add app file and the docker image

Dockerfile

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+# For more information, please refer to https://aka.ms/vscode-docker-python
+FROM python:3.9-slim
+
+# Keeps Python from generating .pyc files in the container
+ENV PYTHONDONTWRITEBYTECODE=1
+
+# Turns off buffering for easier container logging
+ENV PYTHONUNBUFFERED=1
+# Where we'll copy the code
+WORKDIR /code
+
+# Install pip requirements
+COPY requirements.txt /code/requirements.txt
+RUN python -m pip install --no-cache-dir --upgrade -r /code/requirements.txt
+
+# Creates a non-root user with an explicit UID and adds permission to access the /code folder
+# For more info, please refer to https://aka.ms/vscode-docker-python-configure-containers
+RUN useradd -u 1000 --disabled-password --gecos "" appuser && chown -R appuser /code
+USER appuser
+
+# During debugging, this entry point will be overridden. For more information, please refer to https://aka.ms/vscode-docker-python-debug
+CMD ["uvicorn", "app:app", "--host", "0.0.0.0", "--port", "7860"]

app.py

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+from transformers import BartForConditionalGeneration, BartTokenizer
+import gradio as gr
+
+# Charger le modèle BART et le tokenizer
+model_name = "facebook/bart-large-cnn"
+tokenizer = BartTokenizer.from_pretrained(model_name)
+model = BartForConditionalGeneration.from_pretrained(model_name)
+
+# Fonction pour générer du texte
+def generate_text(prompt):
+    inputs = tokenizer(prompt, return_tensors="pt", truncation=True, max_length=512)
+    summary_ids = model.generate(inputs["input_ids"], max_length=150, min_length=40, length_penalty=2.0, num_beams=4, early_stopping=True)
+    return tokenizer.decode(summary_ids[0], skip_special_tokens=True)
+
+# Créer une interface de saisie avec Gradio
+interface = gr.Interface(fn=generate_text, inputs="text", outputs="text",title="TeLLMyStory",description="Enter your story idea and the model will generate the story based on it.")
+#Lancer l'interface
+interface.launch()

requirements.txt

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+transformers
+torch
+gradio
+huggingface_hub