feat: add stateless MCP forecasting service - #525
Closed
codeingnoob wants to merge 1 commit into
Closed
codeingnoob wants to merge 1 commit into
codeingnoob wants to merge 1 commit into
Conversation
|
Thanks for your pull request! It looks like this may be your first contribution to a Google open source project. Before we can look at your pull request, you'll need to sign a Contributor License Agreement (CLA). View this failed invocation of the CLA check for more information. For the most up to date status, view the checks section at the bottom of the pull request. |
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
Add this suggestion to a batch that can be applied as a single commit.This suggestion is invalid because no changes were made to the code.Suggestions cannot be applied while the pull request is closed.Suggestions cannot be applied while viewing a subset of changes.Only one suggestion per line can be applied in a batch.Add this suggestion to a batch that can be applied as a single commit.Applying suggestions on deleted lines is not supported.You must change the existing code in this line in order to create a valid suggestion.Outdated suggestions cannot be applied.This suggestion has been applied or marked resolved.Suggestions cannot be applied from pending reviews.Suggestions cannot be applied on multi-line comments.Suggestions cannot be applied while the pull request is queued to merge.Suggestion cannot be applied right now. Please check back later.
Adds a stateless FastMCP forecasting service with dataset inspection and an atomic forecast workflow that performs aggregation, validation, backtesting, TimesFM inference, and local artifact generation. The connector no longer depends on in-process series IDs and supports idempotent request IDs. Includes unit coverage for dataset inspection, forecast artifacts, and request reuse. Validated with: python -m unittest -v test_forecast_service.py test_forecast_output_path.py.