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Dockerfile

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+## use the official Python 3.12 imagae
+FROM python:3.12
+
+## set the working directory in the container
+WORKDIR /code
+
+## copy the dependencies file to the working directory
+COPY ./requirements.txt /code/requirements.txt
+
+#3 instal the requirements.txt
+
+RUN pip install --no-cache-dir --upgrade -r /code/requirements.txt
+
+
+#setup a new user 
+RUN useradd user
+
+#switch to the new user
+USER user
+
+
+#set the home to user's home directory
+
+ENV HOME /home/user \
+    PATH=/home/user/.local/bin:$PATH
+
+
+# set the working directory to the user's home directory
+WORKDIR $HOME/app
+
+# copy the current directiry cintents into the container at /home/user/app
+COPY --chown=user . $HOME/app
+
+## Start the FASTAPI app on 7860
+CMD ["uvicorn", "app:app", "--host", "0.0.0.0", "--port", "7860"]

app.py

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+from fastapi import FastAPI
+from trasformers import pipeline
+
+## Create FastAPI app instance
+app = FastAPI()
+
+# Initialize a text generation pipeline
+# Load model directly
+from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
+
+tokenizer = AutoTokenizer.from_pretrained("google/flan-t5-small")
+model = AutoModelForSeq2SeqLM.from_pretrained("google/flan-t5-small")
+
+@app.get("/")
+def home():
+    return {"message": "Welcome to the Text Generation API!"}
+
+#Define a function to handle the GET request at /generate 
+@app.get("/generate")
+def generate(text:str):
+    ## Generate text using the model
+    output=pipe(text)
+    
+    ##return the text generate in Json response
+    return {"output":output[0]['generated_text']}
+    
+    

requirements.txt

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+fastapi>=0.74,<0.75
+requests>=2.27,<2.28
+uvicorn[standard]>=0.17,<0.18
+torch>=2.0
+transformers>=4.18
+