增加xAI模型支持

推荐llm-models.json新增
```json
,
        {
            "name": "grok-2-vision-1212",
            "model_name": "grok-2-vision-1212",
            "requester": "grok-chat-completions",
            "token_mgr": "grok",
            "vision_supported": true
        }
```
provider.json requester增加
```json
,
        "grok-chat-completions": {
            "args": {},
            "base-url": "https://api.x.ai/v1",
            "timeout": 120
        }
```
keys增加:
```json
,
"grok": [
            "xai-your-key"
        ]
```

pkg/provider/modelmgr/modelmgr.py

@@ -6,7 +6,7 @@ from . import entities, requester
 from ...core import app
 
 from . import token
-from .requesters import chatcmpl, anthropicmsgs, moonshotchatcmpl, deepseekchatcmpl, ollamachat, giteeaichatcmpl
+from .requesters import chatcmpl, anthropicmsgs, moonshotchatcmpl, deepseekchatcmpl, ollamachat, giteeaichatcmpl, grokchatcmpl
 
 FETCH_MODEL_LIST_URL = "https://api.qchatgpt.rockchin.top/api/v2/fetch/model_list"
 

pkg/provider/modelmgr/requesters/grokchatcmpl.py

@@ -0,0 +1,144 @@
+from __future__ import annotations
+
+import asyncio
+import typing
+import json
+import base64
+from typing import AsyncGenerator
+
+import openai
+import openai.types.chat.chat_completion as chat_completion
+import httpx
+import aiohttp
+import async_lru
+
+from .. import entities, errors, requester
+from ....core import entities as core_entities, app
+from ... import entities as llm_entities
+from ...tools import entities as tools_entities
+from ....utils import image
+
+
+@requester.requester_class("grok-chat-completions")
+class GrokChatCompletions(requester.LLMAPIRequester):
+    """grok ChatCompletion API 请求器"""
+
+    client: openai.AsyncClient
+
+    requester_cfg: dict
+
+    def __init__(self, ap: app.Application):
+        self.ap = ap
+
+        self.requester_cfg = self.ap.provider_cfg.data['requester']['grok-chat-completions']
+
+    async def initialize(self):
+
+        self.client = openai.AsyncClient(
+            api_key="",
+            base_url=self.requester_cfg['base-url'],
+            timeout=self.requester_cfg['timeout'],
+            http_client=httpx.AsyncClient(
+                proxies=self.ap.proxy_mgr.get_forward_proxies()
+            )
+        )
+
+    async def _req(
+        self,
+        args: dict,
+    ) -> chat_completion.ChatCompletion:
+        return await self.client.chat.completions.create(**args)
+
+    async def _make_msg(
+        self,
+        chat_completion: chat_completion.ChatCompletion,
+    ) -> llm_entities.Message:
+        chatcmpl_message = chat_completion.choices[0].message.dict()
+
+        # 确保 role 字段存在且不为 None
+        if 'role' not in chatcmpl_message or chatcmpl_message['role'] is None:
+            chatcmpl_message['role'] = 'assistant'
+
+        message = llm_entities.Message(**chatcmpl_message)
+
+        return message
+
+    async def _closure(
+        self,
+        req_messages: list[dict],
+        use_model: entities.LLMModelInfo,
+        use_funcs: list[tools_entities.LLMFunction] = None,
+    ) -> llm_entities.Message:
+        self.client.api_key = use_model.token_mgr.get_token()
+
+        args = self.requester_cfg['args'].copy()
+        args["model"] = use_model.name if use_model.model_name is None else use_model.model_name
+
+        if use_funcs:
+            tools = await self.ap.tool_mgr.generate_tools_for_openai(use_funcs)
+
+            if tools:
+                args["tools"] = tools
+
+        # 设置此次请求中的messages
+        messages = req_messages.copy()
+
+        # 检查vision
+        for msg in messages:
+            if 'content' in msg and isinstance(msg["content"], list):
+                for me in msg["content"]:
+                    if me["type"] == "image_url":
+                        me["image_url"]['url'] = await self.get_base64_str(me["image_url"]['url'])
+
+        args["messages"] = messages
+
+        # 发送请求
+        resp = await self._req(args)
+
+        # 处理请求结果
+        message = await self._make_msg(resp)
+
+        return message
+    
+    async def call(
+        self,
+        model: entities.LLMModelInfo,
+        messages: typing.List[llm_entities.Message],
+        funcs: typing.List[tools_entities.LLMFunction] = None,
+    ) -> llm_entities.Message:
+        req_messages = []  # req_messages 仅用于类内，外部同步由 query.messages 进行
+        for m in messages:
+            msg_dict = m.dict(exclude_none=True)
+            content = msg_dict.get("content")
+            if isinstance(content, list):
+                # 检查 content 列表中是否每个部分都是文本
+                if all(isinstance(part, dict) and part.get("type") == "text" for part in content):
+                    # 将所有文本部分合并为一个字符串
+                    msg_dict["content"] = "\n".join(part["text"] for part in content)
+            req_messages.append(msg_dict)
+
+        try:
+            return await self._closure(req_messages, model, funcs)
+        except asyncio.TimeoutError:
+            raise errors.RequesterError('请求超时')
+        except openai.BadRequestError as e:
+            if 'context_length_exceeded' in e.message:
+                raise errors.RequesterError(f'上文过长，请重置会话: {e.message}')
+            else:
+                raise errors.RequesterError(f'请求参数错误: {e.message}')
+        except openai.AuthenticationError as e:
+            raise errors.RequesterError(f'无效的 api-key: {e.message}')
+        except openai.NotFoundError as e:
+            raise errors.RequesterError(f'请求路径错误: {e.message}')
+        except openai.RateLimitError as e:
+            raise errors.RequesterError(f'请求过于频繁或余额不足: {e.message}')
+        except openai.APIError as e:
+            raise errors.RequesterError(f'请求错误: {e.message}')
+
+    @async_lru.alru_cache(maxsize=128)
+    async def get_base64_str(
+        self,
+        original_url: str,
+    ) -> str:
+        base64_image, image_format = await image.qq_image_url_to_base64(original_url)
+        return f"data:image/{image_format};base64,{base64_image}"