RHIDP-12952: persist interrupted conversation#1971
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WalkthroughThe PR replaces the static interrupted-response message with a mechanism that accumulates streamed token deltas into ChangesStructured Interrupted Response from Partial Tokens
Sequence Diagram(s)sequenceDiagram
participant Client
participant generate_response / generate_agent_response
participant _process_token / response_generator
participant build_interrupted_response
participant close_open_markdown
participant persist_interrupted_turn
rect rgba(100, 149, 237, 0.5)
note over _process_token / response_generator: Normal streaming
_process_token / response_generator-->Client: token SSE events (chunk_id 0, 1, 2…)
_process_token / response_generator->>generate_response / generate_agent_response: appends partial_tokens, sets next_chunk_id
end
rect rgba(220, 100, 100, 0.5)
note over generate_response / generate_agent_response: asyncio.CancelledError
generate_response / generate_agent_response->>build_interrupted_response: partial_tokens
build_interrupted_response->>close_open_markdown: joined text
close_open_markdown-->>build_interrupted_response: repair suffix
build_interrupted_response-->>generate_response / generate_agent_response: (full_text, emit_suffix)
generate_response / generate_agent_response->>persist_interrupted_turn: llm_response = full_text
generate_response / generate_agent_response-->>Client: final token SSE event (emit_suffix, next_chunk_id)
end
Estimated code review effort🎯 3 (Moderate) | ⏱️ ~25 minutes Possibly related PRs
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Actionable comments posted: 2
🤖 Prompt for all review comments with AI agents
Verify each finding against current code. Fix only still-valid issues, skip the
rest with a brief reason, keep changes minimal, and validate.
Inline comments:
In `@src/app/endpoints/streaming_query.py`:
- Around line 637-640: The build_interrupted_response call at line 637 relies
solely on turn_summary.partial_tokens, which may be empty or incomplete if
cancellation occurs after response.output_text.done has populated
turn_summary.llm_response but before all deltas are processed. Modify the
build_interrupted_response call to use turn_summary.llm_response as a fallback
when partial_tokens is empty, ensuring that model output is not lost when
interrupted responses are reconstructed and persisted.
In `@src/utils/markdown_repair.py`:
- Around line 75-90: In the fence closing logic (the elif condition checking
`char == fence_char and len(matched_group) >= fence_len`), add validation to
ensure that any trailing content after the fence marker contains only whitespace
characters (spaces and tabs). Extract the remainder of the line after the
matched fence group and check that it either doesn't exist or contains only
whitespace using a string method like strip() or a regex check. Only allow the
fence to close if this whitespace validation passes, otherwise treat the line as
regular content inside the code block.
🪄 Autofix (Beta)
Fix all unresolved CodeRabbit comments on this PR:
- Push a commit to this branch (recommended)
- Create a new PR with the fixes
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src/app/endpoints/streaming_query.pysrc/constants.pysrc/models/common/turn_summary.pysrc/utils/agents/streaming.pysrc/utils/markdown_repair.pysrc/utils/stream_interrupts.pytests/unit/app/endpoints/test_streaming_query.pytests/unit/utils/agents/test_streaming.pytests/unit/utils/test_markdown_repair.pytests/unit/utils/test_stream_interrupts.py
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🧰 Additional context used
📓 Path-based instructions (5)
src/**/*.py
📄 CodeRabbit inference engine (AGENTS.md)
src/**/*.py: Use absolute imports for internal modules:from authentication import get_auth_dependency
Llama Stack imports: Usefrom llama_stack_client import AsyncLlamaStackClient
Checkconstants.pyfor shared constants before defining new ones
All modules must start with descriptive docstrings explaining purpose
Uselogger = get_logger(__name__)fromlog.pyfor module logging
All functions must have complete type annotations for parameters and return types, use modern syntax (str | int), and include descriptive docstrings
Use snake_case with descriptive, action-oriented names for functions (get_, validate_, check_)
Avoid in-place parameter modification anti-patterns; return new data structures instead of modifying function parameters
Useasync deffor I/O operations and external API calls
Use standard log levels with clear purposes:debug()for diagnostic info,info()for program execution,warning()for unexpected events,error()for serious problems
All classes must have descriptive docstrings explaining purpose and use PascalCase with standard suffixes:Configuration,Error/Exception,Resolver,Interface
Abstract classes must use ABC with@abstractmethoddecorators
Follow Google Python docstring conventions with required sections: Parameters, Returns, Raises, and Attributes for classes
Files:
src/constants.pysrc/models/common/turn_summary.pysrc/utils/markdown_repair.pysrc/utils/stream_interrupts.pysrc/app/endpoints/streaming_query.pysrc/utils/agents/streaming.py
src/constants.py
📄 CodeRabbit inference engine (AGENTS.md)
Use
constants.pyfor shared constants with descriptive comments and type hints usingFinal[type]
Files:
src/constants.py
src/models/**/*.py
📄 CodeRabbit inference engine (AGENTS.md)
Pydantic models must use
@model_validatorand@field_validatorfor validation and complete type annotations for all attributes, avoidingAnytype
Files:
src/models/common/turn_summary.py
tests/**/*.py
📄 CodeRabbit inference engine (AGENTS.md)
tests/**/*.py: Use pytest for all unit and integration tests; do not use unittest
Usepytest.mark.asynciomarker for async tests
Files:
tests/unit/utils/test_markdown_repair.pytests/unit/app/endpoints/test_streaming_query.pytests/unit/utils/agents/test_streaming.pytests/unit/utils/test_stream_interrupts.py
src/app/**/*.py
📄 CodeRabbit inference engine (AGENTS.md)
src/app/**/*.py: FastAPI dependencies: Import fromfastapimodule forAPIRouter,HTTPException,Request,status,Depends
Use FastAPIHTTPExceptionwith appropriate status codes for API endpoints and handleAPIConnectionErrorfrom Llama Stack
Files:
src/app/endpoints/streaming_query.py
🧠 Learnings (3)
📚 Learning: 2026-01-12T10:58:40.230Z
Learnt from: blublinsky
Repo: lightspeed-core/lightspeed-stack PR: 972
File: src/models/config.py:459-513
Timestamp: 2026-01-12T10:58:40.230Z
Learning: In lightspeed-core/lightspeed-stack, for Python files under src/models, when a user claims a fix is done but the issue persists, verify the current code state before accepting the fix. Steps: review the diff, fetch the latest changes, run relevant tests, reproduce the issue, search the codebase for lingering references to the original problem, confirm the fix is applied and not undone by subsequent commits, and validate with local checks to ensure the issue is resolved.
Applied to files:
src/models/common/turn_summary.py
📚 Learning: 2026-02-25T07:46:33.545Z
Learnt from: asimurka
Repo: lightspeed-core/lightspeed-stack PR: 1211
File: src/models/responses.py:8-16
Timestamp: 2026-02-25T07:46:33.545Z
Learning: In the Python codebase, requests.py should use OpenAIResponseInputTool as Tool while responses.py uses OpenAIResponseTool as Tool. This difference is intentional due to differing schemas for input vs output tools in llama-stack-api. Apply this distinction consistently to other models under src/models (e.g., ensure request-related tools use the InputTool variant and response-related tools use the ResponseTool variant). If adding new tools, choose the corresponding InputTool or Tool class based on whether the tool represents input or output, and document the rationale in code comments.
Applied to files:
src/models/common/turn_summary.py
📚 Learning: 2026-04-06T20:18:07.852Z
Learnt from: major
Repo: lightspeed-core/lightspeed-stack PR: 1463
File: src/app/endpoints/rlsapi_v1.py:266-271
Timestamp: 2026-04-06T20:18:07.852Z
Learning: In the lightspeed-stack codebase, within `src/app/endpoints/` inference/MCP endpoints, treat `tools: Optional[list[Any]]` in MCP tool definitions as an intentional, consistent typing pattern (used across `query`, `responses`, `streaming_query`, `rlsapi_v1`). Do not raise or suggest this as a typing issue during code review; changing it in isolation could break endpoint typing consistency across the codebase.
Applied to files:
src/app/endpoints/streaming_query.py
🔇 Additional comments (7)
src/models/common/turn_summary.py (1)
117-126: LGTM!src/constants.py (1)
15-15: LGTM!src/utils/stream_interrupts.py (1)
23-23: LGTM!Also applies to: 219-239, 277-277, 286-286, 368-369
tests/unit/utils/test_stream_interrupts.py (1)
8-21: LGTM!Also applies to: 49-49, 71-72, 100-100, 169-193
src/utils/agents/streaming.py (1)
28-28: LGTM!Also applies to: 68-68, 201-217, 358-364, 415-415
tests/unit/utils/agents/test_streaming.py (1)
67-68: LGTM!Also applies to: 720-722, 813-813, 966-1106
tests/unit/app/endpoints/test_streaming_query.py (1)
54-54: LGTM!Also applies to: 74-75, 1385-1385, 1394-1400
|
/cc @tisnik |
Signed-off-by: Jordan Dubrick <jdubrick@redhat.com>
Signed-off-by: Jordan Dubrick <jdubrick@redhat.com>
Signed-off-by: Jordan Dubrick <jdubrick@redhat.com>
Signed-off-by: Jordan Dubrick <jdubrick@redhat.com>
Signed-off-by: Jordan Dubrick <jdubrick@redhat.com>
Signed-off-by: Jordan Dubrick <jdubrick@redhat.com>
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Actionable comments posted: 3
Caution
Some comments are outside the diff and can’t be posted inline due to platform limitations.
⚠️ Outside diff range comments (1)
src/app/endpoints/streaming_query.py (1)
774-783: 🎯 Functional Correctness | 🟠 Major | ⚡ Quick winAdvance
next_chunk_idbefore yielding each SSE chunk.Because
response_generatorsuspends atyield, cancellation immediately aftergenerate_responsere-yields a token can skip Lines 782-783 or 808-809. The cancellation handler then emits the interruption suffix with the staleturn_summary.next_chunk_id, duplicating the ID of the just-emitted token. Move the ID advancement before eachyieldwhile preserving the event’s current ID.Proposed fix
if event_type == "response.content_part.added": + event_id = chunk_id + chunk_id += 1 + turn_summary.next_chunk_id = chunk_id yield stream_event( { - "id": chunk_id, + "id": event_id, "token": "", }, LLM_TOKEN_EVENT, media_type, ) - chunk_id += 1 - turn_summary.next_chunk_id = chunk_id # Text streaming - emit token delta elif event_type == "response.output_text.delta": delta_chunk = cast(TextDeltaChunk, chunk) text_parts.append(delta_chunk.delta) turn_summary.partial_tokens.append(delta_chunk.delta) + event_id = chunk_id + chunk_id += 1 + turn_summary.next_chunk_id = chunk_id yield stream_event( { - "id": chunk_id, + "id": event_id, "token": delta_chunk.delta, }, LLM_TOKEN_EVENT, media_type, ) - chunk_id += 1 - turn_summary.next_chunk_id = chunk_id @@ elif event_type == "response.completed": latest_response_object = cast( OpenAIResponseObject, getattr(chunk, "response"), # noqa: B009 ) turn_summary.llm_response = turn_summary.llm_response or "".join(text_parts) # Capture structured output items for compacted-mode turn storage # (LCORE-1572), so the persisted turn keeps non-text output items # rather than being flattened to the response text. turn_summary.output_items = list(latest_response_object.output or []) + event_id = chunk_id + chunk_id += 1 + turn_summary.next_chunk_id = chunk_id yield stream_event( { - "id": chunk_id, + "id": event_id, "token": turn_summary.llm_response, }, LLM_TURN_COMPLETE_EVENT, media_type, ) - chunk_id += 1 - turn_summary.next_chunk_id = chunk_idAlso applies to: 800-809, 889-898
🤖 Prompt for AI Agents
Verify each finding against current code. Fix only still-valid issues, skip the rest with a brief reason, keep changes minimal, and validate. In `@src/app/endpoints/streaming_query.py` around lines 774 - 783, The ID advancement in the stream_event yielding blocks happens after the yield statement, which can cause the increment to be skipped during cancellation. Move the `chunk_id += 1` and `turn_summary.next_chunk_id = chunk_id` statements to occur before each `yield stream_event()` call while preserving the event's ID field to use the current chunk_id value at the time of emission. This pattern appears in three locations: the stream_event yielding block around lines 774-783, the similar block around lines 800-809, and the block around lines 889-898. Save the current chunk_id value before incrementing, use the saved value in the event's ID field, and increment the counters before yielding to ensure the ID advancement cannot be skipped by cancellation.
🤖 Prompt for all review comments with AI agents
Verify each finding against current code. Fix only still-valid issues, skip the
rest with a brief reason, keep changes minimal, and validate.
Inline comments:
In `@src/utils/markdown_repair.py`:
- Around line 30-50: The function `_process_html_tags` currently mutates its
`html_stack` parameter in-place using `.pop()` and `.append()` operations.
Refactor this function to return the updated stack instead of modifying the
parameter directly. Change the function signature to return a list (the updated
html_stack) and update all callers to capture the returned value rather than
relying on side effects. This applies to both the main function definition and
any other similar patterns mentioned at lines 77-79.
- Around line 31-36: The docstring for the function starting at line 31 uses
"Parameters:" section header, but Google Python docstring conventions require
"Args:" instead. Update the docstring header from "Parameters:" to "Args:" in
the function at line 31-36, and apply the same fix to the other docstring
mentioned at lines 53-64. Additionally, review both docstrings to ensure they
include all required Google format sections (Args, Returns, Raises) where
applicable based on what each function actually does.
In `@src/utils/stream_interrupts.py`:
- Around line 219-232: The docstring for the build_interrupted_response function
uses "Parameters:" and "Returns:" sections, but the repository standard requires
Google-style docstring format with "Args", "Returns", and "Raises" sections.
Update the docstring by renaming the "Parameters:" section to "Args:" to match
the required convention. Additionally, add a "Raises:" section if the function
can raise any exceptions during execution, following the repository's Google
Python docstring conventions.
---
Outside diff comments:
In `@src/app/endpoints/streaming_query.py`:
- Around line 774-783: The ID advancement in the stream_event yielding blocks
happens after the yield statement, which can cause the increment to be skipped
during cancellation. Move the `chunk_id += 1` and `turn_summary.next_chunk_id =
chunk_id` statements to occur before each `yield stream_event()` call while
preserving the event's ID field to use the current chunk_id value at the time of
emission. This pattern appears in three locations: the stream_event yielding
block around lines 774-783, the similar block around lines 800-809, and the
block around lines 889-898. Save the current chunk_id value before incrementing,
use the saved value in the event's ID field, and increment the counters before
yielding to ensure the ID advancement cannot be skipped by cancellation.
🪄 Autofix (Beta)
Fix all unresolved CodeRabbit comments on this PR:
- Push a commit to this branch (recommended)
- Create a new PR with the fixes
ℹ️ Review info
⚙️ Run configuration
Configuration used: Path: .coderabbit.yaml
Review profile: ASSERTIVE
Plan: Pro
Run ID: 187ae3b8-ac25-444d-befd-f5f266b56a23
📒 Files selected for processing (10)
src/app/endpoints/streaming_query.pysrc/constants.pysrc/models/common/turn_summary.pysrc/utils/agents/streaming.pysrc/utils/markdown_repair.pysrc/utils/stream_interrupts.pytests/unit/app/endpoints/test_streaming_query.pytests/unit/utils/agents/test_streaming.pytests/unit/utils/test_markdown_repair.pytests/unit/utils/test_stream_interrupts.py
📜 Review details
⏰ Context from checks skipped due to timeout. (14)
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🧰 Additional context used
📓 Path-based instructions (5)
src/**/*.py
📄 CodeRabbit inference engine (AGENTS.md)
src/**/*.py: Use absolute imports for internal modules:from authentication import get_auth_dependency
Llama Stack imports: Usefrom llama_stack_client import AsyncLlamaStackClient
Checkconstants.pyfor shared constants before defining new ones
All modules must start with descriptive docstrings explaining purpose
Uselogger = get_logger(__name__)fromlog.pyfor module logging
All functions must have complete type annotations for parameters and return types, use modern syntax (str | int), and include descriptive docstrings
Use snake_case with descriptive, action-oriented names for functions (get_, validate_, check_)
Avoid in-place parameter modification anti-patterns; return new data structures instead of modifying function parameters
Useasync deffor I/O operations and external API calls
Use standard log levels with clear purposes:debug()for diagnostic info,info()for program execution,warning()for unexpected events,error()for serious problems
All classes must have descriptive docstrings explaining purpose and use PascalCase with standard suffixes:Configuration,Error/Exception,Resolver,Interface
Abstract classes must use ABC with@abstractmethoddecorators
Follow Google Python docstring conventions with required sections: Parameters, Returns, Raises, and Attributes for classes
Files:
src/utils/markdown_repair.pysrc/constants.pysrc/models/common/turn_summary.pysrc/utils/agents/streaming.pysrc/utils/stream_interrupts.pysrc/app/endpoints/streaming_query.py
src/constants.py
📄 CodeRabbit inference engine (AGENTS.md)
Use
constants.pyfor shared constants with descriptive comments and type hints usingFinal[type]
Files:
src/constants.py
src/models/**/*.py
📄 CodeRabbit inference engine (AGENTS.md)
Pydantic models must use
@model_validatorand@field_validatorfor validation and complete type annotations for all attributes, avoidingAnytype
Files:
src/models/common/turn_summary.py
tests/**/*.py
📄 CodeRabbit inference engine (AGENTS.md)
tests/**/*.py: Use pytest for all unit and integration tests; do not use unittest
Usepytest.mark.asynciomarker for async tests
Files:
tests/unit/app/endpoints/test_streaming_query.pytests/unit/utils/test_markdown_repair.pytests/unit/utils/agents/test_streaming.pytests/unit/utils/test_stream_interrupts.py
src/app/**/*.py
📄 CodeRabbit inference engine (AGENTS.md)
src/app/**/*.py: FastAPI dependencies: Import fromfastapimodule forAPIRouter,HTTPException,Request,status,Depends
Use FastAPIHTTPExceptionwith appropriate status codes for API endpoints and handleAPIConnectionErrorfrom Llama Stack
Files:
src/app/endpoints/streaming_query.py
🧠 Learnings (3)
📚 Learning: 2026-01-12T10:58:40.230Z
Learnt from: blublinsky
Repo: lightspeed-core/lightspeed-stack PR: 972
File: src/models/config.py:459-513
Timestamp: 2026-01-12T10:58:40.230Z
Learning: In lightspeed-core/lightspeed-stack, for Python files under src/models, when a user claims a fix is done but the issue persists, verify the current code state before accepting the fix. Steps: review the diff, fetch the latest changes, run relevant tests, reproduce the issue, search the codebase for lingering references to the original problem, confirm the fix is applied and not undone by subsequent commits, and validate with local checks to ensure the issue is resolved.
Applied to files:
src/models/common/turn_summary.py
📚 Learning: 2026-02-25T07:46:33.545Z
Learnt from: asimurka
Repo: lightspeed-core/lightspeed-stack PR: 1211
File: src/models/responses.py:8-16
Timestamp: 2026-02-25T07:46:33.545Z
Learning: In the Python codebase, requests.py should use OpenAIResponseInputTool as Tool while responses.py uses OpenAIResponseTool as Tool. This difference is intentional due to differing schemas for input vs output tools in llama-stack-api. Apply this distinction consistently to other models under src/models (e.g., ensure request-related tools use the InputTool variant and response-related tools use the ResponseTool variant). If adding new tools, choose the corresponding InputTool or Tool class based on whether the tool represents input or output, and document the rationale in code comments.
Applied to files:
src/models/common/turn_summary.py
📚 Learning: 2026-04-06T20:18:07.852Z
Learnt from: major
Repo: lightspeed-core/lightspeed-stack PR: 1463
File: src/app/endpoints/rlsapi_v1.py:266-271
Timestamp: 2026-04-06T20:18:07.852Z
Learning: In the lightspeed-stack codebase, within `src/app/endpoints/` inference/MCP endpoints, treat `tools: Optional[list[Any]]` in MCP tool definitions as an intentional, consistent typing pattern (used across `query`, `responses`, `streaming_query`, `rlsapi_v1`). Do not raise or suggest this as a typing issue during code review; changing it in isolation could break endpoint typing consistency across the codebase.
Applied to files:
src/app/endpoints/streaming_query.py
🔇 Additional comments (13)
src/models/common/turn_summary.py (1)
117-126: LGTM!tests/unit/utils/test_markdown_repair.py (1)
1-175: LGTM!src/constants.py (1)
15-15: LGTM!src/utils/stream_interrupts.py (1)
23-23: LGTM!Also applies to: 277-287, 368-369
tests/unit/utils/test_stream_interrupts.py (1)
8-21: LGTM!Also applies to: 49-49, 71-73, 100-100, 169-193
src/utils/agents/streaming.py (3)
28-28: LGTM!Also applies to: 68-68
201-217: LGTM!
358-364: LGTM!Also applies to: 415-415
tests/unit/utils/agents/test_streaming.py (2)
67-68: LGTM!Also applies to: 720-722, 813-813
966-1106: LGTM!src/app/endpoints/streaming_query.py (1)
124-124: LGTM!Also applies to: 637-652
tests/unit/app/endpoints/test_streaming_query.py (2)
54-54: LGTM!Also applies to: 74-75
1385-1400: LGTM!
| def _process_html_tags(line: str, html_stack: list[str]) -> None: | ||
| """Update *html_stack* with block-level HTML open/close tags found in *line*. | ||
|
|
||
| Parameters: | ||
| line: A single line of text to scan for HTML tags. | ||
| html_stack: Mutable stack tracking open block-level tags. | ||
| """ | ||
| for tag_match in _TAG_RE.finditer(line): | ||
| is_closing = tag_match.group(1) == "/" | ||
| tag_name = tag_match.group(2).lower() | ||
| is_self_closing = tag_match.group(4) == "/" | ||
|
|
||
| if tag_name not in BLOCK_HTML_TAGS or is_self_closing: | ||
| continue | ||
|
|
||
| if is_closing: | ||
| if html_stack and html_stack[-1] == tag_name: | ||
| html_stack.pop() | ||
| else: | ||
| html_stack.append(tag_name) | ||
|
|
There was a problem hiding this comment.
📐 Maintainability & Code Quality | 🟠 Major | ⚡ Quick win
Avoid in-place mutation of function parameters in _process_html_tags.
_process_html_tags currently mutates html_stack directly. Return an updated stack instead so the helper remains side-effect explicit and easier to reason about.
As per coding guidelines, "Avoid in-place parameter modification anti-patterns; return new data structures instead of modifying function parameters."
Proposed refactor
-def _process_html_tags(line: str, html_stack: list[str]) -> None:
+def _process_html_tags(line: str, html_stack: list[str]) -> list[str]:
@@
- for tag_match in _TAG_RE.finditer(line):
+ updated_stack = [*html_stack]
+ for tag_match in _TAG_RE.finditer(line):
@@
- if is_closing:
- if html_stack and html_stack[-1] == tag_name:
- html_stack.pop()
+ if is_closing:
+ if updated_stack and updated_stack[-1] == tag_name:
+ updated_stack.pop()
else:
- html_stack.append(tag_name)
+ updated_stack.append(tag_name)
+ return updated_stack
@@
- _process_html_tags(line, html_stack)
+ html_stack = _process_html_tags(line, html_stack)Also applies to: 77-79
🤖 Prompt for AI Agents
Verify each finding against current code. Fix only still-valid issues, skip the
rest with a brief reason, keep changes minimal, and validate.
In `@src/utils/markdown_repair.py` around lines 30 - 50, The function
`_process_html_tags` currently mutates its `html_stack` parameter in-place using
`.pop()` and `.append()` operations. Refactor this function to return the
updated stack instead of modifying the parameter directly. Change the function
signature to return a list (the updated html_stack) and update all callers to
capture the returned value rather than relying on side effects. This applies to
both the main function definition and any other similar patterns mentioned at
lines 77-79.
Source: Coding guidelines
| """Update *html_stack* with block-level HTML open/close tags found in *line*. | ||
|
|
||
| Parameters: | ||
| line: A single line of text to scan for HTML tags. | ||
| html_stack: Mutable stack tracking open block-level tags. | ||
| """ |
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📐 Maintainability & Code Quality | 🟠 Major | ⚡ Quick win
Align new function docstrings with required Google docstring sections.
The new docstrings should use the repository’s required Google format (Args, Returns, Raises) for consistency.
As per coding guidelines, "Follow Google Python docstring conventions with required sections: Parameters, Returns, Raises, and Attributes for classes."
Also applies to: 53-64
🤖 Prompt for AI Agents
Verify each finding against current code. Fix only still-valid issues, skip the
rest with a brief reason, keep changes minimal, and validate.
In `@src/utils/markdown_repair.py` around lines 31 - 36, The docstring for the
function starting at line 31 uses "Parameters:" section header, but Google
Python docstring conventions require "Args:" instead. Update the docstring
header from "Parameters:" to "Args:" in the function at line 31-36, and apply
the same fix to the other docstring mentioned at lines 53-64. Additionally,
review both docstrings to ensure they include all required Google format
sections (Args, Returns, Raises) where applicable based on what each function
actually does.
Source: Coding guidelines
| def build_interrupted_response(partial_tokens: list[str]) -> tuple[str, str]: | ||
| """Build the final interrupted response text from accumulated tokens. | ||
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| Joins partial tokens, repairs any open markdown constructs, and appends | ||
| an italicized interruption indicator. | ||
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| Parameters: | ||
| partial_tokens: List of text deltas accumulated during streaming. | ||
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| Returns: | ||
| A tuple of (full_response_text, suffix_to_emit) where full_response_text | ||
| is the complete message for persistence and suffix_to_emit is the new | ||
| content to send as a final SSE token event. | ||
| """ |
There was a problem hiding this comment.
📐 Maintainability & Code Quality | 🟠 Major | ⚡ Quick win
Use required Google-style docstring sections in build_interrupted_response.
Please update the new helper docstring to the required convention (Args, Returns, Raises) for consistency with repository standards.
As per coding guidelines, "Follow Google Python docstring conventions with required sections: Parameters, Returns, Raises, and Attributes for classes."
🤖 Prompt for AI Agents
Verify each finding against current code. Fix only still-valid issues, skip the
rest with a brief reason, keep changes minimal, and validate.
In `@src/utils/stream_interrupts.py` around lines 219 - 232, The docstring for the
build_interrupted_response function uses "Parameters:" and "Returns:" sections,
but the repository standard requires Google-style docstring format with "Args",
"Returns", and "Raises" sections. Update the docstring by renaming the
"Parameters:" section to "Args:" to match the required convention. Additionally,
add a "Raises:" section if the function can raise any exceptions during
execution, following the repository's Google Python docstring conventions.
Source: Coding guidelines
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