adding garment description feature using openai

app.py

@@ -5,9 +5,11 @@ from io import BytesIO
 import fal_client
 import os
 import base_generator
-
+import openai
+import base64
 
 app = FastAPI()
+openai.api_key = os.getenv("OPENAI_API_KEY")
 
 @app.get("/")
 def greet_json():
@@ -160,3 +162,32 @@ def videoStatus(request_id: str):
 async def videoResult(request_id: str):
     result = await fal_client.result_async("fal-ai/kling-video/v1.6/pro/image-to-video", request_id)
     return(result)
+
+
+
+#Auxiliary functions
+
+@app.post("/describeGarment")
+async def describe_garment(image: UploadFile = File(...)):
+    image_bytes = await image.read()
+    base64_image = base64.b64encode(image_bytes).decode("utf-8")
+
+    response = openai.ChatCompletion.create(
+        model="gpt-4o",  # See discussion below
+        messages=[
+            {
+                "role": "user",
+                "content": [
+                    {"type": "text", "text": "Describe this garment or garments to be inserted into the sentence: a man wearing ..... in front of a white background. be detailed but online describe the garmensts, not the rest of the images"},
+                    {
+                        "type": "image_url",
+                        "image_url": {"url": f"data:image/jpeg;base64,{base64_image}"}
+                    }
+                ]
+            }
+        ],
+        max_tokens=300
+    )
+
+    description = response["choices"][0]["message"]["content"]
+    return {"description": description}

base_generator.py

@@ -7,6 +7,16 @@ import requests
 # a way to support loras directly
 # A way to get a description of the outfit
 
+def import_lora(lora_name):
+    print("we are importing a lora")
+    return("Tetsok")
+
+def return_pose(pose_id: int):
+    print("we are returning a pose")
+    return("Tetsok")
+
+
+
 
 def run_workflow(body):
     print("run workflow")

requirements.txt

@@ -3,4 +3,6 @@ uvicorn[standard]
 httpx
 python-multipart
 fal-client
-requests
+requests
+openai
+base64