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https://github.com/linyqh/NarratoAI.git
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完成了 narrato-api 生成视频脚本的逻辑
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linyqh
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@ -2,8 +2,24 @@
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project_version="0.3.0"
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# 支持视频理解的大模型提供商
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# gemini
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# NarratoAPI
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# qwen2-vl (待增加)
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video_llm_provider="gemini"
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vision_llm_provider="gemini"
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vision_batch_size = 5
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vision_analysis_prompt = "你是资深视频内容分析专家，擅长分析视频画面信息，分析下面视频画面内容，只输出客观的画面描述不要给任何总结或评价"
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########## Vision Gemini API Key
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vision_gemini_api_key = ""
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vision_gemini_model_name = "gemini-1.5-flash"
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########### Vision NarratoAPI Key
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# NarratoAPI 是为了便捷访问不了 Gemini API 的用户， 提供的代理服务
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narrato_api_key = ""
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narrato_api_url = ""
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narrato_vision_model = "gemini-1.5-flash"
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narrato_vision_key = ""
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narrato_llm_model = "gpt-4o"
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narrato_llm_key = ""
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# 用于生成文案的大模型支持的提供商 (Supported providers):
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# openai (默认)
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@ -13,63 +29,52 @@
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# azure
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# qwen (通义千问)
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# gemini
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llm_provider="openai"
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########## Ollama Settings
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# No need to set it unless you want to use your own proxy
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ollama_base_url = ""
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# Check your available models at https://ollama.com/library
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ollama_model_name = ""
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text_llm_provider="openai"
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########## OpenAI API Key
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# Get your API key at https://platform.openai.com/api-keys
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openai_api_key = ""
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text_openai_api_key = ""
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# No need to set it unless you want to use your own proxy
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openai_base_url = ""
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text_openai_base_url = ""
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# Check your available models at https://platform.openai.com/account/limits
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openai_model_name = "gpt-4o"
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text_openai_model_name = "gpt-4o-mini"
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########## Moonshot API Key
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# Visit https://platform.moonshot.cn/console/api-keys to get your API key.
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moonshot_api_key=""
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moonshot_base_url = "https://api.moonshot.cn/v1"
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moonshot_model_name = "moonshot-v1-8k"
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########## OneAPI API Key
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# Visit https://github.com/songquanpeng/one-api to get your API key
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oneapi_api_key=""
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oneapi_base_url=""
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oneapi_model_name=""
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text_moonshot_api_key=""
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text_moonshot_base_url = "https://api.moonshot.cn/v1"
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text_moonshot_model_name = "moonshot-v1-8k"
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########## G4F
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# Visit https://github.com/xtekky/gpt4free to get more details
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# Supported model list: https://github.com/xtekky/gpt4free/blob/main/g4f/models.py
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g4f_model_name = "gpt-3.5-turbo"
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text_g4f_model_name = "gpt-3.5-turbo"
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########## Azure API Key
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# Visit https://learn.microsoft.com/zh-cn/azure/ai-services/openai/ to get more details
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# API documentation: https://learn.microsoft.com/zh-cn/azure/ai-services/openai/reference
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azure_api_key = ""
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azure_base_url=""
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azure_model_name="gpt-35-turbo" # replace with your model deployment name
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azure_api_version = "2024-02-15-preview"
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text_azure_api_key = ""
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text_azure_base_url=""
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text_azure_model_name="gpt-35-turbo" # replace with your model deployment name
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text_azure_api_version = "2024-02-15-preview"
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########## Gemini API Key
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gemini_api_key=""
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gemini_model_name = "gemini-1.5-pro"
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text_gemini_api_key=""
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text_gemini_model_name = "gemini-1.5-flash"
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########## Qwen API Key
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# Visit https://dashscope.console.aliyun.com/apiKey to get your API key
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# Visit below links to get more details
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# https://tongyi.aliyun.com/qianwen/
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# https://help.aliyun.com/zh/dashscope/developer-reference/model-introduction
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qwen_api_key = ""
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qwen_model_name = "qwen-max"
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text_qwen_api_key = ""
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text_qwen_model_name = "qwen-max"
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########## DeepSeek API Key
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# Visit https://platform.deepseek.com/api_keys to get your API key
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deepseek_api_key = ""
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deepseek_base_url = "https://api.deepseek.com"
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deepseek_model_name = "deepseek-chat"
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text_deepseek_api_key = ""
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text_deepseek_base_url = "https://api.deepseek.com"
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text_deepseek_model_name = "deepseek-chat"
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# 字幕提供商、可选，支持 whisper 和 faster-whisper-large-v2"whisper"
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# 默认为 faster-whisper-large-v2 模型地址：https://huggingface.co/guillaumekln/faster-whisper-large-v2
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@ -283,9 +283,10 @@ def generate_script(tr, params):
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raise Exception(f"关键帧提取失败: {str(e)}")
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# 根据不同的 LLM 提供商处理
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video_llm_provider = st.session_state.get('video_llm_providers', 'Gemini').lower()
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vision_llm_provider = st.session_state.get('vision_llm_providers').lower()
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logger.debug(f"Vision LLM 提供商: {vision_llm_provider}")
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if video_llm_provider == 'gemini':
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if vision_llm_provider == 'gemini':
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try:
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# ===================初始化视觉分析器===================
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update_progress(30, "正在初始化视觉分析器...")
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@ -443,7 +444,7 @@ def generate_script(tr, params):
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logger.exception(f"Gemini 处理过程中发生错误\n{traceback.format_exc()}")
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raise Exception(f"视觉分析失败: {str(e)}")
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else: # NarratoAPI
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elif vision_llm_provider == 'narratoapi': # NarratoAPI
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try:
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# 创建临时目录
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temp_dir = utils.temp_dir("narrato")
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@ -451,12 +452,11 @@ def generate_script(tr, params):
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# 打包关键帧
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update_progress(30, "正在打包关键帧...")
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zip_path = os.path.join(temp_dir, f"keyframes_{int(time.time())}.zip")
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if not file_utils.create_zip(keyframe_files, zip_path):
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raise Exception("打包关键帧失败")
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# 获取API配置
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api_url = st.session_state.get('narrato_api_url', 'http://127.0.0.1:8000/api/v1/video/analyze')
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api_url = st.session_state.get('narrato_api_url')
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api_key = st.session_state.get('narrato_api_key')
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if not api_key:
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@ -480,12 +480,13 @@ def generate_script(tr, params):
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}
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# 发送API请求
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logger.info(f"请求 NarratoAPI:{api_url}")
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update_progress(40, "正在上传文件...")
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with open(zip_path, 'rb') as f:
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files = {'file': (os.path.basename(zip_path), f, 'application/x-zip-compressed')}
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try:
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response = requests.post(
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api_url,
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f"{api_url}/video/analyze",
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headers=headers,
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params=api_params,
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files=files,
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@ -493,10 +494,11 @@ def generate_script(tr, params):
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)
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response.raise_for_status()
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except requests.RequestException as e:
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logger.error(f"Narrato API 请求失败:\n{traceback.format_exc()}")
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raise Exception(f"API请求失败: {str(e)}")
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task_data = response.json()
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task_id = task_data.get('task_id')
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task_id = task_data["data"].get('task_id')
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if not task_id:
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raise Exception(f"无效的API响应: {response.text}")
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@ -508,7 +510,7 @@ def generate_script(tr, params):
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while retry_count < max_retries:
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try:
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status_response = requests.get(
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f"{api_url}/tasks/{task_id}",
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f"{api_url}/video/tasks/{task_id}",
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headers=headers,
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timeout=10
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)
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@ -516,14 +518,12 @@ def generate_script(tr, params):
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task_status = status_response.json()['data']
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if task_status['status'] == 'SUCCESS':
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script = task_status['result']
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script = task_status['result']['data']
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break
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elif task_status['status'] in ['FAILURE', 'RETRY']:
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raise Exception(f"任务失败: {task_status.get('error')}")
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retry_count += 1
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progress = min(70, 50 + (retry_count * 20 / max_retries))
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update_progress(progress, "正在分析中...")
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time.sleep(2)
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except requests.RequestException as e:
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@ -536,7 +536,7 @@ def generate_script(tr, params):
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raise Exception("任务执行超时")
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except Exception as e:
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logger.exception("NarratoAPI 处理过程中发生错误")
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logger.exception(f"NarratoAPI 处理过程中发生错误\n{traceback.format_exc()}")
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raise Exception(f"NarratoAPI 处理失败: {str(e)}")
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finally:
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# 清理临时文件
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@ -546,12 +546,14 @@ def generate_script(tr, params):
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except Exception as e:
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logger.warning(f"清理临时文件失败: {str(e)}")
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else:
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logger.exception("Vision Model 未启用，请检查配置")
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if script is None:
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st.error("生成脚本失败，请检查日志")
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st.stop()
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script = utils.clean_model_output(script)
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st.session_state['video_clip_json'] = json.loads(script)
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logger.info(f"脚本生成完成\n{script} \n{type(script)}")
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st.session_state['video_clip_json'] = script
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update_progress(90, "脚本生成完成")
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time.sleep(0.5)
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@ -561,7 +563,7 @@ def generate_script(tr, params):
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except Exception as err:
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st.error(f"生成过程中发生错误: {str(err)}")
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logger.exception("生成脚本时发生错误")
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logger.exception(f"生成脚本时发生错误\n{traceback.format_exc()}")
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finally:
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time.sleep(2)
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progress_bar.empty()
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@ -188,13 +188,14 @@ def ensure_directory(directory):
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logger.error(f"创建目录失败: {directory}, 错误: {e}")
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return False
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def create_zip(files: list, zip_path: str, base_dir: str = None) -> bool:
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def create_zip(files: list, zip_path: str, base_dir: str = None, folder_name: str = "demo") -> bool:
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"""
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创建zip文件
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Args:
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files: 要打包的文件列表
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zip_path: zip文件保存路径
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base_dir: 基础目录，用于保持目录结构
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folder_name: zip解压后的文件夹名称，默认为frames
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Returns:
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bool: 是否成功
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"""
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@ -210,19 +211,18 @@ def create_zip(files: list, zip_path: str, base_dir: str = None) -> bool:
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logger.warning(f"文件不存在，跳过: {file}")
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continue
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# 计算文件在zip中的路径
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# 计算文件在zip中的路径，添加folder_name作为前缀目录
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if base_dir:
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arcname = os.path.relpath(file, base_dir)
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arcname = os.path.join(folder_name, os.path.relpath(file, base_dir))
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else:
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arcname = os.path.basename(file)
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arcname = os.path.join(folder_name, os.path.basename(file))
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try:
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zipf.write(file, arcname)
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except Exception as e:
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logger.error(f"添加文件到zip失败: {file}, 错误: {e}")
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continue
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logger.info(f"创建zip文件成功: {zip_path}")
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return True
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except Exception as e:
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