simple version test interface
Browse files- app.py +63 -2
- requirements.txt +2 -0
app.py
CHANGED
|
@@ -1,4 +1,65 @@
|
|
|
|
|
|
|
|
| 1 |
import streamlit as st
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 2 |
|
| 3 |
-
|
| 4 |
-
st.
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
# app.py
|
| 2 |
+
|
| 3 |
import streamlit as st
|
| 4 |
+
from transformers import pipeline
|
| 5 |
+
import pandas as pd
|
| 6 |
+
|
| 7 |
+
|
| 8 |
+
@st.cache(allow_output_mutation=True)
|
| 9 |
+
def load_model():
|
| 10 |
+
return pipeline(model="seara/rubert-tiny2-ru-go-emotions")
|
| 11 |
+
|
| 12 |
+
model = load_model()
|
| 13 |
+
|
| 14 |
+
emotion_labels = {
|
| 15 |
+
"admiration": ("восхищение", "🌟"),
|
| 16 |
+
"amusement": ("веселье", "😄"),
|
| 17 |
+
"anger": ("злость", "😡"),
|
| 18 |
+
"annoyance": ("раздражение", "😠"),
|
| 19 |
+
"approval": ("одобрение", "👍"),
|
| 20 |
+
"caring": ("забота", "🤗"),
|
| 21 |
+
"confusion": ("непонимание", "😕"),
|
| 22 |
+
"curiosity": ("любопытство", "🧐"),
|
| 23 |
+
"desire": ("желание", "🔥"),
|
| 24 |
+
"disappointment": ("разочарование", "😞"),
|
| 25 |
+
"disapproval": ("неодобрение", "👎"),
|
| 26 |
+
"disgust": ("отвращение", "🤢"),
|
| 27 |
+
"embarrassment": ("смущение", "😳"),
|
| 28 |
+
"excitement": ("возбуждение", "🤩"),
|
| 29 |
+
"fear": ("страх", "😱"),
|
| 30 |
+
"gratitude": ("признательность", "🙏"),
|
| 31 |
+
"grief": ("горе", "😭"),
|
| 32 |
+
"joy": ("радость", "😊"),
|
| 33 |
+
"love": ("любовь", "❤️"),
|
| 34 |
+
"nervousness": ("нервозность", "😬"),
|
| 35 |
+
"optimism": ("оптимизм", "🌈"),
|
| 36 |
+
"pride": ("гордость", "🏅"),
|
| 37 |
+
"realization": ("осознание", "💡"),
|
| 38 |
+
"relief": ("облегчение", "😌"),
|
| 39 |
+
"remorse": ("раскаяние", "😔"),
|
| 40 |
+
"sadness": ("грусть", "😢"),
|
| 41 |
+
"surprise": ("удивление", "😲"),
|
| 42 |
+
"neutral": ("нейтральность", "😐")
|
| 43 |
+
}
|
| 44 |
+
|
| 45 |
+
st.title("🎭 Эмоциональный анализ текста")
|
| 46 |
+
st.write("Введите текст на русском, и мы покажем, какие эмоции в нём распознаны.")
|
| 47 |
+
|
| 48 |
+
text_input = st.text_area("Введите текст здесь:")
|
| 49 |
+
|
| 50 |
+
if text_input:
|
| 51 |
+
results = model(text_input)
|
| 52 |
+
|
| 53 |
+
threshold = 0.1
|
| 54 |
+
filtered = [r for r in results if r["score"] >= threshold]
|
| 55 |
+
filtered.sort(key=lambda x: x["score"], reverse=True)
|
| 56 |
|
| 57 |
+
if filtered:
|
| 58 |
+
st.subheader("Распознанные эмоции:")
|
| 59 |
+
for item in filtered:
|
| 60 |
+
label = item["label"]
|
| 61 |
+
score = item["score"]
|
| 62 |
+
ru_label, emoji = emotion_labels.get(label, (label, "❓"))
|
| 63 |
+
st.markdown(f"**{ru_label.capitalize()}** {emoji} — {score:.2%}")
|
| 64 |
+
else:
|
| 65 |
+
st.info("Эмоции не распознаны с достаточной уверенностью.")
|
requirements.txt
CHANGED
|
@@ -0,0 +1,2 @@
|
|
|
|
|
|
|
|
|
|
| 1 |
+
transformers
|
| 2 |
+
torch
|