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Pull Request Overview
This PR adds MLflow support to the project by integrating a dedicated MLflow service into the Docker setup and wiring experiment tracking into both the retrosynthesis module and the LLM agent. Key changes include:
- Adding MLflowTracker usage in retrosynthesis and client code for logging parameters, metrics, and artifacts.
- Integrating MLflow support into the main agent and updating Docker/Docker Compose to expose the MLflow UI.
- Updating project documentation and dependencies to reflect the new MLflow integration.
Reviewed Changes
Copilot reviewed 9 out of 9 changed files in this pull request and generated 2 comments.
Show a summary per file
| File | Description |
|---|---|
| src/reagentai/tools/retrosynthesis.py | Adds MLflowTracker initialization and logging around retrosynthesis workflow. |
| src/reagentai/common/mlflow_tracking.py | Implements the MLflowTracker abstraction for experiment tracking. |
| src/reagentai/common/client.py | Injects MLflowTracker into LLMClient and logs interactions and model changes. |
| src/reagentai/agents/main/main_agent.py | Integrates MLflow tracking with the main agent by sharing a tracker instance. |
| pyproject.toml | Adds the MLflow dependency. |
| docker-compose.yml | Defines the new MLflow service with appropriate port and network configuration. |
| README.md | Updates documentation with usage instructions for MLflow including Docker commands. |
| Dockerfile.mlflow | Provides Docker instructions to run the MLflow server. |
Comments suppressed due to low confidence (1)
src/reagentai/common/client.py:119
- [nitpick] The commented-out code for generating the MLflow run name could be removed to improve code clarity if it is no longer needed.
// commented out hash-based run name generation
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Closed, functionality in #14 |
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This pull request introduces the following updates to the project's Docker setup:
Addition of MLflow Service:
mlflowservice in the file.docker-compose.ymlDockerfile.mlflow5000for accessing the MLflow server UI.Integration with Reagent AI Service:
reagentaiservice in the file.docker-compose.ymlreagentaiandmlflowservices using the .mlflow-networkMLFLOW_TRACKING_URICustom Network Configuration:
mlflow-network