feat(rlsapi): add v1 /infer endpoint module #902

major · 2025-12-10T12:56:16Z

Description

Create the endpoint structure for stateless inference requests from the RHEL Lightspeed Command Line Assistant (CLA).

POST /infer endpoint with RlsapiV1InferRequest/Response models
Authentication via get_auth_dependency()
Authorization via @authorize(Action.RLSAPI_V1_INFER)
OpenAPI response schemas for 200/401/403/422
Unit tests for endpoint functionality

LLM integration will be wired up in a follow-up PR.

Type of change

Tools used to create PR

Assisted-by: Claude

Related Tickets & Documents

Related Issue # RSPEED-2229
Closes #

Checklist before requesting a review

I have performed a self-review of my code.
PR has passed all pre-merge test jobs.
If it is a core feature, I have added thorough tests.

Testing

Existing unit tests should cover this code.

Summary by CodeRabbit

New Features
- Added a stateless /infer API endpoint with authorization, request tracking, and a placeholder response; each call returns a unique request_id and logs processing details.
Tests
- Added unit tests for minimal and full-context requests, response shape/content, unique request_id, and validation for empty/whitespace questions.

_{✏️ Tip: You can customize this high-level summary in your review settings.}

coderabbitai · 2025-12-10T12:56:26Z

Walkthrough

Adds a new FastAPI module exposing a stateless POST /infer for RLSAPI v1 with auth enforcement, request_id generation via get_suid, logging of input metadata, OpenAPI response mappings, and unit tests validating minimal/full-context requests and validation behavior.

Changes

Cohort / File(s)	Summary
RLSAPI v1 Endpoint Implementation `src/app/endpoints/rlsapi_v1.py`	New APIRouter `router` exposing POST `/infer`. Implements `infer_endpoint(infer_request, auth)` that enforces authentication via `get_auth_dependency()` and an authorization decorator, generates a `request_id` with `get_suid`, logs input-source length and processing start, returns a `RlsapiV1InferResponse` with placeholder `data.text` and `data.request_id`, and exposes `infer_responses` mapping for 200/401/403/422.
RLSAPI v1 Unit Tests `tests/unit/app/endpoints/test_rlsapi_v1.py`	New unit tests that mock auth and call the handler: minimal request, full-context request (stdin, attachments, terminal, systeminfo), uniqueness of generated `request_id`s, and parameterized validation tests for empty/whitespace questions. Asserts response type, presence of `data.text`, and valid SUID format for `data.request_id`.

Estimated code review effort

🎯 3 (Moderate) | ⏱️ ~20 minutes

Verify correct wiring of get_auth_dependency() and the authorization decorator with AuthTuple.
Confirm infer_responses OpenAPI mappings align with response models and status codes.
Review tests for coverage and consider adding negative-path tests for 401/403/422.

Possibly related PRs

Add rlsapi v1 infer request/response models #896 — Adds the RlsapiV1 request/response Pydantic models used by this endpoint.

Suggested reviewers

tisnik

Pre-merge checks and finishing touches

✅ Passed checks (3 passed)

Check name	Status	Explanation
Description Check	✅ Passed	Check skipped - CodeRabbit’s high-level summary is enabled.
Title check	✅ Passed	The title accurately summarizes the main change: adding a new v1 /infer endpoint module to the rlsapi, which is exactly what the changeset introduces.
Docstring Coverage	✅ Passed	Docstring coverage is 100.00% which is sufficient. The required threshold is 80.00%.

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Post copyable unit tests in a comment

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src/**/*.py

📄 CodeRabbit inference engine (CLAUDE.md)

src/**/*.py: Use absolute imports for internal modules in LCS project (e.g., from auth import get_auth_dependency)
All modules must start with descriptive docstrings explaining their purpose
Use logger = logging.getLogger(__name__) pattern for module logging
All functions must include complete type annotations for parameters and return types, using modern syntax (str | int) and Optional[Type] or Type | None
All functions must have docstrings with brief descriptions following Google Python docstring conventions
Function names must use snake_case with descriptive, action-oriented names (get_, validate_, check_)
Avoid in-place parameter modification anti-patterns; return new data structures instead of modifying input parameters
Use async def for I/O operations and external API calls
All classes must include descriptive docstrings explaining their purpose following Google Python docstring conventions
Class names must use PascalCase with descriptive names and standard suffixes: Configuration for config classes, Error/Exception for exceptions, Resolver for strategy patterns, Interface for abstract base classes
Abstract classes must use ABC with @abstractmethod decorators
Include complete type annotations for all class attributes in Python classes
Use import logging and module logger pattern with standard log levels: debug, info, warning, error

Files:

src/app/endpoints/rlsapi_v1.py

src/app/endpoints/**/*.py

📄 CodeRabbit inference engine (CLAUDE.md)

Use FastAPI HTTPException with appropriate status codes for API endpoint error handling

Files:

src/app/endpoints/rlsapi_v1.py

src/**/{client,app/endpoints/**}.py

📄 CodeRabbit inference engine (CLAUDE.md)

Handle APIConnectionError from Llama Stack in integration code

Files:

src/app/endpoints/rlsapi_v1.py

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🔇 Additional comments (5)

src/app/endpoints/rlsapi_v1.py (5)
1-26: LGTM! Module structure follows guidelines.

The module docstring, absolute imports, logger pattern, and router setup all adhere to the coding guidelines.

29-36: LGTM! Response mapping is comprehensive.

The OpenAPI response schemas correctly document all expected HTTP status codes (200, 401, 403, 422) for this endpoint.

39-60: LGTM! Function signature and auth handling are correct.

Complete type annotations, Google-style docstring, and appropriate auth dependency usage all follow the coding guidelines. The _ = auth assignment correctly indicates the variable is intentionally unused since auth enforcement is handled by FastAPI dependencies.

65-65: Privacy issue resolved - user_id no longer logged.

The previous review concern about logging user identifiers has been addressed. The INFO-level log now only includes the request_id for tracing, which aligns with privacy/compliance guidelines.

71-82: Verify APIConnectionError handling will be added with LLM integration.

The placeholder response is appropriate for this PR. However, when the LLM integration is implemented (as noted in line 71), ensure you add proper error handling for APIConnectionError from Llama Stack, as required by the coding guidelines for endpoint files.

Consider wrapping the LLM call in a try-except block:
try:
    # LLM call here
    response_text = await llm_client.generate(...)
except APIConnectionError as e:
    logger.error("LLM connection failed for request %s: %s", request_id, e)
    raise HTTPException(status_code=503, detail="Service temporarily unavailable")

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openshift-ci · 2025-12-10T12:56:27Z

Hi @major. Thanks for your PR.

I'm waiting for a github.com member to verify that this patch is reasonable to test. If it is, they should reply with /ok-to-test on its own line. Until that is done, I will not automatically test new commits in this PR, but the usual testing commands by org members will still work. Regular contributors should join the org to skip this step.

Once the patch is verified, the new status will be reflected by the ok-to-test label.

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coderabbitai

Actionable comments posted: 0

🧹 Nitpick comments (1)

src/app/endpoints/rlsapi_v1.py (1)
1-27: Align logger with module-level __name__ pattern

The module docstring and imports look good, but the logger is initialized with a hard-coded name "app.endpoints.handlers" instead of __name__. To follow the standard pattern and avoid surprises if this module is moved or renamed, consider:
-logger = logging.getLogger("app.endpoints.handlers")
+logger = logging.getLogger(__name__)
As per coding guidelines, the logger = logging.getLogger(__name__) pattern is preferred.

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tests/{unit,integration}/**/*.py

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tests/{unit,integration}/**/*.py: Use pytest for all unit and integration tests; do not use unittest framework
Unit tests must achieve 60% code coverage; integration tests must achieve 10% coverage

Files:

tests/unit/app/endpoints/test_rlsapi_v1.py

tests/**/*.py

📄 CodeRabbit inference engine (CLAUDE.md)

Use pytest-mock with AsyncMock objects for mocking in tests

Files:

tests/unit/app/endpoints/test_rlsapi_v1.py

src/**/*.py

📄 CodeRabbit inference engine (CLAUDE.md)

src/**/*.py: Use absolute imports for internal modules in LCS project (e.g., from auth import get_auth_dependency)
All modules must start with descriptive docstrings explaining their purpose
Use logger = logging.getLogger(__name__) pattern for module logging
All functions must include complete type annotations for parameters and return types, using modern syntax (str | int) and Optional[Type] or Type | None
All functions must have docstrings with brief descriptions following Google Python docstring conventions
Function names must use snake_case with descriptive, action-oriented names (get_, validate_, check_)
Avoid in-place parameter modification anti-patterns; return new data structures instead of modifying input parameters
Use async def for I/O operations and external API calls
All classes must include descriptive docstrings explaining their purpose following Google Python docstring conventions
Class names must use PascalCase with descriptive names and standard suffixes: Configuration for config classes, Error/Exception for exceptions, Resolver for strategy patterns, Interface for abstract base classes
Abstract classes must use ABC with @abstractmethod decorators
Include complete type annotations for all class attributes in Python classes
Use import logging and module logger pattern with standard log levels: debug, info, warning, error

Files:

src/app/endpoints/rlsapi_v1.py

src/app/endpoints/**/*.py

📄 CodeRabbit inference engine (CLAUDE.md)

Use FastAPI HTTPException with appropriate status codes for API endpoint error handling

Files:

src/app/endpoints/rlsapi_v1.py

src/**/{client,app/endpoints/**}.py

📄 CodeRabbit inference engine (CLAUDE.md)

Handle APIConnectionError from Llama Stack in integration code

Files:

src/app/endpoints/rlsapi_v1.py

🧬 Code graph analysis (1)

src/app/endpoints/rlsapi_v1.py (6)

src/authentication/__init__.py (1)

get_auth_dependency (21-72)

src/authorization/middleware.py (1)

authorize (111-122)

src/models/config.py (1)

Action (755-808)

src/models/responses.py (3)

ForbiddenResponse (1382-1529)

UnauthorizedResponse (1298-1379)

UnprocessableEntityResponse (1623-1668)

src/models/rlsapi/requests.py (2)

RlsapiV1InferRequest (123-200)

get_input_source (178-200)

src/models/rlsapi/responses.py (2)

RlsapiV1InferData (9-26)

RlsapiV1InferResponse (29-53)

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🔇 Additional comments (6)

tests/unit/app/endpoints/test_rlsapi_v1.py (4)

1-21: Good use of pytest and clear setup

The module-level setup (docstring, imports, MOCK_AUTH) is clean and aligns with the pytest + pytest-mock guidelines. The explicit AuthTuple type and static auth fixture make the tests easy to follow and reuse.

23-35: Minimal request test is focused and validates UUID semantics

test_infer_minimal_request neatly covers the happy path with the minimal required payload and additionally verifies that request_id parses as a real UUID, not just a non-empty string. This is a solid behavioral contract for the endpoint.

37-56: Full-context test effectively exercises get_input_source path

test_infer_full_context_request sensibly constructs a rich RlsapiV1Context (stdin, attachment, terminal, systeminfo), ensuring the endpoint correctly accepts and processes the full shape of the request. Asserting text and non-empty request_id keeps the test robust against future LLM changes while still validating the contract.

58-67: Unique request ID behavior is well-covered

test_infer_generates_unique_request_ids is a concise way to enforce per-call uniqueness for request_id given identical inputs, which matches how you’re generating UUIDs server-side. This should catch accidental reuse or caching bugs going forward.

src/app/endpoints/rlsapi_v1.py (2)

29-36: Reusing shared OpenAPI response schemas is a solid approach

infer_responses correctly wires the endpoint into the shared UnauthorizedResponse, ForbiddenResponse, and UnprocessableEntityResponse OpenAPI helpers, keeping the API surface consistent with the rest of the stack and centralizing error schema definitions.

39-84: Endpoint implementation is clean, stateless, and matches the models/tests

The /infer route is well-structured: async, fully typed, guarded by get_auth_dependency() and @authorize(Action.RLSAPI_V1_INFER), generates a per-call UUID request_id, logs with user context, and uses RlsapiV1InferRequest.get_input_source() before returning a typed RlsapiV1InferResponse. The placeholder response text is clearly marked and should be straightforward to replace with real LLM integration later without changing the external contract.

coderabbitai

Actionable comments posted: 1

🧹 Nitpick comments (1)

src/app/endpoints/rlsapi_v1.py (1)
45-58: Align docstring with current placeholder behavior

The docstring says the endpoint “returns an LLM-generated response”, but the implementation currently returns a static placeholder message until LLM integration is added. Consider updating the docstring to match current behavior (and adjust again once the LLM call is wired) to avoid confusion.

For example:
-    Accepts a question with optional context (stdin, attachments, terminal output,
-    system info) and returns an LLM-generated response.
+    Accepts a question with optional context (stdin, attachments, terminal output,
+    system info) and returns a placeholder response. LLM integration will be
+    added in a subsequent update.

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src/**/*.py

📄 CodeRabbit inference engine (CLAUDE.md)

src/**/*.py: Use absolute imports for internal modules in LCS project (e.g., from auth import get_auth_dependency)
All modules must start with descriptive docstrings explaining their purpose
Use logger = logging.getLogger(__name__) pattern for module logging
All functions must include complete type annotations for parameters and return types, using modern syntax (str | int) and Optional[Type] or Type | None
All functions must have docstrings with brief descriptions following Google Python docstring conventions
Function names must use snake_case with descriptive, action-oriented names (get_, validate_, check_)
Avoid in-place parameter modification anti-patterns; return new data structures instead of modifying input parameters
Use async def for I/O operations and external API calls
All classes must include descriptive docstrings explaining their purpose following Google Python docstring conventions
Class names must use PascalCase with descriptive names and standard suffixes: Configuration for config classes, Error/Exception for exceptions, Resolver for strategy patterns, Interface for abstract base classes
Abstract classes must use ABC with @abstractmethod decorators
Include complete type annotations for all class attributes in Python classes
Use import logging and module logger pattern with standard log levels: debug, info, warning, error

Files:

src/app/endpoints/rlsapi_v1.py

src/app/endpoints/**/*.py

📄 CodeRabbit inference engine (CLAUDE.md)

Use FastAPI HTTPException with appropriate status codes for API endpoint error handling

Files:

src/app/endpoints/rlsapi_v1.py

src/**/{client,app/endpoints/**}.py

📄 CodeRabbit inference engine (CLAUDE.md)

Handle APIConnectionError from Llama Stack in integration code

Files:

src/app/endpoints/rlsapi_v1.py

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🔇 Additional comments (2)

src/app/endpoints/rlsapi_v1.py (2)

1-36: Good module setup and OpenAPI response wiring

Docstring, absolute imports, logger pattern, APIRouter usage, and the typed infer_responses mapping all look consistent with the project guidelines and FastAPI conventions. No issues here.

69-84: Placeholder implementation is clean and type-safe; ensure APIConnectionError handling when adding LLM integration

The endpoint correctly combines input sources, generates a request ID, and returns a properly typed response. When adding the actual LLM call, handle APIConnectionError from Llama Stack by translating it to an appropriate HTTPException status code per the endpoint guidelines.

src/app/endpoints/rlsapi_v1.py

coderabbitai

Actionable comments posted: 0

🧹 Nitpick comments (2)

tests/unit/app/endpoints/test_rlsapi_v1.py (2)

36-55: LGTM! Full context test provides good coverage.

The test validates the endpoint handles full context data (stdin, attachments, terminal, systeminfo) without errors. Since LLM integration is deferred, the placeholder response approach is appropriate.

Optional enhancement for future: Once LLM integration is added, consider verifying that the context fields influence the response or are logged appropriately.

1-66: Consider adding error case tests for better coverage.

The current tests provide solid happy-path coverage. To meet the 60% unit test coverage guideline, consider adding tests for:

Invalid requests (empty/whitespace-only questions)

Authorization failures (if testable at this layer)

Response schema validation

These additions would strengthen the test suite and help ensure edge cases are handled correctly.

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tests/{unit,integration}/**/*.py

📄 CodeRabbit inference engine (CLAUDE.md)

tests/{unit,integration}/**/*.py: Use pytest for all unit and integration tests; do not use unittest framework
Unit tests must achieve 60% code coverage; integration tests must achieve 10% coverage

Files:

tests/unit/app/endpoints/test_rlsapi_v1.py

tests/**/*.py

📄 CodeRabbit inference engine (CLAUDE.md)

Use pytest-mock with AsyncMock objects for mocking in tests

Files:

tests/unit/app/endpoints/test_rlsapi_v1.py

src/**/*.py

📄 CodeRabbit inference engine (CLAUDE.md)

src/**/*.py: Use absolute imports for internal modules in LCS project (e.g., from auth import get_auth_dependency)
All modules must start with descriptive docstrings explaining their purpose
Use logger = logging.getLogger(__name__) pattern for module logging
All functions must include complete type annotations for parameters and return types, using modern syntax (str | int) and Optional[Type] or Type | None
All functions must have docstrings with brief descriptions following Google Python docstring conventions
Function names must use snake_case with descriptive, action-oriented names (get_, validate_, check_)
Avoid in-place parameter modification anti-patterns; return new data structures instead of modifying input parameters
Use async def for I/O operations and external API calls
All classes must include descriptive docstrings explaining their purpose following Google Python docstring conventions
Class names must use PascalCase with descriptive names and standard suffixes: Configuration for config classes, Error/Exception for exceptions, Resolver for strategy patterns, Interface for abstract base classes
Abstract classes must use ABC with @abstractmethod decorators
Include complete type annotations for all class attributes in Python classes
Use import logging and module logger pattern with standard log levels: debug, info, warning, error

Files:

src/app/endpoints/rlsapi_v1.py

src/app/endpoints/**/*.py

📄 CodeRabbit inference engine (CLAUDE.md)

Use FastAPI HTTPException with appropriate status codes for API endpoint error handling

Files:

src/app/endpoints/rlsapi_v1.py

src/**/{client,app/endpoints/**}.py

📄 CodeRabbit inference engine (CLAUDE.md)

Handle APIConnectionError from Llama Stack in integration code

Files:

src/app/endpoints/rlsapi_v1.py

🧬 Code graph analysis (1)

tests/unit/app/endpoints/test_rlsapi_v1.py (5)

src/app/endpoints/rlsapi_v1.py (1)

infer_endpoint (41-82)

src/models/rlsapi/requests.py (5)

RlsapiV1Attachment (8-25)

RlsapiV1Context (89-120)

RlsapiV1InferRequest (123-200)

RlsapiV1SystemInfo (42-66)

RlsapiV1Terminal (28-39)

src/models/rlsapi/responses.py (1)

RlsapiV1InferResponse (29-53)

tests/unit/utils/auth_helpers.py (1)

mock_authorization_resolvers (8-26)

src/utils/suid.py (1)

check_suid (19-98)

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🔇 Additional comments (9)

tests/unit/app/endpoints/test_rlsapi_v1.py (4)

1-17: LGTM! Clean imports and module structure.

The module docstring is descriptive, and all imports follow the absolute import pattern required by the coding guidelines.

19-19: LGTM! Well-defined test constant.

The MOCK_AUTH constant provides a clean, reusable authentication fixture for the tests.

22-34: LGTM! Solid minimal request test.

The test properly validates the basic happy path: response structure, text presence, and request_id validity using check_suid. Type annotations and docstring follow guidelines.

57-66: LGTM! Important uniqueness validation.

This test ensures each request gets a unique identifier, which is critical for request tracing and debugging. Clean and focused test case.

src/app/endpoints/rlsapi_v1.py (5)

1-23: LGTM! Excellent module documentation and imports.

The module docstring clearly describes the purpose, and all imports follow the absolute import pattern required by the coding guidelines.

25-26: LGTM! Proper logger and router initialization.

Logger follows the required logging.getLogger(__name__) pattern, and the router is appropriately tagged for API organization.

29-36: LGTM! Comprehensive OpenAPI response documentation.

The response schemas properly document all success and error cases (200, 401, 403, 422) with appropriate examples, improving API documentation quality.

39-58: LGTM! Excellent function signature and documentation.

The endpoint is properly decorated with routing and authorization, includes complete type annotations, and has a comprehensive Google-style docstring that clearly explains its purpose, parameters, and return value.

59-82: LGTM! Clean implementation with privacy concern addressed.

The implementation is well-structured:

Line 65 logs only the request_id at INFO level, addressing the privacy concern from the previous review about not logging user identifiers.

Request tracking via get_suid() is appropriate for tracing.

Placeholder response with clear NOTE comment is acceptable given the PR objectives (LLM integration deferred to follow-up).

async def is appropriate for future LLM integration even though current implementation is synchronous.

tisnik · 2025-12-10T15:19:25Z

/ok-to-test

@authorize

Create the endpoint structure for stateless inference requests from the RHEL Lightspeed Command Line Assistant (CLA). - POST /infer endpoint with RlsapiV1InferRequest/Response models - Authentication via get_auth_dependency() - Authorization via @authorize(Action.RLSAPI_V1_INFER) - OpenAPI response schemas for 200/401/403/422 - Unit tests for endpoint functionality LLM integration will be wired up in a follow-up PR. Signed-off-by: Major Hayden <major@redhat.com>

tisnik · 2025-12-15T15:26:22Z

/ok-to-test

tisnik

it looks ok, thank you

openshift-ci bot added the needs-ok-to-test label Dec 10, 2025

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major force-pushed the rlsapi-v1 branch from d246799 to b2632c8 Compare December 10, 2025 13:23

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major force-pushed the rlsapi-v1 branch from b2632c8 to d5f0d9f Compare December 10, 2025 13:42

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major force-pushed the rlsapi-v1 branch from d5f0d9f to 4892834 Compare December 10, 2025 15:17

openshift-ci bot added ok-to-test and removed needs-ok-to-test labels Dec 10, 2025

major force-pushed the rlsapi-v1 branch from 4892834 to 3e08f8d Compare December 15, 2025 14:53

tisnik approved these changes Dec 15, 2025

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tisnik merged commit 2a2a30f into lightspeed-core:main Dec 15, 2025
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major deleted the rlsapi-v1 branch December 15, 2025 16:57

This was referenced Dec 15, 2025

feat(rlsapi): implement LLM integration for v1 /infer endpoint #916

Merged

RSPEED-2229: Add rlsapi v1 endpoint registration and CLA documentation #928

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test(rlsapi): add initial e2e test for v1 infer endpoint #929

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This was referenced Jan 12, 2026

LCORE-1169: Up to date OpenAPI documentation #980

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fix(rlsapi): add error handling, metrics, and system context #1006

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major commented Dec 10, 2025 • edited by coderabbitai bot Loading Uh oh! There was an error while loading. Please reload this page.

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coderabbitai bot commented Dec 10, 2025 • edited Loading Uh oh! There was an error while loading. Please reload this page.

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openshift-ci bot commented Dec 10, 2025

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tisnik commented Dec 10, 2025

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tisnik commented Dec 15, 2025

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major commented Dec 10, 2025 •

edited by coderabbitai bot

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coderabbitai bot commented Dec 10, 2025 •

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