Create app.py

app.py

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+import gradio as gr
+from huggingface_hub import InferenceClient
+
+# Connect to your Hugging Face LLM
+client = InferenceClient("HuggingFaceH4/zephyr-7b-beta")
+
+# Vibe Coding Tools suggestions
+VIBE_TOOLS = [
+    ("Lovable", "https://lovable.so", "Browser-based AI + no-code prototyping for apps"),
+    ("Rocket.new", "https://www.rocket.new/", "Quick web app MVP generator"),
+    ("Bolt", "https://bolt.com", "Rapid prototyping + automation, great for MVPs"),
+    ("V0", "https://v0.dev", "Serverless backend + front-end scaffolding"),
+    ("Replit", "https://replit.com", "Full online dev environment, collaborative coding"),
+    ("Glide", "https://www.glideapps.com", "AI + no-code, spreadsheet-based apps"),
+    ("Softr", "https://www.softr.io", "Web apps on Airtable/Google Sheets"),
+    ("Builder.io", "https://www.builder.io", "Figma-to-code web apps"),
+    ("TeleportHQ", "https://teleporthq.io", "AI-assisted web front-end builder"),
+    ("Plasmic", "https://www.plasmic.app", "Frontend builder for marketing + product hybrid"),
+]
+
+# Core function to generate rich prompt
+def generate_rich_prompt(app_name, description, personas, features, tone="professional"):
+    system_message = "You are an expert hackathon product designer and AI prompt engineer."
+    user_message = f"""
+Generate a rich hackathon-ready prompt for Vibe Coding Tools (Lovable, Rocket.new, Bolt, etc.)
+Include everything needed to deliver a polished MVP & PoC.
+
+Use the following info to create a full prompt (like the X-EdTech example):
+
+Project name: {app_name}
+Summary: {description}
+Personas / Roles: {personas}
+Features: {features}
+Tone: {tone}
+
+Output structure:
+
+1. Project summary (short)
+2. Priority outcome for hackathon (clickable prototype + MVP)
+3. Opinion on tech stack & approach
+4. Deliverables expected
+5. Core modules & features with [MVP]/[PoC] markings
+6. Demo accounts with role-specific landing cards
+7. Sample data model & seed dataset
+8. Charts & dashboard details
+9. Design system & Liquid Glassmorphism rules
+10. Dark / Light toggle specifics
+11. Prototype screens to produce (minimum)
+12. AI features to simulate
+13. APIs & mock endpoints
+14. Acceptance criteria
+15. Polish / wow factors
+16. Acceptance copy / microcopy examples
+17. Constraints / nonfunctional
+18. Hackathon priorities
+19. One-slide pitch summary
+
+List 10 Vibe Coding Tools, link, purpose, and recommended techniques. Ensure the output is clear, structured, and ready-to-use by a developer or designer in a hackathon.
+"""
+
+    messages = [
+        {"role": "system", "content": system_message},
+        {"role": "user", "content": user_message}
+    ]
+
+    response = ""
+    for message in client.chat_completion(messages, max_tokens=2048, stream=True, temperature=0.7):
+        token = message.choices[0].delta.content
+        response += token
+        yield response
+
+# Build Gradio interface
+with gr.Blocks(title="X-Build: Rich Hackathon Prompt Generator") as demo:
+
+    gr.Markdown("<h2 style='text-align:center'>X-Build: Hackathon-Ready Prompt Generator</h2>")
+
+    with gr.Row():
+        with gr.Column(scale=1):
+            app_name = gr.Textbox(label="App Name", placeholder="Enter your app name")
+            description = gr.Textbox(label="App Description", placeholder="Describe your app")
+            personas = gr.Textbox(label="Personas / Roles", placeholder="Teacher, Student, Admin...")
+            features = gr.Textbox(label="Features", placeholder="Forms, Quizzes, Analytics...")
+            tone = gr.Dropdown(label="Prompt Tone", choices=["professional", "casual", "friendly"], value="professional")
+            generate_btn = gr.Button("Generate Rich Prompt")
+
+        with gr.Column(scale=1):
+            output = gr.Textbox(label="Generated Rich Prompt", lines=30, interactive=False)
+
+    generate_btn.click(
+        fn=generate_rich_prompt,
+        inputs=[app_name, description, personas, features, tone],
+        outputs=output
+    )
+
+    # Basic Dark/Light toggle
+    theme_toggle = gr.Checkbox(label="Dark Mode", info="Toggle dark/light theme")
+
+    def toggle_theme(dark_mode):
+        if dark_mode:
+            return gr.update(elem_classes="dark-theme")
+        else:
+            return gr.update(elem_classes="")
+    theme_toggle.change(fn=toggle_theme, inputs=theme_toggle, outputs=[])
+
+# Launch
+if __name__ == "__main__":
+    demo.launch()