Test: Parse context pieces separately in MusiqueQAAdapter and adjust tests [cog-1234] (#561)

<!-- .github/pull_request_template.md -->

## Description
<!-- Provide a clear description of the changes in this PR -->

## DCO Affirmation
I affirm that all code in every commit of this pull request conforms to
the terms of the Topoteretes Developer Certificate of Origin


<!-- This is an auto-generated comment: release notes by coderabbit.ai
-->
## Summary by CodeRabbit

- **Tests**
- Updated evaluation checks by removing assertions related to the
relationship between `corpus_list` and `qa_pairs`, now focusing solely
on `qa_pairs` limits.

- **Refactor**
- Improved content processing to append each paragraph individually to
`corpus_list`, enhancing clarity in data structure.
- Simplified type annotations in the `load_corpus` method across
multiple adapters, ensuring consistency in return types.

- **Chores**
- Updated dependency installation commands in GitHub Actions workflows
for Python 3.10, 3.11, and 3.12 to include additional evaluation-related
dependencies.
<!-- end of auto-generated comment: release notes by coderabbit.ai -->

---------

Co-authored-by: Vasilije <8619304+Vasilije1990@users.noreply.github.com>

.github/workflows/test_python_3_10.yml

@@ -47,7 +47,7 @@ jobs:
           installer-parallel: true
 
       - name: Install dependencies
-        run: poetry install --no-interaction -E docs
+        run: poetry install --no-interaction -E docs -E evals
       - name: Download NLTK tokenizer data
         run: |
           poetry run python -m nltk.downloader punkt_tab averaged_perceptron_tagger_eng

.github/workflows/test_python_3_11.yml

@@ -48,7 +48,7 @@ jobs:
           installer-parallel: true
 
       - name: Install dependencies
-        run: poetry install --no-interaction -E docs
+        run: poetry install --no-interaction -E docs -E evals
 
       - name: Download NLTK tokenizer data
         run: |

.github/workflows/test_python_3_12.yml

@@ -48,7 +48,7 @@ jobs:
           installer-parallel: true
 
       - name: Install dependencies
-        run: poetry install --no-interaction -E docs
+        run: poetry install --no-interaction -E docs -E evals
       - name: Download NLTK tokenizer data
         run: |
           poetry run python -m nltk.downloader punkt_tab averaged_perceptron_tagger_eng

cognee/tests/unit/eval_framework/benchmark_adapters_test.py

@@ -1,5 +1,4 @@
 import pytest
-import random
 from evals.eval_framework.benchmark_adapters.hotpot_qa_adapter import HotpotQAAdapter
 from evals.eval_framework.benchmark_adapters.musique_adapter import MusiqueQAAdapter
 from evals.eval_framework.benchmark_adapters.dummy_adapter import DummyAdapter
@@ -46,12 +45,6 @@ def test_adapter_returns_some_content(AdapterClass):
     assert len(corpus_list) > 0, f"{AdapterClass.__name__} returned an empty corpus_list."
     assert len(qa_pairs) > 0, f"{AdapterClass.__name__} returned an empty question_answer_pairs."
 
-    # Check the shape
-    assert len(corpus_list) == len(qa_pairs), (
-        f"{AdapterClass.__name__} corpus_list and question_answer_pairs "
-        "should typically be the same length. Adjust if your adapter differs."
-    )
-
     for item in qa_pairs:
         assert "question" in item, f"{AdapterClass.__name__} missing 'question' key in QA pair."
         assert "answer" in item, f"{AdapterClass.__name__} missing 'answer' key in QA pair."
@@ -70,9 +63,7 @@ def test_adapter_limit(AdapterClass):
 
     # Confirm that we didn't receive more than 'limit'
     # (Some adapters might be allowed to return fewer if the dataset is small)
-    assert len(corpus_list) <= limit, (
+
-        f"{AdapterClass.__name__} returned more items than requested limit={limit}."
-    )
     assert len(qa_pairs) <= limit, (
         f"{AdapterClass.__name__} returned more QA items than requested limit={limit}."
     )

evals/eval_framework/benchmark_adapters/dummy_adapter.py

@@ -1,4 +1,4 @@
-from typing import Optional, Union, Any, LiteralString
+from typing import Optional
 
 from evals.eval_framework.benchmark_adapters.base_benchmark_adapter import BaseBenchmarkAdapter
 
@@ -6,7 +6,7 @@ from evals.eval_framework.benchmark_adapters.base_benchmark_adapter import BaseB
 class DummyAdapter(BaseBenchmarkAdapter):
     def load_corpus(
         self, limit: Optional[int] = None, seed: int = 42
-    ) -> tuple[list[Union[LiteralString, str]], list[dict[str, str]]]:
+    ) -> tuple[list[str], list[dict[str, str]]]:
         corpus_list = [
             "The cognee is an AI memory engine that supports different vector and graph databases",
             "Neo4j is a graph database supported by cognee",

evals/eval_framework/benchmark_adapters/hotpot_qa_adapter.py

@@ -2,7 +2,7 @@ import requests
 import os
 import json
 import random
-from typing import Optional, Union, Any, LiteralString
+from typing import Optional, Any
 from evals.eval_framework.benchmark_adapters.base_benchmark_adapter import BaseBenchmarkAdapter
 
 
@@ -16,7 +16,7 @@ class HotpotQAAdapter(BaseBenchmarkAdapter):
 
     def load_corpus(
         self, limit: Optional[int] = None, seed: int = 42
-    ) -> tuple[list[Union[LiteralString, str]], list[dict[str, Any]]]:
+    ) -> tuple[list[str], list[dict[str, Any]]]:
         filename = self.dataset_info["filename"]
 
         if os.path.exists(filename):

evals/eval_framework/benchmark_adapters/musique_adapter.py

@@ -1,7 +1,7 @@
 import os
 import json
 import random
-from typing import Optional, Union, Any, LiteralString
+from typing import Optional, Any
 import zipfile
 
 import gdown
@@ -64,8 +64,8 @@ class MusiqueQAAdapter(BaseBenchmarkAdapter):
         for item in data:
             # Each 'paragraphs' is a list of dicts; we can concatenate their 'paragraph_text'
             paragraphs = item.get("paragraphs", [])
-            combined_paragraphs = " ".join(paragraph["paragraph_text"] for paragraph in paragraphs)
+            for paragraph in paragraphs:
-            corpus_list.append(combined_paragraphs)
+                corpus_list.append(paragraph["paragraph_text"])
 
             question = item.get("question", "")
             answer = item.get("answer", "")

evals/eval_framework/benchmark_adapters/twowikimultihop_adapter.py

@@ -2,7 +2,7 @@ import requests
 import os
 import json
 import random
-from typing import Optional, Union, Any, LiteralString
+from typing import Optional, Any
 from evals.eval_framework.benchmark_adapters.base_benchmark_adapter import BaseBenchmarkAdapter
 
 
@@ -14,7 +14,7 @@ class TwoWikiMultihopAdapter(BaseBenchmarkAdapter):
 
     def load_corpus(
         self, limit: Optional[int] = None, seed: int = 42
-    ) -> tuple[list[Union[LiteralString, str]], list[dict[str, Any]]]:
+    ) -> tuple[list[str], list[dict[str, Any]]]:
         filename = self.dataset_info["filename"]
 
         if os.path.exists(filename):