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Dockerfile

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+# using the offical python 3.12.1 image
+from python:3.12.1
+# set  the working directory to / code 
+WORKDIR / code
+#copy the current directoy contentents in container at / code
+copy ./ requirements.txt/code/ requirements.txt
+# install the  requirements.txt
+RUN pip install --no-cache-dir -r requirements.txt
+# set up a new user name "user"
+RUN useradd user
+
+USER user
+# set home  to home user's  directory 
+ENV HOME=/home/user \ 
+    PATH=/home/user/.local/bin:$PATH
+# Set the working directory in the container to the home directory of the new user
+WORKDIR $HOME/app
+
+# Set the working directory in the container to the home directory of the new user
+WORKDIR $HOME/app
+# Change the ownership of the copied files to the new user
+COPY --chown=user .$HOME/app
+
+# Start FastAPI with uvicorn
+CMD ["uvicorn", "app:app", "--host" , "0.0.0.0", "--port", "7860"]
+
+
+

README.md

@@ -1,11 +1 @@
----
-title: Text2textwithDockers
-emoji: ⚡
-colorFrom: purple
-colorTo: green
-sdk: docker
-pinned: false
-license: mit
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+# dockersgenAI

app.py

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+# @title Default title text
+from fastapi import FastAPI
+from transformers import pipeline
+
+#create nea fastAPI app instance
+app=FastAPI()
+
+# Use a pipeline as a high-level helper
+
+
+
+pipeline=pipeline("text2text-generation", model="google/flan-t5-small")
+
+@app.get("/")
+def home():
+  return  {"messag":" hellow word"}
+  @app.get("/generate")
+  def generate(text:str):
+    # Initialize the text generation pipeline
+
+    output=pipe(text)
+
+    return  {"output_text":output}[0]['generated_text']

requirements.txt

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+fastapi==0.76.*
+requests==2.27.*
+uvicorn[standard]==0.17.*
+sentencepiece==0.1.*
+torch==1.11.*
+transformers==4.*