text generator

Dockerfile

@@ -1,13 +1,22 @@
+
+# read the doc: https://huggingface.co/docs/hub/spaces-sdks-docker
+# you will also find guides on how best to write your Dockerfile
+
 FROM python:3.9
 
+# The two following lines are requirements for the Dev Mode to be functional
+# Learn more about the Dev Mode at https://huggingface.co/dev-mode-explorers
 RUN useradd -m -u 1000 user
-
 WORKDIR /app
 
 COPY --chown=user ./requirements.txt requirements.txt
-
 RUN pip install --no-cache-dir --upgrade -r requirements.txt
 
 COPY --chown=user . /app
 
-CMD ["uvicorn", "app:app", "--host", "0.0.0.0", "--port", "7860"]
+USER user
+
+ENV HOME=/home/user \
+	PATH=/home/user/.local/bin:$PATH
+
+CMD ["uvicorn", "main:app", "--host", "0.0.0.0", "--port", "7860"]

app.py

@@ -1,6 +1,6 @@
 from fastapi import  FastAPI
-
-
+from starlette.responses import FileResponse
+from starlette.staticfiles import StaticFiles
 
 from transformers import pipeline
 
@@ -13,6 +13,13 @@ def t5(input):
     output = pipe_flan(input)
     return {"output": output[0]["generated_text"]}
 
+
+app.mount("/", StaticFiles(directory="static", html=True), name="static")
+
+@app.get("/")
+def index() -> FileResponse:
+    return FileResponse(path="/app/static/index.html", media_type="text/html")
+
 # @app.get('/')
 # def greet():
 #     return {'Hello': 'Moti'}

static/index.html

@@ -0,0 +1,24 @@
+<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/sctipt.js

@@ -0,0 +1,17 @@
+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);
+});