import os
import sys
# Add src directory to Python path for Hugging Face Spaces compatibility
PROJECT_ROOT = os.path.dirname(os.path.abspath(__file__))
SRC_DIR = os.path.join(PROJECT_ROOT, "src")
sys.path.insert(0, SRC_DIR)
import json
import gradio as gr
from numpy import add
from novel_heroes.i18n import i18n
from novel_heroes.llm_call import LLMCall
from novel_heroes.mcp_server import get_book_content, get_book_list
# NOTE: In Gradio, global variables are SHARED across all users.
# https://www.gradio.app/guides/state-in-blocks#global-state
# Maximum length for book content in characters.
# If the book is too long, it will be truncated.
# NOTE: Gemma-3-4B has a context length of 128k in tokens
BOOK_CONTENT_MAX_LENGTH = 300 * 1000
def load_book_content(book_name, progress=gr.Progress()):
"""Load book content and extract heroes."""
if not book_name:
return gr.Dropdown(choices=[], value=""), "Please select a book first."
progress(0.1, desc="Loading book content...")
book_content = get_book_content(book_name, BOOK_CONTENT_MAX_LENGTH)
progress(0.5, desc="Extracting heroes from the book...")
# Extract heroes using LLM
try:
call_llm = LLMCall()
heroes = call_llm.listup_heroes(book_content)
progress(1.0, desc="Complete!")
if heroes:
return (
book_name,
book_content,
heroes,
gr.Dropdown(choices=heroes, value=heroes[0]),
f"Successfully loaded '{book_name}' and found {len(heroes)} heroes.",
)
else:
return (
book_name,
book_content,
heroes,
gr.Dropdown(choices=[], value=""),
f"Loaded '{book_name}' but no heroes were found.",
)
except Exception as e:
return (
book_name,
book_content,
heroes,
gr.Dropdown(choices=[], value=""),
f"Error extracting heroes: {str(e)}",
)
def custom_respond(
message, history, book_name, book_content, selected_hero, lang_prompt
):
"""Custom respond function with dynamic system prompt."""
if not book_name or not selected_hero:
yield "Please select a book and hero first."
return
if not book_content:
book_content = get_book_content(book_name, BOOK_CONTENT_MAX_LENGTH)
# Generate system prompt
# fmt: off
system_prompt = (
f"You are {selected_hero}, a character from the book '{book_name}'. "
"Behave and respond according to the personality and attitude of this character. "
"If the character is unfriendly, respond unfriendly; if the character is kind, respond kindly. "
"You don't know that you are a character in a book."
"Below is the book content:\n\n"
"====================\n"
f"{book_content}\n"
"====================\n"
f"{lang_prompt}"
)
# fmt: on
# Call the original respond method with custom system prompt
call_llm = LLMCall()
for response in call_llm.respond(message, history, system_prompt=system_prompt):
yield response
def gradio_ui():
book_name = gr.BrowserState("")
heroes = gr.BrowserState([])
selected_hero = gr.BrowserState("")
book_choices = json.loads(get_book_list())
with gr.Blocks() as demo:
with gr.Tab("CLOSED"):
gr.Markdown(
# fmt: off
"⚠️**Note:**
"
"The Modal server used in this project has been stopped.
"
"If you would like to run it yourself, please clone this project via git and follow the instructions in the README.md to set up and run it."
# fmt: on
)
with gr.Tab("Chat"):
# Title
with gr.Row():
gr.Markdown("# Novel Heroes")
# Status
with gr.Row():
status_markdown = gr.Markdown(label="Status")
status_markdown.value = (
# fmt: off
"Welcome! "
"Please select a book and push the button to load it.
"
"⚠️**Note:** Cold start may take up to 3 minutes. Please wait patiently for the initial response."
# fmt: on
)
# Hidden textbox for book content
book_content = gr.Textbox(visible=False)
with gr.Row():
with gr.Column(scale=1):
# Book selection
with gr.Row():
book_dropdown = gr.Dropdown(
label="📚 Select a Book",
choices=book_choices,
interactive=True,
)
with gr.Row():
load_button = gr.Button(
"Load Book & Extract Heroes", variant="primary"
)
# Hero selection
with gr.Row():
hero_dropdown = gr.Dropdown(
label="🦸 Select a Hero", choices=[], interactive=True
)
load_button.click(
fn=load_book_content,
inputs=[book_dropdown],
outputs=[
book_name,
book_content,
heroes,
hero_dropdown,
status_markdown,
],
)
def update_hero_selection(
hero,
):
"""Update selected hero."""
return hero
hero_dropdown.change(
fn=update_hero_selection,
inputs=[hero_dropdown],
outputs=[selected_hero],
)
with gr.Row():
lang_textbox = gr.Textbox(
label="🌐 Language Prompt",
value=i18n("lang_prompt"),
)
with gr.Row():
gr.Markdown(
"💡 **Tip:** You can change the language prompt to make the chatbot reply in your favorite language!
"
"For example, try 'Please respond in Japanese.' or '日本語で答えて。' 🌏
"
"
"
"🔄 **Note:** Once you start chatting, you can't change the book or hero.
"
"If you want to pick a different one, just hit the reset button and start fresh! 😊
"
)
with gr.Column(scale=2):
# Chat interface
chat_interface = gr.ChatInterface(
fn=custom_respond,
additional_inputs=[
book_dropdown,
book_content,
hero_dropdown,
lang_textbox,
],
type="messages",
autofocus=False
)
reset_button = gr.Button("Reset", variant="secondary")
reset_button.click(
lambda: (
gr.update(value=""),
gr.update(value=""),
gr.update(choices=[], value=None),
gr.update(value=i18n("lang_prompt")),
"Status reset.",
[],
),
outputs=[
book_dropdown,
book_content,
hero_dropdown,
lang_textbox,
status_markdown,
chat_interface.chatbot_value,
],
)
with gr.Tab("List Books"):
gr.Markdown("📚 Get the list of available books.")
btn = gr.Button("Get")
output_text = gr.Textbox(label="Books")
btn.click(get_book_list, None, output_text)
with gr.Tab("Book Content"):
gr.Markdown("📖 Get the content of a book by its name.")
book_name = gr.Textbox(label="Book Name")
book_len = gr.Number(label="Max Length", value=1000)
book_content = gr.Textbox(label="Book Content", lines=20)
btn = gr.Button("Get")
btn.click(get_book_content, [book_name, book_len], book_content)
return demo
if __name__ == "__main__":
demo = gradio_ui()
# Launch the Gradio app with MCP server enabled.
# NOTE: It is required to restart the app when you add or remove MCP tools.
demo.launch(i18n=i18n, mcp_server=True)