Fix/language unification (#283)

* [changes]add user_summary language unification

* [add]Entity extraction, user memory, emotion suggestions, unified language type for writing

* [add]Complete the switch between Chinese and English for the emotion labels and emotion suggestions fields.

* [changes]add user_summary language unification

* [add]Entity extraction, user memory, emotion suggestions, unified language type for writing

* [add]Complete the switch between Chinese and English for the emotion labels and emotion suggestions fields.

* [changes]Modify the code based on the AI review
This commit is contained in:
乐力齐
2026-02-03 16:03:08 +08:00
committed by GitHub
parent 63fa4dc8ec
commit 8670aaba1e
30 changed files with 1033 additions and 810 deletions

View File

@@ -11,6 +11,7 @@ Routes:
"""
from app.core.error_codes import BizCode
from app.core.language_utils import get_language_from_header
from app.core.logging_config import get_api_logger
from app.core.response_utils import fail, success
from app.dependencies import get_current_user, get_db
@@ -45,11 +46,14 @@ emotion_service = EmotionAnalyticsService()
@router.post("/tags", response_model=ApiResponse)
async def get_emotion_tags(
request: EmotionTagsRequest,
language_type: str = Header(default="zh", alias="X-Language-Type"),
language_type: str = Header(default=None, alias="X-Language-Type"),
current_user: User = Depends(get_current_user),
):
try:
# 使用集中化的语言校验
language = get_language_from_header(language_type)
api_logger.info(
f"用户 {current_user.username} 请求获取情绪标签统计",
extra={
@@ -57,7 +61,8 @@ async def get_emotion_tags(
"emotion_type": request.emotion_type,
"start_date": request.start_date,
"end_date": request.end_date,
"limit": request.limit
"limit": request.limit,
"language_type": language
}
)
@@ -67,7 +72,8 @@ async def get_emotion_tags(
emotion_type=request.emotion_type,
start_date=request.start_date,
end_date=request.end_date,
limit=request.limit
limit=request.limit,
language=language
)
api_logger.info(
@@ -97,11 +103,14 @@ async def get_emotion_tags(
@router.post("/wordcloud", response_model=ApiResponse)
async def get_emotion_wordcloud(
request: EmotionWordcloudRequest,
language_type: str = Header(default="zh", alias="X-Language-Type"),
language_type: str = Header(default=None, alias="X-Language-Type"),
current_user: User = Depends(get_current_user),
):
try:
# 使用集中化的语言校验
language = get_language_from_header(language_type)
api_logger.info(
f"用户 {current_user.username} 请求获取情绪词云数据",
extra={
@@ -144,11 +153,14 @@ async def get_emotion_wordcloud(
@router.post("/health", response_model=ApiResponse)
async def get_emotion_health(
request: EmotionHealthRequest,
language_type: str = Header(default="zh", alias="X-Language-Type"),
language_type: str = Header(default=None, alias="X-Language-Type"),
current_user: User = Depends(get_current_user),
):
try:
# 使用集中化的语言校验
language = get_language_from_header(language_type)
# 验证时间范围参数
if request.time_range not in ["7d", "30d", "90d"]:
raise HTTPException(
@@ -199,7 +211,7 @@ async def get_emotion_health(
@router.post("/suggestions", response_model=ApiResponse)
async def get_emotion_suggestions(
request: EmotionSuggestionsRequest,
language_type: str = Header(default="zh", alias="X-Language-Type"),
language_type: str = Header(default=None, alias="X-Language-Type"),
db: Session = Depends(get_db),
current_user: User = Depends(get_current_user),
):
@@ -214,6 +226,9 @@ async def get_emotion_suggestions(
缓存的个性化情绪建议响应
"""
try:
# 使用集中化的语言校验
language = get_language_from_header(language_type)
api_logger.info(
f"用户 {current_user.username} 请求获取个性化情绪建议(缓存)",
extra={
@@ -265,7 +280,7 @@ async def get_emotion_suggestions(
@router.post("/generate_suggestions", response_model=ApiResponse)
async def generate_emotion_suggestions(
request: EmotionGenerateSuggestionsRequest,
language_type: str = Header(default="zh", alias="X-Language-Type"),
language_type: str = Header(default=None, alias="X-Language-Type"),
db: Session = Depends(get_db),
current_user: User = Depends(get_current_user),
):
@@ -280,6 +295,9 @@ async def generate_emotion_suggestions(
新生成的个性化情绪建议响应
"""
try:
# 使用集中化的语言校验
language = get_language_from_header(language_type)
api_logger.info(
f"用户 {current_user.username} 请求生成个性化情绪建议",
extra={
@@ -290,7 +308,8 @@ async def generate_emotion_suggestions(
# 调用服务层生成建议
data = await emotion_service.generate_emotion_suggestions(
end_user_id=request.end_user_id,
db=db
db=db,
language=language
)
# 保存到缓存