Spaces:
Sleeping
Sleeping
File size: 4,422 Bytes
a659071 28d44d6 a659071 28d44d6 a659071 c7381d6 28d44d6 c7381d6 a659071 c7381d6 28d44d6 c7381d6 a659071 c7381d6 28d44d6 c7381d6 a659071 c735027 2a4ebb2 a659071 2a4ebb2 a659071 c7381d6 2a4ebb2 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 |
import gradio as gr
from huggingface_hub import InferenceClient
# Initialize the Inference Client
client = InferenceClient(model="HuggingFaceH4/zephyr-7b-beta")
# Function for text summarization
def summarize(text):
try:
prompt = f"Summarize the following text:\n\n{text}\n\nSummary:"
response = client.text_generation(prompt, max_new_tokens=100)
return response
except Exception as e:
return f"Error in summarization: {str(e)}"
# Function for generating flashcards
def generate_flashcards(text):
try:
prompt = f"Generate flashcards for the following text:\n\n{text}\n\nFlashcards:"
response = client.text_generation(prompt, max_new_tokens=200)
return response
except Exception as e:
return f"Error in flashcard generation: {str(e)}"
# Function for question answering
def answer_question(text, question):
try:
prompt = f"Answer the following question based on the text:\n\nText: {text}\n\nQuestion: {question}\n\nAnswer:"
response = client.text_generation(prompt, max_new_tokens=100)
return response
except Exception as e:
return f"Error in question answering: {str(e)}"
# Function to handle task selection
def study_assistant(text, task, question=None):
if task == "Summarize":
return summarize(text)
elif task == "Generate Flashcards":
return generate_flashcards(text)
elif task == "Answer Question":
if not question:
return "Please enter a question."
return answer_question(text, question)
else:
return "Invalid task selected."
# Gradio Blocks for advanced UI
with gr.Blocks(
theme=gr.themes.Soft(primary_hue="teal", secondary_hue="pink"), # Use a vibrant theme
css=".gradio-container {background: linear-gradient(135deg, #f5f7fa, #c3cfe2);} "
".output-text {font-family: 'Arial', sans-serif; font-size: 16px; color: #333;} "
".input-text {font-family: 'Arial', sans-serif; font-size: 16px; color: #555;} "
"button {background: linear-gradient(135deg, #6a11cb, #2575fc); color: white; border: none; padding: 10px 20px; border-radius: 5px;} "
"button:hover {background: linear-gradient(135deg, #2575fc, #6a11cb);} "
) as demo:
# Title and description
gr.Markdown(
"""
# 🚀 **AI-Powered Study Assistant**
**Summarize text, generate flashcards, or answer questions using AI!**
"""
)
# Inputs
with gr.Row():
text_input = gr.Textbox(
lines=10,
label="📝 **Input Text**",
placeholder="Paste your text here...",
elem_classes="input-text"
)
question_input = gr.Textbox(
lines=2,
label="❓ **Question (for Answer Question task)**",
placeholder="Enter your question here...",
elem_classes="input-text"
)
# Task selection
task_radio = gr.Radio(
choices=["Summarize", "Generate Flashcards", "Answer Question"],
label="🎯 **Task**",
value="Summarize"
)
# Output
output_text = gr.Textbox(
label="📄 **Output**",
lines=10,
elem_classes="output-text"
)
# Submit button
submit_button = gr.Button("✨ **Submit**")
# Examples
gr.Examples(
examples=[
["The French Revolution was a period of radical social and political upheaval in France that lasted from 1789 to 1799. It led to the rise of Napoleon Bonaparte and the eventual decline of the French monarchy.", "Summarize"],
["Photosynthesis is the process by which green plants use sunlight to synthesize foods with the help of chlorophyll. It converts carbon dioxide and water into glucose and oxygen.", "Generate Flashcards"],
["The Industrial Revolution began in the 18th century and marked a major turning point in history. Almost every aspect of daily life was influenced in some way.", "Answer Question", "When did the Industrial Revolution begin?"],
],
inputs=[text_input, task_radio, question_input],
outputs=output_text,
fn=study_assistant,
label="📚 **Examples**"
)
# Link button to function
submit_button.click(
study_assistant,
inputs=[text_input, task_radio, question_input],
outputs=output_text
)
# Launch the app
demo.launch() |