Spaces:
Sleeping
Sleeping
Update app.py
Browse files
app.py
CHANGED
|
@@ -2,70 +2,63 @@ import streamlit as st
|
|
| 2 |
import pandas as pd
|
| 3 |
import joblib
|
| 4 |
import io
|
|
|
|
| 5 |
|
| 6 |
-
# Load mô hình CRF đã train
|
| 7 |
@st.cache_resource
|
| 8 |
def load_model():
|
| 9 |
return joblib.load("chunking_crf_model.pkl")
|
| 10 |
|
| 11 |
crf = load_model()
|
| 12 |
|
| 13 |
-
# Hàm trích xuất feature
|
| 14 |
def extract_features(sentence):
|
| 15 |
return [{"word": token, "pos": pos} for token, pos in zip(sentence["Token"], sentence["POS"])]
|
| 16 |
|
| 17 |
st.title("📝 Preprocessing tool")
|
| 18 |
|
| 19 |
-
# Upload file
|
| 20 |
uploaded_file = st.file_uploader("📤 Tải lên file CSV hoặc Excel chứa dữ liệu cần gán nhãn", type=["csv", "xlsx"])
|
| 21 |
|
| 22 |
if uploaded_file:
|
| 23 |
-
# Kiểm tra định dạng file
|
| 24 |
file_type = uploaded_file.name.split(".")[-1]
|
| 25 |
|
| 26 |
try:
|
| 27 |
if file_type == "csv":
|
| 28 |
df_test = pd.read_csv(uploaded_file)
|
| 29 |
-
else:
|
| 30 |
-
df_test = pd.read_excel(uploaded_file, engine="openpyxl")
|
| 31 |
|
| 32 |
-
# Kiểm tra nếu thiếu cột cần thiết
|
| 33 |
required_columns = {"Sentence_ID", "Token", "POS"}
|
| 34 |
if not required_columns.issubset(df_test.columns):
|
| 35 |
st.error(f"⚠️ File phải chứa các cột: {', '.join(required_columns)}")
|
| 36 |
else:
|
| 37 |
-
# Xóa cột Chunk nếu tồn tại
|
| 38 |
if "Chunk" in df_test.columns:
|
| 39 |
df_test = df_test.drop(columns=["Chunk"])
|
| 40 |
|
| 41 |
-
# Nhóm theo câu
|
| 42 |
sentences = [group.copy() for _, group in df_test.groupby("Sentence_ID")]
|
| 43 |
|
| 44 |
-
# Gán nhãn chunking
|
| 45 |
all_sentences = []
|
| 46 |
for sentence in sentences:
|
| 47 |
X_test = [extract_features(sentence)]
|
| 48 |
y_pred = crf.predict(X_test)[0]
|
| 49 |
-
sentence.loc[:, "Chunk"] = y_pred
|
| 50 |
all_sentences.append(sentence)
|
| 51 |
|
| 52 |
-
# Ghép lại thành dataframe
|
| 53 |
df_chunked = pd.concat(all_sentences)
|
| 54 |
|
| 55 |
-
# Tạo file CSV để tải xuống
|
| 56 |
csv_buffer = io.StringIO()
|
| 57 |
df_chunked.to_csv(csv_buffer, index=False, encoding="utf-8")
|
| 58 |
csv_data = csv_buffer.getvalue()
|
| 59 |
|
| 60 |
-
# Tạo file Excel để tải xuống
|
| 61 |
excel_buffer = io.BytesIO()
|
| 62 |
with pd.ExcelWriter(excel_buffer, engine="openpyxl") as writer:
|
| 63 |
df_chunked.to_excel(writer, index=False, sheet_name="Chunked Data")
|
| 64 |
excel_data = excel_buffer.getvalue()
|
| 65 |
|
| 66 |
-
|
| 67 |
-
|
| 68 |
-
|
|
|
|
|
|
|
|
|
|
| 69 |
|
| 70 |
except Exception as e:
|
| 71 |
st.error(f"❌ Lỗi khi xử lý file: {e}")
|
|
|
|
| 2 |
import pandas as pd
|
| 3 |
import joblib
|
| 4 |
import io
|
| 5 |
+
import os
|
| 6 |
|
|
|
|
| 7 |
@st.cache_resource
|
| 8 |
def load_model():
|
| 9 |
return joblib.load("chunking_crf_model.pkl")
|
| 10 |
|
| 11 |
crf = load_model()
|
| 12 |
|
|
|
|
| 13 |
def extract_features(sentence):
|
| 14 |
return [{"word": token, "pos": pos} for token, pos in zip(sentence["Token"], sentence["POS"])]
|
| 15 |
|
| 16 |
st.title("📝 Preprocessing tool")
|
| 17 |
|
|
|
|
| 18 |
uploaded_file = st.file_uploader("📤 Tải lên file CSV hoặc Excel chứa dữ liệu cần gán nhãn", type=["csv", "xlsx"])
|
| 19 |
|
| 20 |
if uploaded_file:
|
|
|
|
| 21 |
file_type = uploaded_file.name.split(".")[-1]
|
| 22 |
|
| 23 |
try:
|
| 24 |
if file_type == "csv":
|
| 25 |
df_test = pd.read_csv(uploaded_file)
|
| 26 |
+
else:
|
| 27 |
+
df_test = pd.read_excel(uploaded_file, engine="openpyxl")
|
| 28 |
|
|
|
|
| 29 |
required_columns = {"Sentence_ID", "Token", "POS"}
|
| 30 |
if not required_columns.issubset(df_test.columns):
|
| 31 |
st.error(f"⚠️ File phải chứa các cột: {', '.join(required_columns)}")
|
| 32 |
else:
|
|
|
|
| 33 |
if "Chunk" in df_test.columns:
|
| 34 |
df_test = df_test.drop(columns=["Chunk"])
|
| 35 |
|
|
|
|
| 36 |
sentences = [group.copy() for _, group in df_test.groupby("Sentence_ID")]
|
| 37 |
|
|
|
|
| 38 |
all_sentences = []
|
| 39 |
for sentence in sentences:
|
| 40 |
X_test = [extract_features(sentence)]
|
| 41 |
y_pred = crf.predict(X_test)[0]
|
| 42 |
+
sentence.loc[:, "Chunk"] = y_pred
|
| 43 |
all_sentences.append(sentence)
|
| 44 |
|
|
|
|
| 45 |
df_chunked = pd.concat(all_sentences)
|
| 46 |
|
|
|
|
| 47 |
csv_buffer = io.StringIO()
|
| 48 |
df_chunked.to_csv(csv_buffer, index=False, encoding="utf-8")
|
| 49 |
csv_data = csv_buffer.getvalue()
|
| 50 |
|
|
|
|
| 51 |
excel_buffer = io.BytesIO()
|
| 52 |
with pd.ExcelWriter(excel_buffer, engine="openpyxl") as writer:
|
| 53 |
df_chunked.to_excel(writer, index=False, sheet_name="Chunked Data")
|
| 54 |
excel_data = excel_buffer.getvalue()
|
| 55 |
|
| 56 |
+
file_base_name = os.path.splitext(uploaded_file.name)[0]
|
| 57 |
+
csv_filename = f"{file_base_name}_chunked.csv"
|
| 58 |
+
excel_filename = f"{file_base_name}_chunked.xlsx"
|
| 59 |
+
|
| 60 |
+
st.download_button("📥 Tải xuống dữ liệu đã gán nhãn (CSV)", csv_data, csv_filename, "text/csv")
|
| 61 |
+
st.download_button("📥 Tải xuống dữ liệu đã gán nhãn (Excel)", excel_data, excel_filename, "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet")
|
| 62 |
|
| 63 |
except Exception as e:
|
| 64 |
st.error(f"❌ Lỗi khi xử lý file: {e}")
|