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Improve node distance reranker speed #107
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❌ Changes requested. Reviewed everything up to a903094 in 1 minute and 41 seconds
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- Looked at
100
lines of code in3
files - Skipped
0
files when reviewing. - Skipped posting
1
drafted comments based on config settings.
1. examples/podcast/podcast_runner.py:66
- Draft comment:
Increasing the range from 3:14 to 3:130 may lead to performance issues if the number of messages is large. Consider the impact on execution time. - Reason this comment was not posted:
Confidence changes required:50%
The change in the range of messages from 3:14 to 3:130 in the loop might lead to performance issues if the number of messages is large. This should be noted as it could affect the execution time significantly.
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👍 Looks good to me! Incremental review on de09ab7 in 1 minute and 23 seconds
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2
drafted comments based on config settings.
1. graphiti_core/search/search_utils.py:38
- Draft comment:
The indentation of the function parameters is inconsistent with PEP 8 style guidelines. Consider aligning them with the opening parenthesis for better readability. This issue is also present in other functions likeentity_similarity_search
,entity_fulltext_search
,edge_fulltext_search
,hybrid_node_search
,get_relevant_nodes
, andget_relevant_edges
. - Reason this comment was not posted:
Confidence changes required:10%
The indentation of the function parameters is inconsistent with PEP 8 style guidelines. This is a minor style issue but should be corrected for consistency and readability.
2. graphiti_core/search/search_utils.py:517
- Draft comment:
Consider using a more descriptive variable name thanrecords
for the result ofresult[0]
to improve code clarity. Additionally, the logic for settingdistance
could be simplified by directly assigningrecord['score']
whenrecord
is notNone
. - Reason this comment was not posted:
Confidence changes required:30%
Thenode_distance_reranker
function usesasyncio.gather
to execute queries in parallel, which is a good optimization for performance. However, the logic for handling the results could be improved for clarity and efficiency.
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👍 Looks good to me! Incremental review on 71920a9 in 1 minute and 0 seconds
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perf: optimize node distance reranker and update podcast example
Summary:
Optimize
node_distance_reranker()
, updatepodcast_runner.py
, and clean uptest_graphiti_int.py
.Key points:
node_distance_reranker()
insearch_utils.py
usingasyncio.gather
for parallel execution.podcast_runner.py
to process messages from 11 to 127 whenuse_bulk
isFalse
.test_graphiti_int.py
related tobuild_communities()
and initial search query.Generated with ❤️ by ellipsis.dev