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313d10b
1
Parent(s):
516364e
gemini recreate merge balance tool
Browse files
README.md
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@@ -11,3 +11,29 @@ short_description: Набор инструментов для баланса м
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---
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Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
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---
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Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
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Задача сделать тулзу для удобной работы с балансом мердж-2 игры.
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1) Одна из основных фичей тулзы это Симуляция работы Генератора Заказов на базе конфигов с его правилами и конфигов мердж-цепочек. На выходе мы получаем таблицу с данными по симуляции и небольшой текстовый файл с сводными данными.
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2) В этой тулзе также можно менять параметры разных мердж конфигов - опять же если нужно протестировать значения. Значит важно чтобы мы могли загружать оригинальные файлы конфигов (.asset) и в интерфейсе удобно автоматически раскладывать их по типу и сразу исключая лишние данные (например ключи переводов и тд) - оставлять только важные параметры влияющие на баланс игры.
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3) Расчет стоимости предметов мердж цепочки исходя из весов предметов требуемых для производства других уровней предметов цепочки выпадающих из спавнеров.
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MergeOrderSimulationService - проверенный, рабочий в юнити симулятор генератора заказов который нам нужно переписать под новый инструмент.
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MergeChainCostCalculator - инструмент для расчета стоимости в энергии предметов мердж цепочек. Скрипт пока не работает должным образом. Хорошо если мы его починим для нашего инструмента.
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Далее.
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Наша задача взять все эти данные, сделать анализ конфигов для импорта, забрать наработки, сделать удобный интерфейс и произвести стабильный расширяемый при необходимости инструмент для балансировки игровых механик.
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Я хочу, чтобы инструмент был сделан реализован на библиотеке и компонентах gradio.app на python.
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app.py
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import gradio as gr
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import gradio as gr
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import pandas as pd
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import yaml
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import io
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import random
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from collections import deque
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# HELPER FUNCTIONS TO PARSE .asset FILES
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def parse_asset_file(file):
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"""Parses a YAML-like .asset file, skipping the initial %YAML and %TAG lines."""
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if file is None:
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return None
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try:
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content = file.decode('utf-8')
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# Find the first '---' which indicates the start of the YAML document
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yaml_start = content.find('---')
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if yaml_start == -1:
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raise ValueError("Not a valid Unity .asset file (missing '---')")
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# Clean up the content for standard YAML parsing
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yaml_content = content[yaml_start:]
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# Remove the MonoBehaviour header which is not valid YAML
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lines = yaml_content.split('\n')
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cleaned_lines = [line for line in lines if not line.strip().startswith('MonoBehaviour:')]
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cleaned_yaml = '\n'.join(cleaned_lines)
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# The file seems to have a custom serialization format within 'serializationData'.
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# For now, we will parse the main structure.
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# A more robust solution might need a dedicated parser for Unity's format.
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# Let's try to parse the main body first
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data = yaml.safe_load(io.StringIO(cleaned_yaml))
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# A simplified approach to extract key-value pairs for now
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# This will need to be much more robust based on the actual file structure.
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config_data = {}
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for line in content.split('\n'):
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if ':' in line:
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parts = line.split(':', 1)
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key = parts[0].strip()
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value = parts[1].strip()
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if key.startswith('_'):
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config_data[key] = value
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return config_data, data
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except Exception as e:
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print(f"Error parsing file: {e}")
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return None, None
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# --- SIMULATION LOGIC ---
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def run_simulation_logic(ruleset_file, chain_files, iteration_count, initial_energy):
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"""
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This function will contain the Python port of the C# MergeOrderSimulationService.
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For now, it returns placeholder data.
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"""
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# Placeholder for parsed ruleset
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ruleset_id = "ruleset_placeholder"
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# Placeholder for selected chain IDs
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selected_chain_ids = [f"chain_{i}" for i in range(len(chain_files))]
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# --- This is where the core simulation logic will go ---
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# We will replicate the steps from MergeOrderSimulationService.cs:
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# 1. Get all available items from selected chains.
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# 2. Apply MergeBoardItemFinder simulation.
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# 3. Filter by unlock level.
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# 4. Filter recently used items.
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# 5. Generate order with proper difficulty.
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# 6. Update history.
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# 7. Calculate costs and rewards.
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# 8. Store data for CSV.
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# For now, let's generate some dummy data to show in the UI
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sim_data = []
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current_energy = initial_energy
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difficulty_history = deque(maxlen=5) # Assuming max history of 5 from ruleset
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for i in range(iteration_count):
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req1 = f"merge_item_wood_branch_{random.randint(1, 3)}"
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req2 = f"merge_item_stones_stones_{random.randint(1, 2)}" if random.random() > 0.5 else ""
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energy_cost = random.randint(5, 20)
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current_energy -= energy_cost
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total_difficulty = random.randint(500, 2000)
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difficulty_history.append(total_difficulty)
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sim_data.append({
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"Order": i + 1,
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"MEnergy_Price": energy_cost,
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"MEnergy_Amount": current_energy,
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"Requirement_1": req1,
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"Weight_1": random.randint(50, 150),
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"ChainId_1": "orders_merge_wood",
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"Level_1": int(req1.split('_')[-1]),
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"Requirement_2": req2,
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"Weight_2": random.randint(75, 125) if req2 else 0,
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"ChainId_2": "merge_stones" if req2 else "",
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"Level_2": int(req2.split('_')[-1]) if req2 else 0,
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"Total_Difficulty": total_difficulty,
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"Adjusted_Difficulty": total_difficulty + sum(list(difficulty_history)[:-1]),
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})
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df = pd.DataFrame(sim_data)
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# Placeholder for statistics report
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stats_report = f"""
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SIMULATION STATISTICS
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=====================
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Total Orders Generated: {iteration_count}
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Average Difficulty: {df['Total_Difficulty'].mean():.2f}
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Item Frequency (Top 5):
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{df['Requirement_1'].value_counts().head(5).to_string()}
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"""
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return df, stats_report, "simulation_results.csv", "simulation_stats.txt"
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def run_simulation_interface(ruleset_file, chain_files, iteration_count, initial_energy):
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if not ruleset_file or not chain_files:
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raise gr.Error("Пожалуйста, загрузите файл правил и хотя бы один файл цепочки.")
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df, stats_report, df_path, report_path = run_simulation_logic(
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ruleset_file, chain_files, iteration_count, initial_energy
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)
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# Convert DataFrame to a downloadable CSV file
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csv_buffer = io.StringIO()
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df.to_csv(csv_buffer, index=False)
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csv_bytes = csv_buffer.getvalue().encode('utf-8')
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return df, stats_report, gr.File.update(value=csv_bytes, visible=True, name=df_path), gr.File.update(value=stats_report.encode('utf-8'), visible=True, name=report_path)
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# --- COST CALCULATION LOGIC ---
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def run_cost_calculation_logic(chain_files, item_files):
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"""
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This function will contain the Python port of the C# MergeChainCostCalculator.
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For now, it returns placeholder data.
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"""
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# --- This is where the core cost calculation logic will go ---
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# We will replicate the steps from MergeChainCostCalculator.cs:
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# 1. Load and parse all merge chain and item configs.
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# 2. For each chain, find its associated producer (spawner).
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# 3. For each item in the chain, calculate the expected number of attempts to get it.
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# 4. Calculate the final energy cost (expected attempts * spawn cost).
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# 5. Handle dynamic weights (IncWeight).
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# Dummy data for now
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cost_data = []
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for i, chain_file in enumerate(chain_files):
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chain_id = f"chain_{i+1}"
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for level in range(1, 7):
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cost_data.append({
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"Chain ID": chain_id,
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"Item ID": f"{chain_id}_item_{level}",
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"Level": level,
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"Producer ID": f"spawner_{i+1}",
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"Spawn Cost": 5,
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"Weight": 100 - (level * 10),
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"Inc Weight": 0,
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"Expected Attempts": 1.0 + (level * 0.5),
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"Energy Cost": (1.0 + (level * 0.5)) * 5,
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"Warning": ""
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})
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df = pd.DataFrame(cost_data)
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return df
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def run_cost_calculation_interface(chain_files, item_files):
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if not chain_files or not item_files:
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raise gr.Error("Пожалуйста, загрузите файлы цепочек и предметов.")
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df = run_cost_calculation_logic(chain_files, item_files)
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return df
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# --- CONFIG EDITOR LOGIC ---
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def view_config_file(file):
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if file is None:
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return "Загрузите файл для просмотра.", ""
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raw_content = file.decode('utf-8')
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# A simple display of the raw content.
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# In a real scenario, we would parse this into editable components.
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return raw_content, os.path.basename(file.name)
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# --- GRADIO UI ---
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with gr.Blocks(theme=gr.themes.Soft(), title="Инструмент Балансировки Merge-2") as demo:
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gr.Markdown("# Инструмент для Балансировки Игр Merge-2")
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with gr.Tabs():
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# --- SIMULATION TAB ---
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with gr.TabItem("Симуляция генератора заказов"):
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| 192 |
+
gr.Markdown("## Симуляция генератора заказов\nЗагрузите конфиги и запустите симуляцию для получения данных по генерации заказов.")
|
| 193 |
+
with gr.Row():
|
| 194 |
+
with gr.Column(scale=1):
|
| 195 |
+
sim_ruleset_upload = gr.File(label="Загрузить Ruleset (.asset)")
|
| 196 |
+
sim_chains_upload = gr.File(label="Загрузить файлы цепочек (.asset)", file_count="multiple")
|
| 197 |
+
sim_iterations = gr.Slider(10, 1000, value=100, step=10, label="Количество итераций")
|
| 198 |
+
sim_initial_energy = gr.Number(value=10000, label="Начальное количество энергии")
|
| 199 |
+
sim_run_button = gr.Button("Запустить симуляцию", variant="primary")
|
| 200 |
+
with gr.Column(scale=3):
|
| 201 |
+
gr.Markdown("### Результаты симуляции")
|
| 202 |
+
sim_results_df = gr.DataFrame(label="Данные по заказам")
|
| 203 |
+
gr.Markdown("### Сводный отчет")
|
| 204 |
+
sim_stats_report = gr.Textbox(label="Статистика", lines=10)
|
| 205 |
+
with gr.Row():
|
| 206 |
+
sim_download_csv = gr.File(label="Скачать CSV", visible=False)
|
| 207 |
+
sim_download_report = gr.File(label="Скачать отчет", visible=False)
|
| 208 |
+
|
| 209 |
+
# --- COST CALCULATION TAB ---
|
| 210 |
+
with gr.TabItem("Расчет стоимости цепочек"):
|
| 211 |
+
gr.Markdown("## Расчет стоимости предметов\nЗагрузите конфиги цепочек и спавнеров для расчета стоимости производства предметов в энергии.")
|
| 212 |
+
with gr.Row():
|
| 213 |
+
with gr.Column(scale=1):
|
| 214 |
+
cost_chains_upload = gr.File(label="Загрузить файлы цепочек (.asset)", file_count="multiple")
|
| 215 |
+
cost_items_upload = gr.File(label="Загрузить файлы спавнеров/предметов (.asset)", file_count="multiple")
|
| 216 |
+
cost_run_button = gr.Button("Рассчитать стоимость", variant="primary")
|
| 217 |
+
with gr.Column(scale=3):
|
| 218 |
+
gr.Markdown("### Рассчитанная стоимость")
|
| 219 |
+
cost_results_df = gr.DataFrame(label="Стоимость предметов в энергии")
|
| 220 |
+
|
| 221 |
+
# --- CONFIG EDITOR TAB ---
|
| 222 |
+
with gr.TabItem("Редактор конфигов"):
|
| 223 |
+
gr.Markdown("## Редактор Конфигурационных Файлов\nЗагрузите файл для просмотра и редактирования его параметров.")
|
| 224 |
+
with gr.Row():
|
| 225 |
+
with gr.Column(scale=1):
|
| 226 |
+
config_upload = gr.File(label="Загрузить файл .asset для редактирования")
|
| 227 |
+
config_file_name = gr.Label(label="Выбранный файл")
|
| 228 |
+
with gr.Column(scale=2):
|
| 229 |
+
# For now, just a textbox. Could be replaced with dynamic fields.
|
| 230 |
+
config_content_viewer = gr.Textbox(label="Содержимое файла", lines=30, interactive=True)
|
| 231 |
+
config_save_button = gr.Button("Сохранить изменения (не реализовано)", interactive=False)
|
| 232 |
+
|
| 233 |
+
# --- Event Handlers ---
|
| 234 |
+
sim_run_button.click(
|
| 235 |
+
fn=run_simulation_interface,
|
| 236 |
+
inputs=[sim_ruleset_upload, sim_chains_upload, sim_iterations, sim_initial_energy],
|
| 237 |
+
outputs=[sim_results_df, sim_stats_report, sim_download_csv, sim_download_report]
|
| 238 |
+
)
|
| 239 |
+
|
| 240 |
+
cost_run_button.click(
|
| 241 |
+
fn=run_cost_calculation_interface,
|
| 242 |
+
inputs=[cost_chains_upload, cost_items_upload],
|
| 243 |
+
outputs=[cost_results_df]
|
| 244 |
+
)
|
| 245 |
+
|
| 246 |
+
config_upload.upload(
|
| 247 |
+
fn=lambda x: x.name if x else "",
|
| 248 |
+
inputs=config_upload,
|
| 249 |
+
outputs=config_file_name
|
| 250 |
+
)
|
| 251 |
+
|
| 252 |
+
config_upload.upload(
|
| 253 |
+
fn=lambda file: file.decode('utf-8') if file else "",
|
| 254 |
+
inputs=config_upload,
|
| 255 |
+
outputs=config_content_viewer
|
| 256 |
+
)
|
| 257 |
+
|
| 258 |
+
|
| 259 |
+
if __name__ == "__main__":
|
| 260 |
+
demo.launch()
|