diff --git a/backend/danswer/configs/model_configs.py b/backend/danswer/configs/model_configs.py
index a0b635566..b8e29f1d9 100644
--- a/backend/danswer/configs/model_configs.py
+++ b/backend/danswer/configs/model_configs.py
@@ -21,5 +21,5 @@ BATCH_SIZE_ENCODE_CHUNKS = 8
 # QA Model API Configs
 # https://platform.openai.com/docs/models/model-endpoint-compatibility
 INTERNAL_MODEL_VERSION = os.environ.get("INTERNAL_MODEL", "openai-chat-completion")
-OPENAPI_MODEL_VERSION = os.environ.get("OPENAI_MODEL_VERSION", "gpt-4")
+OPENAI_MODEL_VERSION = os.environ.get("OPENAI_MODEL_VERSION", "gpt-4")
 OPENAI_MAX_OUTPUT_TOKENS = 512
diff --git a/backend/danswer/datastores/qdrant/indexing.py b/backend/danswer/datastores/qdrant/indexing.py
index 67299acaa..02e61ab72 100644
--- a/backend/danswer/datastores/qdrant/indexing.py
+++ b/backend/danswer/datastores/qdrant/indexing.py
@@ -18,6 +18,7 @@ from qdrant_client import QdrantClient
 from qdrant_client.http.exceptions import ResponseHandlingException
 from qdrant_client.http.models.models import UpdateResult
 from qdrant_client.http.models.models import UpdateStatus
+from qdrant_client.models import CollectionsResponse
 from qdrant_client.models import Distance
 from qdrant_client.models import PointStruct
 from qdrant_client.models import VectorParams
@@ -27,6 +28,10 @@ logger = setup_logger()
 DEFAULT_BATCH_SIZE = 30
 
 
+def list_collections() -> CollectionsResponse:
+    return get_qdrant_client().get_collections()
+
+
 def create_collection(
     collection_name: str, embedding_dim: int = DOC_EMBEDDING_DIM
 ) -> None:
diff --git a/backend/danswer/direct_qa/question_answer.py b/backend/danswer/direct_qa/question_answer.py
index 1fcdf4d1b..f232f9e4d 100644
--- a/backend/danswer/direct_qa/question_answer.py
+++ b/backend/danswer/direct_qa/question_answer.py
@@ -21,7 +21,7 @@ from danswer.configs.constants import SEMANTIC_IDENTIFIER
 from danswer.configs.constants import SOURCE_LINK
 from danswer.configs.constants import SOURCE_TYPE
 from danswer.configs.model_configs import OPENAI_MAX_OUTPUT_TOKENS
-from danswer.configs.model_configs import OPENAPI_MODEL_VERSION
+from danswer.configs.model_configs import OPENAI_MODEL_VERSION
 from danswer.direct_qa.interfaces import QAModel
 from danswer.direct_qa.qa_prompts import ANSWER_PAT
 from danswer.direct_qa.qa_prompts import get_chat_reflexion_msg
@@ -185,7 +185,7 @@ class OpenAICompletionQA(QAModel):
     def __init__(
         self,
         prompt_processor: Callable[[str, list[str]], str] = json_processor,
-        model_version: str = OPENAPI_MODEL_VERSION,
+        model_version: str = OPENAI_MODEL_VERSION,
         max_output_tokens: int = OPENAI_MAX_OUTPUT_TOKENS,
     ) -> None:
         self.prompt_processor = prompt_processor
@@ -282,7 +282,7 @@ class OpenAIChatCompletionQA(QAModel):
         prompt_processor: Callable[
             [str, list[str]], list[dict[str, str]]
         ] = json_chat_processor,
-        model_version: str = OPENAPI_MODEL_VERSION,
+        model_version: str = OPENAI_MODEL_VERSION,
         max_output_tokens: int = OPENAI_MAX_OUTPUT_TOKENS,
         reflexion_try_count: int = 0,
     ) -> None:
diff --git a/backend/danswer/main.py b/backend/danswer/main.py
index 714a6a932..3d4694327 100644
--- a/backend/danswer/main.py
+++ b/backend/danswer/main.py
@@ -10,6 +10,7 @@ from danswer.configs.app_configs import APP_PORT
 from danswer.configs.app_configs import ENABLE_OAUTH
 from danswer.configs.app_configs import SECRET
 from danswer.configs.app_configs import WEB_DOMAIN
+from danswer.datastores.qdrant.indexing import list_collections
 from danswer.server.admin import router as admin_router
 from danswer.server.event_loading import router as event_processing_router
 from danswer.server.search_backend import router as backend_router
@@ -100,8 +101,11 @@ def get_application() -> FastAPI:
         from danswer.datastores.qdrant.indexing import create_collection
         from danswer.configs.app_configs import QDRANT_DEFAULT_COLLECTION
 
-        create_collection(collection_name=QDRANT_DEFAULT_COLLECTION)
-        logger.info("Collection ready")
+        if QDRANT_DEFAULT_COLLECTION not in {
+            collection.name for collection in list_collections().collections
+        }:
+            logger.info(f"Creating collection with name: {QDRANT_DEFAULT_COLLECTION}")
+            create_collection(collection_name=QDRANT_DEFAULT_COLLECTION)
 
         warm_up_models()
         logger.info("Semantic Search models are ready.")
diff --git a/deployment/env.dev.template b/deployment/env.dev.template
index f322a3de9..7387cbd76 100644
--- a/deployment/env.dev.template
+++ b/deployment/env.dev.template
@@ -9,7 +9,7 @@ OPENAI_API_KEY=
 INTERNAL_MODEL_VERSION=openai-chat-completion
 
 # Use a valid model for the choice above, consult https://platform.openai.com/docs/models/model-endpoint-compatibility
-OPENAPI_MODEL_VERSION=gpt-3.5-turbo
+OPENAI_MODEL_VERSION=gpt-3.5-turbo
 
 
 # Can leave these as defaults
diff --git a/deployment/env.prod.template b/deployment/env.prod.template
index 1d35825e0..46df0363c 100644
--- a/deployment/env.prod.template
+++ b/deployment/env.prod.template
@@ -8,7 +8,7 @@ OPENAI_API_KEY=
 # Choose between "openai-chat-completion" and "openai-completion"
 INTERNAL_MODEL_VERSION=openai-chat-completion
 # Use a valid model for the choice above, consult https://platform.openai.com/docs/models/model-endpoint-compatibility
-OPENAPI_MODEL_VERSION=gpt-4
+OPENAI_MODEL_VERSION=gpt-4
 
 # Could be something like danswer.companyname.com. Requires additional setup if not localhost
 WEB_DOMAIN=http://localhost:3000