numpy issue debugging

Dockerfile

@@ -22,7 +22,6 @@ COPY app.py .
 COPY qwen_classifier/ ./qwen_classifier/
 COPY setup.py . 
 RUN pip install --no-cache-dir -r requirements.txt
-RUN pip install --no-cache-dir numpy
 
 # Install PyTorch with CUDA support
 RUN pip install --no-cache-dir \

app.py

@@ -6,6 +6,7 @@ os.makedirs(os.environ['HF_HOME'], exist_ok=True)  # Ensure directory exists
 from fastapi import FastAPI
 from fastapi.responses import HTMLResponse
 import torch
+import numpy
 from transformers import AutoTokenizer
 from huggingface_hub import login
 from pydantic import BaseModel
@@ -18,6 +19,7 @@ from qwen_classifier.globals import global_model, global_tokenizer
 from qwen_classifier.model import QwenClassifier
 from qwen_classifier.config import HF_REPO, DEVICE
 
+print(numpy.__version__)
 
 app = FastAPI(title="Qwen Classifier")
 hf_repo = os.getenv("HF_REPO")

qwen_classifier/evaluate.py

@@ -15,7 +15,7 @@ from pathlib import Path
 from .config import TAG_NAMES, DEVICE, SPACE_URL, EVAL_LIMIT
 from .globals import global_model, global_tokenizer
 
-
+print(np.__version__)
 
 def _load_data(test_data_path):
     eval_limit = os.getenv("EVAL_LIM")

requirements.txt

@@ -1,5 +1,6 @@
 # Core requirements from setup.py
 torch>=2.1.0
+numpy==1.23.5
 transformers>=4.36.0
 click>=8.1.0
 scikit-learn>=1.3.0