Create app.py

app.py

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+from fastapi import FastAPI
+from transformers import pipeline
+
+
+description = """
+## Text Generation with 🤗 transformers, FastAPI, and Docker
+
+This app shows how to do text generation with Flan-T5 using FastAPI in a Docker Space 🚀
+
+Check out the [`/generate`](#/default/generate_generate_get) endpoint below to try it out!
+"""
+
+# NOTE - we configure docs_url to serve the interactive Docs at the root path
+# of the app. This way, we can use the docs as a landing page for the app on Spaces.
+app = FastAPI(docs_url="/", description=description)
+
+pipe = pipeline("text2text-generation", model="google/flan-t5-small")
+
+
+@app.get("/generate")
+def generate(text: str):
+    """
+    Using the text2text-generation pipeline from `transformers`, generate text
+    from the given input text. The model used is `google/flan-t5-small`, which
+    can be found [here](https://huggingface.co/google/flan-t5-small).
+    """
+    output = pipe(text)
+    return {"output": output[0]["generated_text"]}