LCORE-1429: Added configurable search mode option for solr provider#1511
LCORE-1429: Added configurable search mode option for solr provider#1511asimurka wants to merge 1 commit intolightspeed-core:mainfrom
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WalkthroughAdds a structured per-request Solr vector search payload ( Changes
Sequence Diagram(s):sequenceDiagram
participant Client
participant API as API Layer
participant ReqModel as SolrVectorSearchRequest
participant VectorUtil as vector_search
participant VectorIO as client.vector_io
participant Solr as Solr Backend
Client->>API: send request with `solr` payload
API->>ReqModel: validate/coerce payload (legacy -> {mode:null, filters:...})
API->>VectorUtil: build_rag_context/_fetch_solr_rag(solr=ReqModel)
VectorUtil->>VectorIO: query(..., params={mode, solr: filters?})
VectorIO->>Solr: forward params and query
Solr-->>VectorIO: results
VectorIO-->>VectorUtil: results
VectorUtil-->>API: enriched RAG context
API-->>Client: response
Estimated code review effort🎯 3 (Moderate) | ⏱️ ~20 minutes 🚥 Pre-merge checks | ✅ 3✅ Passed checks (3 passed)
✏️ Tip: You can configure your own custom pre-merge checks in the settings. ✨ Finishing Touches🧪 Generate unit tests (beta)
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Actionable comments posted: 4
🤖 Prompt for all review comments with AI agents
Verify each finding against the current code and only fix it if needed.
Inline comments:
In `@docs/rag_guide.md`:
- Around line 362-371: The fenced JSON example after the "Example:" label starts
immediately on the next line which violates MD031; edit the markdown around the
```json fence so there is a blank line before the opening ```json fence and
ensure there is a blank line after the closing ``` fence (i.e., add one empty
line between the "Example:" paragraph and the ```json block and keep a blank
line following the closing fence) to satisfy markdownlint; look for the
"Example:" text and the ```json fenced block to locate the change.
In `@src/models/requests.py`:
- Around line 124-129: Update the SolrVectorSearchRequest Pydantic model
docstring to include an "Attributes:" section that documents each model field
(e.g., mode, filters, provider-related fields) with their types and short
descriptions; modify the docstring in class SolrVectorSearchRequest (subclassing
BaseModel) to enumerate every attribute present on the model so readers and
tools can discover what fields are expected and what they mean.
- Line 6: Replace the current import of Self from typing with an import from
typing_extensions: remove Self from the "from typing import Any, Literal,
Optional, Self" line and instead add "from typing_extensions import Self"; keep
the other typing imports (Any, Literal, Optional) as-is so validator return
annotations that reference Self (used in your model validators) import the
correct symbol per repository standards.
In `@tests/unit/models/requests/test_query_request.py`:
- Around line 144-153: The test test_solr_legacy_plain_dict should also assert
that a deprecation warning is emitted for the legacy solr payload shape: when
constructing QueryRequest(query="q", solr={"fq": ["a:b"]}) and validating via
SolrVectorSearchRequest.model_validate(qr.solr), wrap the validation in a
pytest.warns(ExpectedWarningType) (or warnings.catch_warnings and record) and
assert the warning message or category matches the expected deprecation notice
so the legacy-shape deprecation contract is checked alongside the existing
assertions on mode and filters.
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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 unit tests
Files:
tests/unit/models/requests/test_query_request.pytests/unit/utils/test_vector_search.py
tests/unit/**/*.py
📄 CodeRabbit inference engine (AGENTS.md)
Use
pytest-mockfor AsyncMock objects in unit tests
Files:
tests/unit/models/requests/test_query_request.pytests/unit/utils/test_vector_search.py
src/**/*.py
📄 CodeRabbit inference engine (AGENTS.md)
src/**/*.py: Use absolute imports for internal modules (e.g.,from authentication import get_auth_dependency)
Usefrom llama_stack_client import AsyncLlamaStackClientfor Llama Stack imports
Checkconstants.pyfor shared constants before defining new ones
All modules start with descriptive docstrings explaining purpose
Uselogger = get_logger(__name__)fromlog.pyfor module logging
Type aliases defined at module level for clarity
All functions require docstrings with brief descriptions
Use complete type annotations for function parameters and return types
Use union types with modern syntax:str | intinstead ofUnion[str, int]
UseOptional[Type]for optional types in type annotations
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 parameters
Useasync deffor I/O operations and external API calls
HandleAPIConnectionErrorfrom Llama Stack in error handling
Uselogger.debug()for detailed diagnostic information
Uselogger.info()for general information about program execution
Uselogger.warning()for unexpected events or potential problems
Uselogger.error()for serious problems that prevented function execution
All classes require descriptive docstrings explaining purpose
Use PascalCase for class names with descriptive names and standard suffixes:Configuration,Error/Exception,Resolver,Interface
Use complete type annotations for all class attributes; avoid usingAny
Follow Google Python docstring conventions for all modules, classes, and functions
IncludeParameters:,Returns:,Raises:sections in function docstrings as needed
Files:
src/utils/vector_search.pysrc/models/requests.py
src/models/**/*.py
📄 CodeRabbit inference engine (AGENTS.md)
src/models/**/*.py: Use@field_validatorand@model_validatorfor custom validation in Pydantic models
Usetyping_extensions.Selffor model validators in type annotations
Pydantic data models should extendBaseModel
IncludeAttributes:section in Pydantic model docstrings
Files:
src/models/requests.py
🧠 Learnings (6)
📓 Common learnings
Learnt from: are-ces
Repo: lightspeed-core/lightspeed-stack PR: 1335
File: docs/config.md:411-411
Timestamp: 2026-03-17T11:34:53.242Z
Learning: In the lightspeed-stack project (`src/models/config.py`, `docs/config.md`), the internal Solr filter `is_chunk:true` (defined as `SOLR_CHUNK_FILTER_QUERY` in `src/constants.py`) is always injected by the system for OKP searches and is intentionally hidden from users. The `chunk_filter_query` field in `OkpConfiguration` is user-facing and additive-only, but the documentation must NOT mention the internal `is_chunk:true` behavior — this is a deliberate design decision by the maintainers.
📚 Learning: 2026-03-17T11:34:53.242Z
Learnt from: are-ces
Repo: lightspeed-core/lightspeed-stack PR: 1335
File: docs/config.md:411-411
Timestamp: 2026-03-17T11:34:53.242Z
Learning: In the lightspeed-stack project (`src/models/config.py`, `docs/config.md`), the internal Solr filter `is_chunk:true` (defined as `SOLR_CHUNK_FILTER_QUERY` in `src/constants.py`) is always injected by the system for OKP searches and is intentionally hidden from users. The `chunk_filter_query` field in `OkpConfiguration` is user-facing and additive-only, but the documentation must NOT mention the internal `is_chunk:true` behavior — this is a deliberate design decision by the maintainers.
Applied to files:
docs/rag_guide.mddocs/responses.mdsrc/models/requests.py
📚 Learning: 2026-02-23T14:11:46.950Z
Learnt from: asimurka
Repo: lightspeed-core/lightspeed-stack PR: 1198
File: src/utils/responses.py:184-188
Timestamp: 2026-02-23T14:11:46.950Z
Learning: The query request validator in the Responses API flow requires that `query_request.model` and `query_request.provider` must either both be specified or both be absent. The concatenated format (e.g., `model="provider/model"` with `provider=None`) is not permitted by the validator.
Applied to files:
src/models/requests.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/requests.py
📚 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/requests.py
📚 Learning: 2026-04-15T18:54:07.540Z
Learnt from: Lifto
Repo: lightspeed-core/lightspeed-stack PR: 1510
File: src/models/requests.py:769-773
Timestamp: 2026-04-15T18:54:07.540Z
Learning: In lightspeed-core/lightspeed-stack request models, keep schema-level size limits defined as inline numeric literals (e.g., Pydantic Field max_length values used for validation) rather than extracting them into constants.py. Only extract values intended as configurable runtime defaults (e.g., DEFAULT_* settings like header/file upload sizes). Do not flag inline numeric literals used directly in Pydantic Field constraints or field validators as an extraction-to-constants issue.
Applied to files:
src/models/requests.py
🪛 markdownlint-cli2 (0.22.0)
docs/rag_guide.md
[warning] 363-363: Fenced code blocks should be surrounded by blank lines
(MD031, blanks-around-fences)
🔇 Additional comments (3)
tests/unit/utils/test_vector_search.py (1)
78-103: Good Solr mode/filter test coverage.These additions correctly lock in default/override mode behavior and verify request-level mode/filters are forwarded to
vector_io.query.Also applies to: 634-667
docs/responses.md (1)
111-112: Solr extension documentation is clear and aligned.The updated
solrfield description captures both the structured payload and legacy compatibility in a concise way.Also applies to: 602-603
src/utils/vector_search.py (1)
56-87: Typed Solr plumbing in vector search looks good.The mode resolution and
filterspassthrough are correctly separated, and function signatures now enforce the structured Solr contract end-to-end.Also applies to: 453-457, 529-535
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♻️ Duplicate comments (2)
tests/unit/models/requests/test_query_request.py (1)
144-152: 🧹 Nitpick | 🔵 TrivialAssert the legacy Solr deprecation warning.
This validates coercion, but still misses the warning contract for deprecated top-level filter payloads.
Proposed test update
- def test_solr_legacy_plain_dict(self) -> None: + def test_solr_legacy_plain_dict( + self, caplog: pytest.LogCaptureFixture + ) -> None: """Legacy clients may send filter keys as a plain object on ``solr``.""" - qr = QueryRequest( - query="q", - solr={"fq": ["a:b"]}, - ) # pyright: ignore[reportCallIssue] + with caplog.at_level("WARNING", logger="models.requests"): + qr = QueryRequest( + query="q", + solr={"fq": ["a:b"]}, + ) # pyright: ignore[reportCallIssue] solr_request = SolrVectorSearchRequest.model_validate(qr.solr) assert solr_request.mode is None assert solr_request.filters == {"fq": ["a:b"]} + assert "deprecated and will be removed" in caplog.text🤖 Prompt for AI Agents
Verify each finding against the current code and only fix it if needed. In `@tests/unit/models/requests/test_query_request.py` around lines 144 - 152, The test test_solr_legacy_plain_dict currently verifies coercion but misses asserting the deprecation warning for top-level Solr filter payloads; update the test to wrap the call that triggers coercion (the SolrVectorSearchRequest.model_validate(qr.solr) invocation) in a pytest.warns context for the expected DeprecationWarning (or the project's specific deprecation warning class) so the test both validates the resulting SolrVectorSearchRequest fields and asserts the deprecation warning was emitted when QueryRequest/solr is validated.src/models/requests.py (1)
7-7: 🛠️ Refactor suggestion | 🟠 MajorImport
Selffromtyping_extensions.This module uses
Selfin Pydantic model validators, and the repository standard requirestyping_extensions.Self.Proposed import fix
-from typing import Any, Literal, Optional, Self +from typing import Any, Literal, Optional + +from typing_extensions import SelfRun this read-only check to verify the import and validator usage:
#!/bin/bash rg -nP --type=py 'from typing import .*\\bSelf\\b|from typing_extensions import Self|def .*\\(self\\) -> Self' src/models/requests.pyAs per coding guidelines:
**/*.py: "Usetyping_extensions.Selffor model validators in Pydantic models".🤖 Prompt for AI Agents
Verify each finding against the current code and only fix it if needed. In `@src/models/requests.py` at line 7, The module currently imports Self from typing but the project standard requires using typing_extensions.Self for Pydantic model validators; update the import in src/models/requests.py by removing Self from the "from typing import ..." line and instead import Self from typing_extensions (e.g., add "from typing_extensions import Self"), ensuring any validators or annotations that reference Self (used in the Pydantic model methods/validators in this file) keep the same symbol name but now come from typing_extensions.
🤖 Prompt for all review comments with AI agents
Verify each finding against the current code and only fix it if needed.
Duplicate comments:
In `@src/models/requests.py`:
- Line 7: The module currently imports Self from typing but the project standard
requires using typing_extensions.Self for Pydantic model validators; update the
import in src/models/requests.py by removing Self from the "from typing import
..." line and instead import Self from typing_extensions (e.g., add "from
typing_extensions import Self"), ensuring any validators or annotations that
reference Self (used in the Pydantic model methods/validators in this file) keep
the same symbol name but now come from typing_extensions.
In `@tests/unit/models/requests/test_query_request.py`:
- Around line 144-152: The test test_solr_legacy_plain_dict currently verifies
coercion but misses asserting the deprecation warning for top-level Solr filter
payloads; update the test to wrap the call that triggers coercion (the
SolrVectorSearchRequest.model_validate(qr.solr) invocation) in a pytest.warns
context for the expected DeprecationWarning (or the project's specific
deprecation warning class) so the test both validates the resulting
SolrVectorSearchRequest fields and asserts the deprecation warning was emitted
when QueryRequest/solr is validated.
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📒 Files selected for processing (6)
docs/rag_guide.mddocs/responses.mdsrc/models/requests.pysrc/utils/vector_search.pytests/unit/models/requests/test_query_request.pytests/unit/utils/test_vector_search.py
📜 Review details
⏰ Context from checks skipped due to timeout of 90000ms. You can increase the timeout in your CodeRabbit configuration to a maximum of 15 minutes (900000ms). (9)
- GitHub Check: build-pr
- GitHub Check: Konflux kflux-prd-rh02 / lightspeed-stack-on-pull-request
- GitHub Check: E2E: server mode / ci / group 1
- GitHub Check: E2E: library mode / ci / group 3
- GitHub Check: E2E: server mode / ci / group 3
- GitHub Check: E2E: library mode / ci / group 1
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🧰 Additional context used
📓 Path-based instructions (3)
**/*.py
📄 CodeRabbit inference engine (AGENTS.md)
**/*.py: Use absolute imports for internal modules:from authentication import get_auth_dependency
Import FastAPI dependencies with:from fastapi import APIRouter, HTTPException, Request, status, Depends
Import Llama Stack client with:from llama_stack_client import AsyncLlamaStackClient
Checkconstants.pyfor shared constants before defining new ones
All modules start with descriptive docstrings explaining purpose
Uselogger = get_logger(__name__)fromlog.pyfor module logging
Type aliases defined at module level for clarity
Use Final[type] as type hint for all constants
All functions require docstrings with brief descriptions
Complete type annotations for parameters and return types in functions
Usetyping_extensions.Selffor model validators in Pydantic models
Use modern union type syntaxstr | intinstead ofUnion[str, int]
UseOptional[Type]for optional type hints
Use snake_case with descriptive, action-oriented function names (get_, validate_, check_)
Avoid in-place parameter modification anti-patterns; return new data structures instead
Useasync deffor I/O operations and external API calls
HandleAPIConnectionErrorfrom Llama Stack in error handling
Use standard log levels with clear purposes: debug, info, warning, error
All classes require descriptive docstrings explaining purpose
Use PascalCase for class names with standard suffixes: Configuration, Error/Exception, Resolver, Interface
Use ABC for abstract base classes with@abstractmethoddecorators
Use@model_validatorand@field_validatorfor Pydantic model validation
Complete type annotations for all class attributes; use specific types, notAny
Follow Google Python docstring conventions with Parameters, Returns, Raises, and Attributes sections
Files:
tests/unit/models/requests/test_query_request.pysrc/models/requests.pytests/unit/utils/test_vector_search.pysrc/utils/vector_search.py
tests/{unit,integration}/**/*.py
📄 CodeRabbit inference engine (AGENTS.md)
tests/{unit,integration}/**/*.py: Use pytest for all unit and integration tests
Do not use unittest; pytest is the standard for this project
Usepytest-mockfor AsyncMock objects in tests
Use markerpytest.mark.asynciofor async tests
Unit tests require 60% coverage, integration tests 10%
Files:
tests/unit/models/requests/test_query_request.pytests/unit/utils/test_vector_search.py
src/**/*.py
📄 CodeRabbit inference engine (AGENTS.md)
Pydantic models extend
ConfigurationBasefor config,BaseModelfor data models
Files:
src/models/requests.pysrc/utils/vector_search.py
🧠 Learnings (6)
📚 Learning: 2026-02-23T14:11:46.950Z
Learnt from: asimurka
Repo: lightspeed-core/lightspeed-stack PR: 1198
File: src/utils/responses.py:184-188
Timestamp: 2026-02-23T14:11:46.950Z
Learning: The query request validator in the Responses API flow requires that `query_request.model` and `query_request.provider` must either both be specified or both be absent. The concatenated format (e.g., `model="provider/model"` with `provider=None`) is not permitted by the validator.
Applied to files:
tests/unit/models/requests/test_query_request.pysrc/models/requests.py
📚 Learning: 2026-04-19T15:40:25.624Z
Learnt from: CR
Repo: lightspeed-core/lightspeed-stack PR: 0
File: AGENTS.md:0-0
Timestamp: 2026-04-19T15:40:25.624Z
Learning: Applies to **/*.py : Use `typing_extensions.Self` for model validators in Pydantic models
Applied to files:
src/models/requests.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/requests.py
📚 Learning: 2026-03-17T11:34:53.242Z
Learnt from: are-ces
Repo: lightspeed-core/lightspeed-stack PR: 1335
File: docs/config.md:411-411
Timestamp: 2026-03-17T11:34:53.242Z
Learning: In the lightspeed-stack project (`src/models/config.py`, `docs/config.md`), the internal Solr filter `is_chunk:true` (defined as `SOLR_CHUNK_FILTER_QUERY` in `src/constants.py`) is always injected by the system for OKP searches and is intentionally hidden from users. The `chunk_filter_query` field in `OkpConfiguration` is user-facing and additive-only, but the documentation must NOT mention the internal `is_chunk:true` behavior — this is a deliberate design decision by the maintainers.
Applied to files:
src/models/requests.pydocs/rag_guide.md
📚 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/requests.py
📚 Learning: 2026-04-15T18:54:07.540Z
Learnt from: Lifto
Repo: lightspeed-core/lightspeed-stack PR: 1510
File: src/models/requests.py:769-773
Timestamp: 2026-04-15T18:54:07.540Z
Learning: In lightspeed-core/lightspeed-stack request models, keep schema-level size limits defined as inline numeric literals (e.g., Pydantic Field max_length values used for validation) rather than extracting them into constants.py. Only extract values intended as configurable runtime defaults (e.g., DEFAULT_* settings like header/file upload sizes). Do not flag inline numeric literals used directly in Pydantic Field constraints or field validators as an extraction-to-constants issue.
Applied to files:
src/models/requests.py
🔇 Additional comments (7)
docs/responses.md (1)
111-111: LGTM — the Responses docs now reflect the structured Solr payload.The updated text clearly documents the optional
mode,filters, and legacy filter-only compatibility.Also applies to: 602-602
tests/unit/models/requests/test_query_request.py (1)
154-162: LGTM — structured Solr payload coverage is clear.This verifies both explicit
modeforwarding and filter preservation for the new request shape.src/models/requests.py (2)
126-173: LGTM — the Solr request model preserves compatibility cleanly.The structured fields,
extra="forbid", and before-validator provide typed request handling while preserving legacy filter-only payloads.
191-191: LGTM — request models now expose the typed Solr payload.
QueryRequestandResponsesRequestconsistently useOptional[SolrVectorSearchRequest], which keeps downstream vector search code type-safe.Also applies to: 282-292, 755-755, 781-781
docs/rag_guide.md (1)
342-342: LGTM — OKP/Solr request-mode guidance is aligned.The guide documents the default mode, per-request
solrpayload, and legacy compatibility without exposing internal Solr-only filters.Also applies to: 360-372
src/utils/vector_search.py (1)
20-20: LGTM — Solr query params now use the typed request shape.
modeis correctly defaulted when absent, and onlyfiltersis forwarded as the provider-specificsolrpayload.Also applies to: 56-87, 453-456, 529-535
tests/unit/utils/test_vector_search.py (1)
72-102: LGTM — vector-search Solr mode coverage is solid.The tests cover explicit mode, defaulting, filter forwarding, and the actual
vector_io.queryparams path.Also applies to: 634-666
PR Reviewer Guide 🔍(Review updated until commit aa1abc1)Here are some key observations to aid the review process:
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config.ignore_pr_source_branches = []
config.ignore_pr_labels = []
config.ignore_pr_authors = []
config.ignore_repositories = []
config.ignore_language_framework = []
config.is_auto_command = False
config.enable_ai_metadata = False
config.reasoning_effort = 'medium'
config.enable_claude_extended_thinking = False
config.extract_issue_from_branch = True
config.branch_issue_regex = ''
config.enable_custom_labels = False
==================== PR_REVIEWER ====================
pr_reviewer.require_score_review = False
pr_reviewer.require_tests_review = True
pr_reviewer.require_estimate_effort_to_review = True
pr_reviewer.require_can_be_split_review = False
pr_reviewer.require_security_review = True
pr_reviewer.require_estimate_contribution_time_cost = False
pr_reviewer.require_todo_scan = False
pr_reviewer.require_ticket_analysis_review = True
pr_reviewer.publish_output_no_suggestions = True
pr_reviewer.persistent_comment = True
pr_reviewer.extra_instructions = ''
pr_reviewer.num_max_findings = 3
pr_reviewer.final_update_message = True
pr_reviewer.enable_review_labels_security = True
pr_reviewer.enable_review_labels_effort = True
pr_reviewer.require_all_thresholds_for_incremental_review = False
pr_reviewer.minimal_commits_for_incremental_review = 0
pr_reviewer.minimal_minutes_for_incremental_review = 0
pr_reviewer.enable_intro_text = True
pr_reviewer.enable_help_text = False
==================== PR_DESCRIPTION ====================
pr_description.publish_labels = False
pr_description.add_original_user_description = True
pr_description.generate_ai_title = False
pr_description.use_bullet_points = True
pr_description.extra_instructions = ''
pr_description.enable_pr_type = True
pr_description.final_update_message = True
pr_description.enable_help_text = False
pr_description.enable_help_comment = False
pr_description.enable_pr_diagram = True
pr_description.publish_description_as_comment = False
pr_description.publish_description_as_comment_persistent = True
pr_description.enable_semantic_files_types = True
pr_description.collapsible_file_list = 'adaptive'
pr_description.collapsible_file_list_threshold = 6
pr_description.inline_file_summary = False
pr_description.use_description_markers = False
pr_description.enable_large_pr_handling = True
pr_description.include_generated_by_header = True
pr_description.max_ai_calls = 4
pr_description.async_ai_calls = True
==================== PR_QUESTIONS ====================
pr_questions.enable_help_text = False
pr_questions.use_conversation_history = True
==================== PR_CODE_SUGGESTIONS ====================
pr_code_suggestions.commitable_code_suggestions = False
pr_code_suggestions.dual_publishing_score_threshold = -1
pr_code_suggestions.focus_only_on_problems = True
pr_code_suggestions.extra_instructions = ''
pr_code_suggestions.enable_help_text = False
pr_code_suggestions.enable_chat_text = False
pr_code_suggestions.persistent_comment = True
pr_code_suggestions.max_history_len = 4
pr_code_suggestions.publish_output_no_suggestions = True
pr_code_suggestions.suggestions_score_threshold = 0
pr_code_suggestions.new_score_mechanism = True
pr_code_suggestions.new_score_mechanism_th_high = 9
pr_code_suggestions.new_score_mechanism_th_medium = 7
pr_code_suggestions.auto_extended_mode = True
pr_code_suggestions.num_code_suggestions_per_chunk = 3
pr_code_suggestions.max_number_of_calls = 3
pr_code_suggestions.parallel_calls = True
pr_code_suggestions.final_clip_factor = 0.8
pr_code_suggestions.decouple_hunks = False
pr_code_suggestions.demand_code_suggestions_self_review = False
pr_code_suggestions.code_suggestions_self_review_text = '**Author self-review**: I have reviewed the PR code suggestions, and addressed the relevant ones.'
pr_code_suggestions.approve_pr_on_self_review = False
pr_code_suggestions.fold_suggestions_on_self_review = True
==================== PR_CUSTOM_PROMPT ====================
pr_custom_prompt.prompt = 'The code suggestions should focus only on the following:\n- ...\n- ...\n...\n'
pr_custom_prompt.suggestions_score_threshold = 0
pr_custom_prompt.num_code_suggestions_per_chunk = 3
pr_custom_prompt.self_reflect_on_custom_suggestions = True
pr_custom_prompt.enable_help_text = False
==================== PR_ADD_DOCS ====================
pr_add_docs.extra_instructions = ''
pr_add_docs.docs_style = 'Sphinx'
pr_add_docs.file = ''
pr_add_docs.class_name = ''
==================== PR_UPDATE_CHANGELOG ====================
pr_update_changelog.push_changelog_changes = False
pr_update_changelog.extra_instructions = ''
pr_update_changelog.add_pr_link = True
pr_update_changelog.skip_ci_on_push = True
==================== PR_ANALYZE ====================
pr_analyze.enable_help_text = True
==================== PR_TEST ====================
pr_test.extra_instructions = ''
pr_test.testing_framework = ''
pr_test.num_tests = 3
pr_test.avoid_mocks = True
pr_test.file = ''
pr_test.class_name = ''
pr_test.enable_help_text = False
==================== PR_IMPROVE_COMPONENT ====================
pr_improve_component.num_code_suggestions = 4
pr_improve_component.extra_instructions = ''
pr_improve_component.file = ''
pr_improve_component.class_name = ''
==================== PR_HELP ====================
pr_help.force_local_db = False
pr_help.num_retrieved_snippets = 5
==================== PR_HELP_DOCS ====================
pr_help_docs.repo_url = ''
pr_help_docs.repo_default_branch = 'main'
pr_help_docs.docs_path = 'docs'
pr_help_docs.exclude_root_readme = False
pr_help_docs.supported_doc_exts = ['.md', '.mdx', '.rst']
pr_help_docs.enable_help_text = False
==================== PR_SIMILAR_ISSUE ====================
pr_similar_issue.skip_comments = False
pr_similar_issue.force_update_dataset = False
pr_similar_issue.max_issues_to_scan = 500
pr_similar_issue.vectordb = 'pinecone'
==================== PR_FIND_SIMILAR_COMPONENT ====================
pr_find_similar_component.class_name = ''
pr_find_similar_component.file = ''
pr_find_similar_component.search_from_org = False
pr_find_similar_component.allow_fallback_less_words = True
pr_find_similar_component.number_of_results = 5 |
|
Persistent review updated to latest commit aa1abc1 |
| media_type: The optional media type for response format (application/json or text/plain). | ||
| vector_store_ids: The optional list of specific vector store IDs to query for RAG. | ||
| shield_ids: The optional list of safety shield IDs to apply. | ||
| solr: Optional Solr inline RAG options (mode, filters) or legacy filter-only dict. |
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For mode this is fine, but I think we will have to make filters available for any RAG provider. WDYT?
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I'm not sure what's a long term goal. But what is now solr.filters was solr before. What I'm trying to achieve is that it is clear that mode attribute is related to solr.
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Description
Introduces a typed solr payload on query and Responses requests with optional
mode(semantic / hybrid / lexical) andfiltersfor Solr vector_io; legacy top-level-only filter objects remain accepted via a before-validator but log a deprecation warning. Adds short notes indocs/rag_guide.mdanddocs/responses.md.Type of change
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