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Create app.py
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app.py
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| 1 |
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import os
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| 2 |
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import re
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| 3 |
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import time
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import json
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import subprocess
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import gradio as gr
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from openai import OpenAI
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from duckduckgo_search import DDGS
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| 9 |
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# --- OpenRouter Setup ---
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OPENROUTER_API_KEY = os.getenv("OPENROUTER_API_KEY", "your-openrouter-key")
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client = OpenAI(
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base_url="https://openrouter.ai/api/v1",
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api_key=OPENROUTER_API_KEY,
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)
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# --- Model Definitions ---
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MODEL_RESEARCHER = "z-ai/glm-4.5-air"
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MODEL_PLANNER = "arcee-ai/trinity-large-preview"
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MODEL_FRONTEND = "qwen/qwen3-coder"
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MODEL_BACKEND = "minimax/minimax-m2.5"
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WORKSPACE_DIR = "/app/workspace"
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preview_process = None
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# --- Helper Functions ---
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def extract_code(text, lang="javascript"):
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"""Extracts code blocks from markdown responses."""
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pattern = rf"```{lang}\n(.*?)\n```"
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matches = re.findall(pattern, text, re.DOTALL)
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if matches:
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return matches[0]
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# Fallback to any code block
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pattern_any = r"```.*?\n(.*?)\n```"
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matches_any = re.findall(pattern_any, text, re.DOTALL)
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return matches_any[0] if matches_any else text
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def web_search(query):
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"""Real-time web search for the Researcher AI"""
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try:
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results = DDGS().text(query, max_results=3)
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return "\n".join([f"- {r['title']}: {r['body']}" for r in results])
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except Exception as e:
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return f"Web search failed: {e}"
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def run_openrouter(model, system_prompt, user_prompt):
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"""Wrapper for OpenRouter API calls"""
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response = client.chat.completions.create(
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model=model,
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messages=[
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{"role": "system", "content": system_prompt},
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{"role": "user", "content": user_prompt}
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]
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)
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return response.choices[0].message.content
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# --- Multi-Agent Pipeline ---
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def generate_website(prompt):
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global preview_process
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logs = []
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yield "Step 1: π Researcher (GLM-4.5-Air) gathering real-time data...", "", ""
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# 1. RESEARCHER
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search_context = web_search(prompt)
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research_prompt = f"User Request: {prompt}\nReal-time Web Context: {search_context}\nSummarize the requirements, target audience, and modern tech trends for this app."
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research_data = run_openrouter(
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MODEL_RESEARCHER,
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"You are an expert tech researcher. Analyze the user request and web data.",
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research_prompt
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)
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logs.append("β
Research completed.")
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yield "\n".join(logs), "Step 2: ποΈ Planner (Trinity-Large) designing architecture...", ""
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# 2. PLANNER
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plan_prompt = f"Based on this research: {research_data}\nCreate a full stack architecture plan. Define the React frontend components and Express backend endpoints."
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architecture_plan = run_openrouter(
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MODEL_PLANNER,
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"You are a Lead Solutions Architect. Output a clear, structured technical design.",
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plan_prompt
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)
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logs.append("β
Architecture planned.")
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yield "\n".join(logs), "Step 3: π» Frontend Coder (Qwen3-Coder) building UI...", ""
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# 3. FRONTEND CODER
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fe_prompt = f"Architecture: {architecture_plan}\nWrite a complete React App using standard React and Tailwind. Output two things: 1. A package.json file wrapped in ```json ... ``` containing required dependencies. 2. A complete App.jsx wrapped in ```javascript ... ```."
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frontend_code_raw = run_openrouter(
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MODEL_FRONTEND,
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"You are an Expert React Developer. Generate functional, modern React code.",
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fe_prompt
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)
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app_jsx = extract_code(frontend_code_raw, "javascript")
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package_json = extract_code(frontend_code_raw, "json")
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# Save Frontend files
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os.makedirs(os.path.join(WORKSPACE_DIR, "frontend", "src"), exist_ok=True)
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with open(os.path.join(WORKSPACE_DIR, "frontend", "package.json"), "w") as f:
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f.write(package_json)
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with open(os.path.join(WORKSPACE_DIR, "frontend", "src", "App.jsx"), "w") as f:
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f.write(app_jsx)
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logs.append("β
Frontend generated and saved.")
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yield "\n".join(logs), "Step 4: π Backend Coder (MiniMax-M2.5) building secure API...", ""
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# 4. BACKEND CODER & INSTRUCTION GUIDE
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be_prompt = f"Architecture: {architecture_plan}\nWrite a secure Express.js backend. Provide the server code wrapped in ```javascript ... ```. Then, provide a detailed Markdown guide wrapped in ```markdown ... ``` explaining exactly where the user needs to add their Postgres/MongoDB strings, Stripe Secret Keys, and Clerk/Auth0 tokens."
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backend_code_raw = run_openrouter(
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MODEL_BACKEND,
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"You are a Senior Security & Backend Engineer.",
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be_prompt
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)
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server_js = extract_code(backend_code_raw, "javascript")
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setup_guide = extract_code(backend_code_raw, "markdown")
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# Save Backend files
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os.makedirs(os.path.join(WORKSPACE_DIR, "backend"), exist_ok=True)
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with open(os.path.join(WORKSPACE_DIR, "backend", "server.js"), "w") as f:
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f.write(server_js)
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with open(os.path.join(WORKSPACE_DIR, "SETUP_GUIDE.md"), "w") as f:
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f.write(setup_guide)
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logs.append("β
Backend and Setup Guide generated.")
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yield "\n".join(logs), "Step 5: βοΈ Installing Dependencies & Starting Live Preview...", setup_guide
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# 5. EXECUTION & DEPENDENCY DOWNLOAD
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try:
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# Install dependencies
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subprocess.run(["npm", "install"], cwd=os.path.join(WORKSPACE_DIR, "frontend"), check=True)
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logs.append("β
AI successfully downloaded dependencies.")
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yield "\n".join(logs), "Starting Server...", setup_guide
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# Kill previous process if it exists
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if preview_process:
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preview_process.kill()
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# Normally you would use a bundler like Vite. To keep it robust for this example,
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# we start a simple HTTP server or a lightweight bundler command if defined in package.json.
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# Assuming AI creates standard start scripts:
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preview_process = subprocess.Popen(
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["npm", "start"],
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cwd=os.path.join(WORKSPACE_DIR, "frontend"),
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env=dict(os.environ, PORT="3000")
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)
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# Give server time to boot
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time.sleep(5)
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logs.append("π Live preview is running!")
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iframe_html = f'<iframe src="https://{os.getenv("SPACE_HOST", "localhost")}:3000" width="100%" height="600px" style="border:1px solid #ccc; border-radius: 8px;"></iframe>'
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yield "\n".join(logs), iframe_html, setup_guide
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except Exception as e:
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logs.append(f"β Execution Error: {str(e)}")
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yield "\n".join(logs), "Failed to start live preview.", setup_guide
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| 158 |
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# --- UI Setup (Gradio) ---
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with gr.Blocks(theme=gr.themes.Soft()) as demo:
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| 161 |
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gr.Markdown("# π Multi-Agent AI Full-Stack Builder")
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gr.Markdown("Powered by `z-ai/glm-4.5-air` (Researcher), `arcee-ai/trinity-large` (Architect), `qwen/qwen3-coder` (Frontend), and `minimax-m2.5` (Backend).")
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with gr.Row():
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with gr.Column(scale=1):
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prompt_input = gr.Textbox(lines=4, placeholder="E.g., Build a SaaS dashboard for an AI writing tool with Stripe subscriptions...", label="App Idea")
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| 167 |
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build_btn = gr.Button("Build Application", variant="primary")
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| 168 |
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status_box = gr.Textbox(label="Agent Status Logs", lines=10, interactive=False)
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with gr.Column(scale=2):
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gr.Markdown("### Live Website Preview")
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preview_box = gr.HTML("<div style='text-align:center; padding: 50px; border:1px dashed gray;'>Preview will appear here once built.</div>")
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with gr.Row():
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gr.Markdown("### Setup Guide (DB, Auth & Payments)")
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guide_box = gr.Markdown("Setup instructions will appear here.")
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build_btn.click(
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fn=generate_website,
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inputs=[prompt_input],
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outputs=[status_box, preview_box, guide_box]
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)
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if __name__ == "__main__":
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demo.launch(server_name="0.0.0.0", server_port=7860)
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