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refactor(script): remove sync endpoint, add thread-pool & timeout

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- Remove unused POST /script/generate sync endpoint and frontend generate()
- Move JSON parsing/validation to asyncio.to_thread() to avoid event-loop blocking
- Add 60s asyncio.timeout() around entire script generation pipeline
- Migrate volcengine_provider to unified AsyncArk client
This commit is contained in:
小鱼开发
2026-04-30 23:51:30 +08:00
parent 08a430ad9d
commit feddeed950
4 changed files with 94 additions and 135 deletions
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python-api/app/ai/providers/volcengine_provider.py
+10 -26
View File
@@ -35,21 +35,13 @@ logger = logging.getLogger(__name__)
# 尝试导入火山方舟 SDK
try:
from volcenginesdkarkruntime import Ark
from volcenginesdkarkruntime import AsyncArk
VOLCENGINE_SDK_AVAILABLE = True
except ImportError:
VOLCENGINE_SDK_AVAILABLE = False
logger.warning("火山方舟 SDK 未安装，请运行: pip install 'volcengine-python-sdk[ark]'")
try:
from openai import AsyncOpenAI
ASYNC_OPENAI_AVAILABLE = True
except ImportError:
ASYNC_OPENAI_AVAILABLE = False
logger.warning("OpenAI SDK 未安装，流式生成将不可用")
class VolcengineProvider(LLMProvider):
"""
@@ -137,16 +129,10 @@ class VolcengineProvider(LLMProvider):
self.default_model = "doubao-seed-2-0-lite-260215"
self.client = self._create_client()
import httpx
self.async_client = AsyncOpenAI(
api_key=self.api_key,
base_url=self.base_url or self.DEFAULT_BASE_URL,
http_client=httpx.AsyncClient(headers={"Accept-Encoding": "identity"}),
)
def _create_client(self) -> Ark:
"""创建火山方舟客户端"""
return Ark(
def _create_client(self) -> AsyncArk:
"""创建火山方舟异步客户端"""
return AsyncArk(
api_key=self.api_key,
base_url=self.base_url or self.DEFAULT_BASE_URL,
timeout=self.timeout,
@@ -203,7 +189,7 @@ class VolcengineProvider(LLMProvider):
request_params["response_format"] = {"type": "json_object"}
# 调用 API
completion = self.client.chat.completions.create(**request_params)
completion = await self.client.chat.completions.create(**request_params)
# 解析结果
content = completion.choices[0].message.content or ""
@@ -238,8 +224,6 @@ class VolcengineProvider(LLMProvider):
"""
流式生成文本
使用 AsyncOpenAI 客户端避免 Ark SDK 同步流式缓冲问题。
Args:
prompt: 用户提示词
model: 模型名称
@@ -271,7 +255,7 @@ class VolcengineProvider(LLMProvider):
if "reasoning_effort" in kwargs:
request_params["extra_body"] = {"reasoning_effort": kwargs["reasoning_effort"]}
stream = await self.async_client.chat.completions.create(**request_params)
stream = await self.client.chat.completions.create(**request_params)
async for chunk in stream:
if chunk.choices and chunk.choices[0].delta.content:
@@ -338,7 +322,7 @@ class VolcengineProvider(LLMProvider):
prompt_tokens = 0
completion_tokens = 0
stream = await self.async_client.chat.completions.create(**request_params)
stream = await self.client.chat.completions.create(**request_params)
async for chunk in stream:
if chunk.usage:
@@ -387,7 +371,7 @@ class VolcengineProvider(LLMProvider):
# 图片生成需要单独的图片模型，不在当前配置中
# 如需使用，请在模型广场开通 doubao-seed-1.6 并配置
image_model = model or "doubao-seed-1.6-flash-250828"
response = self.client.images.generate(
response = await self.client.images.generate(
model=image_model, prompt=prompt, size=size, **kwargs
)
@@ -424,7 +408,7 @@ class VolcengineProvider(LLMProvider):
dict: 包含向量化结果
"""
try:
response = self.client.embeddings.create(
response = await self.client.embeddings.create(
model=model or "doubao-embedding-1.5", input=texts, **kwargs
)
@@ -457,7 +441,7 @@ class VolcengineProvider(LLMProvider):
test_model = model or self.default_model
try:
response = self.client.chat.completions.create(
response = await self.client.chat.completions.create(
model=test_model,
messages=[{"role": "user", "content": "Hi"}],
max_tokens=5,
python-api/app/api/v1/script.py
-23
View File
@@ -49,29 +49,6 @@ async def get_categories():
)
@router.post("/generate", response_model=ApiResponse[list[ScriptShot]])
async def generate_script(request: GenerateScriptRequest):
"""
同步生成脚本
直接返回生成的分镜列表，适合快速预览。
"""
service = get_script_service()
shots = await service.generate_script(
category=request.category,
subcategory=request.subcategory,
duration=request.duration,
script_type=request.script_type,
model=request.model,
)
return success_response(
data=shots,
message=f"成功生成 {len(shots)} 个分镜",
)
@router.post("/generate/stream")
async def generate_script_stream(request: Request, data: GenerateScriptRequest):
"""
python-api/app/services/script_service.py
+84 -73
View File
@@ -141,89 +141,100 @@ class ScriptService:
model_router = await get_model_router()
try:
# 加载 Prompt
system_prompt = load_system_prompt(category, subcategory)
if not system_prompt:
yield ScriptGenerationEvent(
type="error",
message=f"未找到提示词: category={category}, subcategory={subcategory}",
)
return
user_prompt = load_script_user_prompt(
topic=f"{category}/{subcategory}",
duration=duration,
)
yield ScriptGenerationEvent(
type="start",
message="准备生成...",
)
full_content = ""
has_shown_generating = False
async for chunk in model_router.generate_stream_with_progress(
prompt=user_prompt,
system_prompt=system_prompt,
model_id=model,
task_type="script",
temperature=0.7,
response_format="json_object",
):
if chunk["type"] == "chunk":
chunk_content = chunk.get("content", "")
if not chunk_content:
continue
full_content += chunk_content
if not has_shown_generating:
yield ScriptGenerationEvent(
type="generating",
message="正在创作脚本...",
)
has_shown_generating = True
if not full_content or not full_content.strip():
yield ScriptGenerationEvent(
type="error",
message="AI 返回内容为空，请检查模型配置或重试",
)
return
success, parsed_data, error_msg = safe_parse_ai_json_response(full_content)
if not success:
yield ScriptGenerationEvent(
type="error",
message=f"脚本解析失败: {error_msg or '无法解析 AI 返回的内容'}",
)
return
try:
shots_data = validate_and_normalize_shots(parsed_data)
if not shots_data:
async with asyncio.timeout(60):
# 加载 Prompt
system_prompt = load_system_prompt(category, subcategory)
if not system_prompt:
yield ScriptGenerationEvent(
type="error",
message="AI 返回的分镜数据为空或格式不正确",
message=f"未找到提示词: category={category}, subcategory={subcategory}",
)
return
shots = [ScriptShot(**shot) for shot in shots_data]
yield ScriptGenerationEvent(
type="complete",
message="脚本生成成功",
result=shots,
user_prompt = load_script_user_prompt(
topic=f"{category}/{subcategory}",
duration=duration,
)
except Exception as e:
yield ScriptGenerationEvent(
type="error",
message=f"分镜数据处理失败: {str(e)}",
type="start",
message="准备生成...",
)
full_content = ""
has_shown_generating = False
async for chunk in model_router.generate_stream_with_progress(
prompt=user_prompt,
system_prompt=system_prompt,
model_id=model,
task_type="script",
temperature=0.7,
response_format="json_object",
):
if chunk["type"] == "chunk":
chunk_content = chunk.get("content", "")
if not chunk_content:
continue
full_content += chunk_content
if not has_shown_generating:
yield ScriptGenerationEvent(
type="generating",
message="正在创作脚本...",
)
has_shown_generating = True
if not full_content or not full_content.strip():
yield ScriptGenerationEvent(
type="error",
message="AI 返回内容为空，请检查模型配置或重试",
)
return
success, parsed_data, error_msg = await asyncio.to_thread(
safe_parse_ai_json_response, full_content
)
if not success:
yield ScriptGenerationEvent(
type="error",
message=f"脚本解析失败: {error_msg or '无法解析 AI 返回的内容'}",
)
return
try:
shots_data = await asyncio.to_thread(
validate_and_normalize_shots, parsed_data
)
if not shots_data:
yield ScriptGenerationEvent(
type="error",
message="AI 返回的分镜数据为空或格式不正确",
)
return
shots = [ScriptShot(**shot) for shot in shots_data]
yield ScriptGenerationEvent(
type="complete",
message="脚本生成成功",
result=shots,
)
except Exception as e:
yield ScriptGenerationEvent(
type="error",
message=f"分镜数据处理失败: {str(e)}",
)
except asyncio.TimeoutError:
yield ScriptGenerationEvent(
type="error",
message="脚本生成超时，请重试",
)
except Exception as e:
yield ScriptGenerationEvent(
type="error",
tauri-app/src/api/modules/script.ts
-13
View File
@@ -112,19 +112,6 @@ export const scriptApi = {
return client.get<CategoryItem[]>('/script/categories');
},
/**
* 生成脚本内容（同步）
* POST /script/generate
*/
generate: async (params: GenerateScriptParams): Promise<ScriptShot[]> => {
return client.post<ScriptShot[]>('/script/generate', {
category: params.category,
subcategory: params.subcategory,
duration: params.duration,
scriptType: params.type,
});
},
/**
* 流式生成脚本（SSE）
* POST /script/generate/stream