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from dotenv import load_dotenv
from utils.src.utils import ppt_to_images, get_json_from_response
import json
from camel.models import ModelFactory
from camel.agents import ChatAgent
from utils.wei_utils import *
from camel.messages import BaseMessage
from PIL import Image
import pickle as pkl
from utils.pptx_utils import *
from utils.critic_utils import *
import yaml
import argparse
import shutil
from jinja2 import Environment, StrictUndefined
load_dotenv()
MAX_ATTEMPTS = 5
def deoverflow(args, actor_config, critic_config):
total_input_token, total_output_token = 0, 0
style_ckpt = pkl.load(open(f'checkpoints/{args.model_name}_{args.poster_name}_style_ckpt_{args.index}.pkl', 'rb'))
logs_ckpt = pkl.load(open(f'checkpoints/{args.model_name}_{args.poster_name}_ckpt_{args.index}.pkl', 'rb'))
style_logs = style_ckpt['style_logs']
sections = list(style_logs.keys())
sections = [s for s in sections if s != 'meta']
slide_width = style_ckpt['outline']['meta']['width']
slide_height = style_ckpt['outline']['meta']['height']
content = json.load(open(f'contents/{args.model_name}_{args.poster_name}_poster_content_{args.index}.json', 'r'))
outline = logs_ckpt['outline']
name_to_hierarchy = get_hierarchy(outline, 1)
critic_agent_name = 'critic_overlap_agent'
with open(f"prompt_templates/{critic_agent_name}.yaml", "r") as f:
deoverflow_critic_config = yaml.safe_load(f)
actor_agent_name = 'actor_editor_agent'
with open(f"prompt_templates/{actor_agent_name}.yaml", "r") as f:
deoverflow_actor_config = yaml.safe_load(f)
actor_model = ModelFactory.create(
model_platform=actor_config['model_platform'],
model_type=actor_config['model_type'],
model_config_dict=actor_config['model_config'],
)
actor_sys_msg = deoverflow_actor_config['system_prompt']
actor_agent = ChatAgent(
system_message=actor_sys_msg,
model=actor_model,
message_window_size=10,
)
critic_model = ModelFactory.create(
model_platform=critic_config['model_platform'],
model_type=critic_config['model_type'],
model_config_dict=critic_config['model_config'],
)
critic_sys_msg = deoverflow_critic_config['system_prompt']
critic_agent = ChatAgent(
system_message=critic_sys_msg,
model=critic_model,
message_window_size=None,
)
jinja_env = Environment(undefined=StrictUndefined)
actor_template = jinja_env.from_string(deoverflow_actor_config["template"])
critic_template = jinja_env.from_string(deoverflow_critic_config["template"])
critic_logs = {}
actor_logs = {}
img_logs = {}
# Load neg and pos examples
neg_img = Image.open('overflow_example/neg.jpg')
pos_img = Image.open('overflow_example/pos.jpg')
for section_index in range(len(sections)):
section_name = sections[section_index]
section_code = style_logs[section_name][-1]['code']
if 'subsections' in content[section_name]:
subsections = list(content[section_name]['subsections'].keys())
else:
subsections = [section_name]
log = []
for leaf_section in subsections:
if leaf_section in outline:
leaf_name = outline[leaf_section]['name']
else:
leaf_name = outline[section_name]['subsections'][leaf_section]['name']
num_rounds = 0
while True:
print(f"Section: {section_name}, Leaf Section: {leaf_section}, Round: {num_rounds}")
num_rounds += 1
if num_rounds > MAX_ATTEMPTS:
break
poster = create_poster(slide_width, slide_height)
add_blank_slide(poster)
save_presentation(poster, file_name='poster.pptx')
curr_location, zoomed_in_img, zoomed_in_img_path = get_snapshot_from_section(
leaf_section,
section_name,
name_to_hierarchy,
leaf_name,
section_code
)
if not leaf_section in img_logs:
img_logs[leaf_section] = []
img_logs[leaf_section].append(zoomed_in_img)
jinja_args = {
'content_json': content[leaf_section] if leaf_section in content else content[section_name]['subsections'][leaf_section],
'existing_code': section_code,
}
critic_prompt = critic_template.render(**jinja_args)
critic_msg = BaseMessage.make_user_message(
role_name="User",
content=critic_prompt,
image_list=[neg_img, pos_img, zoomed_in_img],
)
critic_agent.reset()
response = critic_agent.step(critic_msg)
resp = response.msgs[0].content
input_token, output_token = account_token(response)
total_input_token += input_token
total_output_token += output_token
if not leaf_section in critic_logs:
critic_logs[leaf_section] = []
critic_logs[leaf_section].append(response)
if type(resp) == str:
if resp in ['NO', 'NO.', '"NO"', "'NO'"]:
break
feedback = get_json_from_response(resp)
print(feedback)
jinja_args = {
'content_json': content[leaf_section] if leaf_section in content else content[section_name]['subsections'][leaf_section],
'function_docs': documentation,
'existing_code': section_code,
'suggestion_json': feedback,
}
actor_prompt = actor_template.render(**jinja_args)
log = edit_code(actor_agent, actor_prompt, 3, existing_code='')
if log[-1]['error'] is not None:
raise Exception(log[-1]['error'])
input_token = log[-1]['cumulative_tokens'][0]
output_token = log[-1]['cumulative_tokens'][1]
total_input_token += input_token
total_output_token += output_token
section_code = log[-1]['code']
if not leaf_section in actor_logs:
actor_logs[leaf_section] = []
actor_logs[leaf_section].append(log)
if len(log) > 0:
style_logs[section_name].append(log[-1])
final_code = ''
for section in sections:
final_code += style_logs[section][-1]['code'] + '\n'
run_code_with_utils(final_code, utils_functions)
ppt_to_images(f'poster.pptx', 'tmp/non_overlap_preview')
result_dir = f'results/{args.poster_name}/{args.model_name}/{args.index}'
if not os.path.exists(result_dir):
os.makedirs(result_dir)
shutil.copy('poster.pptx', f'{result_dir}/non_overlap_poster.pptx')
ppt_to_images(f'poster.pptx', f'{result_dir}/non_overlap_poster_preview')
final_code_by_section = {}
for section in sections:
final_code_by_section[section] = style_logs[section][-1]['code']
non_overlap_ckpt = {
'critic_logs': critic_logs,
'actor_logs': actor_logs,
'img_logs': img_logs,
'name_to_hierarchy': name_to_hierarchy,
'final_code': final_code,
'final_code_by_section': final_code_by_section,
'total_input_token': total_input_token,
'total_output_token': total_output_token
}
pkl.dump(non_overlap_ckpt, open(f'checkpoints/{args.model_name}_{args.poster_name}_non_overlap_ckpt_{args.index}.pkl', 'wb'))
return total_input_token, total_output_token
if __name__ == '__main__':
parser = argparse.ArgumentParser()
parser.add_argument('--poster_name', type=str, default=None)
parser.add_argument('--model_name', type=str, default='4o')
parser.add_argument('--poster_path', type=str, required=True)
parser.add_argument('--index', type=int, default=0)
parser.add_argument('--max_retry', type=int, default=3)
args = parser.parse_args()
actor_config = get_agent_config(args.model_name)
critic_config = get_agent_config(args.model_name)
if args.poster_name is None:
args.poster_name = args.poster_path.split('/')[-1].replace('.pdf', '').replace(' ', '_')
input_token, output_token = deoverflow(args, actor_config, critic_config)
print(f'Token consumption: {input_token} -> {output_token}') |