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fusion-app/app_api.py

@@ -14,6 +14,7 @@ HERE = Path(__file__).parent
 LABEL_ITEMS = json.loads((HERE / "labels.json").read_text())["labels"]
 LABELS  = [x["name"]   for x in LABEL_ITEMS]
 PROMPTS = [x["prompt"] for x in LABEL_ITEMS]   
+CSV_API = HERE / "runs_api.csv"
 
 CLIP_MODEL = "openai/clip-vit-base-patch32"
 W2V2_MODEL = "facebook/wav2vec2-base"
@@ -142,6 +143,9 @@ def top1_label(p: np.ndarray) -> str:
     return LABELS[int(np.argmax(p))]
 
 def predict_video(video, alpha=0.7):
+    if HF_TOKEN is None:
+        return "Error: HuggingFace token required", {"error": "Please set HF_Token environment variable to use API features"}, {"error": "No token available"}
+
     t0 = time.time()
 
     # FULL video analysis
@@ -178,6 +182,9 @@ def predict_video(video, alpha=0.7):
     return pred, probs, lat
 
 def predict_image_audio(image: Image.Image, audio_path: str, alpha=0.7):
+    if HF_TOKEN is None:
+        return "Error: HuggingFace token required", {"error": "Please set HF_Token environment variable to use API features"}, {"error": "No token available"}
+
     t0 = time.time()
     wave = load_audio_16k(audio_path)
 

fusion-app/app_local.py

@@ -6,7 +6,7 @@ from fusion import clip_image_probs, wav2vec2_embed_energy, wav2vec2_zero_shot_p
 
 HERE = Path(__file__).parent
 lables_PATH = HERE / "labels.json"
-
+CSV_API = HERE / "runs_api.csv"
 lables = [x["name"] for x in json.loads(lables_PATH.read_text())["labels"]]
 
 # lables = [x ["name"] for x in json.load(Path("fusion-app/labels.json").read_text())["labels"]]