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完成了 narrato-api 生成视频脚本的逻辑

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linyqh 2024-11-09 20:08:51 +08:00
parent 8267a0b3eb
commit 49b52041ce
3 changed files with 60 additions and 53 deletions
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67
config.example.toml
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@ -2,8 +2,24 @@
project_version="0.3.0" project_version="0.3.0"
# 支持视频理解的大模型提供商 # 支持视频理解的大模型提供商
# gemini # gemini
# NarratoAPI
# qwen2-vl (待增加) # qwen2-vl (待增加)
video_llm_provider="gemini" vision_llm_provider="gemini"
vision_batch_size = 5
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"
########## Vision Gemini API Key
vision_gemini_api_key = ""
vision_gemini_model_name = "gemini-1.5-flash"
########### Vision NarratoAPI Key
# NarratoAPI 是为了便捷访问不了 Gemini API 的用户， 提供的代理服务
narrato_api_key = ""
narrato_api_url = ""
narrato_vision_model = "gemini-1.5-flash"
narrato_vision_key = ""
narrato_llm_model = "gpt-4o"
narrato_llm_key = ""
# 用于生成文案的大模型支持的提供商 (Supported providers): # 用于生成文案的大模型支持的提供商 (Supported providers):
# openai (默认) # openai (默认)
@ -13,63 +29,52 @@
# azure # azure
# qwen (通义千问) # qwen (通义千问)
# gemini # gemini
llm_provider="openai" text_llm_provider="openai"
########## Ollama Settings
# No need to set it unless you want to use your own proxy
ollama_base_url = ""
# Check your available models at https://ollama.com/library
ollama_model_name = ""
########## OpenAI API Key ########## OpenAI API Key
# Get your API key at https://platform.openai.com/api-keys # Get your API key at https://platform.openai.com/api-keys
openai_api_key = "" text_openai_api_key = ""
# No need to set it unless you want to use your own proxy # No need to set it unless you want to use your own proxy
openai_base_url = "" text_openai_base_url = ""
# Check your available models at https://platform.openai.com/account/limits # Check your available models at https://platform.openai.com/account/limits
openai_model_name = "gpt-4o" text_openai_model_name = "gpt-4o-mini"
########## Moonshot API Key ########## Moonshot API Key
# Visit https://platform.moonshot.cn/console/api-keys to get your API key. # Visit https://platform.moonshot.cn/console/api-keys to get your API key.
moonshot_api_key="" text_moonshot_api_key=""
moonshot_base_url = "https://api.moonshot.cn/v1" text_moonshot_base_url = "https://api.moonshot.cn/v1"
moonshot_model_name = "moonshot-v1-8k" text_moonshot_model_name = "moonshot-v1-8k"
########## OneAPI API Key
# Visit https://github.com/songquanpeng/one-api to get your API key
oneapi_api_key=""
oneapi_base_url=""
oneapi_model_name=""
########## G4F ########## G4F
# Visit https://github.com/xtekky/gpt4free to get more details # Visit https://github.com/xtekky/gpt4free to get more details
# Supported model list: https://github.com/xtekky/gpt4free/blob/main/g4f/models.py # Supported model list: https://github.com/xtekky/gpt4free/blob/main/g4f/models.py
g4f_model_name = "gpt-3.5-turbo" text_g4f_model_name = "gpt-3.5-turbo"
########## Azure API Key ########## Azure API Key
# Visit https://learn.microsoft.com/zh-cn/azure/ai-services/openai/ to get more details # Visit https://learn.microsoft.com/zh-cn/azure/ai-services/openai/ to get more details
# API documentation: https://learn.microsoft.com/zh-cn/azure/ai-services/openai/reference # API documentation: https://learn.microsoft.com/zh-cn/azure/ai-services/openai/reference
azure_api_key = "" text_azure_api_key = ""
azure_base_url="" text_azure_base_url=""
azure_model_name="gpt-35-turbo" # replace with your model deployment name text_azure_model_name="gpt-35-turbo" # replace with your model deployment name
azure_api_version = "2024-02-15-preview" text_azure_api_version = "2024-02-15-preview"
########## Gemini API Key ########## Gemini API Key
gemini_api_key="" text_gemini_api_key=""
gemini_model_name = "gemini-1.5-pro" text_gemini_model_name = "gemini-1.5-flash"
########## Qwen API Key ########## Qwen API Key
# Visit https://dashscope.console.aliyun.com/apiKey to get your API key # Visit https://dashscope.console.aliyun.com/apiKey to get your API key
# Visit below links to get more details # Visit below links to get more details
# https://tongyi.aliyun.com/qianwen/ # https://tongyi.aliyun.com/qianwen/
# https://help.aliyun.com/zh/dashscope/developer-reference/model-introduction # https://help.aliyun.com/zh/dashscope/developer-reference/model-introduction
qwen_api_key = "" text_qwen_api_key = ""
qwen_model_name = "qwen-max" text_qwen_model_name = "qwen-max"
########## DeepSeek API Key ########## DeepSeek API Key
# Visit https://platform.deepseek.com/api_keys to get your API key # Visit https://platform.deepseek.com/api_keys to get your API key
deepseek_api_key = "" text_deepseek_api_key = ""
deepseek_base_url = "https://api.deepseek.com" text_deepseek_base_url = "https://api.deepseek.com"
deepseek_model_name = "deepseek-chat" text_deepseek_model_name = "deepseek-chat"
# 字幕提供商、可选，支持 whisper 和 faster-whisper-large-v2"whisper" # 字幕提供商、可选，支持 whisper 和 faster-whisper-large-v2"whisper"
# 默认为 faster-whisper-large-v2 模型地址：https://huggingface.co/guillaumekln/faster-whisper-large-v2 # 默认为 faster-whisper-large-v2 模型地址：https://huggingface.co/guillaumekln/faster-whisper-large-v2

34
webui/components/script_settings.py
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@ -283,9 +283,10 @@ def generate_script(tr, params):
raise Exception(f"关键帧提取失败: {str(e)}") raise Exception(f"关键帧提取失败: {str(e)}")
# 根据不同的 LLM 提供商处理 # 根据不同的 LLM 提供商处理
video_llm_provider = st.session_state.get('video_llm_providers', 'Gemini').lower() vision_llm_provider = st.session_state.get('vision_llm_providers').lower()
logger.debug(f"Vision LLM 提供商: {vision_llm_provider}")
if video_llm_provider == 'gemini': if vision_llm_provider == 'gemini':
try: try:
# ===================初始化视觉分析器=================== # ===================初始化视觉分析器===================
update_progress(30, "正在初始化视觉分析器...") update_progress(30, "正在初始化视觉分析器...")
@ -443,7 +444,7 @@ def generate_script(tr, params):
logger.exception(f"Gemini 处理过程中发生错误\n{traceback.format_exc()}") logger.exception(f"Gemini 处理过程中发生错误\n{traceback.format_exc()}")
raise Exception(f"视觉分析失败: {str(e)}") raise Exception(f"视觉分析失败: {str(e)}")
else: # NarratoAPI elif vision_llm_provider == 'narratoapi': # NarratoAPI
try: try:
# 创建临时目录 # 创建临时目录
temp_dir = utils.temp_dir("narrato") temp_dir = utils.temp_dir("narrato")
@ -451,12 +452,11 @@ def generate_script(tr, params):
# 打包关键帧 # 打包关键帧
update_progress(30, "正在打包关键帧...") update_progress(30, "正在打包关键帧...")
zip_path = os.path.join(temp_dir, f"keyframes_{int(time.time())}.zip") zip_path = os.path.join(temp_dir, f"keyframes_{int(time.time())}.zip")
if not file_utils.create_zip(keyframe_files, zip_path): if not file_utils.create_zip(keyframe_files, zip_path):
raise Exception("打包关键帧失败") raise Exception("打包关键帧失败")
# 获取API配置 # 获取API配置
api_url = st.session_state.get('narrato_api_url', 'http://127.0.0.1:8000/api/v1/video/analyze') api_url = st.session_state.get('narrato_api_url')
api_key = st.session_state.get('narrato_api_key') api_key = st.session_state.get('narrato_api_key')
if not api_key: if not api_key:
@ -480,12 +480,13 @@ def generate_script(tr, params):
} }
# 发送API请求 # 发送API请求
logger.info(f"请求 NarratoAPI:{api_url}")
update_progress(40, "正在上传文件...") update_progress(40, "正在上传文件...")
with open(zip_path, 'rb') as f: with open(zip_path, 'rb') as f:
files = {'file': (os.path.basename(zip_path), f, 'application/x-zip-compressed')} files = {'file': (os.path.basename(zip_path), f, 'application/x-zip-compressed')}
try: try:
response = requests.post( response = requests.post(
api_url, f"{api_url}/video/analyze",
headers=headers, headers=headers,
params=api_params, params=api_params,
files=files, files=files,
@ -493,10 +494,11 @@ def generate_script(tr, params):
) )
response.raise_for_status() response.raise_for_status()
except requests.RequestException as e: except requests.RequestException as e:
logger.error(f"Narrato API 请求失败:\n{traceback.format_exc()}")
raise Exception(f"API请求失败: {str(e)}") raise Exception(f"API请求失败: {str(e)}")
task_data = response.json() task_data = response.json()
task_id = task_data.get('task_id') task_id = task_data["data"].get('task_id')
if not task_id: if not task_id:
raise Exception(f"无效的API响应: {response.text}") raise Exception(f"无效的API响应: {response.text}")
@ -508,7 +510,7 @@ def generate_script(tr, params):
while retry_count < max_retries: while retry_count < max_retries:
try: try:
status_response = requests.get( status_response = requests.get(
f"{api_url}/tasks/{task_id}", f"{api_url}/video/tasks/{task_id}",
headers=headers, headers=headers,
timeout=10 timeout=10
) )
@ -516,14 +518,12 @@ def generate_script(tr, params):
task_status = status_response.json()['data'] task_status = status_response.json()['data']
if task_status['status'] == 'SUCCESS': if task_status['status'] == 'SUCCESS':
script = task_status['result'] script = task_status['result']['data']
break break
elif task_status['status'] in ['FAILURE', 'RETRY']: elif task_status['status'] in ['FAILURE', 'RETRY']:
raise Exception(f"任务失败: {task_status.get('error')}") raise Exception(f"任务失败: {task_status.get('error')}")
retry_count += 1 retry_count += 1
progress = min(70, 50 + (retry_count * 20 / max_retries))
update_progress(progress, "正在分析中...")
time.sleep(2) time.sleep(2)
except requests.RequestException as e: except requests.RequestException as e:
@ -536,7 +536,7 @@ def generate_script(tr, params):
raise Exception("任务执行超时") raise Exception("任务执行超时")
except Exception as e: except Exception as e:
logger.exception("NarratoAPI 处理过程中发生错误") logger.exception(f"NarratoAPI 处理过程中发生错误\n{traceback.format_exc()}")
raise Exception(f"NarratoAPI 处理失败: {str(e)}") raise Exception(f"NarratoAPI 处理失败: {str(e)}")
finally: finally:
# 清理临时文件 # 清理临时文件
@ -546,12 +546,14 @@ def generate_script(tr, params):
except Exception as e: except Exception as e:
logger.warning(f"清理临时文件失败: {str(e)}") logger.warning(f"清理临时文件失败: {str(e)}")
else:
logger.exception("Vision Model 未启用，请检查配置")
if script is None: if script is None:
st.error("生成脚本失败，请检查日志") st.error("生成脚本失败，请检查日志")
st.stop() st.stop()
logger.info(f"脚本生成完成\n{script} \n{type(script)}")
script = utils.clean_model_output(script) st.session_state['video_clip_json'] = script
st.session_state['video_clip_json'] = json.loads(script)
update_progress(90, "脚本生成完成") update_progress(90, "脚本生成完成")
time.sleep(0.5) time.sleep(0.5)
@ -561,7 +563,7 @@ def generate_script(tr, params):
except Exception as err: except Exception as err:
st.error(f"生成过程中发生错误: {str(err)}") st.error(f"生成过程中发生错误: {str(err)}")
logger.exception("生成脚本时发生错误") logger.exception(f"生成脚本时发生错误\n{traceback.format_exc()}")
finally: finally:
time.sleep(2) time.sleep(2)
progress_bar.empty() progress_bar.empty()

12
webui/utils/file_utils.py
View File

@ -188,13 +188,14 @@ def ensure_directory(directory):
logger.error(f"创建目录失败: {directory}, 错误: {e}") logger.error(f"创建目录失败: {directory}, 错误: {e}")
return False return False
def create_zip(files: list, zip_path: str, base_dir: str = None) -> bool: def create_zip(files: list, zip_path: str, base_dir: str = None, folder_name: str = "demo") -> bool:
""" """
创建zip文件 创建zip文件
Args: Args:
files: 要打包的文件列表 files: 要打包的文件列表
zip_path: zip文件保存路径 zip_path: zip文件保存路径
base_dir: 基础目录，用于保持目录结构 base_dir: 基础目录，用于保持目录结构
folder_name: zip解压后的文件夹名称，默认为frames
Returns: Returns:
bool: 是否成功 bool: 是否成功
""" """
@ -210,19 +211,18 @@ def create_zip(files: list, zip_path: str, base_dir: str = None) -> bool:
logger.warning(f"文件不存在，跳过: {file}") logger.warning(f"文件不存在，跳过: {file}")
continue continue
# 计算文件在zip中的路径 # 计算文件在zip中的路径，添加folder_name作为前缀目录
if base_dir: if base_dir:
arcname = os.path.relpath(file, base_dir) arcname = os.path.join(folder_name, os.path.relpath(file, base_dir))
else: else:
arcname = os.path.basename(file) arcname = os.path.join(folder_name, os.path.basename(file))
try: try:
zipf.write(file, arcname) zipf.write(file, arcname)
except Exception as e: except Exception as e:
logger.error(f"添加文件到zip失败: {file}, 错误: {e}") logger.error(f"添加文件到zip失败: {file}, 错误: {e}")
continue continue
logger.info(f"创建zip文件成功: {zip_path}")
return True return True
except Exception as e: except Exception as e: