updates

app.py

@@ -1,9 +1,6 @@
 import gradio as gr
 import sys
-
-from src.ui.components.actions import generate_text, clear
-from src.ui.components.inputs import main_component
-from src.ui.components.static import load_buttons, load_examples, model_settings
+from src.ui.components.form import form_block
 from src.ui.setup import load_html_from_file
 from src.text_generation.vertexai_setup import initialize_vertexai_params
 
@@ -21,17 +18,7 @@ def create_ui():
     with gr.Blocks(
             theme=gr.themes.Default(primary_hue=gr.themes.colors.green, secondary_hue=gr.themes.colors.blue)) as app:
         gr.HTML(html_content)
-        country, starting_point, query, sustainable, model = main_component()
-        output = gr.Textbox(label="Generated Results", lines=4)
-        max_new_tokens, temperature = model_settings()
-
-        # Load the buttons for the interface
-        load_buttons(country, starting_point, query, sustainable, model,
-                     max_new_tokens, temperature,
-                     output,
-                     generate_text_fn=generate_text,
-                     clear_fn=clear)
-        load_examples(country, starting_point, query, sustainable, model, output, generate_text)
+        form_block()
 
     return app
 

src/text_generation/mapper.py

@@ -1,7 +1,7 @@
 MODEL_MAPPER = {
-    "Gemini-1.0-pro": "gemini-1.0-pro",
     "Gemini-1.5-Flash": "gemini-1.5-flash-001",
     "Gemini-1.5-Pro": "gemini-1.5-pro-001",
+    "Gemini-1.0-pro": "gemini-1.0-pro",
     'Gemma-2-9B-it': "google/gemma-2-9b-it",
     'Gemma-2-2B-it': "google/gemma-2-2b-it",
     "Claude3.5-sonnet": "claude-3-5-sonnet@20240620",

src/ui/components/actions.py

@@ -3,16 +3,17 @@ from typing import Optional
 from src.pipeline import pipeline
 
 
-def clear():
-    return None, None, None, None, None, None
+# Define the clear function dynamically based on the number of inputs
+def clear(*args):
+    return tuple([None] * len(args))  # Return None for each input/output component dynamically
 
 
 def generate_text(
                   country: Optional[str],
                   starting_point: Optional[str],
                   query_text: str,
-                  is_sustainable: Optional[bool],
-                  model: Optional[str],
+                  is_sustainable: Optional[bool] = True,
+                  model: Optional[str] = "Gemini-1.5-Pro",
                   max_tokens: Optional[int] = 1024,
                   temp: Optional[float] = 0.49,
                   ):

src/ui/components/form.py

@@ -0,0 +1,20 @@
+import gradio as gr
+
+from src.ui.components.actions import generate_text, clear
+from src.ui.components.inputs import main_component
+from src.ui.components.static import model_settings, load_buttons, load_examples
+
+
+def form_block():
+    country, starting_point, query, model = main_component()
+    output = gr.Textbox(label="Your recommendations are sustainable with respect to the environment, your starting "
+                              "location, and month of travel.", lines=4)
+    max_new_tokens, temperature = model_settings()
+
+    # Load the buttons for the interface
+    load_buttons(country, starting_point, query, model,
+                 max_new_tokens, temperature,
+                 output,
+                 generate_text_fn=generate_text,
+                 clear_fn=clear)
+    load_examples(country, starting_point, query, model, output, generate_text)

src/ui/components/inputs.py

@@ -21,7 +21,7 @@ def update_cities(selected_country, df):
     return gr.Dropdown(choices=filtered_cities, interactive=True)
 
 
-def main_component() -> Tuple[gr.Dropdown, gr.Dropdown, gr.Textbox, gr.Checkbox, gr.Dropdown]:
+def main_component() -> Tuple[gr.Dropdown, gr.Dropdown, gr.Textbox, gr.Dropdown]:
     """
     Creates the main Gradio interface components and returns them.
 
@@ -53,22 +53,24 @@ def main_component() -> Tuple[gr.Dropdown, gr.Dropdown, gr.Textbox, gr.Checkbox,
         )
 
         # User query input
-        query = gr.Textbox(label="Query", placeholder="Ask for your city recommendation here!")
+        query = gr.Textbox(label="Enter your preferences e.g. beaches, night life etc. and ask for your "
+                                 "recommendation for European cities!", placeholder="Ask for your city recommendation"
+                                                                                    " here!")
 
         # Checkbox for sustainable travel option
-        sustainable = gr.Checkbox(
-            label="Sustainable",
-            info="Do you want your recommendations to be sustainable with regards to the environment, "
-                 "your starting location, and month of travel?"
-        )
+        # sustainable = gr.Checkbox(
+        #     label="Sustainable",
+        #     info="Do you want your recommendations to be sustainable with regards to the environment, "
+        #          "your starting location, and month of travel?"
+        # )
 
-        models = list(MODEL_MAPPER.keys())[:3]
+        models = list(MODEL_MAPPER.keys())[:2]
         # Model selection dropdown
         model = gr.Dropdown(
             choices=models,
             label="Model",
-            info="Select your model. The model will generate the recommendations based on your query."
+            info="Select your model. The model will generate sustainable recommendations based on your query."
         )
 
     # Return all the components individually
-    return country, starting_point, query, sustainable, model
+    return country, starting_point, query, model

src/ui/components/static.py

@@ -3,17 +3,13 @@ from typing import Callable, Tuple, Optional
 import gradio as gr
 
 from src.ui.components.inputs import get_places, update_cities, main_component
-
-
-def show_examples(examples):
-    return gr.Dataset(samples=examples)
+from src.ui.templates.example_data import EXAMPLES
 
 
 def load_examples(
         country: gr.components.Component,
         starting_point: gr.components.Component,
         query: gr.components.Component,
-        sustainable: gr.components.Component,
         model: gr.components.Component,
         output: gr.components.Component,
         generate_text_fn: Callable[
@@ -23,17 +19,10 @@ def load_examples(
     # Load the places data
     df = get_places()
     # Provide examples
-    example_data = [
-        ["Austria", "Vienna",
-         "I'm planning a trip in July and enjoy beaches, nightlife, and vibrant cities. Recommend some cities.",
-         True, "Gemini-1.0-pro"],
-        ["Germany", "Berlin",
-         "For winter travel, can you recommend destinations for Christmas markets? I love festive atmospheres.", False,
-         "Gemini-1.5-Pro"],
-    ]
+    example_data = EXAMPLES
     gr.Examples(
         examples=example_data,
-        inputs=[country, starting_point, query, sustainable, model],
+        inputs=[country, starting_point, query, model],
         fn=generate_text_fn,
         outputs=[output],
         cache_examples=True,
@@ -51,7 +40,6 @@ def load_buttons(
         starting_point: gr.components.Component,
         query: gr.components.Component,
         model: gr.components.Component,
-        sustainable: gr.components.Component,
         max_new_tokens: gr.components.Component,
         temperature: gr.components.Component,
         output: gr.components.Component,
@@ -80,27 +68,27 @@ def load_buttons(
     """
     with gr.Group() as btns:
         with gr.Row():
-            submit_btn = gr.Button("Submit", variant="primary")
+            submit_btn = gr.Button("Search", variant="primary")
             clear_btn = gr.Button("Clear", variant="secondary")
             cancel_btn = gr.Button("Cancel", variant="stop")
 
         # Bind actions to the buttons
         submit_btn.click(
             fn=generate_text_fn,  # Function to generate text
-            inputs=[query, model, sustainable,
+            inputs=[query, model,
                     starting_point, max_new_tokens,
                     temperature],  # Input components for generation
             outputs=[output]  # Output component
         )
         clear_btn.click(
             fn=clear_fn,  # Function to clear inputs
-            inputs=[],  # No inputs for clearing
-            outputs=[query, model, sustainable, starting_point, country, output]  # Clear all inputs and output
+            inputs=[query, model, starting_point, country, output],  # inputs for clearing
+            outputs=[query, model, starting_point, country, output]  # Clear all inputs and output
         )
         cancel_btn.click(
             fn=clear_fn,  # Function to cancel and clear inputs
-            inputs=[],  # No inputs for cancel
-            outputs=[query, model, sustainable, starting_point, country, output]  # Clear all inputs and output
+            inputs=[query, model, starting_point, country, output],  #inputs for cancel
+            outputs=[query, model, starting_point, country, output]  # Clear all inputs and output
         )
     return btns
 

src/ui/templates/example_data.py

@@ -0,0 +1,7 @@
+EXAMPLES = [
+        ["Austria", "Vienna",
+         "I'm planning a trip in July and enjoy beaches, nightlife, and vibrant cities. Recommend some cities.", "Gemini-1.5-Flash"],
+        ["Germany", "Berlin",
+         "For winter travel, can you recommend destinations for Christmas markets? I love festive atmospheres.",
+         "Gemini-1.5-Pro"],
+    ]

src/ui/templates/intro.html

@@ -32,11 +32,18 @@
     The vector embeddings are stored and accessed in a VectorDB (LanceDB) hosted in Google Cloud.
 </p>
 
-<p style="text-align: justify">This is an extension of the work by <a href="https://arxiv.org/abs/2403.18604">Banerjee
-    et al.</a></p>
-<p style="text-align: justify">To cite, please use the following:</p>
+<p style="text-align: justify">This is an extension of the following work. To <b>cite</b>, please use the following:</p>
+
+<blockquote>
+    <p> [1] <b>Enhancing sustainability in Tourism Recommender Systems,</b> <i>Ashmi Banerjee, Adithi Satish, Wolfgang
+        Wörndl</i>, In Proceedings of the 1st International Workshop on Recommender Systems for Sustainability and Social
+        Good (RecSoGood 2024), co-located with ACM RecSys 2024, Bari, Italy.
+    </p>
+</blockquote>
 <blockquote>
-    <p>Enhancing sustainability in Tourism Recommender Systems, Ashmi Banerjee, Adithi Satish, Wolfgang Wörndl.</p>
+    <p> [2] <b>Modeling Sustainable City Trips: Integrating CO2e Emissions, Popularity, and Seasonality into Tourism Recommender Systems,</b> <i>Ashmi Banerjee, Tunar Mahmudov, Emil Adler, Fitri Nur Aisyah, Wolfgang
+        Wörndl</i>, arXiv preprint <a href="https://arxiv.org/abs/2403.18604">arXiv:2403.18604 (2024)</a>.
+    </p>
 </blockquote>
 <br>
 <p style="text-align: justify; font-weight: bold"><sup>*</sup>Google Cloud credits are provided for this project.</p>