Create backup.app.py

backup.app.py

@@ -0,0 +1,54 @@
+import streamlit as st
+import random
+from transformers import pipeline
+import pandas as pd
+
+generator = pipeline('text-generation', model='gpt2')
+max_length = 50
+
+prompts = {
+    "Difficulty sleeping": [
+        "Try keeping a consistent sleep schedule and avoid caffeine before bedtime.",
+        "Make your bedroom a comfortable and calming environment.",
+        "Avoid using electronic devices before bedtime.",
+        "Try relaxation techniques like deep breathing or meditation.",
+        "Consider talking to a healthcare provider if sleep problems persist."
+    ],
+    "Time management": [
+        "Use a planner or time-tracking app to prioritize tasks and stay on schedule.",
+        "Break down large tasks into smaller ones.",
+        "Limit multitasking and focus on one task at a time.",
+        "Delegate tasks to others when possible.",
+        "Take regular breaks and avoid overworking yourself."
+    ],
+    "Stress management": [
+        "Practice mindfulness techniques such as deep breathing or meditation.",
+        "Get regular exercise to reduce stress and improve mood.",
+        "Get enough sleep and practice good sleep habits.",
+        "Take breaks throughout the day to reduce stress levels.",
+        "Try to identify the sources of stress in your life and develop strategies to manage them."
+    ]
+}
+
+def generate_prompt(prompt):
+    solution = random.choice(prompts[prompt])
+    prompt_text = f"What can I do to {prompt.lower()}? "
+    output = generator(prompt_text, max_length=max_length, num_return_sequences=1, no_repeat_ngram_size=2, early_stopping=True)
+    output_text = output[0]['generated_text'][len(prompt_text):].strip()
+    return prompt_text, output_text, solution
+
+st.title('ICL-LM Interface')
+option = st.selectbox('Select a problem:', list(prompts.keys()))
+
+if st.button('Generate Prompt and Solution'):
+    results = []
+    for _ in range(3):
+        prompt_text, prompt, solution = generate_prompt(option)
+        results.append([prompt_text, prompt, solution])
+        
+    with open('results.txt', 'a') as f:
+        for result in results:
+            f.write(f"{result[0]}\t{result[1]}\t{result[2]}\n")
+    
+    df = pd.read_csv('results.txt', sep='\t', header=None, names=['Input', 'Prompt', 'Solution'])
+    st.write(df)