Update app.py

app.py

@@ -1,15 +1,3 @@
-"""
-HUGGINGFACE SPACE - API FOR STARLIGHT MINI
-This creates a Space with automatic API endpoints
-
-Deploy this to get a FREE, ALWAYS-ON API for your users!
-"""
-
-# ============================================
-# File: app.py (Main file for your Space)
-# ============================================
-
-APP_PY = '''
 import gradio as gr
 from transformers import AutoTokenizer, AutoModelForCausalLM
 import torch
@@ -35,10 +23,7 @@ def generate_text(
     temperature: float = 0.7,
     top_p: float = 0.9
 ) -> str:
-    """
-    Generate text from prompt
-    This function is automatically exposed as an API endpoint!
-    """
+    """Generate text from prompt"""
     if not prompt:
         return "Error: Please provide a prompt"
     
@@ -61,240 +46,53 @@ def generate_text(
     except Exception as e:
         return f"Error: {str(e)}"
 
-# Create Gradio interface with API
+# Create Gradio interface
 with gr.Blocks(title="Starlight Mini API") as demo:
-    gr.Markdown("""
-    # 🌟 Starlight Mini API
-    **Free AI Text Generation - 8B Parameters**
+    gr.Markdown("# 🌟 Starlight Mini API\n**Free AI Text Generation - 8B Parameters**")
     
-    This Space provides both a web UI and automatic API endpoints!
-    """)
-    
-    with gr.Tab("💬 Chat Interface"):
+    with gr.Tab("💬 Chat"):
         with gr.Row():
             with gr.Column():
-                prompt_input = gr.Textbox(
-                    label="Prompt",
-                    placeholder="Enter your prompt here...",
-                    lines=5
-                )
+                prompt_input = gr.Textbox(label="Prompt", placeholder="Enter your prompt...", lines=5)
                 
-                with gr.Accordion("⚙️ Settings", open=False):
-                    max_tokens_slider = gr.Slider(
-                        minimum=10,
-                        maximum=500,
-                        value=100,
-                        step=10,
-                        label="Max Tokens"
-                    )
-                    temperature_slider = gr.Slider(
-                        minimum=0.1,
-                        maximum=2.0,
-                        value=0.7,
-                        step=0.1,
-                        label="Temperature"
-                    )
-                    top_p_slider = gr.Slider(
-                        minimum=0.1,
-                        maximum=1.0,
-                        value=0.9,
-                        step=0.05,
-                        label="Top P"
-                    )
+                with gr.Accordion("Settings", open=False):
+                    max_tokens_slider = gr.Slider(10, 500, 100, step=10, label="Max Tokens")
+                    temperature_slider = gr.Slider(0.1, 2.0, 0.7, step=0.1, label="Temperature")
+                    top_p_slider = gr.Slider(0.1, 1.0, 0.9, step=0.05, label="Top P")
                 
                 generate_btn = gr.Button("✨ Generate", variant="primary")
             
             with gr.Column():
-                output_text = gr.Textbox(
-                    label="Generated Text",
-                    lines=10
-                )
+                output_text = gr.Textbox(label="Output", lines=10)
         
         gr.Examples(
-            examples=[
-                ["Once upon a time in a magical forest,"],
-                ["Explain quantum computing in simple terms:"],
-                ["Write a haiku about coding:"],
-            ],
+            [["Once upon a time"], ["Explain AI:"], ["Code a function:"]], 
             inputs=[prompt_input]
         )
     
-    with gr.Tab("📡 API Documentation"):
+    with gr.Tab("📡 API Docs"):
         gr.Markdown("""
-        ## Using the API
-        
-        This Space automatically provides API endpoints!
+        ## API Usage
         
-        ### Python Example:
+        **Python:**
         ```python
         from gradio_client import Client
-        
         client = Client("arthu1/Exquisite-Starlight")
-        result = client.predict(
-            prompt="Hello, Starlight!",
-            max_tokens=100,
-            temperature=0.7,
-            top_p=0.9,
-            api_name="/predict"
-        )
-        print(result)
+        result = client.predict("Hello!", 100, 0.7, 0.9, api_name="/predict")
         ```
         
-        ### cURL Example:
+        **cURL:**
         ```bash
         curl -X POST https://arthu1-exquisite-starlight.hf.space/api/predict \\
           -H "Content-Type: application/json" \\
-          -d '{"data": ["Your prompt here", 100, 0.7, 0.9]}'
+          -d '{"data": ["Hello!", 100, 0.7, 0.9]}'
         ```
-        
-        ### JavaScript Example:
-        ```javascript
-        const response = await fetch(
-          "https://arthu1-exquisite-starlight.hf.space/api/predict",
-          {
-            method: "POST",
-            headers: { "Content-Type": "application/json" },
-            body: JSON.stringify({
-              data: ["Your prompt here", 100, 0.7, 0.9]
-            })
-          }
-        );
-        const result = await response.json();
-        console.log(result.data[0]);
-        ```
-        
-        ### Rate Limits:
-        - Free tier: Generous limits for personal/small commercial use
-        - If you need more, consider upgrading the Space hardware
-        
-        ### Support:
-        - Report issues on the Space's Community tab
-        - Share feedback and improvements!
         """)
     
-    # Connect the button
     generate_btn.click(
         fn=generate_text,
         inputs=[prompt_input, max_tokens_slider, temperature_slider, top_p_slider],
         outputs=output_text
     )
 
-# Launch with API enabled
-demo.launch(
-    show_api=True,  # This enables automatic API endpoints!
-    share=False  # Space URL is already public
-)
-'''
-
-# ============================================
-# File: requirements.txt
-# ============================================
-
-REQUIREMENTS = '''
-gradio
-transformers
-torch
-accelerate
-gradio_client
-'''
-
-# ============================================
-# File: README.md
-# ============================================
-
-README = '''---
-title: Starlight Mini API
-emoji: 🌟
-colorFrom: purple
-colorTo: blue
-sdk: gradio
-sdk_version: 4.44.0
-app_file: app.py
-pinned: false
----
-
-# Starlight Mini API
-
-Free AI text generation API powered by an 8B parameter model.
-
-## Features
-- 🌟 8B parameter model
-- 💬 Web UI for testing
-- 📡 Automatic API endpoints
-- 🚀 Always online (free CPU tier)
-- ⚡ Fast inference
-
-## Usage
-
-### Web UI
-Just visit this Space and start chatting!
-
-### API
-See the "API Documentation" tab for code examples in Python, JavaScript, and cURL.
-
-## Model
-Based on arthu1/starlight-mini - a fine-tuned model optimized for helpfulness and coding tasks.
-
-## Credits
-Created by arthu1 / Nova Devs (North.ai)
-'''
-
-# ============================================
-# DEPLOYMENT INSTRUCTIONS
-# ============================================
-
-INSTRUCTIONS = """
-HOW TO DEPLOY YOUR SPACE:
-
-1. Go to https://huggingface.co/new-space
-
-2. Fill in:
-   - Space name: Exquisite-Starlight (or whatever you want)
-   - License: Apache-2.0
-   - SDK: Gradio
-   - Hardware: CPU (free!) or upgrade to GPU if needed
-
-3. Create the Space
-
-4. Upload these 3 files:
-   - app.py (the code above)
-   - requirements.txt
-   - README.md
-
-5. Wait 5-10 minutes for it to build
-
-6. Done! You get:
-   ✅ Public URL: https://huggingface.co/spaces/arthu1/Exquisite-Starlight
-   ✅ API URL: https://arthu1-exquisite-starlight.hf.space/api/predict
-   ✅ Web UI for testing
-   ✅ Always online (free!)
-
-7. Share the URLs with your users!
-
-IMPORTANT:
-- CPU is FREE forever
-- If you need faster inference, upgrade to GPU (costs money)
-- API endpoints are automatic - Gradio creates them for you!
-- Users can call your API from any language
-
-Your users will be happy because:
-- Free access
-- ChatGPT-like experience
-- Simple API to integrate
-- Always online
-"""
-
-print(f"""
-FILES TO CREATE:
-
-1. app.py:
-{APP_PY}
-
-2. requirements.txt:
-{REQUIREMENTS}
-
-3. README.md:
-{README}
-
-{INSTRUCTIONS}
-""")
+demo.launch(show_api=True, share=True)