made few changes

Dockerfile

@@ -8,7 +8,9 @@ RUN --mount=type=secret,id=CLEARML_API_ACCESS_KEY,required=true \
 RUN useradd -m -u 1000 user
 USER user
 ENV PATH="/home/user/.local/bin:$PATH"
-
+ENV CLEARML_WEB_HOST="https://app.clear.ml/"
+ENV CLEARML_API_HOST="https://api.clear.ml"
+ENV CLEARML_FILES_HOST="https://files.clear.ml"
 WORKDIR /app
 
 COPY --chown=user ./requirements.txt requirements.txt

app.py

@@ -3,7 +3,7 @@ from fastapi.responses import HTMLResponse, RedirectResponse, JSONResponse
 from pydantic import BaseModel
 from typing import List
 import os                                    # ← add this
-from clearml import Model
+from clearml import Model, Task
 import torch
 from configs import add_args
 from models import build_or_load_gen_model
@@ -19,6 +19,15 @@ CLEARML_ACCESS_KEY   = os.environ["CLEARML_API_ACCESS_KEY"]
 CLEARML_SECRET_KEY   = os.environ["CLEARML_API_SECRET_KEY"]
 # ───────────────────────────────────────────────────────────────────────────────
 
+# Configure ClearML SDK with injected environment variables
+Task.set_credentials(
+    api_host=CLEARML_API_SERVER,
+    web_host=CLEARML_WEB_SERVER,
+    files_host=CLEARML_FILES_SERVER,
+    key=CLEARML_ACCESS_KEY,
+    secret=CLEARML_SECRET_KEY,
+)
+
 MAX_SOURCE_LENGTH = 512
 
 def pad_assert(tokenizer, source_ids):
@@ -57,16 +66,7 @@ config, base_model, tokenizer = build_or_load_gen_model(args)
 print("Base model architecture and tokenizer loaded.")
 
 # Download the fine-tuned weights via ClearML using your injected creds
-model_obj = Model(
-    model_id="34e25deb24c64b74b29c8519ed15fe3e",
-    api_host=CLEARML_API_SERVER,
-    web_host=CLEARML_WEB_SERVER,
-    files_host=CLEARML_FILES_SERVER,
-    credentials={
-        "access_key": CLEARML_ACCESS_KEY,
-        "secret_key": CLEARML_SECRET_KEY,
-    },
-)
+model_obj = Model(model_id="34e25deb24c64b74b29c8519ed15fe3e")
 finetuned_weights_path = model_obj.get_local_copy()
 adapter_dir = os.path.dirname(finetuned_weights_path)
 print(f"Fine-tuned adapter weights downloaded to directory: {adapter_dir}")