mvp ok

apps/go/requester/activities/update_task_tree.go

@@ -2,12 +2,13 @@ package activities
 
 import (
 	"context"
+	"requester/common"
+	"requester/types"
+
 	"go.mongodb.org/mongo-driver/bson"
 	"go.mongodb.org/mongo-driver/bson/primitive"
 	"go.mongodb.org/mongo-driver/mongo"
 	"go.temporal.io/sdk/temporal"
-	"requester/common"
-	"requester/types"
 )
 
 type UpdateTaskTreeRequest struct {

apps/python/evaluator/activities/signatures/tokenizer_evaluate.py

@@ -137,7 +137,7 @@ async def tokenizer_evaluate(args: PocketNetworkEvaluationTaskRequest) -> bool:
         try:
             async with mongo_client.start_transaction() as session:
                 await mongo_client.db["results"].find_one_and_update(
-                    {"results_data.task_id": args.task_id},
+                    {"result_data.task_id": args.task_id},
                     {"$set": result.model_dump(by_alias=True)},
                     session=session,
                 )

docker-compose/morse-poc/dependencies_configs/mongodb/init-db.js

@@ -27,7 +27,7 @@ db.createCollection('nodes');
 db.nodes.createIndex({address: 1, service: 1}, {unique: true});
 
 db.createCollection('results');
-db.nodes.createIndex({'results_data.task_id': 1}, {unique: true});
+db.nodes.createIndex({'result_data.task_id': 1}, {unique: true});
 
 db.createCollection('buffers_numerical');
 db.buffers_numerical.createIndex({"task_data.node_id": 1, "task_data.framework": 1, "task_data.task": 1}, {unique: true});

docker-compose/morse-poc/dependencies_configs/temporal/initialize.sh

@@ -6,8 +6,8 @@ sleep 3
 
 
 all_services="A100,A101,A102,A103"
-two_services="A100,A101"
-one_services="A100,A102,A103"
+two_services="A100,A103"
+one_services="A100"
 # change this if you want a different set of datasets, by default it create everything
 keys_services=$one_services
 
@@ -16,7 +16,6 @@ keys_services_array=(${keys_services//,/ })
 everything="arc_challenge,hellaswag,truthfulqa_mc2,mmlu_abstract_algebra,mmlu_anatomy,mmlu_astronomy,mmlu_business_ethics,mmlu_clinical_knowledge,mmlu_college_biology,mmlu_college_chemistry,mmlu_college_computer_science,mmlu_college_mathematics,mmlu_college_medicine,mmlu_college_physics,mmlu_computer_security,mmlu_conceptual_physics,mmlu_econometrics,mmlu_electrical_engineering,mmlu_elementary_mathematics,mmlu_formal_logic,mmlu_global_facts,mmlu_high_school_biology,mmlu_high_school_chemistry,mmlu_high_school_computer_science,mmlu_high_school_european_history,mmlu_high_school_geography,mmlu_high_school_government_and_politics,mmlu_high_school_macroeconomics,mmlu_high_school_mathematics,mmlu_high_school_microeconomics,mmlu_high_school_physics,mmlu_high_school_psychology,mmlu_high_school_statistics,mmlu_high_school_us_history,mmlu_high_school_world_history,mmlu_human_aging,mmlu_human_sexuality,mmlu_international_law,mmlu_jurisprudence,mmlu_logical_fallacies,mmlu_machine_learning,mmlu_management,mmlu_marketing,mmlu_medical_genetics,mmlu_miscellaneous,mmlu_moral_disputes,mmlu_moral_scenarios,mmlu_nutrition,mmlu_philosophy,mmlu_prehistory,mmlu_professional_accounting,mmlu_professional_law,mmlu_professional_medicine,mmlu_professional_psychology,mmlu_public_relations,mmlu_security_studies,mmlu_sociology,mmlu_us_foreign_policy,mmlu_virology,mmlu_world_religions,winogrande,gsm8k"
 mmlu="mmlu_abstract_algebra,mmlu_anatomy,mmlu_astronomy,mmlu_business_ethics,mmlu_clinical_knowledge,mmlu_college_biology,mmlu_college_chemistry,mmlu_college_computer_science,mmlu_college_mathematics,mmlu_college_medicine,mmlu_college_physics,mmlu_computer_security,mmlu_conceptual_physics,mmlu_econometrics,mmlu_electrical_engineering,mmlu_elementary_mathematics,mmlu_formal_logic,mmlu_global_facts,mmlu_high_school_biology,mmlu_high_school_chemistry,mmlu_high_school_computer_science,mmlu_high_school_european_history,mmlu_high_school_geography,mmlu_high_school_government_and_politics,mmlu_high_school_macroeconomics,mmlu_high_school_mathematics,mmlu_high_school_microeconomics,mmlu_high_school_physics,mmlu_high_school_psychology,mmlu_high_school_statistics,mmlu_high_school_us_history,mmlu_high_school_world_history,mmlu_human_aging,mmlu_human_sexuality,mmlu_international_law,mmlu_jurisprudence,mmlu_logical_fallacies,mmlu_machine_learning,mmlu_management,mmlu_marketing,mmlu_medical_genetics,mmlu_miscellaneous,mmlu_moral_disputes,mmlu_moral_scenarios,mmlu_nutrition,mmlu_philosophy,mmlu_prehistory,mmlu_professional_accounting,mmlu_professional_law,mmlu_professional_medicine,mmlu_professional_psychology,mmlu_public_relations,mmlu_security_studies,mmlu_sociology,mmlu_us_foreign_policy,mmlu_virology,mmlu_world_religions"
 heavy="arc_challenge,hellaswag,truthfulqa_mc2,winogrande,gsm8k"
-some="mmlu_philosophy,mmlu_anatomy,mmlu_medical_genetics,mmlu_high_school_psychology,mmlu_human_sexuality,mmlu_professional_law,mmlu_moral_disputes,mmlu_virology,mmlu_international_law,mmlu_professional_psychology,mmlu_high_school_world_history,mmlu_professional_medicine,mmlu_professional_accounting,mmlu_miscellaneous,mmlu_us_foreign_policy,mmlu_high_school_chemistry,mmlu_security_studies,mmlu_high_school_european_history,mmlu_sociology,mmlu_high_school_us_history"
 one="gsm8k"
 # change this if you want a different set of datasets, by default it create everything
 keys=$one

packages/python/lmeh/utils/generator.py

@@ -353,14 +353,14 @@ async def save_results(
                 for result in insert_mongo_results:
                     bulk_op.append(
                         UpdateOne(
-                            {'results_data.task_id': result['results_data']['task_id']},
+                            {'result_data.task_id': result['result_data']['task_id']},
                             {'$set': result},
                             upsert=True
                         )
                     )
                     bulk_task_op.append(
                         UpdateOne(
-                            {'_id': result['results_data']['task_id']},
+                            {'_id': result['result_data']['task_id']},
                             {'$set': {"evaluated": True}},
                         )
                     )