkeypatch.setattr("publish.MeterProvider", mock_provider_init) + monkeypatch.setattr("publish.OTLPMetricExporter", mock_exporter_init) + + with pytest.raises(Exception, match="Connection refused"): create_and_push_metrics( overall_scores=overall_scores, workflow_name="test-workflow", otlp_endpoint="localhost:4318", ) - # Verify OTLPMetricExporter was initialized with correct endpoint - mock_exporter_class.assert_called_once_with(endpoint="http://localhost:4318/v1/metrics") - - # Verify force_flush and shutdown were called - mock_provider.force_flush.assert_called_once() - mock_provider.shutdown.assert_called_once() - - @patch("publish.OTLPMetricExporter") - @patch("publish.MeterProvider") - @patch("publish.metrics.get_meter") - def test_handles_push_error(self, mock_get_meter, mock_provider_class, mock_exporter_class): - """Test error handling when OTLP export fails""" - # Mock the provider to raise an exception on force_flush - mock_provider = MagicMock() - mock_provider.force_flush.side_effect = Exception("Connection refused") - mock_provider_class.return_value = mock_provider - - # Mock the meter - mock_gauge = MagicMock() - mock_meter = MagicMock() - mock_meter.create_gauge.return_value = mock_gauge - mock_get_meter.return_value = mock_meter - - overall_scores = {"faithfulness": 0.85} - - with self.assertRaises(Exception) as context: - create_and_push_metrics( - overall_scores=overall_scores, - workflow_name="test-workflow", - otlp_endpoint="localhost:4318", - ) - - self.assertIn("Connection refused", str(context.exception)) - - # Verify shutdown is still called in finally block - mock_provider.shutdown.assert_called_once() - - -class TestPublishMetrics(unittest.TestCase): - """Test the publish_metrics function""" - - def setUp(self): - """Set up temporary directory and test file""" - self.temp_dir = tempfile.mkdtemp() - self.test_file = Path(self.temp_dir) / "evaluation_scores.json" - - # Create test evaluation scores file - test_data = { - "overall_scores": {"faithfulness": 0.85, "answer_relevancy": 0.90}, - "individual_results": [], - "total_tokens": {"input_tokens": 0, "output_tokens": 0}, - "total_cost": 0.0, - } - - with open(self.test_file, "w") as f: - json.dump(test_data, f) - - def tearDown(self): - """Clean up temporary directory""" - shutil.rmtree(self.temp_dir, ignore_errors=True) - - @patch("publish.create_and_push_metrics") - def test_publish_metrics_calls_create_and_push(self, mock_create_push): - """Test that publish_metrics calls create_and_push_metrics""" - publish_metrics( - input_file=str(self.test_file), - workflow_name="test-workflow", - otlp_endpoint="localhost:4318", + # Verify shutdown is still called in finally block + assert len(shutdown_calls) == 1 + + +# TestPublishMetrics tests +def test_publish_metrics_calls_create_and_push(evaluation_scores_file, monkeypatch): + """Test that publish_metrics calls create_and_push_metrics""" + create_push_calls = [] + + def mock_create_push(overall_scores, workflow_name, otlp_endpoint): + create_push_calls.append( + { + "overall_scores": overall_scores, + "workflow_name": workflow_name, + "otlp_endpoint": otlp_endpoint, + } ) - # Verify create_and_push_metrics was called - mock_create_push.assert_called_once() + monkeypatch.setattr("publish.create_and_push_metrics", mock_create_push) - # Verify parameters (positional arguments) - call_args = mock_create_push.call_args - self.assertEqual(call_args[0][0]["faithfulness"], 0.85) - self.assertEqual(call_args[0][0]["answer_relevancy"], 0.90) - self.assertEqual(call_args[0][1], "test-workflow") - self.assertEqual(call_args[0][2], "localhost:4318") + publish_metrics( + input_file=str(evaluation_scores_file), + workflow_name="test-workflow", + otlp_endpoint="localhost:4318", + ) - @patch("publish.create_and_push_metrics") - def test_publish_metrics_with_empty_scores(self, mock_create_push): - """Test behavior when overall_scores is empty""" - # Create file with empty overall_scores - test_data = {"overall_scores": {}, "individual_results": []} + # Verify create_and_push_metrics was called + assert len(create_push_calls) == 1 - empty_file = Path(self.temp_dir) / "empty_scores.json" - with open(empty_file, "w") as f: - json.dump(test_data, f) + # Verify parameters + assert create_push_calls[0]["overall_scores"]["faithfulness"] == 0.85 + assert create_push_calls[0]["overall_scores"]["answer_relevancy"] == 0.90 + assert create_push_calls[0]["workflow_name"] == "test-workflow" + assert create_push_calls[0]["otlp_endpoint"] == "localhost:4318" - publish_metrics( - input_file=str(empty_file), - workflow_name="test-workflow", - otlp_endpoint="localhost:4318", - ) - # Verify create_and_push_metrics was NOT called - mock_create_push.assert_not_called() - - -class TestIntegrationWithTestData(unittest.TestCase): - """Integration tests with realistic evaluation data""" - - def setUp(self): - """Set up temporary directory with realistic test data""" - self.temp_dir = tempfile.mkdtemp() - self.test_file = Path(self.temp_dir) / "evaluation_scores.json" - - # Create realistic evaluation scores - test_data = { - "overall_scores": { - "faithfulness": 0.8523, - "answer_relevancy": 0.9012, - "context_precision": 0.7845, - "context_recall": 0.8234, - }, - "individual_results": [ - { - "user_input": "What is the weather?", - "response": "It is sunny.", - "faithfulness": 0.85, - "answer_relevancy": 0.90, - } - ], - "total_tokens": {"input_tokens": 0, "output_tokens": 0}, - "total_cost": 0.0, - } - - with open(self.test_file, "w") as f: - json.dump(test_data, f, indent=2) - - def tearDown(self): - """Clean up temporary directory""" - shutil.rmtree(self.temp_dir, ignore_errors=True) - - @patch("publish.OTLPMetricExporter") - @patch("publish.MeterProvider") - @patch("publish.metrics.get_meter") - def test_publish_realistic_scores(self, mock_get_meter, mock_provider_class, mock_exporter_class): - """Test publishing realistic evaluation scores""" - # Mock the meter and gauge - mock_gauge = MagicMock() - mock_meter = MagicMock() - mock_meter.create_gauge.return_value = mock_gauge - mock_get_meter.return_value = mock_meter - - # Mock the provider - mock_provider = MagicMock() - mock_provider_class.return_value = mock_provider - - publish_metrics( - input_file=str(self.test_file), - workflow_name="weather-assistant-test", - otlp_endpoint="localhost:4318", - ) +def test_publish_metrics_with_empty_scores(temp_dir, monkeypatch): + """Test behavior when overall_scores is empty""" + # Create file with empty overall_scores + test_data = {"overall_scores": {}, "individual_results": []} + + empty_file = Path(temp_dir) / "empty_scores.json" + with open(empty_file, "w") as f: + json.dump(test_data, f) + + create_push_calls = [] + + def mock_create_push(overall_scores, workflow_name, otlp_endpoint): + create_push_calls.append(True) + + monkeypatch.setattr("publish.create_and_push_metrics", mock_create_push) + + publish_metrics( + input_file=str(empty_file), + workflow_name="test-workflow", + otlp_endpoint="localhost:4318", + ) + + # Verify create_and_push_metrics was NOT called + assert len(create_push_calls) == 0 + + +# TestIntegrationWithTestData tests +def test_publish_realistic_scores(realistic_scores_file, monkeypatch): + """Test publishing realistic evaluation scores""" + # Mock the meter and gauge + create_gauge_calls = [] + + class MockGauge: + def set(self, value, attributes): + pass + + class MockMeter: + def create_gauge(self, name, unit=None, description=None): + create_gauge_calls.append({"name": name}) + return MockGauge() + + mock_meter = MockMeter() + + def mock_get_meter(*args, **kwargs): + return mock_meter + + # Mock the provider + class MockProvider: + def force_flush(self): + pass + + def shutdown(self): + pass + + def mock_provider_init(**kwargs): + return MockProvider() + + # Mock the exporter + class MockExporter: + _preferred_temporality = {} + _preferred_aggregation = {} + + exporter_calls = [] + + def mock_exporter_init(endpoint): + exporter_calls.append(True) + return MockExporter() - # Verify OTLPMetricExporter was called - mock_exporter_class.assert_called_once() + monkeypatch.setattr("publish.metrics.get_meter", mock_get_meter) + monkeypatch.setattr("publish.MeterProvider", mock_provider_init) + monkeypatch.setattr("publish.OTLPMetricExporter", mock_exporter_init) - # Verify 4 metrics were created (faithfulness, answer_relevancy, context_precision, context_recall) - self.assertEqual(mock_meter.create_gauge.call_count, 4) + publish_metrics( + input_file=str(realistic_scores_file), + workflow_name="weather-assistant-test", + otlp_endpoint="localhost:4318", + ) + # Verify OTLPMetricExporter was called + assert len(exporter_calls) == 1 -if __name__ == "__main__": - unittest.main() + # Verify 4 metrics were created (faithfulness, answer_relevancy, context_precision, context_recall) + assert len(create_gauge_calls) == 4 diff --git a/testworkflows/tests/test_run.py b/testworkflows/tests/test_run.py index 4533944..fce093b 100644 --- a/testworkflows/tests/test_run.py +++ b/testworkflows/tests/test_run.py @@ -4,189 +4,210 @@ Tests the agent query execution and experiment functionality. """ +import os import shutil import sys import tempfile -import unittest from pathlib import Path -from unittest.mock import AsyncMock, MagicMock, patch + +import pytest sys.path.insert(0, str(Path(__file__).parent.parent / "scripts")) from run import initialize_client, main, run_agent_experiment -class TestInitializeClient(unittest.TestCase): - """Test the initialize_client function""" - - @patch("run.ClientFactory") - @patch("run.minimal_agent_card") - async def test_initialize_client_creates_client(self, mock_agent_card, mock_factory): - """Test that initialize_client creates a client correctly""" - # Mock the agent card - mock_card = MagicMock() - mock_agent_card.return_value = mock_card - - # Mock the factory and client - mock_client = MagicMock() - mock_factory_instance = MagicMock() - mock_factory_instance.create.return_value = mock_client - mock_factory.return_value = mock_factory_instance - - # Call the function - result = await initialize_client("http://test-agent:8000") - - # Verify - mock_agent_card.assert_called_once_with("http://test-agent:8000") - mock_factory_instance.create.assert_called_once_with(mock_card) - self.assertEqual(result, mock_client) - - -class TestRunAgentExperiment(unittest.TestCase): - """Test the run_agent_experiment function""" - - def setUp(self): - """Set up temporary directory for experiment outputs""" - self.temp_dir = tempfile.mkdtemp() - self.original_cwd = Path.cwd() - - def tearDown(self): - """Clean up temporary directory""" - shutil.rmtree(self.temp_dir, ignore_errors=True) - - @patch("run.logging.getLogger") - @patch("run.initialize_client") - async def test_run_agent_experiment_success(self, mock_init_client, mock_get_logger): - """Test successful agent query execution""" - # Mock logger - mock_logger = MagicMock() - mock_get_logger.return_value = mock_logger - - # Mock the client - mock_client = MagicMock() - - # Create a mock task response - mock_task = MagicMock() - mock_task.model_dump.return_value = { - "artifacts": [{"parts": [{"text": "Agent response text"}]}], - "history": [], - } - - # Mock the async generator returned by send_message - async def mock_send_message(message): +# Fixtures +@pytest.fixture +def temp_dir(): + """Create a temporary directory for tests""" + tmp = tempfile.mkdtemp() + original_cwd = Path.cwd() + yield tmp, original_cwd + shutil.rmtree(tmp, ignore_errors=True) + + +# TestInitializeClient tests +@pytest.mark.asyncio +async def test_initialize_client_creates_client(monkeypatch): + """Test that initialize_client creates a client correctly""" + + # Mock the agent card + class MockCard: + pass + + mock_card = MockCard() + + def mock_agent_card(url): + return mock_card + + # Mock the factory and client + class MockClient: + pass + + mock_client = MockClient() + + class MockFactory: + def create(self, card): + return mock_client + + def mock_factory_init(config=None): + return MockFactory() + + monkeypatch.setattr("run.minimal_agent_card", mock_agent_card) + monkeypatch.setattr("run.ClientFactory", mock_factory_init) + + # Call the function + result = await initialize_client("http://test-agent:8000") + + # Verify + assert result == mock_client + + +# TestRunAgentExperiment tests +@pytest.mark.asyncio +async def test_run_agent_experiment_success(monkeypatch): + """Test successful agent query execution""" + + # Mock the client + class MockTask: + def model_dump(self, **kwargs): + return { + "artifacts": [{"parts": [{"text": "Agent response text"}]}], + "history": [], + } + + mock_task = MockTask() + + class MockClient: + async def send_message(self, message): yield (mock_task, None) - mock_client.send_message = mock_send_message - mock_init_client.return_value = mock_client - - # Create test row - test_row = { - "user_input": "What is the weather?", - "retrieved_contexts": ["Context about weather"], - "reference": "Expected answer", - } - - # Mock httpx AsyncClient - with patch("run.httpx.AsyncClient") as mock_httpx: - mock_httpx_instance = AsyncMock() - mock_httpx_instance.__aenter__.return_value = mock_httpx_instance - mock_httpx_instance.__aexit__.return_value = None - mock_httpx.return_value = mock_httpx_instance - - # Create an async function that mimics the experiment function - async def test_experiment_func(row, agent_url): - return await run_agent_experiment.func(row, agent_url=agent_url) - - # Call the function - result = await test_experiment_func(test_row, agent_url="http://test-agent:8000") - - # Verify result structure - self.assertIn("user_input", result) - self.assertIn("retrieved_contexts", result) - self.assertIn("reference", result) - self.assertIn("response", result) - self.assertEqual(result["user_input"], "What is the weather?") - self.assertEqual(result["response"], "Agent response text") - - @patch("run.logging.getLogger") - @patch("run.initialize_client") - async def test_run_agent_experiment_error(self, mock_init_client, mock_get_logger): - """Test agent query with error handling""" - # Mock logger - mock_logger = MagicMock() - mock_get_logger.return_value = mock_logger - - # Mock client that raises an error - mock_init_client.side_effect = Exception("Connection failed") - - # Create test row - test_row = { - "user_input": "What is the weather?", - "retrieved_contexts": ["Context"], - "reference": "Answer", - } - - # Mock httpx AsyncClient - with patch("run.httpx.AsyncClient") as mock_httpx: - mock_httpx_instance = AsyncMock() - mock_httpx_instance.__aenter__.return_value = mock_httpx_instance - mock_httpx_instance.__aexit__.return_value = None - mock_httpx.return_value = mock_httpx_instance - - # Create an async function that mimics the experiment function - async def test_experiment_func(row, agent_url): - return await run_agent_experiment.func(row, agent_url=agent_url) - - # Call the function - result = await test_experiment_func(test_row, agent_url="http://test-agent:8000") - - # Verify error is captured in response - self.assertIn("response", result) - self.assertIn("ERROR", result["response"]) - self.assertIn("Connection failed", result["response"]) - - -class TestMain(unittest.TestCase): - """Test the main function""" - - def setUp(self): - """Set up temporary directory""" - self.temp_dir = tempfile.mkdtemp() - self.original_cwd = Path.cwd() - - def tearDown(self): - """Clean up temporary directory""" - shutil.rmtree(self.temp_dir, ignore_errors=True) - - @patch("run.run_agent_experiment.arun") - @patch("run.Dataset.load") - async def test_main_execution(self, mock_dataset_load, mock_arun): - """Test main function execution flow""" - import os - - os.chdir(self.temp_dir) - - try: - # Create a mock dataset - mock_dataset = MagicMock() - mock_dataset.__len__ = MagicMock(return_value=2) - mock_dataset_load.return_value = mock_dataset - - # Mock experiment results - mock_experiment = MagicMock() - mock_arun.return_value = mock_experiment - - # Run main - await main("http://test-agent:8000") - - # Verify Dataset.load was called - mock_dataset_load.assert_called_once() - - # Verify experiment was run - mock_arun.assert_called_once() - finally: - os.chdir(self.original_cwd) - - -if __name__ == "__main__": - unittest.main() + mock_client = MockClient() + + async def mock_init_client(url): + return mock_client + + # Mock httpx AsyncClient + class MockAsyncClient: + async def __aenter__(self): + return self + + async def __aexit__(self, exc_type, exc_val, exc_tb): + pass + + def mock_httpx_client(): + return MockAsyncClient() + + monkeypatch.setattr("run.initialize_client", mock_init_client) + monkeypatch.setattr("run.httpx.AsyncClient", mock_httpx_client) + + # Create test row + test_row = { + "user_input": "What is the weather?", + "retrieved_contexts": ["Context about weather"], + "reference": "Expected answer", + } + + # Call the function + result = await run_agent_experiment.func(test_row, agent_url="http://test-agent:8000") + + # Verify result structure + assert "user_input" in result + assert "retrieved_contexts" in result + assert "reference" in result + assert "response" in result + assert result["user_input"] == "What is the weather?" + assert result["response"] == "Agent response text" + + +@pytest.mark.asyncio +async def test_run_agent_experiment_error(monkeypatch): + """Test agent query with error handling""" + + # Mock client that raises an error + async def mock_init_client(url): + raise Exception("Connection failed") + + # Mock httpx AsyncClient + class MockAsyncClient: + async def __aenter__(self): + return self + + async def __aexit__(self, exc_type, exc_val, exc_tb): + pass + + def mock_httpx_client(): + return MockAsyncClient() + + monkeypatch.setattr("run.initialize_client", mock_init_client) + monkeypatch.setattr("run.httpx.AsyncClient", mock_httpx_client) + + # Create test row + test_row = { + "user_input": "What is the weather?", + "retrieved_contexts": ["Context"], + "reference": "Answer", + } + + # Call the function + result = await run_agent_experiment.func(test_row, agent_url="http://test-agent:8000") + + # Verify error is captured in response + assert "response" in result + assert "ERROR" in result["response"] + assert "Connection failed" in result["response"] + + +# TestMain tests +@pytest.mark.asyncio +async def test_main_execution(temp_dir, monkeypatch): + """Test main function execution flow""" + + tmp, original_cwd = temp_dir + os.chdir(tmp) + + try: + # Create a mock dataset + class MockDataset: + def __len__(self): + return 2 + + mock_dataset = MockDataset() + + def mock_dataset_load(path, backend): + return mock_dataset + + # Mock experiment results + class MockExperiment: + pass + + mock_experiment = MockExperiment() + + async def mock_arun(*args, **kwargs): + return mock_experiment + + calls_to_load = [] + calls_to_arun = [] + + def mock_dataset_load_tracked(**kwargs): + calls_to_load.append(kwargs) + return mock_dataset + + async def mock_arun_tracked(*args, **kwargs): + calls_to_arun.append({"args": args, "kwargs": kwargs}) + return mock_experiment + + monkeypatch.setattr("run.Dataset.load", mock_dataset_load_tracked) + monkeypatch.setattr("run.run_agent_experiment.arun", mock_arun_tracked) + + # Run main + await main("http://test-agent:8000") + + # Verify Dataset.load was called + assert len(calls_to_load) == 1 + + # Verify experiment was run + assert len(calls_to_arun) == 1 + finally: + os.chdir(original_cwd) diff --git a/testworkflows/tests/test_setup.py b/testworkflows/tests/test_setup.py index 988bfec..9e594b9 100644 --- a/testworkflows/tests/test_setup.py +++ b/testworkflows/tests/test_setup.py @@ -4,205 +4,210 @@ Tests the dataset download, conversion, and Ragas dataset creation functionality. """ +import os import shutil import sys import tempfile -import unittest from io import BytesIO from pathlib import Path -from unittest.mock import MagicMock, patch import pandas as pd +import pytest sys.path.insert(0, str(Path(__file__).parent.parent / "scripts")) from setup import custom_convert_csv, dataframe_to_ragas_dataset, get_converter, main -class TestCustomConvertCSV(unittest.TestCase): - """Test the custom_convert_csv function""" +# Fixtures +@pytest.fixture +def temp_dir(): + """Create a temporary directory for tests""" + tmp = tempfile.mkdtemp() + original_cwd = Path.cwd() + yield tmp, original_cwd + shutil.rmtree(tmp, ignore_errors=True) - def test_converts_string_to_list(self): - """Test that retrieved_contexts strings are converted to lists""" + +# TestCustomConvertCSV tests +def test_converts_string_to_list(): + """Test that retrieved_contexts strings are converted to lists""" + csv_content = b"user_input,retrieved_contexts,reference\n" + csv_content += b'"Question?","Context text","Answer"\n' + + buffer = BytesIO(csv_content) + df = custom_convert_csv(buffer) + + assert isinstance(df["retrieved_contexts"].iloc[0], list) + assert df["retrieved_contexts"].iloc[0] == ["Context text"] + + +def test_handles_empty_retrieved_contexts(): + """Test handling of empty retrieved_contexts""" + csv_content = b"user_input,retrieved_contexts,reference\n" + csv_content += b'"Question?","","Answer"\n' + + buffer = BytesIO(csv_content) + df = custom_convert_csv(buffer) + + # Empty string becomes [nan] in pandas, which then becomes [] + # The function converts non-list values to lists + result = df["retrieved_contexts"].iloc[0] + # Check that it's a list and handle NaN case + assert isinstance(result, list) + # If it contains NaN, that's acceptable behavior for empty strings in CSV + if result and pd.isna(result[0]): + # This is expected - pandas converts empty string to NaN + pass + else: + # Or it should be an empty list + assert result == [] + + +def test_missing_retrieved_contexts_column(): + """Test that CSV without retrieved_contexts column works""" + csv_content = b"user_input,reference\n" + csv_content += b'"Question?","Answer"\n' + + buffer = BytesIO(csv_content) + df = custom_convert_csv(buffer) + + assert "retrieved_contexts" not in df.columns + + +# TestGetConverter tests +def test_unsupported_format(): + """Test that unsupported formats raise TypeError""" + with pytest.raises(TypeError) as exc_info: + get_converter("https://example.com/data.xlsx") + + assert "Unsupported filetype" in str(exc_info.value) + + +# TestDataframeToRagasDataset tests +def test_creates_ragas_dataset_file(temp_dir): + """Test that ragas_dataset.jsonl is created""" + + tmp, original_cwd = temp_dir + os.chdir(tmp) + + try: + df = pd.DataFrame( + { + "user_input": ["Question 1"], + "retrieved_contexts": [["Context 1"]], + "reference": ["Answer 1"], + } + ) + + dataframe_to_ragas_dataset(df) + + # Check for the file in the datasets subdirectory + dataset_file = Path(tmp) / "data" / "datasets" / "ragas_dataset.jsonl" + assert dataset_file.exists(), f"Dataset file not found at {dataset_file}" + finally: + os.chdir(original_cwd) + + +# TestMain tests +def test_main_with_csv(temp_dir, monkeypatch): + """Test main function with CSV file""" + + tmp, original_cwd = temp_dir + os.chdir(tmp) + + try: + # Mock the HTTP response csv_content = b"user_input,retrieved_contexts,reference\n" csv_content += b'"Question?","Context text","Answer"\n' - buffer = BytesIO(csv_content) - df = custom_convert_csv(buffer) + class MockResponse: + def __init__(self): + self.content = csv_content - self.assertIsInstance(df["retrieved_contexts"].iloc[0], list) - self.assertEqual(df["retrieved_contexts"].iloc[0], ["Context text"]) + def raise_for_status(self): + pass - def test_handles_empty_retrieved_contexts(self): - """Test handling of empty retrieved_contexts""" - csv_content = b"user_input,retrieved_contexts,reference\n" - csv_content += b'"Question?","","Answer"\n' + calls = [] + + def mock_get(url, timeout=None): + calls.append({"url": url, "timeout": timeout}) + return MockResponse() + + monkeypatch.setattr("setup.requests.get", mock_get) + + # Run main + main("https://example.com/data.csv") + + # Verify dataset was created in datasets subdirectory + dataset_file = Path(tmp) / "data" / "datasets" / "ragas_dataset.jsonl" + assert dataset_file.exists(), f"Dataset file not found at {dataset_file}" + + # Verify requests.get was called correctly + assert len(calls) == 1 + assert calls[0]["url"] == "https://example.com/data.csv" + assert calls[0]["timeout"] == 20 + finally: + os.chdir(original_cwd) + + +def test_main_with_json(temp_dir, monkeypatch): + """Test main function with JSON file""" + + tmp, original_cwd = temp_dir + os.chdir(tmp) + + try: + # Mock the HTTP response + json_content = b"""[ + { + "user_input": "Question?", + "retrieved_contexts": ["Context text"], + "reference": "Answer" + } + ]""" - buffer = BytesIO(csv_content) - df = custom_convert_csv(buffer) + class MockResponse: + def __init__(self): + self.content = json_content - # Empty string becomes [nan] in pandas, which then becomes [] - # The function converts non-list values to lists - result = df["retrieved_contexts"].iloc[0] - # Check that it's a list and handle NaN case - self.assertIsInstance(result, list) - # If it contains NaN, that's acceptable behavior for empty strings in CSV - if result and pd.isna(result[0]): - # This is expected - pandas converts empty string to NaN - pass - else: - # Or it should be an empty list - self.assertEqual(result, []) + def raise_for_status(self): + pass - def test_missing_retrieved_contexts_column(self): - """Test that CSV without retrieved_contexts column works""" - csv_content = b"user_input,reference\n" - csv_content += b'"Question?","Answer"\n' + def mock_get(url, timeout=None): + return MockResponse() - buffer = BytesIO(csv_content) - df = custom_convert_csv(buffer) + monkeypatch.setattr("setup.requests.get", mock_get) - self.assertNotIn("retrieved_contexts", df.columns) + # Run main + main("https://example.com/data.json") + # Verify dataset was created in datasets subdirectory + dataset_file = Path(tmp) / "data" / "datasets" / "ragas_dataset.jsonl" + assert dataset_file.exists(), f"Dataset file not found at {dataset_file}" + finally: + os.chdir(original_cwd) -class TestGetConverter(unittest.TestCase): - """Test the get_converter function""" - - def test_unsupported_format(self): - """Test that unsupported formats raise TypeError""" - with self.assertRaises(TypeError) as context: - get_converter("https://example.com/data.xlsx") - - self.assertIn("Unsupported filetype", str(context.exception)) +def test_main_with_invalid_url(temp_dir, monkeypatch): + """Test main function with invalid URL (HTTP error)""" -class TestDataframeToRagasDataset(unittest.TestCase): - """Test the dataframe_to_ragas_dataset function""" - - def setUp(self): - """Set up temporary directory for test outputs""" - self.temp_dir = tempfile.mkdtemp() - self.original_cwd = Path.cwd() - - def tearDown(self): - """Clean up temporary directory""" - shutil.rmtree(self.temp_dir, ignore_errors=True) - - def test_creates_ragas_dataset_file(self): - """Test that ragas_dataset.jsonl is created""" - import os - - os.chdir(self.temp_dir) - - try: - df = pd.DataFrame( - { - "user_input": ["Question 1"], - "retrieved_contexts": [["Context 1"]], - "reference": ["Answer 1"], - } - ) - - dataframe_to_ragas_dataset(df) - - # Check for the file in the datasets subdirectory - dataset_file = Path(self.temp_dir) / "data" / "datasets" / "ragas_dataset.jsonl" - self.assertTrue(dataset_file.exists(), f"Dataset file not found at {dataset_file}") - finally: - os.chdir(self.original_cwd) - - -class TestMain(unittest.TestCase): - """Test the main function with mocked HTTP requests""" - - def setUp(self): - """Set up temporary directory""" - self.temp_dir = tempfile.mkdtemp() - self.original_cwd = Path.cwd() - - def tearDown(self): - """Clean up temporary directory""" - shutil.rmtree(self.temp_dir, ignore_errors=True) - - @patch("setup.requests.get") - def test_main_with_csv(self, mock_get): - """Test main function with CSV file""" - import os - - os.chdir(self.temp_dir) - - try: - # Mock the HTTP response - csv_content = b"user_input,retrieved_contexts,reference\n" - csv_content += b'"Question?","Context text","Answer"\n' - - mock_response = MagicMock() - mock_response.content = csv_content - mock_response.raise_for_status = MagicMock() - mock_get.return_value = mock_response - - # Run main - main("https://example.com/data.csv") - - # Verify dataset was created in datasets subdirectory - dataset_file = Path(self.temp_dir) / "data" / "datasets" / "ragas_dataset.jsonl" - self.assertTrue(dataset_file.exists(), f"Dataset file not found at {dataset_file}") + tmp, original_cwd = temp_dir + os.chdir(tmp) - # Verify requests.get was called - mock_get.assert_called_once_with("https://example.com/data.csv", timeout=20) - finally: - os.chdir(self.original_cwd) + try: + # Mock HTTP error + class MockResponse: + def raise_for_status(self): + raise Exception("HTTP 404") - @patch("setup.requests.get") - def test_main_with_json(self, mock_get): - """Test main function with JSON file""" - import os + def mock_get(url, timeout=None): + return MockResponse() - os.chdir(self.temp_dir) + monkeypatch.setattr("setup.requests.get", mock_get) - try: - # Mock the HTTP response - json_content = b"""[ - { - "user_input": "Question?", - "retrieved_contexts": ["Context text"], - "reference": "Answer" - } - ]""" - - mock_response = MagicMock() - mock_response.content = json_content - mock_response.raise_for_status = MagicMock() - mock_get.return_value = mock_response - - # Run main - main("https://example.com/data.json") - - # Verify dataset was created in datasets subdirectory - dataset_file = Path(self.temp_dir) / "data" / "datasets" / "ragas_dataset.jsonl" - self.assertTrue(dataset_file.exists(), f"Dataset file not found at {dataset_file}") - finally: - os.chdir(self.original_cwd) - - @patch("setup.requests.get") - def test_main_with_invalid_url(self, mock_get): - """Test main function with invalid URL (HTTP error)""" - import os - - os.chdir(self.temp_dir) - - try: - # Mock HTTP error - mock_response = MagicMock() - mock_response.raise_for_status.side_effect = Exception("HTTP 404") - mock_get.return_value = mock_response - - # Verify that the error propagates - with self.assertRaises(Exception): - main("https://example.com/nonexistent.csv") - finally: - os.chdir(self.original_cwd) - - -if __name__ == "__main__": - unittest.main() + # Verify that the error propagates + with pytest.raises(Exception, match="HTTP 404"): + main("https://example.com/nonexistent.csv") + finally: + os.chdir(original_cwd) diff --git a/testworkflows/tests_e2e/test_e2e.py b/testworkflows/tests_e2e/test_e2e.py index 3eff507..946f884 100755 --- a/testworkflows/tests_e2e/test_e2e.py +++ b/testworkflows/tests_e2e/test_e2e.py @@ -17,8 +17,9 @@ pytest tests/test_e2e.py """ +import os import logging -import subprocess +import subprocess # nosec from pathlib import Path from typing import List @@ -96,7 +97,7 @@ def run_command(self, command: List[str], step_name: str) -> bool: logger.info(f"{'=' * 60}\n") try: - result = subprocess.run(command, check=True, capture_output=True, text=True) + result = subprocess.run(command, check=True, capture_output=True, text=True) # nosec # Log stdout if present if result.stdout: @@ -228,7 +229,6 @@ def test_e2e_pipeline(): Example: E2E_DATASET_URL="https://example.com/data.csv" pytest tests/test_e2e.py """ - import os # Get configuration from environment variables with sensible defaults dataset_url = os.getenv("E2E_DATASET_URL", "http://localhost:8000/dataset.json") From fe34bd0e8f1f0691e570ead46b5f73706714f464 Mon Sep 17 00:00:00 2001 From: MiaAppel Date: Tue, 11 Nov 2025 12:46:01 +0100 Subject: [PATCH 55/61] FIX: remove issues Linter & Bandit currently ignore --- testworkflows/pyproject.toml | 12 ++---------- 1 file changed, 2 insertions(+), 10 deletions(-) diff --git a/testworkflows/pyproject.toml b/testworkflows/pyproject.toml index 4e07aa6..e9856fc 100644 --- a/testworkflows/pyproject.toml +++ b/testworkflows/pyproject.toml @@ -12,6 +12,7 @@ dev = [ "poethepoet>=0.31.1", "ruff>=0.12.7", "pytest>=7.4.0", + "pytest-asyncio>=1.3.0", ] prod = [ @@ -58,20 +59,11 @@ line-length = 120 # DTZ --> datetime timezone awareness extend-select = ["Q", "N", "I001", "PT", "TID251", "DTZ"] -ignore = [ - "PT009", # allow unittest-style assertions (assertEqual, assertAlmostEqual, etc.) - "PT027" # allow unittest.TestCase without using pytest fixtures -] - [tool.mypy] mypy_path = "scripts" [tool.bandit] exclude_dirs = [".cache", ".venv"] -skips = [ - "B404", # Usage of 'subprocess' module - "B603", # 'Subprocess' call without check for execution of untrusted input -] [tool.bandit.assert_used] -skips = ["*_test.py", "*test_*.py"] \ No newline at end of file +skips = ["*_test.py", "*test_*.py"] From c5fbfd3c2718ae518eda0f718a14fbbd7be919e7 Mon Sep 17 00:00:00 2001 From: MiaAppel Date: Tue, 11 Nov 2025 12:48:49 +0100 Subject: [PATCH 56/61] FIX: Formatting --- testworkflows/tests_e2e/test_e2e.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/testworkflows/tests_e2e/test_e2e.py b/testworkflows/tests_e2e/test_e2e.py index 946f884..34d78a3 100755 --- a/testworkflows/tests_e2e/test_e2e.py +++ b/testworkflows/tests_e2e/test_e2e.py @@ -17,8 +17,8 @@ pytest tests/test_e2e.py """ -import os import logging +import os import subprocess # nosec from pathlib import Path from typing import List From f04ba0abdb099eb68fa5e36378dc4198a664275b Mon Sep 17 00:00:00 2001 From: MiaAppel Date: Tue, 11 Nov 2025 12:48:57 +0100 Subject: [PATCH 57/61] FIX: Imports --- testworkflows/tests/test_evaluate.py | 10 +++++----- 1 file changed, 5 insertions(+), 5 deletions(-) diff --git a/testworkflows/tests/test_evaluate.py b/testworkflows/tests/test_evaluate.py index 199ea5e..cf29fe8 100644 --- a/testworkflows/tests/test_evaluate.py +++ b/testworkflows/tests/test_evaluate.py @@ -4,18 +4,17 @@ Tests the RAGAS evaluation functionality. """ -import os import json +import os import shutil import sys import tempfile from argparse import ArgumentError from pathlib import Path -from ragas.metrics import Metric -from evaluate import convert_metrics import pandas as pd import pytest +from ragas.metrics import Metric sys.path.insert(0, str(Path(__file__).parent.parent / "scripts")) @@ -280,6 +279,7 @@ def test_available_metrics_loaded(): # TestConvertMetrics tests def test_convert_metrics_with_valid_metrics(): """Test that convert_metrics correctly converts valid metric names to objects""" + from evaluate import convert_metrics # Use metrics that are commonly available in RAGAS metric_names = ["faithfulness", "answer_relevancy"] @@ -302,6 +302,7 @@ def test_convert_metrics_with_valid_metrics(): def test_convert_metrics_with_invalid_metrics(): """Test that convert_metrics handles invalid metric names""" + from evaluate import convert_metrics # Test with only invalid metrics - should raise ValueError with pytest.raises(ValueError, match="No valid metrics provided"): @@ -310,6 +311,7 @@ def test_convert_metrics_with_invalid_metrics(): def test_convert_metrics_mixed_valid_invalid(): """Test convert_metrics with mixed valid and invalid metric names""" + from evaluate import convert_metrics # Get one valid metric name from AVAILABLE_METRICS if not AVAILABLE_METRICS: @@ -323,6 +325,4 @@ def test_convert_metrics_mixed_valid_invalid(): # Should only return the valid metric assert len(metric_objects) == 1 - - assert isinstance(metric_objects[0], Metric) From d28695e5ae87dc3027bbf76bf58192c0b83a8b67 Mon Sep 17 00:00:00 2001 From: MiaAppel Date: Tue, 11 Nov 2025 12:50:31 +0100 Subject: [PATCH 58/61] FIX: Imports --- testworkflows/tests/test_evaluate.py | 5 +---- 1 file changed, 1 insertion(+), 4 deletions(-) diff --git a/testworkflows/tests/test_evaluate.py b/testworkflows/tests/test_evaluate.py index cf29fe8..b1cd89b 100644 --- a/testworkflows/tests/test_evaluate.py +++ b/testworkflows/tests/test_evaluate.py @@ -18,7 +18,7 @@ sys.path.insert(0, str(Path(__file__).parent.parent / "scripts")) -from evaluate import AVAILABLE_METRICS, format_evaluation_scores, main +from evaluate import AVAILABLE_METRICS, convert_metrics, format_evaluation_scores, main # Fixtures @@ -279,7 +279,6 @@ def test_available_metrics_loaded(): # TestConvertMetrics tests def test_convert_metrics_with_valid_metrics(): """Test that convert_metrics correctly converts valid metric names to objects""" - from evaluate import convert_metrics # Use metrics that are commonly available in RAGAS metric_names = ["faithfulness", "answer_relevancy"] @@ -302,7 +301,6 @@ def test_convert_metrics_with_valid_metrics(): def test_convert_metrics_with_invalid_metrics(): """Test that convert_metrics handles invalid metric names""" - from evaluate import convert_metrics # Test with only invalid metrics - should raise ValueError with pytest.raises(ValueError, match="No valid metrics provided"): @@ -311,7 +309,6 @@ def test_convert_metrics_with_invalid_metrics(): def test_convert_metrics_mixed_valid_invalid(): """Test convert_metrics with mixed valid and invalid metric names""" - from evaluate import convert_metrics # Get one valid metric name from AVAILABLE_METRICS if not AVAILABLE_METRICS: From 057a092be8ac91b6a7174d1fd564596f9452e08e Mon Sep 17 00:00:00 2001 From: MiaAppel Date: Tue, 11 Nov 2025 12:54:11 +0100 Subject: [PATCH 59/61] FIX: Update uv.lock --- testworkflows/uv.lock | 51 +++++++++++++++++++++++++++++++------------ 1 file changed, 37 insertions(+), 14 deletions(-) diff --git a/testworkflows/uv.lock b/testworkflows/uv.lock index a129116..31b6180 100644 --- a/testworkflows/uv.lock +++ b/testworkflows/uv.lock @@ -2163,6 +2163,19 @@ wheels = [ { url = "https://files.pythonhosted.org/packages/a8/a4/20da314d277121d6534b3a980b29035dcd51e6744bd79075a6ce8fa4eb8d/pytest-8.4.2-py3-none-any.whl", hash = "sha256:872f880de3fc3a5bdc88a11b39c9710c3497a547cfa9320bc3c5e62fbf272e79", size = 365750, upload-time = "2025-09-04T14:34:20.226Z" }, ] +[[package]] +name = "pytest-asyncio" +version = "1.3.0" +source = { registry = "https://pypi.org/simple" } +dependencies = [ + { name = "pytest" }, + { name = "typing-extensions", marker = "python_full_version < '3.13'" }, +] +sdist = { url = "https://files.pythonhosted.org/packages/90/2c/8af215c0f776415f3590cac4f9086ccefd6fd463befeae41cd4d3f193e5a/pytest_asyncio-1.3.0.tar.gz", hash = "sha256:d7f52f36d231b80ee124cd216ffb19369aa168fc10095013c6b014a34d3ee9e5", size = 50087, upload-time = "2025-11-10T16:07:47.256Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/e5/35/f8b19922b6a25bc0880171a2f1a003eaeb93657475193ab516fd87cac9da/pytest_asyncio-1.3.0-py3-none-any.whl", hash = "sha256:611e26147c7f77640e6d0a92a38ed17c3e9848063698d5c93d5aa7aa11cebff5", size = 15075, upload-time = "2025-11-10T16:07:45.537Z" }, +] + [[package]] name = "python-dateutil" version = "2.9.0.post0" @@ -2679,48 +2692,58 @@ wheels = [ name = "test-bench" version = "0.1.0" source = { virtual = "." } -dependencies = [ + +[package.dev-dependencies] +dev = [ + { name = "bandit" }, + { name = "import-linter" }, + { name = "mypy" }, + { name = "poethepoet" }, + { name = "pytest" }, + { name = "pytest-asyncio" }, + { name = "ruff" }, +] +prod = [ { name = "a2a" }, { name = "a2a-sdk" }, - { name = "bandit" }, { name = "httpx" }, - { name = "import-linter" }, { name = "langchain-openai" }, - { name = "mypy" }, { name = "opentelemetry-api" }, { name = "opentelemetry-exporter-otlp-proto-http" }, { name = "opentelemetry-sdk" }, { name = "pandas" }, { name = "pandas-stubs" }, - { name = "poethepoet" }, { name = "pyarrow" }, - { name = "pytest" }, { name = "ragas" }, { name = "requests" }, - { name = "ruff" }, { name = "types-requests" }, ] [package.metadata] -requires-dist = [ + +[package.metadata.requires-dev] +dev = [ + { name = "bandit", extras = ["toml"], specifier = ">=1.7.8" }, + { name = "import-linter", specifier = ">=2.0" }, + { name = "mypy", specifier = ">=1.17.0" }, + { name = "poethepoet", specifier = ">=0.31.1" }, + { name = "pytest", specifier = ">=7.4.0" }, + { name = "pytest-asyncio", specifier = ">=1.3.0" }, + { name = "ruff", specifier = ">=0.12.7" }, +] +prod = [ { name = "a2a", specifier = ">=0.44" }, { name = "a2a-sdk", specifier = ">=0.3.10" }, - { name = "bandit", extras = ["toml"], specifier = ">=1.7.8" }, { name = "httpx", specifier = ">=0.28.1" }, - { name = "import-linter", specifier = ">=2.0" }, { name = "langchain-openai", specifier = ">=1.0.2" }, - { name = "mypy", specifier = ">=1.17.0" }, { name = "opentelemetry-api", specifier = ">=1.20.0" }, { name = "opentelemetry-exporter-otlp-proto-http", specifier = ">=1.20.0" }, { name = "opentelemetry-sdk", specifier = ">=1.20.0" }, { name = "pandas", specifier = ">=2.3.3" }, { name = "pandas-stubs", specifier = ">=2.3.0" }, - { name = "poethepoet", specifier = ">=0.31.1" }, { name = "pyarrow", specifier = ">=21.0.0" }, - { name = "pytest", specifier = ">=7.4.0" }, { name = "ragas", specifier = ">=0.3.5" }, { name = "requests", specifier = ">=2.32.5" }, - { name = "ruff", specifier = ">=0.12.7" }, { name = "types-requests", specifier = ">=2.32.0" }, ] From 6e27c6c1918b48c222b3a0b3eed8a4775d6d983d Mon Sep 17 00:00:00 2001 From: MiaAppel Date: Tue, 11 Nov 2025 14:55:57 +0100 Subject: [PATCH 60/61] FEAT: Documentation for Testworkflows --- testworkflows/README.md | 533 +++++++++++++++++++++++++++++- testworkflows/scripts/evaluate.py | 6 +- 2 files changed, 520 insertions(+), 19 deletions(-) diff --git a/testworkflows/README.md b/testworkflows/README.md index 2624424..079b2a5 100644 --- a/testworkflows/README.md +++ b/testworkflows/README.md @@ -1,24 +1,525 @@ -# Getting Started with Testkube +# Test Workflows - Automated Agent Evaluation System -## Testkube Setup +An automated evaluation and testing system for AI agents using the **RAGAS** (Retrieval Augmented Generation Assessment) framework. This system downloads test datasets, executes queries through agents via the **A2A** protocol, evaluates responses using configurable metrics, and publishes results to **OpenTelemetry** for monitoring. -**Install Testkube locally:** -```shell -# Install Testkube CLI -brew install testkube +---- -# Install Testkube in your cluster -testkube init +## Table of Contents + +- [Architecture](#architecture) +- [Prerequisites](#prerequisites) +- [Getting Started](#getting-started) +- [Quick Start](#quick-start) +- [Detailed Usage](#detailed-usage) +- [Dataset Requirements](#dataset-requirements) +- [Testing](#testing) +- [Development](#development) +- [Troubleshooting](#troubleshooting) +- [Project Structure](#project-structure) +- [Contributing](#contributing) + +---- + +## Overview + +This project provides a complete pipeline for evaluating AI agent performance: + +- **Automated Testing**: Run predefined test queries through your agents +- **Multi-Format Support**: Accept datasets in CSV, JSON, or Parquet formats +- **Flexible Evaluation**: Configure multiple RAGAS metrics for comprehensive assessment +- **Observability**: Publish metrics to OpenTelemetry endpoints for monitoring and analysis +- **Type-Safe**: Built with type hints and validated with MyPy +- **Limitation**: Currently only support SingleTurnSample Metrics (see [Available Metrics](#available-metrics)) + +---- + +## Architecture + +``` +Input Dataset (user_input, retrieved_contexts, reference) + | + v + [1. setup.py] - Downloads & converts to RAGAS JSONL format + | + v +data/datasets/ragas_dataset.jsonl + | + v + [2. run.py] - Executes queries via A2A protocol, adds responses + | ^ + | | + | Agent URL + v +data/experiments/ragas_experiment.jsonl + | + v + [3. evaluate.py] - Calculates RAGAS metrics + | ^ + | | + | LLM Model + v +results/evaluation_scores.json + | + v + [4. publish.py] - Publishes to OTLP endpoint + | + v +OpenTelemetry Collector +``` +### Key Design Principles + +- **RAGAS-Native Format**: Uses RAGAS column names (`user_input`, `response`, `retrieved_contexts`, `reference`) throughout +- **JSONL Backend**: Internal storage uses JSONL for native list support +- **Format-Aware Input**: Intelligent handling of CSV (list conversion), JSON, and Parquet formats + +---- + +## Prerequisites + +- **Python 3.13+** +- **API Key**: `OPENAI_API_KEY` environment variable (required for LLM-based evaluation) +- **OTLP Endpoint**: Optional, defaults to `localhost:4318` + +---- + +## Getting Started + +### Install dependencies using UV + +```bash +# Clone the repository +git clone git@github.com:agentic-layer/testbench.git +cd testworkflows + +# Install (dev & prod) dependencies with uv +uv sync --group dev --group prod +``` + +### Environment Setup + +```bash +# Required for evaluation +export OPENAI_API_KEY="your-api-key-here" + +# Optional: Configure custom OTLP endpoint +export OTLP_ENDPOINT="http://otlp-collector:4318" +``` + +The system automatically creates the required directories (`data/`, `results/`) on first run. + +---- + +## Quick Start + +Run the complete evaluation pipeline in 4 steps: + +```bash +# 1. Download and prepare dataset +python3 scripts/setup.py "https://example.com/dataset.csv" + +# 2. Execute queries through your agent +python3 scripts/run.py "http://localhost:8000" + +# 3. Evaluate responses with RAGAS metrics +python3 scripts/evaluate.py gemini-2.5-flash-lite faithfulness answer_relevancy + +# 4. Publish metrics to OpenTelemetry +python3 scripts/publish.py "my-agent-evaluation" +``` + +---- + +## Detailed Usage + +### 1. setup.py - Dataset Preparation + +Downloads and converts test datasets to RAGAS-native JSONL format. + +**Syntax:** +```bash +python3 scripts/setup.py +``` + +**Arguments:** +- `dataset_url` (required): URL to dataset file (`.csv`, `.json`, or `.parquet`) + +**Required Dataset Schema:** +- See [Dataset Requirements](#dataset-requirements) + +**Output:** +- `data/datasets/ragas_dataset.jsonl` - RAGAS Dataset in JSONL format + +--- + +### 2. run.py - Agent Query Execution + +Executes test queries through an agent using the A2A protocol and collects responses. + +**Syntax:** +```bash +python3 scripts/run.py +``` + +**Arguments:** +- `agent_url` (required): URL to the agent's A2A endpoint + +**Input:** +- `data/datasets/ragas_dataset.jsonl` (loaded automatically) + +**Output:** +- `data/experiments/ragas_experiment.jsonl` - Agent responses with preserved context + +**Output Schema:** +```jsonl +{"user_input": "What is X?", "retrieved_contexts": ["Context about X"], "reference": "X is...", "response": "Agent's answer"} +``` + +**Notes:** +- Uses asynchronous A2A client for efficient communication +- Preserves all original dataset fields +- Automatically handles response streaming + +--- + +### 3. evaluate.py - RAGAS Metric Evaluation + +Evaluates agent responses using configurable RAGAS metrics and calculates costs. + +**Syntax:** +```bash +python3 scripts/evaluate.py [metric2 ...] [--cost-per-input COST] [--cost-per-output COST] +``` + +**Arguments:** +- `model` (required): Model name for evaluation (e.g., `gemini-2.5-flash-lite`, `gpt-4`) +- `metrics` (required): One or more RAGAS metric names +- `--cost-per-input` (optional): Cost per input token (default: 0.000005, i.e., $5 per 1M tokens) +- `--cost-per-output` (optional): Cost per output token (default: 0.000015, i.e., $15 per 1M tokens) + +### **Available Metrics:** + +| Metric | Special required columns | +|--------|-------------------------| +| `faithfulness` | retrieved_contexts | +| `context_precision` | retrieved_contexts | +| `context_recall` | retrieved_contexts | +| `context_entity_recall` | retrieved_contexts| +| `context_utilization` | retrieved_contexts| +| `llm_context_precision_with_reference` | retrieved_contexts| +|`llm_context_precision_without_reference`| retrieved_contexts| +|`faithful_rate`| retrieved_contexts| +|`relevance_rate`| retrieved_contexts| +|`noise_sensitivity`| retrieved_contexts| +|`factual_correctness`| | +|`domain_specific_rubrics`| | +|`nv_accuracy`| | +|`nv_context_relevance`| retrieved_contexts| +|`nv_response_groundedness`| retrieved_contexts| +|`string_present`| | +|`exact_match`| | +|`summary_score`| reference_contexts | +|`llm_sql_equivalence_with_reference`| reference_contexts | + + + +**Input:** +- `data/experiments/ragas_experiment.jsonl` (loaded automatically) + +**Examples:** +```bash +# Single metric +python3 scripts/evaluate.py gemini-2.5-flash-lite faithfulness + +# Multiple metrics +python3 scripts/evaluate.py gemini-2.5-flash-lite faithfulness answer_relevancy context_precision + +# Custom token costs +python3 scripts/evaluate.py gpt-4 faithfulness answer_correctness \ + --cost-per-input 0.00003 \ + --cost-per-output 0.00006 +``` + +**Output:** +- `results/evaluation_scores.json` - Evaluation results with metrics, token usage, and costs + +**Output Format:** +```json +{ + "overall_scores": { + "faithfulness": 0.95, + "answer_relevancy": 0.98 + }, + "individual_results": [ + { + "user_input": "What is the capital of France?", + "response": "Paris is the capital of France.", + "faithfulness": 0.95, + "answer_relevancy": 0.98 + } + ], + "total_tokens": { + "input_tokens": 1500, + "output_tokens": 500 + }, + "total_cost": 0.015 +} +``` + +**Notes:** +- Currently only support **SingleTurnSample** Metrics (see [Available Metrics](#available-metrics)) +- Dynamically discovers available metrics from `ragas.metrics` module +- Invalid metric names will show available options +- Token costs can be customized per model pricing + +--- + +### 4. publish.py - Metrics Publishing + +Publishes evaluation metrics to an OpenTelemetry OTLP endpoint for monitoring. + +**Syntax:** +```bash +python3 scripts/publish.py [otlp_endpoint] +``` + +**Arguments:** +- `workflow_name` (required): Name of the test workflow (used as metric label) +- `otlp_endpoint` (optional): OTLP HTTP endpoint URL (default: `localhost:4318`) + +**Input:** +- `results/evaluation_scores.json` (loaded automatically) + +**Published Metrics:** + +Each RAGAS metric is published as a gauge with the workflow name as an attribute: + +``` +ragas_evaluation_faithfulness{workflow_name="weather-assistant-eval"} = 0.85 +ragas_evaluation_answer_relevancy{workflow_name="weather-assistant-eval"} = 0.92 +``` + +**Notes:** +- Sends metrics to `/v1/metrics` endpoint +- Uses resource with `service.name="ragas-evaluation"` +- Forces flush to ensure delivery before exit + +---- + +## Dataset Requirements + +### Schema + +Your input dataset must contain these columns: + +```python +{ + "user_input": str, # Test question/prompt + "retrieved_contexts": [str], # List of context strings (must be array type) (Optional but required by many metrics) + "reference": str # Ground truth answer +} +``` + +### Format-Specific Notes + +**CSV Files:** +- `retrieved_contexts` must be formatted as quoted array strings +- Example: `"['Context 1', 'Context 2', 'Context 3']"` +- The system automatically parses these strings into Python lists + +**JSON Files:** +```json +[ + { + "user_input": "What is the capital of France?", + "retrieved_contexts": ["Paris is a city in France.", "France is in Europe."], + "reference": "Paris" + } +] +``` + +**Parquet Files:** +- Use native list/array columns for `retrieved_contexts` + +### Example Dataset + +```csv +user_input,retrieved_contexts,reference +"What is Python?","['Python is a programming language', 'Python was created by Guido van Rossum']","Python is a high-level programming language" +"What is AI?","['AI stands for Artificial Intelligence', 'AI systems can learn from data']","AI is the simulation of human intelligence by machines" +``` + +---- + +## Testing + +### Unit Tests + +Run all unit tests: +```bash +uv run pytest tests/ -v +``` + +Or using the task runner: +```bash +uv run poe test +``` + +### End-to-End Tests + +Run the complete pipeline integration test: + +```bash +uv run pytest tests_e2e/test_e2e.py -v +``` + +Or using the task runner: +```bash +uv run poe test_e2e ``` -**Run Testkube workflows:** -```shell -# Apply workflow configuration -kubectl apply -f first_workflow.yaml +**Configuration via Environment Variables:** -# Run a workflow -testkube run workflow my-test +```bash +export E2E_DATASET_URL="http://localhost:8000/dataset.json" +export E2E_AGENT_URL="http://localhost:11010" +export E2E_MODEL="gemini-2.5-flash-lite" +export E2E_METRICS="faithfulness,answer_relevancy" +export E2E_WORKFLOW_NAME="Test Workflow" +export E2E_OTLP_ENDPOINT="localhost:4318" -# Check workflow status -testkube get workflows +pytest tests_e2e/test_e2e.py -v ``` + +**Test Coverage:** +1. Scripts exist and are executable +2. `setup.py` creates `data/datasets/ragas_dataset.jsonl` +3. `run.py` creates `data/experiments/ragas_experiment.jsonl` +4. `evaluate.py` creates `results/evaluation_scores.json` +5. `publish.py` successfully pushes metrics to OTLP + +---- + +## Development + +## Code Quality Standards +### Code Style: +- **Linting**: Ruff with 120 character line limit +- **Type Checking**: mypy for static type analysis +- **Security**: Bandit for security vulnerability detection +- **Import Organization**: import-linter for dependency management + +### Development Commands: + +This project uses `poethepoet` for task automation: + +```bash +# Run all quality checks +uv run poe check + +# Individual checks +uv run poe mypy # Type checking +uv run poe ruff # Linting and formatting +uv run poe bandit # Security analysis +uv run poe lint-imports # Import dependency validation +uv run poe test # Execute test suite +uv run poe test_e2e # Execute end-to-end tests + +# Auto-formatting +uv run poe format # Code formatting +uv run poe lint # Auto-fix linting issues +``` + +---- + +## Troubleshooting + +### "Source dataset is missing required columns" + +**Problem**: Dataset doesn't have the required schema. + +**Solution**: +- Verify your dataset has columns: `user_input`, `retrieved_contexts`, and `reference` +- Check that column names match exactly (case-sensitive) +- Ensure `retrieved_contexts` is formatted as a list (see Dataset Requirements) + +Example fix for CSV: +```csv +# Wrong (missing columns) +question,context,answer + +# Correct +user_input,retrieved_contexts,reference +``` + +### "No results found in experiment" + +**Problem**: `evaluate.py` can't find experiment results. + +**Solution**: +- Check if `data/experiments/ragas_experiment.jsonl` exists +- Verify `run.py` completed successfully without errors +- Ensure the agent URL was accessible during execution +- Check file permissions on the `data/` directory + +### CSV List Conversion Issues + +**Problem**: `retrieved_contexts` not parsing correctly from CSV. + +**Solution**: +- Ensure lists are formatted as Python array strings: `"['item1', 'item2']"` +- Use proper quoting in CSV: wrap the entire array string in double quotes +- Consider using JSON or Parquet format for complex data types + +Example: +```csv +user_input,retrieved_contexts,reference +"What is X?","['Context about X', 'More context']","X is..." +``` + +### Evaluation Metrics Fail + +**Problem**: Certain metrics fail during evaluation. + +**Solution**: +- Some metrics require the `reference` field (e.g., `context_precision`, `context_recall`) +- Verify your dataset includes all required fields for the metrics you're using +- Check the RAGAS documentation for metric-specific requirements + +---- + +## Project Structure + +``` +testworkflows/ +├── scripts/ # Main pipeline scripts +│ ├── setup.py # Dataset download & conversion +│ ├── run.py # Agent query execution +│ ├── evaluate.py # RAGAS metric evaluation +│ └── publish.py # Metrics publishing to OTLP +├── tests/ # Unit tests +│ ├── test_setup.py +│ ├── test_run.py +│ ├── test_evaluate.py +│ ├── test_publish.py +│ └── test_data/ # Sample test datasets +│ ├── dataset.csv +│ └── dataset.json +├── tests_e2e/ # End-to-end integration tests +│ └── test_e2e.py +├── data/ # Runtime data (gitignored) +│ ├── datasets/ # Input datasets (RAGAS format) +│ │ └── ragas_dataset.jsonl +│ └── experiments/ # Agent responses with context +│ └── ragas_experiment.jsonl +├── results/ # Evaluation outputs (gitignored) +│ └── evaluation_scores.json +├── pyproject.toml # Dependencies & project config +├── uv.lock # Lock file for uv package manager +├── .python-version # Python Version file +``` + +---- + +## Contributing + +See [Contribution Guide](https://github.com/agentic-layer/testbench?tab=contributing-ov-file) for details on contribution, and the process for submitting pull requests. \ No newline at end of file diff --git a/testworkflows/scripts/evaluate.py b/testworkflows/scripts/evaluate.py index f93a60e..a0070d4 100644 --- a/testworkflows/scripts/evaluate.py +++ b/testworkflows/scripts/evaluate.py @@ -209,15 +209,15 @@ def main( Available metrics: {", ".join(AVAILABLE_METRICS.keys())} Examples: - python3 scripts/evaluate.py gemini-flash-latest faithfulness - python3 scripts/evaluate.py gemini-flash-latest faithfulness context_precision context_recall + python3 scripts/evaluate.py gemini-2.5-flash-lite faithfulness + python3 scripts/evaluate.py gemini-2.5-flash-lite faithfulness context_precision context_recall """, ) parser.add_argument( "model", type=str, - help="Model name to use for evaluation (e.g., gemini-flash-latest)", + help="Model name to use for evaluation (e.g., gemini-2.5-flash-lite)", ) parser.add_argument( From d1ee69e78a19df1b25f785b51fce68a09d60011c Mon Sep 17 00:00:00 2001 From: MiaAppel Date: Thu, 13 Nov 2025 09:10:59 +0100 Subject: [PATCH 61/61] REFACTOR: restructure Dependencies & dependency groups --- .github/workflows/check.yml | 2 +- .github/workflows/test-e2e.yml | 2 +- .github/workflows/test.yml | 2 +- testworkflows/pyproject.toml | 25 ++++++++++++------------- 4 files changed, 15 insertions(+), 16 deletions(-) diff --git a/.github/workflows/check.yml b/.github/workflows/check.yml index a33cc15..9313b10 100644 --- a/.github/workflows/check.yml +++ b/.github/workflows/check.yml @@ -38,7 +38,7 @@ jobs: python-version-file: "testworkflows/.python-version" - name: Install Dependencies - run: uv sync --group dev --group prod + run: uv sync - name: Run Checks run: uv run poe check diff --git a/.github/workflows/test-e2e.yml b/.github/workflows/test-e2e.yml index d6f50ea..0ab8032 100644 --- a/.github/workflows/test-e2e.yml +++ b/.github/workflows/test-e2e.yml @@ -43,7 +43,7 @@ jobs: python-version-file: "testworkflows/.python-version" - name: Install Dependencies - run: uv sync --group dev --group prod + run: uv sync - name: Set up Kubernetes (kind) uses: 'helm/kind-action@v1' diff --git a/.github/workflows/test.yml b/.github/workflows/test.yml index bc535b0..795fb82 100644 --- a/.github/workflows/test.yml +++ b/.github/workflows/test.yml @@ -40,7 +40,7 @@ jobs: python-version-file: "testworkflows/.python-version" - name: Install Dependencies - run: uv sync --group dev --group prod + run: uv sync - name: Run Tests run: uv run poe test diff --git a/testworkflows/pyproject.toml b/testworkflows/pyproject.toml index e9856fc..4ffb991 100644 --- a/testworkflows/pyproject.toml +++ b/testworkflows/pyproject.toml @@ -3,19 +3,7 @@ name = "test-bench" version = "0.1.0" description = "Testbench to evaluate agents using Ragas" requires-python = ">=3.12" - -[dependency-groups] -dev = [ - "bandit[toml]>=1.7.8", - "mypy>=1.17.0", - "import-linter>=2.0", - "poethepoet>=0.31.1", - "ruff>=0.12.7", - "pytest>=7.4.0", - "pytest-asyncio>=1.3.0", -] - -prod = [ +dependencies = [ "a2a>=0.44", "a2a-sdk>=0.3.10", "httpx>=0.28.1", @@ -31,6 +19,17 @@ prod = [ "opentelemetry-exporter-otlp-proto-http>=1.20.0", ] +[dependency-groups] +dev = [ + "bandit[toml]>=1.7.8", + "mypy>=1.17.0", + "import-linter>=2.0", + "poethepoet>=0.31.1", + "ruff>=0.12.7", + "pytest>=7.4.0", + "pytest-asyncio>=1.3.0", +] + [tool.poe.tasks] test = "pytest tests/ -v" test_e2e = "pytest tests_e2e/ -v"