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refactor(openai): drop SDK dependency and switch to native HTTP client

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zhayujie
2026-04-27 20:21:54 +08:00
parent 5c65196e44
commit 8752f0cc60
8 changed files with 920 additions and 330 deletions
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161
models/chatgpt/chat_gpt_bot.py
View File

@@ -3,8 +3,15 @@
import time
import json
import openai
from models.openai.openai_compat import error as openai_error, RateLimitError, Timeout, APIError, APIConnectionError
from models.openai.openai_compat import (
error as openai_error,
RateLimitError,
Timeout,
APIError,
APIConnectionError,
wrap_http_error,
)
from models.openai.openai_http_client import OpenAIHTTPClient, OpenAIHTTPError
import requests
from common import const
from models.bot import Bot
@@ -23,18 +30,19 @@ from models.baidu.baidu_wenxin_session import BaiduWenxinSession
class ChatGPTBot(Bot, OpenAIImage, OpenAICompatibleBot):
def __init__(self):
super().__init__()
# set the default api_key / api_base based on bot_type
# Resolve api key / base from config (no global SDK state anymore).
if conf().get("bot_type") == "custom":
openai.api_key = conf().get("custom_api_key", "")
if conf().get("custom_api_base"):
openai.api_base = conf().get("custom_api_base")
self._api_key = conf().get("custom_api_key", "")
self._api_base = conf().get("custom_api_base") or None
else:
openai.api_key = conf().get("open_ai_api_key")
if conf().get("open_ai_api_base"):
openai.api_base = conf().get("open_ai_api_base")
proxy = conf().get("proxy")
if proxy:
openai.proxy = proxy
self._api_key = conf().get("open_ai_api_key")
self._api_base = conf().get("open_ai_api_base") or None
self._proxy = conf().get("proxy") or None
self._http_client = OpenAIHTTPClient(
api_key=self._api_key,
api_base=self._api_base,
proxy=self._proxy,
)
if conf().get("rate_limit_chatgpt"):
self.tb4chatgpt = TokenBucket(conf().get("rate_limit_chatgpt", 20))
conf_model = conf().get("model") or "gpt-3.5-turbo"
@@ -72,6 +80,10 @@ class ChatGPTBot(Bot, OpenAIImage, OpenAICompatibleBot):
'default_presence_penalty': conf().get("presence_penalty", 0.0),
}
def _get_http_client(self) -> OpenAIHTTPClient:
"""Override the default HTTP client to reuse our pre-configured one."""
return self._http_client
def reply(self, query, context=None):
# acquire reply content
if context.type == ContextType.TEXT:
@@ -195,20 +207,16 @@ class ChatGPTBot(Bot, OpenAIImage, OpenAICompatibleBot):
logger.info(f"[CHATGPT] Calling vision API with model: {model}")
# Call OpenAI API
kwargs = {
"model": model,
"messages": messages,
"max_tokens": 1000
}
if api_key:
kwargs["api_key"] = api_key
if api_base:
kwargs["api_base"] = api_base
# Call OpenAI-compatible API via HTTP
response = self._http_client.chat_completions(
api_key=api_key or None,
api_base=api_base or None,
model=model,
messages=messages,
max_tokens=1000,
)
response = openai.ChatCompletion.create(**kwargs)
content = response.choices[0]["message"]["content"]
content = response["choices"][0]["message"]["content"]
logger.info(f"[CHATGPT] Vision API response: {content[:100]}...")
# Clean up temp file
@@ -237,18 +245,37 @@ class ChatGPTBot(Bot, OpenAIImage, OpenAICompatibleBot):
try:
if conf().get("rate_limit_chatgpt") and not self.tb4chatgpt.get_token():
raise RateLimitError("RateLimitError: rate limit exceeded")
# if api_key == None, the default openai.api_key will be used
# If api_key is None, the per-instance default key will be used.
if args is None:
args = self.args
response = openai.ChatCompletion.create(api_key=api_key, messages=session.messages, **args)
# logger.debug("[CHATGPT] response={}".format(response))
logger.info("[ChatGPT] reply={}, total_tokens={}".format(response.choices[0]['message']['content'], response["usage"]["total_tokens"]))
# Translate old SDK kwargs to HTTP client params:
# - request_timeout / timeout -> per-call timeout
call_args = dict(args)
timeout = call_args.pop("request_timeout", None) or call_args.pop("timeout", None)
response = self._http_client.chat_completions(
api_key=api_key or None,
timeout=timeout,
messages=session.messages,
**call_args,
)
logger.info("[ChatGPT] reply={}, total_tokens={}".format(
response["choices"][0]["message"]["content"],
response["usage"]["total_tokens"]
))
return {
"total_tokens": response["usage"]["total_tokens"],
"completion_tokens": response["usage"]["completion_tokens"],
"content": response.choices[0]["message"]["content"],
"content": response["choices"][0]["message"]["content"],
}
except OpenAIHTTPError as http_err:
return self._handle_reply_error(
wrap_http_error(http_err), session, api_key, args, retry_count
)
except Exception as e:
return self._handle_reply_error(e, session, api_key, args, retry_count)
def _handle_reply_error(self, e, session, api_key, args, retry_count):
"""Map exception to user-facing reply with retry/backoff (mirrors SDK behavior)."""
need_retry = retry_count < 2
result = {"completion_tokens": 0, "content": "我现在有点累了，等会再来吧"}
if isinstance(e, RateLimitError):
@@ -261,16 +288,16 @@ class ChatGPTBot(Bot, OpenAIImage, OpenAICompatibleBot):
result["content"] = "我没有收到你的消息"
if need_retry:
time.sleep(5)
elif isinstance(e, APIError):
logger.warn("[CHATGPT] Bad Gateway: {}".format(e))
result["content"] = "请再问我一次"
if need_retry:
time.sleep(10)
elif isinstance(e, APIConnectionError):
logger.warn("[CHATGPT] APIConnectionError: {}".format(e))
result["content"] = "我连接不到你的网络"
if need_retry:
time.sleep(5)
elif isinstance(e, APIError):
logger.warn("[CHATGPT] Bad Gateway: {}".format(e))
result["content"] = "请再问我一次"
if need_retry:
time.sleep(10)
else:
logger.exception("[CHATGPT] Exception: {}".format(e))
need_retry = False
@@ -279,15 +306,39 @@ class ChatGPTBot(Bot, OpenAIImage, OpenAICompatibleBot):
if need_retry:
logger.warn("[CHATGPT] 第{}次重试".format(retry_count + 1))
return self.reply_text(session, api_key, args, retry_count + 1)
else:
return result
class AzureChatGPTBot(ChatGPTBot):
"""Azure OpenAI variant.
Azure's HTTP shape differs from public OpenAI:
URL : {endpoint}/openai/deployments/{deployment}/chat/completions
Auth : api-key header (not Bearer)
Query : ?api-version={version}
We model that with a dedicated HTTP client and override _get_http_client
so the OpenAICompatibleBot streaming/tool path uses it transparently.
"""
def __init__(self):
super().__init__()
openai.api_type = "azure"
openai.api_version = conf().get("azure_api_version", "2023-06-01-preview")
self.args["deployment_id"] = conf().get("azure_deployment_id")
self._azure_api_version = conf().get("azure_api_version", "2023-06-01-preview")
self._azure_deployment_id = conf().get("azure_deployment_id")
# Drop legacy SDK kwarg; Azure deployment is encoded in the URL now.
self.args.pop("deployment_id", None)
endpoint = (self._api_base or "").rstrip("/")
deployment = self._azure_deployment_id or ""
# Build a base that already includes /openai/deployments/{deployment}.
# /chat/completions will be appended by the client.
azure_base = (
f"{endpoint}/openai/deployments/{deployment}" if endpoint and deployment else endpoint
)
self._http_client = _AzureChatHTTPClient(
api_key=self._api_key,
api_base=azure_base,
api_version=self._azure_api_version,
proxy=self._proxy,
)
def create_img(self, query, retry_count=0, api_key=None):
text_to_image_model = conf().get("text_to_image")
@@ -357,3 +408,35 @@ class AzureChatGPTBot(ChatGPTBot):
return False, "图片生成失败"
else:
return False, "图片生成失败，未配置text_to_image参数"
class _AzureChatHTTPClient(OpenAIHTTPClient):
"""Subclass that injects Azure's ``api-version`` query param and ``api-key``
header on every chat-completion request, and accepts the deployment-scoped
base URL set by :class:`AzureChatGPTBot`.
"""
def __init__(self, api_key, api_base, api_version, proxy=None, timeout=None):
super().__init__(
api_key=api_key, api_base=api_base, proxy=proxy, timeout=timeout
)
self._api_version = api_version
def _build_headers(self, api_key, extra_headers):
# Azure uses api-key header, not Bearer token.
key = api_key if api_key is not None else self.api_key
headers = {"Content-Type": "application/json"}
if key:
headers["api-key"] = key
if self.extra_headers:
headers.update(self.extra_headers)
if extra_headers:
headers.update(extra_headers)
return headers
def chat_completions(self, **kwargs):
# Always force api-version query param for Azure.
eq = dict(kwargs.get("extra_query") or {})
eq.setdefault("api-version", self._api_version)
kwargs["extra_query"] = eq
return super().chat_completions(**kwargs)

144
models/openai/open_ai_bot.py
View File

@@ -2,8 +2,14 @@
import time
import openai
from models.openai.openai_compat import RateLimitError, Timeout, APIConnectionError
from models.openai.openai_compat import (
RateLimitError,
Timeout,
APIConnectionError,
APIError,
wrap_http_error,
)
from models.openai.openai_http_client import OpenAIHTTPClient, OpenAIHTTPError
from models.bot import Bot
from models.openai_compatible_bot import OpenAICompatibleBot
@@ -22,12 +28,14 @@ user_session = dict()
class OpenAIBot(Bot, OpenAIImage, OpenAICompatibleBot):
def __init__(self):
super().__init__()
openai.api_key = conf().get("open_ai_api_key")
if conf().get("open_ai_api_base"):
openai.api_base = conf().get("open_ai_api_base")
proxy = conf().get("proxy")
if proxy:
openai.proxy = proxy
self._api_key = conf().get("open_ai_api_key")
self._api_base = conf().get("open_ai_api_base") or None
self._proxy = conf().get("proxy") or None
self._http_client = OpenAIHTTPClient(
api_key=self._api_key,
api_base=self._api_base,
proxy=self._proxy,
)
self.sessions = SessionManager(OpenAISession, model=conf().get("model") or "text-davinci-003")
self.args = {
@@ -54,6 +62,10 @@ class OpenAIBot(Bot, OpenAIImage, OpenAICompatibleBot):
'default_presence_penalty': conf().get("presence_penalty", 0.0),
}
def _get_http_client(self) -> OpenAIHTTPClient:
"""Reuse the per-instance HTTP client for the streaming/tool path."""
return self._http_client
def reply(self, query, context=None):
# acquire reply content
if context and context.type:
@@ -96,8 +108,14 @@ class OpenAIBot(Bot, OpenAIImage, OpenAICompatibleBot):
def reply_text(self, session: OpenAISession, retry_count=0):
try:
response = openai.Completion.create(prompt=str(session), **self.args)
res_content = response.choices[0]["text"].strip().replace("<|endoftext|>", "")
call_args = dict(self.args)
timeout = call_args.pop("request_timeout", None) or call_args.pop("timeout", None)
response = self._http_client.completions(
timeout=timeout,
prompt=str(session),
**call_args,
)
res_content = response["choices"][0]["text"].strip().replace("<|endoftext|>", "")
total_tokens = response["usage"]["total_tokens"]
completion_tokens = response["usage"]["completion_tokens"]
logger.info("[OPEN_AI] reply={}".format(res_content))
@@ -106,7 +124,13 @@ class OpenAIBot(Bot, OpenAIImage, OpenAICompatibleBot):
"completion_tokens": completion_tokens,
"content": res_content,
}
except OpenAIHTTPError as http_err:
return self._handle_legacy_error(wrap_http_error(http_err), session, retry_count)
except Exception as e:
return self._handle_legacy_error(e, session, retry_count)
def _handle_legacy_error(self, e, session, retry_count):
"""Map exception -> reply for the legacy /completions endpoint."""
need_retry = retry_count < 2
result = {"completion_tokens": 0, "content": "我现在有点累了，等会再来吧"}
if isinstance(e, RateLimitError):
@@ -131,100 +155,10 @@ class OpenAIBot(Bot, OpenAIImage, OpenAICompatibleBot):
if need_retry:
logger.warn("[OPEN_AI] 第{}次重试".format(retry_count + 1))
return self.reply_text(session, retry_count + 1)
else:
return result
def call_with_tools(self, messages, tools=None, stream=False, **kwargs):
"""
Call OpenAI API with tool support for agent integration
Note: This bot uses the old Completion API which doesn't support tools.
For tool support, use ChatGPTBot instead.
This method converts to ChatCompletion API when tools are provided.
Args:
messages: List of messages
tools: List of tool definitions (OpenAI format)
stream: Whether to use streaming
**kwargs: Additional parameters
Returns:
Formatted response in OpenAI format or generator for streaming
"""
try:
# The old Completion API doesn't support tools
# We need to use ChatCompletion API instead
logger.info("[OPEN_AI] Using ChatCompletion API for tool support")
# Build request parameters for ChatCompletion
request_params = {
"model": kwargs.get("model", conf().get("model") or "gpt-4.1"),
"messages": messages,
"temperature": kwargs.get("temperature", conf().get("temperature", 0.9)),
"top_p": kwargs.get("top_p", 1),
"frequency_penalty": kwargs.get("frequency_penalty", conf().get("frequency_penalty", 0.0)),
"presence_penalty": kwargs.get("presence_penalty", conf().get("presence_penalty", 0.0)),
"stream": stream
}
# Add max_tokens if specified
if kwargs.get("max_tokens"):
request_params["max_tokens"] = kwargs["max_tokens"]
# Add tools if provided
if tools:
request_params["tools"] = tools
request_params["tool_choice"] = kwargs.get("tool_choice", "auto")
# Make API call using ChatCompletion
if stream:
return self._handle_stream_response(request_params)
else:
return self._handle_sync_response(request_params)
except Exception as e:
logger.error(f"[OPEN_AI] call_with_tools error: {e}")
if stream:
def error_generator():
yield {
"error": True,
"message": str(e),
"status_code": 500
}
return error_generator()
else:
return {
"error": True,
"message": str(e),
"status_code": 500
}
def _handle_sync_response(self, request_params):
"""Handle synchronous OpenAI ChatCompletion API response"""
try:
response = openai.ChatCompletion.create(**request_params)
logger.info(f"[OPEN_AI] call_with_tools reply, model={response.get('model')}, "
f"total_tokens={response.get('usage', {}).get('total_tokens', 0)}")
return response
except Exception as e:
logger.error(f"[OPEN_AI] sync response error: {e}")
raise
def _handle_stream_response(self, request_params):
"""Handle streaming OpenAI ChatCompletion API response"""
try:
stream = openai.ChatCompletion.create(**request_params)
for chunk in stream:
yield chunk
except Exception as e:
logger.error(f"[OPEN_AI] stream response error: {e}")
yield {
"error": True,
"message": str(e),
"status_code": 500
}
# NOTE: Tool-call routing is delegated to OpenAICompatibleBot.call_with_tools,
# which calls /chat/completions via our shared HTTP client. The previous
# bespoke implementation here bypassed Claude->OpenAI message/tool conversion
# and was effectively broken for agent flows; we now inherit the correct
# implementation from the base class.

41
models/openai/open_ai_image.py
View File

@@ -1,17 +1,25 @@
import time
import openai
from models.openai.openai_compat import RateLimitError
from common.log import logger
from common.token_bucket import TokenBucket
from config import conf
from models.openai.openai_compat import RateLimitError, wrap_http_error
from models.openai.openai_http_client import OpenAIHTTPClient, OpenAIHTTPError
# OPENAI提供的画图接口
# OpenAI image generation API wrapper
class OpenAIImage(object):
def __init__(self):
openai.api_key = conf().get("open_ai_api_key")
# Lazy default client; subclasses (ChatGPTBot/OpenAIBot) typically
# construct their own _http_client and override _get_image_client().
self._image_api_key = conf().get("open_ai_api_key")
self._image_api_base = conf().get("open_ai_api_base") or None
self._image_proxy = conf().get("proxy") or None
self._image_client = OpenAIHTTPClient(
api_key=self._image_api_key,
api_base=self._image_api_base,
proxy=self._image_proxy,
)
if conf().get("rate_limit_dalle"):
self.tb4dalle = TokenBucket(conf().get("rate_limit_dalle", 50))
@@ -20,23 +28,34 @@ class OpenAIImage(object):
if conf().get("rate_limit_dalle") and not self.tb4dalle.get_token():
return False, "请求太快了，请休息一下再问我吧"
logger.info("[OPEN_AI] image_query={}".format(query))
response = openai.Image.create(
api_key=api_key,
prompt=query, # 图片描述
n=1, # 每次生成图片的数量
response = self._image_client.images_generate(
api_key=api_key or None,
api_base=api_base or None,
prompt=query, # image description
n=1,
model=conf().get("text_to_image") or "dall-e-2",
# size=conf().get("image_create_size", "256x256"), # 图片大小,可选有 256x256, 512x512, 1024x1024
# size=conf().get("image_create_size", "256x256"),
)
image_url = response["data"][0]["url"]
logger.info("[OPEN_AI] image_url={}".format(image_url))
return True, image_url
except OpenAIHTTPError as http_err:
mapped = wrap_http_error(http_err)
if isinstance(mapped, RateLimitError):
logger.warn(mapped)
if retry_count < 1:
time.sleep(5)
logger.warn("[OPEN_AI] ImgCreate RateLimit exceed, 第{}次重试".format(retry_count + 1))
return self.create_img(query, retry_count + 1)
return False, "画图出现问题，请休息一下再问我吧"
logger.exception(mapped)
return False, "画图出现问题，请休息一下再问我吧"
except RateLimitError as e:
logger.warn(e)
if retry_count < 1:
time.sleep(5)
logger.warn("[OPEN_AI] ImgCreate RateLimit exceed, 第{}次重试".format(retry_count + 1))
return self.create_img(query, retry_count + 1)
else:
return False, "画图出现问题，请休息一下再问我吧"
except Exception as e:
logger.exception(e)

239
models/openai/openai_compat.py
View File

@@ -1,102 +1,163 @@
"""
OpenAI compatibility layer for different versions.
OpenAI-compatible exception layer.
This module provides a compatibility layer between OpenAI library versions:
- OpenAI < 1.0 (old API with openai.error module)
- OpenAI >= 1.0 (new API with direct exception imports)
This module used to bridge between openai SDK 0.x and 1.x exception types.
Since we no longer depend on the `openai` SDK at all (we call HTTP directly
via :mod:`models.openai.openai_http_client`), this file now provides:
1. Pure Python exception classes that match the *names* the rest of the
codebase already imports (RateLimitError / Timeout / APIError /
APIConnectionError / AuthenticationError / InvalidRequestError ...).
2. A :func:`map_http_error` helper that converts an
:class:`OpenAIHTTPError` (or any HTTP status code + message) into the
appropriate exception subclass, so existing ``except RateLimitError``
``except Timeout`` etc. blocks keep working unchanged.
This keeps the behavior of all existing bots (rate-limit backoff, timeout
retry, auth-error fast-fail) identical to the openai-SDK-based version, while
removing the hard dependency on the `openai` package.
"""
try:
# Try new OpenAI >= 1.0 API
from openai import (
OpenAIError,
RateLimitError,
APIError,
APIConnectionError,
AuthenticationError,
APITimeoutError,
BadRequestError,
)
from typing import Optional
# Create a mock error module for backward compatibility
class ErrorModule:
# --------------------------------------------------------------------------- #
# Exception hierarchy (mirrors openai SDK names so call sites don't change)
# --------------------------------------------------------------------------- #
class OpenAIError(Exception):
"""Base exception for all OpenAI-compatible API errors."""
def __init__(self, message: str = "", status_code: Optional[int] = None,
body=None):
super().__init__(message)
self.message = message
self.status_code = status_code
self.body = body
class APIError(OpenAIError):
"""Generic API error (5xx and unclassified errors)."""
class APIConnectionError(OpenAIError):
"""Network / connection failure (DNS, refused, reset...)."""
class Timeout(OpenAIError):
"""Request timeout. Aliased as APITimeoutError for new-SDK style imports."""
class AuthenticationError(OpenAIError):
"""401 Unauthorized."""
class PermissionDeniedError(OpenAIError):
"""403 Forbidden."""
class NotFoundError(OpenAIError):
"""404 Not Found."""
class InvalidRequestError(OpenAIError):
"""400 Bad Request. Aliased as BadRequestError."""
class RateLimitError(OpenAIError):
"""429 Too Many Requests."""
# Aliases used by some new-SDK-style code paths in the project.
APITimeoutError = Timeout
BadRequestError = InvalidRequestError
# --------------------------------------------------------------------------- #
# Backward-compat ``error`` module-style accessor
# --------------------------------------------------------------------------- #
# Some legacy code in the codebase (and possibly user plugins) does
# from models.openai.openai_compat import error
# except error.RateLimitError: ...
# Keep that path working by exposing an attribute namespace.
class _ErrorModule:
OpenAIError = OpenAIError
RateLimitError = RateLimitError
APIError = APIError
APIConnectionError = APIConnectionError
AuthenticationError = AuthenticationError
Timeout = APITimeoutError # Renamed in new version
InvalidRequestError = BadRequestError # Renamed in new version
error = ErrorModule()
# Also export with new names
Timeout = APITimeoutError
InvalidRequestError = BadRequestError
except ImportError:
# Fall back to old OpenAI < 1.0 API
try:
import openai.error as error
# Export individual exceptions for direct import
OpenAIError = error.OpenAIError
RateLimitError = error.RateLimitError
APIError = error.APIError
APIConnectionError = error.APIConnectionError
AuthenticationError = error.AuthenticationError
InvalidRequestError = error.InvalidRequestError
Timeout = error.Timeout
BadRequestError = error.InvalidRequestError # Alias
APITimeoutError = error.Timeout # Alias
except (ImportError, AttributeError):
# Neither version works, create dummy classes
class OpenAIError(Exception):
pass
class RateLimitError(OpenAIError):
pass
class APIError(OpenAIError):
pass
class APIConnectionError(OpenAIError):
pass
class AuthenticationError(OpenAIError):
pass
class InvalidRequestError(OpenAIError):
pass
class Timeout(OpenAIError):
pass
BadRequestError = InvalidRequestError
APITimeoutError = Timeout
# Create error module
class ErrorModule:
OpenAIError = OpenAIError
RateLimitError = RateLimitError
APIError = APIError
APIConnectionError = APIConnectionError
AuthenticationError = AuthenticationError
InvalidRequestError = InvalidRequestError
Timeout = Timeout
AuthenticationError = AuthenticationError
PermissionDeniedError = PermissionDeniedError
NotFoundError = NotFoundError
InvalidRequestError = InvalidRequestError
RateLimitError = RateLimitError
error = _ErrorModule()
# --------------------------------------------------------------------------- #
# HTTP -> exception mapping
# --------------------------------------------------------------------------- #
def map_http_error(status_code: Optional[int], message: str = "",
body=None) -> OpenAIError:
"""Convert an HTTP status (+ optional message/body) to the right subclass.
Used by HTTP-based bot wrappers so that downstream ``except RateLimitError``
blocks behave identically to when the openai SDK was raising them.
"""
sc = status_code or 0
msg = message or ""
msg_lower = msg.lower()
# Connection-level (no status / non-HTTP failure)
if sc == 0:
if "timeout" in msg_lower or "timed out" in msg_lower:
return Timeout(msg, sc, body)
return APIConnectionError(msg, sc, body)
if sc == 408:
return Timeout(msg, sc, body)
if sc == 401:
return AuthenticationError(msg, sc, body)
if sc == 403:
return PermissionDeniedError(msg, sc, body)
if sc == 404:
return NotFoundError(msg, sc, body)
if sc == 429:
return RateLimitError(msg, sc, body)
if 400 <= sc < 500:
return InvalidRequestError(msg, sc, body)
if sc >= 500:
return APIError(msg, sc, body)
return APIError(msg, sc, body)
def wrap_http_error(http_err) -> OpenAIError:
"""Adapter for :class:`OpenAIHTTPError` -> compat exception subclass.
Accepts any object with ``status_code`` / ``message`` / ``body`` attrs.
"""
sc = getattr(http_err, "status_code", None)
msg = getattr(http_err, "message", "") or str(http_err)
body = getattr(http_err, "body", None)
return map_http_error(sc, msg, body)
error = ErrorModule()
# Export all for easy import
__all__ = [
'error',
'OpenAIError',
'RateLimitError',
'APIError',
'APIConnectionError',
'AuthenticationError',
'InvalidRequestError',
'Timeout',
'BadRequestError',
'APITimeoutError',
"error",
"OpenAIError",
"APIError",
"APIConnectionError",
"Timeout",
"APITimeoutError",
"AuthenticationError",
"PermissionDeniedError",
"NotFoundError",
"InvalidRequestError",
"BadRequestError",
"RateLimitError",
"map_http_error",
"wrap_http_error",
]

456
models/openai/openai_http_client.py Normal file
View File

@@ -0,0 +1,456 @@
# encoding:utf-8
"""
Lightweight HTTP client for OpenAI-compatible APIs.
This client is a drop-in replacement for the parts of the `openai` SDK that this
project actually uses (chat completions, completions, image generation), so we
can drop the hard dependency on `openai==0.27.x`.
Design goals:
- Pure `requests` based (no httpx / pydantic / openai SDK dependency).
- Returns plain `dict` responses with the same shape OpenAI's HTTP API returns,
so existing code that does `response["choices"][0]["message"]["content"]` /
`response["usage"]["total_tokens"]` keeps working.
- Streaming yields plain `dict` chunks (parsed SSE `data:` JSON), matching the
shape that `agent/protocol/agent_stream.py` consumes:
chunk["choices"][0]["delta"]["content" | "tool_calls" | "reasoning_content"]
chunk["choices"][0]["finish_reason"]
Plus dict-style error chunks: {"error": True, "message": ..., "status_code": ...}
- Compatible with arbitrary OpenAI-compatible endpoints (LinkAI, Azure-style
proxies, DeepSeek, Moonshot, etc.) by allowing per-call api_key / api_base
override and trusting whatever path/payload shape the caller passes.
"""
import json
from typing import Any, Dict, Generator, Optional
import requests
from common.log import logger
DEFAULT_API_BASE = "https://api.openai.com/v1"
DEFAULT_TIMEOUT = 600 # seconds; matches old openai SDK default
class OpenAIHTTPError(Exception):
"""Raised for non-2xx responses. Carries status code + parsed body."""
def __init__(self, status_code: int, body: Any, message: str = ""):
self.status_code = status_code
self.body = body
# Try to extract human-readable message from OpenAI-style error envelope
if not message and isinstance(body, dict):
err = body.get("error") or {}
if isinstance(err, dict):
message = err.get("message") or ""
elif isinstance(err, str):
message = err
if not message:
message = str(body)[:500]
self.message = message
super().__init__(f"HTTP {status_code}: {message}")
class OpenAIHTTPClient:
"""Minimal HTTP client for OpenAI-compatible endpoints.
Per-instance defaults (api_key / api_base / proxy / timeout) can be
overridden on every call. Callers can also pass ``extra_headers`` for
Azure-style ``api-key`` headers or custom routing headers.
"""
def __init__(
self,
api_key: Optional[str] = None,
api_base: Optional[str] = None,
proxy: Optional[str] = None,
timeout: Optional[float] = None,
extra_headers: Optional[Dict[str, str]] = None,
):
self.api_key = api_key
self.api_base = (api_base or DEFAULT_API_BASE).rstrip("/")
self.timeout = timeout if timeout is not None else DEFAULT_TIMEOUT
self.proxies = (
{"http": proxy, "https": proxy} if proxy else None
)
self.extra_headers = dict(extra_headers) if extra_headers else {}
# ------------------------------------------------------------------ #
# Public API surface (mirrors what the old openai SDK provided)
# ------------------------------------------------------------------ #
def chat_completions(
self,
*,
api_key: Optional[str] = None,
api_base: Optional[str] = None,
timeout: Optional[float] = None,
proxy: Optional[str] = None,
extra_headers: Optional[Dict[str, str]] = None,
extra_query: Optional[Dict[str, str]] = None,
path: str = "/chat/completions",
stream: bool = False,
**payload,
):
"""POST /chat/completions.
When ``stream=True`` returns a generator yielding parsed SSE chunks
(plain ``dict``). On error during streaming, yields a single dict with
``{"error": True, ...}`` and stops, matching the contract expected by
``agent/protocol/agent_stream.py``.
"""
payload["stream"] = stream
return self._request(
path=path,
payload=payload,
api_key=api_key,
api_base=api_base,
timeout=timeout,
proxy=proxy,
extra_headers=extra_headers,
extra_query=extra_query,
stream=stream,
)
def completions(
self,
*,
api_key: Optional[str] = None,
api_base: Optional[str] = None,
timeout: Optional[float] = None,
**payload,
) -> Dict[str, Any]:
"""POST /completions (legacy text completion). Non-streaming only."""
payload.pop("stream", None)
return self._request(
path="/completions",
payload=payload,
api_key=api_key,
api_base=api_base,
timeout=timeout,
stream=False,
)
def images_generate(
self,
*,
api_key: Optional[str] = None,
api_base: Optional[str] = None,
timeout: Optional[float] = None,
**payload,
) -> Dict[str, Any]:
"""POST /images/generations."""
return self._request(
path="/images/generations",
payload=payload,
api_key=api_key,
api_base=api_base,
timeout=timeout,
stream=False,
)
# ------------------------------------------------------------------ #
# Internal helpers
# ------------------------------------------------------------------ #
def _build_headers(
self,
api_key: Optional[str],
extra_headers: Optional[Dict[str, str]],
) -> Dict[str, str]:
key = api_key if api_key is not None else self.api_key
headers = {"Content-Type": "application/json"}
if key:
headers["Authorization"] = f"Bearer {key}"
if self.extra_headers:
headers.update(self.extra_headers)
if extra_headers:
headers.update(extra_headers)
return headers
def _request(
self,
*,
path: str,
payload: Dict[str, Any],
api_key: Optional[str],
api_base: Optional[str],
timeout: Optional[float],
stream: bool,
proxy: Optional[str] = None,
extra_headers: Optional[Dict[str, str]] = None,
extra_query: Optional[Dict[str, str]] = None,
):
base = (api_base or self.api_base).rstrip("/") if api_base else self.api_base
url = f"{base}{path}" if path.startswith("/") else f"{base}/{path}"
headers = self._build_headers(api_key, extra_headers)
req_timeout = timeout if timeout is not None else self.timeout
proxies = (
{"http": proxy, "https": proxy} if proxy else self.proxies
)
# Drop None-valued keys; some providers reject explicit nulls.
clean_payload = {k: v for k, v in payload.items() if v is not None}
if stream:
# Return a generator. Errors during stream are yielded as a single
# error chunk so callers (agent_stream) can map them to their
# existing error-handling path without try/except around the loop.
return self._stream_chat(
url=url,
headers=headers,
payload=clean_payload,
proxies=proxies,
timeout=req_timeout,
params=extra_query,
)
try:
resp = requests.post(
url,
headers=headers,
json=clean_payload,
timeout=req_timeout,
proxies=proxies,
params=extra_query,
)
except requests.exceptions.Timeout as e:
raise OpenAIHTTPError(408, {}, f"Request timed out: {e}")
except requests.exceptions.ConnectionError as e:
raise OpenAIHTTPError(0, {}, f"Connection error: {e}")
except requests.exceptions.RequestException as e:
raise OpenAIHTTPError(0, {}, f"Request failed: {e}")
return self._parse_response(resp)
@staticmethod
def _parse_response(resp: requests.Response) -> Dict[str, Any]:
# Try JSON, fall back to text
try:
data = resp.json()
except ValueError:
data = {"raw": resp.text}
if resp.status_code >= 400:
raise OpenAIHTTPError(resp.status_code, data)
return data
def _stream_chat(
self,
*,
url: str,
headers: Dict[str, str],
payload: Dict[str, Any],
proxies: Optional[Dict[str, str]],
timeout: float,
params: Optional[Dict[str, str]] = None,
) -> Generator[Dict[str, Any], None, None]:
"""Stream SSE response and yield parsed JSON chunks.
Yields:
- Normal chunks: dict with ``choices[0].delta`` etc.
- Error chunks: ``{"error": True, "message": str, "status_code": int}``
followed by termination of the generator.
"""
try:
resp = requests.post(
url,
headers=headers,
json=payload,
timeout=timeout,
proxies=proxies,
stream=True,
params=params,
)
except requests.exceptions.Timeout as e:
yield self._make_error_chunk(408, f"Request timed out: {e}")
return
except requests.exceptions.ConnectionError as e:
yield self._make_error_chunk(0, f"Connection error: {e}")
return
except requests.exceptions.RequestException as e:
yield self._make_error_chunk(0, f"Request failed: {e}")
return
if resp.status_code >= 400:
# Read full body once for error reporting
try:
body = resp.json()
except ValueError:
body = {"raw": resp.text[:1000]}
err_msg = ""
err_code = ""
err_type = ""
if isinstance(body, dict):
err = body.get("error") or {}
if isinstance(err, dict):
err_msg = err.get("message") or ""
err_code = err.get("code") or ""
err_type = err.get("type") or ""
elif isinstance(err, str):
err_msg = err
if not err_msg:
err_msg = str(body)[:500]
yield {
"error": {
"message": err_msg,
"code": err_code,
"type": err_type,
},
# Top-level fields kept for backward compatibility with the
# error-shape that `_handle_stream_response` previously emitted.
"message": err_msg,
"status_code": resp.status_code,
}
return
# IMPORTANT: do NOT use `iter_lines(decode_unicode=True)`.
#
# `requests` decodes per-network-chunk using the response's declared
# encoding (often Latin-1 / ISO-8859-1 for SSE), which mangles UTF-8
# codepoints that straddle a chunk boundary. Some upstreams (Azure
# OpenAI proxies, Cloudflare-fronted gateways, ...) split TCP chunks
# aggressively in the middle of multibyte characters, producing
# garbled text and "skip malformed SSE chunk" errors.
#
# The fix is to read raw bytes, accumulate them until we have a
# complete SSE event (terminated by a blank line per the SSE spec:
# https://html.spec.whatwg.org/multipage/server-sent-events.html),
# and only THEN decode as UTF-8. This mirrors what the official
# openai SDK 1.x does in `openai/_streaming.py::SSEDecoder` (which
# itself is copied from httpx-sse).
try:
for sse_event in self._iter_sse_events(resp):
# `sse_event` is the joined `data:` payload as a str.
if sse_event == "[DONE]":
return
if not sse_event:
continue
try:
chunk = json.loads(sse_event)
except ValueError:
logger.debug(
f"[OpenAIHTTP] skip malformed SSE chunk: {sse_event[:200]}"
)
continue
yield chunk
except requests.exceptions.ChunkedEncodingError as e:
yield self._make_error_chunk(0, f"Stream interrupted: {e}")
except requests.exceptions.RequestException as e:
yield self._make_error_chunk(0, f"Stream error: {e}")
finally:
try:
resp.close()
except Exception:
pass
@staticmethod
def _iter_sse_events(resp: requests.Response) -> Generator[str, None, None]:
"""Decode an SSE byte stream into joined `data:` payloads.
Implements the subset of the SSE spec that OpenAI / OpenAI-compatible
endpoints actually use:
- Events are separated by blank lines (\\r\\r, \\n\\n, or \\r\\n\\r\\n).
- Within an event, multiple ``data:`` lines are concatenated with
"\\n" (per spec).
- ``event:``, ``id:``, ``retry:`` and comment lines (``:``) are
tolerated but not yielded — for chat-completion we only care
about the JSON payload in ``data:``.
- Bytes are buffered until a complete event boundary is seen so
UTF-8 codepoints split across TCP chunks decode correctly.
Yields each event's joined ``data`` string. The terminal sentinel
``[DONE]`` is yielded as a literal string so the caller can break.
"""
buf = b""
for raw in resp.iter_content(chunk_size=None, decode_unicode=False):
if not raw:
continue
buf += raw
# Find complete events (terminated by a blank line).
while True:
# Look for the earliest event terminator. SSE allows three
# forms; check all and pick the earliest match.
idx_nn = buf.find(b"\n\n")
idx_rr = buf.find(b"\r\r")
idx_rnrn = buf.find(b"\r\n\r\n")
candidates = [i for i in (idx_nn, idx_rr, idx_rnrn) if i != -1]
if not candidates:
break
# We need to know the length of the matched terminator to
# advance past it correctly.
end_pos = min(candidates)
if end_pos == idx_rnrn:
term_len = 4
else:
term_len = 2
event_bytes = buf[:end_pos]
buf = buf[end_pos + term_len:]
# Decode the full event as UTF-8. ``errors="replace"`` is a
# belt-and-suspenders safety net for truly malformed upstream
# bytes; it should never trigger for well-formed providers.
try:
event_text = event_bytes.decode("utf-8")
except UnicodeDecodeError:
event_text = event_bytes.decode("utf-8", errors="replace")
data_lines = []
for line in event_text.splitlines():
if not line or line.startswith(":"):
continue
field, _, value = line.partition(":")
# Per SSE spec, a single optional space after the colon
# is part of the framing, not the value.
if value.startswith(" "):
value = value[1:]
if field == "data":
data_lines.append(value)
# Other fields (event/id/retry) are intentionally ignored
# — chat-completion endpoints don't use them in a way we
# need for parsing.
if data_lines:
yield "\n".join(data_lines)
# Flush any trailing bytes the server forgot to terminate. This is
# rare but spec-allowed (some providers omit the final \n\n).
if buf.strip():
try:
event_text = buf.decode("utf-8")
except UnicodeDecodeError:
event_text = buf.decode("utf-8", errors="replace")
data_lines = []
for line in event_text.splitlines():
if not line or line.startswith(":"):
continue
field, _, value = line.partition(":")
if value.startswith(" "):
value = value[1:]
if field == "data":
data_lines.append(value)
if data_lines:
yield "\n".join(data_lines)
@staticmethod
def _make_error_chunk(status_code: int, message: str) -> Dict[str, Any]:
return {
"error": {"message": message, "code": "", "type": ""},
"message": message,
"status_code": status_code,
}
# A tiny helper for callers that just need a one-shot client without storing
# state. Keeps call sites cleaner than instantiating the class every time.
def get_default_client(
api_key: Optional[str] = None,
api_base: Optional[str] = None,
proxy: Optional[str] = None,
timeout: Optional[float] = None,
) -> OpenAIHTTPClient:
return OpenAIHTTPClient(
api_key=api_key, api_base=api_base, proxy=proxy, timeout=timeout
)

90
models/openai_compatible_bot.py
View File

@@ -8,11 +8,11 @@ This includes: OpenAI, LinkAI, Azure OpenAI, and many third-party providers.
"""
import json
import openai
import requests
from typing import Optional
from common.log import logger
from agent.protocol.message_utils import drop_orphaned_tool_results_openai
from models.openai.openai_http_client import OpenAIHTTPClient, OpenAIHTTPError
class OpenAICompatibleBot:
@@ -135,49 +135,87 @@ class OpenAICompatibleBot:
"status_code": 500
}
def _get_http_client(self) -> OpenAIHTTPClient:
"""Build an HTTP client honoring the global proxy config.
Subclasses can override this for custom auth headers (e.g. Azure's
``api-key`` header) by returning a pre-configured client.
"""
from config import conf
proxy = conf().get("proxy") or None
return OpenAIHTTPClient(proxy=proxy)
def _handle_sync_response(self, request_params, api_key, api_base):
"""Handle synchronous OpenAI API response"""
"""Handle synchronous chat-completion via HTTP."""
params = dict(request_params)
params.pop("stream", None)
# Translate legacy SDK timeout kwarg to our HTTP client kwarg.
timeout = params.pop("request_timeout", None) or params.pop("timeout", None)
try:
# Build kwargs with explicit API configuration
kwargs = dict(request_params)
if api_key:
kwargs["api_key"] = api_key
if api_base:
kwargs["api_base"] = api_base
response = openai.ChatCompletion.create(**kwargs)
return response
client = self._get_http_client()
return client.chat_completions(
api_key=api_key,
api_base=api_base,
timeout=timeout,
stream=False,
**params,
)
except OpenAIHTTPError as e:
logger.error(
f"[{self.__class__.__name__}] sync response error: "
f"HTTP {e.status_code}: {e.message}"
)
return {
"error": True,
"message": e.message,
"status_code": e.status_code or 500,
}
except Exception as e:
logger.error(f"[{self.__class__.__name__}] sync response error: {e}")
return {
"error": True,
"message": str(e),
"status_code": 500
"status_code": 500,
}
def _handle_stream_response(self, request_params, api_key, api_base):
"""Handle streaming OpenAI API response"""
"""Handle streaming chat-completion via HTTP (SSE).
Yields dict chunks in OpenAI's standard streaming shape:
{"choices": [{"delta": {...}, "finish_reason": ...}], ...}
On error, yields a single ``{"error": ..., "status_code": ...}`` chunk
— the same contract :mod:`agent.protocol.agent_stream` already handles.
"""
params = dict(request_params)
params.pop("stream", None)
timeout = params.pop("request_timeout", None) or params.pop("timeout", None)
try:
# Build kwargs with explicit API configuration
kwargs = dict(request_params)
if api_key:
kwargs["api_key"] = api_key
if api_base:
kwargs["api_base"] = api_base
stream = openai.ChatCompletion.create(**kwargs)
# Stream chunks to caller
client = self._get_http_client()
stream = client.chat_completions(
api_key=api_key,
api_base=api_base,
timeout=timeout,
stream=True,
**params,
)
for chunk in stream:
yield chunk
except OpenAIHTTPError as e:
logger.error(
f"[{self.__class__.__name__}] stream response error: "
f"HTTP {e.status_code}: {e.message}"
)
yield {
"error": True,
"message": e.message,
"status_code": e.status_code or 500,
}
except Exception as e:
logger.error(f"[{self.__class__.__name__}] stream response error: {e}")
yield {
"error": True,
"message": str(e),
"status_code": 500
"status_code": 500,
}
def _convert_tools_to_openai_format(self, tools):

1
requirements.txt
View File

@@ -1,4 +1,3 @@
openai==0.27.8
aiohttp>=3.8.6,<3.10
requests>=2.28.2
chardet>=5.1.0

6
voice/openai/openai_voice.py
View File

@@ -3,8 +3,6 @@ google voice service
"""
import json
import openai
from bridge.reply import Reply, ReplyType
from common.log import logger
from config import conf
@@ -15,7 +13,9 @@ import datetime, random
class OpenaiVoice(Voice):
def __init__(self):
openai.api_key = conf().get("open_ai_api_key")
# No-op: this implementation calls OpenAI HTTP endpoints directly via
# `requests`, so it does not need a global SDK to be configured.
pass
def voiceToText(self, voice_file):
logger.debug("[Openai] voice file name={}".format(voice_file))