Rename app.py to app.p

app.p

@@ -0,0 +1,102 @@
+import gradio as gr
+import json
+from deforum_engine import DeforumRunner
+
+runner = DeforumRunner(device="cpu")
+
+def process(prompts_json, neg, frames, width, height,
+            z, a, tx, ty, stre, noi, 
+            fps, steps, cadence, 
+            color, border, seed_beh, init_img, 
+            model, lora, sched):
+    try:
+        p_dict = json.loads(prompts_json.replace("'", '"'))
+        prompts = {int(k): v for k, v in p_dict.items()}
+    except Exception as e:
+        yield None, None, None, f"JSON Error: {str(e)}"
+        return
+
+    # Pass exactly 20 args + self implicitly
+    yield from runner.render(
+        prompts, neg, int(frames), int(width), int(height),
+        z, a, tx, ty, stre, noi,
+        int(fps), int(steps), int(cadence),
+        color, border, seed_beh, init_img,
+        model, lora, sched
+    )
+
+def stop_gen():
+    runner.stop()
+    return "Stopping..."
+
+css = """
+#col-container {max_width: 1000px; margin: 0 auto;}
+"""
+
+with gr.Blocks() as demo:
+    gr.Markdown("# 🌀 Deforum CPU: Full Featured\nAuthentic implementation with Cadence, Seed Control, and proper Color Coherence.")
+    
+    with gr.Row(elem_id="col-container"):
+        with gr.Column(scale=1):
+            
+            with gr.Accordion("⚙️ Engine Settings", open=False):
+                model = gr.Dropdown(label="Model", value="AlekseyCalvin/acs_model", 
+                                    choices=["AlekseyCalvin/acs_model", "runwayml/stable-diffusion-v1-5", "IDKiro/sdxs-512-dreamshaper"])
+                lora = gr.Dropdown(label="LoRA", value="latent-consistency/lcm-lora-sdv1-5", 
+                                   choices=["latent-consistency/lcm-lora-sdv1-5", "None"])
+                sched = gr.Dropdown(label="Sampler", value="LCM", 
+                                    choices=["LCM", "Euler A", "DDIM", "DPM++ 2M"])
+                seed_beh = gr.Dropdown(label="Seed Behavior", value="iter", choices=["iter", "fixed", "random"])
+                init_img = gr.Image(label="Init Image", type="pil", height=200)
+
+            prompts = gr.Code(label="Prompts (JSON)", language="json", 
+                              value='{\n "0": "a beautiful forest, sun rays, 8k",\n "30": "forest fire, smoke, dramatic lighting"\n}')
+            neg = gr.Textbox(label="Negative Prompt", value="lowres, text, error, cropped, worst quality, low quality")
+            
+            with gr.Row():
+                frames = gr.Number(label="Max Frames", value=120)
+                fps = gr.Number(label="FPS", value=15)
+            
+            with gr.Row():
+                width = gr.Slider(256, 512, value=256, step=64, label="Width")
+                height = gr.Slider(256, 512, value=256, step=64, label="Height")
+                
+            with gr.Row():
+                steps = gr.Slider(1, 20, value=4, step=1, label="Steps")
+                cadence = gr.Slider(1, 8, value=2, step=1, label="Cadence (Speed/Smoothness)")
+
+            with gr.Accordion("🎬 Motion & Coherence", open=True):
+                with gr.Row():
+                    color = gr.Dropdown(label="Color Match", value="LAB", choices=["None", "LAB", "HSV", "RGB"])
+                    border = gr.Dropdown(label="Border Mode", value="Reflect", choices=["Reflect", "Replicate", "Wrap", "Black"])
+                
+                z = gr.Textbox(label="Zoom", value="0:(1.01)")
+                a = gr.Textbox(label="Angle", value="0:(0)")
+                tx = gr.Textbox(label="Translation X", value="0:(0)")
+                ty = gr.Textbox(label="Translation Y", value="0:(0)")
+                stre = gr.Textbox(label="Strength (Decay)", value="0:(0.65)")
+                noi = gr.Textbox(label="Noise (Grain)", value="0:(0.02)")
+                
+            with gr.Row():
+                btn = gr.Button("GENERATE", variant="primary", scale=2)
+                stop = gr.Button("STOP", variant="stop", scale=1)
+            
+        with gr.Column(scale=1):
+            status = gr.Markdown("Ready")
+            preview = gr.Image(label="Last Frame")
+            video_out = gr.Video(label="Rendered Video")
+            zip_out = gr.File(label="Frames ZIP")
+
+    # Arguments: 20 inputs + self implicitly handled by click
+    inputs = [
+        prompts, neg, frames, width, height,
+        z, a, tx, ty, stre, noi,
+        fps, steps, cadence,
+        color, border, seed_beh, init_img,
+        model, lora, sched
+    ]
+    
+    btn.click(process, inputs=inputs, outputs=[preview, video_out, zip_out, status])
+    stop.click(stop_gen, outputs=status)
+
+demo.queue().launch(css=css, theme=gr.themes.Glass())

app.py

@@ -1,39 +0,0 @@
-import gradio as gr
-import json
-from deforum_engine import DeforumRunner
-
-runner = DeforumRunner(device="cpu")
-
-def process(prompts_json, neg, frames, z, a, tx, ty, stre, noi, steps, color, border, blend, init_img, model, lora, sched):
-    try:
-        p_dict = json.loads(prompts_json.replace("'", '"'))
-        p_dict = {int(k): v for k, v in p_dict.items()}
-    except: yield None, None, None, "JSON Format Error"; return
-    yield from runner.render(p_dict, neg, int(frames), 256, 256, z, a, tx, ty, stre, noi, 12, int(steps), 1, color, border, blend, init_img, model, lora, sched)
-
-with gr.Blocks() as demo:
-    gr.Markdown("# 🌀 Deforum CPU: Pro Toolkit\n**Prompt Interpolation + Anti-Crash Logic**")
-    with gr.Row():
-        with gr.Column():
-            with gr.Accordion("Pipeline", open=False):
-                m = gr.Dropdown(label="Model", value="AlekseyCalvin/acs_model", choices=["AlekseyCalvin/acs_model", "runwayml/stable-diffusion-v1-5"])
-                l = gr.Dropdown(label="LoRA", value="latent-consistency/lcm-lora-sdv1-5", choices=["latent-consistency/lcm-lora-sdv1-5", "None"])
-                s = gr.Dropdown(label="Sched", value="LCM", choices=["LCM", "Euler A"])
-                init = gr.Image(label="Init Image", type="pil")
-            prompts = gr.Code(label="Prompt Keyframes", language="json", value='{"0": "ocean wave", "50": "fire forest"}')
-            neg = gr.Textbox(label="Negative", value="blur, noise")
-            with gr.Row():
-                frames = gr.Number(label="Frames", value=60); steps = gr.Slider(2, 10, 4, label="Steps"); blend = gr.Slider(0.0, 0.4, 0.1, label="Stability Blend")
-            with gr.Accordion("Animation", open=True):
-                z, a = gr.Textbox(label="Zoom", value="0:(1.02)"), gr.Textbox(label="Angle", value="0:(0)")
-                tx, ty = gr.Textbox(label="TX", value="0:(0)"), gr.Textbox(label="TY", value="0:(0)")
-                st, no = gr.Textbox(label="Strength", value="0:(0.55)"), gr.Textbox(label="Noise", value="0:(0.02)")
-                col, bor = gr.Dropdown(label="Color", value="LAB", choices=["None","LAB"]), gr.Dropdown(label="Border", value="Reflect", choices=["Reflect","Wrap"])
-            btn = gr.Button("Generate", variant="primary"); stop = gr.Button("Stop", variant="stop")
-        with gr.Column():
-            stat = gr.Markdown("Ready"); pre = gr.Image(label="Preview"); out_v = gr.Video(label="Video"); out_z = gr.File(label="ZIP")
-
-    btn.click(process, [prompts, neg, frames, z, a, tx, ty, st, no, steps, col, bor, blend, init, m, l, s], [pre, out_v, out_z, stat])
-    stop.click(lambda: runner.stop())
-
-demo.queue().launch(theme=gr.themes.Glass())