Merge 4f833f7561 into cb8e8b43c0

openai_api.py

@@ -7,17 +7,89 @@
 import time
 import torch
 import uvicorn
-from pydantic import BaseModel, Field
+from contextlib import asynccontextmanager
+from datetime import datetime, timedelta
+from fastapi import Depends, FastAPI, HTTPException, status
 from fastapi import FastAPI, HTTPException
 from fastapi.middleware.cors import CORSMiddleware
-from contextlib import asynccontextmanager
+from fastapi.security import OAuth2PasswordBearer, OAuth2PasswordRequestForm
-from typing import Any, Dict, List, Literal, Optional, Union
+from jose import JWTError, jwt
-from transformers import AutoTokenizer, AutoModel
+from passlib.context import CryptContext
+from pydantic import BaseModel
+from pydantic import BaseModel, Field
 from sse_starlette.sse import ServerSentEvent, EventSourceResponse
+from transformers import AutoTokenizer, AutoModel
+from typing import Any, Dict, List, Literal, Optional, Union
+from typing import Union
+
+# to get a string like this run:
+# openssl rand -hex 32
+SECRET_KEY = "09d25e094faa6ca2556c818166b7a9563b93f7099f6f0f4caa6cf63b88e8d3e7"
+ALGORITHM = "HS256"
+ACCESS_TOKEN_EXPIRE_MINUTES = 30
+
+'''
+用户数据（模拟数据库用户表）；用于我们稍后验证。
+账号：johndoe 密码：secret
+
+为了数据安全，我们利用PassLib对入库的用户密码进行加密处理，推荐的加密算法是"Bcrypt"
+其中，我们主要使用下面方法：
+from passlib.context import CryptContext
+pwd_context = CryptContext(schemes=["bcrypt"], deprecated="auto")
+pwd_context.hash(password) # 获取对密码进行加密的密文
+pwd_context.verify(password, hashed_password) # 对密码进行校验
+
+获取api-key 方法见：
+官方文档: https://fastapi.tiangolo.com/zh/tutorial/security/oauth2-jwt/#_5
+Postman: https://blog.csdn.net/Disany/article/details/109365066
+'''
+fake_users_db = {
+    "johndoe": {
+        "username": "johndoe",
+        "full_name": "John Doe",
+        "email": "johndoe@example.com",
+        # 得到这串加密后的密文，请运行:
+        # pwd_context.hash(password)
+        "hashed_password": "$2b$12$EixZaYVK1fsbw1ZfbX3OXePaWxn96p36WQoeG6Lruj3vjPGga31lW",
+        "disabled": False,
+    }
+}
+
+
+class Token(BaseModel):
+    access_token: str
+    token_type: str
+
+
+class TokenData(BaseModel):
+    username: Union[str, None] = None
+
+
+class User(BaseModel):
+    username: str
+    email: Union[str, None] = None
+    full_name: Union[str, None] = None
+    disabled: Union[bool, None] = None
+
+
+class UserInDB(User):
+    hashed_password: str
+
+
+# Context是上下文,CryptContext是密码上下文
+pwd_context = CryptContext(schemes=["bcrypt"], deprecated="auto")
+
+'''
+OAuth2PasswordBearer是接收URL作为参数的一个类：客户端会向该URL发送username和password参数，然后得到一个token值。
+OAuth2PasswordBearer并不会创建相应的URL路径操作，只是指明了客户端用来获取token的目标URL。
+当请求到来的时候，FastAPI会检查请求的Authorization头信息，如果没有找到Authorization头信息，或者头信息的内容不是Bearer token，它会返回401状态码(UNAUTHORIZED)。
+'''
+# oauth2_scheme是令牌对象，token: str = Depends(oauth2_scheme)后就是之前加密的令牌
+oauth2_scheme = OAuth2PasswordBearer(tokenUrl="token")
 
 
 @asynccontextmanager
-async def lifespan(app: FastAPI): # collects GPU memory
+async def lifespan(app: FastAPI):  # collects GPU memory
     yield
     if torch.cuda.is_available():
         torch.cuda.empty_cache()
@@ -34,6 +106,7 @@ app.add_middleware(
     allow_headers=["*"],
 )
 
+
 class ModelCard(BaseModel):
     id: str
     object: str = "model"
@@ -87,15 +160,124 @@ class ChatCompletionResponse(BaseModel):
     created: Optional[int] = Field(default_factory=lambda: int(time.time()))
 
 
+# verify_password验证密码
+# plain_password普通密码, hashed_password哈希密码
+# 返回True和False
+def verify_password(plain_password, hashed_password):
+    return pwd_context.verify(plain_password, hashed_password)
+
+
+# 获取哈希密码;普通密码进去，对应的哈希密码出来。
+def get_password_hash(password):
+    return pwd_context.hash(password)
+
+
+# 模拟从数据库读取用户信息
+def get_user(db, username: str):
+    if username in db:
+        user_dict = db[username]
+        return UserInDB(**user_dict)
+
+
+# 验证用户
+def authenticate_user(fake_db, username: str, password: str):
+    user = get_user(fake_db, username)
+    if not user:
+        return False
+    if not verify_password(password, user.hashed_password):
+        return False
+    return user
+
+
+# 创建访问令牌（token）
+def create_access_token(data: dict, expires_delta: Union[timedelta, None] = None):
+    to_encode = data.copy()
+    if expires_delta:
+        expire = datetime.utcnow() + expires_delta
+    else:
+        expire = datetime.utcnow() + timedelta(minutes=15)
+    to_encode.update({"exp": expire})
+    encoded_jwt = jwt.encode(to_encode, SECRET_KEY, algorithm=ALGORITHM)
+    return encoded_jwt
+
+
+'''数据请求验证
+用户拿到token信息后，必须在后续请求中，头信息的Authorization带有Bearer token，才能访问其他数据接口。
+下面添加一个校验函数，对请求的合法性进行校验，读取token内容解析并进行验证，验证token通过后，获取接口响应数据
+'''
+
+
+# 获取当前用户
+# 通过oauth2_scheme，拿到用户请求头文件里的token
+async def get_current_user(token: str = Depends(oauth2_scheme)):
+    credentials_exception = HTTPException(
+        status_code=status.HTTP_401_UNAUTHORIZED,
+        detail="Could not validate credentials",
+        headers={"WWW-Authenticate": "Bearer"},
+    )
+    try:
+        # jwt 解码
+        payload = jwt.decode(token, SECRET_KEY, algorithms=[ALGORITHM])
+        # 通常在jwt 解码会进行验证抛出各种异常PyJWTError，如令牌过期等；
+        # 获取生成token时候，我们放进去的username信息
+        username: str = payload.get("sub")
+        if username is None:
+            raise credentials_exception
+        token_data = TokenData(username=username)
+    except JWTError:
+        raise credentials_exception
+    # 获取该用户信息
+    user = get_user(fake_users_db, username=token_data.username)
+    if user is None:
+        raise credentials_exception
+    return user
+
+
+# 获取当前激活用户，通过数据库信息及相关条件对用户有效性进行过滤；如该用户存在，密码正确，token验证通过，但数据库字段显示该用户被封号或欠费了（非激活用户），就这此处触发异常，结束访问。
+async def get_current_active_user(current_user: User = Depends(get_current_user)):
+    if current_user.disabled:
+        raise HTTPException(status_code=400, detail="Inactive user")
+    return current_user
+
+
+''' ----  登录验证，获取token的接口 --------
+        用户发送post请求获取token,后端验证该用户是否存在，密码是否正确。如果验证通过，会生成‘token’给到用户。
+'''
+
+
+# name = johndoe    password = secret
+@app.post("/token", response_model=Token)
+async def login_for_access_token(form_data: OAuth2PasswordRequestForm = Depends()):
+    # 1、验证用户
+    user = authenticate_user(fake_users_db, form_data.username, form_data.password)
+    if not user:
+        raise HTTPException(
+            status_code=status.HTTP_401_UNAUTHORIZED,
+            detail="Incorrect username or password",
+            headers={"WWW-Authenticate": "Bearer"},
+        )
+    # 2、access_token_expires访问令牌过期
+    access_token_expires = timedelta(minutes=ACCESS_TOKEN_EXPIRE_MINUTES)
+    # 3、create_access_token创建访问令牌
+    access_token = create_access_token(
+        data={"sub": user.username}, expires_delta=access_token_expires
+    )
+    return {"access_token": access_token, "token_type": "bearer"}
+
+
 @app.get("/v1/models", response_model=ModelList)
-async def list_models():
+# 如果不需要apikey功能，可将括号中传参的 current_user 变量删除，既可允许任意访问，无需api-key身份认证。如下示例：
+# async def list_models():
+async def list_models(current_user: User = Depends(get_current_active_user)):
     global model_args
     model_card = ModelCard(id="gpt-3.5-turbo")
     return ModelList(data=[model_card])
 
 
 @app.post("/v1/chat/completions", response_model=ChatCompletionResponse)
-async def create_chat_completion(request: ChatCompletionRequest):
+# 如果不需要apikey功能，可将括号中传参的 current_user 变量删除，既可允许任意访问，无需api-key身份认证。如下示例：
+# async def create_chat_completion(request: ChatCompletionRequest):
+async def create_chat_completion(request: ChatCompletionRequest, current_user: User = Depends(get_current_active_user)):
     global model, tokenizer
 
     if request.messages[-1].role != "user":
@@ -109,8 +291,8 @@ async def create_chat_completion(request: ChatCompletionRequest):
     history = []
     if len(prev_messages) % 2 == 0:
         for i in range(0, len(prev_messages), 2):
-            if prev_messages[i].role == "user" and prev_messages[i+1].role == "assistant":
+            if prev_messages[i].role == "user" and prev_messages[i + 1].role == "assistant":
-                history.append([prev_messages[i].content, prev_messages[i+1].content])
+                history.append([prev_messages[i].content, prev_messages[i + 1].content])
 
     if request.stream:
         generate = predict(query, history, request.model)
@@ -154,7 +336,6 @@ async def predict(query: str, history: List[List[str]], model_id: str):
         chunk = ChatCompletionResponse(model=model_id, choices=[choice_data], object="chat.completion.chunk")
         yield "{}".format(chunk.json(exclude_unset=True, ensure_ascii=False))
 
-
     choice_data = ChatCompletionResponseStreamChoice(
         index=0,
         delta=DeltaMessage(),
@@ -165,7 +346,6 @@ async def predict(query: str, history: List[List[str]], model_id: str):
     yield '[DONE]'
 
 
-
 if __name__ == "__main__":
     tokenizer = AutoTokenizer.from_pretrained("THUDM/chatglm2-6b", trust_remote_code=True)
     model = AutoModel.from_pretrained("THUDM/chatglm2-6b", trust_remote_code=True).cuda()

requirements.txt

@@ -7,4 +7,6 @@ mdtex2html
 sentencepiece
 accelerate
 sse-starlette
-streamlit>=1.24.0
+streamlit>=1.24.0
+passlib
+python-jose