Update interface.py

interface.py

@@ -98,46 +98,74 @@ def forge_agent(parent_id, new_id, collapse_torque, emotional_resonance, tier_dr
 
 # --- Validation Stages Dispatcher ---
 def run_stage(stage_name, mode, epochs, batch, lr):
-    if stage_name == "Stage 1 — CIFAR-10 Baseline":
-        return stage1.train(mode=mode, epochs=int(epochs), batch=int(batch), lr=float(lr),
-                            log_path="stage1_cifar10_log.jsonl")
-    elif stage_name == "Stage 2 — Orbital & Agent Coupling":
-        return stage2.train(mode=mode, steps=int(epochs), n=int(batch), r0=0.165,
-                            log_path="stage2_agents.jsonl")
-    elif stage_name == "Stage 3 — Unified Telemetry":
-        return stage3.train(mode=mode, steps=int(epochs), batch=int(batch),
-                            log_path="stage3_telemetry.jsonl")
-    elif stage_name == "Stage 4 — ViT-Tiny (ImageNet Subset)":
-        return stage4.train(mode=mode, data_dir=None, steps=int(epochs), batch=int(batch),
-                            lr=float(lr), log_path="stage4_vit_tiny.jsonl")
-    elif stage_name == "Stage 5 — ViT-Small/B32 (ImageNet Subset)":
-        return stage5.run(mode=mode, data_dir=None, steps=int(epochs), batch=int(batch),
-                          lr=float(lr), log="stage5_vit_small_b32.jsonl")
-    elif stage_name == "Stage 6 — ViT-Base (Full ImageNet-1K)":
-        return stage6.run(mode=mode, data_dir=None, epochs=int(epochs), batch=int(batch),
-                          lr=float(lr), log_path="stage6_vit_base.jsonl")
-    elif stage_name == "Stage 7 — CLIP Multi-Modal (Text–Image)":
-        return stage7.run(mode=mode, steps=int(epochs), batch=int(batch),
-                          lr=float(lr), log="stage7_clip.jsonl")
-    elif stage_name == "Stage 8 — RFT-LLM (Language-Only Transformer)":
-        return stage8.run(mode=mode, steps=int(epochs), batch=int(batch),
-                          lr=float(lr), log="stage8_llm.jsonl")
-    elif stage_name == "Stage 9 — Distributed LLM (DDP, 4×A100)":
-        return stage9.run_ddp(mode=mode, steps=int(epochs), batch=int(batch),
-                              seq=256, vocab=32768, lr=float(lr),
-                              log="stage9_dist_llm.jsonl")
-    elif stage_name == "Stage 10 — RFT-GPT-30B (DDP, 8×A100)":
-        return stage10.run(mode=mode, steps=int(epochs), batch=int(batch),
-                           seq=1024, vocab=32768, lr=float(lr),
-                           log="stage10_gpt30b.jsonl")
-    elif stage_name == "Stage 11 — RFT-GPT-70B (DDP, 16×A100)":
-        return stage11.run(mode=mode, steps=int(epochs), batch=int(batch),
-                           vocab=32768, lr=float(lr),
-                           log="stage11_gpt70b.jsonl")
-    elif stage_name == "Stage 12 — Production Pilot & Monitoring":
-        return stage12.main()
-    else:
-        return "Stage not yet implemented."
+    try:
+        if stage_name == "Stage 1 — CIFAR-10 Baseline":
+            stage1.train(mode=mode, epochs=int(epochs), batch=int(batch), lr=float(lr),
+                         log_path="stage1_cifar10_log.jsonl")
+            return "✅ Stage 1 complete. Log saved to stage1_cifar10_log.jsonl"
+
+        elif stage_name == "Stage 2 — Orbital & Agent Coupling":
+            stage2.train(mode=mode, steps=int(epochs), n=int(batch), r0=0.165,
+                         log_path="stage2_agents.jsonl")
+            return "✅ Stage 2 complete. Log saved to stage2_agents.jsonl"
+
+        elif stage_name == "Stage 3 — Unified Telemetry":
+            stage3.train(mode=mode, steps=int(epochs), batch=int(batch),
+                         log_path="stage3_telemetry.jsonl")
+            return "✅ Stage 3 complete. Log saved to stage3_telemetry.jsonl"
+
+        elif stage_name == "Stage 4 — ViT-Tiny (ImageNet Subset)":
+            stage4.train(mode=mode, data_dir=None, steps=int(epochs), batch=int(batch),
+                         lr=float(lr), log_path="stage4_vit_tiny.jsonl")
+            return "✅ Stage 4 complete. Log saved to stage4_vit_tiny.jsonl"
+
+        elif stage_name == "Stage 5 — ViT-Small/B32 (ImageNet Subset)":
+            stage5.run(mode=mode, data_dir=None, steps=int(epochs), batch=int(batch),
+                       lr=float(lr), log="stage5_vit_small_b32.jsonl")
+            return "✅ Stage 5 complete. Log saved to stage5_vit_small_b32.jsonl"
+
+        elif stage_name == "Stage 6 — ViT-Base (Full ImageNet-1K)":
+            stage6.run(mode=mode, data_dir=None, epochs=int(epochs), batch=int(batch),
+                       lr=float(lr), log_path="stage6_vit_base.jsonl")
+            return "✅ Stage 6 complete. Log saved to stage6_vit_base.jsonl"
+
+        elif stage_name == "Stage 7 — CLIP Multi-Modal (Text–Image)":
+            stage7.run(mode=mode, steps=int(epochs), batch=int(batch),
+                       lr=float(lr), log="stage7_clip.jsonl")
+            return "✅ Stage 7 complete. Log saved to stage7_clip.jsonl"
+
+        elif stage_name == "Stage 8 — RFT-LLM (Language-Only Transformer)":
+            stage8.run(mode=mode, steps=int(epochs), batch=int(batch),
+                       lr=float(lr), log="stage8_llm.jsonl")
+            return "✅ Stage 8 complete. Log saved to stage8_llm.jsonl"
+
+        elif stage_name == "Stage 9 — Distributed LLM (DDP, 4×A100)":
+            stage9.run_ddp(mode=mode, steps=int(epochs), batch=int(batch),
+                           seq=256, vocab=32768, lr=float(lr),
+                           log="stage9_dist_llm.jsonl")
+            return "✅ Stage 9 complete. Log saved to stage9_dist_llm.jsonl"
+
+        elif stage_name == "Stage 10 — RFT-GPT-30B (DDP, 8×A100)":
+            stage10.run(mode=mode, steps=int(epochs), batch=int(batch),
+                        seq=1024, vocab=32768, lr=float(lr),
+                        log="stage10_gpt30b.jsonl")
+            return "✅ Stage 10 complete. Log saved to stage10_gpt30b.jsonl"
+
+        elif stage_name == "Stage 11 — RFT-GPT-70B (DDP, 16×A100)":
+            stage11.run(mode=mode, steps=int(epochs), batch=int(batch),
+                        vocab=32768, lr=float(lr),
+                        log="stage11_gpt70b.jsonl")
+            return "✅ Stage 11 complete. Log saved to stage11_gpt70b.jsonl"
+
+        elif stage_name == "Stage 12 — Production Pilot & Monitoring":
+            stage12.main()
+            return "✅ Stage 12 monitoring started."
+
+        else:
+            return "Stage not yet implemented."
+    except Exception as e:
+        return f"❌ Error running {stage_name}: {e}"
+
 
 # --- Gradio Interface ---
 with gr.Blocks(theme="soft") as demo: