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146 lines
5.1 KiB
Python
146 lines
5.1 KiB
Python
from __future__ import annotations
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import asyncio
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import typing
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import json
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import base64
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from typing import AsyncGenerator
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import openai
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import openai.types.chat.chat_completion as chat_completion
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import httpx
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import aiohttp
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import async_lru
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from . import chatcmpl
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from .. import entities, errors, requester
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from ....core import entities as core_entities, app
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from ... import entities as llm_entities
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from ...tools import entities as tools_entities
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from ....utils import image
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@requester.requester_class("xai-chat-completions")
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class XaiChatCompletions(chatcmpl.OpenAIChatCompletions):
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"""xAI ChatCompletion API 请求器"""
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client: openai.AsyncClient
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requester_cfg: dict
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def __init__(self, ap: app.Application):
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self.ap = ap
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self.requester_cfg = self.ap.provider_cfg.data['requester']['xai-chat-completions']
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# async def initialize(self):
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# self.client = openai.AsyncClient(
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# api_key="",
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# base_url=self.requester_cfg['base-url'],
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# timeout=self.requester_cfg['timeout'],
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# http_client=httpx.AsyncClient(
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# proxies=self.ap.proxy_mgr.get_forward_proxies()
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# )
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# )
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# async def _req(
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# self,
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# args: dict,
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# ) -> chat_completion.ChatCompletion:
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# return await self.client.chat.completions.create(**args)
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# async def _make_msg(
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# self,
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# chat_completion: chat_completion.ChatCompletion,
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# ) -> llm_entities.Message:
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# chatcmpl_message = chat_completion.choices[0].message.dict()
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# # 确保 role 字段存在且不为 None
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# if 'role' not in chatcmpl_message or chatcmpl_message['role'] is None:
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# chatcmpl_message['role'] = 'assistant'
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# message = llm_entities.Message(**chatcmpl_message)
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# return message
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# async def _closure(
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# self,
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# req_messages: list[dict],
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# use_model: entities.LLMModelInfo,
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# use_funcs: list[tools_entities.LLMFunction] = None,
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# ) -> llm_entities.Message:
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# self.client.api_key = use_model.token_mgr.get_token()
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# args = self.requester_cfg['args'].copy()
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# args["model"] = use_model.name if use_model.model_name is None else use_model.model_name
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# if use_funcs:
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# tools = await self.ap.tool_mgr.generate_tools_for_openai(use_funcs)
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# if tools:
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# args["tools"] = tools
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# # 设置此次请求中的messages
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# messages = req_messages.copy()
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# # 检查vision
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# for msg in messages:
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# if 'content' in msg and isinstance(msg["content"], list):
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# for me in msg["content"]:
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# if me["type"] == "image_url":
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# me["image_url"]['url'] = await self.get_base64_str(me["image_url"]['url'])
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# args["messages"] = messages
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# # 发送请求
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# resp = await self._req(args)
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# # 处理请求结果
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# message = await self._make_msg(resp)
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# return message
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# async def call(
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# self,
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# model: entities.LLMModelInfo,
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# messages: typing.List[llm_entities.Message],
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# funcs: typing.List[tools_entities.LLMFunction] = None,
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# ) -> llm_entities.Message:
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# req_messages = [] # req_messages 仅用于类内，外部同步由 query.messages 进行
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# for m in messages:
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# msg_dict = m.dict(exclude_none=True)
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# content = msg_dict.get("content")
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# if isinstance(content, list):
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# # 检查 content 列表中是否每个部分都是文本
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# if all(isinstance(part, dict) and part.get("type") == "text" for part in content):
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# # 将所有文本部分合并为一个字符串
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# msg_dict["content"] = "\n".join(part["text"] for part in content)
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# req_messages.append(msg_dict)
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# try:
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# return await self._closure(req_messages, model, funcs)
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# except asyncio.TimeoutError:
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# raise errors.RequesterError('请求超时')
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# except openai.BadRequestError as e:
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# if 'context_length_exceeded' in e.message:
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# raise errors.RequesterError(f'上文过长，请重置会话: {e.message}')
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# else:
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# raise errors.RequesterError(f'请求参数错误: {e.message}')
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# except openai.AuthenticationError as e:
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# raise errors.RequesterError(f'无效的 api-key: {e.message}')
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# except openai.NotFoundError as e:
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# raise errors.RequesterError(f'请求路径错误: {e.message}')
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# except openai.RateLimitError as e:
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# raise errors.RequesterError(f'请求过于频繁或余额不足: {e.message}')
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# except openai.APIError as e:
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# raise errors.RequesterError(f'请求错误: {e.message}')
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# @async_lru.alru_cache(maxsize=128)
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# async def get_base64_str(
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# self,
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# original_url: str,
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# ) -> str:
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# base64_image, image_format = await image.qq_image_url_to_base64(original_url)
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# return f"data:image/{image_format};base64,{base64_image}"
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