created an initial app

app.py

@@ -0,0 +1,64 @@
+"""
+The Streamlit app for the project demo.
+In the demo, the user can write a prompt and the model will generate a response using the grouped sampling algorithm.
+"""
+
+import streamlit as st
+from grouped_sampling import GroupedSamplingPipeLine
+
+available_models_list = "https://huggingface.co/models?pipeline_tag=text-generation&sort=downloads"
+
+
+def create_pipeline(model_name: str, group_size) -> GroupedSamplingPipeLine:
+    """
+    Creates a pipeline with the given model name and group size.
+    :param model_name: The name of the model to use.
+    :param group_size: The size of the groups to use.
+    :return: A pipeline with the given model name and group size.
+    """
+    return GroupedSamplingPipeLine(model_name=model_name, group_size=group_size)
+
+
+def on_form_submit(model_name: str, group_size: int, prompt: str) -> str:
+    """
+    Called when the user submits the form.
+    :param model_name: The name of the model to use.
+    :param group_size: The size of the groups to use.
+    :param prompt: The prompt to use.
+    :return: The output of the model.
+    """
+    pipeline = create_pipeline(model_name, group_size)
+    return pipeline(prompt)["generated_text"]
+
+
+with st.form("request_form"):
+    selected_model_name: str = st.text_input(
+        label="Model name",
+        value="gpt2",
+        help=f"The name of the model to use. Must be a model from this list: {available_models_list}"
+    )
+
+    output_length: int = st.number_input(
+        label="Output Length in tokens",
+        min_value=1,
+        max_value=4096,
+        value=100,
+        help="The length of the output text in tokens (word pieces)."
+    )
+
+    submitted_prompt: str = st.text_area(
+        label="Input for the model",
+        help="Enter the prompt for the model. The model will generate a response based on this prompt.",
+        max_chars=16384,
+    )
+
+    submitted: bool = st.form_submit_button(
+        label="Generate",
+        help="Generate the output text.",
+        disabled=False
+
+    )
+
+    if submitted:
+        output = on_form_submit(selected_model_name, output_length, submitted_prompt)
+        st.write(f"Generated text: {output}")