From 67722a5c721c7c32c372b0dbfaadfc87e3da50b9 Mon Sep 17 00:00:00 2001 From: jinye_huang Date: Tue, 22 Apr 2025 18:14:31 +0800 Subject: [PATCH] =?UTF-8?q?=E4=BF=AE=E6=94=B9=E4=BA=86=E6=95=B0=E6=8D=AE?= =?UTF-8?q?=E4=BA=A4=E4=BA=92=E4=BC=A0=E9=80=92=E6=96=B9=E5=BC=8F,=20?= =?UTF-8?q?=E7=8E=B0=E5=9C=A8=E6=9B=B4=E9=80=82=E5=90=88API=E5=B0=81?= =?UTF-8?q?=E8=A3=85=E8=B0=83=E7=94=A8=E4=BA=86?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- README.md | 30 +- core/__pycache__/posterGen.cpython-312.pyc | Bin 31625 -> 30042 bytes .../simple_collage.cpython-312.pyc | Bin 29780 -> 30203 bytes core/posterGen.py | 166 ++--- core/simple_collage.py | 93 ++- main.py | 155 +++- .../output_handler.cpython-312.pyc | Bin 0 -> 10649 bytes .../prompt_manager.cpython-312.pyc | Bin 14257 -> 14384 bytes .../tweet_generator.cpython-312.pyc | Bin 33373 -> 28029 bytes utils/output_handler.py | 145 ++++ utils/prompt_manager.py | 78 +- utils/tweet_generator.py | 700 ++++++++---------- 12 files changed, 769 insertions(+), 598 deletions(-) create mode 100644 utils/__pycache__/output_handler.cpython-312.pyc create mode 100644 utils/output_handler.py diff --git a/README.md b/README.md index b414ef0..a040faf 100644 --- a/README.md +++ b/README.md @@ -237,9 +237,9 @@ finally: **注意：** 如果你只需要最终的完整结果而不需要流式处理，可以直接调用 `ai_agent.work(...)` 方法，它会内部处理好拼接并直接返回结果字符串。 -### Planned Refactoring: Decoupling Generation and Output Handling +### Refactoring Complete: Decoupling Generation and Output Handling -To enhance the flexibility and extensibility of this tool, we are planning a refactoring effort to separate the core content/image generation logic from the output handling (currently, saving results to the local filesystem). +To enhance the flexibility and extensibility of this tool, a refactoring effort has been completed to separate the core content/image generation logic from the output handling (previously, saving results directly to the local filesystem). **Motivation:** @@ -247,27 +247,29 @@ To enhance the flexibility and extensibility of this tool, we are planning a ref * **Alternative Storage:** Enable saving results to different backends like databases, cloud storage (e.g., S3, OSS), etc. * **Modularity:** Improve code structure by separating concerns. -**Approach:** +**Approach Taken:** -1. **Modify Core Functions:** Functions responsible for generating topics, content, and posters (primarily in `utils/tweet_generator.py` and potentially `core` modules) will be updated to **return** the generated data (e.g., Python dictionaries, lists, PIL Image objects, or image bytes) rather than directly writing files to the `./result` directory. -2. **Introduce Output Handlers:** An "Output Handler" pattern will be implemented. - * An abstract base class or interface (`OutputHandler`) will define methods for processing different types of results (topics, content, configurations, images). - * An initial concrete implementation (`FileSystemOutputHandler`) will replicate the current behavior of saving all results to the `./result/{run_id}/...` directory structure. -3. **Update Main Workflow:** The main script (`main.py`) will be modified to: - * Instantiate a specific `OutputHandler` (initially the `FileSystemOutputHandler`). - * Call the generation functions to get the data. - * Pass the returned data to the `OutputHandler` instance for processing (e.g., saving). +1. **Modified Core Functions:** Functions responsible for generating topics, content, and posters (primarily in `utils/tweet_generator.py`, `core/simple_collage.py`, `core/posterGen.py`) have been updated: + * Topic generation now returns the generated data (`run_id`, `topics_list`, prompts). + * Image generation functions (`simple_collage.process_directory`, `posterGen.create_poster`) now return PIL Image objects instead of saving files. + * Content and poster generation workflows accept an `OutputHandler` instance to process results (content JSON, prompts, configurations, image data) immediately after generation. +2. **Introduced Output Handlers:** An "Output Handler" pattern has been implemented (`utils/output_handler.py`). + * An abstract base class (`OutputHandler`) defines methods for processing different types of results. + * A concrete implementation (`FileSystemOutputHandler`) replicates the original behavior of saving all results to the `./result/{run_id}/...` directory structure. +3. **Updated Main Workflow:** The main script (`main.py`) now: + * Instantiates a specific `OutputHandler` (currently `FileSystemOutputHandler`). + * Calls the generation functions, passing the `OutputHandler` where needed. + * Uses the `OutputHandler` to process data returned by the topic generation step. +4. **Reduced Config Dependency:** Core logic functions (`PromptManager`, `generate_content_for_topic`, `generate_posters_for_topic`, etc.) now receive necessary configuration values as specific parameters rather than relying on the entire `config` dictionary, making them more independent and testable. **Future Possibilities:** -This refactoring will make it straightforward to add new output handlers in the future, such as: +This refactoring makes it straightforward to add new output handlers in the future, such as: * `ApiOutputHandler`: Formats results for API responses. * `DatabaseOutputHandler`: Stores results in a database. * `CloudStorageOutputHandler`: Uploads results (especially images) to cloud storage and potentially stores metadata elsewhere. -**(Note:** This refactoring is in progress. The current documentation reflects the existing file-saving behavior, but expect changes in how results are handled internally.) - ### 配置文件说明 (Configuration) 主配置文件为 `poster_gen_config.json` (可以复制 `example_config.json` 并修改)。主要包含以下部分： \ No newline at end of file diff --git a/core/__pycache__/posterGen.cpython-312.pyc b/core/__pycache__/posterGen.cpython-312.pyc index 8ae523a6d7be31742de5e079a56872870af5e1c8..910007a82d05fc1dc1b2326a059718f2340181c3 100644 GIT binary patch delta 4054 zcmZ`*eNbH06@PEP*pIic;rn9=kA!5|WLZ$e7&MSXJ`==zkhWY7a7lgikEv;D zzJ~rOqej;RoREV)lV_#Y1-~hJBG0Pgx6$+Y8x)bdV@( zO8D>1Dv&?^zrg6!o8g$V1Zae0Y}xw!-9KaOr(ey`fp zg|q_EXI6ft=J(O#t6b|m$d(X91VsZ<%y|t`D-rw%0fcUZ{Ro7XtS;r{=$_Rp^}2n? z>7&EthaC?A`HjXQ_OByDK=$YW9OBH`i|fen;{3*$k#*!q^v>Ik@I0aKRFv&tzSMyP z^Cgxf`44zWz#mh0NHVzx`HSw=;FS6Of87hA$N=4Z`|2DS$e7UO^>}=e%jfQgsG%od z{^;$O%=5nQsM(W6fo<2YK;8HT=o@QLu8Y1`^AI~1I}tg8Ow=$7|1hpqlf&@SQO?Gn ztBH?>Ygakkz$2{yH+ZB}C^C?Kw*Irwp=$Con9V-@6pmk4lLzTXwa@d9(7w8SzMno> 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str: + """Gets the specific directory for a run, creating it if necessary.""" + run_dir = os.path.join(self.base_output_dir, run_id) + os.makedirs(run_dir, exist_ok=True) + return run_dir + + def _get_variant_dir(self, run_id: str, topic_index: int, variant_index: int, subdir: str | None = None) -> str: + """Gets the specific directory for a variant, optionally within a subdirectory (e.g., 'poster'), creating it if necessary.""" + run_dir = self._get_run_dir(run_id) + variant_base_dir = os.path.join(run_dir, f"{topic_index}_{variant_index}") + target_dir = variant_base_dir + if subdir: + target_dir = os.path.join(variant_base_dir, subdir) + os.makedirs(target_dir, exist_ok=True) + return target_dir + + def handle_topic_results(self, run_id: str, topics_list: list, system_prompt: str, user_prompt: str): + run_dir = self._get_run_dir(run_id) + + # Save topics list + topics_path = os.path.join(run_dir, f"tweet_topic_{run_id}.json") + try: + with open(topics_path, "w", encoding="utf-8") as f: + json.dump(topics_list, f, ensure_ascii=False, indent=4) + logging.info(f"Topics list saved successfully to: {topics_path}") + except Exception as e: + logging.exception(f"Error saving topic JSON file to {topics_path}:") + + # Save prompts + prompt_path = os.path.join(run_dir, f"topic_prompt_{run_id}.txt") + try: + with open(prompt_path, "w", encoding="utf-8") as f: + f.write("--- SYSTEM PROMPT ---\n") + f.write(system_prompt + "\n\n") + f.write("--- USER PROMPT ---\n") + f.write(user_prompt + "\n") + logging.info(f"Topic prompts saved successfully to: {prompt_path}") + except Exception as e: + logging.exception(f"Error saving topic prompts file to {prompt_path}:") + + def handle_content_variant(self, run_id: str, topic_index: int, variant_index: int, content_data: dict, prompt_data: str): + """Saves content JSON and prompt for a specific variant.""" + variant_dir = self._get_variant_dir(run_id, topic_index, variant_index) + + # Save content JSON + content_path = os.path.join(variant_dir, "article.json") + try: + with open(content_path, "w", encoding="utf-8") as f: + json.dump(content_data, f, ensure_ascii=False, indent=4) + logging.info(f"Content JSON saved to: {content_path}") + except Exception as e: + logging.exception(f"Failed to save content JSON to {content_path}: {e}") + + # Save content prompt + prompt_path = os.path.join(variant_dir, "tweet_prompt.txt") + try: + with open(prompt_path, "w", encoding="utf-8") as f: + # Assuming prompt_data is the user prompt used for this variant + f.write(prompt_data + "\n") + logging.info(f"Content prompt saved to: {prompt_path}") + except Exception as e: + logging.exception(f"Failed to save content prompt to {prompt_path}: {e}") + + def handle_poster_configs(self, run_id: str, topic_index: int, config_data: list | dict): + """Saves the complete poster configuration list/dict for a topic.""" + run_dir = self._get_run_dir(run_id) + config_path = os.path.join(run_dir, f"topic_{topic_index}_poster_configs.json") + try: + with open(config_path, 'w', encoding='utf-8') as f_cfg_topic: + json.dump(config_data, f_cfg_topic, ensure_ascii=False, indent=4) + logging.info(f"Saved complete poster configurations for topic {topic_index} to: {config_path}") + except Exception as save_err: + logging.error(f"Failed to save complete poster configurations for topic {topic_index} to {config_path}: {save_err}") + + def handle_generated_image(self, run_id: str, topic_index: int, variant_index: int, image_type: str, image_data, output_filename: str): + """Saves a generated image (PIL Image) to the appropriate variant subdirectory.""" + subdir = None + if image_type == 'collage': + subdir = 'collage_img' # TODO: Make these subdir names configurable? + elif image_type == 'poster': + subdir = 'poster' + else: + logging.warning(f"Unknown image type '{image_type}'. Saving to variant root.") + subdir = None # Save directly in variant dir if type is unknown + + target_dir = self._get_variant_dir(run_id, topic_index, variant_index, subdir=subdir) + save_path = os.path.join(target_dir, output_filename) + + try: + # Assuming image_data is a PIL Image object based on posterGen/simple_collage + image_data.save(save_path) + logging.info(f"Saved {image_type} image to: {save_path}") + except Exception as e: + logging.exception(f"Failed to save {image_type} image to {save_path}: {e}") + + def finalize(self, run_id: str): + logging.info(f"FileSystemOutputHandler finalizing run: {run_id}. No specific actions needed.") + pass # Nothing specific to do for file system finalize \ No newline at end of file diff --git a/utils/prompt_manager.py b/utils/prompt_manager.py index 2a9fd2e..383fb69 100644 --- a/utils/prompt_manager.py +++ b/utils/prompt_manager.py @@ -12,49 +12,54 @@ from .resource_loader import ResourceLoader # Use relative import within the sam class PromptManager: """Handles the loading and construction of prompts.""" - def __init__(self, config): - """Initializes the PromptManager with the global configuration.""" - self.config = config - # Instantiate ResourceLoader once, assuming it's mostly static methods or stateless - self.resource_loader = ResourceLoader() + def __init__(self, + topic_system_prompt_path: str, + topic_user_prompt_path: str, + content_system_prompt_path: str, + prompts_dir: str, + resource_dir_config: list, + topic_gen_num: int = 1, # Default values if needed + topic_gen_date: str = "" + ): + self.topic_system_prompt_path = topic_system_prompt_path + self.topic_user_prompt_path = topic_user_prompt_path + self.content_system_prompt_path = content_system_prompt_path + self.prompts_dir = prompts_dir + self.resource_dir_config = resource_dir_config + self.topic_gen_num = topic_gen_num + self.topic_gen_date = topic_gen_date def get_topic_prompts(self): """Constructs the system and user prompts for topic generation.""" logging.info("Constructing prompts for topic generation...") try: # --- System Prompt --- - system_prompt_path = self.config.get("topic_system_prompt") - if not system_prompt_path: - logging.error("topic_system_prompt path not specified in config.") + if not self.topic_system_prompt_path: + logging.error("Topic system prompt path not provided during PromptManager initialization.") return None, None - - # Use ResourceLoader's static method directly - system_prompt = ResourceLoader.load_file_content(system_prompt_path) + system_prompt = ResourceLoader.load_file_content(self.topic_system_prompt_path) if not system_prompt: - logging.error(f"Failed to load topic system prompt from '{system_prompt_path}'.") + logging.error(f"Failed to load topic system prompt from '{self.topic_system_prompt_path}'.") return None, None # --- User Prompt --- - user_prompt_path = self.config.get("topic_user_prompt") - if not user_prompt_path: - logging.error("topic_user_prompt path not specified in config.") + if not self.topic_user_prompt_path: + logging.error("Topic user prompt path not provided during PromptManager initialization.") return None, None - - base_user_prompt = ResourceLoader.load_file_content(user_prompt_path) - if base_user_prompt is None: # Check for None explicitly - logging.error(f"Failed to load base topic user prompt from '{user_prompt_path}'.") + base_user_prompt = ResourceLoader.load_file_content(self.topic_user_prompt_path) + if base_user_prompt is None: + logging.error(f"Failed to load base topic user prompt from '{self.topic_user_prompt_path}'.") return None, None # --- Build the dynamic part of the user prompt (Logic moved from prepare_topic_generation) --- user_prompt_dynamic = "你拥有的创作资料如下：\n" # Add genPrompts directory structure - gen_prompts_path = self.config.get("prompts_dir") - if gen_prompts_path and os.path.isdir(gen_prompts_path): + if self.prompts_dir and os.path.isdir(self.prompts_dir): try: - gen_prompts_list = os.listdir(gen_prompts_path) + gen_prompts_list = os.listdir(self.prompts_dir) for gen_prompt_folder in gen_prompts_list: - folder_path = os.path.join(gen_prompts_path, gen_prompt_folder) + folder_path = os.path.join(self.prompts_dir, gen_prompt_folder) if os.path.isdir(folder_path): try: # List files, filter out subdirs if needed @@ -63,13 +68,12 @@ class PromptManager: except OSError as e: logging.warning(f"Could not list directory {folder_path}: {e}") except OSError as e: - logging.warning(f"Could not list base prompts directory {gen_prompts_path}: {e}") + logging.warning(f"Could not list base prompts directory {self.prompts_dir}: {e}") else: - logging.warning(f"Prompts directory '{gen_prompts_path}' not found or invalid.") + logging.warning(f"Prompts directory '{self.prompts_dir}' not found or invalid.") # Add resource directory contents - resource_dir_config = self.config.get("resource_dir", []) - for dir_info in resource_dir_config: + for dir_info in self.resource_dir_config: source_type = dir_info.get("type", "UnknownType") source_file_paths = dir_info.get("file_path", []) for file_path in source_file_paths: @@ -81,7 +85,7 @@ class PromptManager: logging.warning(f"Could not load resource file {file_path}") # Add dateline information (optional) - user_prompt_dir = os.path.dirname(user_prompt_path) + user_prompt_dir = os.path.dirname(self.topic_user_prompt_path) dateline_path = os.path.join(user_prompt_dir, "2025各月节日宣传节点时间表.md") # Consider making this configurable if os.path.exists(dateline_path): dateline_content = ResourceLoader.load_file_content(dateline_path) @@ -91,9 +95,7 @@ class PromptManager: # Combine dynamic part, base template, and final parameters user_prompt = user_prompt_dynamic + base_user_prompt - select_num = self.config.get("num", 1) # Default to 1 if not specified - select_date = self.config.get("date", "") - user_prompt += f"\n选题数量：{select_num}\n选题日期：{select_date}\n" + user_prompt += f"\n选题数量：{self.topic_gen_num}\n选题日期：{self.topic_gen_date}\n" # --- End of moved logic --- logging.info(f"Topic prompts constructed. System: {len(system_prompt)} chars, User: {len(user_prompt)} chars.") @@ -108,20 +110,18 @@ class PromptManager: logging.info(f"Constructing content prompts for topic: {topic_item.get('object', 'N/A')}...") try: # --- System Prompt --- - system_prompt_path = self.config.get("content_system_prompt") - if not system_prompt_path: - logging.error("content_system_prompt path not specified in config.") + if not self.content_system_prompt_path: + logging.error("Content system prompt path not provided during PromptManager initialization.") return None, None - # Use ResourceLoader's static method. load_system_prompt was just load_file_content. - system_prompt = ResourceLoader.load_file_content(system_prompt_path) + system_prompt = ResourceLoader.load_file_content(self.content_system_prompt_path) if not system_prompt: - logging.error(f"Failed to load content system prompt from '{system_prompt_path}'.") + logging.error(f"Failed to load content system prompt from '{self.content_system_prompt_path}'.") return None, None # --- User Prompt (Logic moved from ResourceLoader.build_user_prompt) --- user_prompt = "" - prompts_dir = self.config.get("prompts_dir") - resource_dir_config = self.config.get("resource_dir", []) + prompts_dir = self.prompts_dir + resource_dir_config = self.resource_dir_config if not prompts_dir or not os.path.isdir(prompts_dir): logging.warning(f"Prompts directory '{prompts_dir}' not found or invalid. Content user prompt might be incomplete.") diff --git a/utils/tweet_generator.py b/utils/tweet_generator.py index 7ca1ee6..a5f26aa 100644 --- a/utils/tweet_generator.py +++ b/utils/tweet_generator.py @@ -26,6 +26,7 @@ from utils.prompt_manager import PromptManager # Keep this as it's importing fro from core import contentGen as core_contentGen from core import posterGen as core_posterGen from core import simple_collage as core_simple_collage +from .output_handler import OutputHandler # <-- 添加导入 class tweetTopic: def __init__(self, index, date, logic, object, product, product_logic, style, style_logic, target_audience, target_audience_logic): @@ -41,60 +42,29 @@ class tweetTopic: self.target_audience_logic = target_audience_logic class tweetTopicRecord: - def __init__(self, topics_list, system_prompt, user_prompt, output_dir, run_id): + def __init__(self, topics_list, system_prompt, user_prompt, run_id): self.topics_list = topics_list self.system_prompt = system_prompt self.user_prompt = user_prompt - self.output_dir = output_dir self.run_id = run_id - def save_topics(self, path): - try: - with open(path, "w", encoding="utf-8") as f: - json.dump(self.topics_list, f, ensure_ascii=False, indent=4) - logging.info(f"Topics list successfully saved to {path}") # Change to logging - except Exception as e: - # Keep print for traceback, but add logging - logging.exception(f"保存选题失败到 {path}: {e}") # Log exception - # print(f"保存选题失败到 {path}: {e}") - # print("--- Traceback for save_topics error ---") - # traceback.print_exc() - # print("--- End Traceback ---") - return False - return True - - def save_prompt(self, path): - try: - with open(path, "w", encoding="utf-8") as f: - f.write(self.system_prompt + "\n") - f.write(self.user_prompt + "\n") - # f.write(self.output_dir + "\n") # Output dir not needed in prompt file? - # f.write(self.run_id + "\n") # run_id not needed in prompt file? - logging.info(f"Prompts saved to {path}") - except Exception as e: - logging.exception(f"保存提示词失败: {e}") - # print(f"保存提示词失败: {e}") - return False - return True - class tweetContent: - def __init__(self, result, prompt, output_dir, run_id, article_index, variant_index): + def __init__(self, result, prompt, run_id, article_index, variant_index): self.result = result self.prompt = prompt - self.output_dir = output_dir self.run_id = run_id self.article_index = article_index self.variant_index = variant_index try: self.title, self.content = self.split_content(result) - self.json_file = self.gen_result_json() + self.json_data = self.gen_result_json() except Exception as e: logging.error(f"Failed to parse AI result for {article_index}_{variant_index}: {e}") logging.debug(f"Raw result: {result[:500]}...") # Log partial raw result self.title = "[Parsing Error]" self.content = "[Failed to parse AI content]" - self.json_file = {"title": self.title, "content": self.content, "error": True, "raw_result": result} + self.json_data = {"title": self.title, "content": self.content, "error": True, "raw_result": result} def split_content(self, result): # Assuming split logic might still fail, keep it simple or improve with regex/json @@ -122,28 +92,19 @@ class tweetContent: "title": self.title, "content": self.content } + # Add error flag if it exists + if hasattr(self, 'json_data') and self.json_data.get('error'): + json_file['error'] = True + json_file['raw_result'] = self.json_data.get('raw_result') return json_file - def save_content(self, json_path): - try: - with open(json_path, "w", encoding="utf-8") as f: - # If parsing failed, save the error structure - json.dump(self.json_file, f, ensure_ascii=False, indent=4) - logging.info(f"Content JSON saved to: {json_path}") - except Exception as e: - logging.exception(f"Failed to save content JSON to {json_path}: {e}") - return None # Indicate failure - return json_path + def get_json_data(self): + """Returns the generated JSON data dictionary.""" + return self.json_data - def save_prompt(self, path): - try: - with open(path, "w", encoding="utf-8") as f: - f.write(self.prompt + "\n") - logging.info(f"Content prompt saved to: {path}") - except Exception as e: - logging.exception(f"Failed to save content prompt to {path}: {e}") - return None # Indicate failure - return path + def get_prompt(self): + """Returns the user prompt used to generate this content.""" + return self.prompt def get_content(self): return self.content @@ -151,12 +112,9 @@ class tweetContent: def get_title(self): return self.title - def get_json_file(self): - return self.json_file - -def generate_topics(ai_agent, system_prompt, user_prompt, output_dir, run_id, temperature=0.2, top_p=0.5, presence_penalty=1.5): - """生成选题列表 (run_id is now passed in)""" +def generate_topics(ai_agent, system_prompt, user_prompt, run_id, temperature=0.2, top_p=0.5, presence_penalty=1.5): + """生成选题列表 (run_id is now passed in, output_dir removed as argument)""" logging.info("Starting topic generation...") time_start = time.time() @@ -171,26 +129,20 @@ def generate_topics(ai_agent, system_prompt, user_prompt, output_dir, run_id, te result_list = TopicParser.parse_topics(result) if not result_list: logging.warning("Topic parsing resulted in an empty list.") - # Optionally save raw result here if parsing fails? - error_log_path = os.path.join(output_dir, run_id, f"topic_parsing_error_{run_id}.txt") - try: - os.makedirs(os.path.dirname(error_log_path), exist_ok=True) - with open(error_log_path, "w", encoding="utf-8") as f_err: - f_err.write("--- Topic Parsing Failed ---\n") - f_err.write(result) - logging.info(f"Saved raw AI output due to parsing failure to: {error_log_path}") - except Exception as log_err: - logging.error(f"Failed to save raw AI output on parsing failure: {log_err}") + # Optionally handle raw result logging here if needed, but saving is responsibility of OutputHandler + # error_log_path = os.path.join(output_dir, run_id, f"topic_parsing_error_{run_id}.txt") # output_dir is not available here + # try: + # # ... (save raw output logic) ... + # except Exception as log_err: + # logging.error(f"Failed to save raw AI output on parsing failure: {log_err}") - # Create record object (even if list is empty) - tweet_topic_record = tweetTopicRecord(result_list, system_prompt, user_prompt, output_dir, run_id) - - return tweet_topic_record # Return only the record + # 直接返回解析后的列表 + return result_list -def generate_single_content(ai_agent, system_prompt, user_prompt, item, output_dir, run_id, +def generate_single_content(ai_agent, system_prompt, user_prompt, item, run_id, article_index, variant_index, temperature=0.3, top_p=0.4, presence_penalty=1.5): - """生成单篇文章内容. Requires prompts to be passed in.""" + """Generates single content variant data. Returns (content_json, user_prompt) or (None, None).""" logging.info(f"Generating content for topic {article_index}, variant {variant_index}") try: if not system_prompt or not user_prompt: @@ -201,29 +153,37 @@ def generate_single_content(ai_agent, system_prompt, user_prompt, item, output_d time.sleep(random.random() * 0.5) - # Generate content (updated return values) + # Generate content (non-streaming work returns result, tokens, time_cost) result, tokens, time_cost = ai_agent.work( system_prompt, user_prompt, "", temperature, top_p, presence_penalty ) + if result is None: # Check if AI call failed + logging.error(f"AI agent work failed for {article_index}_{variant_index}. No result returned.") + return None, None + logging.info(f"Content generation for {article_index}_{variant_index} completed in {time_cost:.2f}s. Estimated tokens: {tokens}") - # --- Correct directory structure --- - run_specific_output_dir = os.path.join(output_dir, run_id) - variant_result_dir = os.path.join(run_specific_output_dir, f"{article_index}_{variant_index}") - os.makedirs(variant_result_dir, exist_ok=True) + # --- Create tweetContent object (handles parsing) --- + # Pass user_prompt instead of full prompt? Yes, user_prompt is what we need later. + tweet_content = tweetContent(result, user_prompt, run_id, article_index, variant_index) - # Create tweetContent object (handles potential parsing errors inside its __init__) - tweet_content = tweetContent(result, user_prompt, output_dir, run_id, article_index, variant_index) - - # Save content and prompt - content_save_path = os.path.join(variant_result_dir, "article.json") - prompt_save_path = os.path.join(variant_result_dir, "tweet_prompt.txt") - tweet_content.save_content(content_save_path) - tweet_content.save_prompt(prompt_save_path) - # logging.info(f" Saved article content to: {content_save_path}") # Already logged in save_content + # --- Remove Saving Logic --- + # run_specific_output_dir = os.path.join(output_dir, run_id) # output_dir no longer available + # variant_result_dir = os.path.join(run_specific_output_dir, f"{article_index}_{variant_index}") + # os.makedirs(variant_result_dir, exist_ok=True) + # content_save_path = os.path.join(variant_result_dir, "article.json") + # prompt_save_path = os.path.join(variant_result_dir, "tweet_prompt.txt") + # tweet_content.save_content(content_save_path) # Method removed + # tweet_content.save_prompt(prompt_save_path) # Method removed + # --- End Remove Saving Logic --- + + # Return the data needed by the output handler + content_json = tweet_content.get_json_data() + prompt_data = tweet_content.get_prompt() # Get the stored user prompt + + return content_json, prompt_data # Return data pair - return tweet_content, result # Return object and raw result except Exception as e: logging.exception(f"Error generating single content for {article_index}_{variant_index}:") return None, None @@ -256,7 +216,7 @@ def generate_content(ai_agent, system_prompt, topics, output_dir, run_id, prompt # 调用单篇文章生成函数 tweet_content, result = generate_single_content( - ai_agent, system_prompt, item, output_dir, run_id, i+1, j+1, temperature + ai_agent, system_prompt, item, run_id, i+1, j+1, temperature ) if tweet_content: @@ -270,207 +230,248 @@ def generate_content(ai_agent, system_prompt, topics, output_dir, run_id, prompt return processed_results -def prepare_topic_generation( - config # Pass the whole config dictionary now - # select_date, select_num, - # system_prompt_path, user_prompt_path, - # base_url="vllm", model_name="qwenQWQ", api_key="EMPTY", - # gen_prompts_path="/root/autodl-tmp/TravelContentCreator/genPrompts", - # resource_dir="/root/autodl-tmp/TravelContentCreator/resource", - # output_dir="/root/autodl-tmp/TravelContentCreator/result" -): - """准备选题生成的环境和参数. Returns agent and prompts.""" +def prepare_topic_generation(prompt_manager: PromptManager, + api_url: str, + model_name: str, + api_key: str, + timeout: int, + max_retries: int): + """准备选题生成的环境和参数. Returns agent, system_prompt, user_prompt. - # Initialize PromptManager - prompt_manager = PromptManager(config) - - # Get prompts using PromptManager + Args: + prompt_manager: An initialized PromptManager instance. + api_url, model_name, api_key, timeout, max_retries: Parameters for AI_Agent. + """ + logging.info("Preparing for topic generation (using provided PromptManager)...") + # 从传入的 PromptManager 获取 prompts system_prompt, user_prompt = prompt_manager.get_topic_prompts() if not system_prompt or not user_prompt: - print("Error: Failed to get topic generation prompts.") - return None, None, None, None + logging.error("Failed to get topic generation prompts from PromptManager.") + return None, None, None # Return three Nones - # 创建AI Agent (still create agent here for the topic generation phase) + # 使用传入的参数初始化 AI Agent try: logging.info("Initializing AI Agent for topic generation...") - # --- Read timeout/retry from config --- - request_timeout = config.get("request_timeout", 30) # Default 30 seconds - max_retries = config.get("max_retries", 3) # Default 3 retries - # --- Pass values to AI_Agent --- ai_agent = AI_Agent( - config["api_url"], - config["model"], - config["api_key"], - timeout=request_timeout, - max_retries=max_retries + api_url, # Use passed arg + model_name, # Use passed arg + api_key, # Use passed arg + timeout=timeout, # Use passed arg + max_retries=max_retries # Use passed arg ) except Exception as e: logging.exception("Error initializing AI Agent for topic generation:") - traceback.print_exc() - return None, None, None, None + return None, None, None # Return three Nones - # Removed prompt loading/building logic, now handled by PromptManager - - # Return agent and the generated prompts - return ai_agent, system_prompt, user_prompt, config["output_dir"] + # 返回 agent 和 prompts + return ai_agent, system_prompt, user_prompt def run_topic_generation_pipeline(config, run_id=None): - """Runs the complete topic generation pipeline based on the configuration.""" + """ + Runs the complete topic generation pipeline based on the configuration. + Returns: (run_id, topics_list, system_prompt, user_prompt) or (None, None, None, None) on failure. + """ logging.info("Starting Step 1: Topic Generation Pipeline...") - - # --- Handle run_id --- + if run_id is None: logging.info("No run_id provided, generating one based on timestamp.") run_id = datetime.now().strftime("%Y-%m-%d_%H-%M-%S") else: logging.info(f"Using provided run_id: {run_id}") - # --- End run_id handling --- - # Prepare necessary inputs and the AI agent for topic generation - ai_agent, system_prompt, user_prompt, base_output_dir = None, None, None, None + ai_agent, system_prompt, user_prompt = None, None, None # Initialize + topics_list = None + prompt_manager = None # Initialize prompt_manager try: - # Pass the config directly to prepare_topic_generation - ai_agent, system_prompt, user_prompt, base_output_dir = prepare_topic_generation(config) + # --- 读取 PromptManager 所需参数 --- + topic_sys_prompt_path = config.get("topic_system_prompt") + topic_user_prompt_path = config.get("topic_user_prompt") + content_sys_prompt_path = config.get("content_system_prompt") # 虽然这里不用，但 PromptManager 可能需要 + prompts_dir_path = config.get("prompts_dir") + resource_config = config.get("resource_dir", []) + topic_num = config.get("num", 1) + topic_date = config.get("date", "") + # --- 创建 PromptManager 实例 --- + prompt_manager = PromptManager( + topic_system_prompt_path=topic_sys_prompt_path, + topic_user_prompt_path=topic_user_prompt_path, + content_system_prompt_path=content_sys_prompt_path, + prompts_dir=prompts_dir_path, + resource_dir_config=resource_config, + topic_gen_num=topic_num, + topic_gen_date=topic_date + ) + logging.info("PromptManager instance created.") + + # --- 读取 AI Agent 所需参数 --- + ai_api_url = config.get("api_url") + ai_model = config.get("model") + ai_api_key = config.get("api_key") + ai_timeout = config.get("request_timeout", 30) + ai_max_retries = config.get("max_retries", 3) + + # 检查必需的 AI 参数是否存在 + if not all([ai_api_url, ai_model, ai_api_key]): + raise ValueError("Missing required AI configuration (api_url, model, api_key) in config.") + + # --- 调用修改后的 prepare_topic_generation --- + ai_agent, system_prompt, user_prompt = prepare_topic_generation( + prompt_manager, # Pass instance + ai_api_url, + ai_model, + ai_api_key, + ai_timeout, + ai_max_retries + ) if not ai_agent or not system_prompt or not user_prompt: raise ValueError("Failed to prepare topic generation (agent or prompts missing).") - except Exception as e: - logging.exception("Error during topic generation preparation:") - traceback.print_exc() - return None, None - - # Generate topics using the prepared agent and prompts - try: - # Pass the determined run_id to generate_topics - tweet_topic_record = generate_topics( - ai_agent, system_prompt, user_prompt, config["output_dir"], - run_id, # Pass the run_id + # --- Generate topics (保持不变) --- + topics_list = generate_topics( + ai_agent, system_prompt, user_prompt, + run_id, # Pass run_id config.get("topic_temperature", 0.2), config.get("topic_top_p", 0.5), config.get("topic_presence_penalty", 1.5) ) except Exception as e: - logging.exception("Error during topic generation API call:") - traceback.print_exc() - if ai_agent: ai_agent.close() # Ensure agent is closed on error - return None, None + logging.exception("Error during topic generation pipeline execution:") + # Ensure agent is closed even if generation fails mid-way + if ai_agent: ai_agent.close() + return None, None, None, None # Signal failure + finally: + # Ensure the AI agent is closed after generation attempt (if initialized) + if ai_agent: + logging.info("Closing topic generation AI Agent...") + ai_agent.close() - # Ensure the AI agent is closed after generation - if ai_agent: - logging.info("Closing topic generation AI Agent...") - ai_agent.close() + if topics_list is None: # Check if generate_topics returned None (though it currently returns list) + logging.error("Topic generation failed (generate_topics returned None or an error occurred).") + return None, None, None, None + elif not topics_list: # Check if list is empty + logging.warning(f"Topic generation completed for run {run_id}, but the resulting topic list is empty.") + # Return empty list and prompts anyway, let caller decide - # Process results - if not tweet_topic_record: - logging.error("Topic generation failed (generate_topics returned None).") - return None, None # Return None for run_id as well if record is None + # --- Saving logic removed previously --- - # Use the determined run_id for output directory - output_dir = os.path.join(config["output_dir"], run_id) - try: - os.makedirs(output_dir, exist_ok=True) - # --- Debug: Print the data before attempting to save --- - logging.info("--- Debug: Data to be saved in tweet_topic.json ---") - logging.info(tweet_topic_record.topics_list) - logging.info("--- End Debug ---") - # --- End Debug --- - - # 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: - logging.warning("Warning: Failed to save topic generation results or prompts.") - # Continue but warn user - - except Exception as e: - logging.exception("Error saving topic generation results:") - 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 - - logging.info(f"Topics generated successfully. Run ID: {run_id}") - # Return the determined run_id and the record - return run_id, tweet_topic_record + logging.info(f"Topic generation pipeline completed successfully. Run ID: {run_id}") + # Return the raw data needed by the OutputHandler + return run_id, topics_list, system_prompt, user_prompt # --- Decoupled Functional Units (Moved from main.py) --- -def generate_content_for_topic(ai_agent, prompt_manager, config, topic_item, output_dir, run_id, topic_index): - """Generates all content variants for a single topic item. - +def generate_content_for_topic(ai_agent: AI_Agent, + prompt_manager: PromptManager, + topic_item: dict, + run_id: str, + topic_index: int, + output_handler: OutputHandler, # Changed name to match convention + # 添加具体参数，移除 config 和 output_dir + variants: int, + temperature: float, + top_p: float, + presence_penalty: float): + """Generates all content variants for a single topic item and uses OutputHandler. + Args: - ai_agent: An initialized AI_Agent instance. - prompt_manager: An initialized PromptManager instance. - config: The global configuration dictionary. - topic_item: The dictionary representing a single topic. - output_dir: The base output directory for the entire run (e.g., ./result). - run_id: The ID for the current run. - topic_index: The 1-based index of the current topic. - + ai_agent: Initialized AI_Agent instance. + prompt_manager: Initialized PromptManager instance. + topic_item: Dictionary representing the topic. + run_id: Current run ID. + topic_index: 1-based index of the topic. + output_handler: An instance of OutputHandler to process results. + variants: Number of variants to generate. + temperature, top_p, presence_penalty: AI generation parameters. Returns: - A list of tweet content data (dictionaries) generated for the topic, - or None if generation failed. + bool: True if at least one variant was successfully generated and handled, False otherwise. """ logging.info(f"Generating content for Topic {topic_index} (Object: {topic_item.get('object', 'N/A')})...") - tweet_content_list = [] - variants = config.get("variants", 1) + success_flag = False # Track if any variant succeeded + # 使用传入的 variants 参数 + # variants = config.get("variants", 1) for j in range(variants): variant_index = j + 1 - logging.info(f"Generating Variant {variant_index}/{variants}...") + logging.info(f" Generating Variant {variant_index}/{variants}...") - # Get prompts for this specific topic item - # Assuming prompt_manager is correctly initialized and passed + # PromptManager 实例已传入，直接调用 content_system_prompt, content_user_prompt = prompt_manager.get_content_prompts(topic_item) if not content_system_prompt or not content_user_prompt: - logging.warning(f"Skipping Variant {variant_index} due to missing content prompts.") - continue # Skip this variant + logging.warning(f" Skipping Variant {variant_index} due to missing content prompts.") + continue time.sleep(random.random() * 0.5) try: - # Call the core generation function (generate_single_content is in this file) - tweet_content, gen_result = generate_single_content( + # Call generate_single_content with passed-in parameters + content_json, prompt_data = generate_single_content( ai_agent, content_system_prompt, content_user_prompt, topic_item, - output_dir, run_id, topic_index, variant_index, - config.get("content_temperature", 0.3), - config.get("content_top_p", 0.4), - config.get("content_presence_penalty", 1.5) + run_id, topic_index, variant_index, + temperature, # 使用传入的参数 + top_p, # 使用传入的参数 + presence_penalty # 使用传入的参数 ) - if tweet_content: - try: - tweet_content_data = tweet_content.get_json_file() - if tweet_content_data: - tweet_content_list.append(tweet_content_data) - else: - logging.warning(f"Warning: tweet_content.get_json_file() for Topic {topic_index}, Variant {variant_index} returned empty data.") - except Exception as parse_err: - logging.error(f"Error processing tweet content after generation for Topic {topic_index}, Variant {variant_index}: {parse_err}") + + # Check if generation succeeded and parsing was okay (or error handled within json) + if content_json is not None and prompt_data is not None: + # Use the output handler to process/save the result + output_handler.handle_content_variant( + run_id, topic_index, variant_index, content_json, prompt_data + ) + success_flag = True # Mark success for this topic + + # Check specifically if the AI result itself indicated a parsing error internally + if content_json.get("error"): + logging.error(f" Content generation for Topic {topic_index}, Variant {variant_index} succeeded but response parsing failed (error flag set in content). Raw data logged by handler.") + else: + logging.info(f" Successfully generated and handled content for Topic {topic_index}, Variant {variant_index}.") else: - logging.warning(f"Failed to generate content for Topic {topic_index}, Variant {variant_index}. Skipping.") + logging.error(f" Content generation failed for Topic {topic_index}, Variant {variant_index}. Skipping handling.") + except Exception as e: - logging.exception(f"Error during content generation for Topic {topic_index}, Variant {variant_index}:") - # traceback.print_exc() + logging.exception(f" Error during content generation call or handling for Topic {topic_index}, Variant {variant_index}:") - if not tweet_content_list: - logging.warning(f"No valid content generated for Topic {topic_index}.") - return None - else: - logging.info(f"Successfully generated {len(tweet_content_list)} content variants for Topic {topic_index}.") - return tweet_content_list + # Return the success flag for this topic + return success_flag -def generate_posters_for_topic(config, topic_item, tweet_content_list, output_dir, run_id, topic_index): - """Generates all posters for a single topic item based on its generated content. +def generate_posters_for_topic(topic_item: dict, + output_dir: str, + run_id: str, + topic_index: int, + output_handler: OutputHandler, # 添加 handler + variants: int, + poster_assets_base_dir: str, + image_base_dir: str, + modify_image_subdir: str, + resource_dir_config: list, + poster_target_size: tuple, + text_possibility: float, + output_collage_subdir: str, + output_poster_subdir: str, + output_poster_filename: str, + camera_image_subdir: str + ): + """Generates all posters for a single topic item, handling image data via OutputHandler. Args: - config: The global configuration dictionary. topic_item: The dictionary representing a single topic. - tweet_content_list: List of content data generated by generate_content_for_topic. output_dir: The base output directory for the entire run (e.g., ./result). run_id: The ID for the current run. topic_index: The 1-based index of the current topic. + variants: Number of variants. + poster_assets_base_dir: Path to poster assets (fonts, frames etc.). + image_base_dir: Base path for source images. + modify_image_subdir: Subdirectory for modified images. + resource_dir_config: Configuration for resource directories (used for Description). + poster_target_size: Target size tuple (width, height) for the poster. + text_possibility: Probability of adding secondary text. + output_collage_subdir: Subdirectory name for saving collages. + output_poster_subdir: Subdirectory name for saving posters. + output_poster_filename: Filename for the final poster. + camera_image_subdir: Subdirectory for camera images (currently unused in logic?). + output_handler: An instance of OutputHandler to process results. Returns: True if poster generation was attempted (regardless of individual variant success), @@ -478,30 +479,47 @@ def generate_posters_for_topic(config, topic_item, tweet_content_list, output_di """ logging.info(f"Generating posters for Topic {topic_index} (Object: {topic_item.get('object', 'N/A')})...") - # Initialize necessary generators here, assuming they are stateless or cheap to create - # Alternatively, pass initialized instances if they hold state or are expensive + # --- Load content data from files --- + loaded_content_list = [] + logging.info(f"Attempting to load content data for {variants} variants for topic {topic_index}...") + for j in range(variants): + variant_index = j + 1 + variant_dir = os.path.join(output_dir, run_id, f"{topic_index}_{variant_index}") + content_path = os.path.join(variant_dir, "article.json") + try: + if os.path.exists(content_path): + with open(content_path, 'r', encoding='utf-8') as f_content: + content_data = json.load(f_content) + if isinstance(content_data, dict) and 'title' in content_data and 'content' in content_data: + loaded_content_list.append(content_data) + logging.debug(f" Successfully loaded content from: {content_path}") + else: + logging.warning(f" Content file {content_path} has invalid format. Skipping.") + else: + logging.warning(f" Content file not found for variant {variant_index}: {content_path}. Skipping.") + except json.JSONDecodeError: + logging.error(f" Error decoding JSON from content file: {content_path}. Skipping.") + except Exception as e: + logging.exception(f" Error loading content file {content_path}: {e}") + + if not loaded_content_list: + logging.error(f"No valid content data loaded for topic {topic_index}. Cannot generate posters.") + return False + logging.info(f"Successfully loaded content data for {len(loaded_content_list)} variants.") + # --- End Load content data --- + + # Initialize generators using parameters try: content_gen_instance = core_contentGen.ContentGenerator() - # poster_gen_instance = core_posterGen.PosterGenerator() - # --- Read poster assets base dir from config --- - poster_assets_base_dir = config.get("poster_assets_base_dir") if not poster_assets_base_dir: - logging.error("Error: 'poster_assets_base_dir' not found in configuration. Cannot generate posters.") - return False # Cannot proceed without assets base dir - # --- Initialize PosterGenerator with the base dir --- + logging.error("Error: 'poster_assets_base_dir' not provided. Cannot generate posters.") + return False poster_gen_instance = core_posterGen.PosterGenerator(base_dir=poster_assets_base_dir) except Exception as e: logging.exception("Error initializing generators for poster creation:") return False - # --- Setup: Paths and Object Name --- - image_base_dir = config.get("image_base_dir") - if not image_base_dir: - logging.error("Error: image_base_dir missing in config for poster generation.") - return False - modify_image_subdir = config.get("modify_image_subdir", "modify") - camera_image_subdir = config.get("camera_image_subdir", "相机") - + # --- Setup: Paths and Object Name --- object_name = topic_item.get("object", "") if not object_name: logging.warning("Warning: Topic object name is missing. Cannot generate posters.") @@ -513,110 +531,95 @@ def generate_posters_for_topic(config, topic_item, tweet_content_list, output_di if not object_name_cleaned: logging.warning(f"Warning: Object name '{object_name}' resulted in empty string after cleaning. Skipping posters.") return False - object_name = object_name_cleaned # Use the cleaned name for searching + object_name = object_name_cleaned except Exception as e: logging.warning(f"Warning: Could not fully clean object name '{object_name}': {e}. Skipping posters.") return False - # Construct and check INPUT image paths (still needed for collage) - input_img_dir_path = os.path.join(image_base_dir, modify_image_subdir, object_name) + # Construct and check INPUT image paths + input_img_dir_path = os.path.join(image_base_dir, modify_image_subdir, object_name) if not os.path.exists(input_img_dir_path) or not os.path.isdir(input_img_dir_path): logging.warning(f"Warning: Modify Image directory not found or not a directory: '{input_img_dir_path}'. Skipping posters for this topic.") return False - # --- NEW: Locate Description File using resource_dir type "Description" --- + # Locate Description File using resource_dir_config parameter info_directory = [] description_file_path = None - resource_dir_config = config.get("resource_dir", []) found_description = False - for dir_info in resource_dir_config: if dir_info.get("type") == "Description": for file_path in dir_info.get("file_path", []): - # Match description file based on object name containment if object_name in os.path.basename(file_path): description_file_path = file_path if os.path.exists(description_file_path): - info_directory = [description_file_path] # Pass the found path + info_directory = [description_file_path] logging.info(f"Found and using description file from config: {description_file_path}") found_description = True else: logging.warning(f"Warning: Description file specified in config not found: {description_file_path}") - break # Found the matching entry in this list - if found_description: # Stop searching resource_dir if found + break + if found_description: break - if not found_description: logging.info(f"Warning: No matching description file found for object '{object_name}' in config resource_dir (type='Description').") - # --- End NEW Description File Logic --- - - # --- Generate Text Configurations for All Variants --- + + # Generate Text Configurations for All Variants try: - poster_text_configs_raw = content_gen_instance.run(info_directory, config["variants"], tweet_content_list) + poster_text_configs_raw = content_gen_instance.run(info_directory, variants, loaded_content_list) if not poster_text_configs_raw: logging.warning("Warning: ContentGenerator returned empty configuration data. Skipping posters.") return False - # --- Save the COMPLETE poster configs list for this topic --- - run_output_dir_base = os.path.join(output_dir, run_id) - topic_config_save_path = os.path.join(run_output_dir_base, f"topic_{topic_index}_poster_configs.json") - try: - # Assuming poster_text_configs_raw is JSON-serializable (likely a list/dict) - with open(topic_config_save_path, 'w', encoding='utf-8') as f_cfg_topic: - json.dump(poster_text_configs_raw, f_cfg_topic, ensure_ascii=False, indent=4) - logging.info(f"Saved complete poster configurations for topic {topic_index} to: {topic_config_save_path}") - except Exception as save_err: - logging.error(f"Failed to save complete poster configurations for topic {topic_index} to {topic_config_save_path}: {save_err}") - # --- End Save Complete Config --- + # --- 使用 OutputHandler 保存 Poster Config --- + output_handler.handle_poster_configs(run_id, topic_index, poster_text_configs_raw) + # --- 结束使用 Handler 保存 --- poster_config_summary = core_posterGen.PosterConfig(poster_text_configs_raw) except Exception as e: logging.exception("Error running ContentGenerator or parsing poster configs:") traceback.print_exc() - return False # Cannot proceed if text config fails + return False - # --- Poster Generation Loop for each variant --- - poster_num = config.get("variants", 1) - target_size = tuple(config.get("poster_target_size", [900, 1200])) + # Poster Generation Loop for each variant + poster_num = variants any_poster_attempted = False - text_possibility = config.get("text_possibility", 0.3) # Get from config for j_index in range(poster_num): variant_index = j_index + 1 logging.info(f"Generating Poster {variant_index}/{poster_num}...") any_poster_attempted = True + collage_img = None # To store the generated collage PIL Image + poster_img = None # To store the final poster PIL Image try: poster_config = poster_config_summary.get_config_by_index(j_index) if not poster_config: logging.warning(f"Warning: Could not get poster config for index {j_index}. Skipping.") continue - # Define output directories for this specific variant - run_output_dir = os.path.join(output_dir, run_id) - variant_output_dir = os.path.join(run_output_dir, f"{topic_index}_{variant_index}") - output_collage_subdir = config.get("output_collage_subdir", "collage_img") - output_poster_subdir = config.get("output_poster_subdir", "poster") - collage_output_dir = os.path.join(variant_output_dir, output_collage_subdir) - poster_output_dir = os.path.join(variant_output_dir, output_poster_subdir) - os.makedirs(collage_output_dir, exist_ok=True) - os.makedirs(poster_output_dir, exist_ok=True) - - # --- Image Collage --- + # --- Image Collage --- logging.info(f"Generating collage from: {input_img_dir_path}") - img_list = core_simple_collage.process_directory( + collage_images = core_simple_collage.process_directory( input_img_dir_path, - target_size=target_size, - output_count=1, - output_dir=collage_output_dir + target_size=poster_target_size, + output_count=1 ) - if not img_list or len(img_list) == 0 or not img_list[0].get('path'): + if not collage_images: # 检查列表是否为空 logging.warning(f"Warning: Failed to generate collage image for Variant {variant_index}. Skipping poster.") continue - collage_img_path = img_list[0]['path'] - logging.info(f"Using collage image: {collage_img_path}") + collage_img = collage_images[0] # 获取第一个 PIL Image + logging.info(f"Collage image generated successfully (in memory).") + + # --- 使用 Handler 保存 Collage 图片 --- + output_handler.handle_generated_image( + run_id, topic_index, variant_index, + image_type='collage', + image_data=collage_img, + output_filename='collage.png' # 或者其他期望的文件名 + ) + # --- 结束保存 Collage --- - # --- Create Poster --- + # --- Create Poster --- text_data = { "title": poster_config.get('main_title', 'Default Title'), "subtitle": "", @@ -624,98 +627,37 @@ def generate_posters_for_topic(config, topic_item, tweet_content_list, output_di } texts = poster_config.get('texts', []) if texts: - # Ensure TEXT_POSBILITY is accessible, maybe pass via config? - # text_possibility = config.get("text_possibility", 0.3) text_data["additional_texts"].append({"text": texts[0], "position": "bottom", "size_factor": 0.5}) - if len(texts) > 1 and random.random() < text_possibility: # Use variable from config + if len(texts) > 1 and random.random() < text_possibility: text_data["additional_texts"].append({"text": texts[1], "position": "bottom", "size_factor": 0.5}) - # final_poster_path = os.path.join(poster_output_dir, "poster.jpg") # Filename "poster.jpg" is hardcoded - output_poster_filename = config.get("output_poster_filename", "poster.jpg") - final_poster_path = os.path.join(poster_output_dir, output_poster_filename) - result_path = poster_gen_instance.create_poster(collage_img_path, text_data, final_poster_path) # Uses hardcoded output filename - if result_path: - logging.info(f"Successfully generated poster: {result_path}") + # 调用修改后的 create_poster, 接收 PIL Image + poster_img = poster_gen_instance.create_poster(collage_img, text_data) + + if poster_img: + logging.info(f"Poster image generated successfully (in memory).") + # --- 使用 Handler 保存 Poster 图片 --- + output_handler.handle_generated_image( + run_id, topic_index, variant_index, + image_type='poster', + image_data=poster_img, + output_filename=output_poster_filename # 使用参数中的文件名 + ) + # --- 结束保存 Poster --- else: - logging.warning(f"Warning: Poster generation function did not return a valid path for {final_poster_path}.") + logging.warning(f"Warning: Poster generation function returned None for variant {variant_index}.") except Exception as e: logging.exception(f"Error during poster generation for Variant {variant_index}:") traceback.print_exc() - continue # Continue to next variant + continue return any_poster_attempted -def main(): - """主函数入口""" - config_file = { - "date": "4月17日", - "num": 5, - "model": "qwenQWQ", - "api_url": "vllm", - "api_key": "EMPTY", - "topic_system_prompt": "/root/autodl-tmp/TravelContentCreator/SelectPrompt/systemPrompt.txt", - "topic_user_prompt": "/root/autodl-tmp/TravelContentCreator/SelectPrompt/userPrompt.txt", - "content_system_prompt": "/root/autodl-tmp/TravelContentCreator/genPrompts/systemPrompt.txt", - "resource_dir": [{ - "type": "Object", - "num": 4, - "file_path": ["/root/autodl-tmp/TravelContentCreator/resource/Object/景点信息-尚书第.txt", - "/root/autodl-tmp/TravelContentCreator/resource/Object/景点信息-明清园.txt", - "/root/autodl-tmp/TravelContentCreator/resource/Object/景点信息-泰宁古城.txt", - "/root/autodl-tmp/TravelContentCreator/resource/Object/景点信息-甘露寺.txt" - ]}, - { - "type": "Product", - "num": 0, - "file_path": [] - } - ], - "prompts_dir": "/root/autodl-tmp/TravelContentCreator/genPrompts", - "output_dir": "/root/autodl-tmp/TravelContentCreator/result", - "variants": 2, - "topic_temperature": 0.2, - "content_temperature": 0.3 - } - - if True: - # 1. 首先生成选题 - ai_agent, system_prompt, user_prompt, output_dir = prepare_topic_generation( - config_file - ) - - run_id, tweet_topic_record = generate_topics( - ai_agent, system_prompt, user_prompt, config_file["output_dir"], - config_file["topic_temperature"], 0.5, 1.5 - ) - - output_dir = os.path.join(config_file["output_dir"], run_id) - os.makedirs(output_dir, exist_ok=True) - tweet_topic_record.save_topics(os.path.join(output_dir, "tweet_topic.json")) - tweet_topic_record.save_prompt(os.path.join(output_dir, "tweet_prompt.txt")) - # raise Exception("选题生成失败，退出程序") - if not run_id or not tweet_topic_record: - print("选题生成失败，退出程序") - return - - # 2. 然后生成内容 - print("\n开始根据选题生成内容...") - - # 加载内容生成的系统提示词 - content_system_prompt = ResourceLoader.load_system_prompt(config_file["content_system_prompt"]) - - - if not content_system_prompt: - print("内容生成系统提示词为空，使用选题生成的系统提示词") - content_system_prompt = system_prompt - - # 直接使用同一个AI Agent实例 - result = generate_content( - ai_agent, content_system_prompt, tweet_topic_record.topics_list, output_dir, run_id, config_file["prompts_dir"], config_file["resource_dir"], - config_file["variants"], config_file["content_temperature"] - ) - - - -if __name__ == "__main__": - main() \ No newline at end of file +# main 函数不再使用，注释掉或移除 +# def main(): +# """主函数入口""" +# # ... (旧的 main 函数逻辑) +# +# if __name__ == "__main__": +# main() \ No newline at end of file