initiate

Dockerfile

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+FROM python:3.9
+
+WORKDIR /code
+
+COPY ./requirements.txt /code/requirements.txt
+
+RUN pip install --no-cache-dir --upgrade -r /code/requirements.txt
+
+# Set up a new user named "user" with user ID 1000
+RUN useradd -m -u 1000 user
+
+# Switch to the "user" user
+USER user
+
+# Set home to the 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 directory contents into the container at $HOME/app setting the owner to the user
+COPY --chown=user . $HOME/app
+
+CMD ["uvicorn", "main:app", "--host", "0.0.0.0", "--port", "7860"]

main.py

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+from fastapi import FastAPI
+from transformers import pipeline
+
+pipe_flan = pipeline("text2text-generation", model="google/flan-t5-small")
+
+app = FastAPI()
+
+@app.get("/infer_t5")
+def t5(input):
+    output = pipe_flan(input)
+    return {"output": output[0]["generated_text"]}
+
+app.mount("/", StaticFiles(directory="static", html=True), name="static")
+def index() -> FileResponse:
+    return FileResponse(path="/app/static/index.html", media_type="text/html")

requirements.txt

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+fastapi==0.74.*
+requests==2.27.*
+sentencepiece==0.1.*
+torch==1.11.*
+transformers==4.*
+uvicorn[standard]==0.17.*

static/index.html

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+<main>
+  <section id="text-gen">
+    <h2>Text generation using Flan T5</h2>
+    <p>
+      Model:
+      <a
+        href="https://huggingface.co/google/flan-t5-small"
+        rel="noreferrer"
+        target="_blank"
+        >google/flan-t5-small
+      </a>
+    </p>
+    <form class="text-gen-form">
+      <label for="text-gen-input">Text prompt</label>
+      <input
+        id="text-gen-input"
+        type="text"
+        value="German: There are many ducks"
+      />
+      <button id="text-gen-submit">Submit</button>
+      <p class="text-gen-output"></p>
+    </form>
+  </section>
+</main>

static/script.js

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+const textGenForm = document.querySelector(".text-gen-form");
+
+const translateText = async (text) => {
+  const inferResponse = await fetch(`infer_t5?input=${text}`);
+  const inferJson = await inferResponse.json();
+
+  return inferJson.output;
+};
+
+textGenForm.addEventListener("submit", async (event) => {
+  event.preventDefault();
+
+  const textGenInput = document.getElementById("text-gen-input");
+  const textGenParagraph = document.querySelector(".text-gen-output");
+
+  textGenParagraph.textContent = await translateText(textGenInput.value);
+});