Create app.py

app.py

@@ -0,0 +1,36 @@
+from fastapi import FastAPI
+from pydantic import BaseModel
+from transformers import AutoModelForSeq2SeqLM, AutoTokenizer
+import torch
+
+# Load Model from Hugging Face Model Hub
+MODEL_NAME = "your_username/aws-bot-model"  # Replace with your actual Hugging Face model path
+model = AutoModelForSeq2SeqLM.from_pretrained(MODEL_NAME)
+tokenizer = AutoTokenizer.from_pretrained(MODEL_NAME)
+
+def generate_response(user_input: str):
+    inputs = tokenizer(user_input, return_tensors="pt", truncation=True, max_length=128)
+    outputs = model.generate(**inputs, max_length=128)
+    response = tokenizer.decode(outputs[0], skip_special_tokens=True)
+    return response
+
+# FastAPI App
+app = FastAPI()
+
+class Query(BaseModel):
+    message: str
+
+@app.post("/chat")
+def chat(query: Query):
+    user_input = query.message.lower()
+    
+    # Placeholder for external API handling (Uncomment when you have API key)
+    # if is_unrelated_query(user_input):
+    #     return {"response": handle_external_query(user_input)}
+    
+    bot_response = generate_response(user_input)
+    return {"response": bot_response}
+
+@app.get("/")
+def root():
+    return {"message": "AWS Bot API is running!"}