Create app.py

app.py

@@ -0,0 +1,29 @@
+from fastapi import FastAPI
+from pydantic import BaseModel
+from transformers import AutoModelForCausalLM, AutoTokenizer
+import torch
+
+app = FastAPI()
+
+# Charger le modèle et le tokenizer
+#model_name = "mistralai/Mistral-7B-Instruct-v0.1"  # Modèle Mistral 7B
+#model_name = "HuggingFaceH4/zephyr-3b"
+#model_name = "serkanarslan/mistral-7b-mini-ft"
+model_name = "microsoft/phi-2"
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForCausalLM.from_pretrained(
+    model_name,
+    torch_dtype=torch.float16,
+    device_map="auto"  # Utilise le GPU si dispo
+)
+
+# Définir le format des requêtes
+class ChatRequest(BaseModel):
+    message: str
+
+@app.post("/chat")
+async def chat(request: ChatRequest):
+    inputs = tokenizer(request.message, return_tensors="pt").to("cuda")
+    output = model.generate(**inputs, max_length=100)
+    response = tokenizer.decode(output[0], skip_special_tokens=True)
+    return {"response": response}