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@@ -0,0 +1,22 @@
+FROM python:3.10-slim
+ENV DEBIAN_FRONTEND=noninteractive
+
+WORKDIR /app
+
+COPY requirements.txt .
+
+RUN apt-get update && \
+    apt-get install -y --no-install-recommends \
+        build-essential \
+        && rm -rf /var/lib/apt/lists/*
+
+RUN pip install --upgrade pip && \
+    pip install -r requirements.txt
+
+COPY . .
+
+EXPOSE 5000
+
+ENV PORT=8000
+EXPOSE $PORT
+CMD ["sh", "-c", "uvicorn app:app --host 0.0.0.0 --port $PORT"]

app.py

@@ -23,8 +23,7 @@ app.add_middleware(
 
 class Opt:
     def __init__(self):
-        self.model_name = "./unsup-simcse-xlm-roberta-base"
-        self.model_path = "core/model.pth"
+        self.model_name = "ngocminhta/falcon-v1"
         self.database_path = "core/seen_db"
         self.embedding_dim = 768
         self.device_num = 1
@@ -40,12 +39,12 @@ def load_model_resources():
     global model, tokenizer, index, label_dict, is_mixed_dict
     
     model = TextEmbeddingModel(opt.model_name)
-    state_dict = torch.load(opt.model_path, map_location=model.model.device)
-    new_state_dict={}
-    for key in state_dict.keys():
-        if key.startswith('model.'):
-            new_state_dict[key[6:]]=state_dict[key]
-    model.load_state_dict(state_dict)
+    # state_dict = torch.load(opt.model_path, map_location=model.model.device)
+    # new_state_dict={}
+    # for key in state_dict.keys():
+    #     if key.startswith('model.'):
+    #         new_state_dict[key[6:]]=state_dict[key]
+    # model.load_state_dict(state_dict)
     tokenizer=model.tokenizer
 
     index = Indexer(opt.embedding_dim)