[AINode] Concurrent inference bug fix

[CRZbulabula]

This PR improves the core codes of AINode. We should distinguish the usage of model_id and model_type, thus we pass model_info.

[Copilot]

Pull Request Overview

This PR fixes a concurrent inference bug in AINode by refactoring how model information is passed and used throughout the system. The key change is transitioning from passing model_id strings to passing complete ModelInfo objects, which properly distinguishes between model_id and model_type.

Key changes:

• Removed model validation and information retrieval from the analysis phase, deferring it to runtime
• Changed pool scheduler and inference pool to accept ModelInfo objects instead of model_id strings
• Fixed model type checking to use model_type from ModelInfo instead of comparing model_id directly

Reviewed Changes

Copilot reviewed 17 out of 17 changed files in this pull request and generated 4 comments.

Show a summary per file

File	Description
ForecastTableFunction.java	Removed early model validation and replaced maxInputLength with Integer.MAX_VALUE
ModelInferenceDescriptor.java	Changed constructor to remove ModelInformation parameter, making it mutable
ModelFetcher.java	Simplified model fetching to only return AINode endpoint without model information
AnalyzeVisitor.java	Commented out window size validation checks
ModelInfo.java	Removed serialization of model information in response
ModelManager.java	Simplified getModelInfo to always return first registered AINode
GetModelInfoResp.java	Removed model information serialization fields
model_storage.py	Added get_model_info method to retrieve model information
model_manager.py	Added get_model_info method wrapper
inference_manager.py	Changed to use model_type from ModelInfo instead of comparing model_id
basic_pool_scheduler.py	Changed to accept and use ModelInfo objects instead of model_id strings
abstract_pool_scheduler.py	Updated interface to accept ModelInfo instead of model_id
pool_group.py	Added get_running_pool_count method to count running pools
pool_controller.py	Updated to pass ModelInfo objects and use model_type for comparisons
inference_request_pool.py	Changed to store and use ModelInfo instead of model_id, fixed output tensor dimension
AINodeInferenceSQLIT.java	Commented out test methods
AINodeConcurrentInferenceIT.java	Added test annotations and fixed SQL column name from timestamp to time

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[Copilot]

The allocation result for the unloaded model is set to 0 after already being computed in the conditional expression. This overwrites the computed value and may cause incorrect behavior. Lines 156-157 should be removed as the logic at lines 147-155 already handles this case correctly.

Suggested change

	if len(existing_model_infos) > 0:
	allocation_result[model_info.model_id] = 0

[CRZbulabula]

U R wrong

[codecov]

Codecov Report

❌ Patch coverage is 8.33333% with 11 lines in your changes missing coverage. Please review.
✅ Project coverage is 38.67%. Comparing base (2a12077) to head (1c09df3).
⚠️ Report is 6 commits behind head on master.

Files with missing lines	Patch %	Lines
.../apache/iotdb/confignode/manager/ModelManager.java	0.00%	8 Missing ⚠️
...otdb/db/queryengine/plan/analyze/ModelFetcher.java	0.00%	2 Missing ⚠️
...plan/parameter/model/ModelInferenceDescriptor.java	0.00%	1 Missing ⚠️

Additional details and impacted files

@@             Coverage Diff              @@
##             master   #16595      +/-   ##
============================================
+ Coverage     38.66%   38.67%   +0.01%     
  Complexity      207      207              
============================================
  Files          4937     4937              
  Lines        327011   326949      -62     
  Branches      41496    41495       -1     
============================================
+ Hits         126434   126448      +14     
+ Misses       200577   200501      -76     

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[sonarqubecloud]

Quality Gate passed

Issues
9 New issues
0 Accepted issues

Measures
0 Security Hotspots
0.0% Coverage on New Code
0.0% Duplication on New Code

See analysis details on SonarQube Cloud