Spaces:
Runtime error
Runtime error
major update
Browse files
app.py
CHANGED
@@ -1,30 +1,48 @@
|
|
1 |
import streamlit as st
|
2 |
from transformers import pipeline
|
3 |
|
4 |
-
pipe=pipeline('sentiment-analysis')
|
5 |
-
# Set the title
|
6 |
-
st.title("Sentiment Analysis")
|
7 |
|
8 |
-
#
|
9 |
-
|
|
|
|
|
|
|
|
|
10 |
# Input for text to analyze sentiment
|
11 |
text = st.text_area("Enter text for sentiment analysis:")
|
12 |
|
13 |
-
# Add a button
|
14 |
submit_button = st.form_submit_button("Analyze Sentiment")
|
15 |
|
16 |
# Check if the form was submitted
|
17 |
if text and submit_button:
|
|
|
18 |
out = pipe(text)
|
19 |
result = out[0] # Assuming you want the first result if multiple are returned
|
20 |
sentiment = result["label"]
|
21 |
score = round(result["score"], 2) # Round the score to two decimal places
|
22 |
-
st.write(f"Sentiment: {sentiment}")
|
23 |
-
st.write(f"Sentiment Score: {score}")
|
24 |
-
|
25 |
-
|
26 |
-
|
27 |
|
28 |
-
|
29 |
-
|
30 |
-
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
import streamlit as st
|
2 |
from transformers import pipeline
|
3 |
|
4 |
+
pipe = pipeline('sentiment-analysis')
|
|
|
|
|
5 |
|
6 |
+
# Set the title and add introductory text
|
7 |
+
st.title("Sentiment Analysis App")
|
8 |
+
st.write("This simple app analyzes the sentiment of your text.")
|
9 |
+
|
10 |
+
# Use 'form' to group input elements together
|
11 |
+
with st.form("sentiment_form"):
|
12 |
# Input for text to analyze sentiment
|
13 |
text = st.text_area("Enter text for sentiment analysis:")
|
14 |
|
15 |
+
# Add a button with a label
|
16 |
submit_button = st.form_submit_button("Analyze Sentiment")
|
17 |
|
18 |
# Check if the form was submitted
|
19 |
if text and submit_button:
|
20 |
+
# Analyze sentiment
|
21 |
out = pipe(text)
|
22 |
result = out[0] # Assuming you want the first result if multiple are returned
|
23 |
sentiment = result["label"]
|
24 |
score = round(result["score"], 2) # Round the score to two decimal places
|
|
|
|
|
|
|
|
|
|
|
25 |
|
26 |
+
# Display sentiment analysis results
|
27 |
+
st.header("Sentiment Analysis Result")
|
28 |
+
st.write(f"**Sentiment**: {sentiment}")
|
29 |
+
st.write(f"**Sentiment Score**: {score}")
|
30 |
+
|
31 |
+
# Add a section for instructions on how to use the app
|
32 |
+
st.header("How to Use")
|
33 |
+
st.write("1. Enter text in the text area above.")
|
34 |
+
st.write("2. Click the 'Analyze Sentiment' button to analyze the sentiment.")
|
35 |
+
st.write("3. The sentiment label and score will be displayed below.")
|
36 |
+
|
37 |
+
# Add a section with information about the sentiment analysis model
|
38 |
+
st.header("About the Model")
|
39 |
+
st.write("The sentiment analysis is performed using the Hugging Face Transformers library.")
|
40 |
+
st.write("The model used is 'nlptown/bert-base-multilingual-uncased-sentiment'.")
|
41 |
+
|
42 |
+
# Footer with a link to LinkedIn profile
|
43 |
+
st.header("Connect with Me on LinkedIn")
|
44 |
+
st.write("Feel free to connect with me on LinkedIn for any inquiries or collaborations.")
|
45 |
+
st.markdown("[LinkedIn Profile](https://www.linkedin.com/in/iam-manoj/)")
|
46 |
+
|
47 |
+
# Footer with additional information or links
|
48 |
+
st.footer("For more information, visit the [Hugging Face Transformers website](https://huggingface.co/transformers/).")
|