diff --git a/Dockerfile.mlflow b/Dockerfile.mlflow new file mode 100644 index 0000000..1d0e6f3 --- /dev/null +++ b/Dockerfile.mlflow @@ -0,0 +1,10 @@ +FROM python:3.11-slim + +# Install MLflow and downgrade protobuf to a compatible version +RUN pip install mlflow==2.22.1 protobuf==3.20.1 + +# Expose the port for MLflow UI +EXPOSE 5000 + +# Command to run the MLflow server +CMD ["mlflow", "server", "--host", "0.0.0.0", "--port", "5000"] diff --git a/README.md b/README.md index 4fa74a6..70fefb4 100644 --- a/README.md +++ b/README.md @@ -7,12 +7,24 @@ Create a `.env` file in the root directory with the following content: ```env GEMINI_API_KEY=your_gemini_api_key ``` +The simplest way to run the application is to use `uv` and `docker` commands: +```shell +uv run download_public_data data +sudo docker compose up +``` +Then open your browser and go to: +http://localhost:7860/ (ReAgentAI) +http://localhost:5000/ (MLflow) #### setup with uv ```sh uv run download_public_data data uv run run.py ``` +Optionally you can set the `MLFLOW_TRACKING_URI` environment variable to point to your MLflow server: +```sh +MLFLOW_TRACKING_URI=http://localhost:5000 uv run run.py +``` Note: You need a trained model and a stock collection. You can download a publicly available model based on USPTO and a stock collection from ZINC database using the following command `download_public_data data`. #### setup with pip @@ -35,13 +47,36 @@ Build the Docker image: ```sh sudo docker build -t reagentai . ``` +Optionally you can set the `MLFLOW_TRACKING_URI` environment variable to point to your MLflow server. Run the Docker container: ```sh sudo docker run -p 7860:7860 --env-file .env reagentai ``` Access the application in your browser at: http://127.0.0.1:7860/ +### MLflow +```shell +uv run mlflow server +``` +### MLflow in a Docker container +```shell +sudo docker network create mlflow-network +``` +```shell +sudo docker build -f Dockerfile.mlflow -t mlflow-server . +``` +To run just mlflow-server: +```shell +sudo docker run --rm -p 5000:5000 mlflow-server +``` +To run both MLflow server and ReAgentAI: +```shell +sudo docker compose up +``` - +### Running Tests +```shell +pytest +``` ### Troubleshooting Problem: diff --git a/docker-compose.yml b/docker-compose.yml new file mode 100644 index 0000000..d8f2ed0 --- /dev/null +++ b/docker-compose.yml @@ -0,0 +1,24 @@ +version: '3' +services: + mlflow: + build: + context: . + dockerfile: Dockerfile.mlflow + ports: + - "5000:5000" + networks: + - mlflow-network + reagentai: + build: + context: . + dockerfile: Dockerfile + ports: + - "7860:7860" + env_file: + - .env + environment: + - MLFLOW_TRACKING_URI=http://mlflow:5000 + networks: + - mlflow-network +networks: + mlflow-network: \ No newline at end of file diff --git a/pyproject.toml b/pyproject.toml index 199716f..cfd83ab 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -9,8 +9,18 @@ dependencies = [ "pydantic-ai>=0.2.4", "python-dotenv>=1.1.0", "gradio>=5.29.1", + "mlflow>=2.22.1", ] +[dependency-groups] +dev = [ + "pytest>=8.3.5", +] + +[tool.pytest.ini_options] +testpaths = ["tests"] +python_files = "test_*.py" + [tool.black] target-version = ["py310", "py311"] line-length = 99 diff --git a/src/reagentai/common/mlflow_tracking.py b/src/reagentai/common/mlflow_tracking.py new file mode 100644 index 0000000..a05249a --- /dev/null +++ b/src/reagentai/common/mlflow_tracking.py @@ -0,0 +1,118 @@ +import logging +import os +from typing import Any + +import mlflow +from mlflow.tracking import MlflowClient + +logger = logging.getLogger(__name__) + + +class MLflowTracker: + """ + Handles MLflow experiment tracking for ReagentAI. + """ + + def __init__(self, experiment_name: str = "reagentai_experiments"): + """ + Initialize MLflow tracker. + + Args: + experiment_name: The name of the MLflow experiment to use + """ + self.experiment_name = experiment_name + self.tracking_uri = os.environ.get("MLFLOW_TRACKING_URI", "") + self.active_run = None + self.mlflow_enabled = bool(self.tracking_uri) + + if not self.mlflow_enabled: + logger.info("MLflow tracking is disabled - MLFLOW_TRACKING_URI is not set.") + return + + try: + mlflow.set_tracking_uri(self.tracking_uri) + + # Create or get the experiment + self.experiment = mlflow.get_experiment_by_name(experiment_name) + if not self.experiment: + self.experiment_id = mlflow.create_experiment(experiment_name) + else: + self.experiment_id = self.experiment.experiment_id + + self.client = MlflowClient() + except Exception as e: + logger.warning(f"MLflow experiment setup failed: {e}") + self.mlflow_enabled = False + + def start_run(self, run_name: str | None = None) -> str | None: + """ + Start a new MLflow run. + + Args: + run_name: Optional name for the run + + Returns: + The run ID of the created run or None if MLflow is disabled + """ + if not self.mlflow_enabled: + logger.debug("MLflow tracking disabled. Not starting run.") + return None + + try: + self.active_run = mlflow.start_run(experiment_id=self.experiment_id, run_name=run_name) + return self.active_run.info.run_id + except Exception as e: + logger.warning(f"Failed to start MLflow run: {e}") + self.mlflow_enabled = False + return None + + def end_run(self) -> None: + """End the current MLflow run.""" + if not self.mlflow_enabled or not self.active_run: + return + + try: + mlflow.end_run() + self.active_run = None + except Exception as e: + logger.warning(f"Error ending MLflow run: {e}") + + def log_params(self, params: dict[str, Any]) -> None: + """Log parameters to the current run.""" + if not self.mlflow_enabled or not self.active_run: + return + + try: + mlflow.log_params(params) + except Exception as e: + logger.warning(f"Failed to log params to MLflow: {e}") + + def log_metrics(self, metrics: dict[str, float | int], step: int | None = None) -> None: + """Log metrics to the current run.""" + if not self.mlflow_enabled or not self.active_run: + return + + try: + mlflow.log_metrics(metrics, step=step) + except Exception as e: + logger.warning(f"Failed to log metrics to MLflow: {e}") + + def log_artifact(self, local_path: str) -> None: + """Log an artifact to the current run.""" + if not self.mlflow_enabled or not self.active_run: + return + + try: + mlflow.log_artifact(local_path) + except Exception as e: + logger.warning(f"Failed to log artifact to MLflow: {e}") + + def set_tags(self, tags: dict[str, str]) -> None: + """Set tags on the current run.""" + if not self.mlflow_enabled or not self.active_run: + return + + try: + mlflow.set_tags(tags) + except Exception as e: + logger.warning(f"Failed to set tags in MLflow: {e}") diff --git a/src/reagentai/main.py b/src/reagentai/main.py index 3436e3c..39f7851 100644 --- a/src/reagentai/main.py +++ b/src/reagentai/main.py @@ -1,8 +1,10 @@ import logging +import os from dotenv import load_dotenv from src.reagentai.agents.main.main_agent import create_main_agent +from src.reagentai.common.mlflow_tracking import MLflowTracker from src.reagentai.logging import setup_logging from src.reagentai.ui.app import create_gradio_app @@ -13,7 +15,45 @@ def start_agent(): setup_logging() load_dotenv() + # Initialize MLflow tracking + tracker = MLflowTracker(experiment_name="reagentai_experiments") + + # Start a new run for this application session + run_id = tracker.start_run(run_name="reagentai_session") + logger.info(f"MLflow tracking {'enabled' if run_id else 'disabled'}") + + # Log system information and configuration parameters + if tracker.mlflow_enabled: + import platform + import sys + + # Log system info as tags + tracker.set_tags( + { + "python_version": sys.version, + "platform": platform.platform(), + "application": "ReagentAI", + } + ) + + # Log configuration parameters + tracker.log_params( + { + "log_to_file": os.environ.get("LOG_TO_FILE", "True"), + "app_version": "0.1.0", # Could be pulled from a version file + } + ) + main_agent = create_main_agent() - app = create_gradio_app(main_agent) - app.launch(server_name="0.0.0.0") + # Pass the MLflow tracker to the Gradio app + app = create_gradio_app(main_agent, mlflow_tracker=tracker) + + # Launch the application + try: + app.launch(server_name="0.0.0.0") + finally: + # End the MLflow run when the application exits + if tracker.mlflow_enabled: + tracker.end_run() + logger.info("MLflow tracking session ended") diff --git a/src/reagentai/ui/app.py b/src/reagentai/ui/app.py index 32b9669..0549962 100644 --- a/src/reagentai/ui/app.py +++ b/src/reagentai/ui/app.py @@ -74,7 +74,7 @@ def add_user_message_to_history( def handle_bot_response( - chat_history: ChatHistory, llm_client: MainAgent + chat_history: ChatHistory, llm_client: MainAgent, mlflow_tracker=None ) -> tuple[ChatHistory, int]: """ Gets LLM response, updates chat history and token usage. @@ -83,6 +83,20 @@ def handle_bot_response( response: list[ChatMessage] = llm_client.respond(user_query) chat_history.extend(response) token_used: int = llm_client.get_token_usage() + + # Log metrics to MLflow + if mlflow_tracker and mlflow_tracker.mlflow_enabled: + mlflow_tracker.log_metrics( + {"token_usage": token_used, "conversation_length": len(chat_history)} + ) + + # Log user query as param for tracking purposes + mlflow_tracker.log_params( + { + f"query_{len(chat_history)}": user_query[:100] # Truncate long queries + } + ) + return chat_history, token_used @@ -96,12 +110,17 @@ def handle_clear_chat(llm_client: MainAgent) -> tuple[list[None], Literal[0]]: return [], 0 -def handle_model_change(model_name: str, llm_client: MainAgent) -> None: +def handle_model_change(model_name: str, llm_client: MainAgent, mlflow_tracker=None) -> None: """ Sets the new LLM model in the client. """ llm_client.set_model(model_name) + # Log model change to MLflow + if mlflow_tracker and mlflow_tracker.mlflow_enabled: + mlflow_tracker.log_params({"llm_model": model_name}) + mlflow_tracker.set_tags({"model_changed": "true"}) + def re_enable_chat_input() -> gr.MultimodalTextbox: """ @@ -111,7 +130,7 @@ def re_enable_chat_input() -> gr.MultimodalTextbox: # Main App Creation Function -def create_gradio_app(llm_client: MainAgent) -> gr.Blocks: +def create_gradio_app(llm_client: MainAgent, mlflow_tracker=None) -> gr.Blocks: with gr.Blocks( theme=gr.themes.Origin(), ) as demo: @@ -131,7 +150,9 @@ def create_gradio_app(llm_client: MainAgent) -> gr.Blocks: inputs=[chatbot_display, chat_input], outputs=[chatbot_display, chat_input], ).then( - fn=functools.partial(handle_bot_response, llm_client=llm_client), + fn=functools.partial( + handle_bot_response, llm_client=llm_client, mlflow_tracker=mlflow_tracker + ), inputs=chatbot_display, outputs=[chatbot_display, token_usage_display], api_name="bot_response", @@ -145,7 +166,9 @@ def create_gradio_app(llm_client: MainAgent) -> gr.Blocks: ) llm_model_dropdown.change( - fn=functools.partial(handle_model_change, llm_client=llm_client), + fn=functools.partial( + handle_model_change, llm_client=llm_client, mlflow_tracker=mlflow_tracker + ), inputs=llm_model_dropdown, outputs=[], ) diff --git a/tests/test_reagentai.py b/tests/test_reagentai.py new file mode 100644 index 0000000..2198f4a --- /dev/null +++ b/tests/test_reagentai.py @@ -0,0 +1,173 @@ +import os +import sys +import tempfile +from unittest.mock import MagicMock, patch + +import pytest + +from src.reagentai.common.mlflow_tracking import MLflowTracker + + +class TestReAgentAI: + """End-to-end tests for ReAgentAI application.""" + + @pytest.fixture(scope="class") + def mlflow_tracker(self): + """Create a MLflowTracker for testing.""" + # Use a temporary directory as a valid file URI + temp_dir = tempfile.mkdtemp() + tracking_uri = f"file://{temp_dir}" + os.environ["MLFLOW_TRACKING_URI"] = tracking_uri + tracker = MLflowTracker(experiment_name="test_experiment") + yield tracker + # Clean up + tracker.end_run() + if "MLFLOW_TRACKING_URI" in os.environ: + del os.environ["MLFLOW_TRACKING_URI"] + + def test_mlflow_tracker_initialization(self): + """Test MLflowTracker initialization with different configurations.""" + # Create a temporary directory for a valid mlflow file URI + temp_dir = tempfile.mkdtemp() + valid_uri = f"file://{temp_dir}" + + # Test with valid tracking URI + os.environ["MLFLOW_TRACKING_URI"] = valid_uri + with patch("mlflow.set_tracking_uri") as mock_set_uri: + with patch("mlflow.get_experiment_by_name") as mock_get_exp: + # Set up the mock to return a valid experiment + mock_exp = MagicMock() + mock_exp.experiment_id = "test-exp-id" + mock_get_exp.return_value = mock_exp + + tracker = MLflowTracker() + assert tracker.mlflow_enabled is True + assert tracker.tracking_uri == valid_uri + mock_set_uri.assert_called_once_with(valid_uri) + + # Test without tracking URI + if "MLFLOW_TRACKING_URI" in os.environ: + del os.environ["MLFLOW_TRACKING_URI"] + tracker = MLflowTracker() + assert tracker.mlflow_enabled is False + assert tracker.tracking_uri == "" + + def test_mlflow_tracker_lifecycle(self): + """Test the full lifecycle of MLflowTracker with patching at the right level.""" + # Create a temporary directory for a valid mlflow file URI + temp_dir = tempfile.mkdtemp() + valid_uri = f"file://{temp_dir}" + os.environ["MLFLOW_TRACKING_URI"] = valid_uri + + # Define a class to simulate the MLflow implementation + class MockMLflow: + @staticmethod + def set_tracking_uri(uri): + pass + + @staticmethod + def get_experiment_by_name(name): + mock_exp = MagicMock() + mock_exp.experiment_id = "test-exp-id" + return mock_exp + + @staticmethod + def create_experiment(name): + return "new-exp-id" + + @staticmethod + def start_run(experiment_id=None, run_name=None): + mock_run = MagicMock() + mock_run.info.run_id = "test-run-id" + return mock_run + + @staticmethod + def end_run(): + pass + + @staticmethod + def log_params(params): + pass + + @staticmethod + def log_metrics(metrics, step=None): + pass + + @staticmethod + def log_artifact(local_path): + pass + + @staticmethod + def set_tags(tags): + pass + + # Patch the entire mlflow module with our MockMLflow + with patch.object( + sys.modules["src.reagentai.common.mlflow_tracking"], "mlflow", MockMLflow + ): + # Now initialize the tracker with our mocked MLflow + tracker = MLflowTracker(experiment_name="test_experiment") + assert tracker.mlflow_enabled is True + + # Spy on the methods to verify they're called + with patch.object( + MockMLflow, "start_run", wraps=MockMLflow.start_run + ) as mock_start_run: + run_id = tracker.start_run(run_name="test_run") + assert run_id == "test-run-id" + mock_start_run.assert_called_once_with( + experiment_id="test-exp-id", run_name="test_run" + ) + + # Test log_params + with patch.object( + MockMLflow, "log_params", wraps=MockMLflow.log_params + ) as mock_log_params: + params = {"param1": "value1", "param2": 42} + tracker.log_params(params) + mock_log_params.assert_called_once_with(params) + + # Test log_metrics + with patch.object( + MockMLflow, "log_metrics", wraps=MockMLflow.log_metrics + ) as mock_log_metrics: + metrics = {"metric1": 0.95, "metric2": 0.87} + tracker.log_metrics(metrics) + mock_log_metrics.assert_called_once_with(metrics, step=None) + + # Test log_artifact + with patch.object( + MockMLflow, "log_artifact", wraps=MockMLflow.log_artifact + ) as mock_log_artifact: + test_file = "test_artifact.txt" + tracker.log_artifact(test_file) + mock_log_artifact.assert_called_once_with(test_file) + + # Test set_tags + with patch.object(MockMLflow, "set_tags", wraps=MockMLflow.set_tags) as mock_set_tags: + tags = {"tag1": "value1", "tag2": "value2"} + tracker.set_tags(tags) + mock_set_tags.assert_called_once_with(tags) + + # Test end_run + with patch.object(MockMLflow, "end_run", wraps=MockMLflow.end_run) as mock_end_run: + tracker.end_run() + mock_end_run.assert_called_once() + + def test_handle_errors_gracefully(self): + """Test that MLflowTracker handles errors gracefully.""" + # Use an invalid URI to trigger error handling + os.environ["MLFLOW_TRACKING_URI"] = "invalid://uri" + + # Should not raise an exception even with invalid URI + tracker = MLflowTracker() + assert tracker.mlflow_enabled is False + + # These should not raise exceptions + tracker.start_run() + tracker.log_params({"test": "value"}) + tracker.log_metrics({"accuracy": 0.95}) + tracker.end_run() + + if "MLFLOW_TRACKING_URI" in os.environ: + del os.environ["MLFLOW_TRACKING_URI"] diff --git a/uv.lock b/uv.lock index cdf21d6..3538757 100644 --- a/uv.lock +++ b/uv.lock @@ -2,8 +2,10 @@ version = 1 revision = 2 requires-python = ">=3.10, <3.12" resolution-markers = [ - "python_full_version >= '3.11'", - "python_full_version < '3.11'", + "python_full_version >= 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