start api

app.py

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+import gradio as gr
+from transformers import pipeline
+
+# pipeline as high level
+pipe = pipeline("text-generation", model="HuggingFaceTB/SmolLM2-360M-Instruct", device="cpu")
+
+# 3 adjectives + don't repeat + don't elaborate
+system_instruction = """
+You are given a short description of a person. 
+Respond only with three different adjectives that best describe the person, based on the description. 
+No explanation.
+"""
+
+def get_vibe(caption):
+    messages = [
+        {"role": "system", "content": system_instruction},
+        {"role": "user", "content": caption}
+    ]
+    output = pipe(messages, max_new_tokens=32, do_sample=True, temperature=0.8, top_p=0.9)[0]["generated_text"]
+
+    # extract assistant reply
+    assistant_text = next(
+        (entry['content'] for entry in output if entry['role'] == 'assistant'),
+        ""
+    )
+
+    # normalize to "word, word, word"
+    cleaned = assistant_text.replace(", and", ",").replace(" and", ",")
+    adjectives = [word.strip() for word in cleaned.split(",") if word.strip()]
+    return ", ".join(adjectives[:3])
+
+# api w/ gradio
+api = gr.Interface(
+    fn=get_vibe,
+    inputs=gr.Textbox(label="Input Caption"),
+    outputs="text"
+)
+
+api.launch(show_api=True)

requirements.txt

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+transformers
+torch
+gradio