init

app.py

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+
+import pandas as pd
+import warnings
+from ast import literal_eval
+import gradio as gr
+
+warnings.filterwarnings('ignore')
+
+# Load the CSV file.
+# For Hugging Face Spaces, place the CSV file in your repository (or update the path accordingly).
+df = pd.read_csv('df_chatbot_response.csv')
+
+# Create new conversation columns for variants A and B.
+df['full_conversation_a'] = ''
+df['full_conversation_b'] = ''
+
+for i in range(len(df)):
+    a = literal_eval(df['history_conversation'][i])
+    a.append({'AI': df['existing_answer'][i]})
+    b = literal_eval(df['history_conversation'][i])
+    b.append({'AI': df['new_answer'][i]})
+    df.at[i, 'full_conversation_a'] = a
+    df.at[i, 'full_conversation_b'] = b
+
+# Store conversation rounds as a list of dictionaries.
+conversation_rounds = []
+for i in range(len(df)):
+    a = df['full_conversation_a'][i]
+    # Replace literal "\n" with actual newline characters.
+    for d in a:
+        for key, value in d.items():
+            if isinstance(value, str):
+                d[key] = value.replace('\\n', '\n')
+    b = df['full_conversation_b'][i]
+    for d in b:
+        for key, value in d.items():
+            if isinstance(value, str):
+                d[key] = value.replace('\\n', '\n')
+    data_conv = {"a": df['full_conversation_a'][i], "b": df['full_conversation_b'][i]}
+    conversation_rounds.append(data_conv)
+
+# --- Helper Function to Format Conversations ---
+def format_conversation(conv):
+    """
+    Convert a list of dictionaries (with 'human' and 'AI' keys) into a list of tuples,
+    pairing each human message with its subsequent AI response.
+    """
+    pairs = []
+    i = 0
+    while i < len(conv):
+        if 'human' in conv[i]:
+            human_msg = conv[i]['human']
+            # If the next message exists and is from AI, pair them
+            if i + 1 < len(conv) and 'AI' in conv[i+1]:
+                ai_msg = conv[i+1]['AI']
+                pairs.append((human_msg, ai_msg))
+                i += 2
+            else:
+                pairs.append((human_msg, ""))
+                i += 1
+        else:
+            # If conversation starts with an AI message
+            if 'AI' in conv[i]:
+                pairs.append(("", conv[i]['AI']))
+            i += 1
+    return pairs
+
+def get_conversation(round_idx):
+    """Return formatted conversation pairs for a given round index."""
+    if round_idx < len(conversation_rounds):
+        conv = conversation_rounds[round_idx]
+        existing_pairs = format_conversation(conv["a"])
+        new_pairs = format_conversation(conv["b"])
+        return existing_pairs, new_pairs
+    else:
+        # End-of-conversation message if no more rounds.
+        return [("End of conversation.", "")], [("End of conversation.", "")]
+
+def update_conversation(choice, current_idx, choices_list):
+    """
+    Update the conversation round when the user clicks the button.
+    - 'choice' is the user's selection ("A" or "B") for the current round.
+    - 'current_idx' is the current conversation round index.
+    - 'choices_list' accumulates all the user's choices.
+    """
+    choices_list = choices_list + [choice]
+    new_idx = current_idx + 1
+
+    if new_idx >= len(conversation_rounds):
+        summary_text = "Semua percakapan selesai.\nPilihan pengguna per ronde: " + ", ".join(choices_list)
+        # Display the summary in both chatbots when done.
+        return new_idx, [("End of conversation.", summary_text)], [("End of conversation.", summary_text)], choices_list
+    else:
+        existing_pairs, new_pairs = get_conversation(new_idx)
+        return new_idx, existing_pairs, new_pairs, choices_list
+
+# --- Gradio UI Setup ---
+with gr.Blocks() as demo:
+    gr.Markdown("## Perbandingan Percakapan")
+    
+    # States to track the current round and store user choices.
+    conversation_index = gr.State(0)
+    user_choices = gr.State([])
+
+    # Display the two conversation variants side by side.
+    with gr.Row():
+        existing_chat = gr.Chatbot(label="A")
+        new_chat = gr.Chatbot(label="B")
+    
+    # Initialize the chatbots with the first conversation round.
+    initial_existing, initial_new = get_conversation(0)
+    existing_chat.value = initial_existing
+    new_chat.value = initial_new
+    
+    # Radio button for the user to choose their preferred conversation variant.
+    flag_choice = gr.Radio(choices=["A", "B"], label="Pilih percakapan yang lebih disukai:")
+    next_button = gr.Button("Percakapan Berikutnya")
+    
+    # Textbox to display the final summary of user choices.
+    summary_output = gr.Textbox(label="Ringkasan Pilihan", interactive=False)
+    
+    next_button.click(
+        update_conversation,
+        inputs=[flag_choice, conversation_index, user_choices],
+        outputs=[conversation_index, existing_chat, new_chat, user_choices]
+    )
+
+    def show_summary(choices):
+        choices_a = choices.count("A")
+        choices_b = choices.count("B")
+        return f"A: {choices_a}\nB: {choices_b}"
+    
+    gr.Button("Tampilkan Ringkasan").click(
+        show_summary,
+        inputs=[user_choices],
+        outputs=[summary_output]
+    )
+
+# Launch the Gradio app.
+if __name__ == "__main__":
+    demo.launch()

requirements.txt

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+
+pandas
+gradio