tweak config docs

Author: emrgnt-cmplxty

docs/api-reference/openapi.json

@@ -92,8 +92,7 @@ async def ingest_files_app(
                 description=ingest_files_descriptions.get("ingestion_config"),
             ),
             auth_user=Depends(self.service.providers.auth.auth_wrapper),
-            response_model=WrappedIngestionResponse,
-        ):
+        ) -> WrappedIngestionResponse:  # type: ignore
             """
             Ingest files into the system.
 
@@ -189,8 +188,7 @@ async def update_files_app(
                 description=ingest_files_descriptions.get("ingestion_config"),
             ),
             auth_user=Depends(self.service.providers.auth.auth_wrapper),
-            response_model=WrappedUpdateResponse,
-        ):
+        ) -> WrappedUpdateResponse:  # type: ignore
             """
             Update existing files in the system.
 
@@ -280,8 +278,7 @@ async def ingest_chunks_app(
                 None, description=ingest_files_descriptions.get("metadata")
             ),
             auth_user=Depends(self.service.providers.auth.auth_wrapper),
-            response_model=WrappedIngestionResponse,
-        ):
+        ) -> WrappedIngestionResponse:  # type: ignore
             """
             Ingest text chunks into the system.
 

py/core/main/api/ingestion_router.py

@@ -72,7 +72,7 @@ async def create_graph(
                 description="Settings for the graph creation process.",
             ),
             auth_user=Depends(self.service.providers.auth.auth_wrapper),
-        ) -> WrappedKGCreationResponse:
+        ) -> WrappedKGCreationResponse:  # type: ignore
             """
             Creating a graph on your documents. This endpoint takes input a list of document ids and KGCreationSettings. If document IDs are not provided, the graph will be created on all documents in the system.
             This step extracts the relevant entities and relationships from the documents and creates a graph based on the extracted information.

py/core/main/api/kg_router.py

@@ -112,7 +112,7 @@ async def search_app(
                 description=search_descriptions.get("kg_search_settings"),
             ),
             auth_user=Depends(self.service.providers.auth.auth_wrapper),
-        ) -> WrappedSearchResponse:
+        ) -> WrappedSearchResponse:  # type: ignore
             """
             Perform a search query on the vector database and knowledge graph.
 
@@ -168,7 +168,7 @@ async def rag_app(
                 description=rag_descriptions.get("include_title_if_available"),
             ),
             auth_user=Depends(self.service.providers.auth.auth_wrapper),
-        ) -> WrappedRAGResponse:
+        ) -> WrappedRAGResponse:  # type: ignore
             """
             Execute a RAG (Retrieval-Augmented Generation) query.
 
@@ -240,7 +240,7 @@ async def agent_app(
                 ),
             ),
             auth_user=Depends(self.service.providers.auth.auth_wrapper),
-        ) -> WrappedRAGAgentResponse:
+        ) -> WrappedRAGAgentResponse:  # type: ignore
             """
             Implement an agent-based interaction for complex query processing.
 

py/core/main/api/retrieval_router.py

@@ -4,7 +4,7 @@
 import math
 import uuid
 
-from hatchet_sdk import Context, ConcurrencyLimitStrategy
+from hatchet_sdk import ConcurrencyLimitStrategy, Context
 
 from core import GenerationConfig
 from core.base import OrchestrationProvider
@@ -41,8 +41,8 @@ class KGExtractDescribeEmbedWorkflow:
         def __init__(self, kg_service: KgService):
             self.kg_service = kg_service
 
-        @orchestration_provider.concurrency(
-            max_runs=orchestration_provider.config.kg_creation_concurrency_limit,
+        @orchestration_provider.concurrency(  # type: ignore
+            max_runs=orchestration_provider.config.kg_creation_concurrency_limit,  # type: ignore
             limit_strategy=ConcurrencyLimitStrategy.GROUP_ROUND_ROBIN,
         )
         def concurrency(self, context) -> str:

py/core/main/orchestration/hatchet/kg_workflow.py

@@ -60,6 +60,7 @@ def generate_random_vector_entry(
         generate_random_vector_entry(i, dimension) for i in range(num_entries)
     ]
 
+
 @pytest.fixture(scope="function")
 def app_config():
     collection_id = uuid.uuid4()
@@ -68,6 +69,7 @@ def app_config():
 
     return AppConfig(project_name=random_project_name)
 
+
 # Crypto
 @pytest.fixture(scope="function")
 def crypto_config(app_config):
@@ -82,9 +84,7 @@ def crypto_provider(crypto_config, app_config):
 # Postgres
 @pytest.fixture(scope="function")
 def db_config(app_config):
-    return DatabaseConfig.create(
-        provider="postgres",  app=app_config
-    )
+    return DatabaseConfig.create(provider="postgres", app=app_config)
 
 
 @pytest.fixture(scope="function")
@@ -138,7 +138,7 @@ def auth_config(app_config):
         access_token_lifetime_in_minutes=15,
         refresh_token_lifetime_in_days=1,
         require_email_verification=False,
-        app=app_config
+        app=app_config,
     )
 
 
@@ -160,7 +160,7 @@ def litellm_provider(app_config):
         provider="litellm",
         base_model="text-embedding-3-small",
         base_dimension=1536,
-        app=app_config
+        app=app_config,
     )
     return LiteLLMEmbeddingProvider(config)
 

py/tests/conftest.py

@@ -25,7 +25,7 @@ def openai_provider(app_config):
         provider="openai",
         base_model="text-embedding-ada-002",
         base_dimension=1536,
-        app=app_config
+        app=app_config,
     )
     return OpenAIEmbeddingProvider(config)
 
@@ -36,6 +36,6 @@ def ollama_provider(app_config):
         provider="ollama",
         base_model="mxbai-embed-large",
         base_dimension=1024,
-        app=app_config
+        app=app_config,
     )
     return OllamaEmbeddingProvider(config)

py/tests/core/providers/embedding/conftest.py

@@ -26,7 +26,7 @@ def litellm_provider(app_config):
         provider="litellm",
         base_model="openai/text-embedding-3-small",
         base_dimension=1536,
-        app=app_config
+        app=app_config,
     )
 
     return LiteLLMEmbeddingProvider(config)
@@ -80,7 +80,7 @@ def test_litellm_rerank_model_not_supported(app_config):
         base_model="openai/text-embedding-3-small",
         base_dimension=1536,
         rerank_model="some-model",
-        app=app_config
+        app=app_config,
     )
     with pytest.raises(
         ValueError, match="does not support separate reranking"
@@ -93,7 +93,7 @@ def test_litellm_unsupported_stage(app_config):
         provider="litellm",
         base_model="openai/text-embedding-3-small",
         base_dimension=1536,
-        app=app_config
+        app=app_config,
     )
     provider = LiteLLMEmbeddingProvider(config)
     with pytest.raises(
@@ -110,7 +110,7 @@ async def test_litellm_async_unsupported_stage(app_config):
         provider="litellm",
         base_model="openai/text-embedding-3-small",
         base_dimension=1536,
-        app=app_config
+        app=app_config,
     )
     provider = LiteLLMEmbeddingProvider(config)
     with pytest.raises(