迁移了选题模块
This commit is contained in:
parent
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commit
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@ -5,12 +5,14 @@
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"""
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import os
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import sys
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import traceback
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# 添加项目根目录到Python路径
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sys.path.append(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
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# 导入所需模块
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from main import load_config, generate_topics_step
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from main import load_config
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from utils.tweet_generator import run_topic_generation_pipeline
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if __name__ == "__main__":
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print("==== 阶段 1: 仅生成选题 ====")
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@ -24,7 +26,7 @@ if __name__ == "__main__":
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# 2. 执行选题生成
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print("\n执行选题生成...")
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run_id, tweet_topic_record = generate_topics_step(config)
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run_id, tweet_topic_record = run_topic_generation_pipeline(config)
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if run_id and tweet_topic_record:
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output_dir = config.get("output_dir", "./result")
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@ -40,6 +42,5 @@ if __name__ == "__main__":
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except Exception as e:
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print(f"\n处理过程中出错: {e}")
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import traceback
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traceback.print_exc()
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sys.exit(1)
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@ -13,6 +13,8 @@ sys.path.append(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
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# 导入所需模块
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from main import load_config, generate_topics_step, generate_content_and_posters_step
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from utils.tweet_generator import run_topic_generation_pipeline
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from core.topic_parser import TopicParser
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def test_full_workflow():
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"""测试完整的工作流程，从选题生成到海报制作"""
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@ -26,7 +28,7 @@ def test_full_workflow():
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# 2. 执行选题生成
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print("\n步骤 2: 生成选题...")
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run_id, tweet_topic_record = generate_topics_step(config)
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run_id, tweet_topic_record = run_topic_generation_pipeline(config)
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if not run_id or not tweet_topic_record:
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print("选题生成失败，测试终止。")
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@ -84,7 +86,7 @@ def test_steps_separately():
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# 2. 仅执行选题生成
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print("\n步骤 2: 仅测试选题生成...")
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run_id, tweet_topic_record = generate_topics_step(test_config)
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run_id, tweet_topic_record = run_topic_generation_pipeline(test_config)
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if not run_id or not tweet_topic_record:
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print("选题生成失败，测试终止。")
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@ -104,7 +106,6 @@ def test_steps_separately():
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# 这部分通常是由main函数中的流程自动处理的
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# 这里为了演示分段流程，模拟手动加载数据并处理
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from core.topic_parser import TopicParser
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if os.path.exists(topics_file):
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with open(topics_file, 'r', encoding='utf-8') as f:
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142
main.py
142
main.py
@ -7,15 +7,15 @@ import traceback
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import json
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from core.ai_agent import AI_Agent
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from core.topic_parser import TopicParser
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# from core.topic_parser import TopicParser # No longer needed directly in main?
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import core.contentGen as contentGen
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import core.posterGen as posterGen
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import core.simple_collage as simple_collage
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from utils.resource_loader import ResourceLoader
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from utils.tweet_generator import prepare_topic_generation, generate_topics, generate_single_content
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from utils.tweet_generator import generate_single_content, run_topic_generation_pipeline # Import the new pipeline function
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import random
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TEXT_POSBILITY = 0.3
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TEXT_POSBILITY = 0.3 # Consider moving this to config if it varies
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def load_config(config_path="poster_gen_config.json"):
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"""Loads configuration from a JSON file."""
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@ -29,8 +29,8 @@ def load_config(config_path="poster_gen_config.json"):
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# Basic validation (can be expanded)
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required_keys = ["api_url", "model", "api_key", "resource_dir", "prompts_dir", "output_dir", "num", "variants", "topic_system_prompt", "topic_user_prompt", "content_system_prompt", "image_base_dir"]
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if not all(key in config for key in required_keys):
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print(f"Error: Config file '{config_path}' is missing one or more required keys.")
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print(f"Required keys are: {required_keys}")
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missing_keys = [key for key in required_keys if key not in config]
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print(f"Error: Config file '{config_path}' is missing required keys: {missing_keys}")
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sys.exit(1)
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# Resolve relative paths based on config location or a defined base path if necessary
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# For simplicity, assuming paths in config are relative to project root or absolute
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@ -42,35 +42,8 @@ def load_config(config_path="poster_gen_config.json"):
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print(f"Error loading configuration from '{config_path}': {e}")
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sys.exit(1)
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def generate_topics_step(config):
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"""Generates topics based on the configuration."""
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print("Step 1: Generating Topics...")
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ai_agent, system_prompt, user_prompt, base_output_dir = prepare_topic_generation(
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config.get("date", datetime.now().strftime("%Y-%m-%d")), # Use current date if not specified
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config["num"], config["topic_system_prompt"], config["topic_user_prompt"],
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config["api_url"], config["model"], config["api_key"], config["prompts_dir"],
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config["resource_dir"], config["output_dir"]
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)
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run_id, tweet_topic_record = generate_topics(
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ai_agent, system_prompt, user_prompt, config["output_dir"],
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config.get("topic_temperature", 0.2), config.get("topic_top_p", 0.5), config.get("topic_max_tokens", 1.5) # Added defaults for safety
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)
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if not run_id or not tweet_topic_record:
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print("Topic generation failed. Exiting.")
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ai_agent.close()
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return None, None
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output_dir = os.path.join(config["output_dir"], run_id)
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os.makedirs(output_dir, exist_ok=True)
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tweet_topic_record.save_topics(os.path.join(output_dir, "tweet_topic.json"))
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tweet_topic_record.save_prompt(os.path.join(output_dir, "tweet_prompt.txt"))
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ai_agent.close()
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print(f"Topics generated successfully. Run ID: {run_id}")
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return run_id, tweet_topic_record
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# Removed generate_topics_step function definition from here
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# Its logic is now in utils.tweet_generator.run_topic_generation_pipeline
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def generate_content_and_posters_step(config, run_id, tweet_topic_record):
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"""Generates content and posters based on generated topics."""
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@ -78,55 +51,75 @@ def generate_content_and_posters_step(config, run_id, tweet_topic_record):
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print("Missing run_id or topics data. Skipping content and poster generation.")
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return
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print("Step 2: Generating Content and Posters...")
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print("\nStep 2: Generating Content and Posters...")
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base_output_dir = config["output_dir"]
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output_dir = os.path.join(base_output_dir, run_id) # Directory for this specific run
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# Load content generation system prompt
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# --- Pre-load resources and initialize shared objects ---
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# Load content generation system prompt once
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content_system_prompt = ResourceLoader.load_system_prompt(config["content_system_prompt"])
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if not content_system_prompt:
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print("Warning: Content generation system prompt is empty. Using default logic if available or might fail.")
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# Potentially load topic system prompt as fallback if needed, or handle error
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# content_system_prompt = ResourceLoader.load_system_prompt(config["topic_system_prompt"])
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# Initialize AI Agent once for the entire content generation phase
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ai_agent = None
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try:
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print(f"Initializing AI Agent ({config['model']})...")
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ai_agent = AI_Agent(config["api_url"], config["model"], config["api_key"])
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except Exception as e:
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print(f"Error initializing AI Agent: {e}. Cannot proceed with content generation.")
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traceback.print_exc()
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return # Cannot continue without AI agent
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# Check image base directory
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image_base_dir = config.get("image_base_dir", None)
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if not image_base_dir:
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print("Error: 'image_base_dir' not specified in config. Cannot locate images.")
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if not image_base_dir or not os.path.isdir(image_base_dir):
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print(f"Error: 'image_base_dir' ({image_base_dir}) not specified or not a valid directory in config. Cannot locate images.")
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if ai_agent: ai_agent.close() # Close agent if initialized
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return
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camera_image_subdir = config.get("camera_image_subdir", "相机") # Default '相机'
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modify_image_subdir = config.get("modify_image_subdir", "modify") # Default 'modify'
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# Initialize ContentGenerator and PosterGenerator once if they are stateless
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# Assuming they are stateless for now
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content_gen = contentGen.ContentGenerator()
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poster_gen_instance = posterGen.PosterGenerator()
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# --- Process each topic ---
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for i, topic in enumerate(tweet_topic_record.topics_list):
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topic_index = i + 1
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print(f"Processing Topic {topic_index}/{len(tweet_topic_record.topics_list)}: {topic.get('title', 'N/A')}")
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print(f"\nProcessing Topic {topic_index}/{len(tweet_topic_record.topics_list)}: {topic.get('title', 'N/A')}")
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tweet_content_list = []
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# --- Content Generation Loop ---
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# --- Content Generation Loop (using the single AI Agent) ---
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for j in range(config["variants"]):
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variant_index = j + 1
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print(f" Generating Variant {variant_index}/{config['variants']}...")
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time.sleep(random.random()) # Keep the random delay? Okay for now.
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ai_agent = AI_Agent(config["api_url"], config["model"], config["api_key"])
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time.sleep(random.random() * 0.5) # Slightly reduced delay
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try:
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# Use the pre-initialized AI Agent
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tweet_content, gen_result = generate_single_content(
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ai_agent, content_system_prompt, topic,
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config["prompts_dir"], config["resource_dir"],
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output_dir, run_id, topic_index, variant_index, config.get("content_temperature", 0.3) # Added default
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output_dir, run_id, topic_index, variant_index, config.get("content_temperature", 0.3)
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)
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if tweet_content:
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tweet_content_list.append(tweet_content.get_json_file()) # Assuming this returns the structured data needed later
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# Assuming get_json_file() returns a dictionary or similar structure
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tweet_content_data = tweet_content.get_json_file()
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if tweet_content_data:
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tweet_content_list.append(tweet_content_data)
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else:
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print(f" Warning: generate_single_content for Topic {topic_index}, Variant {variant_index} returned empty data.")
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else:
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print(f" Failed to generate content for Topic {topic_index}, Variant {variant_index}. Skipping.")
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except Exception as e:
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print(f" Error during content generation for Topic {topic_index}, Variant {variant_index}: {e}")
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traceback.print_exc()
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finally:
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ai_agent.close() # Ensure agent is closed
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# Decide if traceback is needed here, might be too verbose for loop errors
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# traceback.print_exc()
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# Do NOT close the agent here
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if not tweet_content_list:
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print(f" No content generated for Topic {topic_index}. Skipping poster generation.")
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print(f" No valid content generated for Topic {topic_index}. Skipping poster generation.")
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continue
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# --- Poster Generation Setup ---
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@ -137,21 +130,22 @@ def generate_content_and_posters_step(config, run_id, tweet_topic_record):
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# Clean object name (consider making this a utility function)
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try:
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object_name = object_name.split(".")[0]
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if "景点信息-" in object_name:
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object_name = object_name.split("景点信息-")[1]
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# Handle cases like "景点A+景点B"? Needs clearer logic if required.
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# More robust cleaning might be needed depending on actual object name formats
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object_name_cleaned = object_name.split(".")[0].replace("景点信息-", "").strip()
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if not object_name_cleaned:
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print(f" Warning: Object name '{object_name}' resulted in empty string after cleaning.")
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continue
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object_name = object_name_cleaned
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except Exception as e:
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print(f" Warning: Could not fully clean object name '{object_name}': {e}")
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# Continue with potentially unclean name? Or skip?
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# Let's continue for now, path checks below might catch issues.
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# Construct and check image paths using config base dir
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# Path for collage/poster input images (e.g., from 'modify' dir)
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input_img_dir_path = os.path.join(image_base_dir, modify_image_subdir, object_name)
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# Path for potential description file (e.g., from '相机' dir)
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camera_img_dir_path = os.path.join(image_base_dir, camera_image_subdir, object_name)
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description_file_path = os.path.join(camera_img_dir_path, "description.txt")
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if not os.path.exists(input_img_dir_path) or not os.path.isdir(input_img_dir_path):
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print(f" Image directory not found or not a directory: '{input_img_dir_path}'. Skipping poster generation for this topic.")
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continue
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@ -164,21 +158,22 @@ def generate_content_and_posters_step(config, run_id, tweet_topic_record):
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print(f" Description file not found: '{description_file_path}'. Using generated content for poster text.")
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# --- Generate Text Configurations for Posters ---
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content_gen = contentGen.ContentGenerator()
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try:
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# Assuming tweet_content_list contains the JSON data needed by content_gen.run
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# Pass the list of content data directly
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poster_text_configs_raw = content_gen.run(info_directory, config["variants"], tweet_content_list)
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print(f" Raw poster text configs: {poster_text_configs_raw}") # For debugging
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# print(f" Raw poster text configs: {poster_text_configs_raw}") # For debugging
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if not poster_text_configs_raw:
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print(" Warning: ContentGenerator returned empty configuration data.")
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continue # Skip if no text configs generated
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poster_config_summary = posterGen.PosterConfig(poster_text_configs_raw)
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except Exception as e:
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print(f" Error running ContentGenerator or parsing poster configs: {e}")
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traceback.print_exc()
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continue # Skip poster generation for this topic
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# --- Poster Generation Loop ---
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poster_num = config["variants"] # Same as content variants
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target_size = tuple(config.get("poster_target_size", [900, 1200])) # Add default size
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target_size = tuple(config.get("poster_target_size", [900, 1200]))
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for j_index in range(poster_num):
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variant_index = j_index + 1
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@ -202,7 +197,6 @@ def generate_content_and_posters_step(config, run_id, tweet_topic_record):
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output_count=1, # Assuming 1 collage image per poster variant
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output_dir=collage_output_dir
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)
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# print(f" Collage image list: {img_list}") # Debugging
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if not img_list or len(img_list) == 0 or not img_list[0].get('path'):
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print(f" Failed to generate collage image for Variant {variant_index}. Skipping poster.")
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@ -210,24 +204,18 @@ def generate_content_and_posters_step(config, run_id, tweet_topic_record):
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collage_img_path = img_list[0]['path']
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print(f" Using collage image: {collage_img_path}")
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# --- Create Poster ---
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poster_gen_instance = posterGen.PosterGenerator() # Renamed to avoid conflict
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# Prepare text data (Simplified logic, adjust TEXT_POSBILITY if needed)
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# Consider moving text data preparation into posterGen or a dedicated function
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# --- Create Poster (using the single poster_gen_instance) ---
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text_data = {
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"title": poster_config.get('main_title', 'Default Title'),
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"subtitle": "", # Subtitle seems unused?
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"subtitle": "",
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"additional_texts": []
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}
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texts = poster_config.get('texts', [])
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if texts:
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text_data["additional_texts"].append({"text": texts[0], "position": "bottom", "size_factor": 0.5})
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if len(texts) > 1 and random.random() < TEXT_POSBILITY: # Apply possibility check
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if len(texts) > 1 and random.random() < TEXT_POSBILITY:
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text_data["additional_texts"].append({"text": texts[1], "position": "bottom", "size_factor": 0.5})
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# print(f" Text data for poster: {text_data}") # Debugging
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final_poster_path = os.path.join(poster_output_dir, "poster.jpg")
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result_path = poster_gen_instance.create_poster(collage_img_path, text_data, final_poster_path)
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if result_path:
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@ -240,13 +228,21 @@ def generate_content_and_posters_step(config, run_id, tweet_topic_record):
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traceback.print_exc()
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continue # Continue to next variant
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# --- Cleanup ---
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# Close the AI Agent after processing all topics
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if ai_agent:
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print("\nClosing AI Agent...")
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ai_agent.close()
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def main():
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# No argparse for now, directly load default config
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config = load_config() # Load from poster_gen_config.json
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# Execute steps sequentially
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run_id, tweet_topic_record = generate_topics_step(config)
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# Step 1: Generate Topics (using the function from utils.tweet_generator)
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run_id, tweet_topic_record = run_topic_generation_pipeline(config)
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# Step 2: Generate Content and Posters (if Step 1 was successful)
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if run_id and tweet_topic_record:
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generate_content_and_posters_step(config, run_id, tweet_topic_record)
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else:
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@ -8,6 +8,7 @@ import argparse
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import json
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from datetime import datetime
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import sys
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import traceback
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sys.path.append('/root/autodl-tmp')
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# 从本地模块导入
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from TravelContentCreator.core.ai_agent import AI_Agent
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@ -259,6 +260,67 @@ def prepare_topic_generation(
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return ai_agent, system_prompt, user_prompt, output_dir
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def run_topic_generation_pipeline(config):
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"""Runs the complete topic generation pipeline based on the configuration."""
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print("Step 1: Generating Topics...")
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# Prepare necessary inputs and the AI agent for topic generation
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# Note: prepare_topic_generation already initializes an AI_Agent
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try:
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ai_agent, system_prompt, user_prompt, base_output_dir = prepare_topic_generation(
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config.get("date", datetime.now().strftime("%Y-%m-%d")), # Use current date if not specified
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config["num"], config["topic_system_prompt"], config["topic_user_prompt"],
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config["api_url"], config["model"], config["api_key"], config["prompts_dir"],
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config["resource_dir"], config["output_dir"]
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)
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except Exception as e:
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print(f"Error during topic generation preparation: {e}")
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traceback.print_exc()
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return None, None
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# Generate topics using the prepared agent and prompts
|
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try:
|
||||
run_id, tweet_topic_record = generate_topics(
|
||||
ai_agent, system_prompt, user_prompt, config["output_dir"],
|
||||
config.get("topic_temperature", 0.2),
|
||||
config.get("topic_top_p", 0.5),
|
||||
config.get("topic_max_tokens", 1.5) # Consider if max_tokens name is accurate here (was presence_penalty?)
|
||||
)
|
||||
except Exception as e:
|
||||
print(f"Error during topic generation API call: {e}")
|
||||
traceback.print_exc()
|
||||
if ai_agent: ai_agent.close() # Ensure agent is closed on error
|
||||
return None, None
|
||||
|
||||
# Ensure the AI agent is closed after generation
|
||||
if ai_agent:
|
||||
ai_agent.close()
|
||||
|
||||
# Process results
|
||||
if not run_id or not tweet_topic_record:
|
||||
print("Topic generation failed (no run_id or topics returned).")
|
||||
return None, None
|
||||
|
||||
output_dir = os.path.join(config["output_dir"], run_id)
|
||||
try:
|
||||
os.makedirs(output_dir, exist_ok=True)
|
||||
# Save topics and prompt details
|
||||
save_topics_success = tweet_topic_record.save_topics(os.path.join(output_dir, "tweet_topic.json"))
|
||||
save_prompt_success = tweet_topic_record.save_prompt(os.path.join(output_dir, "tweet_prompt.txt"))
|
||||
if not save_topics_success or not save_prompt_success:
|
||||
print("Warning: Failed to save topic generation results or prompts.")
|
||||
# Continue but warn user
|
||||
|
||||
except Exception as e:
|
||||
print(f"Error saving topic generation results: {e}")
|
||||
traceback.print_exc()
|
||||
# Return the generated data even if saving fails, but maybe warn more strongly?
|
||||
# return run_id, tweet_topic_record # Decide if partial success is okay
|
||||
return None, None # Or consider failure if saving is critical
|
||||
|
||||
print(f"Topics generated successfully. Run ID: {run_id}")
|
||||
return run_id, tweet_topic_record
|
||||
|
||||
def main():
|
||||
"""主函数入口"""
|
||||
config_file = {
|
||||
|
||||
Loading…
x
Reference in New Issue
Block a user