revert changes

app.py

@@ -1,75 +1,58 @@
 import gradio as gr
-from transformers import pipeline
 
-# Initialize a dictionary of models for each strategy
-models = {
-    "GPT-2": "gpt2",
-    "ChatGPT": "EleutherAI/gpt-neo-1.3",
-    "LLaMa": "model_for_LLaMa",
-    "Vicuna": "model_for_Vicuna",
-    "Alpaca": "model_for_Alpaca",
-    "Flan-T5": "model_for_Flan-T5",
-}
+theme = gr.themes.Soft()
 
-# Define a function to generate text based on the selected model
-def generate_text(input_instruction, selected_model):
-    if selected_model in models:
-        model_name = models[selected_model]
-        pipe = pipeline("text-generation", model=model_name)
-        generated_text = pipe(input_instruction, max_length=100, do_sample=True)[0]['generated_text']
-        return generated_text
-    else:
-        return "Please select a model for this strategy."
-
-# Define example instructions for testing
-instruction_examples = [
-    ("Write a short story about a cat."),
-    ("Explain the concept of artificial intelligence."),
-    ("Compose a poem about nature."),
+query_examples=[
+    ("Default Option 1"),
+    ("Default Option 2"),
+    ("Default Option 3")
 ]
 
-# Create a Gradio interface
-iface = gr.Interface(
-    fn=generate_text,
-    inputs=gr.Textbox(placeholder="Enter instruction here..."),
+# Define a function that echoes the input text
+def echo_text(input_text):
+    return input_text
+
+with gr.Interface(
+    fn=echo_text,
+    inputs=gr.Textbox(placeholder="Enter text here..."),
     outputs=gr.Textbox(),
-    examples=instruction_examples,
+    examples=query_examples, 
     live=True,
-    title="Text Generation with Dynamic Model Selection",
-)
-
-# Additional input section 1 - User input
-with gr.Row():
-    user_input = gr.Textbox(placeholder="Enter your input...")
-
-# Additional input section 2 - Strategy 1
-with gr.Row():
-    strategy1_selector = gr.Dropdown(list(models.keys()), label="Strategy 1 - QA-Based Prompting")
-
-# Additional input section 3 - Strategy 2
-with gr.Row():
-    strategy2_selector = gr.Dropdown(list(models.keys()), label="Strategy 2 - Instruction-Based Prompting")
-
-# Additional input section 4 - Strategy 3
-with gr.Row():
-    strategy3_selector = gr.Dropdown(list(models.keys()), label="Strategy 3 - Structured Prompting")
-
-# Create a callback function for dynamic model selection
-def update_model_and_generate_text(input_instruction, selected_model):
-    if selected_model:
-        selected_model_name = strategy1_selector.value if selected_model == "Strategy 1 - QA-Based Prompting" else (
-            strategy2_selector.value if selected_model == "Strategy 2 - Instruction-Based Prompting" else
-            strategy3_selector.value)
-        iface.set_function(generate_text, inputs=[user_input, selected_model], outputs="outputs")
-        return "Selected model: " + selected_model_name
-
-# Add a submit button to trigger dynamic model selection
-submit_button = gr.Button("Submit")
-
-# Set the function for the Gradio interface to the update_model_and_generate_text function
-iface.fn = update_model_and_generate_text
-
-# Add the submit button to the interface
-iface.add(submit_button)
-
-iface.launch()
+    title="LLM Evaluator with Linguistic Scrutiny",
+    theme=theme
+) as iface:
+    blocks = gr.Blocks()
+    
+    with gr.Row():
+        vicuna_model_selector = gr.Dropdown(["7b", "13b", "33b"], label="Vicuna Model", placeholder="Select model size")
+        llama_model_selector = gr.Dropdown(["7B", "13B", "30B", "65B"], label="LLaMa Model", placeholder="Select model size")
+        chatgpt_api_key = gr.Textbox(label="ChatGPT API Key", type="password", placeholder="Enter your API key")
+
+    # Strategy 1 - QA-Based Prompting
+    with gr.Accordion("Strategy 1 - QA-Based Prompting", style="font-weight: bold; font-size: 16px;"):
+        with gr.Row():
+            chatgpt_btn = gr.Button("ChatGPT")
+            llama_btn = gr.Button("LLaMA")
+            vicuna_btn = gr.Button("Vicuna")
+            alpaca_btn = gr.Button("Alpaca")
+            flant5_btn = gr.Button("Flan-T5")
+
+    # Strategy 2 - Instruction-Based Prompting
+    with gr.Accordion("Strategy 2 - Instruction-Based Prompting", style="font-weight: bold; font-size: 16px;"):
+        with gr.Row():
+            chatgpt_btn = gr.Button("ChatGPT")
+            llama_btn = gr.Button("LLaMA")
+            vicuna_btn = gr.Button("Vicuna")
+            alpaca_btn = gr.Button("Alpaca")
+            flant5_btn = gr.Button("Flan-T5")
+
+    # Strategy 3 - Structured Prompting
+    with gr.Accordion("Strategy 3 - Structured Prompting", style="font-weight: bold; font-size: 16px;"):
+        with gr.Row():
+            chatgpt_btn = gr.Button("ChatGPT")
+            llama_btn = gr.Button("LLaMA")
+            vicuna_btn = gr.Button("Vicuna")
+            alpaca_btn = gr.Button("Alpaca")
+            flant5_btn = gr.Button("Flan-T5")
+    
+    iface.launch()