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  1. Dockerfile +11 -0
  2. app.py +28 -0
  3. requirements.txt +6 -0
Dockerfile ADDED
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+ FROM python:3.9
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+
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+ WORKDIR /code
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+
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+ COPY ./requirements.txt /code/requirements.txt
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+
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+ RUN pip install --no-cache-dir --upgrade -r /code/requirements.txt
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+
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+ COPY . .
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+
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+ CMD ["uvicorn", "app.main:app", "--host", "0.0.0.0", "--port", "7860"]
app.py ADDED
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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 a new FastAPI app instance
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+ app = FastAPI()
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+
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+ # Initialize the text generation pipeline
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+ # This function will be able to generate text
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+ # given an input.
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+ pipe = pipeline("text2text-generation",
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+ model="google/flan-t5-small")
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+
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+ # Define a function to handle the GET request at `/generate`
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+ # The generate() function is defined as a FastAPI route that takes a
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+ # string parameter called text. The function generates text based on the # input using the pipeline() object, and returns a JSON response
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+ # containing the generated text under the key "output"
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+ @app.get("/generate")
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+ def generate(text: str):
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+ """
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+ Using the text2text-generation pipeline from `transformers`, generate text
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+ from the given input text. The model used is `google/flan-t5-small`, which
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+ can be found [here](<https://huggingface.co/google/flan-t5-small>).
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+ """
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+ # Use the pipeline to generate text from the given input text
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+ output = pipe(text)
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+
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+ # Return the generated text in a JSON response
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+ return {"output": output[0]["generated_text"]}
requirements.txt ADDED
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+ fastapi==0.74.*
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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.*