Deploy backend from GitHub Actions

🚀 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <[email protected]>

README.md

@@ -137,7 +137,7 @@ Environment variables:
 ```env
 # OpenAI
 OPENAI_API_KEY=your_api_key_here
-OPENAI_MODEL=gpt-5-nano
+OPENAI_MODEL=gpt-4.1-nano
 OPENAI_EMBEDDING_MODEL=text-embedding-3-small
 
 # Qdrant

chatkit_server.py

@@ -32,7 +32,7 @@ class Settings(BaseSettings):
     openai_api_key: str
     qdrant_url: str
     qdrant_api_key: str
-    openai_model: str = "gpt-5-nano"
+    openai_model: str = "gpt-4o-mini"
     openai_embedding_model: str = "text-embedding-3-small"
 
     class Config:

main.py

@@ -58,7 +58,7 @@ class Settings(BaseSettings):
 
     # OpenAI Configuration
     openai_api_key: str = os.getenv("OPENAI_API_KEY", "")
-    openai_model: str = os.getenv("OPENAI_MODEL", "gpt-5-nano")
+    openai_model: str = os.getenv("OPENAI_MODEL", "gpt-4o-mini")
     openai_embedding_model: str = os.getenv("OPENAI_EMBEDDING_MODEL", "text-embedding-3-small")
 
     # Qdrant Configuration

rag/chat.py

@@ -33,7 +33,7 @@ class ChatHandler:
         self,
         qdrant_manager: QdrantManager,
         openai_api_key: str,
-        model: str = "gpt-5-nano",
+        model: str = "gpt-4.1-nano",
         embedding_model: str = "text-embedding-3-small",
         max_context_messages: int = 3,
         context_window_size: int = 4000,

rag/generation.py

@@ -23,7 +23,7 @@ class ResponseGenerator:
     def __init__(
         self,
         openai_api_key: str,
-        model: str = "gpt-5-nano",
+        model: str = "gpt-4.1-nano",
         max_tokens: int = 1000,
         temperature: float = 0.7
     ):

test_chat.py

@@ -46,7 +46,7 @@ async def test_chat():
         chat_handler = ChatHandler(
             qdrant_manager=qdrant_manager,
             openai_api_key=os.getenv("OPENAI_API_KEY"),
-            model=os.getenv("OPENAI_MODEL", "gpt-5-nano"),
+            model=os.getenv("OPENAI_MODEL", "gpt-4.1-nano"),
             embedding_model=os.getenv("OPENAI_EMBEDDING_MODEL", "text-embedding-3-small")
         )