Create app.py

app.py

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+# ==========================================================
+# 🧮 Decentralized Compute Network Simulation (Hugging Face Ready)
+# ==========================================================
+import gradio as gr
+import threading
+import time
+import random
+import queue
+
+# ==========================================================
+# ⚙️ Worker Node Class (With Trust & Reliability)
+# ==========================================================
+class WorkerNode:
+    def __init__(self, node_id, reliability=0.9, speed=1.0):
+        self.node_id = node_id
+        self.reliability = reliability
+        self.speed = speed
+        self.trust_score = 100
+        self.jobs_completed = 0
+        self.jobs_failed = 0
+
+    def process_job(self, job_data):
+        """Simulate compute job."""
+        complexity = len(job_data) / 10
+        delay = random.uniform(1, 3) * complexity / self.speed
+        time.sleep(delay)
+
+        try:
+            correct_result = eval(job_data)
+        except Exception as e:
+            return {"node": self.node_id, "result": str(e), "status": "error", "trust": self.trust_score}
+
+        if random.random() < self.reliability:
+            result = correct_result
+            self.trust_score = min(100, self.trust_score + 1)
+            self.jobs_completed += 1
+            status = "✅"
+        else:
+            result = correct_result + random.randint(1, 10)
+            self.trust_score = max(0, self.trust_score - 5)
+            self.jobs_failed += 1
+            status = "❌"
+
+        return {"node": self.node_id, "result": result, "status": status, "trust": self.trust_score}
+
+
+# ==========================================================
+# 🧩 Scheduler (Job Distribution + Verification)
+# ==========================================================
+class Scheduler:
+    def __init__(self, num_nodes=4):
+        self.nodes = [
+            WorkerNode(f"Node-{i+1}", reliability=random.uniform(0.7, 0.98), speed=random.uniform(0.8, 1.5))
+            for i in range(num_nodes)
+        ]
+        self.job_queue = queue.Queue()
+
+    def distribute_job(self, job_data):
+        """Send job to all nodes concurrently."""
+        results = {}
+        threads = []
+
+        def worker_task(node):
+            res = node.process_job(job_data)
+            results[node.node_id] = res
+
+        for node in self.nodes:
+            t = threading.Thread(target=worker_task, args=(node,))
+            t.start()
+            threads.append(t)
+
+        for t in threads:
+            t.join()
+        return results
+
+    def verify_results(self, results):
+        """Consensus based on trust-weighted voting."""
+        trust_weight = {}
+        for res in results.values():
+            val = res["result"]
+            trust_weight[val] = trust_weight.get(val, 0) + res["trust"]
+
+        verified_result = max(trust_weight, key=trust_weight.get)
+        agreement = trust_weight[verified_result] / sum(trust_weight.values())
+        return verified_result, round(agreement * 100, 2)
+
+
+# ==========================================================
+# 🧠 Job Handler
+# ==========================================================
+scheduler = Scheduler(num_nodes=4)
+
+def submit_job(job_expression):
+    """Handle job execution request."""
+    if not job_expression.strip():
+        return "⚠️ Please enter a valid Python expression.", "", "", "", ""
+
+    start_time = time.time()
+    results = scheduler.distribute_job(job_expression)
+    verified_result, agreement = scheduler.verify_results(results)
+    elapsed = round(time.time() - start_time, 2)
+
+    # Node result logs
+    node_logs = "\n".join([
+        f"{r['node']}: {r['status']} → {r['result']} (Trust: {r['trust']})"
+        for r in results.values()
+    ])
+
+    # Node statistics
+    performance = "\n".join([
+        f"{node.node_id} | Reliability: {node.reliability:.2f} | Trust: {node.trust_score} | Jobs: {node.jobs_completed}/{node.jobs_failed}"
+        for node in scheduler.nodes
+    ])
+
+    summary = (
+        f"✅ **Job Completed in {elapsed}s**\n\n"
+        f"**Verified Result:** {verified_result}\n"
+        f"**Node Agreement:** {agreement}%"
+    )
+
+    return summary, node_logs, verified_result, agreement, performance
+
+
+# ==========================================================
+# 🎨 Gradio Interface
+# ==========================================================
+with gr.Blocks(
+    theme=gr.themes.Soft(primary_hue="cyan", secondary_hue="indigo"),
+    title="🧮 Decentralized Compute Network Simulation"
+) as demo:
+
+    gr.Markdown("""
+    # 🌐 **Decentralized Compute Network Simulation**
+    Simulate how multiple worker nodes compute, verify, and agree on results.  
+    🧠 Experience a simple *distributed computing model* with **consensus and trust mechanisms**.
+
+    ---
+    ### 💡 Example Jobs:
+    - `(2 + 3) ** 4`
+    - `10 * (5 + 6)`
+    - `(50 / 2) + (3 * 9)`
+    ---
+    """)
+
+    with gr.Row():
+        job_input = gr.Textbox(label="💻 Job Expression", placeholder="Enter Python expression...")
+        submit_btn = gr.Button("🚀 Run Job", variant="primary")
+
+    with gr.Row():
+        result_output = gr.Markdown(label="🧾 Verified Result")
+
+    with gr.Row():
+        node_outputs = gr.Textbox(label="📡 Node Responses", lines=6)
+        verified_value = gr.Textbox(label="✅ Verified Output")
+        agreement_value = gr.Textbox(label="🤝 Agreement (%)")
+
+    gr.Markdown("---")
+    gr.Markdown("### ⚙️ **Node Performance & Trust Levels**")
+    performance_box = gr.Textbox(label="Node Statistics", lines=6)
+
+    submit_btn.click(
+        fn=submit_job,
+        inputs=job_input,
+        outputs=[result_output, node_outputs, verified_value, agreement_value, performance_box]
+    )
+
+# ✅ For Hugging Face Spaces
+demo.launch()