Update app/api/image_router.py

app/api/image_router.py

@@ -6,6 +6,7 @@ from app.schemas.image import ShoeGenerateRequest
 from io import BytesIO
 from app.services import image_service
 from app.services.image_service import generate_shoe_images
+from app.schemas.image import ShoeCheckResponse, UserInput, DressCheckResponse
 
 logger = logging.getLogger(__name__)
 
@@ -197,3 +198,85 @@ async def generate_shoe(request: ShoeGenerateRequest):
     except Exception as e:
         logger.exception("Error in /generate-shoe: %s", e)
         raise HTTPException(status_code=500, detail=str(e))
+
+from app.core.config import settings
+
+from groq import Groq
+import json
+
+client = Groq(api_key=settings.LANGCHAIN_API_KEY)
+
+# --- Endpoint ---
+@router.post("/check-shoe", response_model=ShoeCheckResponse)
+async def check_shoe(user_input: UserInput):
+    """
+    Check if the user input text is related to shoe images using Groq model.
+    Returns {"answer": "Yes"} or {"answer": "No"}.
+    """
+    try:
+        # Define the JSON schema for response
+        response_format = {
+            "type": "json_schema",
+            "json_schema": {
+                "name": "shoe_check",
+                "schema": ShoeCheckResponse.model_json_schema()
+            }
+        }
+
+        # System + user prompt
+        messages = [
+            {"role": "system", "content": "You are a strict classifier that determines if text is about shoe images."},
+            {"role": "user", "content": user_input.text}
+        ]
+
+        # Call Groq model
+        response = client.chat.completions.create(
+            model="moonshotai/kimi-k2-instruct-0905",
+            messages=messages,
+            response_format=response_format
+        )
+
+        # Parse model output
+        result = ShoeCheckResponse.model_validate(json.loads(response.choices[0].message.content))
+        return result
+
+    except Exception as e:
+        raise HTTPException(status_code=500, detail=str(e))
+
+
+# --- Dress Check Endpoint ---
+@router.post("/check-dress", response_model=DressCheckResponse)
+async def check_dress(user_input: UserInput):
+    """
+    Check if the user input text is related to dress images using Groq model.
+    Returns {"answer": "Yes"} or {"answer": "No"}.
+    """
+    try:
+        response_format = {
+            "type": "json_schema",
+            "json_schema": {
+                "name": "dress_check",
+                "schema": DressCheckResponse.model_json_schema()
+            }
+        }
+
+        # System + user prompt
+        messages = [
+            {"role": "system", "content": "You are a strict classifier that determines if text is about dress images."},
+            {"role": "user", "content": user_input.text}
+        ]
+
+        # Call Groq model
+        response = client.chat.completions.create(
+            model="moonshotai/kimi-k2-instruct-0905",
+            messages=messages,
+            response_format=response_format
+        )
+
+        # Parse model output
+        result = DressCheckResponse.model_validate(json.loads(response.choices[0].message.content))
+        return result
+
+    except Exception as e:
+        raise HTTPException(status_code=500, detail=str(e))
+