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02bffa3 b38933f 02bffa3 b38933f b3d6596 b38933f b3d6596 b38933f 8229863 b38933f 90e05cc b38933f 8229863 b38933f 8229863 b38933f d062f91 b38933f 8229863 b38933f | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 | import gradio as gr
import os
import logging
# Enable logging
logging.basicConfig(level=logging.INFO)
# Get the token
hf_token = os.getenv("HF_TOKEN")
if not hf_token:
raise ValueError("❌ HF_TOKEN environment variable is not set")
# Define the private Space path
PRIVATE_SPACE = "entropy25/private"
def load_private_space():
"""Load private space via token"""
try:
private_fn = gr.load(f"spaces/{PRIVATE_SPACE}", hf_token=hf_token)
logging.info("✅ Successfully connected to private space")
return private_fn
except Exception as e:
logging.error(f"❌ Connection failed: {e}")
return None
# Load once during startup
private_analyzer = load_private_space()
def analyze_sentiment(text):
"""Call the private space for sentiment analysis"""
if not private_analyzer:
return "❌ Error: Failed to connect to private space"
if not text.strip():
return "⚠️ Please enter text to analyze"
try:
result = private_analyzer(text)
logging.info(f"✅ Analysis result: {result}")
return result
except Exception as e:
error_msg = f"❌ Analysis failed: {str(e)}"
logging.error(error_msg)
return error_msg
def create_interface():
"""Build the public-facing UI"""
with gr.Blocks(title="Sentiment Analyzer - Public", theme=gr.themes.Soft()) as demo:
gr.Markdown("# 🎭 Sentiment Analysis Tool")
gr.Markdown("Call a private Hugging Face space for sentiment analysis")
with gr.Row():
with gr.Column(scale=2):
text_input = gr.Textbox(
label="📝 Input Text",
placeholder="Type a sentence to analyze...",
lines=3,
max_lines=10
)
analyze_btn = gr.Button("🔍 Analyze Sentiment", variant="primary")
with gr.Column(scale=2):
result_output = gr.Textbox(
label="📊 Analysis Result",
lines=5,
max_lines=10
)
analyze_btn.click(
fn=analyze_sentiment,
inputs=text_input,
outputs=result_output
)
gr.Examples(
examples=[
["I'm feeling great today!"],
["That movie was a waste of time."],
["The weather is nice, perfect for a walk."],
["Service was okay, but the quality was mediocre."]
],
inputs=text_input
)
return demo
if __name__ == "__main__":
demo = create_interface()
demo.launch(
server_name="0.0.0.0",
server_port=7860,
share=False
)
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