diff --git a/.github/workflows/mcp-composite-action/action.yml b/.github/workflows/mcp-composite-action/action.yml new file mode 100644 index 0000000..7e8627e --- /dev/null +++ b/.github/workflows/mcp-composite-action/action.yml @@ -0,0 +1,34 @@ +name: 'MCP server setup' +description: 'Sync uv dependencies and run MCP server' + + +inputs: + DUCKDB_FILENAME: + description: 'path to duckdb file' + required: false + default: 'tests/duckdb.example' + +runs: + using: "composite" + steps: + - name: Set up Python + uses: actions/setup-python@v5 + with: + python-version: '3.13' + - name: Install uv + run: curl -LsSf https://astral.sh/uv/install.sh | sh + shell: bash + - name: Install dependencies + run: uv sync --group dev + shell: bash + - name: Run fileserver + run: uv run --directory tests/ fileserver.py & + shell: bash + - name: Run mcp server + run: uv run fastmcp run -t http app/main.py & + env: + DUCKDB_FILENAME: ${{ inputs.DUCKDB_FILENAME }} + shell: bash + - name: Wait for mcp initialization + run: sleep 5 + shell: bash diff --git a/.github/workflows/tests.yml b/.github/workflows/tests.yml new file mode 100644 index 0000000..0b83956 --- /dev/null +++ b/.github/workflows/tests.yml @@ -0,0 +1,41 @@ +name: tests + +on: [push] + +env: + DUCKDB_FILENAME: tests/duckdb.example + OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }} + OPIK_API_KEY: ${{ secrets.OPIK_API_KEY }} + OPIK_WORKSPACE: ${{ secrets.OPIK_WORKSPACE }} + +jobs: + test: + runs-on: ubuntu-latest + steps: + - uses: actions/checkout@v4 + - uses: ./.github/workflows/mcp-composite-action + with: + DUCKDB_FILENAME: 'tests/duckdb.example' + - name: Run tests + run: uv run --directory tests/ pytest query_tests.py + inspector: + runs-on: ubuntu-latest + steps: + - uses: actions/checkout@v5 + - uses: actions/setup-node@v4 + with: + node-version: '20' + - uses: ./.github/workflows/mcp-composite-action + with: + DUCKDB_FILENAME: 'tests/duckdb.example' + - name: Run inspector + run: npx @modelcontextprotocol/inspector --cli http://127.0.0.1:8000/mcp --method tools/list + opik: + runs-on: ubuntu-latest + steps: + - uses: actions/checkout@v5 + - uses: ./.github/workflows/mcp-composite-action + with: + DUCKDB_FILENAME: 'tests/duckdb.example' + - name: Run opik experiments + run: uv run tests/opik/tool_calls.py diff --git a/README.md b/README.md index 3886eb4..c4d78a4 100644 --- a/README.md +++ b/README.md @@ -53,6 +53,7 @@ Want to try it out? **[πŸš€ Getting Started](docs/getting-started.md)** - **[πŸ”§ Configuration](docs/configuration.md)** - Environment variables and settings - **[πŸ› οΈ MCP Tools](docs/mcp-tools.md)** - All available tools - **[πŸ—ΊοΈ Roadmap](docs/roadmap.md)** - Upcoming features and roadmap +- **[πŸ§ͺ Testing](docs/tests.md)** - Instructions on tests and how to run them **Need help?** Looking for guidance on use cases or implementation? Don't hesitate to ask your question in our [GitHub discussion forum](https://github.com/the-momentum/apple-health-mcp-server/discussions)! You'll also find interesting use cases, tips, and community insights there. diff --git a/app/config.py b/app/config.py index f4227c7..753273d 100644 --- a/app/config.py +++ b/app/config.py @@ -37,6 +37,11 @@ class Settings(BaseSettings): RAW_XML_PATH: str = "raw.xml" XML_SAMPLE_SIZE: int = 1000 + # Opik tests + OPENAI_API_KEY: str = "" + OPIK_WORKSPACE: str = "" + OPIK_API_KEY: str = "" + @field_validator("BACKEND_CORS_ORIGINS", mode="after") @classmethod def assemble_cors_origins(cls, v: str | list[str]) -> list[str] | str: diff --git a/app/services/health/clickhouse.py b/app/services/health/clickhouse.py index 0a5bcd5..498cad4 100644 --- a/app/services/health/clickhouse.py +++ b/app/services/health/clickhouse.py @@ -49,7 +49,7 @@ def search_values_from_ch( date_to: str | None = None, ) -> dict[str, Any]: return ch.inquire(f""" - SELECT * FROM {ch.db_name}.{ch.table_name} WHERE textvalue = '{value}' + SELECT * FROM {ch.db_name}.{ch.table_name} WHERE textValue = '{value}' {f"AND type = '{record_type}'" if record_type else ""} {f"AND startDate >= '{date_from}'" if date_from else ""} {f"AND startDate <= '{date_to}'" if date_to else ""} diff --git a/app/services/health/duckdb_queries.py b/app/services/health/duckdb_queries.py index 8f3621e..286363f 100644 --- a/app/services/health/duckdb_queries.py +++ b/app/services/health/duckdb_queries.py @@ -141,8 +141,8 @@ def main() -> None: pars = HealthRecordSearchParams( limit=20, record_type="HKWorkoutActivityTypeRunning", - date_from="2016-01-01T00:00:00+00:00", - date_to="2016-12-31T23:59:59+00:00", + min_workout_duration="45", + max_workout_duration="53", ) logger.info( f"records for search_health_records_from_duckdb: {search_health_records_from_duckdb(pars)}", diff --git a/config/.env.example b/config/.env.example index 047d7c8..dd4275b 100644 --- a/config/.env.example +++ b/config/.env.example @@ -4,3 +4,6 @@ ES_HOST="localhost" DUCKDB_FILENAME="applehealth.duckdb" CHUNK_SIZE="50000" RAW_XML_PATH="raw.xml" +OPENAI_API_KEY="sk-proj-***" +OPIK_WORKSPACE="username" +OPIK_API_KEY="abcdef12345" diff --git a/docs/getting-started.md b/docs/getting-started.md index 628912b..069cd23 100644 --- a/docs/getting-started.md +++ b/docs/getting-started.md @@ -41,8 +41,8 @@ Follow these steps to set up Apple Health MCP Server in your environment. - Run `make duckdb` to create a parquet file with your exported XML data - If you want to connect to the file through http(s): - The only thing you need to do is change the .env path, e.g. `localhost:8080/applehealth.parquet` - - If you want an example on how to host the files locally, run `uv run tests/fileserver.py` - + - If you want an example on how to host the files locally, run `uv run tests/fileserver.py` + ## Configuration Files diff --git a/docs/tests.md b/docs/tests.md new file mode 100644 index 0000000..323f689 --- /dev/null +++ b/docs/tests.md @@ -0,0 +1,72 @@ +[← Back to README](../README.md) + +## Testing πŸ§ͺ + +There are 3 types of tests in this projects, all of which are included in the pipeline: + +Every test is done on [pre-prepared mock apple health data](https://gist.github.com/czajkub/7ee7a01c35990f910f034f46dbf83b66): + + +## Unit tests πŸ”§: + - Testing the importing of XML data to .duckdb and database calls to DuckDB + +## MCP Inspector tests πŸ”: + - Uses the [MCP Inspector](https://modelcontextprotocol.io/docs/tools/inspector) provided by Anthropic to test connection to the server hosted with streamable HTTP + - Mainly used in the pipeline, but can be run locally + +## Opik tests πŸ€–: + - End-to-End tests using an agent created from [this](https://github.com/the-momentum/python-ai-kit) AI development kit + - Two types of tests: + - Checking whether the correct tool was called + - Judging the answer from an LLM by three metrics: + - Answer relevancy: whether the answer is relevant to the user's question 🎯 + - Hallucination: whether the answer contains misleading or false information 🚫 + - Levenshtein ratio: Heuristic checking the text structure similarity πŸ“Š + +# How to run tests locally πŸ’»: +- ### Unit tests πŸ”§: +```bash +pytest tests/query_tests.py +``` + +Before running the next tests, make sure you have the server up and running: +```bash +uv run fastmcp run -t http app/main.py +``` + +- ### Inspector tests πŸ”: +```bash +npx @modelcontextprotocol/inspector --cli http://localhost:8000/mcp --transport http --method tools/list +``` + +- ### Opik tests πŸ€–: +Make sure your `OPENAI_API_KEY`, `OPIK_WORKSPACE` and `OPIK_API_KEY` environmental variables are set +(Opik workspace refers to your profile name and not project name) +```bash +uv run tests/opik/tool_calls.py +``` + +### How to run Opik tests in pipeline: +- Create an account on Opik if you already haven't +- Copy your `OPIK_API_KEY` and `OPIK_WORKSPACE` to Github secrets + + +To add new tests, you can either do it in the code ([example from opik](https://www.comet.com/docs/opik/evaluation/manage_datasets)): +```python +import opik +# Get or create a dataset +client = opik.Opik() +dataset = client.get_or_create_dataset(name="My dataset") +# Add dataset items to it +dataset.insert([ + {"user_question": "Hello, world!", "expected_output": {"assistant_answer": "Hello, world!"}}, + {"user_question": "What is the capital of France?", "expected_output": {"assistant_answer": "Paris"}}, +]) +``` + +Or add it on the website: +image + +When adding tool call questions, make sure the `input` and `tool_call` values are present, and when adding output checks make sure `input` and `expected_output` are set correctly. + +[← Back to README](../README.md) diff --git a/pyproject.toml b/pyproject.toml index 1927864..02b1bf2 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -31,6 +31,8 @@ module-name = "app" [dependency-groups] dev = [ "fastapi>=0.116.2", + "opik>=1.8.56", + "pydantic-ai>=1.0.10", "pytest>=8.4.2", "pytest-asyncio>=1.0.0", "pytest-cov>=6.2.1", @@ -50,7 +52,7 @@ exclude = ["./tests/", "./docs/", "./README.md"] [tool.ruff] line-length = 100 target-version = "py313" -extend-exclude = ["tests/", "./docs/", "./README.md"] +extend-exclude = ["./tests/", "./docs/", "./README.md"] [tool.ruff.lint] select = [ diff --git a/scripts/clickhouse_importer.py b/scripts/clickhouse_importer.py index ee00c23..1805ae1 100644 --- a/scripts/clickhouse_importer.py +++ b/scripts/clickhouse_importer.py @@ -26,7 +26,7 @@ def create_table(self) -> None: creationDate DateTime, unit String, value Float32, - textvalue String, + textValue String, ) ENGINE = MergeTree ORDER BY startDate diff --git a/tests/agent.py b/tests/agent.py new file mode 100644 index 0000000..dc9a8f5 --- /dev/null +++ b/tests/agent.py @@ -0,0 +1,81 @@ +import asyncio +import os + +from pydantic_ai.models.openai import OpenAIChatModel +from pydantic_ai.providers.openai import OpenAIProvider +from pydantic_ai import Agent +from pydantic_ai.tools import Tool +from pydantic_ai.mcp import MCPServerStreamableHTTP + +from dotenv import load_dotenv +import opik + +load_dotenv() + +class AgentManager: + def __init__(self): + self.agent: Agent | None = None + self.mcp_client: MCPServerStreamableHTTP | None = None + self.tools: list[Tool] | None = None + self._initialized = False + + async def initialize(self, model: str = "gpt-4o", + system_prompt: str | None = None): + if self._initialized: + return + try: + self.mcp_client = MCPServerStreamableHTTP("http://localhost:8000/mcp") + except Exception as e: + self.mcp_client = None + raise ConnectionError("Could not connect to MCP server") from e + + if system_prompt is None: + system_prompt = "You are an AI assistant to help the user as best as you can. You can use the tools provided to you to help the user." + + self.agent = self._create_agent(model, system_prompt) + self._initialized = True + + def _create_agent(self, model: str, system_prompt: str) -> Agent: + model = OpenAIChatModel(model, provider=OpenAIProvider(api_key=os.getenv("openai_api_key"))) + return Agent( + model=model, + deps_type=dict[str, str], + system_prompt=system_prompt, + toolsets=[self.mcp_client], + output_type=str, + ) + + @opik.track + async def handle_message(self, message: str) -> str: + if not self._initialized: + raise RuntimeError("Agent not initialized. Call initialize() first.") + + async with self.agent: + result = await self.agent.run(message) + return result.output + + def is_initialized(self) -> bool: + return self._initialized + + + +agent_manager = AgentManager() + + +async def main(): + await agent_manager.initialize() + + try: + while True: + user_input = input("Enter your message: ") + if user_input == "exit": + break + print("User: ", user_input) + response = await agent_manager.handle_message(user_input) + print("Agent: ", response) + finally: + print("Closing agent") + + +if __name__ == "__main__": + asyncio.run(main()) diff --git a/tests/duckdb.example b/tests/duckdb.example new file mode 100644 index 0000000..e5b1fcb Binary files /dev/null and b/tests/duckdb.example differ diff --git a/tests/opik/tool_calls.py b/tests/opik/tool_calls.py new file mode 100644 index 0000000..3ab661e --- /dev/null +++ b/tests/opik/tool_calls.py @@ -0,0 +1,151 @@ +import asyncio +import os + +from pydantic_ai.messages import ModelRequest, ModelResponse +from opik import Opik +from opik.evaluation import evaluate +from opik.evaluation.metrics import ( + base_metric, + score_result, + Hallucination, + LevenshteinRatio, + AnswerRelevance +) + +from tests.agent import AgentManager + + +agent_manager = AgentManager() +asyncio.run(agent_manager.initialize()) + + +class ToolSelectionQuality(base_metric.BaseMetric): + def __init__(self, name: str = "tool_selection_quality"): + super().__init__(name) + self.name = name + + def score(self, tool_calls, expected_tool_calls, **kwargs): + try: + actual_tool = tool_calls["function_name"] + expected_tool = expected_tool_calls["function_name"] + + if actual_tool == expected_tool: + return score_result.ScoreResult( + name=self.name, + value=1, + reason=f"Correct tool selected: {actual_tool}" + ) + else: + return score_result.ScoreResult( + name=self.name, + value=0, + reason=f"Wrong tool. Expected {expected_tool}, got {actual_tool}" + ) + except Exception as e: + return score_result.ScoreResult( + name=self.name, + value=0, + reason=f"Scoring error: {e}" + ) + + +def extract_tool_call(messages: list[ModelRequest | ModelResponse]) -> str | None: + for message in messages: + if isinstance(message, ModelRequest): + continue + part = message.parts[0] + try: + return part.tool_name + except Exception: + continue + return None + + +def evaluation_task(dataset_item): + try: + user_message_content = dataset_item["input"] + expected_tool = dataset_item.get("tool_call", "") + reference = dataset_item.get("expected_output", "") + + resp = agent_manager.agent.run_sync(user_message_content) + result = resp.new_messages() + tool_calls = {"function_name": extract_tool_call(result), + "function_parameters": {}} + + return { + "input": user_message_content, + "output": resp.output, + "reference": reference, + "tool_calls": tool_calls, + "expected_tool_calls": {"function_name": expected_tool, "function_parameters": {}} + } + except Exception as e: + return { + "input": dataset_item.get("input", {}), + "output": "Error processing input.", + "reference": dataset_item.get("expected_output", ""), + "tool_calls": {}, + "expected_tool_calls": {"function_name": "unknown", "function_parameters": {}}, + "error": str(e) + } + +# refer to https://github.com/comet-ml/opik/issues/2118 + +opik_workspace = os.getenv("OPIK_WORKSPACE") +opik_api_key = os.getenv("OPIK_API_KEY") + +os.environ["OPIK_WORKSPACE"] = opik_workspace +os.environ["OPIK_API_KEY"] = opik_api_key + +client = Opik( + workspace=opik_workspace, + api_key=opik_api_key +) + +dataset = client.get_dataset(name="tool_calls") + +judge_dataset = client.get_dataset(name="output_checks") + + +tool_call_evals = evaluate( + experiment_name="AgentToolSelectionExperiment", + dataset=dataset, + task=evaluation_task, + scoring_metrics=[ToolSelectionQuality()], + task_threads=1, +) + + +for i, test in enumerate(tool_call_evals.test_results, 1): + try: + print() + print(f"------- Test {i} -------") + print("Test query: ", test.test_case.scoring_inputs['input']) + print("Expected tool call: ", test.test_case.scoring_inputs['expected_tool_calls']['function_name']) + print("Called tool: ", test.test_case.scoring_inputs['tool_calls']['function_name']) + print("----------------------") + print() + except Exception as e: + print(f"Test {i} failed: {e}") + + +output_test_evals = evaluate( + experiment_name="JudgeOutputExperiment", + dataset=judge_dataset, + task=evaluation_task, + scoring_metrics=[Hallucination(), LevenshteinRatio(), AnswerRelevance(require_context=False)], + task_threads=1, +) + + +for i, test in enumerate(output_test_evals.test_results, 1): + try: + print() + print(f"------- Test {i} -------") + print("Test query: ", test.test_case.scoring_inputs['input']) + print("Expected output: ", test.test_case.scoring_inputs['expected_output']) + print("Got output: ", test.test_case.task_output['output']) + print("----------------------") + print() + except Exception as e: + print(f"Test {i} failed: {e}") diff --git a/tests/query_tests.py b/tests/query_tests.py new file mode 100644 index 0000000..c185ab5 --- /dev/null +++ b/tests/query_tests.py @@ -0,0 +1,159 @@ +import os +from pathlib import Path +from typing import Any + +import pytest + +path = Path(__file__).parent / "duckdb.example" +os.environ["DUCKDB_FILENAME"] = str(path) + +from app.schemas.record import HealthRecordSearchParams +from app.services.health.duckdb_queries import ( + get_health_summary_from_duckdb, + get_statistics_by_type_from_duckdb, + get_trend_data_from_duckdb, + search_health_records_from_duckdb, + search_values_from_duckdb, +) + + +@pytest.fixture +def counts() -> dict[str, int]: + return { + "HKQuantityTypeIdentifierStepCount": 14, + "HKQuantityTypeIdentifierHeartRate": 14, + "HKQuantityTypeIdentifierBasalEnergyBurned": 10, + "HKQuantityTypeIdentifierDistanceWalkingRunning": 6, + "HKQuantityTypeIdentifierActiveEnergyBurned": 5, + "HKQuantityTypeIdentifierBodyMassIndex": 5, + "HKQuantityTypeIdentifierBodyMass": 5, + "HKQuantityTypeIdentifierRunningSpeed": 3, + "HKQuantityTypeIdentifierFlightsClimbed": 3, + "HKQuantityTypeIdentifierWalkingHeartRateAverage": 2, + "HKQuantityTypeIdentifierAppleExerciseTime": 2, + "HKQuantityTypeIdentifierWalkingSpeed": 2, + "HKQuantityTypeIdentifierRunningStrideLength": 2, + "HKQuantityTypeIdentifierWalkingDoubleSupportPercentage": 2, + "HKQuantityTypeIdentifierVO2Max": 2, + "HKQuantityTypeIdentifierRunningVerticalOscillation": 2, + "HKQuantityTypeIdentifierOxygenSaturation": 2, + "HKQuantityTypeIdentifierAppleWalkingSteadiness": 2, + "HKQuantityTypeIdentifierRunningGroundContactTime": 2, + "HKQuantityTypeIdentifierRestingHeartRate": 2, + "HKQuantityTypeIdentifierStairDescentSpeed": 2, + "HKQuantityTypeIdentifierHeadphoneAudioExposure": 2, + "HKQuantityTypeIdentifierHeartRateVariabilitySDNN": 2, + "HKQuantityTypeIdentifierWalkingStepLength": 2, + "HKQuantityTypeIdentifierAppleStandTime": 2, + "HKQuantityTypeIdentifierWalkingAsymmetryPercentage": 2, + "HKQuantityTypeIdentifierRunningPower": 2, + "HKQuantityTypeIdentifierEnvironmentalAudioExposure": 2, + "HKQuantityTypeIdentifierStairAscentSpeed": 2, + "HKQuantityTypeIdentifierRespiratoryRate": 2, + "HKQuantityTypeIdentifierHeight": 1, + "HKWorkoutActivityTypeRunning": 24, + "HKWorkoutActivityTypeWalking": 5, + "HKWorkoutActivityTypeHiking": 3, + "HKWorkoutActivityTypeCycling": 3, + "HKWorkoutActivityTypeMixedMetabolicCardioTraining": 2, + "HKWorkoutActivityTypeHockey": 2, + "HKWorkoutActivityTypeHighIntensityIntervalTraining": 2, + "HKWorkoutActivityTypeTraditionalStrengthTraining": 2 + } + + +@pytest.fixture +def summary() -> list[dict[str, Any]]: + return get_health_summary_from_duckdb() + + +@pytest.fixture +def records() -> list[dict[str, Any]]: + return search_health_records_from_duckdb( + HealthRecordSearchParams( + record_type="HKQuantityTypeIdentifierStepCount", + value_min="65", + value_max="90", + ), + ) + +@pytest.fixture +def workouts() -> list[dict[str, Any]]: + return search_health_records_from_duckdb( + HealthRecordSearchParams( + limit=20, + record_type="HKWorkoutActivityTypeRunning", + min_workout_duration="45", + max_workout_duration="53" + ) + ) + + +@pytest.fixture +def statistics() -> list[dict[str, Any]]: + return get_statistics_by_type_from_duckdb( + "HKQuantityTypeIdentifierStepCount", + ) + + +@pytest.fixture +def trend_data() -> list[dict[str, Any]]: + return get_trend_data_from_duckdb( + record_type="HKQuantityTypeIdentifierBasalEnergyBurned", + interval="year" + ) + + +@pytest.fixture +def value_search() -> list[dict[str, Any]]: + return search_values_from_duckdb( + record_type="HKQuantityTypeIdentifierStepCount", + value="13", + ) + + +def test_summary(summary: list[dict[str, Any]], counts: dict[str, int]) -> None: + assert len(summary) == len(counts) + for record in summary: + assert record["count"] == counts[record["type"]] + + +def test_records(records: list[dict[str, Any]]) -> None: + assert len(records) == 2 + for record in records: + assert 65 < record["value"] < 90 + assert record["type"] == "HKQuantityTypeIdentifierStepCount" + +def test_workouts(workouts: list[dict[str, Any]]) -> None: + # 3 records, however there are 20 total stats associated with them + assert len(workouts) == 20 + for record in workouts: + assert 30 < record["duration"] < 60 + assert record["type"] == "HKWorkoutActivityTypeRunning" + + + +def test_statistics(statistics: list[dict[str, Any]] | dict[str, Any]) -> None: + assert len(statistics) == 1 + # turn list containing 1 dict into a dict + stats: dict[str, Any] = statistics[0] + assert stats["min"] == 13 + assert stats["max"] == 4567 + assert stats["count"] == 14 + + +def test_trend_data(trend_data: list[dict[str, Any]] | dict[str, Any]) -> None: + assert len(trend_data) == 2 + # turn list containing 1 dict into a dict + data: dict[str, Any] = trend_data[0] + assert data["count"] == 5 + assert data["min"] == 0.086 + assert data["max"] == 0.086 + # floating point values not exactly matching + assert 0.999 < data["sum"] / (0.086 * 5) < 1.001 + + +def test_value_search(value_search: list[dict[str, Any]]) -> None: + assert len(value_search) == 2 + for record in value_search: + assert record["type"] == "HKQuantityTypeIdentifierStepCount" diff --git a/uv.lock b/uv.lock index 33a715d..93ee96c 100644 --- a/uv.lock +++ b/uv.lock @@ -2,6 +2,73 @@ version = 1 revision = 2 requires-python = ">=3.13" +[[package]] +name = "ag-ui-protocol" +version = "0.1.9" +source = { registry = "https://pypi.org/simple" } +dependencies = [ + { name = "pydantic" }, +] +sdist = { url = "https://files.pythonhosted.org/packages/7b/d7/a8f8789b3b8b5f7263a902361468e8dfefd85ec63d1d5398579b9175d76d/ag_ui_protocol-0.1.9.tar.gz", hash = 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