Update app.py

app.py

@@ -1,11 +1,13 @@
 from fastapi import FastAPI
 from fastapi.middleware.cors import CORSMiddleware
-import uvicorn
+from huggingface_hub import InferenceClient
 import uuid
+import asyncio
+import os
 
 app = FastAPI()
 
-# CORS – pozwala frontendowi łączyć się z API
+# CORS
 app.add_middleware(
     CORSMiddleware,
     allow_origins=["*"],
@@ -13,43 +15,61 @@ app.add_middleware(
     allow_headers=["*"],
 )
 
-# Prosta baza statusów w pamięci
+HF_TOKEN = os.getenv("HF_TOKEN")
+
+# MODELE – wszystkie darmowe
+VIDEO_MODELS = {
+    "tiktok": "tencent/HunyuanVideo",
+    "social": "tencent/HunyuanVideo",
+    "cinematic": "Lightricks/LTX-Video-0.9.7-distilled",
+    "ads": "Lightricks/LTX-Video-0.9.7-distilled",
+    "music": "Wan-AI/Wan2.1-T2V-1.3B",
+    "experimental": "Wan-AI/Wan2.1-T2V-1.3B",
+    "avatar": "OpenTalker/SadTalker",  # darmowy avatar
+    "image2video": "tencent/HunyuanVideo",  # I2V też działa
+}
+
+# Prosta baza zadań
 TASKS = {}
 
-@app.post("/generate")
-async def generate_video(data: dict):
-    """
-    Odbiera prompt, styl, czas trwania itd.
-    Zwraca URL do wygenerowanego wideo.
-    """
-    task_id = str(uuid.uuid4())
+async def generate_video_task(task_id, prompt, mode, image_url=None):
+    model_id = VIDEO_MODELS.get(mode, "tencent/HunyuanVideo")
+    client = InferenceClient(model_id, token=HF_TOKEN)
 
-    # Tu normalnie wywołałbyś model AI
-    # Na razie zwracamy przykładowy URL
-    video_url = "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/video-placeholder.mp4"
+    try:
+        if image_url:
+            # IMAGE → VIDEO
+            result = client.post(
+                json={"prompt": prompt, "image": image_url}
+            )
+        else:
+            # TEXT → VIDEO
+            result = client.post(
+                json={"prompt": prompt}
+            )
 
-    TASKS[task_id] = {
-        "status": "done",
-        "video_url": video_url
-    }
+        TASKS[task_id]["status"] = "done"
+        TASKS[task_id]["video_url"] = result
 
-    return {
-        "task_id": task_id,
-        "video_url": video_url
-    }
+    except Exception as e:
+        TASKS[task_id]["status"] = "error"
+        TASKS[task_id]["error"] = str(e)
 
 
-@app.get("/status/{task_id}")
-async def get_status(task_id: str):
-    """
-    Zwraca status generowania.
-    """
-    if task_id not in TASKS:
-        return {"status": "not_found"}
+@app.post("/generate")
+async def generate(data: dict):
+    prompt = data.get("prompt", "")
+    mode = data.get("mode", "tiktok")
+    image_url = data.get("image_url")
+
+    task_id = str(uuid.uuid4())
+    TASKS[task_id] = {"status": "processing"}
 
-    return TASKS[task_id]
+    asyncio.create_task(generate_video_task(task_id, prompt, mode, image_url))
 
+    return {"task_id": task_id}
 
-# Uruchamianie lokalne (HuggingFace tego nie używa)
-if __name__ == "__main__":
-    uvicorn.run(app, host="0.0.0.0", port=7860)
+
+@app.get("/status/{task_id}")
+async def status(task_id: str):
+    return TASKS.get(task_id, {"status": "not_found"})