fix: add currying to question_answering_non_parallel (#602)

…l to avoid additional params

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

Introduces lambda currying in question answering non parallel function
to avoid unnecessary params

## 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
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## Summary by CodeRabbit

- **Refactor**
- Streamlined the question-answering process for cleaner, more efficient
query handling.
- Updated the handling of parameters in the answer generation process,
allowing for a more dynamic integration of context.
- Simplified test setups by reducing the number of parameters involved
in the mock answer resolver.
<!-- end of auto-generated comment: release notes by coderabbit.ai -->

cognee/eval_framework/answer_generation/answer_generation_executor.py

@@ -2,7 +2,7 @@ import cognee
 from typing import List, Dict, Callable, Awaitable
 from cognee.api.v1.search import SearchType
 
-question_answering_engine_options: Dict[str, Callable[[str], Awaitable[List[str]]]] = {
+question_answering_engine_options: Dict[str, Callable[[str, str], Awaitable[List[str]]]] = {
     "cognee_graph_completion": lambda query, system_prompt_path: cognee.search(
         query_type=SearchType.GRAPH_COMPLETION,
         query_text=query,
@@ -24,14 +24,13 @@ class AnswerGeneratorExecutor:
         self,
         questions: List[Dict[str, str]],
         answer_resolver: Callable[[str], Awaitable[List[str]]],
-        system_prompt: str = "answer_simple_question.txt",
     ) -> List[Dict[str, str]]:
         answers = []
         for instance in questions:
             query_text = instance["question"]
             correct_answer = instance["answer"]
 
-            search_results = await answer_resolver(query_text, system_prompt)
+            search_results = await answer_resolver(query_text)
 
             answers.append(
                 {

cognee/eval_framework/answer_generation/run_question_answering_module.py

@@ -48,8 +48,9 @@ async def run_question_answering(
         answer_generator = AnswerGeneratorExecutor()
         answers = await answer_generator.question_answering_non_parallel(
             questions=questions,
-            answer_resolver=question_answering_engine_options[params["qa_engine"]],
-            system_prompt=system_prompt,
+            answer_resolver=lambda query: question_answering_engine_options[params["qa_engine"]](
+                query, system_prompt
+            ),
         )
         with open(params["answers_path"], "w", encoding="utf-8") as f:
             json.dump(answers, f, ensure_ascii=False, indent=4)

cognee/tests/unit/eval_framework/answer_generation_test.py

@@ -12,11 +12,11 @@ async def test_answer_generation():
     corpus_list, qa_pairs = DummyAdapter().load_corpus(limit=limit)
 
     mock_answer_resolver = AsyncMock()
-    mock_answer_resolver.side_effect = lambda query, system_prompt: ["mock_answer"]
+    mock_answer_resolver.side_effect = lambda query: ["mock_answer"]
 
     answer_generator = AnswerGeneratorExecutor()
     answers = await answer_generator.question_answering_non_parallel(
-        questions=qa_pairs, answer_resolver=mock_answer_resolver, system_prompt="test.txt"
+        questions=qa_pairs, answer_resolver=mock_answer_resolver
     )
 
     assert len(answers) == len(qa_pairs)