├── .gitignore
├── ChatBridge_APIHijackForwarder.py
├── LICENSE
├── README.md
├── index.html
├── index.js
├── manifest.json
├── settings.json.template
└── style.css
/.gitignore:
--------------------------------------------------------------------------------
1 | *.secret
2 | settings.json
3 | .settings.json
4 | *.old
5 | olds
6 | settings.json
7 | SECRET/
8 | apicheck.py
9 | apiTest.py
--------------------------------------------------------------------------------
/ChatBridge_APIHijackForwarder.py:
--------------------------------------------------------------------------------
1 | """
2 | sequenceDiagram
3 | participant User as 外部应用
4 | participant UserAPI as 用户接口
5 | participant WS as WebSocket
6 | participant ST as SillyTavern
7 | participant STAPI as ST接口
8 | participant LLMAPI as LLM接口
9 | participant LLM as 外部LLM
10 |
11 | USER,ST,LLM均属外部逻辑,此脚本不应包含具体实现
12 |
13 | User->>UserAPI: 1.调用API(OpenAI格式)
14 | UserAPI->>WS: 2.转发请求到WebSocket
15 | WS->>ST: 3.通知ST处理请求
16 | ST->>STAPI: 4.处理后调用ST接口
17 | STAPI->>LLMAPI: 5.转发到LLM接口
18 | LLMAPI->>LLM: 6.调用外部LLM
19 | LLM-->>LLMAPI: 7.返回响应
20 | LLMAPI-┬->>STAPI: 8a.转发响应
21 | └->>UserAPI: 8b.同时转发响应
22 | STAPI-->ST: 9a.返回给ST
23 | UserAPI-->>User: 9b.返回给用户
24 | """
25 | # "REMOVED",
26 | # "base_url": "https://api.aiuvdt.top",
27 | #
28 | #"base_url": "https://generativelanguage.googleapis.com/v1beta/openai",
29 | import json
30 | import asyncio
31 | import websockets
32 | import aiohttp
33 | import logging
34 | import os
35 | from collections import deque
36 | import uuid
37 | from aiohttp import web
38 | from typing import List, Dict, Any
39 |
40 | logging.basicConfig(level=logging.INFO)
41 | logger = logging.getLogger(__name__)
42 |
43 | class APIKeyRotator:
44 | def __init__(self, api_keys: List[str]):
45 | self.api_keys = deque(api_keys)
46 |
47 | def get_next_key(self) -> str:
48 | current_key = self.api_keys[0]
49 | self.api_keys.rotate(-1)
50 | return current_key
51 |
52 | class ChatBridgeForwarder:
53 | def __init__(self, settings_path: str):
54 | with open(settings_path, 'r') as f:
55 | self.settings = json.load(f)
56 |
57 | self.ws_clients = set()
58 | self.key_rotator = APIKeyRotator(self.settings['llm_api']['api_keys'])
59 | self.response_futures = {}
60 |
61 | async def start(self):
62 | # 启动WebSocket服务器
63 | ws_server = websockets.serve(
64 | self.handle_websocket,
65 | self.settings['websocket']['host'],
66 | self.settings['websocket']['port']
67 | )
68 |
69 | # 创建ST API服务器
70 | st_app = web.Application()
71 | # 修改路由处理
72 | st_app.router.add_get('/models', self.handle_models)
73 | st_app.router.add_get('/v1/models', self.handle_models)
74 | st_app.router.add_post('/chat/completions', self.handle_chat_completions)
75 | st_app.router.add_post('/v1/chat/completions', self.handle_chat_completions)
76 |
77 | #初始化ST API服务器
78 | st_runner = web.AppRunner(st_app)
79 | await st_runner.setup()
80 | st_site = web.TCPSite(
81 | st_runner,
82 | self.settings['st_api']['host'],
83 | self.settings['st_api']['port']
84 | )
85 |
86 | # 创建用户API服务器
87 | user_app = web.Application()
88 | user_app.router.add_post('/v1/chat/completions', self.handle_user_api)
89 | user_runner = web.AppRunner(user_app)
90 | await user_runner.setup()
91 | user_site = web.TCPSite(
92 | user_runner,
93 | self.settings['user_api']['host'],
94 | self.settings['user_api']['port']
95 | )
96 |
97 | # 启动所有服务器
98 | await asyncio.gather(
99 | ws_server,
100 | st_site.start(),
101 | user_site.start()
102 | )
103 |
104 | logger.info(f"WebSocket服务器运行在 ws://{self.settings['websocket']['host']}:{self.settings['websocket']['port']}")
105 | logger.info(f"ST API服务器运行在 http://{self.settings['st_api']['host']}:{self.settings['st_api']['port']}")
106 | logger.info(f"用户API服务器运行在 http://{self.settings['user_api']['host']}:{self.settings['user_api']['port']}")
107 |
108 | async def handle_websocket(self, websocket):
109 | self.ws_clients.add(websocket)
110 | try:
111 | async for message in websocket:
112 | try:
113 | data = json.loads(message)
114 | logger.info(f"收到WebSocket消息: {data}")
115 |
116 | # 处理ST的响应
117 | if data.get('type') == 'st_response':
118 | request_id = data.get('id')
119 | if request_id in self.response_futures:
120 | future = self.response_futures[request_id]
121 | if not future.done():
122 | future.set_result(data.get('content'))
123 |
124 | except json.JSONDecodeError:
125 | logger.error("无效的WebSocket消息格式")
126 | finally:
127 | self.ws_clients.remove(websocket)
128 |
129 | async def handle_user_api(self, request: web.Request) -> web.Response:
130 | """处理来自用户的API请求"""
131 | if request.headers.get('Authorization') != f"Bearer {self.settings['user_api']['api_key']}":
132 | return web.Response(status=401)
133 |
134 | try:
135 | request_data = await request.json()
136 | request_id = str(uuid.uuid4())
137 | is_stream = request_data.get('stream', False)
138 | logger.info(f"用户API请求 ID={request_id}, stream={is_stream}")
139 |
140 | if is_stream:
141 | # 创建流式响应
142 | stream_response = web.StreamResponse(
143 | status=200,
144 | headers={
145 | 'Content-Type': 'text/event-stream',
146 | 'Cache-Control': 'no-cache',
147 | 'Connection': 'keep-alive'
148 | }
149 | )
150 | await stream_response.prepare(request)
151 |
152 | # 创建事件队列
153 | queue = asyncio.Queue()
154 | self.response_futures[request_id] = queue
155 |
156 | try:
157 | # 发送WebSocket消息
158 | ws_message = {
159 | 'type': 'user_request',
160 | 'id': request_id,
161 | 'content': request_data
162 | }
163 |
164 | if not self.ws_clients:
165 | return web.Response(status=503, text="No WebSocket clients connected")
166 |
167 | for ws in self.ws_clients:
168 | try:
169 | await ws.send(json.dumps(ws_message))
170 | logger.info(f"已发送请求到WebSocket: ID={request_id}")
171 | break
172 | except Exception as e:
173 | logger.error(f"发送WebSocket消息失败: {e}")
174 | continue
175 |
176 | # 等待并转发响应块
177 | received_chunks = []
178 | while True:
179 | try:
180 | chunk = await asyncio.wait_for(queue.get(), timeout=60.0)
181 |
182 | # 只处理非空的有效数据
183 | if chunk and isinstance(chunk, str):
184 | chunk = chunk.strip()
185 | if not chunk:
186 | continue
187 |
188 | if chunk == '[DONE]':
189 | await stream_response.write(b'data: [DONE]\n\n')
190 | logger.info(f"发送流式响应结束标记: ID={request_id}")
191 | break
192 |
193 | # 确保响应格式正确
194 | if not chunk.startswith('data: '):
195 | chunk = f'data: {chunk}'
196 | if not chunk.endswith('\n\n'):
197 | chunk = f'{chunk}\n\n'
198 |
199 | logger.debug(f"发送响应块: {chunk.strip()}")
200 | await stream_response.write(chunk.encode())
201 |
202 | except asyncio.TimeoutError:
203 | logger.warning(f"等待响应块超时: ID={request_id}")
204 | await stream_response.write(b'data: [DONE]\n\n')
205 | break
206 |
207 | return stream_response
208 |
209 | finally:
210 | # 清理队列
211 | self.response_futures.pop(request_id, None)
212 | else:
213 | # 处理非流式请求
214 | future = asyncio.Future()
215 | self.response_futures[request_id] = future
216 |
217 | # 发送WebSocket消息
218 | ws_message = {
219 | 'type': 'user_request',
220 | 'id': request_id,
221 | 'content': request_data
222 | }
223 |
224 | if not self.ws_clients:
225 | return web.Response(status=503, text="No WebSocket clients connected")
226 |
227 | for ws in self.ws_clients:
228 | try:
229 | await ws.send(json.dumps(ws_message))
230 | logger.info(f"已发送请求到WebSocket: ID={request_id}")
231 | break
232 | except Exception as e:
233 | logger.error(f"发送WebSocket消息失败: {e}")
234 | continue
235 |
236 | try:
237 | # 等待响应
238 | response = await asyncio.wait_for(future, timeout=60.0)
239 | return web.json_response(response)
240 | finally:
241 | self.response_futures.pop(request_id, None)
242 |
243 | except Exception as e:
244 | logger.error(f"处理用户API请求失败: {str(e)}", exc_info=True)
245 | return web.Response(status=500, text=f"Internal Server Error: {str(e)}")
246 |
247 | async def handle_models(self, request: web.Request) -> web.Response:
248 | """处理模型列表请求"""
249 | logger.info(f"收到models请求: {request.path}")
250 | api_key = self.key_rotator.get_next_key()
251 | headers = {
252 | 'Authorization': f'Bearer {api_key}',
253 | 'Content-Type': 'application/json'
254 | }
255 |
256 | try:
257 | async with aiohttp.ClientSession() as session:
258 | #remove v1/ of llm_api
259 | target_url = f"{self.settings['llm_api']['base_url']}/models"
260 | logger.info(f"转发请求到: {target_url}")
261 | async with session.get(target_url, headers=headers) as response:
262 | response_data = await response.json()
263 | logger.info(f"模型列表响应: {response_data}")
264 | return web.json_response(response_data)
265 | except Exception as e:
266 | logger.error(f"获取模型列表失败: {str(e)}")
267 | return web.Response(status=500, text=str(e))
268 |
269 | async def handle_chat_completions(self, request: web.Request) -> web.Response:
270 | try:
271 | request_data = await request.json()
272 | is_stream = request_data.get('stream', False)
273 | logger.info(f"收到chat completion请求: PATH={request.path}, STREAM={is_stream}")
274 |
275 | # 找到活跃的用户请求
276 | active_user_futures = {
277 | rid: future for rid, future in self.response_futures.items()
278 | if not getattr(future, 'done', lambda: True)()
279 | }
280 |
281 | if active_user_futures:
282 | logger.info(f"找到 {len(active_user_futures)} 个活跃的用户请求")
283 | else:
284 | logger.warning("没有找到活跃的用户请求")
285 |
286 | api_key = self.key_rotator.get_next_key()
287 | headers = {
288 | 'Authorization': f'Bearer {api_key}',
289 | 'Content-Type': 'application/json'
290 | }
291 | target_url = f"{self.settings['llm_api']['base_url']}/chat/completions"
292 |
293 | async with aiohttp.ClientSession() as session:
294 | async with session.post(target_url, json=request_data, headers=headers) as llm_response:
295 | if llm_response.headers.get('content-type') == 'text/event-stream':
296 | logger.info("处理流式响应")
297 | st_response = web.StreamResponse(
298 | status=llm_response.status,
299 | headers={'Content-Type': 'text/event-stream'}
300 | )
301 | await st_response.prepare(request)
302 |
303 | active_user_queues = {
304 | rid: queue for rid, queue in self.response_futures.items()
305 | if isinstance(queue, asyncio.Queue)
306 | }
307 |
308 | async for chunk in llm_response.content:
309 | if chunk:
310 | chunk_str = chunk.decode()
311 | logger.debug(f"收到数据块: {chunk_str[:100]}...")
312 |
313 | # 发送到ST
314 | await st_response.write(chunk)
315 |
316 | # 转发到用户队列
317 | if active_user_queues:
318 | for queue_id, queue in active_user_queues.items():
319 | try:
320 | await queue.put(chunk_str)
321 | logger.debug(f"转发数据块到用户队列 {queue_id}")
322 | except Exception as e:
323 | logger.error(f"转发到用户队列失败 {queue_id}: {e}")
324 |
325 | # 发送结束标记
326 | if active_user_queues:
327 | for queue_id, queue in active_user_queues.items():
328 | try:
329 | await queue.put('[DONE]')
330 | logger.info(f"发送结束标记到用户队列 {queue_id}")
331 | except Exception as e:
332 | logger.error(f"发送结束标记失败 {queue_id}: {e}")
333 |
334 | return st_response
335 |
336 | else:
337 | logger.info("处理非流式响应")
338 | response_data = await llm_response.json()
339 | logger.info(f"收到LLM响应: {str(response_data)[:200]}...")
340 |
341 | # 转发到所有等待的用户请求
342 | futures_updated = False
343 | for request_id, future in list(active_user_futures.items()):
344 | try:
345 | if isinstance(future, asyncio.Future) and not future.done():
346 | future.set_result(response_data)
347 | logger.info(f"成功设置用户请求结果: ID={request_id}")
348 | futures_updated = True
349 | except Exception as e:
350 | logger.error(f"设置用户请求结果失败 {request_id}: {e}")
351 |
352 | if not futures_updated:
353 | logger.warning("没有成功更新任何用户请求的结果")
354 |
355 | return web.json_response(response_data, status=llm_response.status)
356 |
357 | except Exception as e:
358 | error_msg = f"处理聊天完成请求失败: {str(e)}"
359 | logger.error(error_msg, exc_info=True)
360 | return web.Response(status=500, text=error_msg)
361 |
362 | async def main():
363 | settings_path = os.path.join(os.path.dirname(__file__), 'settings.json')
364 | forwarder = ChatBridgeForwarder(settings_path)
365 | await forwarder.start()
366 | try:
367 | await asyncio.Future() # 保持服务器运行
368 | except KeyboardInterrupt:
369 | pass
370 |
371 | if __name__ == "__main__":
372 | asyncio.run(main())
373 |
--------------------------------------------------------------------------------
/LICENSE:
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--------------------------------------------------------------------------------
/README.md:
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1 | # SillyTavern Extension - ChatBridge
2 |
3 | 一个用于SillyTavern的API桥接扩展，让外部应用（如qq机器人）能够复用SillyTavern的对话功能，像调用api一样在SillyTavern中聊天。
4 |
5 | An API bridging extension for SillyTavern that allows external applications to reuse SillyTavern's conversation functionality, enabling chat in SillyTavern as if calling an API.
6 |
7 | ## 简介 / Introduction
8 | > *我很高兴地宣布我写完了此项目的主要功能，这是最新的更新，和之前的版本完全不同了，重构了基本功能并且实现了向外部开设Openai格式的api，适用于任何openai应用程序调用SillyTavern的强大功能。*
9 |
10 | > *I'm pleased to announce that I have completed the main features of this project. This is the latest update, completely different from previous versions. I've restructured the basic functionality and implemented an OpenAI-format API for external use, suitable for any OpenAI application to leverage SillyTavern's powerful capabilities.*
11 |
12 | 本项目是一个SillyTavern扩展，通过WebSocket和API转发的方式，实现了将SillyTavern作为中间件服务的功能。它包含以下组件：
13 |
14 | This project is a SillyTavern extension that turns SillyTavern into a middleware service through WebSocket and API forwarding. It consists of the following components:
15 |
16 | - SillyTavern UI Extension: 负责与WebSocket服务器通信
17 | - ChatBridge_APIHijackForwarder.py: 核心服务器组件，提供WebSocket和API接口
18 | - 配置文件：用于设置各类连接参数
19 |
20 | - SillyTavern UI Extension: Responsible for communication with the WebSocket server
21 | - ChatBridge_APIHijackForwarder.py: Core server component, providing WebSocket and API interfaces
22 | - Configuration files: Used to set various connection parameters
23 |
24 | 该扩展可以让任何支持OpenAI API格式的外部应用通过SillyTavern的对话管理系统与LLM进行交互。
25 |
26 | This extension allows any external application that supports the OpenAI API format to interact with LLMs through SillyTavern's conversation management system.
27 |
28 | ## 使用说明 / Usage Instructions
29 |
30 | ### 1. 安装扩展 / Install the Extension
31 |
32 | 1. 复制项目文件到SillyTavern扩展目录:
33 | Copy the project files to the SillyTavern extension directory:
34 | ```bash
35 | /public/scripts/extensions/third-party/SillyTavern-Extension-ChatBridge/
36 | ```
37 |
38 | ### 2. 启动服务 / Start the Service
39 |
40 | 0. 你可能需要配置settings.json文件中的各api的base_url和apikey。
41 |
42 | You may need to configure the base_url and apikey for various APIs in the settings.json file.
43 |
44 | 1. 启动Python服务器:
45 | Start the Python server:
46 | ```bash
47 | python ChatBridge_APIHijackForwarder.py
48 | ```
49 |
50 | 2. 在SillyTavern扩展设置中配置并连接WebSocket:
51 | Configure and connect to WebSocket in SillyTavern extension settings:
52 | - 设置服务器地址(默认localhost)
53 | - 设置端口(默认8001)
54 | - 点击"连接"按钮
55 |
56 | - Set the server address (default: localhost)
57 | - Set the port (default: 8001)
58 | - Click the "Connect" button
59 |
60 | ### 3. 外部应用调用 / External Application Calls
61 |
62 | 配置外部应用的API设置， 如:
63 | Configure the API settings for external applications, for example:
64 | ```python
65 | client = OpenAI(
66 | api_key="your-user-api-key",
67 | base_url="http://localhost:8003/v1"
68 | )
69 | ```
70 |
71 | ## 内部逻辑 / Internal Logic
72 |
73 | 请求流程:
74 | Request flow:
75 | 1. 外部应用 → 用户API(8003) → WebSocket(8001)
76 | 2. WebSocket → SillyTavern UI Extension
77 | 3. SillyTavern处理 → ST API(8002)
78 | 4. ST API → LLM API → 获取响应
79 | 5. 响应同时返回给ST和用户API
80 |
81 | 1. External App → User API(8003) → WebSocket(8001)
82 | 2. WebSocket → SillyTavern UI Extension
83 | 3. SillyTavern processing → ST API(8002)
84 | 4. ST API → LLM API → Get response
85 | 5. Response returned to both ST and User API
86 |
87 | ```mermaid
88 | sequenceDiagram
89 | User->>UserAPI: 1.调用API
90 | UserAPI->>WebSocket: 2.转发请求
91 | WebSocket->>ST: 3.通知处理
92 | ST->>STAPI: 4.调用接口
93 | STAPI->>LLM: 5.请求响应
94 | LLM-->>STAPI: 6.返回结果
95 | STAPI-->>ST: 7a.发送响应
96 | LLMAPI-->>UserAPI: 7b.同步发送响应
97 | UserAPI-->>User: 8.返回结果
98 | ```
99 |
100 | ### 重要说明 / Important Notes
101 |
102 | - 需要SillyTavern最新版本支持`context.clearChat()`和`context.printMessages()`
103 | - 所有API采用OpenAI格式
104 | - 支持流式和非流式响应， **但必须保证ST的设置和应用程序的设置都保持流式/非流式一致**
105 | - 支持多个LLM API密钥轮询
106 |
107 | - Requires the latest version of SillyTavern with support for `context.clearChat()` and `context.printMessages()`
108 | - All APIs use OpenAI format
109 | - Supports both streaming and non-streaming responses, **but ensure that ST settings and application settings are consistent for streaming/non-streaming**
110 | - Supports multiple LLM API keys rotation
111 |
112 | ## 依赖要求 / Dependencies
113 |
114 | - Python 3.7+
115 | - SillyTavern最新版本 / Latest version of SillyTavern
116 | - aiohttp
117 | - websockets
118 |
119 | ## 许可证 / License
120 |
121 | 本项目采用AGPL-3.0许可证
122 | This project is licensed under AGPL-3.0
123 |
124 | ## 已知问题
125 |
126 | - 若对UserApi的请求在上一条信息响应未完全结束时，发送另一条请求，有大概率会得到相同的回复。即转发器设计bug使得UserApi对短时间的请求将会给出相同的复制的响应，将在未来的版本修复，此Bug不影响单机串行使用。
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