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import gradio as gr
from database import create_db
from functions import *
from functions import _generate_code
# Supported models
models_options_general = ['GPT2', 'GPT2-medium', 'GPT2-large', 'GPT2-persian', 'GPT-Neo-125M']
models_options_codegen = ['codegen']
models_options_chatbot = ['dialoGPT', 'dialoGPT-medium', 'dialoGPT-large']
# Create database
create_db()
# Interface setup
with gr.Blocks() as interface:
gr.Markdown(
"# **GPT Tools**\n\n"
"Generate something using GPT models. Select the model and adjust the parameters for optimal results."
)
with gr.Tabs():
with gr.Tab("Text Generator"):
with gr.Row():
with gr.Column(scale=1, min_width=350):
input_text = gr.Textbox(label="Input Text", placeholder="Enter your text here...", lines=4, max_lines=6)
selected_model = gr.Radio(choices=models_options_general, value="GPT2", label="Select Model", type="value")
with gr.Row():
max_tokens = gr.Slider(10, 100, value=50, step=1, label="Max New Tokens", interactive=True)
with gr.Column(scale=1, min_width=350):
output_text = gr.Textbox(label="Generated Text", interactive=False, lines=8, max_lines=12)
generate_button = gr.Button("Generate Text", variant="primary")
generate_button.click(
generate,
inputs=[input_text, selected_model, max_tokens],
outputs=output_text,
)
with gr.Tab("Multiverse Story Generator"):
with gr.Row():
with gr.Column(scale=1, min_width=350):
input_text = gr.Textbox(label="Enter your story idea", placeholder="e.g. A scientist discovers a parallel universe...", lines=4, max_lines=6)
selected_model = gr.Radio(choices=models_options_general, value="GPT2", label="Select Model for Story Generation", type="value")
max_length = gr.Slider(50, 300, value=150, step=1, label="Max Length", interactive=True)
with gr.Column(scale=1, min_width=350):
output_text = gr.Textbox(label="Generated Worlds", interactive=False, lines=12, max_lines=20)
generate_button = gr.Button("Generate Parallel Worlds", variant="primary")
generate_button.click(
generate_multiverse,
inputs=[input_text, selected_model, max_length],
outputs=output_text,
)
with gr.Tab("Interactive Story Writing"):
with gr.Row():
with gr.Column(scale=1, min_width=350):
story_input = gr.Textbox(label="Add to Story", placeholder="Enter your part of the story...", lines=4, max_lines=6)
story_model = gr.Radio(choices=models_options_general, value="GPT2", label="Select Model", type="value")
story_max_length = gr.Slider(50, 300, value=50, step=1, label="Max Length", interactive=True)
with gr.Column(scale=1, min_width=350):
story_text = gr.Textbox(label="Story So Far", interactive=False, lines=12, max_lines=20)
story_button = gr.Button("Generate Next Part", variant="primary")
reset_button = gr.Button("Reset Story", variant="secondary")
story_button.click(
interactive_story,
inputs=[story_input, story_model, story_max_length],
outputs=story_text,
)
reset_button.click(
reset_story,
inputs=[],
outputs=story_text,
)
with gr.Tab("Training"):
gr.Markdown("# **Train Model**\n\n")
with gr.Column(scale=1, min_width=250):
train_model_selector = gr.Radio(choices=models_options_general, value="GPT2", label="Select Model for Training", type="value")
train_method = gr.Radio(
choices=["Custom Text", "Database", "Dataset File", "Hugging Face Dataset"],
value="Custom Text",
label="Training Method",
type="value"
)
dataset_name = gr.Textbox(label="Hugging Face Dataset Name", placeholder="Enter dataset name (e.g., ag_news)")
split_name = gr.Textbox(label="Dataset Split", placeholder="e.g., train, test, validation")
epochs = gr.Slider(1, 100, value=10, step=1, label="Epochs", interactive=True)
batch_size = gr.Slider(1, 100, value=8, step=1, label="Batch Size", interactive=True)
password = gr.Textbox(label="Enter Training Password", placeholder="Enter password", type="password")
custom_text = gr.Textbox(label="Custom Text (optional)", placeholder="Enter custom text for training...")
dataset_file = gr.File(label="Upload Dataset", type="filepath", file_types=[".parquet", ".csv", ".json", ".txt"])
train_button = gr.Button("Train Model", variant="primary")
train_status = gr.Textbox(label="Training Status", interactive=False)
train_button.click(
verify_and_train_combined,
inputs=[train_model_selector, train_method, epochs, batch_size, password, custom_text, dataset_file, dataset_name, split_name],
outputs=train_status,
)
train_button.click(
verify_and_train_combined,
inputs=[train_model_selector, train_method, epochs, batch_size, password, custom_text, dataset_file, dataset_name, split_name],
outputs=train_status,
)
with gr.Tab("Code Generator"):
gr.Markdown("### Generate Code from Descriptions")
with gr.Row():
with gr.Column(scale=1, min_width=350):
code_prompt = gr.Textbox(label="Code Prompt", placeholder="Describe your coding task, e.g., 'Write a Python function to calculate Fibonacci numbers.'")
code_max_tokens = gr.Slider(10, 500, value=150, step=10, label="Max Tokens")
with gr.Column(scale=1, min_width=350):
generated_code = gr.Textbox(label="Generated Code", interactive=False, lines=10, max_lines=20)
generate_code_button = gr.Button("Generate Code")
generate_code_button.click(
_generate_code,
inputs=[code_prompt, code_max_tokens],
outputs=generated_code,
)
# Add AI-Powered Story World Builder Tab
with gr.Tab("Story World Builder"):
with gr.Row():
with gr.Column(scale=1, min_width=350):
world_name = gr.Textbox(label="World Name", placeholder="Enter your world name...")
locations = gr.Textbox(label="Locations", placeholder="Enter locations separated by commas...")
characters = gr.Textbox(label="Characters", placeholder="Enter characters separated by commas...")
create_button = gr.Button("Create World", variant='primary')
generate_story_button = gr.Button("Generate Story")
with gr.Column(scale=1, min_width=350):
world_status = gr.Textbox(label="World Status", interactive=False)
generated_story = gr.Textbox(label="Generated Story", interactive=False, lines=12, max_lines=20)
create_button.click(
define_world,
inputs=[world_name, locations, characters],
outputs=world_status,
)
gr.Markdown("### Generate a Story in Your World")
with gr.Row():
with gr.Column(scale=1, min_width=350):
story_world = gr.Textbox(label="Enter World Name", placeholder="World name...")
event = gr.Textbox(label="Event", placeholder="Describe an event in the world...")
selected_model = gr.Radio(choices=models_options_general, value="GPT2", label="Select Model", type="value")
max_length = gr.Slider(50, 300, value=150, step=1, label="Max Length")
with gr.Tab("Chatbot"):
gr.Markdown("### **Chat With AI Models**")
with gr.Row():
with gr.Column(scale=1, min_width=250):
username = gr.Textbox(label="Username", placeholder="Enter your username", lines=1)
chat_id = gr.Textbox(label="Chat ID (optional)", placeholder="Enter chat ID or leave blank for a new chat", lines=1)
selected_model = gr.Radio(models_options_chatbot, label="Select Model", value="dialoGPT")
send_button = gr.Button("Send", variant="primary")
reset_button = gr.Button("Reset Chat", variant="secondary")
with gr.Column(scale=1, min_width=250):
input_text = gr.Textbox(label="Your Message", placeholder="Type your message here...", lines=2)
emotion_output = gr.Textbox(label="Detected Emotion", interactive=False)
chat_output = gr.Textbox(label="Chat History", lines=10, interactive=False)
send_button.click(
chatbot_response_with_emotion,
inputs=[username, input_text, selected_model, chat_id],
outputs=[chat_output, chat_id, emotion_output]
)
reset_button.click(
reset_chat,
inputs=[username],
outputs=[chat_output]
)
gr.Markdown("---")
gr.Markdown("### **Fetch Chat IDs**")
with gr.Row():
with gr.Column(scale=1, min_width=250):
username = gr.Textbox(label="Username", placeholder="Enter your username", lines=1)
fetch_btn = gr.Button("Fetch", variant="primary")
with gr.Column(scale=1, min_width=250):
fetch_output = gr.Textbox(label="Chat IDs", lines=3, interactive=False)
fetch_btn.click(
chat_ids,
inputs=[username],
outputs=[fetch_output],
)
generate_story_button.click(
generate_story,
inputs=[selected_model, story_world, max_length, event],
outputs=generated_story,
)
gr.Markdown("Made by **AliMc2021** with β€οΈ")
# Launch the interface
interface.queue().launch(
server_port=7860,
show_error=True,
inline=False,
#share=True,
) |