Update app.py
Browse files
app.py
CHANGED
|
@@ -10,10 +10,14 @@ MODELS = {
|
|
| 10 |
"ruRoberta": "sberbank-ai/ruRoberta-large"
|
| 11 |
}
|
| 12 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 13 |
def get_embeddings(model, tokenizer, text):
|
| 14 |
-
|
| 15 |
-
prompted_text = f"Товар: {text}. Категория:"
|
| 16 |
-
inputs = tokenizer(prompted_text,
|
| 17 |
padding=True,
|
| 18 |
truncation=True,
|
| 19 |
return_tensors="pt",
|
|
@@ -21,18 +25,22 @@ def get_embeddings(model, tokenizer, text):
|
|
| 21 |
outputs = model(**inputs)
|
| 22 |
return outputs.last_hidden_state[:, 0].detach().numpy()
|
| 23 |
|
| 24 |
-
def classify(model_name: str, item: str, categories: str) -> str:
|
| 25 |
tokenizer = AutoTokenizer.from_pretrained(MODELS[model_name])
|
| 26 |
model = AutoModel.from_pretrained(MODELS[model_name])
|
| 27 |
|
| 28 |
-
#
|
| 29 |
-
|
|
|
|
|
|
|
|
|
|
| 30 |
|
| 31 |
-
# Эмбеддинги
|
| 32 |
-
|
| 33 |
-
|
| 34 |
-
|
| 35 |
-
|
|
|
|
| 36 |
|
| 37 |
# Сравнение
|
| 38 |
similarities = cosine_similarity(item_embedding, np.vstack(category_embeddings))[0]
|
|
@@ -43,9 +51,10 @@ def classify(model_name: str, item: str, categories: str) -> str:
|
|
| 43 |
gr.Interface(
|
| 44 |
fn=classify,
|
| 45 |
inputs=[
|
| 46 |
-
gr.Dropdown(list(MODELS.keys())),
|
| 47 |
-
gr.
|
| 48 |
-
gr.Textbox(
|
|
|
|
| 49 |
],
|
| 50 |
outputs=gr.Textbox()
|
| 51 |
).launch()
|
|
|
|
| 10 |
"ruRoberta": "sberbank-ai/ruRoberta-large"
|
| 11 |
}
|
| 12 |
|
| 13 |
+
PROMPT_TEMPLATES = {
|
| 14 |
+
"basic": "Товар: {item}. Категория:",
|
| 15 |
+
"examples": "Примеры:\n- Молоток → Инструменты\n- Морковь → Овощи\nТовар: {item} → ",
|
| 16 |
+
"strict": "Выбери категорию из [{categories}]. Товар: {item}. Категория:"
|
| 17 |
+
}
|
| 18 |
+
|
| 19 |
def get_embeddings(model, tokenizer, text):
|
| 20 |
+
inputs = tokenizer(text,
|
|
|
|
|
|
|
| 21 |
padding=True,
|
| 22 |
truncation=True,
|
| 23 |
return_tensors="pt",
|
|
|
|
| 25 |
outputs = model(**inputs)
|
| 26 |
return outputs.last_hidden_state[:, 0].detach().numpy()
|
| 27 |
|
| 28 |
+
def classify(model_name: str, prompt_type: str, item: str, categories: str) -> str:
|
| 29 |
tokenizer = AutoTokenizer.from_pretrained(MODELS[model_name])
|
| 30 |
model = AutoModel.from_pretrained(MODELS[model_name])
|
| 31 |
|
| 32 |
+
# Формируем промпт
|
| 33 |
+
prompt = PROMPT_TEMPLATES[prompt_type].format(
|
| 34 |
+
item=item,
|
| 35 |
+
categories=", ".join([c.strip() for c in categories.split(",")])
|
| 36 |
+
)
|
| 37 |
|
| 38 |
+
# Эмбеддинги
|
| 39 |
+
item_embedding = get_embeddings(model, tokenizer, prompt)
|
| 40 |
+
category_embeddings = [
|
| 41 |
+
get_embeddings(model, tokenizer, c.strip())
|
| 42 |
+
for c in categories.split(",")
|
| 43 |
+
]
|
| 44 |
|
| 45 |
# Сравнение
|
| 46 |
similarities = cosine_similarity(item_embedding, np.vstack(category_embeddings))[0]
|
|
|
|
| 51 |
gr.Interface(
|
| 52 |
fn=classify,
|
| 53 |
inputs=[
|
| 54 |
+
gr.Dropdown(list(MODELS.keys()), label="Модель"),
|
| 55 |
+
gr.Dropdown(list(PROMPT_TEMPLATES.keys()), label="Шаблон промпта"),
|
| 56 |
+
gr.Textbox(label="Товар"),
|
| 57 |
+
gr.Textbox(label="Категории", value="Инструменты, Овощи, Техника")
|
| 58 |
],
|
| 59 |
outputs=gr.Textbox()
|
| 60 |
).launch()
|