diff --git a/cognee/modules/retrieval/EntityCompletionRetriever.py b/cognee/modules/retrieval/EntityCompletionRetriever.py
index 6086977ce..14996f902 100644
--- a/cognee/modules/retrieval/EntityCompletionRetriever.py
+++ b/cognee/modules/retrieval/EntityCompletionRetriever.py
@@ -1,5 +1,5 @@
 import asyncio
-from typing import Any, Optional, List
+from typing import Any, Optional, List, Type
 from cognee.shared.logging_utils import get_logger
 
 from cognee.infrastructure.entities.BaseEntityExtractor import BaseEntityExtractor
@@ -85,8 +85,12 @@ class EntityCompletionRetriever(BaseRetriever):
             return None
 
     async def get_completion(
-        self, query: str, context: Optional[Any] = None, session_id: Optional[str] = None
-    ) -> List[str]:
+        self,
+        query: str,
+        context: Optional[Any] = None,
+        session_id: Optional[str] = None,
+        response_model: Type = str,
+    ) -> List[Any]:
         """
         Generate completion using provided context or fetch new context.
 
@@ -102,6 +106,7 @@ class EntityCompletionRetriever(BaseRetriever):
               fetched if not provided. (default None)
             - session_id (Optional[str]): Optional session identifier for caching. If None,
               defaults to 'default_session'. (default None)
+            - response_model (Type): The Pydantic model type for structured output. (default str)
 
         Returns:
         --------
@@ -133,6 +138,7 @@ class EntityCompletionRetriever(BaseRetriever):
                         user_prompt_path=self.user_prompt_path,
                         system_prompt_path=self.system_prompt_path,
                         conversation_history=conversation_history,
+                        response_model=response_model,
                     ),
                 )
             else:
@@ -141,6 +147,7 @@ class EntityCompletionRetriever(BaseRetriever):
                     context=context,
                     user_prompt_path=self.user_prompt_path,
                     system_prompt_path=self.system_prompt_path,
+                    response_model=response_model,
                 )
 
             if session_save:
diff --git a/cognee/modules/retrieval/base_graph_retriever.py b/cognee/modules/retrieval/base_graph_retriever.py
index b0abc2991..b203309ba 100644
--- a/cognee/modules/retrieval/base_graph_retriever.py
+++ b/cognee/modules/retrieval/base_graph_retriever.py
@@ -1,4 +1,4 @@
-from typing import List, Optional
+from typing import Any, List, Optional, Type
 from abc import ABC, abstractmethod
 
 from cognee.modules.graph.cognee_graph.CogneeGraphElements import Edge
@@ -14,7 +14,11 @@ class BaseGraphRetriever(ABC):
 
     @abstractmethod
     async def get_completion(
-        self, query: str, context: Optional[List[Edge]] = None, session_id: Optional[str] = None
-    ) -> str:
+        self,
+        query: str,
+        context: Optional[List[Edge]] = None,
+        session_id: Optional[str] = None,
+        response_model: Type = str,
+    ) -> List[Any]:
         """Generates a response using the query and optional context (triplets)."""
         pass
diff --git a/cognee/modules/retrieval/base_retriever.py b/cognee/modules/retrieval/base_retriever.py
index 1533dd44f..b88c741b8 100644
--- a/cognee/modules/retrieval/base_retriever.py
+++ b/cognee/modules/retrieval/base_retriever.py
@@ -1,5 +1,5 @@
 from abc import ABC, abstractmethod
-from typing import Any, Optional
+from typing import Any, Optional, Type, List
 
 
 class BaseRetriever(ABC):
@@ -12,7 +12,11 @@ class BaseRetriever(ABC):
 
     @abstractmethod
     async def get_completion(
-        self, query: str, context: Optional[Any] = None, session_id: Optional[str] = None
-    ) -> Any:
+        self,
+        query: str,
+        context: Optional[Any] = None,
+        session_id: Optional[str] = None,
+        response_model: Type = str,
+    ) -> List[Any]:
         """Generates a response using the query and optional context."""
         pass
diff --git a/cognee/modules/retrieval/completion_retriever.py b/cognee/modules/retrieval/completion_retriever.py
index bb568924d..126ebcab8 100644
--- a/cognee/modules/retrieval/completion_retriever.py
+++ b/cognee/modules/retrieval/completion_retriever.py
@@ -1,5 +1,5 @@
 import asyncio
-from typing import Any, Optional
+from typing import Any, Optional, Type, List
 
 from cognee.shared.logging_utils import get_logger
 from cognee.infrastructure.databases.vector import get_vector_engine
@@ -75,8 +75,12 @@ class CompletionRetriever(BaseRetriever):
             raise NoDataError("No data found in the system, please add data first.") from error
 
     async def get_completion(
-        self, query: str, context: Optional[Any] = None, session_id: Optional[str] = None
-    ) -> str:
+        self,
+        query: str,
+        context: Optional[Any] = None,
+        session_id: Optional[str] = None,
+        response_model: Type = str,
+    ) -> List[Any]:
         """
         Generates an LLM completion using the context.
 
@@ -91,6 +95,7 @@ class CompletionRetriever(BaseRetriever):
               completion; if None, it retrieves the context for the query. (default None)
             - session_id (Optional[str]): Optional session identifier for caching. If None,
               defaults to 'default_session'. (default None)
+            - response_model (Type): The Pydantic model type for structured output. (default str)
 
         Returns:
         --------
@@ -118,6 +123,7 @@ class CompletionRetriever(BaseRetriever):
                     system_prompt_path=self.system_prompt_path,
                     system_prompt=self.system_prompt,
                     conversation_history=conversation_history,
+                    response_model=response_model,
                 ),
             )
         else:
@@ -127,6 +133,7 @@ class CompletionRetriever(BaseRetriever):
                 user_prompt_path=self.user_prompt_path,
                 system_prompt_path=self.system_prompt_path,
                 system_prompt=self.system_prompt,
+                response_model=response_model,
             )
 
         if session_save:
@@ -137,4 +144,4 @@ class CompletionRetriever(BaseRetriever):
                 session_id=session_id,
             )
 
-        return completion
+        return [completion]
diff --git a/cognee/modules/retrieval/graph_completion_context_extension_retriever.py b/cognee/modules/retrieval/graph_completion_context_extension_retriever.py
index 58b6b586f..b07d11fd2 100644
--- a/cognee/modules/retrieval/graph_completion_context_extension_retriever.py
+++ b/cognee/modules/retrieval/graph_completion_context_extension_retriever.py
@@ -1,5 +1,5 @@
 import asyncio
-from typing import Optional, List, Type
+from typing import Optional, List, Type, Any
 from cognee.modules.graph.cognee_graph.CogneeGraphElements import Edge
 from cognee.shared.logging_utils import get_logger
 from cognee.modules.retrieval.graph_completion_retriever import GraphCompletionRetriever
@@ -56,7 +56,8 @@ class GraphCompletionContextExtensionRetriever(GraphCompletionRetriever):
         context: Optional[List[Edge]] = None,
         session_id: Optional[str] = None,
         context_extension_rounds=4,
-    ) -> List[str]:
+        response_model: Type = str,
+    ) -> List[Any]:
         """
         Extends the context for a given query by retrieving related triplets and generating new
         completions based on them.
@@ -76,6 +77,7 @@ class GraphCompletionContextExtensionRetriever(GraphCompletionRetriever):
               defaults to 'default_session'. (default None)
             - context_extension_rounds: The maximum number of rounds to extend the context with
               new triplets before halting. (default 4)
+            - response_model (Type): The Pydantic model type for structured output. (default str)
 
         Returns:
         --------
@@ -143,6 +145,7 @@ class GraphCompletionContextExtensionRetriever(GraphCompletionRetriever):
                     system_prompt_path=self.system_prompt_path,
                     system_prompt=self.system_prompt,
                     conversation_history=conversation_history,
+                    response_model=response_model,
                 ),
             )
         else:
@@ -152,6 +155,7 @@ class GraphCompletionContextExtensionRetriever(GraphCompletionRetriever):
                 user_prompt_path=self.user_prompt_path,
                 system_prompt_path=self.system_prompt_path,
                 system_prompt=self.system_prompt,
+                response_model=response_model,
             )
 
         if self.save_interaction and context_text and triplets and completion:
diff --git a/cognee/modules/retrieval/graph_completion_cot_retriever.py b/cognee/modules/retrieval/graph_completion_cot_retriever.py
index 299db6855..eb8f502cb 100644
--- a/cognee/modules/retrieval/graph_completion_cot_retriever.py
+++ b/cognee/modules/retrieval/graph_completion_cot_retriever.py
@@ -7,7 +7,7 @@ from cognee.shared.logging_utils import get_logger
 
 from cognee.modules.retrieval.graph_completion_retriever import GraphCompletionRetriever
 from cognee.modules.retrieval.utils.completion import (
-    generate_structured_completion,
+    generate_completion,
     summarize_text,
 )
 from cognee.modules.retrieval.utils.session_cache import (
@@ -44,7 +44,6 @@ class GraphCompletionCotRetriever(GraphCompletionRetriever):
     questions based on reasoning. The public methods are:
 
     - get_completion
-    - get_structured_completion
 
     Instance variables include:
     - validation_system_prompt_path
@@ -121,7 +120,7 @@ class GraphCompletionCotRetriever(GraphCompletionRetriever):
                 triplets += await self.get_context(followup_question)
                 context_text = await self.resolve_edges_to_text(list(set(triplets)))
 
-            completion = await generate_structured_completion(
+            completion = await generate_completion(
                 query=query,
                 context=context_text,
                 user_prompt_path=self.user_prompt_path,
@@ -165,24 +164,28 @@ class GraphCompletionCotRetriever(GraphCompletionRetriever):
 
         return completion, context_text, triplets
 
-    async def get_structured_completion(
+    async def get_completion(
         self,
         query: str,
         context: Optional[List[Edge]] = None,
         session_id: Optional[str] = None,
-        max_iter: int = 4,
+        max_iter=4,
         response_model: Type = str,
-    ) -> Any:
+    ) -> List[Any]:
         """
-        Generate structured completion responses based on a user query and contextual information.
+        Generate completion responses based on a user query and contextual information.
 
-        This method applies the same chain-of-thought logic as get_completion but returns
+        This method interacts with a language model client to retrieve a structured response,
+        using a series of iterations to refine the answers and generate follow-up questions
+        based on reasoning derived from previous outputs. It raises exceptions if the context
+        retrieval fails or if the model encounters issues in generating outputs. It returns
         structured output using the provided response model.
 
         Parameters:
         -----------
+
             - query (str): The user's query to be processed and answered.
-            - context (Optional[List[Edge]]): Optional context that may assist in answering the query.
+            - context (Optional[Any]): Optional context that may assist in answering the query.
               If not provided, it will be fetched based on the query. (default None)
             - session_id (Optional[str]): Optional session identifier for caching. If None,
               defaults to 'default_session'. (default None)
@@ -192,7 +195,8 @@ class GraphCompletionCotRetriever(GraphCompletionRetriever):
 
         Returns:
         --------
-            - Any: The generated structured completion based on the response model.
+
+            - List[str]: A list containing the generated answer to the user's query.
         """
         # Check if session saving is enabled
         cache_config = CacheConfig()
@@ -228,45 +232,4 @@ class GraphCompletionCotRetriever(GraphCompletionRetriever):
                 session_id=session_id,
             )
 
-        return completion
-
-    async def get_completion(
-        self,
-        query: str,
-        context: Optional[List[Edge]] = None,
-        session_id: Optional[str] = None,
-        max_iter=4,
-    ) -> List[str]:
-        """
-        Generate completion responses based on a user query and contextual information.
-
-        This method interacts with a language model client to retrieve a structured response,
-        using a series of iterations to refine the answers and generate follow-up questions
-        based on reasoning derived from previous outputs. It raises exceptions if the context
-        retrieval fails or if the model encounters issues in generating outputs.
-
-        Parameters:
-        -----------
-
-            - query (str): The user's query to be processed and answered.
-            - context (Optional[Any]): Optional context that may assist in answering the query.
-              If not provided, it will be fetched based on the query. (default None)
-            - session_id (Optional[str]): Optional session identifier for caching. If None,
-              defaults to 'default_session'. (default None)
-            - max_iter: The maximum number of iterations to refine the answer and generate
-              follow-up questions. (default 4)
-
-        Returns:
-        --------
-
-            - List[str]: A list containing the generated answer to the user's query.
-        """
-        completion = await self.get_structured_completion(
-            query=query,
-            context=context,
-            session_id=session_id,
-            max_iter=max_iter,
-            response_model=str,
-        )
-
         return [completion]
diff --git a/cognee/modules/retrieval/graph_completion_retriever.py b/cognee/modules/retrieval/graph_completion_retriever.py
index b7ab4edae..df77a11ac 100644
--- a/cognee/modules/retrieval/graph_completion_retriever.py
+++ b/cognee/modules/retrieval/graph_completion_retriever.py
@@ -146,7 +146,8 @@ class GraphCompletionRetriever(BaseGraphRetriever):
         query: str,
         context: Optional[List[Edge]] = None,
         session_id: Optional[str] = None,
-    ) -> List[str]:
+        response_model: Type = str,
+    ) -> List[Any]:
         """
         Generates a completion using graph connections context based on a query.
 
@@ -188,6 +189,7 @@ class GraphCompletionRetriever(BaseGraphRetriever):
                     system_prompt_path=self.system_prompt_path,
                     system_prompt=self.system_prompt,
                     conversation_history=conversation_history,
+                    response_model=response_model,
                 ),
             )
         else:
@@ -197,6 +199,7 @@ class GraphCompletionRetriever(BaseGraphRetriever):
                 user_prompt_path=self.user_prompt_path,
                 system_prompt_path=self.system_prompt_path,
                 system_prompt=self.system_prompt,
+                response_model=response_model,
             )
 
         if self.save_interaction and context and triplets and completion:
diff --git a/cognee/modules/retrieval/temporal_retriever.py b/cognee/modules/retrieval/temporal_retriever.py
index ec68d37bb..f3da02c15 100644
--- a/cognee/modules/retrieval/temporal_retriever.py
+++ b/cognee/modules/retrieval/temporal_retriever.py
@@ -146,8 +146,12 @@ class TemporalRetriever(GraphCompletionRetriever):
         return self.descriptions_to_string(top_k_events)
 
     async def get_completion(
-        self, query: str, context: Optional[str] = None, session_id: Optional[str] = None
-    ) -> List[str]:
+        self,
+        query: str,
+        context: Optional[str] = None,
+        session_id: Optional[str] = None,
+        response_model: Type = str,
+    ) -> List[Any]:
         """
         Generates a response using the query and optional context.
 
@@ -159,6 +163,7 @@ class TemporalRetriever(GraphCompletionRetriever):
               retrieved based on the query. (default None)
             - session_id (Optional[str]): Optional session identifier for caching. If None,
               defaults to 'default_session'. (default None)
+            - response_model (Type): The Pydantic model type for structured output. (default str)
 
         Returns:
         --------
@@ -186,6 +191,7 @@ class TemporalRetriever(GraphCompletionRetriever):
                         user_prompt_path=self.user_prompt_path,
                         system_prompt_path=self.system_prompt_path,
                         conversation_history=conversation_history,
+                        response_model=response_model,
                     ),
                 )
             else:
@@ -194,6 +200,7 @@ class TemporalRetriever(GraphCompletionRetriever):
                     context=context,
                     user_prompt_path=self.user_prompt_path,
                     system_prompt_path=self.system_prompt_path,
+                    response_model=response_model,
                 )
 
             if session_save:
diff --git a/cognee/modules/retrieval/utils/completion.py b/cognee/modules/retrieval/utils/completion.py
index db7a10252..c90ce77f4 100644
--- a/cognee/modules/retrieval/utils/completion.py
+++ b/cognee/modules/retrieval/utils/completion.py
@@ -3,7 +3,7 @@ from cognee.infrastructure.llm.LLMGateway import LLMGateway
 from cognee.infrastructure.llm.prompts import render_prompt, read_query_prompt
 
 
-async def generate_structured_completion(
+async def generate_completion(
     query: str,
     context: str,
     user_prompt_path: str,
@@ -12,7 +12,7 @@ async def generate_structured_completion(
     conversation_history: Optional[str] = None,
     response_model: Type = str,
 ) -> Any:
-    """Generates a structured completion using LLM with given context and prompts."""
+    """Generates a completion using LLM with given context and prompts."""
     args = {"question": query, "context": context}
     user_prompt = render_prompt(user_prompt_path, args)
     system_prompt = system_prompt if system_prompt else read_query_prompt(system_prompt_path)
@@ -28,26 +28,6 @@ async def generate_structured_completion(
     )
 
 
-async def generate_completion(
-    query: str,
-    context: str,
-    user_prompt_path: str,
-    system_prompt_path: str,
-    system_prompt: Optional[str] = None,
-    conversation_history: Optional[str] = None,
-) -> str:
-    """Generates a completion using LLM with given context and prompts."""
-    return await generate_structured_completion(
-        query=query,
-        context=context,
-        user_prompt_path=user_prompt_path,
-        system_prompt_path=system_prompt_path,
-        system_prompt=system_prompt,
-        conversation_history=conversation_history,
-        response_model=str,
-    )
-
-
 async def summarize_text(
     text: str,
     system_prompt_path: str = "summarize_search_results.txt",
diff --git a/cognee/tasks/feedback/generate_improved_answers.py b/cognee/tasks/feedback/generate_improved_answers.py
index e439cf9e5..d2b143d29 100644
--- a/cognee/tasks/feedback/generate_improved_answers.py
+++ b/cognee/tasks/feedback/generate_improved_answers.py
@@ -61,7 +61,7 @@ async def _generate_improved_answer_for_single_interaction(
         )
 
         retrieved_context = await retriever.get_context(query_text)
-        completion = await retriever.get_structured_completion(
+        completion = await retriever.get_completion(
             query=query_text,
             context=retrieved_context,
             response_model=ImprovedAnswerResponse,
@@ -70,9 +70,9 @@ async def _generate_improved_answer_for_single_interaction(
         new_context_text = await retriever.resolve_edges_to_text(retrieved_context)
 
         if completion:
-            enrichment.improved_answer = completion.answer
+            enrichment.improved_answer = completion[0].answer
             enrichment.new_context = new_context_text
-            enrichment.explanation = completion.explanation
+            enrichment.explanation = completion[0].explanation
             return enrichment
         else:
             logger.warning(
diff --git a/cognee/tests/unit/modules/retrieval/graph_completion_retriever_cot_test.py b/cognee/tests/unit/modules/retrieval/graph_completion_retriever_cot_test.py
index 7fcfe0d6b..206cfaf84 100644
--- a/cognee/tests/unit/modules/retrieval/graph_completion_retriever_cot_test.py
+++ b/cognee/tests/unit/modules/retrieval/graph_completion_retriever_cot_test.py
@@ -2,7 +2,6 @@ import os
 import pytest
 import pathlib
 from typing import Optional, Union
-from pydantic import BaseModel
 
 import cognee
 from cognee.low_level import setup, DataPoint
@@ -11,11 +10,6 @@ from cognee.tasks.storage import add_data_points
 from cognee.modules.retrieval.graph_completion_cot_retriever import GraphCompletionCotRetriever
 
 
-class TestAnswer(BaseModel):
-    answer: str
-    explanation: str
-
-
 class TestGraphCompletionCoTRetriever:
     @pytest.mark.asyncio
     async def test_graph_completion_cot_context_simple(self):
@@ -174,48 +168,3 @@ class TestGraphCompletionCoTRetriever:
         assert all(isinstance(item, str) and item.strip() for item in answer), (
             "Answer must contain only non-empty strings"
         )
-
-    @pytest.mark.asyncio
-    async def test_get_structured_completion(self):
-        system_directory_path = os.path.join(
-            pathlib.Path(__file__).parent, ".cognee_system/test_get_structured_completion"
-        )
-        cognee.config.system_root_directory(system_directory_path)
-        data_directory_path = os.path.join(
-            pathlib.Path(__file__).parent, ".data_storage/test_get_structured_completion"
-        )
-        cognee.config.data_root_directory(data_directory_path)
-
-        await cognee.prune.prune_data()
-        await cognee.prune.prune_system(metadata=True)
-        await setup()
-
-        class Company(DataPoint):
-            name: str
-
-        class Person(DataPoint):
-            name: str
-            works_for: Company
-
-        company1 = Company(name="Figma")
-        person1 = Person(name="Steve Rodger", works_for=company1)
-
-        entities = [company1, person1]
-        await add_data_points(entities)
-
-        retriever = GraphCompletionCotRetriever()
-
-        # Test with string response model (default)
-        string_answer = await retriever.get_structured_completion("Who works at Figma?")
-        assert isinstance(string_answer, str), f"Expected str, got {type(string_answer).__name__}"
-        assert string_answer.strip(), "Answer should not be empty"
-
-        # Test with structured response model
-        structured_answer = await retriever.get_structured_completion(
-            "Who works at Figma?", response_model=TestAnswer
-        )
-        assert isinstance(structured_answer, TestAnswer), (
-            f"Expected TestAnswer, got {type(structured_answer).__name__}"
-        )
-        assert structured_answer.answer.strip(), "Answer field should not be empty"
-        assert structured_answer.explanation.strip(), "Explanation field should not be empty"
diff --git a/cognee/tests/unit/modules/retrieval/rag_completion_retriever_test.py b/cognee/tests/unit/modules/retrieval/rag_completion_retriever_test.py
index 252af8352..9bfed68f3 100644
--- a/cognee/tests/unit/modules/retrieval/rag_completion_retriever_test.py
+++ b/cognee/tests/unit/modules/retrieval/rag_completion_retriever_test.py
@@ -3,6 +3,7 @@ from typing import List
 import pytest
 import pathlib
 import cognee
+
 from cognee.low_level import setup
 from cognee.tasks.storage import add_data_points
 from cognee.infrastructure.databases.vector import get_vector_engine
diff --git a/cognee/tests/unit/modules/retrieval/structured_output_test.py b/cognee/tests/unit/modules/retrieval/structured_output_test.py
new file mode 100644
index 000000000..4ad3019ff
--- /dev/null
+++ b/cognee/tests/unit/modules/retrieval/structured_output_test.py
@@ -0,0 +1,204 @@
+import asyncio
+
+import pytest
+import cognee
+import pathlib
+import os
+
+from pydantic import BaseModel
+from cognee.low_level import setup, DataPoint
+from cognee.tasks.storage import add_data_points
+from cognee.modules.chunking.models import DocumentChunk
+from cognee.modules.data.processing.document_types import TextDocument
+from cognee.modules.engine.models import Entity, EntityType
+from cognee.modules.retrieval.entity_extractors.DummyEntityExtractor import DummyEntityExtractor
+from cognee.modules.retrieval.context_providers.DummyContextProvider import DummyContextProvider
+from cognee.modules.retrieval.graph_completion_cot_retriever import GraphCompletionCotRetriever
+from cognee.modules.retrieval.graph_completion_retriever import GraphCompletionRetriever
+from cognee.modules.retrieval.graph_completion_context_extension_retriever import (
+    GraphCompletionContextExtensionRetriever,
+)
+from cognee.modules.retrieval.EntityCompletionRetriever import EntityCompletionRetriever
+from cognee.modules.retrieval.temporal_retriever import TemporalRetriever
+from cognee.modules.retrieval.completion_retriever import CompletionRetriever
+
+
+class TestAnswer(BaseModel):
+    answer: str
+    explanation: str
+
+
+def _assert_string_answer(answer: list[str]):
+    assert isinstance(answer, list), f"Expected str, got {type(answer).__name__}"
+    assert all(isinstance(item, str) and item.strip() for item in answer), "Items should be strings"
+    assert all(item.strip() for item in answer), "Items should not be empty"
+
+
+def _assert_structured_answer(answer: list[TestAnswer]):
+    assert isinstance(answer, list), f"Expected list, got {type(answer).__name__}"
+    assert all(isinstance(x, TestAnswer) for x in answer), "Items should be TestAnswer"
+    assert all(x.answer.strip() for x in answer), "Answer text should not be empty"
+    assert all(x.explanation.strip() for x in answer), "Explanation should not be empty"
+
+
+async def _test_get_structured_graph_completion_cot():
+    retriever = GraphCompletionCotRetriever()
+
+    # Test with string response model (default)
+    string_answer = await retriever.get_completion("Who works at Figma?")
+    _assert_string_answer(string_answer)
+
+    # Test with structured response model
+    structured_answer = await retriever.get_completion(
+        "Who works at Figma?", response_model=TestAnswer
+    )
+    _assert_structured_answer(structured_answer)
+
+
+async def _test_get_structured_graph_completion():
+    retriever = GraphCompletionRetriever()
+
+    # Test with string response model (default)
+    string_answer = await retriever.get_completion("Who works at Figma?")
+    _assert_string_answer(string_answer)
+
+    # Test with structured response model
+    structured_answer = await retriever.get_completion(
+        "Who works at Figma?", response_model=TestAnswer
+    )
+    _assert_structured_answer(structured_answer)
+
+
+async def _test_get_structured_graph_completion_temporal():
+    retriever = TemporalRetriever()
+
+    # Test with string response model (default)
+    string_answer = await retriever.get_completion("When did Steve start working at Figma?")
+    _assert_string_answer(string_answer)
+
+    # Test with structured response model
+    structured_answer = await retriever.get_completion(
+        "When did Steve start working at Figma??", response_model=TestAnswer
+    )
+    _assert_structured_answer(structured_answer)
+
+
+async def _test_get_structured_graph_completion_rag():
+    retriever = CompletionRetriever()
+
+    # Test with string response model (default)
+    string_answer = await retriever.get_completion("Where does Steve work?")
+    _assert_string_answer(string_answer)
+
+    # Test with structured response model
+    structured_answer = await retriever.get_completion(
+        "Where does Steve work?", response_model=TestAnswer
+    )
+    _assert_structured_answer(structured_answer)
+
+
+async def _test_get_structured_graph_completion_context_extension():
+    retriever = GraphCompletionContextExtensionRetriever()
+
+    # Test with string response model (default)
+    string_answer = await retriever.get_completion("Who works at Figma?")
+    _assert_string_answer(string_answer)
+
+    # Test with structured response model
+    structured_answer = await retriever.get_completion(
+        "Who works at Figma?", response_model=TestAnswer
+    )
+    _assert_structured_answer(structured_answer)
+
+
+async def _test_get_structured_entity_completion():
+    retriever = EntityCompletionRetriever(DummyEntityExtractor(), DummyContextProvider())
+
+    # Test with string response model (default)
+    string_answer = await retriever.get_completion("Who is Albert Einstein?")
+    _assert_string_answer(string_answer)
+
+    # Test with structured response model
+    structured_answer = await retriever.get_completion(
+        "Who is Albert Einstein?", response_model=TestAnswer
+    )
+    _assert_structured_answer(structured_answer)
+
+
+class TestStructuredOutputCompletion:
+    @pytest.mark.asyncio
+    async def test_get_structured_completion(self):
+        system_directory_path = os.path.join(
+            pathlib.Path(__file__).parent, ".cognee_system/test_get_structured_completion"
+        )
+        cognee.config.system_root_directory(system_directory_path)
+        data_directory_path = os.path.join(
+            pathlib.Path(__file__).parent, ".data_storage/test_get_structured_completion"
+        )
+        cognee.config.data_root_directory(data_directory_path)
+
+        await cognee.prune.prune_data()
+        await cognee.prune.prune_system(metadata=True)
+        await setup()
+
+        class Company(DataPoint):
+            name: str
+
+        class Person(DataPoint):
+            name: str
+            works_for: Company
+            works_since: int
+
+        company1 = Company(name="Figma")
+        person1 = Person(name="Steve Rodger", works_for=company1, works_since=2015)
+
+        entities = [company1, person1]
+        await add_data_points(entities)
+
+        document = TextDocument(
+            name="Steve Rodger's career",
+            raw_data_location="somewhere",
+            external_metadata="",
+            mime_type="text/plain",
+        )
+
+        chunk1 = DocumentChunk(
+            text="Steve Rodger",
+            chunk_size=2,
+            chunk_index=0,
+            cut_type="sentence_end",
+            is_part_of=document,
+            contains=[],
+        )
+        chunk2 = DocumentChunk(
+            text="Mike Broski",
+            chunk_size=2,
+            chunk_index=1,
+            cut_type="sentence_end",
+            is_part_of=document,
+            contains=[],
+        )
+        chunk3 = DocumentChunk(
+            text="Christina Mayer",
+            chunk_size=2,
+            chunk_index=2,
+            cut_type="sentence_end",
+            is_part_of=document,
+            contains=[],
+        )
+
+        entities = [chunk1, chunk2, chunk3]
+        await add_data_points(entities)
+
+        entity_type = EntityType(name="Person", description="A human individual")
+        entity = Entity(name="Albert Einstein", is_a=entity_type, description="A famous physicist")
+
+        entities = [entity]
+        await add_data_points(entities)
+
+        await _test_get_structured_graph_completion_cot()
+        await _test_get_structured_graph_completion()
+        await _test_get_structured_graph_completion_temporal()
+        await _test_get_structured_graph_completion_rag()
+        await _test_get_structured_graph_completion_context_extension()
+        await _test_get_structured_entity_completion()
diff --git a/cognee/tests/unit/modules/retrieval/summaries_retriever_test.py b/cognee/tests/unit/modules/retrieval/summaries_retriever_test.py
index fc96081bf..5f4b93425 100644
--- a/cognee/tests/unit/modules/retrieval/summaries_retriever_test.py
+++ b/cognee/tests/unit/modules/retrieval/summaries_retriever_test.py
@@ -13,7 +13,7 @@ from cognee.modules.retrieval.exceptions.exceptions import NoDataError
 from cognee.modules.retrieval.summaries_retriever import SummariesRetriever
 
 
-class TextSummariesRetriever:
+class TestSummariesRetriever:
     @pytest.mark.asyncio
     async def test_chunk_context(self):
         system_directory_path = os.path.join(
diff --git a/cognee/tests/unit/modules/retrieval/temporal_retriever_test.py b/cognee/tests/unit/modules/retrieval/temporal_retriever_test.py
index a322cb237..c3c6a47f6 100644
--- a/cognee/tests/unit/modules/retrieval/temporal_retriever_test.py
+++ b/cognee/tests/unit/modules/retrieval/temporal_retriever_test.py
@@ -1,4 +1,3 @@
-import asyncio
 from types import SimpleNamespace
 import pytest