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Update backend api

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This commit is contained in:
Xin Wang
2026-02-08 15:52:16 +08:00
parent 727fe8a997
commit 7012f8edaf
15 changed files with 3436 additions and 19 deletions
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373
api/init_db.py
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@@ -7,7 +7,7 @@ import sys
sys.path.insert(0, os.path.dirname(os.path.abspath(__file__)))
from app.db import Base, engine, DATABASE_URL
from app.models import Voice
from app.models import Voice, Assistant, KnowledgeBase, Workflow, LLMModel, ASRModel
def init_db():
@@ -22,10 +22,379 @@ def init_db():
print("✅ 数据库表创建完成")
def init_default_data():
from sqlalchemy.orm import Session
from app.db import SessionLocal
from app.models import Voice
db = SessionLocal()
try:
# 检查是否已有数据
if db.query(Voice).count() == 0:
# SiliconFlow CosyVoice 2.0 预设声音 (8个)
# 参考: https://docs.siliconflow.cn/cn/api-reference/audio/create-speech
voices = [
# 男声 (Male Voices)
Voice(id="alex", name="Alex", vendor="SiliconFlow", gender="Male", language="en",
description="Steady male voice.", is_system=True),
Voice(id="benjamin", name="Benjamin", vendor="SiliconFlow", gender="Male", language="en",
description="Deep male voice.", is_system=True),
Voice(id="charles", name="Charles", vendor="SiliconFlow", gender="Male", language="en",
description="Magnetic male voice.", is_system=True),
Voice(id="david", name="David", vendor="SiliconFlow", gender="Male", language="en",
description="Cheerful male voice.", is_system=True),
# 女声 (Female Voices)
Voice(id="anna", name="Anna", vendor="SiliconFlow", gender="Female", language="en",
description="Steady female voice.", is_system=True),
Voice(id="bella", name="Bella", vendor="SiliconFlow", gender="Female", language="en",
description="Passionate female voice.", is_system=True),
Voice(id="claire", name="Claire", vendor="SiliconFlow", gender="Female", language="en",
description="Gentle female voice.", is_system=True),
Voice(id="diana", name="Diana", vendor="SiliconFlow", gender="Female", language="en",
description="Cheerful female voice.", is_system=True),
# 中文方言 (Chinese Dialects) - 可选扩展
Voice(id="amador", name="Amador", vendor="SiliconFlow", gender="Male", language="zh",
description="Male voice with Spanish accent."),
Voice(id="aelora", name="Aelora", vendor="SiliconFlow", gender="Female", language="en",
description="Elegant female voice."),
Voice(id="aelwin", name="Aelwin", vendor="SiliconFlow", gender="Male", language="en",
description="Deep male voice."),
Voice(id="blooming", name="Blooming", vendor="SiliconFlow", gender="Female", language="en",
description="Fresh and clear female voice."),
Voice(id="elysia", name="Elysia", vendor="SiliconFlow", gender="Female", language="en",
description="Smooth and silky female voice."),
Voice(id="leo", name="Leo", vendor="SiliconFlow", gender="Male", language="en",
description="Young male voice."),
Voice(id="lin", name="Lin", vendor="SiliconFlow", gender="Female", language="zh",
description="Standard Chinese female voice."),
Voice(id="rose", name="Rose", vendor="SiliconFlow", gender="Female", language="en",
description="Soft and gentle female voice."),
Voice(id="shao", name="Shao", vendor="SiliconFlow", gender="Male", language="zh",
description="Deep Chinese male voice."),
Voice(id="sky", name="Sky", vendor="SiliconFlow", gender="Male", language="en",
description="Clear and bright male voice."),
Voice(id="ael西山", name="Ael西山", vendor="SiliconFlow", gender="Female", language="zh",
description="Female voice with Chinese dialect."),
]
for v in voices:
db.add(v)
db.commit()
print("✅ 默认声音数据已初始化 (SiliconFlow CosyVoice 2.0)")
finally:
db.close()
def init_default_assistants():
"""初始化默认助手"""
from sqlalchemy.orm import Session
from app.db import SessionLocal
db = SessionLocal()
try:
if db.query(Assistant).count() == 0:
assistants = [
Assistant(
id="default",
user_id=1,
name="AI 助手",
call_count=0,
opener="你好！我是AI助手，有什么可以帮你的吗？",
prompt="你是一个友好的AI助手，请用简洁清晰的语言回答用户的问题。",
language="zh",
voice="anna",
speed=1.0,
hotwords=[],
tools=["search", "calculator"],
interruption_sensitivity=500,
config_mode="platform",
llm_model_id="deepseek-chat",
asr_model_id="paraformer-v2",
),
Assistant(
id="customer_service",
user_id=1,
name="客服助手",
call_count=0,
opener="您好，欢迎致电客服中心，请问有什么可以帮您？",
prompt="你是一个专业的客服人员，耐心解答客户问题，提供优质的服务体验。",
language="zh",
voice="bella",
speed=1.0,
hotwords=["客服", "投诉", "咨询"],
tools=["search"],
interruption_sensitivity=600,
config_mode="platform",
),
Assistant(
id="english_tutor",
user_id=1,
name="英语导师",
call_count=0,
opener="Hello! I'm your English learning companion. How can I help you today?",
prompt="You are a friendly English tutor. Help users practice English conversation and explain grammar points clearly.",
language="en",
voice="alex",
speed=1.0,
hotwords=["grammar", "vocabulary", "practice"],
tools=[],
interruption_sensitivity=400,
config_mode="platform",
),
]
for a in assistants:
db.add(a)
db.commit()
print("✅ 默认助手数据已初始化")
finally:
db.close()
def init_default_workflows():
"""初始化默认工作流"""
from sqlalchemy.orm import Session
from app.db import SessionLocal
from datetime import datetime
db = SessionLocal()
try:
if db.query(Workflow).count() == 0:
now = datetime.utcnow().strftime("%Y-%m-%d %H:%M:%S")
workflows = [
Workflow(
id="simple_conversation",
user_id=1,
name="简单对话",
node_count=2,
created_at=now,
updated_at=now,
global_prompt="处理简单的对话流程，用户问什么答什么。",
nodes=[
{"id": "1", "type": "start", "position": {"x": 100, "y": 100}, "data": {"label": "开始"}},
{"id": "2", "type": "ai_reply", "position": {"x": 300, "y": 100}, "data": {"label": "AI回复"}},
],
edges=[{"source": "1", "target": "2", "id": "e1-2"}],
),
Workflow(
id="voice_input_flow",
user_id=1,
name="语音输入流程",
node_count=4,
created_at=now,
updated_at=now,
global_prompt="处理语音输入的完整流程。",
nodes=[
{"id": "1", "type": "start", "position": {"x": 100, "y": 100}, "data": {"label": "开始"}},
{"id": "2", "type": "asr", "position": {"x": 250, "y": 100}, "data": {"label": "语音识别"}},
{"id": "3", "type": "llm", "position": {"x": 400, "y": 100}, "data": {"label": "LLM处理"}},
{"id": "4", "type": "tts", "position": {"x": 550, "y": 100}, "data": {"label": "语音合成"}},
],
edges=[
{"source": "1", "target": "2", "id": "e1-2"},
{"source": "2", "target": "3", "id": "e2-3"},
{"source": "3", "target": "4", "id": "e3-4"},
],
),
]
for w in workflows:
db.add(w)
db.commit()
print("✅ 默认工作流数据已初始化")
finally:
db.close()
def init_default_knowledge_bases():
"""初始化默认知识库"""
from sqlalchemy.orm import Session
from app.db import SessionLocal
db = SessionLocal()
try:
if db.query(KnowledgeBase).count() == 0:
kb = KnowledgeBase(
id="default_kb",
user_id=1,
name="默认知识库",
description="系统默认知识库，用于存储常见问题解答。",
embedding_model="text-embedding-3-small",
chunk_size=500,
chunk_overlap=50,
doc_count=0,
chunk_count=0,
status="active",
)
db.add(kb)
db.commit()
print("✅ 默认知识库已初始化")
finally:
db.close()
def init_default_llm_models():
"""初始化默认LLM模型"""
from sqlalchemy.orm import Session
from app.db import SessionLocal
db = SessionLocal()
try:
if db.query(LLMModel).count() == 0:
llm_models = [
LLMModel(
id="deepseek-chat",
user_id=1,
name="DeepSeek Chat",
vendor="SiliconFlow",
type="text",
base_url="https://api.deepseek.com",
api_key="YOUR_API_KEY", # 用户需替换
model_name="deepseek-chat",
temperature=0.7,
context_length=4096,
enabled=True,
),
LLMModel(
id="deepseek-reasoner",
user_id=1,
name="DeepSeek Reasoner",
vendor="SiliconFlow",
type="text",
base_url="https://api.deepseek.com",
api_key="YOUR_API_KEY",
model_name="deepseek-reasoner",
temperature=0.7,
context_length=4096,
enabled=True,
),
LLMModel(
id="gpt-4o",
user_id=1,
name="GPT-4o",
vendor="OpenAI",
type="text",
base_url="https://api.openai.com/v1",
api_key="YOUR_API_KEY",
model_name="gpt-4o",
temperature=0.7,
context_length=16384,
enabled=True,
),
LLMModel(
id="glm-4",
user_id=1,
name="GLM-4",
vendor="ZhipuAI",
type="text",
base_url="https://open.bigmodel.cn/api/paas/v4",
api_key="YOUR_API_KEY",
model_name="glm-4",
temperature=0.7,
context_length=8192,
enabled=True,
),
LLMModel(
id="text-embedding-3-small",
user_id=1,
name="Embedding 3 Small",
vendor="OpenAI",
type="embedding",
base_url="https://api.openai.com/v1",
api_key="YOUR_API_KEY",
model_name="text-embedding-3-small",
enabled=True,
),
]
for m in llm_models:
db.add(m)
db.commit()
print("✅ 默认LLM模型已初始化")
finally:
db.close()
def init_default_asr_models():
"""初始化默认ASR模型"""
from sqlalchemy.orm import Session
from app.db import SessionLocal
db = SessionLocal()
try:
if db.query(ASRModel).count() == 0:
asr_models = [
ASRModel(
id="paraformer-v2",
user_id=1,
name="Paraformer V2",
vendor="SiliconFlow",
language="zh",
base_url="https://api.siliconflow.cn/v1",
api_key="YOUR_API_KEY",
model_name="paraformer-v2",
hotwords=["人工智能", "机器学习"],
enable_punctuation=True,
enable_normalization=True,
enabled=True,
),
ASRModel(
id="paraformer-en",
user_id=1,
name="Paraformer English",
vendor="SiliconFlow",
language="en",
base_url="https://api.siliconflow.cn/v1",
api_key="YOUR_API_KEY",
model_name="paraformer-en",
hotwords=[],
enable_punctuation=True,
enable_normalization=True,
enabled=True,
),
ASRModel(
id="whisper-1",
user_id=1,
name="Whisper",
vendor="OpenAI",
language="Multi-lingual",
base_url="https://api.openai.com/v1",
api_key="YOUR_API_KEY",
model_name="whisper-1",
hotwords=[],
enable_punctuation=True,
enable_normalization=True,
enabled=True,
),
ASRModel(
id="sensevoice",
user_id=1,
name="SenseVoice",
vendor="SiliconFlow",
language="Multi-lingual",
base_url="https://api.siliconflow.cn/v1",
api_key="YOUR_API_KEY",
model_name="sensevoice",
hotwords=[],
enable_punctuation=True,
enable_normalization=True,
enabled=True,
),
]
for m in asr_models:
db.add(m)
db.commit()
print("✅ 默认ASR模型已初始化")
finally:
db.close()
if __name__ == "__main__":
# 确保 data 目录存在
data_dir = os.path.join(os.path.dirname(os.path.dirname(os.path.abspath(__file__))), "data")
os.makedirs(data_dir, exist_ok=True)
init_db()
init_default_data()
init_default_assistants()
init_default_workflows()
init_default_knowledge_bases()
init_default_llm_models()
init_default_asr_models()
print("🎉 数据库初始化完成！")