Update app.py

app.py

@@ -3,17 +3,48 @@ import requests
 
 API_URL = "https://rahul7star-FramePack-F1-DiffusionForce.hf.space/api/generate/"
 
-def call_framepack_api(input_image, prompt, t2v, seed, seconds):
+def call_framepack_api(
+    input_image,
+    prompt,
+    t2v,
+    n_prompt,
+    seed,
+    total_second_length,
+    latent_window_size,
+    steps,
+    cfg,
+    gs,
+    rs,
+    gpu_memory_preservation,
+    use_teacache,
+    mp4_crf,
+    lora_file,
+    lora_multiplier,
+    fp8_optimization,
+):
     files = {}
     data = {
         "prompt": prompt,
         "t2v": str(t2v).lower(),
-        "seed": seed,
-        "total_second_length": seconds,
+        "n_prompt": n_prompt,
+        "seed": int(seed),
+        "total_second_length": float(total_second_length),
+        "latent_window_size": int(latent_window_size),
+        "steps": int(steps),
+        "cfg": float(cfg),
+        "gs": float(gs),
+        "rs": float(rs),
+        "gpu_memory_preservation": float(gpu_memory_preservation),
+        "use_teacache": str(use_teacache).lower(),
+        "mp4_crf": int(mp4_crf),
+        "lora_multiplier": float(lora_multiplier),
+        "fp8_optimization": str(fp8_optimization).lower(),
     }
 
     if input_image:
         files["input_image"] = ("input.png", input_image, "image/png")
+    if lora_file:
+        files["lora_file"] = (lora_file.name, lora_file, "application/octet-stream")
 
     try:
         response = requests.post(API_URL, data=data, files=files)
@@ -21,33 +52,64 @@ def call_framepack_api(input_image, prompt, t2v, seed, seconds):
             result = response.json()
             video_url = result.get("video_url")
             preview_url = result.get("preview_image_url")
-            return video_url, preview_url
+            return video_url, preview_url, str(result)
         else:
-            return f"API Error: {response.status_code}", None
+            return None, None, f"API Error: {response.status_code} - {response.text}"
     except Exception as e:
-        return str(e), None
+        return None, None, f"Exception: {str(e)}"
 
 with gr.Blocks() as demo:
-    gr.Markdown("## FramePack API Client")
+    gr.Markdown("# FramePack API Client with Full Options")
 
     with gr.Row():
-        input_image = gr.Image(type="file", label="Input Image (optional)", sources=["upload"])
         with gr.Column():
-            prompt = gr.Textbox(label="Prompt", placeholder="Describe the scene")
+            input_image = gr.File(label="Input Image (PNG/JPG) — optional", file_types=[".png", ".jpg", ".jpeg"])
+            lora_file = gr.File(label="LoRA File (optional)", file_types=[".safetensors", ".pt", ".bin"])
+            prompt = gr.Textbox(label="Prompt")
+            n_prompt = gr.Textbox(label="Negative Prompt (optional)", value="")
             t2v = gr.Checkbox(label="Text-to-Video", value=True)
             seed = gr.Number(label="Seed", value=31337, precision=0)
-            seconds = gr.Slider(label="Video Length (seconds)", minimum=1, maximum=10, value=3)
+            total_second_length = gr.Slider(label="Video Length (seconds)", minimum=1, maximum=120, value=5, step=0.1)
+            latent_window_size = gr.Slider(label="Latent Window Size", minimum=1, maximum=33, value=9, step=1)
+            steps = gr.Slider(label="Steps", minimum=1, maximum=100, value=25, step=1)
+            cfg = gr.Slider(label="CFG Scale", minimum=1.0, maximum=32.0, value=1.0, step=0.01)
+            gs = gr.Slider(label="Distilled CFG Scale", minimum=1.0, maximum=32.0, value=10.0, step=0.01)
+            rs = gr.Slider(label="CFG Re-Scale", minimum=0.0, maximum=1.0, value=0.0, step=0.01)
+            gpu_memory_preservation = gr.Slider(label="GPU Inference Preserved Memory (GB)", minimum=6, maximum=128, value=6, step=0.1)
+            use_teacache = gr.Checkbox(label="Use TeaCache", value=True)
+            mp4_crf = gr.Slider(label="MP4 Compression", minimum=0, maximum=100, value=16, step=1)
+            lora_multiplier = gr.Slider(label="LoRA Multiplier", minimum=0.0, maximum=1.0, value=0.8, step=0.1)
+            fp8_optimization = gr.Checkbox(label="FP8 Optimization", value=False)
 
-    generate_btn = gr.Button("Generate")
+            generate_btn = gr.Button("Generate")
 
-    with gr.Row():
-        video_output = gr.Video(label="Generated Video", autoplay=True)
-        preview_output = gr.Image(label="Preview Image")
+        with gr.Column():
+            video_output = gr.Video(label="Generated Video", autoplay=True)
+            preview_output = gr.Image(label="Preview Image")
+            api_response = gr.Textbox(label="API JSON Response", lines=10)
 
     generate_btn.click(
         fn=call_framepack_api,
-        inputs=[input_image, prompt, t2v, seed, seconds],
-        outputs=[video_output, preview_output]
+        inputs=[
+            input_image,
+            prompt,
+            t2v,
+            n_prompt,
+            seed,
+            total_second_length,
+            latent_window_size,
+            steps,
+            cfg,
+            gs,
+            rs,
+            gpu_memory_preservation,
+            use_teacache,
+            mp4_crf,
+            lora_file,
+            lora_multiplier,
+            fp8_optimization,
+        ],
+        outputs=[video_output, preview_output, api_response],
     )
 
 demo.launch()