From ae69dccc39fd0eee97d123e502527a07a28abf6d Mon Sep 17 00:00:00 2001
From: Ivan Pavlovich <ivan.pavlovic@hes-so.ch>
Date: Mon, 17 Mar 2025 19:02:29 +0100
Subject: [PATCH] Regeneration du calcule de tokens et de prix des LLM avec la
nouvelle sauvegarde locale des articles pubmed
---
models/LLM/Tokenizer/data/token_count.json | 390 ++++++++++-----------
models/LLM/Tokenizer/token_count.py | 51 ++-
models/LLM/prices/data/llm_prices.json | 384 ++++++++++----------
3 files changed, 412 insertions(+), 413 deletions(-)
diff --git a/models/LLM/Tokenizer/data/token_count.json b/models/LLM/Tokenizer/data/token_count.json
index 97e080c23..a4c59fb66 100644
--- a/models/LLM/Tokenizer/data/token_count.json
+++ b/models/LLM/Tokenizer/data/token_count.json
@@ -1,41 +1,41 @@
{
"bert-base-uncased": {
- "ALL": 89156232,
+ "ALL": 77536060,
"NO KEYWORDS": {
"day": {
"input": {
"min": 0,
- "max": 478958,
- "mean": 79249.984
+ "max": 359507,
+ "mean": 68920.94222222222
},
"output": {
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- "max": 47188,
- "mean": 7712.846222222222
+ "max": 32900,
+ "mean": 6704.08
}
},
"week": {
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"min": 0,
- "max": 868077,
- "mean": 553765.4161490683
+ "max": 670490,
+ "mean": 481590.4347826087
},
"output": {
"min": 0,
- "max": 85164,
- "mean": 53894.11180124224
+ "max": 67492,
+ "mean": 46845.27950310559
}
},
"month": {
"input": {
- "min": 206588,
- "max": 2817488,
- "mean": 2409627.891891892
+ "min": 47756,
+ "max": 2483951,
+ "mean": 2095569.189189189
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- "min": 18988,
- "max": 275984,
- "mean": 234512.2162162162
+ "min": 4465,
+ "max": 241157,
+ "mean": 203840.27027027027
}
}
},
@@ -44,36 +44,36 @@
"input": {
"min": 0,
"max": 19599,
- "mean": 3528.703111111111
+ "mean": 3090.5537777777777
},
"output": {
"min": 0,
"max": 1833,
- "mean": 342.41066666666666
+ "mean": 300.0062222222222
}
},
"week": {
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"min": 0,
- "max": 38477,
- "mean": 24657.08695652174
+ "max": 34410,
+ "mean": 21595.48447204969
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- "max": 3901,
- "mean": 2392.6211180124224
+ "max": 3243,
+ "mean": 2096.3167701863354
}
},
"month": {
"input": {
- "min": 16460,
- "max": 147094,
- "mean": 107291.64864864865
+ "min": 4070,
+ "max": 130712,
+ "mean": 93969.54054054055
},
"output": {
- "min": 1457,
- "max": 13865,
- "mean": 10411.135135135135
+ "min": 423,
+ "max": 12361,
+ "mean": 9121.81081081081
}
}
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@@ -82,36 +82,36 @@
"input": {
"min": 0,
"max": 19599,
- "mean": 3528.703111111111
+ "mean": 3090.5537777777777
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"max": 1833,
- "mean": 342.41066666666666
+ "mean": 300.0062222222222
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- "max": 38477,
- "mean": 24657.08695652174
+ "max": 34410,
+ "mean": 21595.48447204969
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"output": {
"min": 0,
- "max": 3901,
- "mean": 2392.6211180124224
+ "max": 3243,
+ "mean": 2096.3167701863354
}
},
"month": {
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- "min": 16460,
- "max": 147094,
- "mean": 107291.64864864865
+ "min": 4070,
+ "max": 130712,
+ "mean": 93969.54054054055
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"output": {
- "min": 1457,
- "max": 13865,
- "mean": 10411.135135135135
+ "min": 423,
+ "max": 12361,
+ "mean": 9121.81081081081
}
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@@ -120,36 +120,36 @@
"input": {
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"max": 24083,
- "mean": 4632.119111111111
+ "mean": 4063.0293333333334
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- "mean": 443.4711111111111
+ "mean": 389.07644444444446
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- "max": 51710,
- "mean": 32367.291925465837
+ "max": 47071,
+ "mean": 28390.732919254657
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- "max": 5264,
- "mean": 3098.7888198757764
+ "max": 4371,
+ "mean": 2718.7018633540374
}
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"month": {
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- "min": 18078,
- "max": 173956,
- "mean": 140841.45945945947
+ "min": 4567,
+ "max": 155888,
+ "mean": 123538.05405405405
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- "min": 1598,
- "max": 16309,
- "mean": 13483.918918918918
+ "min": 470,
+ "max": 14617,
+ "mean": 11830.027027027027
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}
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@@ -157,78 +157,78 @@
"day": {
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"min": 0,
- "max": 33985,
- "mean": 6335.672
+ "max": 34474,
+ "mean": 5556.8497777777775
},
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- "max": 3149,
- "mean": 609.6631111111111
+ "max": 3196,
+ "mean": 535.0897777777777
}
},
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- "max": 71519,
- "mean": 44271
+ "max": 57320,
+ "mean": 38828.91925465839
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- "max": 7191,
- "mean": 4260.068322981367
+ "max": 5828,
+ "mean": 3738.981366459627
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- "max": 240785,
- "mean": 192638.67567567568
+ "min": 6782,
+ "max": 215671,
+ "mean": 168958.27027027027
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- "min": 2162,
- "max": 22654,
- "mean": 18537.054054054053
+ "min": 658,
+ "max": 20304,
+ "mean": 16269.621621621622
}
}
}
},
"roberta-base": {
- "ALL": 87109722,
+ "ALL": 75762923,
"NO KEYWORDS": {
"day": {
"input": {
"min": 0,
- "max": 467190,
- "mean": 77430.864
+ "max": 351373,
+ "mean": 67344.82044444444
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- "max": 43172,
- "mean": 7056.433777777778
+ "max": 30100,
+ "mean": 6133.52
}
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- "max": 848340,
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+ "max": 655753,
+ "mean": 470577.1614906832
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- "max": 77916,
- "mean": 49307.37888198758
+ "max": 61748,
+ "mean": 42858.44720496894
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},
"month": {
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- "min": 201746,
- "max": 2748787,
- "mean": 2354316.810810811
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+ "max": 2426045,
+ "mean": 2047646.5675675676
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"output": {
- "min": 17372,
- "max": 252496,
- "mean": 214553.72972972973
+ "min": 4085,
+ "max": 220633,
+ "mean": 186492.16216216216
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@@ -237,36 +237,36 @@
"input": {
"min": 0,
"max": 19177,
- "mean": 3461.84
+ "mean": 3032.2613333333334
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"max": 1677,
- "mean": 313.26933333333335
+ "mean": 274.4737777777778
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"week": {
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"min": 0,
- "max": 37719,
- "mean": 24189.875776397515
+ "max": 33790,
+ "mean": 21188.16149068323
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"output": {
"min": 0,
- "max": 3569,
- "mean": 2188.9937888198756
+ "max": 2967,
+ "mean": 1917.9068322981366
}
},
"month": {
"input": {
- "min": 16182,
- "max": 144179,
- "mean": 105258.64864864865
+ "min": 4004,
+ "max": 128063,
+ "mean": 92197.13513513513
},
"output": {
- "min": 1333,
- "max": 12685,
- "mean": 9525.081081081082
+ "min": 387,
+ "max": 11309,
+ "mean": 8345.486486486487
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@@ -275,36 +275,36 @@
"input": {
"min": 0,
"max": 19177,
- "mean": 3461.84
+ "mean": 3032.2613333333334
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"max": 1677,
- "mean": 313.26933333333335
+ "mean": 274.4737777777778
}
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"min": 0,
- "max": 37719,
- "mean": 24189.875776397515
+ "max": 33790,
+ "mean": 21188.16149068323
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"output": {
"min": 0,
- "max": 3569,
- "mean": 2188.9937888198756
+ "max": 2967,
+ "mean": 1917.9068322981366
}
},
"month": {
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- "min": 16182,
- "max": 144179,
- "mean": 105258.64864864865
+ "min": 4004,
+ "max": 128063,
+ "mean": 92197.13513513513
},
"output": {
- "min": 1333,
- "max": 12685,
- "mean": 9525.081081081082
+ "min": 387,
+ "max": 11309,
+ "mean": 8345.486486486487
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@@ -313,36 +313,36 @@
"input": {
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- "mean": 4548.530666666667
+ "mean": 3990.280888888889
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"max": 2021,
- "mean": 405.7288888888889
+ "mean": 355.96355555555556
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- "max": 50629,
- "mean": 31783.211180124224
+ "max": 46302,
+ "mean": 27882.39751552795
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- "max": 4816,
- "mean": 2835.0621118012423
+ "max": 3999,
+ "mean": 2487.3229813664598
}
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"month": {
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- "min": 17788,
- "max": 170739,
- "mean": 138299.9189189189
+ "min": 4519,
+ "max": 152970,
+ "mean": 121326.1081081081
},
"output": {
- "min": 1462,
- "max": 14921,
- "mean": 12336.351351351352
+ "min": 430,
+ "max": 13373,
+ "mean": 10823.216216216217
}
}
},
@@ -350,78 +350,78 @@
"day": {
"input": {
"min": 0,
- "max": 33290,
- "mean": 6221.055111111111
+ "max": 33755,
+ "mean": 5456.723555555555
},
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- "max": 2881,
- "mean": 557.7768888888888
+ "max": 2924,
+ "mean": 489.5502222222222
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},
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- "max": 70202,
- "mean": 43470.105590062114
+ "max": 56165,
+ "mean": 38129.27950310559
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- "max": 6579,
- "mean": 3897.509316770186
+ "max": 5332,
+ "mean": 3420.7701863354037
}
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- "min": 23801,
- "max": 236368,
- "mean": 189153.7027027027
+ "min": 6731,
+ "max": 211691,
+ "mean": 165913.8918918919
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- "min": 1978,
- "max": 20726,
- "mean": 16959.432432432433
+ "min": 602,
+ "max": 18576,
+ "mean": 14884.972972972973
}
}
}
},
"facebook/bart-large": {
- "ALL": 87109722,
+ "ALL": 75762923,
"NO KEYWORDS": {
"day": {
"input": {
"min": 0,
- "max": 467190,
- "mean": 77430.864
+ "max": 351373,
+ "mean": 67344.82044444444
},
"output": {
"min": 0,
- "max": 43172,
- "mean": 7056.433777777778
+ "max": 30100,
+ "mean": 6133.52
}
},
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- "max": 848340,
- "mean": 541054.1739130435
+ "max": 655753,
+ "mean": 470577.1614906832
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- "max": 77916,
- "mean": 49307.37888198758
+ "max": 61748,
+ "mean": 42858.44720496894
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},
"month": {
"input": {
- "min": 201746,
- "max": 2748787,
- "mean": 2354316.810810811
+ "min": 46810,
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- "min": 17372,
- "max": 252496,
- "mean": 214553.72972972973
+ "min": 4085,
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+ "mean": 186492.16216216216
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@@ -430,36 +430,36 @@
"input": {
"min": 0,
"max": 19177,
- "mean": 3461.84
+ "mean": 3032.2613333333334
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"max": 1677,
- "mean": 313.26933333333335
+ "mean": 274.4737777777778
}
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- "max": 37719,
- "mean": 24189.875776397515
+ "max": 33790,
+ "mean": 21188.16149068323
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"min": 0,
- "max": 3569,
- "mean": 2188.9937888198756
+ "max": 2967,
+ "mean": 1917.9068322981366
}
},
"month": {
"input": {
- "min": 16182,
- "max": 144179,
- "mean": 105258.64864864865
+ "min": 4004,
+ "max": 128063,
+ "mean": 92197.13513513513
},
"output": {
- "min": 1333,
- "max": 12685,
- "mean": 9525.081081081082
+ "min": 387,
+ "max": 11309,
+ "mean": 8345.486486486487
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}
},
@@ -468,36 +468,36 @@
"input": {
"min": 0,
"max": 19177,
- "mean": 3461.84
+ "mean": 3032.2613333333334
},
"output": {
"min": 0,
"max": 1677,
- "mean": 313.26933333333335
+ "mean": 274.4737777777778
}
},
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- "max": 37719,
- "mean": 24189.875776397515
+ "max": 33790,
+ "mean": 21188.16149068323
},
"output": {
"min": 0,
- "max": 3569,
- "mean": 2188.9937888198756
+ "max": 2967,
+ "mean": 1917.9068322981366
}
},
"month": {
"input": {
- "min": 16182,
- "max": 144179,
- "mean": 105258.64864864865
+ "min": 4004,
+ "max": 128063,
+ "mean": 92197.13513513513
},
"output": {
- "min": 1333,
- "max": 12685,
- "mean": 9525.081081081082
+ "min": 387,
+ "max": 11309,
+ "mean": 8345.486486486487
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}
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@@ -506,36 +506,36 @@
"input": {
"min": 0,
"max": 23618,
- "mean": 4548.530666666667
+ "mean": 3990.280888888889
},
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"max": 2021,
- "mean": 405.7288888888889
+ "mean": 355.96355555555556
}
},
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"min": 0,
- "max": 50629,
- "mean": 31783.211180124224
+ "max": 46302,
+ "mean": 27882.39751552795
},
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"min": 0,
- "max": 4816,
- "mean": 2835.0621118012423
+ "max": 3999,
+ "mean": 2487.3229813664598
}
},
"month": {
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- "min": 17788,
- "max": 170739,
- "mean": 138299.9189189189
+ "min": 4519,
+ "max": 152970,
+ "mean": 121326.1081081081
},
"output": {
- "min": 1462,
- "max": 14921,
- "mean": 12336.351351351352
+ "min": 430,
+ "max": 13373,
+ "mean": 10823.216216216217
}
}
},
@@ -543,37 +543,37 @@
"day": {
"input": {
"min": 0,
- "max": 33290,
- "mean": 6221.055111111111
+ "max": 33755,
+ "mean": 5456.723555555555
},
"output": {
"min": 0,
- "max": 2881,
- "mean": 557.7768888888888
+ "max": 2924,
+ "mean": 489.5502222222222
}
},
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"min": 0,
- "max": 70202,
- "mean": 43470.105590062114
+ "max": 56165,
+ "mean": 38129.27950310559
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- "max": 6579,
- "mean": 3897.509316770186
+ "max": 5332,
+ "mean": 3420.7701863354037
}
},
"month": {
"input": {
- "min": 23801,
- "max": 236368,
- "mean": 189153.7027027027
+ "min": 6731,
+ "max": 211691,
+ "mean": 165913.8918918919
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- "min": 1978,
- "max": 20726,
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+ "min": 602,
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diff --git a/models/LLM/Tokenizer/token_count.py b/models/LLM/Tokenizer/token_count.py
index 7a620050b..ed90fd6c7 100644
--- a/models/LLM/Tokenizer/token_count.py
+++ b/models/LLM/Tokenizer/token_count.py
@@ -10,31 +10,6 @@ sys.path.append(os.path.abspath(os.path.join(os.path.dirname(__file__), "../../.
from testModel.utils import get_article_data
from variables.pubmed import NCDS, NCDS_MESH_TERM, KEYWORDS_MESH_TERM, KEYWORDS_MESH_SUBHEADING, KEYWORDS_MESH_SITE_PROPOSITION, KEYWORDS_MESH_PROPOSITION
-DATA_DIR = os.path.abspath(os.path.join(os.path.dirname(__file__), "../../../dataSources/PubMed/data"))
-RESULT_DATA_DIR = os.path.abspath(os.path.join(os.path.dirname(__file__), "./data"))
-
-INTERVALS = [
- "day",
- "week",
- "month"
-]
-
-CATEGORIES = [
- "NO KEYWORDS",
- "KEYWORDS",
- "SUBHEADINGS",
- "SITE PROPOSITION",
- "PROPOSITION"
-]
-
-TOKENIZERS = [
- #"openai-community/gpt-4",
- #"meta-llama/Llama-2-7b-hf",
- "bert-base-uncased",
- "roberta-base",
- "facebook/bart-large"
-]
-
def lower_keywords(mesh_terms):
res = []
@@ -78,6 +53,30 @@ def add_token_number(article_date, start_date, input_token_num, output_token_num
counts[tokenizer_name][category]["month"]["input"][month_index] += input_token_num
counts[tokenizer_name][category]["month"]["output"][month_index] += output_token_num
+INTERVALS = [
+ "day",
+ "week",
+ "month"
+]
+
+CATEGORIES = [
+ "NO KEYWORDS",
+ "KEYWORDS",
+ "SUBHEADINGS",
+ "SITE PROPOSITION",
+ "PROPOSITION"
+]
+
+TOKENIZERS = [
+ #"openai-community/gpt-4",
+ #"meta-llama/Llama-2-7b-hf",
+ "bert-base-uncased",
+ "roberta-base",
+ "facebook/bart-large"
+]
+
+TMP_DATA_DIR = os.path.abspath(os.path.join(os.path.dirname(__file__), "../../../dataSources/PubMed/tmp"))
+RESULT_DATA_DIR = os.path.abspath(os.path.join(os.path.dirname(__file__), "./data"))
ncds_mesh_terms = [mesh_term.lower() for ncd, mesh_term in NCDS_MESH_TERM.items()]
keywords_mesh_terms = lower_keywords(KEYWORDS_MESH_TERM)
@@ -86,7 +85,7 @@ keywords_site_proposition_mesh_terms = lower_keywords(KEYWORDS_MESH_SITE_PROPOSI
keywords_proposition_mesh_terms = lower_keywords(KEYWORDS_MESH_PROPOSITION)
-file_path = f"{DATA_DIR}/save_3_years.json"
+file_path = f"{TMP_DATA_DIR}/save_3_years.json"
with open(file_path, "r", encoding="utf-8") as file:
data = json.load(file)
diff --git a/models/LLM/prices/data/llm_prices.json b/models/LLM/prices/data/llm_prices.json
index 2e2629707..09118ec84 100644
--- a/models/LLM/prices/data/llm_prices.json
+++ b/models/LLM/prices/data/llm_prices.json
@@ -1,338 +1,338 @@
{
"Mistral Large": {
- "ALL": 702.3351359999999,
+ "ALL": 610.8317493333334,
"NO KEYWORDS": {
- "day": 0.03153566877192982,
- "week": 0.22035793396534814,
- "month": 0.9588547937411096
+ "day": 0.02742357295906432,
+ "week": 0.1916243452108532,
+ "month": 0.833824853485064
},
"KEYWORDS": {
- "day": 0.0014062348538011697,
- "week": 0.009826175220660347,
- "month": 0.04275714082503557
+ "day": 0.0012317829239766082,
+ "week": 0.008607178816606734,
+ "month": 0.03745285917496444
},
"SUBHEADINGS": {
- "day": 0.0014062348538011697,
- "week": 0.009826175220660347,
- "month": 0.04275714082503557
+ "day": 0.0012317829239766082,
+ "week": 0.008607178816606734,
+ "month": 0.03745285917496444
},
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}
\ No newline at end of file
--
GitLab