huemin fix

logos/creation_interfaces/kojii_huemin.py

@@ -174,9 +174,11 @@ def generate_prompt(selected_climate, selected_landform, selected_body_of_water)
     selected_structure = (
         random.choice(list(Structure)).value if random.random() < 0.20 else ""
     )
-    selected_season = random.choice(list(Season)).value if random() < 0.95 else ""
+    selected_season = (
+        random.choice(list(Season)).value if random.random() < 0.95 else ""
+    )
     # selected_time_of_day = random.choice(list(TimeOfDay)).value
-    selected_colors = random.choice(list(Color)).value if random() < 0.95 else ""
+    selected_colors = random.choice(list(Color)).value if random.random() < 0.95 else ""
 
     selected_keywords = [
         selected_climate.value,
@@ -212,21 +214,3 @@ def kojii_huemin(request: KojiiHueminRequest, callback=None):
     image_url, thumbnail_url = replicate.sdxl(config)
 
     return image_url, thumbnail_url
-
-
-def kojii_huemin(request: KojiiHueminRequest, callback=None):
-    print("HUMIN REQUEST")
-    print(request)
-    prompt = generate_prompt(request.climate, request.landform, request.body_of_water)
-    seed = request.seed if request.seed else random.randint(0, 1000000)
-    print(prompt)
-
-    config = {
-        "mode": "kojii/huemin",
-        "text_input": prompt,
-        "seed": seed,
-    }
-
-    image_url, thumbnail_url = replicate.sdxl(config)
-
-    return image_url, thumbnail_url

test.py

@@ -0,0 +1,25 @@
+from logos.llm import LLM
+from pydantic import BaseModel
+
+
+class OutputSchema(BaseModel):
+    """
+    Output schema for LLM
+    """
+
+    description: str
+    numimages: int
+
+
+llm = LLM(model="gpt-4-1106-preview", system_message="You are an AI assistant")
+
+prompt = "Describe this image. In description, tell me what the image is about. In numimages, tell me how many images are attached."
+
+result = llm(
+    prompt,
+    image="https://edenartlab-prod-data.s3.us-east-1.amazonaws.com/27d5f97d76bb6550cec0f82296587bbc1ac1d66d34cfa824f3056046abe8c0e1.jpg",
+    output_schema=OutputSchema,
+    params={"max_tokens": 1000},
+)
+
+print(result)