RAG_AIEXP_01 / index_retriever.py

Commit History

eski holat with utils
40de98c

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eski holat
79d5a5c

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eski holat
f6a9f63

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max rows = 20, 150 + 150 bm25
4c7b0a2

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chunk size = 2048 + rows=15
2eb8b63

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max rows = 20, 100 + 100 bm25
7504d82

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top k reranker = 20, max rows = 10, max chars= 2000 + new deduplication
ec64429

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top k reranker = 20, max rows = 10, max chars= 4000 + new deduplication
d577496

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doc id problem fixed
bb76787

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doc id problem fixed
5514fbd

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new doc id filter + 100 + 100 retrieval
399f589

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Much lower reranking threshold (-0.5 instead of 0.1) + detailed score logging
a83db61

MrSimple07 commited on

Much lower reranking threshold (-0.5 instead of 0.1) + detailed score logging
806f3f9

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removed normalization doc id
ad8e8ec

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index retriever = 100 + 100
31659d7

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index retriever = 100 + 100
8114c87

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max_chars = 1500 + doc id retriever
ae5a669

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new keyword score based index retriever + answer question
dfc7ba2

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new keyword score based index retriever + answer question
d2e7d9e

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chunk size = 1024 + max chars = 1200 + deduplication variant
f79b229

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chunk size = 1024 + max chars = 1200 + keyword based
26c4970

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new embeeding model + new create_quer_engine with keyword matching
2d1ebe6

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simplest version
30be7bf

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simplest version
f3e59e1

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simplest version
9985d37

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added sheet_name
6370d73

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added the load_table_data function
f9e7c0c

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added the load_table_data function
b01a551

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added the load_table_data function
c697463

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table prep changed
aa38fcf

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hybrid_retrieve_with_keywords implemented
eefdfd0

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a new way with keywords
90e6b4c

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a new chunking with 3 000 size for all types of data
c0bcb11

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bm = 40, semantic = 40. hybrid = 60, cutoff = 0.65, topk_reranker= 20
32b4b31

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bm = 20, semantic = 30. hybrid = 40, cutoff = 0.65, topk_reranker= 20
b5a647e

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bm = 20, semantic = 20. hybrid = 40, cutoff = 0.65, topk_reranker= 20
0e69113

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bm = 40, semantic = 40. hybrid = 60, cutoff = 0.5, topk_reranker= 20
f7d9029

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bm = 30, semantic = 30. hybrid = 60, cutoff = 0.7, topk_reranker= 60
a65fa1d

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bm = 25, semantic = 25. hybrid = 50, cutoff = 0.7, topk_reranker= 40
c22a32c

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bm = 20, semantic = 20. hybrid = 40, cutoff = 0.7, topk_reranker= 40
a85d815

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bm = 40, semantic = 20. hybrid = 50, cutoff = 0.7, topk_reranker= 40
dbc2de5

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bm = 45, semantic = 20. hybrid = 50, cutoff = 0.7, topk_reranker= 20
c6d8c50

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bm = 40, semantic = 20. hybrid = 50
4c24c3f

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bm = 30, semantic = 20. hybrid = 50
ea35157

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bm = 20, semantic = 20. hybrid = 40
be783a8

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top k semantic 50, cutof == 0.6, hybdrid = 0.6
eb17fcb

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top k in reranker = 30, bm = 20
f49e798

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bm = 60, semantic = 50. hybrid = 70
9e1a00e

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bm = 50, semantic = 50. hybrid = 50
edc2f6f

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bm = 40, semantic = 50. hybrid = 40
8befcd1

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