Update app.py

app.py

@@ -1,74 +1,68 @@
 import gradio as gr
+from pathlib import Path
+import argparse
+
 from STT.sst import speech_to_text
 from LLM.llm import generate_reply
 from TTS_X.tts import generate_voice
-from FantasyTalking.inference import generate_video
 from FantasyTalking.infer import load_models, main
-from pathlib import Path
-import argparse
 
-# Load FantasyTalking models
-pipe, fantasytalking, wav2vec_processor, wav2vec = load_models(
-    argparse.Namespace(
-        wan_model_dir="./models/Wan2.1-I2V-14B-720P",
-        fantasytalking_model_path="./models/fantasytalking_model.ckpt",
-        wav2vec_model_dir="./models/wav2vec2-base-960h",
-        image_path="",
-        audio_path="",
-        prompt="",
-        output_dir="./output",
-        image_size=512,
-        audio_scale=1.0,
-        prompt_cfg_scale=5.0,
-        audio_cfg_scale=5.0,
-        max_num_frames=81,
-        inference_steps=20,
-        fps=23,
-        num_persistent_param_in_dit=None,
-        seed=1111
-    )
+# ثابتات تحميل النموذج
+args_template = argparse.Namespace(
+    wan_model_dir="./models/Wan2.1-I2V-14B-720P",
+    fantasytalking_model_path="./models/fantasytalking_model.ckpt",
+    wav2vec_model_dir="./models/wav2vec2-base-960h",
+    image_path="",
+    audio_path="",
+    prompt="",
+    output_dir="./output",
+    image_size=512,
+    audio_scale=1.0,
+    prompt_cfg_scale=5.0,
+    audio_cfg_scale=5.0,
+    max_num_frames=81,
+    inference_steps=20,
+    fps=23,
+    num_persistent_param_in_dit=None,
+    seed=1111
 )
 
-def generate_video(image_path, audio_path, prompt, output_dir):
+# تحميل النماذج مرة وحدة فقط
+pipe, fantasytalking, wav2vec_processor, wav2vec = load_models(args_template)
+
+def generate_video(image_path, audio_path, prompt, output_dir="./output"):
     args = argparse.Namespace(
-        wan_model_dir="./models/Wan2.1-I2V-14B-720P",
-        fantasytalking_model_path="./models/fantasytalking_model.ckpt",
-        wav2vec_model_dir="./models/wav2vec2-base-960h",
+        **vars(args_template),
         image_path=image_path,
         audio_path=audio_path,
         prompt=prompt,
-        output_dir=output_dir,
-        image_size=512,
-        audio_scale=1.0,
-        prompt_cfg_scale=5.0,
-        audio_cfg_scale=5.0,
-        max_num_frames=81,
-        inference_steps=20,
-        fps=23,
-        num_persistent_param_in_dit=None,
-        seed=1111
+        output_dir=output_dir
     )
     return main(args, pipe, fantasytalking, wav2vec_processor, wav2vec)
 
+
 def full_pipeline(user_audio, user_image):
+    # 1. تحويل الصوت إلى نص
     user_text = speech_to_text(user_audio)
+
+    # 2. توليد الرد من LLM
     reply = generate_reply(user_text)
-    reply_audio_path = generate_voice(reply)
 
-    # Generate video from reply voice + user image
-    output_dir = "./output"
-    Path(output_dir).mkdir(parents=True, exist_ok=True)
+    # 3. تحويل الرد إلى صوت
+    reply_audio_path = generate_voice(reply)
 
+    # 4. توليد فيديو من الصورة والصوت
+    Path("./output").mkdir(parents=True, exist_ok=True)
     video_path = generate_video(
         image_path=user_image,
         audio_path=reply_audio_path,
-        prompt=reply,
-        output_dir=output_dir
+        prompt=reply
     )
 
     return user_text, reply, reply_audio_path, video_path
 
 
+# واجهة Gradio
 with gr.Blocks(title="🧠 صوتك يحرك صورة!") as demo:
     gr.Markdown("## 🎤➡️💬➡️🔊➡️📽️ من صوتك إلى فيديو متكلم!")
 
@@ -84,8 +78,8 @@ with gr.Blocks(title="🧠 صوتك يحرك صورة!") as demo:
             reply_audio = gr.Audio(label="🔊 الرد المنطوق")
             video_output = gr.Video(label="📽️ الفيديو الناتج")
 
-    btn.click(fn=full_pipeline, inputs=[audio_input, image_input],
+    btn.click(fn=full_pipeline,
+              inputs=[audio_input, image_input],
               outputs=[user_text, reply_text, reply_audio, video_output])
 
 demo.launch(inbrowser=True, share=True)
-