refactor: Change import structure for Elo Evaluation and Aggregation …

…related types and fix elo qa eval notebook

TASK: IL-394

src/documentation/elo_qa_eval.ipynb

@@ -33,7 +33,7 @@
     "from dotenv import load_dotenv\n",
     "\n",
     "from intelligence_layer.connectors import LimitedConcurrencyClient\n",
-    "from intelligence_layer.evaluation.evaluation.elo_evaluator import Match\n",
+    "from intelligence_layer.evaluation.evaluation.evaluator.elo_evaluator import Matches\n",
     "\n",
     "load_dotenv()\n",
     "\n",
@@ -289,19 +289,20 @@
    "metadata": {},
    "outputs": [],
    "source": [
+    "from intelligence_layer.core.model import Llama3InstructModel\n",
     "from intelligence_layer.evaluation import Evaluator\n",
-    "from intelligence_layer.evaluation.evaluation.elo_evaluator import EloEvaluationLogic\n",
+    "from intelligence_layer.examples.qa.elo_qa import EloQaEvaluationLogic\n",
     "\n",
-    "elo_evaluation_logic: EloEvaluationLogic[\n",
-    "    SingleChunkQaInput, SingleChunkQaOutput, SingleChunkQaOutput\n",
-    "] = EloEvaluationLogic()\n",
+    "elo_qa_evaluation_logic = EloQaEvaluationLogic(\n",
+    "    model=Llama3InstructModel(name=\"llama-3-8b-instruct\")\n",
+    ")\n",
     "\n",
     "evaluator = Evaluator(\n",
     "    dataset_repository=dataset_repository,\n",
     "    run_repository=run_repository,\n",
     "    evaluation_repository=evaluation_repository,\n",
     "    description=\"ELO QA evaluation\",  # this description will be used later to query for specific evaluations\n",
-    "    evaluation_logic=elo_evaluation_logic,\n",
+    "    evaluation_logic=elo_qa_evaluation_logic,\n",
     ")"
    ]
   },
@@ -321,11 +322,14 @@
    "outputs": [],
    "source": [
     "# ensure that for each example there are evaluated comparisons\n",
+    "\n",
+    "\n",
     "for example_evaluation in evaluation_repository.example_evaluations(\n",
-    "    evaluation_overview.id, Match\n",
+    "    evaluation_overview.id, Matches\n",
     "):\n",
+    "    assert isinstance(example_evaluation.result, Matches)\n",
     "    assert (\n",
-    "        len(example_evaluation.result.matches) > 0\n",
+    "        len(example_evaluation.result.comparison_evaluations) > 0\n",
     "    ), f\"There are no matches (comparisons) for example ID {example_evaluation.example_id}\""
    ]
   },
@@ -374,17 +378,15 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from intelligence_layer_experiments.use_cases.elo_usecase.elo_qa_aggregator import (\n",
-    "    EloQaAggregationLogic,\n",
-    ")\n",
     "\n",
     "from intelligence_layer.evaluation import Aggregator\n",
+    "from intelligence_layer.evaluation.aggregation.elo_aggregation import MatchesAggregationLogic\n",
     "\n",
     "aggregator = Aggregator(\n",
     "    evaluation_repository=evaluation_repository,\n",
     "    aggregation_repository=aggregation_repository,\n",
     "    description=\"ELO QA aggregation\",\n",
-    "    aggregation_logic=EloQaAggregationLogic(),\n",
+    "    aggregation_logic=MatchesAggregationLogic(),\n",
     ")\n",
     "\n",
     "aggregated_evaluation = aggregator.aggregate_evaluation(evaluation_overview.id)"

src/intelligence_layer/evaluation/aggregation/elo_aggregation.py

@@ -5,10 +5,13 @@
 import numpy as np
 from pydantic import BaseModel
 
-from intelligence_layer.evaluation import ComparisonEvaluation, MatchOutcome
 from intelligence_layer.evaluation.aggregation.accumulator import MeanAccumulator
 from intelligence_layer.evaluation.aggregation.aggregator import AggregationLogic
-from intelligence_layer.evaluation.evaluation.evaluator.elo_evaluator import Matches
+from intelligence_layer.evaluation.evaluation.evaluator.elo_evaluator import (
+    ComparisonEvaluation,
+    Matches,
+    MatchOutcome,
+)
 
 
 class PlayerScore(BaseModel):

src/intelligence_layer/evaluation/evaluation/evaluator/argilla_evaluator.py

@@ -14,7 +14,6 @@
     RecordData,
 )
 from intelligence_layer.core import CompleteOutput, Input, InstructInput, Output
-from intelligence_layer.evaluation import ComparisonEvaluation, MatchOutcome
 from intelligence_layer.evaluation.dataset.dataset_repository import DatasetRepository
 from intelligence_layer.evaluation.dataset.domain import Example, ExpectedOutput
 from intelligence_layer.evaluation.evaluation.domain import (
@@ -31,6 +30,10 @@
 from intelligence_layer.evaluation.evaluation.evaluator.base_evaluator import (
     EvaluationLogicBase,
 )
+from intelligence_layer.evaluation.evaluation.evaluator.elo_evaluator import (
+    ComparisonEvaluation,
+    MatchOutcome,
+)
 from intelligence_layer.evaluation.run.domain import SuccessfulExampleOutput
 from intelligence_layer.evaluation.run.run_repository import RunRepository
 

src/intelligence_layer/evaluation/evaluation/evaluator/elo_evaluator.py

@@ -6,8 +6,8 @@
 from pydantic import BaseModel
 
 from intelligence_layer.core import Input, Output
-from intelligence_layer.evaluation import EvaluationLogic
 from intelligence_layer.evaluation.dataset.domain import Example, ExpectedOutput
+from intelligence_layer.evaluation.evaluation.evaluator.evaluator import EvaluationLogic
 from intelligence_layer.evaluation.run.domain import SuccessfulExampleOutput