fixed generate

Dockerfile

@@ -4,16 +4,18 @@ FROM python:3.9
 # Set the working directory to /code
 WORKDIR /code
 
-# Copy the current directory contents into the container at /code
-COPY ./requirements.txt /code/requirements.txt
+# Copy the requirements.txt file into the container
+COPY requirements.txt .
 
-# Install requirements.txt 
-RUN pip install --no-cache-dir --upgrade -r /code/requirements.txt
+# Install the dependencies
+RUN pip install --no-cache-dir --upgrade -r 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
@@ -24,5 +26,8 @@ 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
 
+# Expose the port FastAPI will run on
+EXPOSE 7860
+
 # Start the FastAPI app on port 7860, the default port expected by Spaces
 CMD ["uvicorn", "app:app", "--host", "0.0.0.0", "--port", "7860"]

app.py

@@ -5,24 +5,22 @@ from transformers import pipeline
 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")
+pipe = pipeline("text2text-generation", model="google/flan-t5-small")
+
+# Define a root path to verify the server is running
+@app.get("/")
+def read_root():
+    return {"message": "Welcome to the FastAPI application. Use /generate to generate text."}
 
 # 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>).
+    from the given input text. The model used is `google/flan-t5-small`.
     """
     # Use the pipeline to generate text from the given input text
     output = pipe(text)
-
+    
     # Return the generated text in a JSON response
-    return {"output": output[0]["generated_text"]}
+    return {"output": output[0]["generated_text"]}