diff --git a/backend/llm_eval/qa_catalog/generator/implementation/ragas/config.py b/backend/llm_eval/qa_catalog/generator/implementation/ragas/config.py
index 7f43262..609cea7 100644
--- a/backend/llm_eval/qa_catalog/generator/implementation/ragas/config.py
+++ b/backend/llm_eval/qa_catalog/generator/implementation/ragas/config.py
@@ -26,9 +26,11 @@ class RagasQACatalogGeneratorPersona(ApiModel):
 class RagasQACatalogGeneratorConfig(QACatalogGeneratorConfig[RagasGeneratorType]):
     knowledge_graph_location: Path | None
     sample_count: int
-    query_distribution: dict[RagasQACatalogQuerySynthesizer, float]
+    query_distribution: list[RagasQACatalogQuerySynthesizer]
     personas: list[RagasQACatalogGeneratorPersona] | None
 
+    use_existing_knowledge_graph: bool = True
+
 
 class RagasQACatalogGeneratorModelConfigSchema(
     QACatalogGeneratorModelConfigSchema[RagasGeneratorType]
diff --git a/backend/llm_eval/qa_catalog/generator/implementation/ragas/generator.py b/backend/llm_eval/qa_catalog/generator/implementation/ragas/generator.py
index 9916e10..6cc6318 100644
--- a/backend/llm_eval/qa_catalog/generator/implementation/ragas/generator.py
+++ b/backend/llm_eval/qa_catalog/generator/implementation/ragas/generator.py
@@ -1,15 +1,8 @@
+import inspect
 import math
-import traceback
-from copy import copy
 from hashlib import md5
 from typing import Callable, Coroutine, get_args, override
 
-from anyio import (
-    CapacityLimiter,
-    create_memory_object_stream,
-    create_task_group,
-)
-from anyio.streams.memory import MemoryObjectSendStream
 from langchain_community.document_loaders import DirectoryLoader
 from langchain_core.documents import Document
 from langchain_text_splitters import RecursiveCharacterTextSplitter
@@ -17,8 +10,8 @@
 from pydantic import ValidationError
 from ragas.embeddings import LangchainEmbeddingsWrapper
 from ragas.testset import TestsetGenerator
+from ragas.testset import persona as ragas_persona
 from ragas.testset.graph import KnowledgeGraph, Node, NodeType
-from ragas.testset.persona import Persona
 from ragas.testset.synthesizers import (
     BaseSynthesizer,
     MultiHopAbstractQuerySynthesizer,
@@ -27,8 +20,19 @@
 )
 from ragas.testset.synthesizers.generate import LangchainLLMWrapper
 from ragas.testset.synthesizers.testset_schema import Testset
-from ragas.testset.transforms import apply_transforms, default_transforms
-from ragas.testset.transforms.default import num_tokens_from_string
+from ragas.testset.transforms import (
+    EmbeddingExtractor,
+    HeadlinesExtractor,
+    HeadlineSplitter,
+    KeyphrasesExtractor,
+    SummaryExtractor,
+    apply_transforms,
+)
+from ragas.testset.transforms.default import (
+    NERExtractor,
+    num_tokens_from_string,
+)
+from typing_extensions import deprecated
 
 from llm_eval.qa_catalog.generator.implementation.QACatalogGeneratorTypes import (  # noqa: E501
     QACatalogGeneratorType,
@@ -48,7 +52,6 @@
     QACatalogGeneratorDataSourceConfig,
     QACatalogGeneratorLocalModelConfig,
 )
-from llm_eval.qa_catalog.graph_utils import create_backup
 from llm_eval.qa_catalog.synthetic_qa_pair import SyntheticQAPair
 from llm_eval.settings import SETTINGS
 from llm_eval.utils.decorators import retry_on_error
@@ -63,6 +66,19 @@
     RagasQACatalogQuerySynthesizer.MULTI_HOP_ABSTRACT: MultiHopAbstractQuerySynthesizer,
 }
 
+query_synthesizer_classes_reverse: dict[
+    type[BaseSynthesizer], RagasQACatalogQuerySynthesizer
+] = {v: k for k, v in query_synthesizer_classes.items()}
+
+
+def has_parameter(cls: type, param_name: str) -> bool:
+    """Check if a class constructor has a specific parameter."""
+    try:
+        signature = inspect.signature(cls.__init__)
+        return param_name in signature.parameters
+    except Exception:
+        return False
+
 
 class RagasQACatalogGenerator(
     QACatalogGenerator[
@@ -100,7 +116,10 @@ def __init__(
             raise RuntimeError(_msg)
 
         self.embeddings = LangchainEmbeddingsWrapper(azure_settings.to_embeddings())
-        if not self.config.knowledge_graph_location:
+        if (
+            not self.config.knowledge_graph_location
+            and self.config.use_existing_knowledge_graph
+        ):
             self.config.knowledge_graph_location = (
                 SETTINGS.file_upload_temp_location / "knowledge_graph_ragas.json"
             )
@@ -109,7 +128,7 @@ def __init__(
 
         self.personas = (
             [
-                Persona(name=p.name, role_description=p.description)
+                ragas_persona.Persona(name=p.name, role_description=p.description)
                 for p in self.config.personas
             ]
             if self.config.personas
@@ -117,10 +136,9 @@ def __init__(
         )
 
     def validate_config(self) -> None:
-        if sum(self.config.query_distribution.values()) != 1:
+        if not self.config.query_distribution:
             raise ValueError(
-                "Given query distribution for the generation is invalid, "
-                "distribution weights should sum up to 1"
+                "At least one query synthesizer must be selected for QA generation"
             )
 
     def _load_and_process_documents(self) -> list[Document]:
@@ -138,10 +156,14 @@ def _load_and_process_documents(self) -> list[Document]:
         docs = loader.load()
         return docs
 
-    def _create_document_nodes(self, docs: list[Document]) -> list[Node]:
+    def _create_knowledge_graph_nodes(
+        self,
+        docs: list[Document],
+        node_type: NodeType = NodeType.DOCUMENT,
+    ) -> list[Node]:
         return [
             Node(
-                type=NodeType.DOCUMENT,
+                type=node_type,
                 properties={
                     "page_content": doc.page_content,
                     "document_metadata": doc.metadata,
@@ -185,20 +207,24 @@ def split_documents(
         Therefore if the document is large enough, we split it into proper subdocuments.
 
         """
+
+        def _split(doc: Document, token_length: int) -> list[Document]:
+            chunk_size = math.ceil(token_length / 2)
+            chunk_overlap = math.ceil(chunk_size * 0.5)
+            splitter = RecursiveCharacterTextSplitter(
+                chunk_size=chunk_size,
+                chunk_overlap=chunk_overlap,
+                length_function=num_tokens_from_string,
+            )
+            return splitter.split_documents([doc])
+
         _docs = []
         split_occurred = False
         for doc in docs:
             token_length = num_tokens_from_string(doc.page_content)
             if token_length > 100_000:
                 split_occurred = True
-                chunk_size = math.ceil(token_length / 2)
-                chunk_overlap = math.ceil(chunk_size * 0.5)
-                splitter = RecursiveCharacterTextSplitter(
-                    chunk_size=chunk_size,
-                    chunk_overlap=chunk_overlap,
-                    length_function=num_tokens_from_string,
-                )
-                _docs.extend(splitter.split_documents([doc]))
+                _docs.extend(_split(doc, token_length))
             else:
                 _docs.append(doc)
 
@@ -208,66 +234,74 @@ def split_documents(
             return _docs
 
     def apply_knowledge_graph_transformations(
-        self, kg: KnowledgeGraph, docs: list[Document]
+        self,
+        knowledge_graph: KnowledgeGraph,
     ) -> None:
-        apply_transforms(
-            kg,
-            default_transforms(
-                self.split_documents(docs),
-                llm=self.llm,
-                embedding_model=self.embeddings,
-            ),
+        headline_extractor = HeadlinesExtractor(llm=self.llm, max_num=20)
+        headline_splitter = HeadlineSplitter(max_tokens=1500, min_tokens=100)
+        keyphrase_extractor = KeyphrasesExtractor(llm=self.llm)
+
+        summary = SummaryExtractor(llm=self.llm)
+        summary_emb_extractor = EmbeddingExtractor(
+            embedding_model=self.embeddings,
+            property_name="summary_embedding",
+            embed_property_name="summary",
+        )
+
+        ner_extractor = NERExtractor(
+            llm=self.llm,
+            property_name="entities",
         )
 
+        transforms = [
+            headline_extractor,
+            headline_splitter,
+            keyphrase_extractor,
+            summary,
+            summary_emb_extractor,
+            ner_extractor,
+        ]
+
+        apply_transforms(knowledge_graph, transforms=transforms)
+
     def create_knowledge_graph(self) -> KnowledgeGraph:
         """
         Loads the knowledge graph if already exists
         and compares it's nodes with the current documents.
-        If the existent graph has these documents already it uses the existent kg
-        otherwise create a new kg out ouf the documents
+        If the existent graph has these documents
+        already it uses the existent knowledge graph
+        otherwise create a new knowledge graph out ouf the documents
         """
 
         docs = self._load_and_process_documents()  # chunks of documents
         if len(docs) == 0:
             raise RuntimeError("No documents found")
 
-        loaded_knowledge_graph = self.load_knowledge_graph()
-        new_nodes = self._create_document_nodes(docs)
-        if loaded_knowledge_graph and self._has_same_nodes(
-            loaded_knowledge_graph.nodes, new_nodes
-        ):
-            logger.info("Using the existent knowledge graph")
-            kg = loaded_knowledge_graph
-        else:
-            logger.info("Generating a new knowledge graph")
-            kg = KnowledgeGraph(nodes=new_nodes)
-            self.apply_knowledge_graph_transformations(kg, docs)
-            if self.config.knowledge_graph_location:
-                create_backup(
-                    self.config.knowledge_graph_location
-                )  # backup the old kg config
-                kg.save(
-                    self.config.knowledge_graph_location
-                )  # save the new kg to system
-                logger.info(
-                    f"Knowledge graph saved to {self.config.knowledge_graph_location}"
-                )
+        chunks = self.split_documents(docs)
+        knowledge_graph = KnowledgeGraph(
+            nodes=self._create_knowledge_graph_nodes(chunks),
+        )
 
-        return kg
+        self.apply_knowledge_graph_transformations(knowledge_graph)
 
-    def load_knowledge_graph(self) -> KnowledgeGraph | None:
+        return knowledge_graph
+
+    @deprecated("Until we have a better way to handle knowledge graph caching")
+    def load_exiting_knowledge_graph(
+        self,
+        docs: list[Document],
+    ) -> KnowledgeGraph | None:
         if not self.config.knowledge_graph_location:
             return None
 
-        knowledge_graph: KnowledgeGraph | None = None
-
         if not self.config.knowledge_graph_location.exists():
             logger.info(
                 f"No knowledge graph found at {self.config.knowledge_graph_location}"
             )
-            return knowledge_graph
+            return None
 
         logger.info(f"Knowledge graph found at {self.config.knowledge_graph_location}")
+        knowledge_graph = None
         try:
             knowledge_graph = KnowledgeGraph.load(self.config.knowledge_graph_location)
         except Exception as e:
@@ -276,78 +310,99 @@ def load_knowledge_graph(self) -> KnowledgeGraph | None:
                 self.config.knowledge_graph_location.absolute().with_suffix(".bak")
             )
 
-        return knowledge_graph
+        new_nodes = self._create_knowledge_graph_nodes(docs)
+        if knowledge_graph and self._has_same_nodes(knowledge_graph.nodes, new_nodes):
+            return knowledge_graph
+
+        return None
+
+    def create_query_distribution(
+        self,
+        knowledge_graph: KnowledgeGraph,
+    ) -> list[tuple[BaseSynthesizer, float]]:
+        properties = ["headlines", "keyphrases", "entities"]
+
+        selected_synthesizer_classes = (
+            query_synthesizer_classes[q] for q in self.config.query_distribution
+        )
+
+        synthesizers = []
+        for synthesizer_class in selected_synthesizer_classes:
+            if has_parameter(synthesizer_class, "property_name"):
+                for property_name in properties:
+                    synthesizers.append(
+                        synthesizer_class(
+                            llm=self.llm,
+                            property_name=property_name,  # type: ignore
+                        )
+                    )
+            else:
+                synthesizers.append(synthesizer_class(llm=self.llm))
+
+        available_queries = []
+        for query in synthesizers:
+            if query.get_node_clusters(knowledge_graph):
+                available_queries.append(query)
+
+        return [(query, 1 / len(available_queries)) for query in available_queries]
 
     @retry_on_error((Exception,), 3)
     def generate_testset(
         self,
         generator: TestsetGenerator,
-        count: int,
+        sample_count: int,
+        query_distribution: list[tuple[BaseSynthesizer, float]],
     ) -> Testset:
+        if len(query_distribution) == 0:
+            raise ValueError("No query distribution provided")
+
+        # Given sample count may not match the outputted sample count
         return generator.generate(
-            count,
-            query_distribution=[
-                (query_synthesizer_classes[synthesizer_type](llm=self.llm), weight)
-                for synthesizer_type, weight in self.config.query_distribution.items()
-                if weight > 0
-            ],
+            sample_count,
+            query_distribution,
         )
 
-    async def _generate_single_sample(
-        self,
-        generator: TestsetGenerator,
-        send_sample: MemoryObjectSendStream[SyntheticQAPair],
-        limiter: CapacityLimiter,
-    ) -> None:
-        try:
-            async with limiter:
-                testset = self.generate_testset(generator, 1)
-                if testset.samples:
-                    async with send_sample:
-                        for testset_sample in testset.samples:
-                            sample = ragas_sample_to_synthetic_qa_pair(testset_sample)
-                            await send_sample.send(sample)
-                else:
-                    logger.error(f"empty testset {testset.samples} {testset.to_list()}")
-        except Exception as e:
-            logger.error(
-                f"Error generating sample: {e}\nTraceback: {traceback.format_exc()}"
-            )
-
     async def a_create_synthetic_qa(
         self,
-        process_sample: Callable[[SyntheticQAPair], Coroutine],
+        collect_samples: Callable[[list[SyntheticQAPair]], Coroutine],
     ) -> None:
-        limiter = CapacityLimiter(SETTINGS.ragas.parallel_generation_limit)
-        send_sample, receive_sample = create_memory_object_stream[SyntheticQAPair]()
+        knowledge_graph = self.create_knowledge_graph()
 
-        kg = self.create_knowledge_graph()
+        if not self.personas:
+            self.personas = ragas_persona.generate_personas_from_kg(
+                knowledge_graph,
+                self.llm,
+            )
+            if not self.personas:
+                raise ValueError("Failed to generate personas")
 
         logger.info(f"Generating {self.config.sample_count} QA pairs")
 
         generator = TestsetGenerator(
             llm=self.llm,
             embedding_model=self.embeddings,
-            knowledge_graph=kg,
+            knowledge_graph=knowledge_graph,
             persona_list=self.personas,
         )
 
-        async with create_task_group() as tg:
-            async with send_sample:
-                for _ in range(self.config.sample_count):
-                    tg.start_soon(
-                        self._generate_single_sample,
-                        copy(generator),
-                        send_sample.clone(),
-                        limiter,
-                    )
+        query_distribution = self.create_query_distribution(knowledge_graph)
+
+        testset = self.generate_testset(
+            generator,
+            self.config.sample_count,
+            query_distribution,
+        )
+        if not testset.samples:
+            raise ValueError("Empty testset")
+
+        samples: list[SyntheticQAPair] = [
+            ragas_sample_to_synthetic_qa_pair(testset_sample)
+            for testset_sample in testset.samples
+        ]
 
-            async with receive_sample:
-                logger.info("Waiting for generated qa samples")
-                async for sample in receive_sample:
-                    await process_sample(sample)
+        await collect_samples(samples)
 
-        logger.info(f"Generated {self.config.sample_count} QA sample sets")
+        logger.info(f"Generated {len(samples)} QA sample sets")
 
     @override
     @staticmethod
diff --git a/backend/llm_eval/qa_catalog/generator/interface.py b/backend/llm_eval/qa_catalog/generator/interface.py
index a4ebf64..ff57a3d 100644
--- a/backend/llm_eval/qa_catalog/generator/interface.py
+++ b/backend/llm_eval/qa_catalog/generator/interface.py
@@ -121,5 +121,6 @@ class AsyncQACatalogGeneratorSupport(ABC):
 
     @abstractmethod
     async def a_create_synthetic_qa(
-        self, process_sample: Callable[[SyntheticQAPair], Coroutine]
+        self,
+        collect_samples: Callable[[list[SyntheticQAPair]], Coroutine],
     ) -> None: ...
diff --git a/backend/llm_eval/qa_catalog/logic/generation.py b/backend/llm_eval/qa_catalog/logic/generation.py
index c4b9709..a27618c 100644
--- a/backend/llm_eval/qa_catalog/logic/generation.py
+++ b/backend/llm_eval/qa_catalog/logic/generation.py
@@ -8,7 +8,6 @@
     QACatalogGeneratorTempDataSourceConfig,
     QACatalogStatus,
 )
-from llm_eval.db import AsyncSessionLocal
 from llm_eval.llm_endpoints.db.find_llm_endpoint import find_llm_endpoint
 from llm_eval.qa_catalog.db.crud_data_source_config import (
     delete_data_source_config,
@@ -69,23 +68,21 @@ async def _generate_catalog_from_config(
 
         if isinstance(generator, AsyncQACatalogGeneratorSupport):
 
-            async def process_sample(sample: SyntheticQAPair) -> None:
-                if sample:
-                    async with AsyncSessionLocal.begin() as db:
-                        store_qa_pairs(
-                            db,
-                            synthethic_qa_pairs_to_db_models([sample], qa_catalog.id),
-                        )
+            async def collect_samples(samples: list[SyntheticQAPair]) -> None:
+                if samples:
+                    store_qa_pairs(
+                        db,
+                        synthethic_qa_pairs_to_db_models(samples, qa_catalog.id),
+                    )
 
-            await generator.a_create_synthetic_qa(process_sample)
+            await generator.a_create_synthetic_qa(collect_samples)
 
         elif isinstance(generator, SyncQACatalogGeneratorSupport):
             qa_pairs = generator.create_synthetic_qa()
-            async with AsyncSessionLocal.begin() as db:
-                store_qa_pairs(
-                    db,
-                    synthethic_qa_pairs_to_db_models(qa_pairs, qa_catalog.id),
-                )
+            store_qa_pairs(
+                db,
+                synthethic_qa_pairs_to_db_models(qa_pairs, qa_catalog.id),
+            )
         else:
             raise RuntimeError(f"{generator} doesnt support sync/async qa generation")
 
@@ -109,38 +106,37 @@ async def generation_cleanup(
     await delete_data_source_config(db, temp_data_source_config)
 
 
-async def generate_catalog(catalog_id: str, data: QACatalogGenerationData) -> None:
-    async with AsyncSessionLocal.begin() as db:
-        qa_catalog = await find_qa_catalog(db, catalog_id)
-        temp_data_source_config = await find_data_source_config(
-            db, data.data_source_config_id
-        )
+async def generate_catalog(
+    db: AsyncSession, catalog_id: str, data: QACatalogGenerationData
+) -> None:
+    qa_catalog = await find_qa_catalog(db, catalog_id)
+    temp_data_source_config = await find_data_source_config(
+        db, data.data_source_config_id
+    )
 
-        if qa_catalog:
-            if not temp_data_source_config:
-                qa_catalog.status = QACatalogStatus.FAILURE
-                qa_catalog.error = (
-                    "Given data source config with id"
-                    f"{data.data_source_config_id} couldn't be found"
+    if qa_catalog:
+        if not temp_data_source_config:
+            qa_catalog.status = QACatalogStatus.FAILURE
+            qa_catalog.error = (
+                "Given data source config with id"
+                f"{data.data_source_config_id} couldn't be found"
+            )
+        else:
+            try:
+                data_source_config = QACatalogGeneratorDataSourceConfig.from_db_json(
+                    temp_data_source_config.config
                 )
-            else:
-                try:
-                    data_source_config = (
-                        QACatalogGeneratorDataSourceConfig.from_db_json(
-                            temp_data_source_config.config
-                        )
-                    )
-                    await _generate_catalog_from_config(
-                        db,
-                        qa_catalog,
-                        data.config,
-                        data.model_config_schema,
-                        data_source_config,
-                    )
-                    await generation_cleanup(db, temp_data_source_config)  # noqa: F821
-                except Exception as e:
-                    logger.error(
-                        f"Error generating qa pairs for {qa_catalog.id}\nError: {e}"
-                    )
-                    qa_catalog.status = QACatalogStatus.FAILURE
-                    qa_catalog.error = repr(e)
+                await _generate_catalog_from_config(
+                    db,
+                    qa_catalog,
+                    data.config,
+                    data.model_config_schema,
+                    data_source_config,
+                )
+                await generation_cleanup(db, temp_data_source_config)  # noqa: F821
+            except Exception as e:
+                logger.error(
+                    f"Error generating qa pairs for {qa_catalog.id}\nError: {e}"
+                )
+                qa_catalog.status = QACatalogStatus.FAILURE
+                qa_catalog.error = repr(e)
diff --git a/backend/llm_eval/qa_catalog/tasks/handle_generate_catalog_task.py b/backend/llm_eval/qa_catalog/tasks/handle_generate_catalog_task.py
index d657bd3..22bdbbb 100644
--- a/backend/llm_eval/qa_catalog/tasks/handle_generate_catalog_task.py
+++ b/backend/llm_eval/qa_catalog/tasks/handle_generate_catalog_task.py
@@ -1,8 +1,9 @@
 from loguru import logger
+from sqlalchemy.ext.asyncio import AsyncSession
 
 from llm_eval.qa_catalog.models import QACatalogGenerationData
 from llm_eval.tasks import app
-from llm_eval.utils.task import async_task
+from llm_eval.utils.task import async_task, with_session
 
 
 def submit_generate_catalog_task(
@@ -20,7 +21,9 @@ def submit_generate_catalog_task(
     max_retries=10,
 )
 @async_task
+@with_session
 async def execute_generate_catalog_task(
+    session: AsyncSession,
     catalog_id: str,
     json_data: str,
 ) -> None:
@@ -32,4 +35,4 @@ async def execute_generate_catalog_task(
     )
     from llm_eval.qa_catalog.logic.generation import generate_catalog
 
-    await generate_catalog(catalog_id, data)
+    await generate_catalog(session, catalog_id, data)
diff --git a/backend/llm_eval/tasks.py b/backend/llm_eval/tasks.py
index 7d3f93a..bbb451e 100644
--- a/backend/llm_eval/tasks.py
+++ b/backend/llm_eval/tasks.py
@@ -1,4 +1,5 @@
 from pathlib import Path
+from typing import Any
 
 from celery import Celery
 from celery.bootsteps import StartStopStep
@@ -18,12 +19,12 @@
 class LivenessProbe(StartStopStep):
     requires = {"celery.worker.components:Timer"}
 
-    def __init__(self, parent: any, **kwargs: dict[str, any]) -> None:
+    def __init__(self, parent, **kwargs: dict[str, Any]) -> None:  # noqa: ANN001
         super().__init__(parent, **kwargs)
         self.requests = []
         self.tref = None
 
-    def start(self, parent: any) -> None:
+    def start(self, parent) -> None:  # noqa: ANN001
         self.tref = parent.timer.call_repeatedly(
             1.0,
             self._update_heartbeat_file,
@@ -31,21 +32,21 @@ def start(self, parent: any) -> None:
             priority=10,
         )
 
-    def stop(self, parent: any) -> None:
+    def stop(self, parent) -> None:  # noqa: ANN001
         HEARTBEAT_FILE.unlink(missing_ok=True)
 
     # noinspection PyMethodMayBeStatic
-    def _update_heartbeat_file(self, parent: any) -> None:
+    def _update_heartbeat_file(self, parent) -> None:  # noqa: ANN001
         HEARTBEAT_FILE.touch()
 
 
 @worker_ready.connect
-def worker_ready(**_: dict[str, any]) -> None:
+def _worker_ready(**_: dict[str, Any]) -> None:
     READINESS_FILE.touch()
 
 
 @worker_shutdown.connect
-def worker_shutdown(**_: dict[str, any]) -> None:
+def _worker_shutdown(**_: dict[str, Any]) -> None:
     READINESS_FILE.unlink(missing_ok=True)
 
 
diff --git a/backend/llm_eval/utils/model_settings/azure_ai_model_settings.py b/backend/llm_eval/utils/model_settings/azure_ai_model_settings.py
index 71fbccd..6ad7e42 100644
--- a/backend/llm_eval/utils/model_settings/azure_ai_model_settings.py
+++ b/backend/llm_eval/utils/model_settings/azure_ai_model_settings.py
@@ -11,13 +11,14 @@ class AzureAiModelSettings(BaseSettings, ModelSettings, prefix="AZURE_OPENAI_"):
     api_version: str = Field(default="2024-02-01")
     endpoint: str = Field(default="https://example.com")
     api_key: str = Field(default="api-key")
-    deployment: str = Field(default="text-embedding-3-large")
+    embedding_deployment: str = Field(default="text-embedding-3-large")
+    chat_deployment: str = Field(default="gpt-4.1")
     response_language: str = Field(default="german")
 
     def to_chat(self) -> BaseChatModel:
         return AzureChatOpenAI(
             api_version=self.api_version,
-            azure_deployment=self.deployment,
+            azure_deployment=self.chat_deployment,
             azure_endpoint=self.endpoint,
             api_key=SecretStr(self.api_key),
         )
@@ -25,7 +26,7 @@ def to_chat(self) -> BaseChatModel:
     def to_embeddings(self) -> Embeddings:
         return AzureOpenAIEmbeddings(
             api_version=self.api_version,
-            azure_deployment=self.deployment,
+            azure_deployment=self.embedding_deployment,
             azure_endpoint=self.endpoint,
             api_key=SecretStr(self.api_key),
         )
diff --git a/backend/poetry.lock b/backend/poetry.lock
index 3638602..be79e2e 100644
--- a/backend/poetry.lock
+++ b/backend/poetry.lock
@@ -180,7 +180,7 @@ version = "5.3.1"
 description = "Low-level AMQP client for Python (fork of amqplib)."
 optional = false
 python-versions = ">=3.6"
-groups = ["main"]
+groups = ["main", "dev"]
 files = [
     {file = "amqp-5.3.1-py3-none-any.whl", hash = "sha256:43b3319e1b4e7d1251833a93d672b4af1e40f3d632d479b98661a95f117880a2"},
     {file = "amqp-5.3.1.tar.gz", hash = "sha256:cddc00c725449522023bad949f70fff7b48f0b1ade74d170a6f10ab044739432"},
@@ -487,7 +487,7 @@ version = "4.2.1"
 description = "Python multiprocessing fork with improvements and bugfixes"
 optional = false
 python-versions = ">=3.7"
-groups = ["main"]
+groups = ["main", "dev"]
 files = [
     {file = "billiard-4.2.1-py3-none-any.whl", hash = "sha256:40b59a4ac8806ba2c2369ea98d876bc6108b051c227baffd928c644d15d8f3cb"},
     {file = "billiard-4.2.1.tar.gz", hash = "sha256:12b641b0c539073fc8d3f5b8b7be998956665c4233c7c1fcd66a7e677c4fb36f"},
@@ -580,7 +580,7 @@ version = "5.5.3"
 description = "Distributed Task Queue."
 optional = false
 python-versions = ">=3.8"
-groups = ["main"]
+groups = ["main", "dev"]
 files = [
     {file = "celery-5.5.3-py3-none-any.whl", hash = "sha256:0b5761a07057acee94694464ca482416b959568904c9dfa41ce8413a7d65d525"},
     {file = "celery-5.5.3.tar.gz", hash = "sha256:6c972ae7968c2b5281227f01c3a3f984037d21c5129d07bf3550cc2afc6b10a5"},
@@ -946,7 +946,7 @@ version = "0.3.1"
 description = "Enables git-like *did-you-mean* feature in click"
 optional = false
 python-versions = ">=3.6.2"
-groups = ["main"]
+groups = ["main", "dev"]
 files = [
     {file = "click_didyoumean-0.3.1-py3-none-any.whl", hash = "sha256:5c4bb6007cfea5f2fd6583a2fb6701a22a41eb98957e63d0fac41c10e7c3117c"},
     {file = "click_didyoumean-0.3.1.tar.gz", hash = "sha256:4f82fdff0dbe64ef8ab2279bd6aa3f6a99c3b28c05aa09cbfc07c9d7fbb5a463"},
@@ -961,7 +961,7 @@ version = "1.1.1"
 description = "An extension module for click to enable registering CLI commands via setuptools entry-points."
 optional = false
 python-versions = "*"
-groups = ["main"]
+groups = ["main", "dev"]
 files = [
     {file = "click-plugins-1.1.1.tar.gz", hash = "sha256:46ab999744a9d831159c3411bb0c79346d94a444df9a3a3742e9ed63645f264b"},
     {file = "click_plugins-1.1.1-py2.py3-none-any.whl", hash = "sha256:5d262006d3222f5057fd81e1623d4443e41dcda5dc815c06b442aa3c02889fc8"},
@@ -979,7 +979,7 @@ version = "0.3.0"
 description = "REPL plugin for Click"
 optional = false
 python-versions = ">=3.6"
-groups = ["main"]
+groups = ["main", "dev"]
 files = [
     {file = "click-repl-0.3.0.tar.gz", hash = "sha256:17849c23dba3d667247dc4defe1757fff98694e90fe37474f3feebb69ced26a9"},
     {file = "click_repl-0.3.0-py3-none-any.whl", hash = "sha256:fb7e06deb8da8de86180a33a9da97ac316751c094c6899382da7feeeeb51b812"},
@@ -1181,14 +1181,14 @@ typing-inspect = ">=0.4.0,<1"
 
 [[package]]
 name = "datasets"
-version = "3.6.0"
+version = "4.0.0"
 description = "HuggingFace community-driven open-source library of datasets"
 optional = false
 python-versions = ">=3.9.0"
 groups = ["main"]
 files = [
-    {file = "datasets-3.6.0-py3-none-any.whl", hash = "sha256:25000c4a2c0873a710df127d08a202a06eab7bf42441a6bc278b499c2f72cd1b"},
-    {file = "datasets-3.6.0.tar.gz", hash = "sha256:1b2bf43b19776e2787e181cfd329cb0ca1a358ea014780c3581e0f276375e041"},
+    {file = "datasets-4.0.0-py3-none-any.whl", hash = "sha256:7ef95e62025fd122882dbce6cb904c8cd3fbc829de6669a5eb939c77d50e203d"},
+    {file = "datasets-4.0.0.tar.gz", hash = "sha256:9657e7140a9050db13443ba21cb5de185af8af944479b00e7ff1e00a61c8dbf1"},
 ]
 
 [package.dependencies]
@@ -1207,18 +1207,17 @@ tqdm = ">=4.66.3"
 xxhash = "*"
 
 [package.extras]
-audio = ["librosa", "soundfile (>=0.12.1)", "soxr (>=0.4.0)"]
+audio = ["soundfile (>=0.12.1)", "torch (>=2.7.0)", "torchcodec (>=0.4.0)"]
 benchmarks = ["tensorflow (==2.12.0)", "torch (==2.0.1)", "transformers (==4.30.1)"]
-dev = ["Pillow (>=9.4.0)", "absl-py", "aiohttp", "decorator", "elasticsearch (>=7.17.12,<8.0.0)", "faiss-cpu (>=1.8.0.post1)", "jax (>=0.3.14) ; sys_platform != \"win32\"", "jaxlib (>=0.3.14) ; sys_platform != \"win32\"", "joblib (<1.3.0)", "joblibspark", "librosa", "lz4", "moto[server]", "polars[timezone] (>=0.20.0)", "protobuf (<4.0.0)", "py7zr", "pyav", "pyspark (>=3.4)", "pytest", "pytest-datadir", "pytest-xdist", "rarfile (>=4.0)", "ruff (>=0.3.0)", "s3fs", "s3fs (>=2021.11.1)", "soundfile (>=0.12.1)", "soundfile (>=0.12.1)", "soxr (>=0.4.0)", "sqlalchemy", "tensorflow (>=2.16.0) ; python_version >= \"3.10\"", "tensorflow (>=2.6.0)", "tensorflow (>=2.6.0) ; python_version < \"3.10\"", "tiktoken", "torch", "torch (>=2.0.0)", "torchdata", "torchvision", "transformers", "transformers (>=4.42.0)", "zstandard"]
-docs = ["s3fs", "tensorflow (>=2.6.0)", "torch", "transformers"]
+dev = ["Pillow (>=9.4.0)", "absl-py", "aiohttp", "decorator", "elasticsearch (>=7.17.12,<8.0.0)", "faiss-cpu (>=1.8.0.post1)", "jax (>=0.3.14) ; sys_platform != \"win32\"", "jaxlib (>=0.3.14) ; sys_platform != \"win32\"", "joblib (<1.3.0)", "joblibspark", "lz4", "moto[server]", "numba (>=0.56.4)", "polars[timezone] (>=0.20.0)", "protobuf (<4.0.0)", "py7zr", "pyspark (>=3.4)", "pytest", "pytest-datadir", "pytest-xdist", "rarfile (>=4.0)", "ruff (>=0.3.0)", "soundfile (>=0.12.1)", "soundfile (>=0.12.1)", "sqlalchemy", "tensorflow (>=2.16.0) ; python_version >= \"3.10\" and sys_platform != \"win32\"", "tensorflow (>=2.6.0)", "tensorflow (>=2.6.0) ; python_version < \"3.10\" and sys_platform != \"win32\"", "tiktoken", "torch", "torch (>=2.0.0)", "torchcodec (>=0.4.0) ; sys_platform != \"win32\"", "torchdata", "transformers", "transformers (>=4.42.0)", "zstandard"]
+docs = ["tensorflow (>=2.6.0)", "torch", "transformers"]
 jax = ["jax (>=0.3.14)", "jaxlib (>=0.3.14)"]
 pdfs = ["pdfplumber (>=0.11.4)"]
 quality = ["ruff (>=0.3.0)"]
-s3 = ["s3fs"]
 tensorflow = ["tensorflow (>=2.6.0)"]
 tensorflow-gpu = ["tensorflow (>=2.6.0)"]
-tests = ["Pillow (>=9.4.0)", "absl-py", "aiohttp", "decorator", "elasticsearch (>=7.17.12,<8.0.0)", "faiss-cpu (>=1.8.0.post1)", "jax (>=0.3.14) ; sys_platform != \"win32\"", "jaxlib (>=0.3.14) ; sys_platform != \"win32\"", "joblib (<1.3.0)", "joblibspark", "librosa", "lz4", "moto[server]", "polars[timezone] (>=0.20.0)", "protobuf (<4.0.0)", "py7zr", "pyav", "pyspark (>=3.4)", "pytest", "pytest-datadir", "pytest-xdist", "rarfile (>=4.0)", "s3fs (>=2021.11.1)", "soundfile (>=0.12.1)", "soundfile (>=0.12.1)", "soxr (>=0.4.0)", "sqlalchemy", "tensorflow (>=2.16.0) ; python_version >= \"3.10\"", "tensorflow (>=2.6.0) ; python_version < \"3.10\"", "tiktoken", "torch (>=2.0.0)", "torchdata", "torchvision", "transformers (>=4.42.0)", "zstandard"]
-tests-numpy2 = ["Pillow (>=9.4.0)", "absl-py", "aiohttp", "decorator", "elasticsearch (>=7.17.12,<8.0.0)", "jax (>=0.3.14) ; sys_platform != \"win32\"", "jaxlib (>=0.3.14) ; sys_platform != \"win32\"", "joblib (<1.3.0)", "joblibspark", "lz4", "moto[server]", "polars[timezone] (>=0.20.0)", "protobuf (<4.0.0)", "py7zr", "pyav", "pyspark (>=3.4)", "pytest", "pytest-datadir", "pytest-xdist", "rarfile (>=4.0)", "s3fs (>=2021.11.1)", "soundfile (>=0.12.1)", "soundfile (>=0.12.1)", "soxr (>=0.4.0)", "sqlalchemy", "tiktoken", "torch (>=2.0.0)", "torchdata", "torchvision", "transformers (>=4.42.0)", "zstandard"]
+tests = ["Pillow (>=9.4.0)", "absl-py", "aiohttp", "decorator", "elasticsearch (>=7.17.12,<8.0.0)", "faiss-cpu (>=1.8.0.post1)", "jax (>=0.3.14) ; sys_platform != \"win32\"", "jaxlib (>=0.3.14) ; sys_platform != \"win32\"", "joblib (<1.3.0)", "joblibspark", "lz4", "moto[server]", "numba (>=0.56.4)", "polars[timezone] (>=0.20.0)", "protobuf (<4.0.0)", "py7zr", "pyspark (>=3.4)", "pytest", "pytest-datadir", "pytest-xdist", "rarfile (>=4.0)", "soundfile (>=0.12.1)", "soundfile (>=0.12.1)", "sqlalchemy", "tensorflow (>=2.16.0) ; python_version >= \"3.10\" and sys_platform != \"win32\"", "tensorflow (>=2.6.0) ; python_version < \"3.10\" and sys_platform != \"win32\"", "tiktoken", "torch (>=2.0.0)", "torchcodec (>=0.4.0) ; sys_platform != \"win32\"", "torchdata", "transformers (>=4.42.0)", "zstandard"]
+tests-numpy2 = ["Pillow (>=9.4.0)", "absl-py", "aiohttp", "decorator", "elasticsearch (>=7.17.12,<8.0.0)", "jax (>=0.3.14) ; sys_platform != \"win32\"", "jaxlib (>=0.3.14) ; sys_platform != \"win32\"", "joblib (<1.3.0)", "joblibspark", "lz4", "moto[server]", "numba (>=0.56.4)", "polars[timezone] (>=0.20.0)", "protobuf (<4.0.0)", "py7zr", "pyspark (>=3.4)", "pytest", "pytest-datadir", "pytest-xdist", "rarfile (>=4.0)", "soundfile (>=0.12.1)", "soundfile (>=0.12.1)", "sqlalchemy", "tiktoken", "torch (>=2.0.0)", "torchcodec (>=0.4.0) ; sys_platform != \"win32\"", "torchdata", "transformers (>=4.42.0)", "zstandard"]
 torch = ["torch"]
 vision = ["Pillow (>=9.4.0)"]
 
@@ -1574,6 +1573,25 @@ files = [
     {file = "flatbuffers-25.2.10.tar.gz", hash = "sha256:97e451377a41262f8d9bd4295cc836133415cc03d8cb966410a4af92eb00d26e"},
 ]
 
+[[package]]
+name = "flower"
+version = "2.0.1"
+description = "Celery Flower"
+optional = false
+python-versions = ">=3.7"
+groups = ["dev"]
+files = [
+    {file = "flower-2.0.1-py2.py3-none-any.whl", hash = "sha256:9db2c621eeefbc844c8dd88be64aef61e84e2deb29b271e02ab2b5b9f01068e2"},
+    {file = "flower-2.0.1.tar.gz", hash = "sha256:5ab717b979530770c16afb48b50d2a98d23c3e9fe39851dcf6bc4d01845a02a0"},
+]
+
+[package.dependencies]
+celery = ">=5.0.5"
+humanize = "*"
+prometheus-client = ">=0.8.0"
+pytz = "*"
+tornado = ">=5.0.0,<7.0.0"
+
 [[package]]
 name = "frozenlist"
 version = "1.7.0"
@@ -2151,6 +2169,21 @@ files = [
 [package.dependencies]
 pyreadline3 = {version = "*", markers = "sys_platform == \"win32\" and python_version >= \"3.8\""}
 
+[[package]]
+name = "humanize"
+version = "4.12.3"
+description = "Python humanize utilities"
+optional = false
+python-versions = ">=3.9"
+groups = ["dev"]
+files = [
+    {file = "humanize-4.12.3-py3-none-any.whl", hash = "sha256:2cbf6370af06568fa6d2da77c86edb7886f3160ecd19ee1ffef07979efc597f6"},
+    {file = "humanize-4.12.3.tar.gz", hash = "sha256:8430be3a615106fdfceb0b2c1b41c4c98c6b0fc5cc59663a5539b111dd325fb0"},
+]
+
+[package.extras]
+tests = ["freezegun", "pytest", "pytest-cov"]
+
 [[package]]
 name = "identify"
 version = "2.6.12"
@@ -2530,7 +2563,7 @@ version = "5.5.4"
 description = "Messaging library for Python."
 optional = false
 python-versions = ">=3.8"
-groups = ["main"]
+groups = ["main", "dev"]
 files = [
     {file = "kombu-5.5.4-py3-none-any.whl", hash = "sha256:a12ed0557c238897d8e518f1d1fdf84bd1516c5e305af2dacd85c2015115feb8"},
     {file = "kombu-5.5.4.tar.gz", hash = "sha256:886600168275ebeada93b888e831352fe578168342f0d1d5833d88ba0d847363"},
@@ -4352,13 +4385,28 @@ nodeenv = ">=0.11.1"
 pyyaml = ">=5.1"
 virtualenv = ">=20.10.0"
 
+[[package]]
+name = "prometheus-client"
+version = "0.22.1"
+description = "Python client for the Prometheus monitoring system."
+optional = false
+python-versions = ">=3.9"
+groups = ["dev"]
+files = [
+    {file = "prometheus_client-0.22.1-py3-none-any.whl", hash = "sha256:cca895342e308174341b2cbf99a56bef291fbc0ef7b9e5412a0f26d653ba7094"},
+    {file = "prometheus_client-0.22.1.tar.gz", hash = "sha256:190f1331e783cf21eb60bca559354e0a4d4378facecf78f5428c39b675d20d28"},
+]
+
+[package.extras]
+twisted = ["twisted"]
+
 [[package]]
 name = "prompt-toolkit"
 version = "3.0.51"
 description = "Library for building powerful interactive command lines in Python"
 optional = false
 python-versions = ">=3.8"
-groups = ["main"]
+groups = ["main", "dev"]
 files = [
     {file = "prompt_toolkit-3.0.51-py3-none-any.whl", hash = "sha256:52742911fde84e2d423e2f9a4cf1de7d7ac4e51958f648d9540e0fb8db077b07"},
     {file = "prompt_toolkit-3.0.51.tar.gz", hash = "sha256:931a162e3b27fc90c86f1b48bb1fb2c528c2761475e57c9c06de13311c7b54ed"},
@@ -4576,67 +4624,55 @@ files = [
 
 [[package]]
 name = "pyarrow"
-version = "20.0.0"
+version = "21.0.0"
 description = "Python library for Apache Arrow"
 optional = false
 python-versions = ">=3.9"
 groups = ["main"]
 files = [
-    {file = "pyarrow-20.0.0-cp310-cp310-macosx_12_0_arm64.whl", hash = "sha256:c7dd06fd7d7b410ca5dc839cc9d485d2bc4ae5240851bcd45d85105cc90a47d7"},
-    {file = "pyarrow-20.0.0-cp310-cp310-macosx_12_0_x86_64.whl", hash = "sha256:d5382de8dc34c943249b01c19110783d0d64b207167c728461add1ecc2db88e4"},
-    {file = "pyarrow-20.0.0-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:6415a0d0174487456ddc9beaead703d0ded5966129fa4fd3114d76b5d1c5ceae"},
-    {file = "pyarrow-20.0.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:15aa1b3b2587e74328a730457068dc6c89e6dcbf438d4369f572af9d320a25ee"},
-    {file = "pyarrow-20.0.0-cp310-cp310-manylinux_2_28_aarch64.whl", hash = "sha256:5605919fbe67a7948c1f03b9f3727d82846c053cd2ce9303ace791855923fd20"},
-    {file = "pyarrow-20.0.0-cp310-cp310-manylinux_2_28_x86_64.whl", hash = "sha256:a5704f29a74b81673d266e5ec1fe376f060627c2e42c5c7651288ed4b0db29e9"},
-    {file = "pyarrow-20.0.0-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:00138f79ee1b5aca81e2bdedb91e3739b987245e11fa3c826f9e57c5d102fb75"},
-    {file = "pyarrow-20.0.0-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:f2d67ac28f57a362f1a2c1e6fa98bfe2f03230f7e15927aecd067433b1e70ce8"},
-    {file = "pyarrow-20.0.0-cp310-cp310-win_amd64.whl", hash = "sha256:4a8b029a07956b8d7bd742ffca25374dd3f634b35e46cc7a7c3fa4c75b297191"},
-    {file = "pyarrow-20.0.0-cp311-cp311-macosx_12_0_arm64.whl", hash = "sha256:24ca380585444cb2a31324c546a9a56abbe87e26069189e14bdba19c86c049f0"},
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 ]
 
 [package.extras]
@@ -5145,7 +5181,7 @@ version = "2025.2"
 description = "World timezone definitions, modern and historical"
 optional = false
 python-versions = "*"
-groups = ["main"]
+groups = ["main", "dev"]
 files = [
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@@ -5256,14 +5292,14 @@ files = [
 
 [[package]]
 name = "ragas"
-version = "0.2.15"
+version = "0.3.0"
 description = ""
 optional = false
 python-versions = ">=3.9"
 groups = ["main"]
 files = [
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 ]
 
 [package.dependencies]
@@ -5281,10 +5317,10 @@ pydantic = ">=2"
 tiktoken = "*"
 
 [package.extras]
-all = ["datacompy", "llama_index", "nltk", "pandas", "r2r", "rapidfuzz", "rouge_score", "sentence-transformers", "transformers"]
-dev = ["black[jupyter]", "datacompy", "fastembed", "graphene", "haystack-ai", "isort", "llama_index", "nltk", "notebook", "pandas", "pyright", "r2r", "rapidfuzz", "rich", "rouge_score", "ruff", "sacrebleu", "sentence-transformers", "sphinx-autobuild", "transformers"]
+all = ["datacompy", "llama_index", "nltk", "pandas", "r2r", "ragas-experimental", "rapidfuzz", "rouge_score", "sentence-transformers", "transformers"]
+dev = ["black[jupyter]", "datacompy", "fastembed", "graphene", "haystack-ai", "llama_index", "nbmake", "nltk", "notebook", "pandas", "pyright", "pytest", "pytest-asyncio", "pytest-xdist[psutil]", "r2r", "rapidfuzz", "rich", "rouge_score", "ruff", "sacrebleu", "sentence-transformers", "sphinx-autobuild", "transformers"]
 docs = ["mkdocs (>=1.6.1)", "mkdocs-autorefs", "mkdocs-gen-files", "mkdocs-git-committers-plugin-2", "mkdocs-git-revision-date-localized-plugin", "mkdocs-glightbox", "mkdocs-literate-nav", "mkdocs-material", "mkdocs-material[imaging]", "mkdocs-section-index", "mkdocstrings[python]"]
-test = ["llama_index", "nbmake", "pytest", "pytest-asyncio", "pytest-xdist[psutil]"]
+experimental = ["ragas-experimental"]
 
 [[package]]
 name = "rapidfuzz"
@@ -6208,6 +6244,28 @@ dev = ["tokenizers[testing]"]
 docs = ["setuptools-rust", "sphinx", "sphinx-rtd-theme"]
 testing = ["black (==22.3)", "datasets", "numpy", "pytest", "requests", "ruff"]
 
+[[package]]
+name = "tornado"
+version = "6.5.1"
+description = "Tornado is a Python web framework and asynchronous networking library, originally developed at FriendFeed."
+optional = false
+python-versions = ">=3.9"
+groups = ["dev"]
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+    {file = "tornado-6.5.1-cp39-abi3-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:253b76040ee3bab8bcf7ba9feb136436a3787208717a1fb9f2c16b744fba7331"},
+    {file = "tornado-6.5.1-cp39-abi3-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:308473f4cc5a76227157cdf904de33ac268af770b2c5f05ca6c1161d82fdd95e"},
+    {file = "tornado-6.5.1-cp39-abi3-musllinux_1_2_aarch64.whl", hash = "sha256:caec6314ce8a81cf69bd89909f4b633b9f523834dc1a352021775d45e51d9401"},
+    {file = "tornado-6.5.1-cp39-abi3-musllinux_1_2_i686.whl", hash = "sha256:13ce6e3396c24e2808774741331638ee6c2f50b114b97a55c5b442df65fd9692"},
+    {file = "tornado-6.5.1-cp39-abi3-musllinux_1_2_x86_64.whl", hash = "sha256:5cae6145f4cdf5ab24744526cc0f55a17d76f02c98f4cff9daa08ae9a217448a"},
+    {file = "tornado-6.5.1-cp39-abi3-win32.whl", hash = "sha256:e0a36e1bc684dca10b1aa75a31df8bdfed656831489bc1e6a6ebed05dc1ec365"},
+    {file = "tornado-6.5.1-cp39-abi3-win_amd64.whl", hash = "sha256:908e7d64567cecd4c2b458075589a775063453aeb1d2a1853eedb806922f568b"},
+    {file = "tornado-6.5.1-cp39-abi3-win_arm64.whl", hash = "sha256:02420a0eb7bf617257b9935e2b754d1b63897525d8a289c9d65690d580b4dcf7"},
+    {file = "tornado-6.5.1.tar.gz", hash = "sha256:84ceece391e8eb9b2b95578db65e920d2a61070260594819589609ba9bc6308c"},
+]
+
 [[package]]
 name = "tqdm"
 version = "4.67.1"
@@ -6320,7 +6378,7 @@ version = "2025.2"
 description = "Provider of IANA time zone data"
 optional = false
 python-versions = ">=2"
-groups = ["main"]
+groups = ["main", "dev"]
 files = [
     {file = "tzdata-2025.2-py2.py3-none-any.whl", hash = "sha256:1a403fada01ff9221ca8044d701868fa132215d84beb92242d9acd2147f667a8"},
     {file = "tzdata-2025.2.tar.gz", hash = "sha256:b60a638fcc0daffadf82fe0f57e53d06bdec2f36c4df66280ae79bce6bd6f2b9"},
@@ -6429,7 +6487,7 @@ version = "5.1.0"
 description = "Python promises."
 optional = false
 python-versions = ">=3.6"
-groups = ["main"]
+groups = ["main", "dev"]
 files = [
     {file = "vine-5.1.0-py3-none-any.whl", hash = "sha256:40fdf3c48b2cfe1c38a49e9ae2da6fda88e4794c810050a728bd7413811fb1dc"},
     {file = "vine-5.1.0.tar.gz", hash = "sha256:8b62e981d35c41049211cf62a0a1242d8c1ee9bd15bb196ce38aefd6799e61e0"},
@@ -6581,7 +6639,7 @@ version = "0.2.13"
 description = "Measures the displayed width of unicode strings in a terminal"
 optional = false
 python-versions = "*"
-groups = ["main"]
+groups = ["main", "dev"]
 files = [
     {file = "wcwidth-0.2.13-py2.py3-none-any.whl", hash = "sha256:3da69048e4540d84af32131829ff948f1e022c1c6bdb8d6102117aac784f6859"},
     {file = "wcwidth-0.2.13.tar.gz", hash = "sha256:72ea0c06399eb286d978fdedb6923a9eb47e1c486ce63e9b4e64fc18303972b5"},
@@ -7191,4 +7249,4 @@ cffi = ["cffi (>=1.11)"]
 [metadata]
 lock-version = "2.1"
 python-versions = "^3.12, <3.13"
-content-hash = "dc93f47ad2ffea514b170c7ba65f07ba1bfa9911b86475fbf2b39f1ed0bd6702"
+content-hash = "0b1cc7cfd0bfb7a9726dbc8be16774f9df3a33d309a8a7973b57ef7569b990d0"
diff --git a/backend/pyproject.toml b/backend/pyproject.toml
index 8626e39..93ec2fe 100644
--- a/backend/pyproject.toml
+++ b/backend/pyproject.toml
@@ -34,9 +34,9 @@ cryptography = "^44.0.2"
 pyjwt = "^2.10.1"
 openpyxl = "^3.1.5"
 celery = { extras = ["redis"], version = "^5.4.0" }
-ragas = "^0.2.14"
 pydantic-settings = "^2.9.1"
 rapidfuzz = "^3.13.0"
+ragas = "^0.3.0"
 
 [tool.poetry.group.dev.dependencies]
 psycopg2-binary = "^2.9.9"
@@ -45,6 +45,7 @@ ruff = "^0.11.2"
 langchain-chroma = "^0.1.2" # just needed for local query
 debugpy = "^1.8.8"
 black = "^24.10.0"
+flower = "^2.0.1"
 
 
 [tool.poetry.group.test.dependencies]
diff --git a/backend/tests/unit/backend/qa_catalog/logic/test_generation.py b/backend/tests/unit/backend/qa_catalog/logic/test_generation.py
index 8cd4d69..5ba80d2 100644
--- a/backend/tests/unit/backend/qa_catalog/logic/test_generation.py
+++ b/backend/tests/unit/backend/qa_catalog/logic/test_generation.py
@@ -87,9 +87,9 @@ def catalog_generator_config(
                 type=generator_type,
                 sample_count=10,
                 knowledge_graph_location=None,
-                query_distribution={
-                    RagasQACatalogQuerySynthesizer.SINGLE_HOP_SPECIFIC: 1.0,
-                },
+                query_distribution=[
+                    RagasQACatalogQuerySynthesizer.SINGLE_HOP_SPECIFIC,
+                ],
                 personas=[
                     RagasQACatalogGeneratorPersona(
                         name="test-persona", description="test description"
@@ -124,12 +124,8 @@ def catalog_generation_data(
 def session_local() -> MockSessionLocal:
     @contextmanager
     def _func():  # noqa: ANN202
-        with patch(
-            "llm_eval.qa_catalog.logic.generation.AsyncSessionLocal",
-        ) as session_local:
-            mock_session = AsyncMock()
-            session_local.begin.return_value.__aenter__.return_value = mock_session
-            yield mock_session
+        mock_session = AsyncMock()
+        yield mock_session
 
     return _func
 
@@ -153,7 +149,7 @@ async def test_generate_catalog_task_happy_path(
         mock_find_qa_catalog.return_value = qa_catalog
         mock_find_data_source_config.return_value = temp_data_source_config
 
-        await generate_catalog(qa_catalog.id, catalog_generation_data)
+        await generate_catalog(mock_session, qa_catalog.id, catalog_generation_data)
 
         mock_find_qa_catalog.assert_called_once_with(mock_session, qa_catalog.id)
         mock_find_data_source_config.assert_called_once_with(
@@ -194,7 +190,7 @@ async def test_generate_catalog_task_temp_data_source_config_not_found(
         mock_find_qa_catalog.return_value = qa_catalog
         mock_find_data_source_config.return_value = None
 
-        await generate_catalog(qa_catalog.id, catalog_generation_data)
+        await generate_catalog(mock_session, qa_catalog.id, catalog_generation_data)
 
         mock_find_qa_catalog.assert_called_once_with(mock_session, qa_catalog.id)
         mock_find_data_source_config.assert_called_once_with(
@@ -308,9 +304,10 @@ def create_model_configuration_from_kwargs(
             return kwargs
 
         async def a_create_synthetic_qa(
-            self, process_sample: Callable[[SyntheticQAPair], Awaitable[Any]]
+            self,
+            process_samples: Callable[[list[SyntheticQAPair]], Awaitable[Any]],
         ) -> None:
-            await process_sample(dummy_pair)
+            await process_samples([dummy_pair])
 
         def create_synthetic_qa(self) -> list[SyntheticQAPair]:
             return [dummy_pair]
diff --git a/backend/tests/unit/backend/qa_catalog/test_router.py b/backend/tests/unit/backend/qa_catalog/test_router.py
index be026af..b489d07 100644
--- a/backend/tests/unit/backend/qa_catalog/test_router.py
+++ b/backend/tests/unit/backend/qa_catalog/test_router.py
@@ -300,9 +300,9 @@ async def test_generate(
                     "type": "RAGAS",
                     "knowledge_graph_location": "/tmp/somefile.pdf",
                     "sample_count": 5,
-                    "query_distribution": {
-                        "SINGLE_HOP_SPECIFIC": 1.5,
-                    },
+                    "query_distribution": [
+                        "SINGLE_HOP_SPECIFIC",
+                    ],
                     "personas": [
                         {"name": "person1", "description": "Beschreibung Persona 1"}
                     ],
diff --git a/backend/tests/unit/qa_catalog/generator/implementation/ragas/test_generator.py b/backend/tests/unit/qa_catalog/generator/implementation/ragas/test_generator.py
index 8bae4e4..5cddca2 100644
--- a/backend/tests/unit/qa_catalog/generator/implementation/ragas/test_generator.py
+++ b/backend/tests/unit/qa_catalog/generator/implementation/ragas/test_generator.py
@@ -2,11 +2,9 @@
 from pathlib import Path
 from random import shuffle
 from typing import Callable, ContextManager, Generator
-from unittest.mock import AsyncMock, MagicMock, patch
+from unittest.mock import MagicMock, patch
 
 import pytest
-from anyio import CapacityLimiter
-from anyio.streams.memory import MemoryObjectSendStream
 from langchain_core.documents import Document
 from ragas.testset.graph import Node, NodeType
 
@@ -32,11 +30,11 @@ def config() -> RagasQACatalogGeneratorConfig:
         type="RAGAS",
         knowledge_graph_location=None,
         sample_count=10,
-        query_distribution={
-            RagasQACatalogQuerySynthesizer.SINGLE_HOP_SPECIFIC: 0.5,
-            RagasQACatalogQuerySynthesizer.MULTI_HOP_SPECIFIC: 0.3,
-            RagasQACatalogQuerySynthesizer.MULTI_HOP_ABSTRACT: 0.2,
-        },
+        query_distribution=[
+            RagasQACatalogQuerySynthesizer.SINGLE_HOP_SPECIFIC,
+            RagasQACatalogQuerySynthesizer.MULTI_HOP_SPECIFIC,
+            RagasQACatalogQuerySynthesizer.MULTI_HOP_ABSTRACT,
+        ],
         personas=None,
     )
 
@@ -175,25 +173,17 @@ async def test_ragas_generator__load_and_process_documents_correctly(
 
 
 @pytest.mark.asyncio
-@pytest.mark.parametrize("weights", [[0.5, 0.3, 0.0], [0.5, 1, 0.2]])
 @patch(
     "llm_eval.qa_catalog.generator.implementation.ragas.generator.RagasQACatalogGenerator.load_chat_model"
 )
-async def test_init_ragas_generator_fails_for_invalid_query_synthesizer(
+async def test_init_ragas_generator_fails_for_empty_query_distribution(
     _: MagicMock,
     config: RagasQACatalogGeneratorConfig,
     data_source_config: QACatalogGeneratorDataSourceConfig,
     ragas_model_config: RagasQACatalogGeneratorModelConfig,
-    weights: list[float],
 ) -> None:
-    invalid_query_synthesizer: dict = {
-        RagasQACatalogQuerySynthesizer.SINGLE_HOP_SPECIFIC: weights[0],
-        RagasQACatalogQuerySynthesizer.MULTI_HOP_ABSTRACT: weights[1],
-        RagasQACatalogQuerySynthesizer.MULTI_HOP_SPECIFIC: weights[2],
-    }
-
-    with pytest.raises(ValueError, match="distribution weights should sum up to 1"):
-        config.query_distribution = invalid_query_synthesizer
+    with pytest.raises(ValueError, match="At least one query synthesizer"):
+        config.query_distribution = []
         RagasQACatalogGenerator(config, data_source_config, ragas_model_config)
 
 
@@ -204,7 +194,7 @@ async def test_ragas_generator_create_document_nodes(
     filenames: list[str],
 ) -> None:
     with ragas_generator_factory() as generator:
-        nodes = generator._create_document_nodes(documents)
+        nodes = generator._create_knowledge_graph_nodes(documents)
 
         assert len(nodes) == len(documents)
         assert all(
@@ -220,33 +210,31 @@ async def test_ragas_generator_has_same_nodes(
 ) -> None:
     with ragas_generator_factory() as generator:
         shuffle(documents)
-        nodes1 = generator._create_document_nodes(documents)
+        nodes1 = generator._create_knowledge_graph_nodes(documents)
         shuffle(documents)
-        nodes2 = generator._create_document_nodes(documents)
+        nodes2 = generator._create_knowledge_graph_nodes(documents)
 
         assert generator._has_same_nodes(nodes1, nodes2)
 
         shuffle(documents)
         documents[0].page_content = "modified content"
-        nodes3 = generator._create_document_nodes(documents)
+        nodes3 = generator._create_knowledge_graph_nodes(documents)
 
         assert not generator._has_same_nodes(nodes1, nodes3)
 
 
 @pytest.mark.asyncio
-@patch("llm_eval.qa_catalog.generator.implementation.ragas.generator.create_backup")
 @patch("llm_eval.qa_catalog.generator.implementation.ragas.generator.KnowledgeGraph")
 async def test_ragas_generator_create_knowledge_graph_new_successfully(
     mock_knowledge_graph: MagicMock,
-    mock_create_backup: MagicMock,
     ragas_generator_factory: RagasGeneratorFactory,
     documents: list[Document],
     nodes: list[Node],
 ) -> None:
     with ragas_generator_factory() as generator:
         generator._load_and_process_documents = MagicMock(return_value=documents)
-        generator._create_document_nodes = MagicMock(return_value=nodes)
-        generator.load_knowledge_graph = MagicMock(return_value=None)
+        generator._create_knowledge_graph_nodes = MagicMock(return_value=nodes)
+        generator.split_documents = MagicMock(return_value=documents)
         generator.apply_knowledge_graph_transformations = MagicMock()
 
         created_kg = mock_knowledge_graph(nodes=nodes)
@@ -254,14 +242,12 @@ async def test_ragas_generator_create_knowledge_graph_new_successfully(
 
         kg = generator.create_knowledge_graph()
 
-        generator._create_document_nodes.assert_called_once_with(documents)
-        generator.load_knowledge_graph.assert_called_once()
-        mock_create_backup.assert_called_once_with(
-            generator.config.knowledge_graph_location
-        )
+        generator._load_and_process_documents.assert_called_once()
+        generator.split_documents.assert_called_once_with(documents)
+        generator._create_knowledge_graph_nodes.assert_called_once_with(documents)
         mock_knowledge_graph.assert_called_with(nodes=nodes)
         generator.apply_knowledge_graph_transformations.assert_called_once_with(
-            created_kg, documents
+            created_kg
         )
         assert kg is not None
 
@@ -276,17 +262,17 @@ async def test_ragas_generator_create_knowledge_graph_use_existing_graph_when_no
 ) -> None:
     with ragas_generator_factory() as generator:
         generator._load_and_process_documents = MagicMock(return_value=documents)
-        generator._create_document_nodes = MagicMock(return_value=nodes)
+        generator._create_knowledge_graph_nodes = MagicMock(return_value=nodes)
+        generator.split_documents = MagicMock(return_value=documents)
         generator.config.knowledge_graph_location = None
         generator.apply_knowledge_graph_transformations = MagicMock(return_value=None)
-        existing_graph = MagicMock(name="existing_graph", nodes=nodes)
-        generator.load_knowledge_graph = MagicMock(return_value=existing_graph)
-        mock_knowledge_graph.return_value = MagicMock(name="generated_graph")
+        generated_graph = MagicMock(name="generated_graph")
+        mock_knowledge_graph.return_value = generated_graph
 
         kg: MagicMock = generator.create_knowledge_graph()  # type: ignore
 
         assert kg is not None
-        assert kg == existing_graph
+        assert kg == generated_graph
 
 
 @pytest.mark.asyncio
@@ -310,14 +296,24 @@ async def test_ragas_generator_load_knowledge_graph(
     with ragas_generator_factory() as generator:
         generator.config.knowledge_graph_location = MagicMock()
         generator.config.knowledge_graph_location.exists = MagicMock(return_value=True)
-        mock_knowledge_graph.load.return_value = MagicMock(name="existing_graph")
+        loaded_graph = MagicMock(name="existing_graph")
+        mock_knowledge_graph.load.return_value = loaded_graph
+
+        # Create proper mock documents with required attributes
+        mock_doc = MagicMock()
+        mock_doc.page_content = "test content"
+        mock_doc.metadata = {"source": "test.txt"}
+        docs = [mock_doc]
 
-        kg = generator.load_knowledge_graph()
+        # Mock _has_same_nodes to return True so the loaded graph is returned
+        generator._has_same_nodes = MagicMock(return_value=True)
+
+        kg = generator.load_exiting_knowledge_graph(docs)
 
         mock_knowledge_graph.load.assert_called_once_with(
             generator.config.knowledge_graph_location
         )
-        assert kg is not None
+        assert kg is loaded_graph
 
 
 @pytest.mark.asyncio
@@ -330,7 +326,8 @@ async def test_ragas_generator_load_knowledge_graph_fails_on_non_existent_file(
         generator.config.knowledge_graph_location = MagicMock()
         generator.config.knowledge_graph_location.exists = MagicMock(return_value=False)
 
-        kg = generator.load_knowledge_graph()
+        docs = [MagicMock()]  # Mock documents
+        kg = generator.load_exiting_knowledge_graph(docs)
 
         assert kg is None
 
@@ -342,7 +339,8 @@ async def test_ragas_generator_load_knowledge_graph_fails_on_none_location(
     with ragas_generator_factory() as generator:
         generator.config.knowledge_graph_location = None
 
-        kg = generator.load_knowledge_graph()
+        docs = [MagicMock()]  # Mock documents
+        kg = generator.load_exiting_knowledge_graph(docs)
 
         assert kg is None
 
@@ -362,7 +360,13 @@ async def test_ragas_generator_load_knowledge_graph_fails_on_load(
         generator.config.knowledge_graph_location.exists = MagicMock(return_value=True)
         mock_knowledge_graph.load.side_effect = RuntimeError("Load failed")
 
-        kg = generator.load_knowledge_graph()
+        # Create proper mock documents with required attributes
+        mock_doc = MagicMock()
+        mock_doc.page_content = "test content"
+        mock_doc.metadata = {"source": "test.txt"}
+        docs = [mock_doc]
+
+        kg = generator.load_exiting_knowledge_graph(docs)
 
         mock_knowledge_graph.load.assert_called_once_with(
             generator.config.knowledge_graph_location
@@ -382,117 +386,72 @@ async def test_ragas_generator_generate_testset(
 
         mock_testset_generator = MagicMock()
         mock_testset_generator.generate.return_value = ["generated query"]
-        testset = generator.generate_testset(mock_testset_generator, 1)
-
-        assert testset[0] == "generated query"  # type: ignore
-
-
-@pytest.mark.asyncio
-@patch(
-    "llm_eval.qa_catalog.generator.implementation.ragas.generator.ragas_sample_to_synthetic_qa_pair",
-)
-async def test_ragas_generator_generate_single_sample(
-    mock_from_ragas: MagicMock,
-    ragas_generator_factory: RagasGeneratorFactory,
-) -> None:
-    with ragas_generator_factory() as generator:
-        generator.generate_testset = MagicMock(return_value=MagicMock(samples=[1]))
-        mock_from_ragas.return_value = "sample"
-
-        send_sample = MagicMock()
-        send_sample.send = AsyncMock()
-        limiter = MagicMock()
-
-        await generator._generate_single_sample(MagicMock(), send_sample, limiter)
 
-        send_sample.send.assert_called_once_with("sample")
+        # Provide a non-empty query distribution
+        mock_synthesizer = MagicMock()
+        query_distribution = [(mock_synthesizer, 1.0)]
 
-
-@pytest.mark.asyncio
-async def test_ragas_generator_generate_single_sample_wont_send_when_fails(
-    ragas_generator_factory: RagasGeneratorFactory,
-) -> None:
-    with ragas_generator_factory() as generator:
-        generator.generate_testset = MagicMock(
-            side_effect=RuntimeError("sample generation failed")
+        testset = generator.generate_testset(
+            mock_testset_generator, 1, query_distribution
         )
 
-        send_sample = MagicMock()
-        send_sample.send = AsyncMock()
-        limiter = MagicMock()
-
-        await generator._generate_single_sample(MagicMock(), send_sample, limiter)
-
-        send_sample.send.assert_not_called()
-
-
-@pytest.mark.asyncio
-async def test_ragas_generator_generate_single_sample_does_nothing_on_empty_generated_testset(  # noqa: E501
-    ragas_generator_factory: RagasGeneratorFactory,
-) -> None:
-    with ragas_generator_factory() as generator:
-        generator.generate_testset = MagicMock(return_value=MagicMock(samples=[]))
-
-        send_sample = MagicMock()
-        send_sample.send = AsyncMock()
-        limiter = MagicMock()
-
-        await generator._generate_single_sample(MagicMock(), send_sample, limiter)
-
-        send_sample.send.assert_not_called()
+        assert testset[0] == "generated query"  # type: ignore
 
 
 @pytest.mark.asyncio
 @patch(
-    "llm_eval.qa_catalog.generator.implementation.ragas.generator.TestsetGenerator",
-    new_callable=AsyncMock,
-)
-@patch(
-    "llm_eval.qa_catalog.generator.implementation.ragas.generator.RagasQACatalogGenerator.load_chat_model",
-    new_callable=AsyncMock,
-)
-@patch(
-    "llm_eval.qa_catalog.generator.implementation.ragas.generator.copy",
-    new_callable=AsyncMock,
+    "llm_eval.qa_catalog.generator.implementation.ragas.generator.ragas_sample_to_synthetic_qa_pair"
 )
+@patch("ragas.testset.persona.generate_personas_from_kg")
 async def test_ragas_generator_a_create_synthetic_qa_successfull(
-    mock_copy: AsyncMock,
-    mock_load_chat_model: AsyncMock,
-    mock_testset_generator: AsyncMock,
-    config: RagasQACatalogGeneratorConfig,
-    ragas_model_config: RagasQACatalogGeneratorModelConfig,
-    data_source_config: QACatalogGeneratorDataSourceConfig,
+    mock_generate_personas: MagicMock,
+    mock_ragas_sample_to_qa_pair: MagicMock,
+    ragas_generator_factory: RagasGeneratorFactory,
 ) -> None:
-    generator = RagasQACatalogGenerator(config, data_source_config, ragas_model_config)
-    generator.create_knowledge_graph = AsyncMock()
-
-    sample = SyntheticQAPair(
-        id="1",
-        question="question",
-        expected_output="expected_output",
-        contexts=[],
-        meta_data={},
-    )
-
-    async def mock_generate(
-        _,  # noqa: ANN001
-        send_sample: MemoryObjectSendStream[SyntheticQAPair | None],
-        limiter: CapacityLimiter,
-    ) -> None:
-        async with limiter:
-            async with send_sample:
-                await send_sample.send(sample)
+    with ragas_generator_factory() as generator:
+        # Mock knowledge graph
+        mock_kg = MagicMock()
+        mock_kg.nodes = []
+        generator.create_knowledge_graph = MagicMock(return_value=mock_kg)
+
+        # Mock personas
+        mock_persona = MagicMock()
+        mock_generate_personas.return_value = [mock_persona]
+
+        # Mock query distribution
+        mock_synthesizer = MagicMock()
+        generator.create_query_distribution = MagicMock(
+            return_value=[(mock_synthesizer, 1.0)]
+        )
 
-    generator._generate_single_sample = AsyncMock(side_effect=mock_generate)
+        # Mock testset generation
+        mock_testset = MagicMock()
+        mock_sample = MagicMock()
+        mock_testset.samples = [mock_sample]
+        generator.generate_testset = MagicMock(return_value=mock_testset)
+
+        # Mock conversion to SyntheticQAPair
+        synthetic_qa_pair = SyntheticQAPair(
+            id="1",
+            question="test question",
+            expected_output="test answer",
+            contexts=[],
+            meta_data={},
+        )
+        mock_ragas_sample_to_qa_pair.return_value = synthetic_qa_pair
 
-    samples = []
+        # Collect samples
+        collected_samples = []
 
-    async def process_sample(sample: SyntheticQAPair) -> None:
-        samples.append(sample)
+        async def collect_samples_fn(samples: list[SyntheticQAPair]) -> None:
+            collected_samples.extend(samples)
 
-    await generator.a_create_synthetic_qa(process_sample)
+        # Test the method
+        await generator.a_create_synthetic_qa(collect_samples_fn)
 
-    assert len(samples) == generator.config.sample_count
+        # Verify results
+        assert len(collected_samples) == 1
+        assert collected_samples[0] == synthetic_qa_pair
 
 
 @pytest.mark.asyncio
diff --git a/frontend/app/[locale]/(authenticated)/eval/[evaluationId]/edit/components/evaluation-edit-form-wizard.tsx b/frontend/app/[locale]/(authenticated)/eval/[evaluationId]/edit/components/evaluation-edit-form-wizard.tsx
index 54d76f5..f59eabc 100644
--- a/frontend/app/[locale]/(authenticated)/eval/[evaluationId]/edit/components/evaluation-edit-form-wizard.tsx
+++ b/frontend/app/[locale]/(authenticated)/eval/[evaluationId]/edit/components/evaluation-edit-form-wizard.tsx
@@ -16,7 +16,7 @@ import { FormWizard, SubmitData } from "@/app/[locale]/components/form-wizard";
 import {
   evaluationsPatch,
   EvaluationUpdate,
-  RagEvalBackendEvalEvaluationsModelsEvaluationResult,
+  LlmEvalEvalEvaluationsModelsEvaluationResult,
 } from "@/app/client";
 import { EditOrigin } from "@/app/types/edit-origin";
 import { callApi } from "@/app/utils/backend-client/client";
@@ -32,7 +32,7 @@ const editSchema = z.object({
 const schemas = { default: editSchema };
 
 export type EvaluationEditFormWizardProps = {
-  evaluation: RagEvalBackendEvalEvaluationsModelsEvaluationResult;
+  evaluation: LlmEvalEvalEvaluationsModelsEvaluationResult;
   origin?: EditOrigin;
 };
 
diff --git a/frontend/app/[locale]/(authenticated)/eval/[evaluationId]/edit/page.test.tsx b/frontend/app/[locale]/(authenticated)/eval/[evaluationId]/edit/page.test.tsx
index c69f652..9439420 100644
--- a/frontend/app/[locale]/(authenticated)/eval/[evaluationId]/edit/page.test.tsx
+++ b/frontend/app/[locale]/(authenticated)/eval/[evaluationId]/edit/page.test.tsx
@@ -12,7 +12,7 @@ import {
   evaluationsGet,
   evaluationsPatch,
   EvaluationStatus,
-  RagEvalBackendEvalEvaluationsModelsEvaluationResult,
+  LlmEvalEvalEvaluationsModelsEvaluationResult,
 } from "@/app/client";
 import {
   expectInputError,
@@ -29,7 +29,7 @@ vi.mock("@/app/client");
 
 describe("Edit Evaluation Page", () => {
   const evaluationId = "123";
-  const testEvaluation: RagEvalBackendEvalEvaluationsModelsEvaluationResult = {
+  const testEvaluation: LlmEvalEvalEvaluationsModelsEvaluationResult = {
     id: evaluationId,
     name: "Evaluation Name",
     createdAt: "2022-01-01T00:00:00Z",
diff --git a/frontend/app/[locale]/(authenticated)/eval/[evaluationId]/results/[evaluationResultId]/components/evaluation-result-details.tsx b/frontend/app/[locale]/(authenticated)/eval/[evaluationId]/results/[evaluationResultId]/components/evaluation-result-details.tsx
index 6147a63..cfb82e2 100644
--- a/frontend/app/[locale]/(authenticated)/eval/[evaluationId]/results/[evaluationResultId]/components/evaluation-result-details.tsx
+++ b/frontend/app/[locale]/(authenticated)/eval/[evaluationId]/results/[evaluationResultId]/components/evaluation-result-details.tsx
@@ -8,7 +8,7 @@ import {
   PropertyList,
   PropertyListItem,
 } from "@/app/[locale]/components/property-list";
-import { RagEvalBackendEvalEvaluateResultsRouterEvaluationResult as EvaluationResult } from "@/app/client";
+import { LlmEvalEvalEvaluateResultsRouterEvaluationResult as EvaluationResult } from "@/app/client";
 
 const TextValue = ({ children }: PropsWithChildren) => {
   return <div className="whitespace-pre-wrap overflow-x-auto">{children}</div>;
diff --git a/frontend/app/[locale]/(authenticated)/eval/[evaluationId]/results/[evaluationResultId]/page.test.tsx b/frontend/app/[locale]/(authenticated)/eval/[evaluationId]/results/[evaluationResultId]/page.test.tsx
index b09fb5f..0bc8f66 100644
--- a/frontend/app/[locale]/(authenticated)/eval/[evaluationId]/results/[evaluationResultId]/page.test.tsx
+++ b/frontend/app/[locale]/(authenticated)/eval/[evaluationId]/results/[evaluationResultId]/page.test.tsx
@@ -6,8 +6,8 @@ import {
   evaluationResultsGet,
   evaluationsGet,
   EvaluationStatus,
-  RagEvalBackendEvalEvaluateResultsRouterEvaluationResult,
-  RagEvalBackendEvalEvaluationsModelsEvaluationResult,
+  LlmEvalEvalEvaluateResultsRouterEvaluationResult,
+  LlmEvalEvalEvaluationsModelsEvaluationResult,
   TestCaseStatus,
 } from "@/app/client";
 import { expectValue } from "@/app/test-utils/details-page";
@@ -19,92 +19,89 @@ import Page from "./page";
 vi.mock("@/app/client");
 
 describe("Evaluation Result Page", () => {
-  const fullTestCase: RagEvalBackendEvalEvaluateResultsRouterEvaluationResult =
-    {
-      id: "tc1",
-      actualOutput: "actual",
-      expectedOutput: "expected",
-      status: TestCaseStatus.SUCCESS,
-      configurationId: "configId1",
-      configurationName: "configName1",
-      configurationVersion: "configVersion1",
-      context: ["context"],
-      input: "input",
-      metaData: {},
-      metricsData: [
-        {
-          id: "m1",
-          name: "metric1",
-          score: 0.5,
-          error: null,
-          evaluationModel: "evalModel1",
-          reason: "reason1",
-          success: true,
-          threshold: 0.3,
-          strictMode: true,
-        },
-        {
-          id: "m2",
-          name: "metric2",
-          score: 0.6,
-          error: "",
-          evaluationModel: "",
-          reason: "",
-          success: false,
-          threshold: 0.7,
-          strictMode: false,
-        },
-        {
-          id: "m3",
-          name: "metric3",
-          score: null,
-          error: "error3",
-          evaluationModel: null,
-          reason: null,
-          success: false,
-          threshold: 0.7,
-          strictMode: false,
-        },
-      ],
-      retrievalContext: ["retrievalContext"],
-      error: null,
-    };
-
-  const minimalTestCase: RagEvalBackendEvalEvaluateResultsRouterEvaluationResult =
-    {
-      id: "tc1",
-      expectedOutput: "expected",
-      actualOutput: null,
-      status: TestCaseStatus.PENDING,
-      configurationId: null,
-      configurationName: null,
-      configurationVersion: null,
-      context: null,
-      input: "input",
-      metaData: null,
-      metricsData: [],
-      retrievalContext: null,
-      error: null,
-    };
-
-  const emptyTestCase: RagEvalBackendEvalEvaluateResultsRouterEvaluationResult =
-    {
-      id: "tc1",
-      expectedOutput: "expected",
-      actualOutput: "",
-      status: TestCaseStatus.PENDING,
-      configurationId: null,
-      configurationName: null,
-      configurationVersion: null,
-      context: [],
-      input: "input",
-      metaData: {},
-      metricsData: [],
-      retrievalContext: [],
-      error: null,
-    };
-
-  const evaluation: RagEvalBackendEvalEvaluationsModelsEvaluationResult = {
+  const fullTestCase: LlmEvalEvalEvaluateResultsRouterEvaluationResult = {
+    id: "tc1",
+    actualOutput: "actual",
+    expectedOutput: "expected",
+    status: TestCaseStatus.SUCCESS,
+    configurationId: "configId1",
+    configurationName: "configName1",
+    configurationVersion: "configVersion1",
+    context: ["context"],
+    input: "input",
+    metaData: {},
+    metricsData: [
+      {
+        id: "m1",
+        name: "metric1",
+        score: 0.5,
+        error: null,
+        evaluationModel: "evalModel1",
+        reason: "reason1",
+        success: true,
+        threshold: 0.3,
+        strictMode: true,
+      },
+      {
+        id: "m2",
+        name: "metric2",
+        score: 0.6,
+        error: "",
+        evaluationModel: "",
+        reason: "",
+        success: false,
+        threshold: 0.7,
+        strictMode: false,
+      },
+      {
+        id: "m3",
+        name: "metric3",
+        score: null,
+        error: "error3",
+        evaluationModel: null,
+        reason: null,
+        success: false,
+        threshold: 0.7,
+        strictMode: false,
+      },
+    ],
+    retrievalContext: ["retrievalContext"],
+    error: null,
+  };
+
+  const minimalTestCase: LlmEvalEvalEvaluateResultsRouterEvaluationResult = {
+    id: "tc1",
+    expectedOutput: "expected",
+    actualOutput: null,
+    status: TestCaseStatus.PENDING,
+    configurationId: null,
+    configurationName: null,
+    configurationVersion: null,
+    context: null,
+    input: "input",
+    metaData: null,
+    metricsData: [],
+    retrievalContext: null,
+    error: null,
+  };
+
+  const emptyTestCase: LlmEvalEvalEvaluateResultsRouterEvaluationResult = {
+    id: "tc1",
+    expectedOutput: "expected",
+    actualOutput: "",
+    status: TestCaseStatus.PENDING,
+    configurationId: null,
+    configurationName: null,
+    configurationVersion: null,
+    context: [],
+    input: "input",
+    metaData: {},
+    metricsData: [],
+    retrievalContext: [],
+    error: null,
+  };
+
+  const evaluation: LlmEvalEvalEvaluationsModelsEvaluationResult = {
     id: "eval1",
     name: "evaluation",
     createdAt: "2021-01-01T00:00:00Z",
@@ -161,7 +158,7 @@ describe("Evaluation Result Page", () => {
   });
 
   const expectTestCase = async (
-    testCase: RagEvalBackendEvalEvaluateResultsRouterEvaluationResult,
+    testCase: LlmEvalEvalEvaluateResultsRouterEvaluationResult,
   ) => {
     await expectValue("EvaluationResultDetails.input", testCase.input);
     await expectValue(
@@ -213,7 +210,7 @@ describe("Evaluation Result Page", () => {
   };
 
   const mockApi = (
-    testCase: RagEvalBackendEvalEvaluateResultsRouterEvaluationResult,
+    testCase: LlmEvalEvalEvaluateResultsRouterEvaluationResult,
   ) => {
     vi.mocked(evaluationsGet).mockResolvedValue(
       successfulServiceResponse(evaluation),
diff --git a/frontend/app/[locale]/(authenticated)/eval/new/page.test.tsx b/frontend/app/[locale]/(authenticated)/eval/new/page.test.tsx
index 4b3c3ad..7271baf 100644
--- a/frontend/app/[locale]/(authenticated)/eval/new/page.test.tsx
+++ b/frontend/app/[locale]/(authenticated)/eval/new/page.test.tsx
@@ -16,6 +16,7 @@ import {
   LlmEndpoint,
   llmEndpointsGet,
   llmEndpointsGetAll,
+  LlmEvalEvalEvaluationsModelsEvaluationResult,
   Metric,
   MetricConfigurationRead,
   metricsGetAll,
@@ -25,7 +26,6 @@ import {
   qaCatalogGetAll,
   QaCatalogPreview,
   QaCatalogStatus,
-  RagEvalBackendEvalEvaluationsModelsEvaluationResult,
 } from "@/app/client";
 import {
   expectComboBoxError,
@@ -278,7 +278,7 @@ describe("New Evaluation Page", () => {
   };
 
   const mockEvaluationCreate = () => {
-    const evaluation: RagEvalBackendEvalEvaluationsModelsEvaluationResult = {
+    const evaluation: LlmEvalEvalEvaluationsModelsEvaluationResult = {
       id: "1",
       name: "Test Execution",
       createdAt: "2021-09-01T00:00:00Z",
diff --git a/frontend/app/[locale]/(authenticated)/qa-catalogs/generate/components/qa-catalog-generation-form-wizard.tsx b/frontend/app/[locale]/(authenticated)/qa-catalogs/generate/components/qa-catalog-generation-form-wizard.tsx
index 7b98f6b..7246f6b 100644
--- a/frontend/app/[locale]/(authenticated)/qa-catalogs/generate/components/qa-catalog-generation-form-wizard.tsx
+++ b/frontend/app/[locale]/(authenticated)/qa-catalogs/generate/components/qa-catalog-generation-form-wizard.tsx
@@ -17,8 +17,8 @@ import {
   ActiveQaCatalogGeneratorType,
   qaCatalogCreateDataSourceConfig,
   qaCatalogGenerate,
+  QaCatalogGenerationConfig,
   QaCatalogGenerationData,
-  RagasQaCatalogGeneratorConfig,
 } from "@/app/client";
 import { callApi } from "@/app/utils/backend-client/client";
 import { useRouter } from "@/i18n/routing";
@@ -109,7 +109,7 @@ export const QACatalogGeneratorFormWizard = ({
         generatorType: data.configuration.type,
       });
 
-      const config: RagasQaCatalogGeneratorConfig = {
+      const config: QaCatalogGenerationConfig = {
         ...data.configuration.config,
         type: data.configuration.type,
         knowledgeGraphLocation: null,
diff --git a/frontend/app/[locale]/(authenticated)/qa-catalogs/generate/page.test.tsx b/frontend/app/[locale]/(authenticated)/qa-catalogs/generate/page.test.tsx
index 4b5a860..7175ff6 100644
--- a/frontend/app/[locale]/(authenticated)/qa-catalogs/generate/page.test.tsx
+++ b/frontend/app/[locale]/(authenticated)/qa-catalogs/generate/page.test.tsx
@@ -1,6 +1,6 @@
+import "@/app/test-utils/mock-intl";
 import "@/app/test-utils/mock-router";
 import "@/app/test-utils/mock-toast";
-import "@/app/test-utils/mock-intl";
 
 import { addToast } from "@heroui/react";
 import {
@@ -24,6 +24,7 @@ import {
   QaCatalogGenerationConfig,
   QaCatalogGenerationModelConfigurationSchema,
   qaCatalogGetGeneratorTypes,
+  RagasQaCatalogQuerySynthesizer,
 } from "@/app/client";
 import {
   clearComboBox,
@@ -105,7 +106,7 @@ describe("Synthetic QA Catalog Generation Page", () => {
 
       await clearComboBox(user, ragasLabel("llmEndpointId"));
 
-      await inputDistributionsForRagas(testCase.configuration, true);
+      await inputDistributionsForRagas(testCase.configuration);
     }
   };
 
@@ -143,11 +144,10 @@ describe("Synthetic QA Catalog Generation Page", () => {
       configuration: {
         type: "RAGAS",
         personas: [],
-        queryDistribution: {
-          MULTI_HOP_ABSTRACT: 0,
-          MULTI_HOP_SPECIFIC: 0.5,
-          SINGLE_HOP_SPECIFIC: 0.5,
-        },
+        queryDistribution: [
+          RagasQaCatalogQuerySynthesizer.MULTI_HOP_SPECIFIC,
+          RagasQaCatalogQuerySynthesizer.SINGLE_HOP_SPECIFIC,
+        ],
         sampleCount: 5,
         knowledgeGraphLocation: null,
       },
@@ -168,11 +168,11 @@ describe("Synthetic QA Catalog Generation Page", () => {
           { name: "p-1", description: "description-1" },
           { name: "p-2", description: "description-2" },
         ],
-        queryDistribution: {
-          MULTI_HOP_ABSTRACT: 0.2,
-          MULTI_HOP_SPECIFIC: 0.4,
-          SINGLE_HOP_SPECIFIC: 0.4,
-        },
+        queryDistribution: [
+          RagasQaCatalogQuerySynthesizer.MULTI_HOP_ABSTRACT,
+          RagasQaCatalogQuerySynthesizer.MULTI_HOP_SPECIFIC,
+          RagasQaCatalogQuerySynthesizer.SINGLE_HOP_SPECIFIC,
+        ],
         sampleCount: 5,
         knowledgeGraphLocation: null,
       },
@@ -181,7 +181,7 @@ describe("Synthetic QA Catalog Generation Page", () => {
         llmEndpoint: "llm-1",
       },
       dataSourceConfigId: "data-source-config-2",
-      files: createFiles(["file-1", "file-2"]),
+      files: createFiles(["file-3", "file-4"]),
     },
   ];
 
@@ -396,20 +396,50 @@ describe("Synthetic QA Catalog Generation Page", () => {
 
   const inputDistributionsForRagas = async (
     configuration: QaCatalogGenerationConfig,
-    clear: boolean = false,
   ) => {
     if (configuration.type == "RAGAS") {
-      const distributions = configuration.queryDistribution;
-
-      for (const [synth, weight] of Object.entries(distributions)) {
-        const slider = screen.getByTestId(`queryDistributionSlider-${synth}`);
-        const sliderInput = within(slider).getByRole("slider", {
-          hidden: true,
-        });
+      const selectedSynthesizers = configuration.queryDistribution;
+
+      // First, uncheck all checkboxes to start from clean state
+      const allSynthesizers = [
+        RagasQaCatalogQuerySynthesizer.MULTI_HOP_ABSTRACT,
+        RagasQaCatalogQuerySynthesizer.MULTI_HOP_SPECIFIC,
+        RagasQaCatalogQuerySynthesizer.SINGLE_HOP_SPECIFIC,
+      ];
+
+      for (const synth of allSynthesizers) {
+        const checkbox = screen.queryByTestId(
+          `queryDistributionCheckbox-${synth}`,
+        );
+        if (checkbox) {
+          // Check if checkbox is currently selected (either checked attribute or data-selected attribute)
+          const isChecked =
+            checkbox.getAttribute("checked") !== null ||
+            checkbox.getAttribute("data-selected") === "true";
+
+          if (isChecked) {
+            fireEvent.click(checkbox);
+            // Wait a bit for the state to update
+            await new Promise((resolve) => setTimeout(resolve, 10));
+          }
+        }
+      }
 
-        fireEvent.change(sliderInput, {
-          target: { value: clear ? 0 : weight },
-        });
+      // Then check the ones we want
+      for (const synth of selectedSynthesizers) {
+        const checkbox = screen.getByTestId(
+          `queryDistributionCheckbox-${synth}`,
+        );
+        // Check if checkbox is currently unselected
+        const isChecked =
+          checkbox.getAttribute("checked") !== null ||
+          checkbox.getAttribute("data-selected") === "true";
+
+        if (!isChecked) {
+          fireEvent.click(checkbox);
+          // Wait a bit for the state to update
+          await new Promise((resolve) => setTimeout(resolve, 10));
+        }
       }
     }
   };
diff --git a/frontend/app/[locale]/(authenticated)/qa-catalogs/plugins/implementations/ragas.tsx b/frontend/app/[locale]/(authenticated)/qa-catalogs/plugins/implementations/ragas.tsx
index 71d244e..1a32809 100644
--- a/frontend/app/[locale]/(authenticated)/qa-catalogs/plugins/implementations/ragas.tsx
+++ b/frontend/app/[locale]/(authenticated)/qa-catalogs/plugins/implementations/ragas.tsx
@@ -2,7 +2,8 @@ import {
   Accordion,
   AccordionItem,
   Button,
-  Slider,
+  Checkbox,
+  CheckboxGroup,
   Textarea,
 } from "@heroui/react";
 import { cx } from "classix";
@@ -30,16 +31,9 @@ const synthesizerTypes = Object.values(RagasQaCatalogQuerySynthesizer) as [
 
 const synthesizerTypeEnum = z.enum(synthesizerTypes);
 
-const getDefaultSynthesizerValues = (): {
-  [key: string]: number;
-} =>
-  synthesizerTypes.reduce(
-    (acc, t) => {
-      acc[t] = 0;
-      return acc;
-    },
-    {} as { [key: string]: number },
-  );
+const getDefaultSynthesizerValues = (): RagasQaCatalogQuerySynthesizer[] => [
+  RagasQaCatalogQuerySynthesizer.SINGLE_HOP_SPECIFIC,
+];
 
 const ragasGeneratorConfigurationShape = {
   config: z.object({
@@ -50,18 +44,9 @@ const ragasGeneratorConfigurationShape = {
       })
       .int({ message: formErrors.int })
       .min(1, { message: formErrors.required }),
-    queryDistribution: z.record(synthesizerTypeEnum, z.number()).refine(
-      (distribution) => {
-        const sum = Object.values(distribution).reduce(
-          (acc, val) => acc + (val == undefined ? 0 : val),
-          0,
-        );
-        return Math.abs(sum - 1) < Number.EPSILON;
-      },
-      {
-        message: "The sum of all values in queryDistribution must equal 1",
-      },
-    ),
+    queryDistribution: z
+      .array(synthesizerTypeEnum)
+      .min(1, { message: "At least one query synthesizer must be selected" }),
     personas: z
       .array(
         z.object({
@@ -220,46 +205,38 @@ const QueryDistributionForm = ({
         </span>
       </div>
       <div className="flex flex-col space-y-3">
-        {synthesizerTypes.map((synth) => (
-          <Controller
-            name={`config.queryDistribution.${synth}`}
-            control={control}
-            key={synth}
-            render={({ field, formState: { errors } }) => (
-              <div className="flex flex-col space-x-2 align-items-center items-end justify-center">
-                <Slider
-                  defaultValue={field.value}
-                  label={t(
-                    `RagasQACatalogGeneratorConfigurationForm.field.queryDistribution.values.${synth}.title`,
-                  )}
-                  maxValue={1}
-                  minValue={0}
-                  step={0.1}
-                  showSteps={true}
-                  size={"sm"}
-                  onChange={(v) => field.onChange(v)}
-                  color={distributionError ? "danger" : "primary"}
-                  data-testid={`queryDistributionSlider-${synth}`}
-                />
-                <span className="text-default-500 text-sm text-left w-full">
-                  {t(
-                    `RagasQACatalogGeneratorConfigurationForm.field.queryDistribution.values.${synth}.description`,
-                  )}
-                </span>
-                {errors.config?.queryDistribution?.[synth] && (
-                  <span className="text-danger text-sm">
-                    {errors.config.queryDistribution[synth].message}
+        <Controller
+          name="config.queryDistribution"
+          control={control}
+          render={({ field }) => (
+            <CheckboxGroup
+              value={field.value}
+              onValueChange={field.onChange}
+              orientation="vertical"
+              color="primary"
+              isInvalid={queryDistributionInvalid}
+              errorMessage={distributionError?.message}
+            >
+              {synthesizerTypes.map((synth) => (
+                <div key={synth} className="flex flex-col space-y-1">
+                  <Checkbox
+                    value={synth}
+                    data-testid={`queryDistributionCheckbox-${synth}`}
+                  >
+                    {t(
+                      `RagasQACatalogGeneratorConfigurationForm.field.queryDistribution.values.${synth}.title`,
+                    )}
+                  </Checkbox>
+                  <span className="text-default-500 text-sm ml-6">
+                    {t(
+                      `RagasQACatalogGeneratorConfigurationForm.field.queryDistribution.values.${synth}.description`,
+                    )}
                   </span>
-                )}
-              </div>
-            )}
-          />
-        ))}
-        {distributionError && (
-          <span className="text-danger text-sm">
-            {distributionError.root?.message}
-          </span>
-        )}
+                </div>
+              ))}
+            </CheckboxGroup>
+          )}
+        />
       </div>
     </div>
   );
@@ -324,11 +301,11 @@ export const ragasGeneratorPlugin = createQACatalogGenerationPlugin({
   configurationForm: RagasGeneratorConfigurationForm,
   getDefaults: () => ({
     config: {
+      type: "RAGAS" as const,
       sampleCount: 5,
-      queryDistribution: {
-        ...getDefaultSynthesizerValues(),
-        SINGLE_HOP_SPECIFIC: 1,
-      },
+      queryDistribution: getDefaultSynthesizerValues(),
+      personas: [],
+      knowledgeGraphLocation: null,
     },
     modelConfig: { llmEndpoint: null },
   }),
diff --git a/frontend/app/client/types.gen.ts b/frontend/app/client/types.gen.ts
index 3435b33..a0bb463 100644
--- a/frontend/app/client/types.gen.ts
+++ b/frontend/app/client/types.gen.ts
@@ -1,7 +1,7 @@
 // This file is auto-generated by @hey-api/openapi-ts
 
 export type ActiveQaCatalogGeneratorType = {
-  type: "RAGAS" | "DEEPEVAL";
+  type: "RAGAS";
 };
 
 export type AnswerRelevancyMetricConfigurationCreate = {
@@ -69,7 +69,7 @@ export type AzureOpenAillmEndpointConfigurationUpdate = {
 export type Base64DownloadUrl = string;
 
 export type BodyCreateDataSourceConfigV1QaCatalogGeneratorUploadPost = {
-  generator_type: "RAGAS" | "DEEPEVAL";
+  generator_type: "RAGAS";
   files: Array<Blob | File>;
 };
 
@@ -142,18 +142,6 @@ export type DashboardStatistics = {
   numberOfEvaluations: number;
 };
 
-export type DeepevalQaCatalogGeneratorConfig = {
-  type: "DEEPEVAL";
-  goldensPerDoc: number;
-  numEvolutions: number;
-  parallelQueries: number;
-};
-
-export type DeepevalQaCatalogGeneratorModelConfigSchema = {
-  type: "DEEPEVAL";
-  llmEndpoint: string;
-};
-
 export type DeleteCatalogResult = {
   previousRevisionId: string | null;
 };
@@ -553,21 +541,27 @@ export type QaCatalog = {
   error?: string | null;
 };
 
-export type QaCatalogGenerationConfig =
-  | RagasQaCatalogGeneratorConfig
-  | DeepevalQaCatalogGeneratorConfig;
+export type QaCatalogGenerationConfig = {
+  type: "RAGAS";
+  knowledgeGraphLocation: string | null;
+  sampleCount: number;
+  queryDistribution: Array<RagasQaCatalogQuerySynthesizer>;
+  personas: Array<RagasQaCatalogGeneratorPersona> | null;
+  useExistingKnowledgeGraph?: boolean;
+};
 
 export type QaCatalogGenerationData = {
-  type: "RAGAS" | "DEEPEVAL";
+  type: "RAGAS";
   name: string;
   config: QaCatalogGenerationConfig;
   dataSourceConfigId: string;
   modelConfigSchema: QaCatalogGenerationModelConfigurationSchema;
 };
 
-export type QaCatalogGenerationModelConfigurationSchema =
-  | RagasQaCatalogGeneratorModelConfigSchema
-  | DeepevalQaCatalogGeneratorModelConfigSchema;
+export type QaCatalogGenerationModelConfigurationSchema = {
+  type: "RAGAS";
+  llmEndpoint: string;
+};
 
 export type QaCatalogGenerationResult = {
   catalogId: string;
@@ -620,21 +614,6 @@ export type QaCatalogEvaluationResult = {
   name: string;
 };
 
-export type RagasQaCatalogGeneratorConfig = {
-  type: "RAGAS";
-  knowledgeGraphLocation: string | null;
-  sampleCount: number;
-  queryDistribution: {
-    [key: string]: number;
-  };
-  personas: Array<RagasQaCatalogGeneratorPersona> | null;
-};
-
-export type RagasQaCatalogGeneratorModelConfigSchema = {
-  type: "RAGAS";
-  llmEndpoint: string;
-};
-
 export type RagasQaCatalogGeneratorPersona = {
   name: string;
   description: string;
@@ -702,7 +681,7 @@ export type ValidationError = {
   type: string;
 };
 
-export type RagEvalBackendEvalEvaluateResultsRouterEvaluationResult = {
+export type LlmEvalEvalEvaluateResultsRouterEvaluationResult = {
   id: string;
   configurationId: string | null;
   configurationName: string | null;
@@ -718,7 +697,7 @@ export type RagEvalBackendEvalEvaluateResultsRouterEvaluationResult = {
   error: string | null;
 };
 
-export type RagEvalBackendEvalEvaluationsModelsEvaluationResult = {
+export type LlmEvalEvalEvaluationsModelsEvaluationResult = {
   id: string;
   name: string;
   createdAt: string;
@@ -794,7 +773,7 @@ export type EvaluationsPostResponses = {
   /**
    * Successful Response
    */
-  200: RagEvalBackendEvalEvaluationsModelsEvaluationResult;
+  200: LlmEvalEvalEvaluationsModelsEvaluationResult;
 };
 
 export type EvaluationsPostResponse =
@@ -849,7 +828,7 @@ export type EvaluationsGetResponses = {
   /**
    * Successful Response
    */
-  200: RagEvalBackendEvalEvaluationsModelsEvaluationResult;
+  200: LlmEvalEvalEvaluationsModelsEvaluationResult;
 };
 
 export type EvaluationsGetResponse =
@@ -882,7 +861,7 @@ export type EvaluationsPatchResponses = {
   /**
    * Successful Response
    */
-  200: RagEvalBackendEvalEvaluationsModelsEvaluationResult;
+  200: LlmEvalEvalEvaluationsModelsEvaluationResult;
 };
 
 export type EvaluationsPatchResponse =
@@ -1005,7 +984,7 @@ export type EvaluationResultsGetResponses = {
   /**
    * Successful Response
    */
-  200: RagEvalBackendEvalEvaluateResultsRouterEvaluationResult;
+  200: LlmEvalEvalEvaluateResultsRouterEvaluationResult;
 };
 
 export type EvaluationResultsGetResponse =
diff --git a/frontend/messages/de.json b/frontend/messages/de.json
index 4433843..9c09060 100644
--- a/frontend/messages/de.json
+++ b/frontend/messages/de.json
@@ -693,7 +693,8 @@
     "action": {
       "delete": "Löschen",
       "edit": "Bearbeiten",
-      "undo": "Rückgängig"
+      "undo": "Rückgängig",
+      "view": "Details"
     },
     "add": "Hinzufügen",
     "addContext": "Kontext hinzufügen",
diff --git a/frontend/messages/en.json b/frontend/messages/en.json
index fa379ce..210562c 100644
--- a/frontend/messages/en.json
+++ b/frontend/messages/en.json
@@ -692,7 +692,8 @@
     "action": {
       "delete": "Delete",
       "edit": "Edit",
-      "undo": "Undo"
+      "undo": "Undo",
+      "view": "Details"
     },
     "add": "Add",
     "addContext": "add context",