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import re
import gradio as gr
from interfaces import utils
from modules import get_llm_factory
async def plot_gen(
temperature,
genre, place, mood,
side_char_enable1, side_char_enable2, side_char_enable3,
main_char_name, main_char_age, main_char_personality, main_char_job,
side_char_name1, side_char_age1, side_char_personality1, side_char_job1,
side_char_name2, side_char_age2, side_char_personality2, side_char_job2,
side_char_name3, side_char_age3, side_char_personality3, side_char_job3,
llm_type="PaLM"
):
factory = get_llm_factory(llm_type)
prompts = factory.create_prompt_manager().prompts
llm_service = factory.create_llm_service()
side_char_prompt = utils.add_side_character(
[side_char_enable1, side_char_enable2, side_char_enable3],
[side_char_name1, side_char_name2, side_char_name3],
[side_char_job1, side_char_job2, side_char_job3],
[side_char_age1, side_char_age2, side_char_age3],
[side_char_personality1, side_char_personality2, side_char_personality3],
)
prompt = prompts['plot_gen']['main_plot_gen'].format(
genre=genre, place=place, mood=mood,
main_char_name=main_char_name,
main_char_job=main_char_job,
main_char_age=main_char_age,
main_char_personality=main_char_personality,
side_char_placeholder=side_char_prompt,
)
print(f"generated prompt:\n{prompt}")
parameters = llm_service.make_params(mode="text", temperature=temperature, top_k=40, top_p=1.0, max_output_tokens=4096)
response_json = await utils.retry_until_valid_json(prompt, parameters=parameters)
return (
response_json['title'],
f"## {response_json['title']}",
response_json['outline']['rising action'],
response_json['outline']['crisis'],
response_json['outline']['climax'],
response_json['outline']['falling action'],
response_json['outline']['denouement'],
)
async def first_story_gen(
title,
rising_action, crisis, climax, falling_action, denouement,
genre, place, mood,
side_char_enable1, side_char_enable2, side_char_enable3,
main_char_name, main_char_age, main_char_personality, main_char_job,
side_char_name1, side_char_age1, side_char_personality1, side_char_job1,
side_char_name2, side_char_age2, side_char_personality2, side_char_job2,
side_char_name3, side_char_age3, side_char_personality3, side_char_job3,
cursors, cur_cursor,
llm_type="PaLM"
):
factory = get_llm_factory(llm_type)
prompts = factory.create_prompt_manager().prompts
llm_service = factory.create_llm_service()
side_char_prompt = utils.add_side_character(
[side_char_enable1, side_char_enable2, side_char_enable3],
[side_char_name1, side_char_name2, side_char_name3],
[side_char_job1, side_char_job2, side_char_job3],
[side_char_age1, side_char_age2, side_char_age3],
[side_char_personality1, side_char_personality2, side_char_personality3],
)
prompt = prompts['plot_gen']['first_story_gen'].format(
genre=genre, place=place, mood=mood,
main_char_name=main_char_name,
main_char_job=main_char_job,
main_char_age=main_char_age,
main_char_personality=main_char_personality,
side_char_placeholder=side_char_prompt,
title=title,
rising_action=rising_action,
crisis=crisis,
climax=climax,
falling_action=falling_action,
denouement=denouement,
)
print(f"generated prompt:\n{prompt}")
parameters = llm_service.make_params(mode="text", temperature=1.0, top_k=40, top_p=1.0, max_output_tokens=4096)
response_json = await utils.retry_until_valid_json(prompt, parameters=parameters)
chapter_title = response_json["chapter_title"]
pattern = r"Chapter\s+\d+\s*[:.]"
chapter_title = re.sub(pattern, "", chapter_title)
cursors.append({
"title": chapter_title,
"plot_type": "rising action",
"story": "\n\n".join(response_json["paragraphs"])
})
return (
f"### {chapter_title} (\"rising action\")",
"\n\n".join(response_json["paragraphs"]),
cursors,
cur_cursor,
gr.update(interactive=True),
gr.update(interactive=True),
gr.update(value=response_json["actions"][0], interactive=True),
gr.update(value=response_json["actions"][1], interactive=True),
gr.update(value=response_json["actions"][2], interactive=True),
) |