Update app.py

app.py

@@ -1,206 +1,206 @@
-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 ❤️")
-
-# Launch the interface
-interface.queue().launch(
-    server_port=7860, 
-    show_error=True, 
-    inline=False,
-    #share=True,
+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", variant="primary")
+
+            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 ❤️")
+
+# Launch the interface
+interface.queue().launch(
+    server_port=7860, 
+    show_error=True, 
+    inline=False,
+    #share=True,
 )