fix(core): Fix fschat and alembic log conflict (#919)

Co-authored-by: chengfangyin2 <chengfangyin3@jd.com>

dbgpt/model/cluster/apiserver/api.py

@@ -13,7 +13,7 @@ from fastapi import APIRouter, FastAPI
 from fastapi import Depends, HTTPException
 from fastapi.exceptions import RequestValidationError
 from fastapi.middleware.cors import CORSMiddleware
-from fastapi.responses import StreamingResponse
+from fastapi.responses import StreamingResponse, JSONResponse
 from fastapi.security.http import HTTPAuthorizationCredentials, HTTPBearer
 
 from pydantic import BaseSettings
@@ -30,10 +30,7 @@ from fastchat.protocol.openai_api_protocol import (
     ModelPermission,
     UsageInfo,
 )
-from fastchat.protocol.api_protocol import (
-    APIChatCompletionRequest,
-)
-from fastchat.serve.openai_api_server import create_error_response, check_requests
+from fastchat.protocol.api_protocol import APIChatCompletionRequest, ErrorResponse
 from fastchat.constants import ErrorCode
 
 from dbgpt.component import BaseComponent, ComponentType, SystemApp
@@ -85,6 +82,68 @@ async def check_api_key(
         return None
 
 
+def create_error_response(code: int, message: str) -> JSONResponse:
+    """Copy from fastchat.serve.openai_api_server.check_requests
+
+    We can't use fastchat.serve.openai_api_server because it has too many dependencies.
+    """
+    return JSONResponse(
+        ErrorResponse(message=message, code=code).dict(), status_code=400
+    )
+
+
+def check_requests(request) -> Optional[JSONResponse]:
+    """Copy from fastchat.serve.openai_api_server.create_error_response
+
+    We can't use fastchat.serve.openai_api_server because it has too many dependencies.
+    """
+    # Check all params
+    if request.max_tokens is not None and request.max_tokens <= 0:
+        return create_error_response(
+            ErrorCode.PARAM_OUT_OF_RANGE,
+            f"{request.max_tokens} is less than the minimum of 1 - 'max_tokens'",
+        )
+    if request.n is not None and request.n <= 0:
+        return create_error_response(
+            ErrorCode.PARAM_OUT_OF_RANGE,
+            f"{request.n} is less than the minimum of 1 - 'n'",
+        )
+    if request.temperature is not None and request.temperature < 0:
+        return create_error_response(
+            ErrorCode.PARAM_OUT_OF_RANGE,
+            f"{request.temperature} is less than the minimum of 0 - 'temperature'",
+        )
+    if request.temperature is not None and request.temperature > 2:
+        return create_error_response(
+            ErrorCode.PARAM_OUT_OF_RANGE,
+            f"{request.temperature} is greater than the maximum of 2 - 'temperature'",
+        )
+    if request.top_p is not None and request.top_p < 0:
+        return create_error_response(
+            ErrorCode.PARAM_OUT_OF_RANGE,
+            f"{request.top_p} is less than the minimum of 0 - 'top_p'",
+        )
+    if request.top_p is not None and request.top_p > 1:
+        return create_error_response(
+            ErrorCode.PARAM_OUT_OF_RANGE,
+            f"{request.top_p} is greater than the maximum of 1 - 'temperature'",
+        )
+    if request.top_k is not None and (request.top_k > -1 and request.top_k < 1):
+        return create_error_response(
+            ErrorCode.PARAM_OUT_OF_RANGE,
+            f"{request.top_k} is out of Range. Either set top_k to -1 or >=1.",
+        )
+    if request.stop is not None and (
+        not isinstance(request.stop, str) and not isinstance(request.stop, list)
+    ):
+        return create_error_response(
+            ErrorCode.PARAM_OUT_OF_RANGE,
+            f"{request.stop} is not valid under any of the given schemas - 'stop'",
+        )
+
+    return None
+
+
 class APIServer(BaseComponent):
     name = ComponentType.MODEL_API_SERVER
 

dbgpt/util/__init__.py

@@ -1,8 +1,5 @@
 from .utils import (
     get_gpu_memory,
-    StreamToLogger,
-    disable_torch_init,
-    pretty_print_semaphore,
     server_error_msg,
     get_or_create_event_loop,
 )

dbgpt/util/utils.py

@@ -111,58 +111,6 @@ def _build_logger(logger_name, logging_level=None, logger_filename: str = None):
     return logger
 
 
-class StreamToLogger(object):
-    """
-    Fake file-like stream object that redirects writes to a logger instance.
-    """
-
-    def __init__(self, logger, log_level=logging.INFO):
-        self.terminal = sys.stdout
-        self.logger = logger
-        self.log_level = log_level
-        self.linebuf = ""
-
-    def __getattr__(self, attr):
-        return getattr(self.terminal, attr)
-
-    def write(self, buf):
-        temp_linebuf = self.linebuf + buf
-        self.linebuf = ""
-        for line in temp_linebuf.splitlines(True):
-            # From the io.TextIOWrapper docs:
-            #   On output, if newline is None, any '\n' characters written
-            #   are translated to the system default line separator.
-            # By default sys.stdout.write() expects '\n' newlines and then
-            # translates them so this is still cross platform.
-            if line[-1] == "\n":
-                encoded_message = line.encode("utf-8", "ignore").decode("utf-8")
-                self.logger.log(self.log_level, encoded_message.rstrip())
-            else:
-                self.linebuf += line
-
-    def flush(self):
-        if self.linebuf != "":
-            encoded_message = self.linebuf.encode("utf-8", "ignore").decode("utf-8")
-            self.logger.log(self.log_level, encoded_message.rstrip())
-        self.linebuf = ""
-
-
-def disable_torch_init():
-    """
-    Disable the redundant torch default initialization to accelerate model creation.
-    """
-    import torch
-
-    setattr(torch.nn.Linear, "reset_parameters", lambda self: None)
-    setattr(torch.nn.LayerNorm, "reset_parameters", lambda self: None)
-
-
-def pretty_print_semaphore(semaphore):
-    if semaphore is None:
-        return "None"
-    return f"Semaphore(value={semaphore._value}, locked={semaphore.locked()})"
-
-
 def get_or_create_event_loop() -> asyncio.BaseEventLoop:
     loop = None
     try:

pilot/meta_data/alembic.ini

@@ -79,38 +79,3 @@ version_path_separator = os  # Use os.pathsep. Default configuration used for ne
 # ruff.type = exec
 # ruff.executable = %(here)s/.venv/bin/ruff
 # ruff.options = --fix REVISION_SCRIPT_FILENAME
-
-# Logging configuration
-[loggers]
-keys = root,sqlalchemy,alembic
-
-[handlers]
-keys = console
-
-[formatters]
-keys = generic
-
-[logger_root]
-level = WARN
-handlers = console
-qualname =
-
-[logger_sqlalchemy]
-level = WARN
-handlers =
-qualname = sqlalchemy.engine
-
-[logger_alembic]
-level = INFO
-handlers =
-qualname = alembic
-
-[handler_console]
-class = StreamHandler
-args = (sys.stderr,)
-level = NOTSET
-formatter = generic
-
-[formatter_generic]
-format = %(levelname)-5.5s [%(name)s] %(message)s
-datefmt = %H:%M:%S

pilot/meta_data/alembic/env.py

@@ -1,5 +1,3 @@
-from logging.config import fileConfig
-
 from sqlalchemy import engine_from_config
 from sqlalchemy import pool
 
@@ -11,10 +9,6 @@ from dbgpt.storage.metadata.meta_data import Base, engine
 # access to the values within the .ini file in use.
 config = context.config
 
-# Interpret the config file for Python logging.
-# This line sets up loggers basically.
-if config.config_file_name is not None:
-    fileConfig(config.config_file_name)
 
 # add your model's MetaData object here
 # for 'autogenerate' support