AI
/
matrix_chatgpt_bot
mirror of https://github.com/hibobmaster/matrix_chatgpt_bot.git
1
0
Fork 0
Code Issues Packages Projects Releases Wiki Activity

Optimize

This commit is contained in:
hibobmaster 2023-09-13 15:27:34 +08:00
parent 5f5a5863ca
commit 8512e3ea22
No known key found for this signature in database
17 changed files with 562 additions and 837 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

20
.env.example
View File

@ -1,20 +1,6 @@
# Please remove the option that is blank
HOMESERVER="https://matrix.xxxxxx.xxxx" # required
HOMESERVER="https://matrix-client.matrix.org" # required
USER_ID="@lullap:xxxxxxxxxxxxx.xxx" # required
PASSWORD="xxxxxxxxxxxxxxx" # Optional
DEVICE_ID="xxxxxxxxxxxxxx" # required
PASSWORD="xxxxxxxxxxxxxxx" # Optional if you use access token
DEVICE_ID="MatrixChatGPTBot" # required
ROOM_ID="!FYCmBSkCRUXXXXXXXXX:matrix.XXX.XXX" # Optional, if not set, bot will work on the room it is in
OPENAI_API_KEY="xxxxxxxxxxxxxxxxx" # Optional, for !chat and !gpt command
API_ENDPOINT="xxxxxxxxxxxxxxx" # Optional, for !chat and !bing command
ACCESS_TOKEN="xxxxxxxxxxxxxxxxxxxxx" # Optional, use user_id and password is recommended
BARD_TOKEN="xxxxxxxxxxxxxxxxxxxx", # Optional, for !bard command
BING_AUTH_COOKIE="xxxxxxxxxxxxxxxxxxx" # _U cookie, Optional, for Bing Image Creator
MARKDOWN_FORMATTED="true" # Optional
OUTPUT_FOUR_IMAGES="true" # Optional
IMPORT_KEYS_PATH="element-keys.txt" # Optional, used for E2EE Room
IMPORT_KEYS_PASSWORD="xxxxxxx" # Optional
FLOWISE_API_URL="http://localhost:3000/api/v1/prediction/xxxx" # Optional
FLOWISE_API_KEY="xxxxxxxxxxxxxxxxxxxxxxx" # Optional
PANDORA_API_ENDPOINT="http://pandora:8008" # Optional, for !talk, !goon command
PANDORA_API_MODEL="text-davinci-002-render-sha-mobile" # Optional
TEMPERATURE="0.8" # Optional

20
.full-env.example Normal file
View File

@ -0,0 +1,20 @@
HOMESERVER="https://matrix-client.matrix.org"
USER_ID="@lullap:xxxxxxxxxxxxx.xxx"
PASSWORD="xxxxxxxxxxxxxxx"
DEVICE_ID="xxxxxxxxxxxxxx"
ROOM_ID="!FYCmBSkCRUXXXXXXXXX:matrix.XXX.XXX"
IMPORT_KEYS_PATH="element-keys.txt"
IMPORT_KEYS_PASSWORD="xxxxxxxxxxxx"
OPENAI_API_KEY="xxxxxxxxxxxxxxxxx"
GPT_API_ENDPOINT="https://api.openai.com/v1/chat/completions"
GPT_MODEL="gpt-3.5-turbo"
MAX_TOKENS=4000
TOP_P=1.0
PRESENCE_PENALTY=0.0
FREQUENCY_PENALTY=0.0
REPLY_COUNT=1
SYSTEM_PROMPT="You are ChatGPT, a large language model trained by OpenAI. Respond conversationally"
TEMPERATURE=0.8
FLOWISE_API_URL="http://flowise:3000/api/v1/prediction/6deb3c89-45bf-4ac4-a0b0-b2d5ef249d21"
FLOWISE_API_KEY="U3pe0bbVDWOyoJtsDzFJjRvHKTP3FRjODwuM78exC3A="
TIMEOUT=120.0

6
README.md
View File

@ -44,12 +44,8 @@ pip install -r requirements.txt
```
3. Create a new config.json file and complete it with the necessary information:<br>
Use password to login(recommended) or provide `access_token` <br>
If not set:<br>
`room_id`: bot will work in the room where it is in <br>
`openai_api_key`: `!gpt` `!chat` command will not work <br>
`api_endpoint`: `!bing` `!chat` command will not work <br>
`bing_auth_cookie`: `!pic` command will not work
```json
{
@ -59,7 +55,7 @@ pip install -r requirements.txt
"device_id": "YOUR_DEVICE_ID",
"room_id": "YOUR_ROOM_ID",
"openai_api_key": "YOUR_API_KEY",
"api_endpoint": "xxxxxxxxx"
"gpt_api_endpoint": "xxxxxxxxx"
}
```

25
compose.yaml
View File

@ -11,32 +11,13 @@ services:
volumes:
# use env file or config.json
# - ./config.json:/app/config.json
# use touch to create an empty file db, for persist database only
- ./db:/app/db
# use touch to create empty db file, for persist database only
- ./sync_db:/app/sync_db
- ./manage_db:/app/manage_db
# import_keys path
# - ./element-keys.txt:/app/element-keys.txt
networks:
- matrix_network
api:
# ChatGPT and Bing API
image: hibobmaster/node-chatgpt-api:latest
container_name: node-chatgpt-api
restart: unless-stopped
volumes:
- ./settings.js:/app/settings.js
networks:
- matrix_network
# pandora:
# # ChatGPT Web
# image: pengzhile/pandora
# container_name: pandora
# restart: unless-stopped
# environment:
# - PANDORA_ACCESS_TOKEN=xxxxxxxxxxxxxx
# - PANDORA_SERVER=0.0.0.0:8008
# networks:
# - matrix_network
networks:
matrix_network:

20
config.json.sample
View File

@ -1,21 +1,7 @@
{
"homeserver": "https://matrix.qqs.tw",
"homeserver": "https://matrix-client.matrix.org",
"user_id": "@lullap:xxxxx.org",
"password": "xxxxxxxxxxxxxxxxxx",
"device_id": "ECYEOKVPLG",
"room_id": "!FYCmBSkCRUNvZDBaDQ:matrix.qqs.tw",
"openai_api_key": "xxxxxxxxxxxxxxxxxxxxxxxx",
"api_endpoint": "http://api:3000/conversation",
"access_token": "xxxxxxx",
"bard_token": "xxxxxxx",
"bing_auth_cookie": "xxxxxxxxxxx",
"markdown_formatted": true,
"output_four_images": true,
"import_keys_path": "element-keys.txt",
"import_keys_password": "xxxxxxxxx",
"flowise_api_url": "http://localhost:3000/api/v1/prediction/6deb3c89-45bf-4ac4-a0b0-b2d5ef249d21",
"flowise_api_key": "U3pe0bbVDWOyoJtsDzFJjRvHKTP3FRjODwuM78exC3A=",
"pandora_api_endpoint": "http://127.0.0.1:8008",
"pandora_api_model": "text-davinci-002-render-sha-mobile",
"temperature": 0.8
"device_id": "MatrixChatGPTBot",
"openai_api_key": "xxxxxxxxxxxxxxxxxxxxxxxx"
}

22
full-config.json.sample Normal file
View File

@ -0,0 +1,22 @@
{
"homeserver": "https://matrix-client.matrix.org",
"user_id": "@lullap:xxxxx.org",
"password": "xxxxxxxxxxxxxxxxxx",
"device_id": "MatrixChatGPTBot",
"room_id": "!xxxxxxxxxxxxxxxxxxxxxx:xxxxx.org",
"import_keys_path": "element-keys.txt",
"import_keys_password": "xxxxxxxxxxxxxxxxxxxx",
"openai_api_key": "xxxxxxxxxxxxxxxxxxxxxxxx",
"gpt_api_endpoint": "https://api.openai.com/v1/chat/completions",
"gpt_model": "gpt-3.5-turbo",
"max_tokens": 4000,
"top_p": 1.0,
"presence_penalty": 0.0,
"frequency_penalty": 0.0,
"reply_count": 1,
"temperature": 0.8,
"system_prompt": "You are ChatGPT, a large language model trained by OpenAI. Respond conversationally",
"flowise_api_url": "http://flowise:3000/api/v1/prediction/6deb3c89-45bf-4ac4-a0b0-b2d5ef249d21",
"flowise_api_key": "U3pe0bbVDWOyoJtsDzFJjRvHKTP3FRjODwuM78exC3A=",
"timeout": 120.0
}

9
requirements-dev.txt Normal file
View File

@ -0,0 +1,9 @@
aiofiles
httpx
Markdown
matrix-nio[e2e]
Pillow
tiktoken
tenacity
python-magic
pytest

2
requirements.txt
View File

@ -1,5 +1,5 @@
aiofiles
aiohttp
httpx
Markdown
matrix-nio[e2e]
Pillow

101
settings.js.example
View File

@ -1,101 +0,0 @@
export default {
// Options for the Keyv cache, see https://www.npmjs.com/package/keyv.
// This is used for storing conversations, and supports additional drivers (conversations are stored in memory by default).
// Only necessary when using `ChatGPTClient`, or `BingAIClient` in jailbreak mode.
cacheOptions: {},
// If set, `ChatGPTClient` and `BingAIClient` will use `keyv-file` to store conversations to this JSON file instead of in memory.
// However, `cacheOptions.store` will override this if set
storageFilePath: process.env.STORAGE_FILE_PATH || './cache.json',
chatGptClient: {
// Your OpenAI API key (for `ChatGPTClient`)
openaiApiKey: process.env.OPENAI_API_KEY || '',
// (Optional) Support for a reverse proxy for the completions endpoint (private API server).
// Warning: This will expose your `openaiApiKey` to a third party. Consider the risks before using this.
// reverseProxyUrl: 'https://chatgpt.hato.ai/completions',
// (Optional) Parameters as described in https://platform.openai.com/docs/api-reference/completions
modelOptions: {
// You can override the model name and any other parameters here.
// The default model is `gpt-3.5-turbo`.
model: 'gpt-3.5-turbo',
// Set max_tokens here to override the default max_tokens of 1000 for the completion.
// max_tokens: 1000,
},
// (Optional) Davinci models have a max context length of 4097 tokens, but you may need to change this for other models.
// maxContextTokens: 4097,
// (Optional) You might want to lower this to save money if using a paid model like `text-davinci-003`.
// Earlier messages will be dropped until the prompt is within the limit.
// maxPromptTokens: 3097,
// (Optional) Set custom instructions instead of "You are ChatGPT...".
// (Optional) Set a custom name for the user
// userLabel: 'User',
// (Optional) Set a custom name for ChatGPT ("ChatGPT" by default)
// chatGptLabel: 'Bob',
// promptPrefix: 'You are Bob, a cowboy in Western times...',
// A proxy string like "http://<ip>:<port>"
proxy: '',
// (Optional) Set to true to enable `console.debug()` logging
debug: false,
},
// Options for the Bing client
bingAiClient: {
// Necessary for some people in different countries, e.g. China (https://cn.bing.com)
host: '',
// The "_U" cookie value from bing.com
userToken: '',
// If the above doesn't work, provide all your cookies as a string instead
cookies: '',
// A proxy string like "http://<ip>:<port>"
proxy: '',
// (Optional) Set 'x-forwarded-for' for the request. You can use a fixed IPv4 address or specify a range using CIDR notation,
// and the program will randomly select an address within that range. The 'x-forwarded-for' is not used by default now.
// xForwardedFor: '13.104.0.0/14',
// (Optional) Set 'genImage' to true to enable bing to create images for you. It's disabled by default.
// features: {
// genImage: true,
// },
// (Optional) Set to true to enable `console.debug()` logging
debug: false,
},
chatGptBrowserClient: {
// (Optional) Support for a reverse proxy for the conversation endpoint (private API server).
// Warning: This will expose your access token to a third party. Consider the risks before using this.
reverseProxyUrl: 'https://bypass.churchless.tech/api/conversation',
// Access token from https://chat.openai.com/api/auth/session
accessToken: '',
// Cookies from chat.openai.com (likely not required if using reverse proxy server).
cookies: '',
// A proxy string like "http://<ip>:<port>"
proxy: '',
// (Optional) Set to true to enable `console.debug()` logging
debug: false,
},
// Options for the API server
apiOptions: {
port: process.env.API_PORT || 3000,
host: process.env.API_HOST || 'localhost',
// (Optional) Set to true to enable `console.debug()` logging
debug: false,
// (Optional) Possible options: "chatgpt", "chatgpt-browser", "bing". (Default: "chatgpt")
// clientToUse: 'bing',
// (Optional) Generate titles for each conversation for clients that support it (only ChatGPTClient for now).
// This will be returned as a `title` property in the first response of the conversation.
generateTitles: false,
// (Optional) Set this to allow changing the client or client options in POST /conversation.
// To disable, set to `null`.
perMessageClientOptionsWhitelist: {
// The ability to switch clients using `clientOptions.clientToUse` will be disabled if `validClientsToUse` is not set.
// To allow switching clients per message, you must set `validClientsToUse` to a non-empty array.
validClientsToUse: ['bing', 'chatgpt'], // values from possible `clientToUse` options above
// The Object key, e.g. "chatgpt", is a value from `validClientsToUse`.
// If not set, ALL options will be ALLOWED to be changed. For example, `bing` is not defined in `perMessageClientOptionsWhitelist` above,
// so all options for `bingAiClient` will be allowed to be changed.
// If set, ONLY the options listed here will be allowed to be changed.
// In this example, each array element is a string representing a property in `chatGptClient` above.
},
},
// Options for the CLI app
cliOptions: {
// (Optional) Possible options: "chatgpt", "bing".
// clientToUse: 'bing',
},
};

45
src/askgpt.py
View File

@ -1,45 +0,0 @@
import json
import aiohttp
from log import getlogger
logger = getlogger()
class askGPT:
def __init__(self, session: aiohttp.ClientSession):
self.session = session
async def oneTimeAsk(
self, prompt: str, api_endpoint: str, headers: dict, temperature: float = 0.8
) -> str:
jsons = {
"model": "gpt-3.5-turbo",
"messages": [
{
"role": "user",
"content": prompt,
},
],
"temperature": temperature,
}
max_try = 2
while max_try > 0:
try:
async with self.session.post(
url=api_endpoint,
json=jsons,
headers=headers,
timeout=120,
) as response:
status_code = response.status
if not status_code == 200:
# print failed reason
logger.warning(str(response.reason))
max_try = max_try - 1
continue
resp = await response.read()
return json.loads(resp)["choices"][0]["message"]["content"]
except Exception as e:
raise Exception(e)

596
src/bot.py
View File

@ -5,9 +5,9 @@ import re
import sys
import traceback
from typing import Union, Optional
import uuid
import aiohttp
import httpx
from nio import (
AsyncClient,
AsyncClientConfig,
@ -28,19 +28,15 @@ from nio import (
)
from nio.store.database import SqliteStore
from askgpt import askGPT
from chatgpt_bing import GPTBOT
from BingImageGen import ImageGenAsync
from log import getlogger
from send_image import send_room_image
from send_message import send_room_message
from bard import Bardbot
from flowise import flowise_query
from pandora_api import Pandora
from gptbot import Chatbot
logger = getlogger()
chatgpt_api_endpoint = "https://api.openai.com/v1/chat/completions"
base_path = Path(os.path.dirname(__file__)).parent
DEVICE_NAME = "MatrixChatGPTBot"
GENERAL_ERROR_MESSAGE = "Something went wrong, please try again or contact admin."
class Bot:
@ -48,77 +44,75 @@ class Bot:
self,
homeserver: str,
user_id: str,
device_id: str,
api_endpoint: Optional[str] = None,
openai_api_key: Union[str, None] = None,
temperature: Union[float, None] = None,
room_id: Union[str, None] = None,
password: Union[str, None] = None,
access_token: Union[str, None] = None,
bard_token: Union[str, None] = None,
jailbreakEnabled: Union[bool, None] = True,
bing_auth_cookie: Union[str, None] = "",
markdown_formatted: Union[bool, None] = False,
output_four_images: Union[bool, None] = False,
device_id: str = "MatrixChatGPTBot",
room_id: Union[str, None] = None,
import_keys_path: Optional[str] = None,
import_keys_password: Optional[str] = None,
openai_api_key: Union[str, None] = None,
gpt_api_endpoint: Optional[str] = None,
gpt_model: Optional[str] = None,
max_tokens: Optional[int] = None,
top_p: Optional[float] = None,
presence_penalty: Optional[float] = None,
frequency_penalty: Optional[float] = None,
reply_count: Optional[int] = None,
system_prompt: Optional[str] = None,
temperature: Union[float, None] = None,
flowise_api_url: Optional[str] = None,
flowise_api_key: Optional[str] = None,
pandora_api_endpoint: Optional[str] = None,
pandora_api_model: Optional[str] = None,
timeout: Union[float, None] = None,
):
if homeserver is None or user_id is None or device_id is None:
logger.warning("homeserver && user_id && device_id is required")
sys.exit(1)
if password is None and access_token is None:
logger.warning("password or access_toekn is required")
if password is None:
logger.warning("password is required")
sys.exit(1)
self.homeserver = homeserver
self.user_id = user_id
self.password = password
self.access_token = access_token
self.bard_token = bard_token
self.device_id = device_id
self.room_id = room_id
self.openai_api_key = openai_api_key
self.bing_auth_cookie = bing_auth_cookie
self.api_endpoint = api_endpoint
self.import_keys_path = import_keys_path
self.import_keys_password = import_keys_password
self.flowise_api_url = flowise_api_url
self.flowise_api_key = flowise_api_key
self.pandora_api_endpoint = pandora_api_endpoint
self.temperature = temperature
self.homeserver: str = homeserver
self.user_id: str = user_id
self.password: str = password
self.device_id: str = device_id
self.room_id: str = room_id
self.session = aiohttp.ClientSession()
self.openai_api_key: str = openai_api_key
self.gpt_api_endpoint: str = (
gpt_api_endpoint or "https://api.openai.com/v1/chat/completions"
)
self.gpt_model: str = gpt_model or "gpt-3.5-turbo"
self.max_tokens: int = max_tokens or 4000
self.top_p: float = top_p or 1.0
self.temperature: float = temperature or 0.8
self.presence_penalty: float = presence_penalty or 0.0
self.frequency_penalty: float = frequency_penalty or 0.0
self.reply_count: int = reply_count or 1
self.system_prompt: str = (
system_prompt
or "You are ChatGPT, \
a large language model trained by OpenAI. Respond conversationally"
)
if openai_api_key is not None:
if not self.openai_api_key.startswith("sk-"):
logger.warning("invalid openai api key")
sys.exit(1)
self.import_keys_path: str = import_keys_path
self.import_keys_password: str = import_keys_password
self.flowise_api_url: str = flowise_api_url
self.flowise_api_key: str = flowise_api_key
if jailbreakEnabled is None:
self.jailbreakEnabled = True
else:
self.jailbreakEnabled = jailbreakEnabled
self.timeout: float = timeout or 120.0
if markdown_formatted is None:
self.markdown_formatted = False
else:
self.markdown_formatted = markdown_formatted
self.base_path = Path(os.path.dirname(__file__)).parent
if output_four_images is None:
self.output_four_images = False
else:
self.output_four_images = output_four_images
self.httpx_client = httpx.AsyncClient(
follow_redirects=True,
timeout=self.timeout,
)
# initialize AsyncClient object
self.store_path = base_path
self.store_path = self.base_path
self.config = AsyncClientConfig(
store=SqliteStore,
store_name="db",
store_name="sync_db",
store_sync_tokens=True,
encryption_enabled=True,
)
@ -130,8 +124,21 @@ class Bot:
store_path=self.store_path,
)
if self.access_token is not None:
self.client.access_token = self.access_token
# initialize Chatbot object
self.chatbot = Chatbot(
aclient=self.httpx_client,
api_key=self.openai_api_key,
api_url=self.gpt_api_endpoint,
engine=self.gpt_model,
timeout=self.timeout,
max_tokens=self.max_tokens,
top_p=self.top_p,
presence_penalty=self.presence_penalty,
frequency_penalty=self.frequency_penalty,
reply_count=self.reply_count,
system_prompt=self.system_prompt,
temperature=self.temperature,
)
# setup event callbacks
self.client.add_event_callback(self.message_callback, (RoomMessageText,))
@ -144,81 +151,22 @@ class Bot:
# regular expression to match keyword commands
self.gpt_prog = re.compile(r"^\s*!gpt\s*(.+)$")
self.chat_prog = re.compile(r"^\s*!chat\s*(.+)$")
self.bing_prog = re.compile(r"^\s*!bing\s*(.+)$")
self.bard_prog = re.compile(r"^\s*!bard\s*(.+)$")
self.pic_prog = re.compile(r"^\s*!pic\s*(.+)$")
self.lc_prog = re.compile(r"^\s*!lc\s*(.+)$")
self.help_prog = re.compile(r"^\s*!help\s*.*$")
self.talk_prog = re.compile(r"^\s*!talk\s*(.+)$")
self.goon_prog = re.compile(r"^\s*!goon\s*.*$")
self.new_prog = re.compile(r"^\s*!new\s*(.+)$")
# initialize askGPT class
self.askgpt = askGPT(self.session)
# request header for !gpt command
self.gptheaders = {
"Content-Type": "application/json",
"Authorization": f"Bearer {self.openai_api_key}",
}
# initialize bing and chatgpt
if self.api_endpoint is not None:
self.gptbot = GPTBOT(self.api_endpoint, self.session)
self.chatgpt_data = {}
self.bing_data = {}
# initialize BingImageGenAsync
if self.bing_auth_cookie != "":
self.imageGen = ImageGenAsync(self.bing_auth_cookie, quiet=True)
# initialize pandora
if pandora_api_endpoint is not None:
self.pandora = Pandora(
api_endpoint=pandora_api_endpoint, clientSession=self.session
)
if pandora_api_model is None:
self.pandora_api_model = "text-davinci-002-render-sha-mobile"
else:
self.pandora_api_model = pandora_api_model
self.pandora_data = {}
# initialize bard
self.bard_data = {}
def __del__(self):
try:
loop = asyncio.get_running_loop()
except RuntimeError:
loop = asyncio.new_event_loop()
asyncio.set_event_loop(loop)
loop.run_until_complete(self._close())
async def _close(self):
await self.session.close()
async def close(self, task: asyncio.Task) -> None:
await self.httpx_client.aclose()
await self.client.close()
task.cancel()
logger.info("Bot closed!")
def chatgpt_session_init(self, sender_id: str) -> None:
self.chatgpt_data[sender_id] = {
"first_time": True,
}
def bing_session_init(self, sender_id: str) -> None:
self.bing_data[sender_id] = {
"first_time": True,
}
def pandora_session_init(self, sender_id: str) -> None:
self.pandora_data[sender_id] = {
"conversation_id": None,
"parent_message_id": str(uuid.uuid4()),
"first_time": True,
}
async def bard_session_init(self, sender_id: str) -> None:
self.bard_data[sender_id] = {
"instance": await Bardbot.create(self.bard_token, 60),
}
# message_callback RoomMessageText event
async def message_callback(self, room: MatrixRoom, event: RoomMessageText) -> None:
if self.room_id is None:
@ -267,7 +215,7 @@ class Bot:
except Exception as e:
logger.error(e, exc_info=True)
if self.api_endpoint is not None:
if self.gpt_api_endpoint is not None:
# chatgpt
n = self.chat_prog.match(content_body)
if n:
@ -293,58 +241,6 @@ class Bot:
self.client, room_id, reply_message="API_KEY not provided"
)
# bing ai
# if self.bing_api_endpoint != "":
# bing ai can be used without cookie
b = self.bing_prog.match(content_body)
if b:
if sender_id not in self.bing_data:
self.bing_session_init(sender_id)
prompt = b.group(1)
# raw_content_body used for construct formatted_body
try:
asyncio.create_task(
self.bing(
room_id,
reply_to_event_id,
prompt,
sender_id,
raw_user_message,
)
)
except Exception as e:
logger.error(e, exc_info=True)
# Image Generation by Microsoft Bing
if self.bing_auth_cookie != "":
i = self.pic_prog.match(content_body)
if i:
prompt = i.group(1)
try:
asyncio.create_task(self.pic(room_id, prompt))
except Exception as e:
logger.error(e, exc_info=True)
# Google's Bard
if self.bard_token is not None:
if sender_id not in self.bard_data:
await self.bard_session_init(sender_id)
b = self.bard_prog.match(content_body)
if b:
prompt = b.group(1)
try:
asyncio.create_task(
self.bard(
room_id,
reply_to_event_id,
prompt,
sender_id,
raw_user_message,
)
)
except Exception as e:
logger.error(e, exc_info=True)
# lc command
if self.flowise_api_url is not None:
m = self.lc_prog.match(content_body)
@ -364,46 +260,10 @@ class Bot:
await send_room_message(self.client, room_id, reply_message={e})
logger.error(e, exc_info=True)
# pandora
if self.pandora_api_endpoint is not None:
t = self.talk_prog.match(content_body)
if t:
if sender_id not in self.pandora_data:
self.pandora_session_init(sender_id)
prompt = t.group(1)
try:
asyncio.create_task(
self.talk(
room_id,
reply_to_event_id,
prompt,
sender_id,
raw_user_message,
)
)
except Exception as e:
logger.error(e, exc_info=True)
g = self.goon_prog.match(content_body)
if g:
if sender_id not in self.pandora_data:
self.pandora_session_init(sender_id)
try:
asyncio.create_task(
self.goon(
room_id,
reply_to_event_id,
sender_id,
raw_user_message,
)
)
except Exception as e:
logger.error(e, exc_info=True)
# !new command
n = self.new_prog.match(content_body)
if n:
new_command_kind = n.group(1)
new_command = n.group(1)
try:
asyncio.create_task(
self.new(
@ -411,7 +271,7 @@ class Bot:
reply_to_event_id,
sender_id,
raw_user_message,
new_command_kind,
new_command,
)
)
except Exception as e:
@ -421,7 +281,11 @@ class Bot:
h = self.help_prog.match(content_body)
if h:
try:
asyncio.create_task(self.help(room_id))
asyncio.create_task(
self.help(
room_id, reply_to_event_id, sender_id, raw_user_message
)
)
except Exception as e:
logger.error(e, exc_info=True)
@ -670,7 +534,7 @@ class Bot:
self, room_id, reply_to_event_id, prompt, sender_id, raw_user_message
):
try:
await self.client.room_typing(room_id, timeout=300000)
await self.client.room_typing(room_id, timeout=int(self.timeout) * 1000)
if (
self.chatgpt_data[sender_id]["first_time"]
or "conversationId" not in self.chatgpt_data[sender_id]
@ -705,128 +569,43 @@ class Bot:
self.client,
room_id,
reply_message=content,
reply_to_event_id="",
reply_to_event_id=reply_to_event_id,
sender_id=sender_id,
user_message=raw_user_message,
markdown_formatted=self.markdown_formatted,
)
except Exception as e:
await send_room_message(self.client, room_id, reply_message=str(e))
except Exception:
await send_room_message(
self.client,
room_id,
reply_message=GENERAL_ERROR_MESSAGE,
reply_to_event_id=reply_to_event_id,
)
# !gpt command
async def gpt(
self, room_id, reply_to_event_id, prompt, sender_id, raw_user_message
) -> None:
try:
# sending typing state
await self.client.room_typing(room_id, timeout=30000)
# timeout 300s
text = await asyncio.wait_for(
self.askgpt.oneTimeAsk(
prompt, chatgpt_api_endpoint, self.gptheaders, self.temperature
),
timeout=300,
# sending typing state, seconds to milliseconds
await self.client.room_typing(room_id, timeout=int(self.timeout) * 1000)
responseMessage = await self.chatbot.oneTimeAsk(
prompt=prompt,
)
text = text.strip()
await send_room_message(
self.client,
room_id,
reply_message=text,
reply_to_event_id="",
reply_message=responseMessage.strip(),
reply_to_event_id=reply_to_event_id,
sender_id=sender_id,
user_message=raw_user_message,
markdown_formatted=self.markdown_formatted,
)
except Exception:
await send_room_message(
self.client,
room_id,
reply_message="Error encountered, please try again or contact admin.",
)
# !bing command
async def bing(
self, room_id, reply_to_event_id, prompt, sender_id, raw_user_message
) -> None:
try:
# sending typing state
await self.client.room_typing(room_id, timeout=300000)
if (
self.bing_data[sender_id]["first_time"]
or "conversationId" not in self.bing_data[sender_id]
):
self.bing_data[sender_id]["first_time"] = False
payload = {
"message": prompt,
"clientOptions": {
"clientToUse": "bing",
},
}
else:
payload = {
"message": prompt,
"clientOptions": {
"clientToUse": "bing",
},
"conversationSignature": self.bing_data[sender_id][
"conversationSignature"
],
"conversationId": self.bing_data[sender_id]["conversationId"],
"clientId": self.bing_data[sender_id]["clientId"],
"invocationId": self.bing_data[sender_id]["invocationId"],
}
resp = await self.gptbot.queryBing(payload)
content = "".join(
[body["text"] for body in resp["details"]["adaptiveCards"][0]["body"]]
)
self.bing_data[sender_id]["conversationSignature"] = resp[
"conversationSignature"
]
self.bing_data[sender_id]["conversationId"] = resp["conversationId"]
self.bing_data[sender_id]["clientId"] = resp["clientId"]
self.bing_data[sender_id]["invocationId"] = resp["invocationId"]
text = content.strip()
await send_room_message(
self.client,
room_id,
reply_message=text,
reply_to_event_id="",
sender_id=sender_id,
user_message=raw_user_message,
markdown_formatted=self.markdown_formatted,
)
except Exception as e:
await send_room_message(self.client, room_id, reply_message=str(e))
# !bard command
async def bard(
self, room_id, reply_to_event_id, prompt, sender_id, raw_user_message
) -> None:
try:
# sending typing state
await self.client.room_typing(room_id)
response = await self.bard_data[sender_id]["instance"].ask(prompt)
content = str(response["content"]).strip()
await send_room_message(
self.client,
room_id,
reply_message=content,
reply_to_event_id="",
sender_id=sender_id,
user_message=raw_user_message,
markdown_formatted=self.markdown_formatted,
)
except TimeoutError:
await send_room_message(self.client, room_id, reply_message="TimeoutError")
except Exception:
await send_room_message(
self.client,
room_id,
reply_message="Error calling Bard API, please contact admin.",
reply_message=GENERAL_ERROR_MESSAGE,
reply_to_event_id=reply_to_event_id,
)
# !lc command
@ -835,120 +614,32 @@ class Bot:
) -> None:
try:
# sending typing state
await self.client.room_typing(room_id)
await self.client.room_typing(room_id, timeout=int(self.timeout) * 1000)
if self.flowise_api_key is not None:
headers = {"Authorization": f"Bearer {self.flowise_api_key}"}
response = await flowise_query(
self.flowise_api_url, prompt, self.session, headers
responseMessage = await flowise_query(
self.flowise_api_url, prompt, self.httpx_client, headers
)
else:
response = await flowise_query(
self.flowise_api_url, prompt, self.session
responseMessage = await flowise_query(
self.flowise_api_url, prompt, self.httpx_client
)
await send_room_message(
self.client,
room_id,
reply_message=response,
reply_to_event_id="",
reply_message=responseMessage.strip(),
reply_to_event_id=reply_to_event_id,
sender_id=sender_id,
user_message=raw_user_message,
markdown_formatted=self.markdown_formatted,
)
except Exception:
await send_room_message(
self.client,
room_id,
reply_message="Error calling flowise API, please contact admin.",
reply_message=GENERAL_ERROR_MESSAGE,
reply_to_event_id=reply_to_event_id,
)
# !talk command
async def talk(
self, room_id, reply_to_event_id, prompt, sender_id, raw_user_message
) -> None:
try:
if self.pandora_data[sender_id]["conversation_id"] is not None:
data = {
"prompt": prompt,
"model": self.pandora_api_model,
"parent_message_id": self.pandora_data[sender_id][
"parent_message_id"
],
"conversation_id": self.pandora_data[sender_id]["conversation_id"],
"stream": False,
}
else:
data = {
"prompt": prompt,
"model": self.pandora_api_model,
"parent_message_id": self.pandora_data[sender_id][
"parent_message_id"
],
"stream": False,
}
# sending typing state
await self.client.room_typing(room_id)
response = await self.pandora.talk(data)
self.pandora_data[sender_id]["conversation_id"] = response[
"conversation_id"
]
self.pandora_data[sender_id]["parent_message_id"] = response["message"][
"id"
]
content = response["message"]["content"]["parts"][0]
if self.pandora_data[sender_id]["first_time"]:
self.pandora_data[sender_id]["first_time"] = False
data = {
"model": self.pandora_api_model,
"message_id": self.pandora_data[sender_id]["parent_message_id"],
}
await self.pandora.gen_title(
data, self.pandora_data[sender_id]["conversation_id"]
)
await send_room_message(
self.client,
room_id,
reply_message=content,
reply_to_event_id="",
sender_id=sender_id,
user_message=raw_user_message,
markdown_formatted=self.markdown_formatted,
)
except Exception as e:
await send_room_message(self.client, room_id, reply_message=str(e))
# !goon command
async def goon(
self, room_id, reply_to_event_id, sender_id, raw_user_message
) -> None:
try:
# sending typing state
await self.client.room_typing(room_id)
data = {
"model": self.pandora_api_model,
"parent_message_id": self.pandora_data[sender_id]["parent_message_id"],
"conversation_id": self.pandora_data[sender_id]["conversation_id"],
"stream": False,
}
response = await self.pandora.goon(data)
self.pandora_data[sender_id]["conversation_id"] = response[
"conversation_id"
]
self.pandora_data[sender_id]["parent_message_id"] = response["message"][
"id"
]
content = response["message"]["content"]["parts"][0]
await send_room_message(
self.client,
room_id,
reply_message=content,
reply_to_event_id="",
sender_id=sender_id,
user_message=raw_user_message,
markdown_formatted=self.markdown_formatted,
)
except Exception as e:
await send_room_message(self.client, room_id, reply_message=str(e))
# !new command
async def new(
self,
@ -956,29 +647,14 @@ class Bot:
reply_to_event_id,
sender_id,
raw_user_message,
new_command_kind,
new_command,
) -> None:
try:
if "talk" in new_command_kind:
self.pandora_session_init(sender_id)
content = (
"New conversation created, please use !talk to start chatting!"
)
elif "chat" in new_command_kind:
if "chat" in new_command:
self.chatgpt_session_init(sender_id)
content = (
"New conversation created, please use !chat to start chatting!"
)
elif "bing" in new_command_kind:
self.bing_session_init(sender_id)
content = (
"New conversation created, please use !bing to start chatting!"
)
elif "bard" in new_command_kind:
await self.bard_session_init(sender_id)
content = (
"New conversation created, please use !bard to start chatting!"
)
else:
content = "Unkown keyword, please use !help to see the usage!"
@ -986,32 +662,41 @@ class Bot:
self.client,
room_id,
reply_message=content,
reply_to_event_id="",
reply_to_event_id=reply_to_event_id,
sender_id=sender_id,
user_message=raw_user_message,
markdown_formatted=self.markdown_formatted,
)
except Exception as e:
await send_room_message(self.client, room_id, reply_message=str(e))
except Exception:
await send_room_message(
self.client,
room_id,
reply_message=GENERAL_ERROR_MESSAGE,
reply_to_event_id=reply_to_event_id,
)
# !pic command
async def pic(self, room_id, prompt):
async def pic(self, room_id, prompt, replay_to_event_id):
try:
await self.client.room_typing(room_id, timeout=300000)
await self.client.room_typing(room_id, timeout=int(self.timeout) * 1000)
# generate image
links = await self.imageGen.get_images(prompt)
image_path_list = await self.imageGen.save_images(
links, base_path / "images", self.output_four_images
links, self.base_path / "images", self.output_four_images
)
# send image
for image_path in image_path_list:
await send_room_image(self.client, room_id, image_path)
await self.client.room_typing(room_id, typing_state=False)
except Exception as e:
await send_room_message(self.client, room_id, reply_message=str(e))
await send_room_message(
self.client,
room_id,
reply_message=str(e),
reply_to_event_id=replay_to_event_id,
)
# !help command
async def help(self, room_id):
async def help(self, room_id, reply_to_event_id, sender_id, user_message):
help_info = (
"!gpt [prompt], generate a one time response without context conversation\n"
+ "!chat [prompt], chat with context conversation\n"
@ -1025,21 +710,24 @@ class Bot:
+ "!help, help message"
) # noqa: E501
await send_room_message(self.client, room_id, reply_message=help_info)
await send_room_message(
self.client,
room_id,
reply_message=help_info,
sender_id=sender_id,
user_message=user_message,
reply_to_event_id=reply_to_event_id,
)
# bot login
async def login(self) -> None:
if self.access_token is not None:
logger.info("Login via access_token")
else:
logger.info("Login via password")
try:
resp = await self.client.login(password=self.password)
if not isinstance(resp, LoginResponse):
logger.error("Login Failed")
sys.exit(1)
except Exception as e:
logger.error(f"Error: {e}", exc_info=True)
resp = await self.client.login(password=self.password, device_name=DEVICE_NAME)
if not isinstance(resp, LoginResponse):
logger.error("Login Failed")
await self.httpx_client.aclose()
await self.client.close()
sys.exit(1)
logger.info("Success login via password")
# import keys
async def import_keys(self):

18
src/flowise.py
View File

@ -1,8 +1,8 @@
import aiohttp
import httpx
async def flowise_query(
api_url: str, prompt: str, session: aiohttp.ClientSession, headers: dict = None
api_url: str, prompt: str, session: httpx.AsyncClient, headers: dict = None
) -> str:
"""
Sends a query to the Flowise API and returns the response.
@ -24,17 +24,15 @@ async def flowise_query(
)
else:
response = await session.post(api_url, json={"question": prompt})
return await response.json()
return await response.text()
async def test():
session = aiohttp.ClientSession()
api_url = (
"http://127.0.0.1:3000/api/v1/prediction/683f9ea8-e670-4d51-b657-0886eab9cea1"
)
prompt = "What is the capital of France?"
response = await flowise_query(api_url, prompt, session)
print(response)
async with httpx.AsyncClient() as session:
api_url = "http://127.0.0.1:3000/api/v1/prediction/683f9ea8-e670-4d51-b657-0886eab9cea1"
prompt = "What is the capital of France?"
response = await flowise_query(api_url, prompt, session)
print(response)
if __name__ == "__main__":

292
src/gptbot.py Normal file
View File

@ -0,0 +1,292 @@
"""
Code derived from https://github.com/acheong08/ChatGPT/blob/main/src/revChatGPT/V3.py
A simple wrapper for the official ChatGPT API
"""
import json
from typing import AsyncGenerator
from tenacity import retry, stop_after_attempt, wait_random_exponential
import httpx
import tiktoken
ENGINES = [
"gpt-3.5-turbo",
"gpt-3.5-turbo-16k",
"gpt-3.5-turbo-0613",
"gpt-3.5-turbo-16k-0613",
"gpt-4",
"gpt-4-32k",
"gpt-4-0613",
"gpt-4-32k-0613",
]
class Chatbot:
"""
Official ChatGPT API
"""
def __init__(
self,
aclient: httpx.AsyncClient,
api_key: str,
api_url: str = None,
engine: str = None,
timeout: float = None,
max_tokens: int = None,
temperature: float = 0.8,
top_p: float = 1.0,
presence_penalty: float = 0.0,
frequency_penalty: float = 0.0,
reply_count: int = 1,
truncate_limit: int = None,
system_prompt: str = None,
) -> None:
"""
Initialize Chatbot with API key (from https://platform.openai.com/account/api-keys)
"""
self.engine: str = engine or "gpt-3.5-turbo"
self.api_key: str = api_key
self.api_url: str = api_url or "https://api.openai.com/v1/chat/completions"
self.system_prompt: str = (
system_prompt
or "You are ChatGPT, \
a large language model trained by OpenAI. Respond conversationally"
)
self.max_tokens: int = max_tokens or (
31000
if "gpt-4-32k" in engine
else 7000
if "gpt-4" in engine
else 15000
if "gpt-3.5-turbo-16k" in engine
else 4000
)
self.truncate_limit: int = truncate_limit or (
30500
if "gpt-4-32k" in engine
else 6500
if "gpt-4" in engine
else 14500
if "gpt-3.5-turbo-16k" in engine
else 3500
)
self.temperature: float = temperature
self.top_p: float = top_p
self.presence_penalty: float = presence_penalty
self.frequency_penalty: float = frequency_penalty
self.reply_count: int = reply_count
self.timeout: float = timeout
self.aclient = aclient
self.conversation: dict[str, list[dict]] = {
"default": [
{
"role": "system",
"content": system_prompt,
},
],
}
if self.get_token_count("default") > self.max_tokens:
raise Exception("System prompt is too long")
def add_to_conversation(
self,
message: str,
role: str,
convo_id: str = "default",
) -> None:
"""
Add a message to the conversation
"""
self.conversation[convo_id].append({"role": role, "content": message})
def __truncate_conversation(self, convo_id: str = "default") -> None:
"""
Truncate the conversation
"""
while True:
if (
self.get_token_count(convo_id) > self.truncate_limit
and len(self.conversation[convo_id]) > 1
):
# Don't remove the first message
self.conversation[convo_id].pop(1)
else:
break
# https://github.com/openai/openai-cookbook/blob/main/examples/How_to_count_tokens_with_tiktoken.ipynb
def get_token_count(self, convo_id: str = "default") -> int:
"""
Get token count
"""
if self.engine not in ENGINES:
raise NotImplementedError(
f"Engine {self.engine} is not supported. Select from {ENGINES}",
)
tiktoken.model.MODEL_TO_ENCODING["gpt-4"] = "cl100k_base"
encoding = tiktoken.encoding_for_model(self.engine)
num_tokens = 0
for message in self.conversation[convo_id]:
# every message follows <im_start>{role/name}\n{content}<im_end>\n
num_tokens += 5
for key, value in message.items():
if value:
num_tokens += len(encoding.encode(value))
if key == "name": # if there's a name, the role is omitted
num_tokens += 5 # role is always required and always 1 token
num_tokens += 5 # every reply is primed with <im_start>assistant
return num_tokens
def get_max_tokens(self, convo_id: str) -> int:
"""
Get max tokens
"""
return self.max_tokens - self.get_token_count(convo_id)
async def ask_stream_async(
self,
prompt: str,
role: str = "user",
convo_id: str = "default",
model: str = None,
pass_history: bool = True,
**kwargs,
) -> AsyncGenerator[str, None]:
"""
Ask a question
"""
# Make conversation if it doesn't exist
if convo_id not in self.conversation:
self.reset(convo_id=convo_id, system_prompt=self.system_prompt)
self.add_to_conversation(prompt, "user", convo_id=convo_id)
self.__truncate_conversation(convo_id=convo_id)
# Get response
async with self.aclient.stream(
"post",
self.api_url,
headers={"Authorization": f"Bearer {kwargs.get('api_key', self.api_key)}"},
json={
"model": model or self.engine,
"messages": self.conversation[convo_id] if pass_history else [prompt],
"stream": True,
# kwargs
"temperature": kwargs.get("temperature", self.temperature),
"top_p": kwargs.get("top_p", self.top_p),
"presence_penalty": kwargs.get(
"presence_penalty",
self.presence_penalty,
),
"frequency_penalty": kwargs.get(
"frequency_penalty",
self.frequency_penalty,
),
"n": kwargs.get("n", self.reply_count),
"user": role,
"max_tokens": min(
self.get_max_tokens(convo_id=convo_id),
kwargs.get("max_tokens", self.max_tokens),
),
},
timeout=kwargs.get("timeout", self.timeout),
) as response:
if response.status_code != 200:
await response.aread()
raise Exception(
f"{response.status_code} {response.reason_phrase} {response.text}",
)
response_role: str = ""
full_response: str = ""
async for line in response.aiter_lines():
line = line.strip()
if not line:
continue
# Remove "data: "
line = line[6:]
if line == "[DONE]":
break
resp: dict = json.loads(line)
if "error" in resp:
raise Exception(f"{resp['error']}")
choices = resp.get("choices")
if not choices:
continue
delta: dict[str, str] = choices[0].get("delta")
if not delta:
continue
if "role" in delta:
response_role = delta["role"]
if "content" in delta:
content: str = delta["content"]
full_response += content
yield content
self.add_to_conversation(full_response, response_role, convo_id=convo_id)
async def ask_async(
self,
prompt: str,
role: str = "user",
convo_id: str = "default",
model: str = None,
pass_history: bool = True,
**kwargs,
) -> str:
"""
Non-streaming ask
"""
response = self.ask_stream_async(
prompt=prompt,
role=role,
convo_id=convo_id,
model=model,
pass_history=pass_history,
**kwargs,
)
full_response: str = "".join([r async for r in response])
return full_response
def reset(self, convo_id: str = "default", system_prompt: str = None) -> None:
"""
Reset the conversation
"""
self.conversation[convo_id] = [
{"role": "system", "content": system_prompt or self.system_prompt},
]
@retry(wait=wait_random_exponential(min=2, max=5), stop=stop_after_attempt(3))
async def oneTimeAsk(
self,
prompt: str,
role: str = "user",
model: str = None,
**kwargs,
) -> str:
async with self.aclient.post(
url=self.api_url,
json={
"model": model or self.engine,
"messages": prompt,
# kwargs
"temperature": kwargs.get("temperature", self.temperature),
"top_p": kwargs.get("top_p", self.top_p),
"presence_penalty": kwargs.get(
"presence_penalty",
self.presence_penalty,
),
"frequency_penalty": kwargs.get(
"frequency_penalty",
self.frequency_penalty,
),
"user": role,
},
headers={"Authorization": f"Bearer {kwargs.get('api_key', self.api_key)}"},
timeout=kwargs.get("timeout", self.timeout),
) as response:
resp = await response.read()
return json.loads(resp)["choices"][0]["message"]["content"]

72
src/main.py
View File

@ -2,6 +2,8 @@ import asyncio
import json
import os
from pathlib import Path
import signal
import sys
from bot import Bot
from log import getlogger
@ -13,8 +15,12 @@ async def main():
need_import_keys = False
config_path = Path(os.path.dirname(__file__)).parent / "config.json"
if os.path.isfile(config_path):
fp = open(config_path, encoding="utf8")
config = json.load(fp)
try:
fp = open(config_path, encoding="utf8")
config = json.load(fp)
except Exception:
logger.error("config.json load error, please check the file")
sys.exit(1)
matrix_bot = Bot(
homeserver=config.get("homeserver"),
@ -22,21 +28,21 @@ async def main():
password=config.get("password"),
device_id=config.get("device_id"),
room_id=config.get("room_id"),
openai_api_key=config.get("openai_api_key"),
api_endpoint=config.get("api_endpoint"),
access_token=config.get("access_token"),
bard_token=config.get("bard_token"),
jailbreakEnabled=config.get("jailbreakEnabled"),
bing_auth_cookie=config.get("bing_auth_cookie"),
markdown_formatted=config.get("markdown_formatted"),
output_four_images=config.get("output_four_images"),
import_keys_path=config.get("import_keys_path"),
import_keys_password=config.get("import_keys_password"),
openai_api_key=config.get("openai_api_key"),
gpt_api_endpoint=config.get("gpt_api_endpoint"),
gpt_model=config.get("gpt_model"),
max_tokens=int(config.get("max_tokens")),
top_p=float(config.get("top_p")),
presence_penalty=float(config.get("presence_penalty")),
frequency_penalty=float(config.get("frequency_penalty")),
reply_count=int(config.get("reply_count")),
system_prompt=config.get("system_prompt"),
temperature=float(config.get("temperature")),
flowise_api_url=config.get("flowise_api_url"),
flowise_api_key=config.get("flowise_api_key"),
pandora_api_endpoint=config.get("pandora_api_endpoint"),
pandora_api_model=config.get("pandora_api_model"),
temperature=float(config.get("temperature", 0.8)),
timeout=float(config.get("timeout")),
)
if (
config.get("import_keys_path")
@ -51,24 +57,21 @@ async def main():
password=os.environ.get("PASSWORD"),
device_id=os.environ.get("DEVICE_ID"),
room_id=os.environ.get("ROOM_ID"),
openai_api_key=os.environ.get("OPENAI_API_KEY"),
api_endpoint=os.environ.get("API_ENDPOINT"),
access_token=os.environ.get("ACCESS_TOKEN"),
bard_token=os.environ.get("BARD_TOKEN"),
jailbreakEnabled=os.environ.get("JAILBREAKENABLED", "false").lower()
in ("true", "1", "t"),
bing_auth_cookie=os.environ.get("BING_AUTH_COOKIE"),
markdown_formatted=os.environ.get("MARKDOWN_FORMATTED", "false").lower()
in ("true", "1", "t"),
output_four_images=os.environ.get("OUTPUT_FOUR_IMAGES", "false").lower()
in ("true", "1", "t"),
import_keys_path=os.environ.get("IMPORT_KEYS_PATH"),
import_keys_password=os.environ.get("IMPORT_KEYS_PASSWORD"),
openai_api_key=os.environ.get("OPENAI_API_KEY"),
gpt_api_endpoint=os.environ.get("GPT_API_ENDPOINT"),
gpt_model=os.environ.get("GPT_MODEL"),
max_tokens=int(os.environ.get("MAX_TOKENS")),
top_p=float(os.environ.get("TOP_P")),
presence_penalty=float(os.environ.get("PRESENCE_PENALTY")),
frequency_penalty=float(os.environ.get("FREQUENCY_PENALTY")),
reply_count=int(os.environ.get("REPLY_COUNT")),
system_prompt=os.environ.get("SYSTEM_PROMPT"),
temperature=float(os.environ.get("TEMPERATURE")),
flowise_api_url=os.environ.get("FLOWISE_API_URL"),
flowise_api_key=os.environ.get("FLOWISE_API_KEY"),
pandora_api_endpoint=os.environ.get("PANDORA_API_ENDPOINT"),
pandora_api_model=os.environ.get("PANDORA_API_MODEL"),
temperature=float(os.environ.get("TEMPERATURE", 0.8)),
timeout=float(os.environ.get("TIMEOUT")),
)
if (
os.environ.get("IMPORT_KEYS_PATH")
@ -80,7 +83,20 @@ async def main():
if need_import_keys:
logger.info("start import_keys process, this may take a while...")
await matrix_bot.import_keys()
await matrix_bot.sync_forever(timeout=30000, full_state=True)
sync_task = asyncio.create_task(
matrix_bot.sync_forever(timeout=30000, full_state=True)
)
# handle signal interrupt
loop = asyncio.get_running_loop()
for signame in ("SIGINT", "SIGTERM"):
loop.add_signal_handler(
getattr(signal, signame),
lambda: asyncio.create_task(matrix_bot.close(sync_task)),
)
await sync_task
if __name__ == "__main__":

111
src/pandora_api.py
View File

@ -1,111 +0,0 @@
# API wrapper for https://github.com/pengzhile/pandora/blob/master/doc/HTTP-API.md
import asyncio
import uuid
import aiohttp
class Pandora:
def __init__(
self,
api_endpoint: str,
clientSession: aiohttp.ClientSession,
) -> None:
self.api_endpoint = api_endpoint.rstrip("/")
self.session = clientSession
async def __aenter__(self):
return self
async def __aexit__(self, exc_type, exc_val, exc_tb):
await self.session.close()
async def gen_title(self, data: dict, conversation_id: str) -> None:
"""
data = {
"model": "",
"message_id": "",
}
:param data: dict
:param conversation_id: str
:return: None
"""
api_endpoint = (
self.api_endpoint + f"/api/conversation/gen_title/{conversation_id}"
)
async with self.session.post(api_endpoint, json=data) as resp:
return await resp.json()
async def talk(self, data: dict) -> None:
api_endpoint = self.api_endpoint + "/api/conversation/talk"
"""
data = {
"prompt": "",
"model": "",
"parent_message_id": "",
"conversation_id": "", # ignore at the first time
"stream": True,
}
:param data: dict
:return: None
"""
data["message_id"] = str(uuid.uuid4())
async with self.session.post(api_endpoint, json=data) as resp:
return await resp.json()
async def goon(self, data: dict) -> None:
"""
data = {
"model": "",
"parent_message_id": "",
"conversation_id": "",
"stream": True,
}
"""
api_endpoint = self.api_endpoint + "/api/conversation/goon"
async with self.session.post(api_endpoint, json=data) as resp:
return await resp.json()
async def test():
model = "text-davinci-002-render-sha-mobile"
api_endpoint = "http://127.0.0.1:8008"
async with aiohttp.ClientSession() as session:
client = Pandora(api_endpoint, session)
conversation_id = None
parent_message_id = str(uuid.uuid4())
first_time = True
async with client:
while True:
prompt = input("BobMaster: ")
if conversation_id:
data = {
"prompt": prompt,
"model": model,
"parent_message_id": parent_message_id,
"conversation_id": conversation_id,
"stream": False,
}
else:
data = {
"prompt": prompt,
"model": model,
"parent_message_id": parent_message_id,
"stream": False,
}
response = await client.talk(data)
conversation_id = response["conversation_id"]
parent_message_id = response["message"]["id"]
content = response["message"]["content"]["parts"][0]
print("ChatGPT: " + content + "\n")
if first_time:
first_time = False
data = {
"model": model,
"message_id": parent_message_id,
}
response = await client.gen_title(data, conversation_id)
if __name__ == "__main__":
asyncio.run(test())

40
src/send_message.py
View File

@ -1,5 +1,3 @@
import re
import markdown
from log import getlogger
from nio import AsyncClient
@ -14,32 +12,19 @@ async def send_room_message(
sender_id: str = "",
user_message: str = "",
reply_to_event_id: str = "",
markdown_formatted: bool = False,
) -> None:
NORMAL_BODY = content = {
"msgtype": "m.text",
"body": reply_message,
}
if reply_to_event_id == "":
if markdown_formatted:
# only format message contains multiline codes, *, |
if re.search(r"```|\*|\|", reply_message) is not None:
content = {
"msgtype": "m.text",
"body": reply_message,
"format": "org.matrix.custom.html",
"formatted_body": markdown.markdown(
reply_message,
extensions=["nl2br", "tables", "fenced_code"],
),
}
else:
content = NORMAL_BODY
else:
content = NORMAL_BODY
content = {
"msgtype": "m.text",
"body": reply_message,
"format": "org.matrix.custom.html",
"formatted_body": markdown.markdown(
reply_message,
extensions=["nl2br", "tables", "fenced_code"],
),
}
else:
body = r"> <" + sender_id + r"> " + user_message + r"\n\n" + reply_message
body = "> <" + sender_id + "> " + user_message + "\n\n" + reply_message
format = r"org.matrix.custom.html"
formatted_body = (
r'<mx-reply><blockquote><a href="https://matrix.to/#/'
@ -53,7 +38,10 @@ async def send_room_message(
+ r"</a><br>"
+ user_message
+ r"</blockquote></mx-reply>"
+ reply_message
+ markdown.markdown(
reply_message,
extensions=["nl2br", "tables", "fenced_code"],
)
)
content = {

BIN
sync_db Normal file
View File

Binary file not shown.