Create main2.py

main2.py

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+from fastapi import FastAPI
+from transformers import pipeline
+ 
+# Create a new FastAPI app instance
+app = FastAPI()
+ 
+# Initialize the text generation pipeline
+# This function will be able to generate text
+# given an input.
+pipe = pipeline("text2text-generation", model="google/flan-t5-small")
+
+summarizer = pipeline("summarization", model="google-t5/t5-base", tokenizer="google-t5/t5-base", framework="tf")
+
+
+# Define a function to handle the GET request at `/generate`
+# The generate() function is defined as a FastAPI route that takes a 
+# string parameter called text. The function generates text based on the # input using the pipeline() object, and returns a JSON response 
+# containing the generated text under the key "output"
+@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>).
+    """
+    # Use the pipeline to generate text from the given input text
+    output = summarizer(text, min_length=5, max_length=20)
+     
+    # Return the generated text in a JSON response
+    return {"output": output[0]["generated_text"]}