Create app.py

app.py

@@ -0,0 +1,41 @@
+from flask import Flask, request, jsonify
+from transformers import AutoTokenizer, AutoModelForCausalLM
+import torch
+
+app = Flask(__name__)
+
+# Используем квантованную модель для экономии памяти
+model_name = "Qwen/Qwen-1_8B-Chat-Int4"
+
+# Загружаем модель и токенизатор
+tokenizer = AutoTokenizer.from_pretrained(model_name, trust_remote_code=True)
+model = AutoModelForCausalLM.from_pretrained(
+    model_name,
+    device_map="auto",
+    torch_dtype=torch.float16,
+    trust_remote_code=True
+)
+
+@app.route("/v1/chat/completions", methods=["POST"])
+def chat():
+    data = request.json
+    prompt = data.get("messages", "")[-1]["content"]
+
+    # Генерируем ответ
+    inputs = tokenizer(prompt, return_tensors="pt").to(model.device)
+    outputs = model.generate(**inputs, max_new_tokens=200)
+    response = tokenizer.decode(outputs[0], skip_special_tokens=True)
+
+    # Возвращаем ответ в формате OpenAI API
+    return jsonify({
+        "choices": [
+            {
+                "message": {
+                    "content": response
+                }
+            }
+        ]
+    })
+
+if __name__ == "__main__":
+    app.run()