feat: using newer hivemind-backend lib version! #107
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WalkthroughThe pull request introduces significant updates to the Changes
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Actionable comments posted: 0
🧹 Outside diff range and nitpick comments (2)
utils/query_engine/subquestion_engine.py (2)
84-96: Consider adding error handling for event dispatchingWhile the instrumentation implementation is good, consider wrapping the event dispatching in try-except blocks to ensure query functionality isn't affected if event dispatching fails.
@dispatcher.span def query( self, str_or_query_bundle: str | QueryBundle ) -> tuple[RESPONSE_TYPE, list[NodeWithScore]]: - dispatcher.event(QueryStartEvent(query=str_or_query_bundle)) + try: + dispatcher.event(QueryStartEvent(query=str_or_query_bundle)) + except Exception as e: + self.callback_manager.on_event_error(e, event_type="QueryStartEvent") with self.callback_manager.as_trace("query"): if isinstance(str_or_query_bundle, str): str_or_query_bundle = QueryBundle(str_or_query_bundle) query_result, qa_pairs_all = self._query(str_or_query_bundle) - dispatcher.event( - QueryEndEvent(query=str_or_query_bundle, response=query_result) - ) + try: + dispatcher.event( + QueryEndEvent(query=str_or_query_bundle, response=query_result) + ) + except Exception as e: + self.callback_manager.on_event_error(e, event_type="QueryEndEvent") return query_result, qa_pairs_all
89-89: Consider adding timeout to trace contextThe trace context should have a reasonable timeout to prevent hanging operations.
- with self.callback_manager.as_trace("query"): + with self.callback_manager.as_trace("query", timeout=300): # 5 minutes timeout
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📒 Files selected for processing (2)
requirements.txt(1 hunks)utils/query_engine/subquestion_engine.py(2 hunks)
🔇 Additional comments (4)
requirements.txt (3)
10-13: Verify integration of new llama-index packages
New llama-index related packages have been added. These seem to support the changes in subquestion_engine.py.
✅ Verification successful
Llama-index packages are actively used throughout the codebase
The codebase extensively uses llama-index packages across multiple components:
- Core functionality in query engines (
utils/query_engine/) - Retrievers implementation (
bot/retrievers/) - Test suites (
tests/unit/) - Subquery handling (
subquery.py)
The new package llama-index-vector-stores-postgres aligns with existing postgres vector store usage in bot/retrievers/retrieve_similar_nodes.py.
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The following scripts were executed for the analysis:
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#!/bin/bash
# Check for llama-index usage
rg "from llama_index|import llama_index"
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14-14:
The version jump from 0.14.1 to 0.31.0 is significant and may introduce breaking changes. Please verify:
- All traceloop instrumentation still works as expected
- No deprecated features are in use
8-8: Verify compatibility with tc-hivemind-backend 1.4.2.post1
The update to tc-hivemind-backend is significant. Please ensure all dependent functionality is tested.
utils/query_engine/subquestion_engine.py (1)
13-18: LGTM: Clean instrumentation setup
The addition of query event tracking is well-structured and follows best practices.
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🧹 Outside diff range and nitpick comments (1)
utils/query_engine/subquestion_engine.py (1)
85-92: Consider adding error handling for event dispatchingThe event dispatching code could benefit from error handling to ensure that failures in event tracking don't affect the main query flow.
Consider wrapping the event dispatching in try-except blocks:
- dispatcher.event(QueryStartEvent(query=str_or_query_bundle)) + try: + dispatcher.event(QueryStartEvent(query=str_or_query_bundle)) + except Exception as e: + logger.warning(f"Failed to dispatch QueryStartEvent: {e}") with self.callback_manager.as_trace("query"): if isinstance(str_or_query_bundle, str): str_or_query_bundle = QueryBundle(str_or_query_bundle) query_result, qa_pairs_all = self._query(str_or_query_bundle) - dispatcher.event( - QueryEndEvent(query=str_or_query_bundle, response=query_result) - ) + try: + dispatcher.event( + QueryEndEvent(query=str_or_query_bundle, response=query_result) + ) + except Exception as e: + logger.warning(f"Failed to dispatch QueryEndEvent: {e}")
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utils/query_engine/subquestion_engine.py(2 hunks)
🔇 Additional comments (4)
utils/query_engine/subquestion_engine.py (4)
3-3: LGTM: Clean instrumentation setup
The new imports and dispatcher initialization are well-organized and follow the standard instrumentation pattern.
Also applies to: 8-8, 16-16
81-81: LGTM: Comprehensive tracing implementation
The implementation properly integrates tracing using both the span decorator and trace context manager, which will provide good observability of query execution.
Also applies to: 86-86
82-84: LGTM: Well-defined type annotations
The type annotations are precise, use modern Python syntax, and accurately reflect the method's input and output types.
82-84: Verify compatibility with existing callers
Since the return type is now explicitly defined, ensure all callers of this method are updated to handle both components of the tuple return value.
✅ Verification successful
Let me gather more information to verify the usage and impact.
Let me check the actual implementation and usage patterns to ensure we have a complete picture.
Return type change is compatible with existing usage
Based on the code analysis:
- In
discord_query.py, the caller unpacks the response object directly asresponse.response, response.source_nodes - In
subquery.py, the caller explicitly handles the tuple return type and correctly unpacks it asresponse, source_nodes = result
Both callers are already handling the return value correctly, making them compatible with the explicit tuple return type annotation. The change is purely a type annotation improvement that matches the existing behavior.
🏁 Scripts executed
The following scripts were executed for the analysis:
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#!/bin/bash
# Search for instances where this class is used
rg -l "CustomSubQuestionQueryEngine" | while read -r file; do
echo "=== $file ==="
# Show usage context
rg -B 2 -A 2 "CustomSubQuestionQueryEngine.*query\(" "$file" || true
done
Length of output: 609
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#!/bin/bash
# Search for any imports of CustomSubQuestionQueryEngine
rg -B 2 -A 2 "from.*CustomSubQuestionQueryEngine|import.*CustomSubQuestionQueryEngine"
# Search for any method calls that use .query( to see the call patterns
rg -B 2 -A 2 "\.query\("
Length of output: 1119
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#!/bin/bash
# Check the implementation of query method and its callers
ast-grep --pattern 'def query($$$)' utils/query_engine/subquestion_engine.py
# Check the actual usage in the calling files
cat discord_query.py
cat subquery.py
Length of output: 8854
Summary by CodeRabbit
numpy,pandas,fastapi, and others.tc-hivemind-backendandtraceloop-sdk.