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  1. Dockerfile +28 -0
  2. README.md +1 -11
  3. app.py +23 -0
  4. requirements.txt +6 -0
Dockerfile ADDED
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+ # using the offical python 3.12.1 image
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+ from python:3.12.1
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+ # set the working directory to / code
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+ WORKDIR / code
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+ #copy the current directoy contentents in container at / code
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+ copy ./ requirements.txt/code/ requirements.txt
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+ # install the requirements.txt
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+ RUN pip install --no-cache-dir -r requirements.txt
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+ # set up a new user name "user"
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+ RUN useradd user
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+
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+ USER user
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+ # set home to home user's directory
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+ ENV HOME=/home/user \
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+ PATH=/home/user/.local/bin:$PATH
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+ # Set the working directory in the container to the home directory of the new user
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+ WORKDIR $HOME/app
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+
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+ # Set the working directory in the container to the home directory of the new user
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+ WORKDIR $HOME/app
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+ # Change the ownership of the copied files to the new user
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+ COPY --chown=user .$HOME/app
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+
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+ # Start FastAPI with uvicorn
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+ CMD ["uvicorn", "app:app", "--host" , "0.0.0.0", "--port", "7860"]
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+
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+
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+
README.md CHANGED
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- ---
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- title: Text2textwithDockers
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- emoji: ⚡
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- colorFrom: purple
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- colorTo: green
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- sdk: docker
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- pinned: false
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- license: mit
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- ---
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-
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- Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
 
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+ # dockersgenAI
 
 
 
 
 
 
 
 
 
 
app.py ADDED
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+ # @title Default title text
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+ from fastapi import FastAPI
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+ from transformers import pipeline
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+
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+ #create nea fastAPI app instance
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+ app=FastAPI()
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+
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+ # Use a pipeline as a high-level helper
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+
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+
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+
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+ pipeline=pipeline("text2text-generation", model="google/flan-t5-small")
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+
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+ @app.get("/")
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+ def home():
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+ return {"messag":" hellow word"}
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+ @app.get("/generate")
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+ def generate(text:str):
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+ # Initialize the text generation pipeline
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+
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+ output=pipe(text)
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+
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+ return {"output_text":output}[0]['generated_text']
requirements.txt ADDED
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+ fastapi==0.76.*
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+ requests==2.27.*
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+ uvicorn[standard]==0.17.*
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+ sentencepiece==0.1.*
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+ torch==1.11.*
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+ transformers==4.*