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Vish AI - Simple Test Server (for local dev container testing)
This is a lightweight version for testing in Python 3.14
The full AI version will run on Hugging Face Spaces (Python 3.10/3.11)
"""
import gradio as gr
import os
from dotenv import load_dotenv
# Load environment variables
load_dotenv()
SUPABASE_URL = os.getenv("NEXT_PUBLIC_SUPABASE_URL", "https://lyebtceryednzafhyunq.supabase.co")
def simple_chat(message: str, history: list) -> str:
"""Simple echo chatbot for testing"""
return f"✅ Vish AI is running!\n\nYou said: {message}\n\n💡 Note: This is a test version. AI models require PyTorch which isn't available in Python 3.14.\n\n🚀 For the full AI experience, deploy to Hugging Face Spaces (Python 3.10/3.11) using the instructions in DEPLOYMENT.md"
def simple_summarize(text: str) -> str:
"""Simple summarizer for testing"""
word_count = len(text.split())
return f"✅ Text received: {word_count} words\n\nFirst 100 chars: {text[:100]}...\n\n🚀 Full summarization available on Hugging Face Spaces"
def simple_sentiment(text: str) -> str:
"""Simple sentiment for testing"""
positive_words = ['good', 'great', 'excellent', 'happy', 'love', 'wonderful', 'amazing']
negative_words = ['bad', 'terrible', 'awful', 'hate', 'sad', 'horrible', 'worst']
text_lower = text.lower()
pos_count = sum(1 for word in positive_words if word in text_lower)
neg_count = sum(1 for word in negative_words if word in text_lower)
if pos_count > neg_count:
return "😊 **POSITIVE** (Simple keyword detection)\n\n🚀 Full sentiment analysis available on Hugging Face Spaces"
elif neg_count > pos_count:
return "😞 **NEGATIVE** (Simple keyword detection)\n\n🚀 Full sentiment analysis available on Hugging Face Spaces"
else:
return "😐 **NEUTRAL** (Simple keyword detection)\n\n🚀 Full sentiment analysis available on Hugging Face Spaces"
# Create Gradio Interface
with gr.Blocks(theme=gr.themes.Soft(), title="Vish AI - Test Server") as demo:
gr.Markdown("""
# 🌟 Vish AI - Test Server
### Local Development Environment
⚠️ **This is a simplified test version for Python 3.14 dev container.**
The full AI-powered version with DistilGPT2, DistilBART, and DistilBERT will run on **Hugging Face Spaces**.
📖 See `DEPLOYMENT.md` for deployment instructions.
""")
gr.Markdown(f"""
### 🔗 Connected to Supabase
- **URL**: {SUPABASE_URL}
- **Status**: ✅ Environment loaded
""")
with gr.Tabs():
# Chat Tab
with gr.Tab("💬 Chat Test"):
chatbot = gr.Chatbot(height=400, label="Test Chat")
msg = gr.Textbox(
label="Your Message",
placeholder="Type something to test...",
lines=2
)
with gr.Row():
submit = gr.Button("Send", variant="primary")
clear = gr.Button("Clear")
msg.submit(simple_chat, [msg, chatbot], chatbot)
submit.click(simple_chat, [msg, chatbot], chatbot)
clear.click(lambda: None, None, chatbot, queue=False)
# Summarization Tab
with gr.Tab("📝 Summarization Test"):
with gr.Row():
with gr.Column():
input_text = gr.Textbox(
label="Enter Text",
placeholder="Paste your text here...",
lines=10
)
summarize_btn = gr.Button("Test Summarize", variant="primary")
with gr.Column():
summary_output = gr.Textbox(
label="Summary Result",
lines=10
)
summarize_btn.click(simple_summarize, input_text, summary_output)
# Sentiment Analysis Tab
with gr.Tab("😊 Sentiment Test"):
with gr.Row():
with gr.Column():
sentiment_input = gr.Textbox(
label="Enter Text",
placeholder="How do you feel?",
lines=5
)
analyze_btn = gr.Button("Test Sentiment", variant="primary")
with gr.Column():
sentiment_output = gr.Textbox(
label="Sentiment Result",
lines=5
)
analyze_btn.click(simple_sentiment, sentiment_input, sentiment_output)
# Info Tab
with gr.Tab("ℹ️ Info"):
gr.Markdown("""
## 🛠️ Development Environment
**Current Setup:**
- Python 3.14.0 (dev container)
- Gradio ✅ Installed
- Supabase ✅ Configured
- PyTorch ❌ Not available (Python 3.14)
**For Full AI Features:**
1. Deploy to Hugging Face Spaces
2. Hugging Face uses Python 3.10/3.11
3. PyTorch and AI models will work there
**Files Ready for Deployment:**
- ✅ `app.py` - Full AI application
- ✅ `requirements.txt` - Dependencies
- ✅ `.env` - Configuration
- ✅ `DEPLOYMENT.md` - Instructions
- ✅ `supabase_setup.sql` - Database schema
## 🚀 Next Steps
1. Test this interface
2. Follow `DEPLOYMENT.md` to deploy to HF Spaces
3. Add secrets in HF Space settings
4. Run `supabase_setup.sql` in Supabase
5. Enjoy full AI features!
---
**VIJ Project** | Powered by Supabase & Hugging Face
""")
gr.Markdown("""
---
🔗 **Quick Links:**
- [Hugging Face Space](https://huggingface.co/spaces/Vishwas896/Vish-AI)
- [Supabase Dashboard](https://supabase.com/dashboard/project/lyebtceryednzafhyunq)
- [DEPLOYMENT.md](./DEPLOYMENT.md)
""")
if __name__ == "__main__":
print("🚀 Starting Vish AI Test Server...")
print("📍 This is a simplified version for local testing")
print("🎯 Full AI features available on Hugging Face Spaces")
print("")
demo.queue()
demo.launch(
server_name="0.0.0.0",
server_port=7860,
share=False
)
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