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.gitignore .gitignore
images images
*.md *.md
Dockerfile Dockerfile
Dockerfile-dev Dockerfile-dev
compose.yaml .dockerignore
compose-dev.yaml config.json
.dockerignore config.json.sample
config.json .vscode
config.json.sample bot.log
.vscode venv
bot.log .venv
venv *.yaml
.venv *.yml
*.yaml .git
*.yml .idea
.git __pycache__
.idea .env
__pycache__ .env.example
src/__pycache__ .github
.env settings.js
.env.example
.github
settings.js
mattermost-server
tests
full-config.json.example
config.json.example
.full-env.example

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@ -1,6 +1,9 @@
SERVER_URL="xxxxx.xxxxxx.xxxxxxxxx" SERVER_URL="xxxxx.xxxxxx.xxxxxxxxx"
ACCESS_TOKEN="xxxxxxxxxxxxxxxxx"
USERNAME="@chatgpt" USERNAME="@chatgpt"
EMAIL="xxxxxx" OPENAI_API_KEY="sk-xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx"
PASSWORD="xxxxxxxxxxxxxx" BING_API_ENDPOINT="http://api:3000/conversation"
OPENAI_API_KEY="xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx" BARD_TOKEN="xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx."
GPT_MODEL="gpt-3.5-turbo" BING_AUTH_COOKIE="xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx"
PANDORA_API_ENDPOINT="http://pandora:8008"
PANDORA_API_MODEL="text-davinci-002-render-sha-mobile"

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@ -1,24 +0,0 @@
SERVER_URL="xxxxx.xxxxxx.xxxxxxxxx"
EMAIL="xxxxxx"
USERNAME="@chatgpt"
PASSWORD="xxxxxxxxxxxxxx"
PORT=443
SCHEME="https"
OPENAI_API_KEY="xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx"
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
IMAGE_GENERATION_ENDPOINT="http://127.0.0.1:7860/sdapi/v1/txt2img"
IMAGE_GENERATION_BACKEND="sdwui" # openai or sdwui or localai
IMAGE_GENERATION_SIZE="512x512"
IMAGE_FORMAT="jpeg"
SDWUI_STEPS=20
SDWUI_SAMPLER_NAME="Euler a"
SDWUI_CFG_SCALE=7
TIMEOUT=120.0

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@ -70,4 +70,4 @@ jobs:
tags: ${{ steps.meta2.outputs.tags }} tags: ${{ steps.meta2.outputs.tags }}
labels: ${{ steps.meta2.outputs.labels }} labels: ${{ steps.meta2.outputs.labels }}
cache-from: type=gha cache-from: type=gha
cache-to: type=gha,mode=max cache-to: type=gha,mode=max

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.github/workflows/pylint.yml vendored Normal file
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name: Pylint
on: [push, pull_request]
jobs:
build:
runs-on: ubuntu-latest
strategy:
matrix:
python-version: ["3.10", "3.11"]
steps:
- uses: actions/checkout@v3
- name: Set up Python ${{ matrix.python-version }}
uses: actions/setup-python@v4
with:
python-version: ${{ matrix.python-version }}
cache: 'pip'
- name: Install dependencies
run: |
pip install -U pip setuptools wheel
pip install -r requirements.txt
pip install pylint
- name: Analysing the code with pylint
run: |
pylint $(git ls-files '*.py') --errors-only

279
.gitignore vendored
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@ -1,140 +1,139 @@
# Byte-compiled / optimized / DLL files # Byte-compiled / optimized / DLL files
__pycache__/ __pycache__/
*.py[cod] *.py[cod]
*$py.class *$py.class
# C extensions # C extensions
*.so *.so
# Distribution / packaging # Distribution / packaging
.Python .Python
build/ build/
develop-eggs/ develop-eggs/
dist/ dist/
downloads/ downloads/
eggs/ eggs/
.eggs/ .eggs/
lib/ lib/
lib64/ lib64/
parts/ parts/
sdist/ sdist/
var/ var/
wheels/ wheels/
pip-wheel-metadata/ pip-wheel-metadata/
share/python-wheels/ share/python-wheels/
*.egg-info/ *.egg-info/
.installed.cfg .installed.cfg
*.egg *.egg
MANIFEST MANIFEST
# PyInstaller # PyInstaller
# Usually these files are written by a python script from a template # Usually these files are written by a python script from a template
# before PyInstaller builds the exe, so as to inject date/other infos into it. # before PyInstaller builds the exe, so as to inject date/other infos into it.
*.manifest *.manifest
*.spec *.spec
# Installer logs # Installer logs
pip-log.txt pip-log.txt
pip-delete-this-directory.txt pip-delete-this-directory.txt
# Unit test / coverage reports # Unit test / coverage reports
htmlcov/ htmlcov/
.tox/ .tox/
.nox/ .nox/
.coverage .coverage
.coverage.* .coverage.*
.cache .cache
nosetests.xml nosetests.xml
coverage.xml coverage.xml
*.cover *.cover
*.py,cover *.py,cover
.hypothesis/ .hypothesis/
.pytest_cache/ .pytest_cache/
# Translations # Translations
*.mo *.mo
*.pot *.pot
# Django stuff: # Django stuff:
*.log *.log
local_settings.py local_settings.py
db.sqlite3 db.sqlite3
db.sqlite3-journal db.sqlite3-journal
# Flask stuff: # Flask stuff:
instance/ instance/
.webassets-cache .webassets-cache
# Scrapy stuff: # Scrapy stuff:
.scrapy .scrapy
# Sphinx documentation # Sphinx documentation
docs/_build/ docs/_build/
# PyBuilder # PyBuilder
target/ target/
# Jupyter Notebook # Jupyter Notebook
.ipynb_checkpoints .ipynb_checkpoints
# IPython # IPython
profile_default/ profile_default/
ipython_config.py ipython_config.py
# pyenv # pyenv
.python-version .python-version
# pipenv # pipenv
# According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control. # According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control.
# However, in case of collaboration, if having platform-specific dependencies or dependencies # However, in case of collaboration, if having platform-specific dependencies or dependencies
# having no cross-platform support, pipenv may install dependencies that don't work, or not # having no cross-platform support, pipenv may install dependencies that don't work, or not
# install all needed dependencies. # install all needed dependencies.
#Pipfile.lock #Pipfile.lock
# PEP 582; used by e.g. github.com/David-OConnor/pyflow # PEP 582; used by e.g. github.com/David-OConnor/pyflow
__pypackages__/ __pypackages__/
# Celery stuff # Celery stuff
celerybeat-schedule celerybeat-schedule
celerybeat.pid celerybeat.pid
# SageMath parsed files # SageMath parsed files
*.sage.py *.sage.py
# custom path # custom path
images images
Dockerfile-dev Dockerfile-dev
compose-dev.yaml compose-dev.yaml
settings.js settings.js
# Environments # Environments
.env .env
.venv .venv
env/ env/
venv/ venv/
ENV/ ENV/
env.bak/ env.bak/
venv.bak/ venv.bak/
config.json config.json
# Spyder project settings # Spyder project settings
.spyderproject .spyderproject
.spyproject .spyproject
# Rope project settings # Rope project settings
.ropeproject .ropeproject
# mkdocs documentation # mkdocs documentation
/site /site
# mypy # mypy
.mypy_cache/ .mypy_cache/
.dmypy.json .dmypy.json
dmypy.json dmypy.json
# Pyre type checker # Pyre type checker
.pyre/ .pyre/
# custom # custom
compose-dev.yaml compose-local-dev.yaml
mattermost-server

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repos:
- repo: https://github.com/pre-commit/pre-commit-hooks
rev: v4.5.0
hooks:
- id: trailing-whitespace
- id: end-of-file-fixer
- id: check-yaml
- repo: https://github.com/psf/black
rev: 23.12.0
hooks:
- id: black
- repo: https://github.com/astral-sh/ruff-pre-commit
rev: v0.1.7
hooks:
- id: ruff
args: [--fix, --exit-non-zero-on-fix]

3
.vscode/settings.json vendored Normal file
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{
"python.formatting.provider": "black"
}

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BingImageGen.py Normal file
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"""
Code derived from:
https://github.com/acheong08/EdgeGPT/blob/f940cecd24a4818015a8b42a2443dd97c3c2a8f4/src/ImageGen.py
"""
from log import getlogger
from uuid import uuid4
import os
import contextlib
import aiohttp
import asyncio
import random
import requests
import regex
logger = getlogger()
BING_URL = "https://www.bing.com"
# Generate random IP between range 13.104.0.0/14
FORWARDED_IP = (
f"13.{random.randint(104, 107)}.{random.randint(0, 255)}.{random.randint(0, 255)}"
)
HEADERS = {
"accept": "text/html,application/xhtml+xml,application/xml;q=0.9,image/webp,image/apng,*/*;q=0.8,application/signed-exchange;v=b3;q=0.7",
"accept-language": "en-US,en;q=0.9",
"cache-control": "max-age=0",
"content-type": "application/x-www-form-urlencoded",
"referrer": "https://www.bing.com/images/create/",
"origin": "https://www.bing.com",
"user-agent": "Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/110.0.0.0 Safari/537.36 Edg/110.0.1587.63",
"x-forwarded-for": FORWARDED_IP,
}
class ImageGenAsync:
"""
Image generation by Microsoft Bing
Parameters:
auth_cookie: str
"""
def __init__(self, auth_cookie: str, quiet: bool = True) -> None:
self.session = aiohttp.ClientSession(
headers=HEADERS,
cookies={"_U": auth_cookie},
)
self.quiet = quiet
async def __aenter__(self):
return self
async def __aexit__(self, *excinfo) -> None:
await self.session.close()
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 get_images(self, prompt: str) -> list:
"""
Fetches image links from Bing
Parameters:
prompt: str
"""
if not self.quiet:
print("Sending request...")
url_encoded_prompt = requests.utils.quote(prompt)
# https://www.bing.com/images/create?q=<PROMPT>&rt=3&FORM=GENCRE
url = f"{BING_URL}/images/create?q={url_encoded_prompt}&rt=4&FORM=GENCRE"
async with self.session.post(url, allow_redirects=False) as response:
content = await response.text()
if "this prompt has been blocked" in content.lower():
raise Exception(
"Your prompt has been blocked by Bing. Try to change any bad words and try again.",
)
if response.status != 302:
# if rt4 fails, try rt3
url = (
f"{BING_URL}/images/create?q={url_encoded_prompt}&rt=3&FORM=GENCRE"
)
async with self.session.post(
url,
allow_redirects=False,
timeout=200,
) as response3:
if response3.status != 302:
print(f"ERROR: {response3.text}")
raise Exception("Redirect failed")
response = response3
# Get redirect URL
redirect_url = response.headers["Location"].replace("&nfy=1", "")
request_id = redirect_url.split("id=")[-1]
await self.session.get(f"{BING_URL}{redirect_url}")
# https://www.bing.com/images/create/async/results/{ID}?q={PROMPT}
polling_url = f"{BING_URL}/images/create/async/results/{request_id}?q={url_encoded_prompt}"
# Poll for results
if not self.quiet:
print("Waiting for results...")
while True:
if not self.quiet:
print(".", end="", flush=True)
# By default, timeout is 300s, change as needed
response = await self.session.get(polling_url)
if response.status != 200:
raise Exception("Could not get results")
content = await response.text()
if content and content.find("errorMessage") == -1:
break
await asyncio.sleep(1)
continue
# Use regex to search for src=""
image_links = regex.findall(r'src="([^"]+)"', content)
# Remove size limit
normal_image_links = [link.split("?w=")[0] for link in image_links]
# Remove duplicates
normal_image_links = list(set(normal_image_links))
# Bad images
bad_images = [
"https://r.bing.com/rp/in-2zU3AJUdkgFe7ZKv19yPBHVs.png",
"https://r.bing.com/rp/TX9QuO3WzcCJz1uaaSwQAz39Kb0.jpg",
]
for im in normal_image_links:
if im in bad_images:
raise Exception("Bad images")
# No images
if not normal_image_links:
raise Exception("No images")
return normal_image_links
async def save_images(self, links: list, output_dir: str) -> str:
"""
Saves images to output directory
"""
if not self.quiet:
print("\nDownloading images...")
with contextlib.suppress(FileExistsError):
os.mkdir(output_dir)
# image name
image_name = str(uuid4())
# we just need one image for better display in chat room
if links:
link = links.pop()
image_path = os.path.join(output_dir, f"{image_name}.jpeg")
try:
async with self.session.get(link, raise_for_status=True) as response:
# save response to file
with open(image_path, "wb") as output_file:
async for chunk in response.content.iter_chunked(8192):
output_file.write(chunk)
return f"{output_dir}/{image_name}.jpeg"
except aiohttp.client_exceptions.InvalidURL as url_exception:
raise Exception(
"Inappropriate contents found in the generated images. Please try again or try another prompt.",
) from url_exception

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# Changelog
## v1.3.2
- Make gptbot more compatible
## v1.3.1
- Expose more stable diffusion webui api parameters
## v1.3.0
- Fix localai v2.0+ image generation
- Support specific output image format(jpeg, png) and size
## v1.2.0
- support sending typing state
## v1.1.0
- remove pandora
- refactor chat and image genderation backend
- reply in thread by default
- introduce pre-commit hooks
## v1.0.4
- refactor code structure and remove unused
- remove Bing AI and Google Bard due to technical problems
- bug fix and improvement

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@ -1,16 +1,16 @@
FROM python:3.11-alpine as base FROM python:3.11-alpine as base
FROM base as builder FROM base as builder
# RUN sed -i 's|v3\.\d*|edge|' /etc/apk/repositories # RUN sed -i 's|v3\.\d*|edge|' /etc/apk/repositories
RUN apk update && apk add --no-cache gcc musl-dev libffi-dev git RUN apk update && apk add --no-cache gcc musl-dev libffi-dev git
COPY requirements.txt . COPY requirements.txt .
RUN pip install -U pip setuptools wheel && pip install --user -r ./requirements.txt && rm ./requirements.txt RUN pip install -U pip setuptools wheel && pip install --user -r ./requirements.txt && rm ./requirements.txt
FROM base as runner FROM base as runner
RUN apk update && apk add --no-cache libffi-dev RUN apk update && apk add --no-cache libffi-dev
COPY --from=builder /root/.local /usr/local COPY --from=builder /root/.local /usr/local
COPY . /app COPY . /app
FROM runner FROM runner
WORKDIR /app WORKDIR /app
CMD ["python", "src/main.py"] CMD ["python", "main.py"]

42
LICENSE
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@ -1,21 +1,21 @@
MIT License MIT License
Copyright (c) 2023 BobMaster Copyright (c) 2023 BobMaster
Permission is hereby granted, free of charge, to any person obtaining a copy Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions: furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software. copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE. SOFTWARE.

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## Introduction ## Introduction
This is a simple Mattermost Bot that uses OpenAI's GPT API(or self-host models) to generate responses to user inputs. The bot responds to these commands: `!gpt`, `!chat` and `!new` and `!help` depending on the first word of the prompt. This is a simple Mattermost Bot that uses OpenAI's GPT API and Bing AI and Google Bard to generate responses to user inputs. The bot responds to these commands: `!gpt`, `!chat` and `!bing` and `!pic` and `!bard` and `!talk` and `!goon` and `!new` and `!help` depending on the first word of the prompt.
## Feature ## Feature
1. Support official openai api and self host models([LocalAI](https://localai.io/model-compatibility/)) 1. Support Openai ChatGPT and Bing AI and Google Bard
2. Image Generation with [DALL·E](https://platform.openai.com/docs/api-reference/images/create) or [LocalAI](https://localai.io/features/image-generation/) or [stable-diffusion-webui](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/API) 2. Support Bing Image Creator
## Installation and Setup 3. [pandora](https://github.com/pengzhile/pandora) with Session isolation support
See https://github.com/hibobmaster/mattermost_bot/wiki ## Installation and Setup
Edit `config.json` or `.env` with proper values See https://github.com/hibobmaster/mattermost_bot/wiki
```sh Edit `config.json` or `.env` with proper values
docker compose up -d
``` ```sh
docker compose up -d
## Commands ```
- `!help` help message ## Commands
- `!gpt + [prompt]` generate a one time response from chatGPT
- `!chat + [prompt]` chat using official chatGPT api with context conversation - `!help` help message
- `!pic + [prompt]` Image generation with DALL·E or LocalAI or stable-diffusion-webui - `!gpt + [prompt]` generate a one time response from chatGPT
- `!chat + [prompt]` chat using official chatGPT api with context conversation
- `!new` start a new converstaion - `!bing + [prompt]` chat with Bing AI with context conversation
- `!bard + [prompt]` chat with Google's Bard
## Demo - `!pic + [prompt]` generate an image from Bing Image Creator
Remove support for Bing AI, Google Bard due to technical problems.
![gpt command](https://imgur.com/vdT83Ln.jpg) The following commands need pandora http api: https://github.com/pengzhile/pandora/blob/master/doc/wiki_en.md#http-restful-api
![image generation](https://i.imgur.com/DQ3i3wW.jpg) - `!talk + [prompt]` chat using chatGPT web with context conversation
- `!goon` ask chatGPT to complete the missing part from previous conversation
## Thanks - `!new` start a new converstaion
<a href="https://jb.gg/OpenSourceSupport" target="_blank">
<img src="https://resources.jetbrains.com/storage/products/company/brand/logos/jb_beam.png" alt="JetBrains Logo (Main) logo." width="200" height="200"> ## Demo
</a>
![demo1](https://i.imgur.com/XRAQB4B.jpg)
![demo2](https://i.imgur.com/if72kyH.jpg)
![demo3](https://i.imgur.com/GHczfkv.jpg)
## Thanks
<a href="https://jb.gg/OpenSourceSupport" target="_blank">
<img src="https://resources.jetbrains.com/storage/products/company/brand/logos/jb_beam.png" alt="JetBrains Logo (Main) logo." width="200" height="200">
</a>

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askgpt.py Normal file
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import aiohttp
import asyncio
import json
from log import getlogger
logger = getlogger()
class askGPT:
def __init__(
self, session: aiohttp.ClientSession, api_endpoint: str, headers: str
) -> None:
self.session = session
self.api_endpoint = api_endpoint
self.headers = headers
async def oneTimeAsk(self, prompt: str) -> str:
jsons = {
"model": "gpt-3.5-turbo",
"messages": [
{
"role": "user",
"content": prompt,
},
],
}
max_try = 2
while max_try > 0:
try:
async with self.session.post(
url=self.api_endpoint, json=jsons, headers=self.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
# wait 2s
await asyncio.sleep(2)
continue
resp = await response.read()
return json.loads(resp)["choices"][0]["message"]["content"]
except Exception as e:
raise Exception(e)

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bard.py Normal file
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"""
Code derived from: https://github.com/acheong08/Bard/blob/main/src/Bard.py
"""
import random
import string
import re
import json
import requests
class Bardbot:
"""
A class to interact with Google Bard.
Parameters
session_id: str
The __Secure-1PSID cookie.
"""
__slots__ = [
"headers",
"_reqid",
"SNlM0e",
"conversation_id",
"response_id",
"choice_id",
"session",
]
def __init__(self, session_id):
headers = {
"Host": "bard.google.com",
"X-Same-Domain": "1",
"User-Agent": "Mozilla/5.0 (Windows NT 10.0; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/91.0.4472.114 Safari/537.36",
"Content-Type": "application/x-www-form-urlencoded;charset=UTF-8",
"Origin": "https://bard.google.com",
"Referer": "https://bard.google.com/",
}
self._reqid = int("".join(random.choices(string.digits, k=4)))
self.conversation_id = ""
self.response_id = ""
self.choice_id = ""
self.session = requests.Session()
self.session.headers = headers
self.session.cookies.set("__Secure-1PSID", session_id)
self.SNlM0e = self.__get_snlm0e()
def __get_snlm0e(self):
resp = self.session.get(url="https://bard.google.com/", timeout=10)
# Find "SNlM0e":"<ID>"
if resp.status_code != 200:
raise Exception("Could not get Google Bard")
SNlM0e = re.search(r"SNlM0e\":\"(.*?)\"", resp.text).group(1)
return SNlM0e
def ask(self, message: str) -> dict:
"""
Send a message to Google Bard and return the response.
:param message: The message to send to Google Bard.
:return: A dict containing the response from Google Bard.
"""
# url params
params = {
"bl": "boq_assistant-bard-web-server_20230326.21_p0",
"_reqid": str(self._reqid),
"rt": "c",
}
# message arr -> data["f.req"]. Message is double json stringified
message_struct = [
[message],
None,
[self.conversation_id, self.response_id, self.choice_id],
]
data = {
"f.req": json.dumps([None, json.dumps(message_struct)]),
"at": self.SNlM0e,
}
# do the request!
resp = self.session.post(
"https://bard.google.com/_/BardChatUi/data/assistant.lamda.BardFrontendService/StreamGenerate",
params=params,
data=data,
timeout=120,
)
chat_data = json.loads(resp.content.splitlines()[3])[0][2]
if not chat_data:
return {"content": f"Google Bard encountered an error: {resp.content}."}
json_chat_data = json.loads(chat_data)
results = {
"content": json_chat_data[0][0],
"conversation_id": json_chat_data[1][0],
"response_id": json_chat_data[1][1],
"factualityQueries": json_chat_data[3],
"textQuery": json_chat_data[2][0] if json_chat_data[2] is not None else "",
"choices": [{"id": i[0], "content": i[1]} for i in json_chat_data[4]],
}
self.conversation_id = results["conversation_id"]
self.response_id = results["response_id"]
self.choice_id = results["choices"][0]["id"]
self._reqid += 100000
return results

64
bing.py Normal file
View file

@ -0,0 +1,64 @@
import aiohttp
import json
import asyncio
from log import getlogger
# api_endpoint = "http://localhost:3000/conversation"
from log import getlogger
logger = getlogger()
class BingBot:
def __init__(
self,
session: aiohttp.ClientSession,
bing_api_endpoint: str,
jailbreakEnabled: bool = True,
):
self.data = {
"clientOptions.clientToUse": "bing",
}
self.bing_api_endpoint = bing_api_endpoint
self.session = session
self.jailbreakEnabled = jailbreakEnabled
if self.jailbreakEnabled:
self.data["jailbreakConversationId"] = True
async def ask_bing(self, prompt) -> str:
self.data["message"] = prompt
max_try = 2
while max_try > 0:
try:
resp = await self.session.post(
url=self.bing_api_endpoint, json=self.data, timeout=120
)
status_code = resp.status
body = await resp.read()
if not status_code == 200:
# print failed reason
logger.warning(str(resp.reason))
max_try = max_try - 1
await asyncio.sleep(2)
continue
json_body = json.loads(body)
if self.jailbreakEnabled:
self.data["jailbreakConversationId"] = json_body[
"jailbreakConversationId"
]
self.data["parentMessageId"] = json_body["messageId"]
else:
self.data["conversationSignature"] = json_body[
"conversationSignature"
]
self.data["conversationId"] = json_body["conversationId"]
self.data["clientId"] = json_body["clientId"]
self.data["invocationId"] = json_body["invocationId"]
return json_body["details"]["adaptiveCards"][0]["body"][0]["text"]
except Exception as e:
logger.error("Error Exception", exc_info=True)
return "Error, please retry"

426
bot.py Normal file
View file

@ -0,0 +1,426 @@
from mattermostdriver import Driver
from typing import Optional
import json
import asyncio
import re
import os
import aiohttp
from askgpt import askGPT
from v3 import Chatbot
from bing import BingBot
from bard import Bardbot
from BingImageGen import ImageGenAsync
from log import getlogger
from pandora import Pandora
import uuid
logger = getlogger()
class Bot:
def __init__(
self,
server_url: str,
username: str,
access_token: Optional[str] = None,
login_id: Optional[str] = None,
password: Optional[str] = None,
openai_api_key: Optional[str] = None,
openai_api_endpoint: Optional[str] = None,
bing_api_endpoint: Optional[str] = None,
pandora_api_endpoint: Optional[str] = None,
pandora_api_model: Optional[str] = None,
bard_token: Optional[str] = None,
bing_auth_cookie: Optional[str] = None,
port: int = 443,
timeout: int = 30,
) -> None:
if server_url is None:
raise ValueError("server url must be provided")
if port is None:
self.port = 443
if timeout is None:
self.timeout = 30
# login relative info
if access_token is None and password is None:
raise ValueError("Either token or password must be provided")
if access_token is not None:
self.driver = Driver(
{
"token": access_token,
"url": server_url,
"port": self.port,
"request_timeout": self.timeout,
}
)
else:
self.driver = Driver(
{
"login_id": login_id,
"password": password,
"url": server_url,
"port": self.port,
"request_timeout": self.timeout,
}
)
# @chatgpt
if username is None:
raise ValueError("username must be provided")
else:
self.username = username
# openai_api_endpoint
if openai_api_endpoint is None:
self.openai_api_endpoint = "https://api.openai.com/v1/chat/completions"
else:
self.openai_api_endpoint = openai_api_endpoint
# aiohttp session
self.session = aiohttp.ClientSession()
self.openai_api_key = openai_api_key
# initialize chatGPT class
if self.openai_api_key is not None:
# request header for !gpt command
self.headers = {
"Content-Type": "application/json",
"Authorization": f"Bearer {self.openai_api_key}",
}
self.askgpt = askGPT(
self.session,
self.openai_api_endpoint,
self.headers,
)
self.chatbot = Chatbot(api_key=self.openai_api_key)
else:
logger.warning(
"openai_api_key is not provided, !gpt and !chat command will not work"
)
self.bing_api_endpoint = bing_api_endpoint
# initialize bingbot
if self.bing_api_endpoint is not None:
self.bingbot = BingBot(
session=self.session,
bing_api_endpoint=self.bing_api_endpoint,
)
else:
logger.warning(
"bing_api_endpoint is not provided, !bing command will not work"
)
self.pandora_api_endpoint = pandora_api_endpoint
# 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 = {}
self.bard_token = bard_token
# initialize bard
if self.bard_token is not None:
self.bardbot = Bardbot(session_id=self.bard_token)
else:
logger.warning("bard_token is not provided, !bard command will not work")
self.bing_auth_cookie = bing_auth_cookie
# initialize image generator
if self.bing_auth_cookie is not None:
self.imagegen = ImageGenAsync(auth_cookie=self.bing_auth_cookie)
else:
logger.warning(
"bing_auth_cookie is not provided, !pic command will not work"
)
# regular expression to match keyword
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*(.+)$")
self.help_prog = re.compile(r"^\s*!help\s*.*$")
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*.*$")
# close session
def __del__(self) -> None:
self.driver.disconnect()
def login(self) -> None:
self.driver.login()
def pandora_init(self, user_id: str) -> None:
self.pandora_data[user_id] = {
"conversation_id": None,
"parent_message_id": str(uuid.uuid4()),
"first_time": True
}
async def run(self) -> None:
await self.driver.init_websocket(self.websocket_handler)
# websocket handler
async def websocket_handler(self, message) -> None:
print(message)
response = json.loads(message)
if "event" in response:
event_type = response["event"]
if event_type == "posted":
raw_data = response["data"]["post"]
raw_data_dict = json.loads(raw_data)
user_id = raw_data_dict["user_id"]
channel_id = raw_data_dict["channel_id"]
sender_name = response["data"]["sender_name"]
raw_message = raw_data_dict["message"]
if user_id not in self.pandora_data:
self.pandora_init(user_id)
try:
asyncio.create_task(
self.message_callback(
raw_message, channel_id, user_id, sender_name
)
)
except Exception as e:
await asyncio.to_thread(self.send_message, channel_id, f"{e}")
# message callback
async def message_callback(
self, raw_message: str, channel_id: str, user_id: str, sender_name: str
) -> None:
# prevent command trigger loop
if sender_name != self.username:
message = raw_message
if self.openai_api_key is not None:
# !gpt command trigger handler
if self.gpt_prog.match(message):
prompt = self.gpt_prog.match(message).group(1)
try:
response = await self.gpt(prompt)
await asyncio.to_thread(
self.send_message, channel_id, f"{response}"
)
except Exception as e:
logger.error(e, exc_info=True)
raise Exception(e)
# !chat command trigger handler
elif self.chat_prog.match(message):
prompt = self.chat_prog.match(message).group(1)
try:
response = await self.chat(prompt)
await asyncio.to_thread(
self.send_message, channel_id, f"{response}"
)
except Exception as e:
logger.error(e, exc_info=True)
raise Exception(e)
if self.bing_api_endpoint is not None:
# !bing command trigger handler
if self.bing_prog.match(message):
prompt = self.bing_prog.match(message).group(1)
try:
response = await self.bingbot.ask_bing(prompt)
await asyncio.to_thread(
self.send_message, channel_id, f"{response}"
)
except Exception as e:
logger.error(e, exc_info=True)
raise Exception(e)
if self.pandora_api_endpoint is not None:
# !talk command trigger handler
if self.talk_prog.match(message):
prompt = self.talk_prog.match(message).group(1)
try:
if self.pandora_data[user_id]["conversation_id"] is not None:
data = {
"prompt": prompt,
"model": self.pandora_api_model,
"parent_message_id": self.pandora_data[user_id]["parent_message_id"],
"conversation_id": self.pandora_data[user_id]["conversation_id"],
"stream": False,
}
else:
data = {
"prompt": prompt,
"model": self.pandora_api_model,
"parent_message_id": self.pandora_data[user_id]["parent_message_id"],
"stream": False,
}
response = await self.pandora.talk(data)
self.pandora_data[user_id]["conversation_id"] = response['conversation_id']
self.pandora_data[user_id]["parent_message_id"] = response['message']['id']
content = response['message']['content']['parts'][0]
if self.pandora_data[user_id]["first_time"]:
self.pandora_data[user_id]["first_time"] = False
data = {
"model": self.pandora_api_model,
"message_id": self.pandora_data[user_id]["parent_message_id"],
}
await self.pandora.gen_title(data, self.pandora_data[user_id]["conversation_id"])
await asyncio.to_thread(
self.send_message, channel_id, f"{content}"
)
except Exception as e:
logger.error(e, exc_info=True)
raise Exception(e)
# !goon command trigger handler
if self.goon_prog.match(message) and self.pandora_data[user_id]["conversation_id"] is not None:
try:
data = {
"model": self.pandora_api_model,
"parent_message_id": self.pandora_data[user_id]["parent_message_id"],
"conversation_id": self.pandora_data[user_id]["conversation_id"],
"stream": False,
}
response = await self.pandora.goon(data)
self.pandora_data[user_id]["conversation_id"] = response['conversation_id']
self.pandora_data[user_id]["parent_message_id"] = response['message']['id']
content = response['message']['content']['parts'][0]
await asyncio.to_thread(
self.send_message, channel_id, f"{content}"
)
except Exception as e:
logger.error(e, exc_info=True)
raise Exception(e)
# !new command trigger handler
if self.new_prog.match(message):
self.pandora_init(user_id)
try:
await asyncio.to_thread(
self.send_message, channel_id, "New conversation created, please use !talk to start chatting!"
)
except Exception:
pass
if self.bard_token is not None:
# !bard command trigger handler
if self.bard_prog.match(message):
prompt = self.bard_prog.match(message).group(1)
try:
# response is dict object
response = await self.bard(prompt)
content = str(response["content"]).strip()
await asyncio.to_thread(
self.send_message, channel_id, f"{content}"
)
except Exception as e:
logger.error(e, exc_info=True)
raise Exception(e)
if self.bing_auth_cookie is not None:
# !pic command trigger handler
if self.pic_prog.match(message):
prompt = self.pic_prog.match(message).group(1)
# generate image
try:
links = await self.imagegen.get_images(prompt)
image_path = await self.imagegen.save_images(links, "images")
except Exception as e:
logger.error(e, exc_info=True)
raise Exception(e)
# send image
try:
await asyncio.to_thread(
self.send_file, channel_id, prompt, image_path
)
except Exception as e:
logger.error(e, exc_info=True)
raise Exception(e)
# !help command trigger handler
if self.help_prog.match(message):
try:
await asyncio.to_thread(self.send_message, channel_id, self.help())
except Exception as e:
logger.error(e, exc_info=True)
# send message to room
def send_message(self, channel_id: str, message: str) -> None:
self.driver.posts.create_post(
options={
"channel_id": channel_id,
"message": message
}
)
# send file to room
def send_file(self, channel_id: str, message: str, filepath: str) -> None:
filename = os.path.split(filepath)[-1]
try:
file_id = self.driver.files.upload_file(
channel_id=channel_id,
files={
"files": (filename, open(filepath, "rb")),
},
)["file_infos"][0]["id"]
except Exception as e:
logger.error(e, exc_info=True)
raise Exception(e)
try:
self.driver.posts.create_post(
options={
"channel_id": channel_id,
"message": message,
"file_ids": [file_id],
}
)
# remove image after posting
os.remove(filepath)
except Exception as e:
logger.error(e, exc_info=True)
raise Exception(e)
# !gpt command function
async def gpt(self, prompt: str) -> str:
return await self.askgpt.oneTimeAsk(prompt)
# !chat command function
async def chat(self, prompt: str) -> str:
return await self.chatbot.ask_async(prompt)
# !bing command function
async def bing(self, prompt: str) -> str:
return await self.bingbot.ask_bing(prompt)
# !bard command function
async def bard(self, prompt: str) -> str:
return await asyncio.to_thread(self.bardbot.ask, prompt)
# !help command function
def help(self) -> str:
help_info = (
"!gpt [content], generate response without context conversation\n"
+ "!chat [content], chat with context conversation\n"
+ "!bing [content], chat with context conversation powered by Bing AI\n"
+ "!bard [content], chat with Google's Bard\n"
+ "!pic [prompt], Image generation by Microsoft Bing\n"
+ "!talk [content], talk using chatgpt web\n"
+ "!goon, continue the incomplete conversation\n"
+ "!new, start a new conversation\n"
+ "!help, help message"
)
return help_info

View file

@ -11,6 +11,14 @@ services:
networks: networks:
- mattermost_network - mattermost_network
# api:
# image: hibobmaster/node-chatgpt-api:latest
# container_name: node-chatgpt-api
# volumes:
# - ./settings.js:/var/chatgpt-api/settings.js
# networks:
# - mattermost_network
# pandora: # pandora:
# image: pengzhile/pandora # image: pengzhile/pandora
# container_name: pandora # container_name: pandora
@ -22,4 +30,4 @@ services:
# - mattermost_network # - mattermost_network
networks: networks:
mattermost_network: mattermost_network:

View file

@ -1,8 +1,11 @@
{ {
"server_url": "xxxx.xxxx.xxxxx", "server_url": "xxxx.xxxx.xxxxx",
"email": "xxxxx", "access_token": "xxxxxxxxxxxxxxxxxxxxxx",
"username": "@chatgpt", "username": "@chatgpt",
"password": "xxxxxxxxxxxxxxxxx", "openai_api_key": "sk-xxxxxxxxxxxxxxxxxxx",
"openai_api_key": "xxxxxxxxxxxxxxxxxxxxxxxxx", "bing_api_endpoint": "http://api:3000/conversation",
"gpt_model": "gpt-3.5-turbo" "bard_token": "xxxxxxxxxxxxxxxxxxxxxxxxxxxxx.",
} "bing_auth_cookie": "xxxxxxxxxxxxxxxxxxxxxxxxxxxxxx",
"pandora_api_endpoint": "http://127.0.0.1:8008",
"pandora_api_model": "text-davinci-002-render-sha-mobile"
}

View file

@ -1,26 +0,0 @@
{
"server_url": "localhost",
"email": "bot@hibobmaster.com",
"username": "@bot",
"password": "SfBKY%K7*e&a%ZX$3g@Am&jQ",
"port": 8065,
"scheme": "http",
"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",
"image_generation_endpoint": "http://localai:8080/v1/images/generations",
"image_generation_backend": "localai",
"image_generation_size": "512x512",
"sdwui_steps": 20,
"sdwui_sampler_name": "Euler a",
"sdwui_cfg_scale": 7,
"image_format": "jpeg",
"timeout": 120.0
}

View file

@ -1,30 +1,30 @@
import logging import logging
def getlogger(): def getlogger():
# create a custom logger if not already created # create a custom logger if not already created
logger = logging.getLogger(__name__) logger = logging.getLogger(__name__)
if not logger.hasHandlers(): if not logger.hasHandlers():
logger.setLevel(logging.INFO) logger.setLevel(logging.INFO)
# create handlers # create handlers
info_handler = logging.StreamHandler() info_handler = logging.StreamHandler()
error_handler = logging.FileHandler("bot.log", mode="a") error_handler = logging.FileHandler("bot.log", mode="a")
error_handler.setLevel(logging.ERROR) error_handler.setLevel(logging.ERROR)
info_handler.setLevel(logging.INFO) info_handler.setLevel(logging.INFO)
# create formatters # create formatters
error_format = logging.Formatter( error_format = logging.Formatter(
"%(asctime)s - %(name)s - %(funcName)s - %(levelname)s - %(message)s" "%(asctime)s - %(name)s - %(funcName)s - %(levelname)s - %(message)s"
) )
info_format = logging.Formatter("%(asctime)s - %(levelname)s - %(message)s") info_format = logging.Formatter("%(asctime)s - %(levelname)s - %(message)s")
# set formatter # set formatter
error_handler.setFormatter(error_format) error_handler.setFormatter(error_format)
info_handler.setFormatter(info_format) info_handler.setFormatter(info_format)
# add handlers to logger # add handlers to logger
logger.addHandler(error_handler) logger.addHandler(error_handler)
logger.addHandler(info_handler) logger.addHandler(info_handler)
return logger return logger

53
main.py Normal file
View file

@ -0,0 +1,53 @@
from bot import Bot
import json
import os
import asyncio
async def main():
if os.path.exists("config.json"):
fp = open("config.json", "r", encoding="utf-8")
config = json.load(fp)
mattermost_bot = Bot(
server_url=config.get("server_url"),
access_token=config.get("access_token"),
login_id=config.get("login_id"),
password=config.get("password"),
username=config.get("username"),
openai_api_key=config.get("openai_api_key"),
openai_api_endpoint=config.get("openai_api_endpoint"),
bing_api_endpoint=config.get("bing_api_endpoint"),
bard_token=config.get("bard_token"),
bing_auth_cookie=config.get("bing_auth_cookie"),
pandora_api_endpoint=config.get("pandora_api_endpoint"),
pandora_api_model=config.get("pandora_api_model"),
port=config.get("port"),
timeout=config.get("timeout"),
)
else:
mattermost_bot = Bot(
server_url=os.environ.get("SERVER_URL"),
access_token=os.environ.get("ACCESS_TOKEN"),
login_id=os.environ.get("LOGIN_ID"),
password=os.environ.get("PASSWORD"),
username=os.environ.get("USERNAME"),
openai_api_key=os.environ.get("OPENAI_API_KEY"),
openai_api_endpoint=os.environ.get("OPENAI_API_ENDPOINT"),
bing_api_endpoint=os.environ.get("BING_API_ENDPOINT"),
bard_token=os.environ.get("BARD_TOKEN"),
bing_auth_cookie=os.environ.get("BING_AUTH_COOKIE"),
pandora_api_endpoint=os.environ.get("PANDORA_API_ENDPOINT"),
pandora_api_model=os.environ.get("PANDORA_API_MODEL"),
port=os.environ.get("PORT"),
timeout=os.environ.get("TIMEOUT"),
)
mattermost_bot.login()
await mattermost_bot.run()
if __name__ == "__main__":
asyncio.run(main())

101
pandora.py Normal file
View file

@ -0,0 +1,101 @@
# https://github.com/pengzhile/pandora/blob/master/doc/HTTP-API.md
import uuid
import aiohttp
import asyncio
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())

View file

@ -1,6 +1,27 @@
httpx aiohttp==3.8.4
Pillow aiosignal==1.3.1
tiktoken anyio==3.6.2
tenacity async-timeout==4.0.2
aiofiles attrs==23.1.0
mattermostdriver @ git+https://github.com/hibobmaster/python-mattermost-driver certifi==2022.12.7
charset-normalizer==3.1.0
click==8.1.3
colorama==0.4.6
frozenlist==1.3.3
h11==0.14.0
httpcore==0.17.0
httpx==0.24.0
idna==3.4
mattermostdriver @ git+https://github.com/hibobmaster/python-mattermost-driver
multidict==6.0.4
mypy-extensions==1.0.0
packaging==23.1
pathspec==0.11.1
platformdirs==3.2.0
regex==2023.3.23
requests==2.28.2
sniffio==1.3.0
tiktoken==0.3.3
urllib3==1.26.15
websockets==11.0.1
yarl==1.8.2

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@ -1,380 +0,0 @@
import sys
import aiofiles.os
from mattermostdriver import AsyncDriver
from typing import Optional
import json
import asyncio
import re
import os
from pathlib import Path
from gptbot import Chatbot
from log import getlogger
import httpx
import imagegen
logger = getlogger()
class Bot:
def __init__(
self,
server_url: str,
username: str,
email: str,
password: str,
port: Optional[int] = 443,
scheme: Optional[str] = "https",
openai_api_key: Optional[str] = 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: Optional[float] = None,
image_generation_endpoint: Optional[str] = None,
image_generation_backend: Optional[str] = None,
image_generation_size: Optional[str] = None,
sdwui_steps: Optional[int] = None,
sdwui_sampler_name: Optional[str] = None,
sdwui_cfg_scale: Optional[float] = None,
image_format: Optional[str] = None,
timeout: Optional[float] = 120.0,
) -> None:
if server_url is None:
raise ValueError("server url must be provided")
if port is None:
self.port = 443
else:
port = int(port)
if port <= 0 or port > 65535:
raise ValueError("port must be between 0 and 65535")
self.port = port
if scheme is None:
self.scheme = "https"
else:
if scheme.strip().lower() not in ["http", "https"]:
raise ValueError("scheme must be either http or https")
self.scheme = scheme
if image_generation_endpoint and image_generation_backend not in [
"openai",
"sdwui",
"localai",
None,
]:
logger.error("image_generation_backend must be openai or sdwui or localai")
sys.exit(1)
if image_format not in ["jpeg", "png", None]:
logger.error("image_format should be jpeg or png, leave blank for jpeg")
sys.exit(1)
# @chatgpt
if username is None:
raise ValueError("username must be provided")
else:
self.username = username
self.openai_api_key: str = openai_api_key
self.gpt_api_endpoint = (
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"
)
self.image_generation_endpoint: str = image_generation_endpoint
self.image_generation_backend: str = image_generation_backend
if image_format:
self.image_format: str = image_format
else:
self.image_format = "jpeg"
if image_generation_size is None:
self.image_generation_size = "512x512"
self.image_generation_width = 512
self.image_generation_height = 512
else:
self.image_generation_size = image_generation_size
self.image_generation_width = self.image_generation_size.split("x")[0]
self.image_generation_height = self.image_generation_size.split("x")[1]
self.sdwui_steps = sdwui_steps
self.sdwui_sampler_name = sdwui_sampler_name
self.sdwui_cfg_scale = sdwui_cfg_scale
self.timeout = timeout or 120.0
self.bot_id = None
self.base_path = Path(os.path.dirname(__file__)).parent
if not os.path.exists(self.base_path / "images"):
os.mkdir(self.base_path / "images")
# httpx session
self.httpx_client = httpx.AsyncClient()
# 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,
)
# login relative info
if email is None and password is None:
raise ValueError("user email and password must be provided")
self.driver = AsyncDriver(
{
"login_id": email,
"password": password,
"url": server_url,
"port": self.port,
"request_timeout": self.timeout,
"scheme": self.scheme,
}
)
# regular expression to match keyword
self.gpt_prog = re.compile(r"^\s*!gpt\s*(.+)$")
self.chat_prog = re.compile(r"^\s*!chat\s*(.+)$")
self.pic_prog = re.compile(r"^\s*!pic\s*(.+)$")
self.help_prog = re.compile(r"^\s*!help\s*.*$")
self.new_prog = re.compile(r"^\s*!new\s*.*$")
# close session
async def close(self, task: asyncio.Task) -> None:
await self.httpx_client.aclose()
self.driver.disconnect()
task.cancel()
async def login(self) -> None:
await self.driver.login()
# get user id
resp = await self.driver.users.get_user(user_id="me")
self.bot_id = resp["id"]
async def run(self) -> None:
await self.driver.init_websocket(self.websocket_handler)
# websocket handler
async def websocket_handler(self, message) -> None:
logger.info(message)
response = json.loads(message)
if "event" in response:
event_type = response["event"]
if event_type == "posted":
raw_data = response["data"]["post"]
raw_data_dict = json.loads(raw_data)
user_id = raw_data_dict["user_id"]
root_id = (
raw_data_dict["root_id"]
if raw_data_dict["root_id"]
else raw_data_dict["id"]
)
channel_id = raw_data_dict["channel_id"]
sender_name = response["data"]["sender_name"]
raw_message = raw_data_dict["message"]
try:
asyncio.create_task(
self.message_callback(
raw_message, channel_id, user_id, sender_name, root_id
)
)
except Exception as e:
await self.send_message(channel_id, f"{e}", root_id)
# message callback
async def message_callback(
self,
raw_message: str,
channel_id: str,
user_id: str,
sender_name: str,
root_id: str,
) -> None:
# prevent command trigger loop
if sender_name != self.username:
message = raw_message
if (
self.openai_api_key is not None
or self.gpt_api_endpoint != "https://api.openai.com/v1/chat/completions"
):
# !gpt command trigger handler
if self.gpt_prog.match(message):
prompt = self.gpt_prog.match(message).group(1)
try:
# sending typing state
await self.driver.users.publish_user_typing(
self.bot_id,
options={
"channel_id": channel_id,
},
)
response = await self.chatbot.oneTimeAsk(prompt)
await self.send_message(channel_id, f"{response}", root_id)
except Exception as e:
logger.error(e, exc_info=True)
raise Exception(e)
# !chat command trigger handler
elif self.chat_prog.match(message):
prompt = self.chat_prog.match(message).group(1)
try:
# sending typing state
await self.driver.users.publish_user_typing(
self.bot_id,
options={
"channel_id": channel_id,
},
)
response = await self.chatbot.ask_async_v2(
prompt=prompt, convo_id=user_id
)
await self.send_message(channel_id, f"{response}", root_id)
except Exception as e:
logger.error(e, exc_info=True)
raise Exception(e)
# !new command trigger handler
if self.new_prog.match(message):
self.chatbot.reset(convo_id=user_id)
try:
await self.send_message(
channel_id,
"New conversation created, "
+ "please use !chat to start chatting!",
root_id,
)
except Exception as e:
logger.error(e, exc_info=True)
raise Exception(e)
# !pic command trigger handler
if self.image_generation_endpoint and self.image_generation_backend:
if self.pic_prog.match(message):
prompt = self.pic_prog.match(message).group(1)
# generate image
try:
# sending typing state
await self.driver.users.publish_user_typing(
self.bot_id,
options={
"channel_id": channel_id,
},
)
image_path_list = await imagegen.get_images(
self.httpx_client,
self.image_generation_endpoint,
prompt,
self.image_generation_backend,
timeount=self.timeout,
api_key=self.openai_api_key,
output_path=self.base_path / "images",
n=1,
size=self.image_generation_size,
width=self.image_generation_width,
height=self.image_generation_height,
steps=self.sdwui_steps,
sampler_name=self.sdwui_sampler_name,
cfg_scale=self.sdwui_cfg_scale,
image_format=self.image_format,
)
# send image
for image_path in image_path_list:
await self.send_file(
channel_id,
f"{prompt}",
image_path,
root_id,
)
await aiofiles.os.remove(image_path)
except Exception as e:
logger.error(e, exc_info=True)
raise Exception(e)
# !help command trigger handler
if self.help_prog.match(message):
try:
await self.send_message(channel_id, self.help(), root_id)
except Exception as e:
logger.error(e, exc_info=True)
# send message to room
async def send_message(self, channel_id: str, message: str, root_id: str) -> None:
await self.driver.posts.create_post(
options={
"channel_id": channel_id,
"message": message,
"root_id": root_id,
}
)
# send file to room
async def send_file(
self, channel_id: str, message: str, filepath: str, root_id: str
) -> None:
filename = os.path.split(filepath)[-1]
try:
file_id = await self.driver.files.upload_file(
channel_id=channel_id,
files={
"files": (filename, open(filepath, "rb")),
},
)
file_id = file_id["file_infos"][0]["id"]
except Exception as e:
logger.error(e, exc_info=True)
raise Exception(e)
try:
await self.driver.posts.create_post(
options={
"channel_id": channel_id,
"message": message,
"file_ids": [file_id],
"root_id": root_id,
}
)
except Exception as e:
logger.error(e, exc_info=True)
raise Exception(e)
# !help command function
def help(self) -> str:
help_info = (
"!gpt [content], generate response without context conversation\n"
+ "!chat [content], chat with context conversation\n"
+ "!pic [prompt], Image generation with DALL·E or LocalAI or stable-diffusion-webui\n" # noqa: E501
+ "!new, start a new conversation\n"
+ "!help, help message"
)
return help_info

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@ -1,106 +0,0 @@
import httpx
from pathlib import Path
import uuid
import base64
import io
from PIL import Image
async def get_images(
aclient: httpx.AsyncClient,
url: str,
prompt: str,
backend_type: str,
output_path: str,
**kwargs,
) -> list[str]:
timeout = kwargs.get("timeout", 180.0)
if backend_type == "openai":
resp = await aclient.post(
url,
headers={
"Content-Type": "application/json",
"Authorization": f"Bearer {kwargs.get('api_key')}",
},
json={
"prompt": prompt,
"n": kwargs.get("n", 1),
"size": kwargs.get("size", "512x512"),
"response_format": "b64_json",
},
timeout=timeout,
)
if resp.status_code == 200:
b64_datas = []
for data in resp.json()["data"]:
b64_datas.append(data["b64_json"])
return save_images_b64(b64_datas, output_path, **kwargs)
else:
raise Exception(
f"{resp.status_code} {resp.reason_phrase} {resp.text}",
)
elif backend_type == "sdwui":
resp = await aclient.post(
url,
headers={
"Content-Type": "application/json",
},
json={
"prompt": prompt,
"sampler_name": kwargs.get("sampler_name", "Euler a"),
"cfg_scale": kwargs.get("cfg_scale", 7),
"batch_size": kwargs.get("n", 1),
"steps": kwargs.get("steps", 20),
"width": kwargs.get("width", 512),
"height": kwargs.get("height", 512),
},
timeout=timeout,
)
if resp.status_code == 200:
b64_datas = resp.json()["images"]
return save_images_b64(b64_datas, output_path, **kwargs)
else:
raise Exception(
f"{resp.status_code} {resp.reason_phrase} {resp.text}",
)
elif backend_type == "localai":
resp = await aclient.post(
url,
headers={
"Content-Type": "application/json",
"Authorization": f"Bearer {kwargs.get('api_key')}",
},
json={
"prompt": prompt,
"size": kwargs.get("size", "512x512"),
},
timeout=timeout,
)
if resp.status_code == 200:
image_url = resp.json()["data"][0]["url"]
return await save_image_url(image_url, aclient, output_path, **kwargs)
def save_images_b64(b64_datas: list[str], path: Path, **kwargs) -> list[str]:
images_path_list = []
for b64_data in b64_datas:
image_path = path / (
str(uuid.uuid4()) + "." + kwargs.get("image_format", "jpeg")
)
img = Image.open(io.BytesIO(base64.decodebytes(bytes(b64_data, "utf-8"))))
img.save(image_path)
images_path_list.append(image_path)
return images_path_list
async def save_image_url(
url: str, aclient: httpx.AsyncClient, path: Path, **kwargs
) -> list[str]:
images_path_list = []
r = await aclient.get(url)
image_path = path / (str(uuid.uuid4()) + "." + kwargs.get("image_format", "jpeg"))
if r.status_code == 200:
img = Image.open(io.BytesIO(r.content))
img.save(image_path)
images_path_list.append(image_path)
return images_path_list

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@ -1,97 +0,0 @@
import signal
from bot import Bot
import json
import os
import sys
import asyncio
from pathlib import Path
from log import getlogger
logger = getlogger()
async def main():
config_path = Path(os.path.dirname(__file__)).parent / "config.json"
if os.path.isfile(config_path):
fp = open("config.json", "r", encoding="utf-8")
try:
config = json.load(fp)
except Exception as e:
logger.error(e, exc_info=True)
sys.exit(1)
mattermost_bot = Bot(
server_url=config.get("server_url"),
email=config.get("email"),
password=config.get("password"),
username=config.get("username"),
port=config.get("port"),
scheme=config.get("scheme"),
openai_api_key=config.get("openai_api_key"),
gpt_api_endpoint=config.get("gpt_api_endpoint"),
gpt_model=config.get("gpt_model"),
max_tokens=config.get("max_tokens"),
top_p=config.get("top_p"),
presence_penalty=config.get("presence_penalty"),
frequency_penalty=config.get("frequency_penalty"),
reply_count=config.get("reply_count"),
system_prompt=config.get("system_prompt"),
temperature=config.get("temperature"),
image_generation_endpoint=config.get("image_generation_endpoint"),
image_generation_backend=config.get("image_generation_backend"),
image_generation_size=config.get("image_generation_size"),
sdwui_steps=config.get("sdwui_steps"),
sdwui_sampler_name=config.get("sdwui_sampler_name"),
sdwui_cfg_scale=config.get("sdwui_cfg_scale"),
image_format=config.get("image_format"),
timeout=config.get("timeout"),
)
else:
mattermost_bot = Bot(
server_url=os.environ.get("SERVER_URL"),
email=os.environ.get("EMAIL"),
password=os.environ.get("PASSWORD"),
username=os.environ.get("USERNAME"),
port=int(os.environ.get("PORT", 443)),
scheme=os.environ.get("SCHEME"),
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", 4000)),
top_p=float(os.environ.get("TOP_P", 1.0)),
presence_penalty=float(os.environ.get("PRESENCE_PENALTY", 0.0)),
frequency_penalty=float(os.environ.get("FREQUENCY_PENALTY", 0.0)),
reply_count=int(os.environ.get("REPLY_COUNT", 1)),
system_prompt=os.environ.get("SYSTEM_PROMPT"),
temperature=float(os.environ.get("TEMPERATURE", 0.8)),
image_generation_endpoint=os.environ.get("IMAGE_GENERATION_ENDPOINT"),
image_generation_backend=os.environ.get("IMAGE_GENERATION_BACKEND"),
image_generation_size=os.environ.get("IMAGE_GENERATION_SIZE"),
sdwui_steps=int(os.environ.get("SDWUI_STEPS", 20)),
sdwui_sampler_name=os.environ.get("SDWUI_SAMPLER_NAME"),
sdwui_cfg_scale=float(os.environ.get("SDWUI_CFG_SCALE", 7)),
image_format=os.environ.get("IMAGE_FORMAT"),
timeout=float(os.environ.get("TIMEOUT", 120.0)),
)
await mattermost_bot.login()
task = asyncio.create_task(mattermost_bot.run())
# handle signal interrupt
loop = asyncio.get_running_loop()
for signame in ("SIGINT", "SIGTERM"):
loop.add_signal_handler(
getattr(signal, signame),
lambda: asyncio.create_task(mattermost_bot.close(task)),
)
try:
await task
except asyncio.CancelledError:
logger.info("Bot stopped")
if __name__ == "__main__":
asyncio.run(main())

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@ -1,344 +1,324 @@
""" """
Code derived from https://github.com/acheong08/ChatGPT/blob/main/src/revChatGPT/V3.py Code derived from: https://github.com/acheong08/ChatGPT/blob/main/src/revChatGPT/V3.py
A simple wrapper for the official ChatGPT API """
"""
import json import json
from typing import AsyncGenerator import os
from tenacity import retry, wait_random_exponential, stop_after_attempt from typing import AsyncGenerator
import httpx import httpx
import tiktoken import requests
import tiktoken
ENGINES = [
"gpt-3.5-turbo", class Chatbot:
"gpt-3.5-turbo-16k", """
"gpt-3.5-turbo-0613", Official ChatGPT API
"gpt-3.5-turbo-16k-0613", """
"gpt-4",
"gpt-4-32k", def __init__(
"gpt-4-0613", self,
"gpt-4-32k-0613", api_key: str,
] engine: str = os.environ.get("GPT_ENGINE") or "gpt-3.5-turbo",
proxy: str = None,
timeout: float = None,
class Chatbot: max_tokens: int = None,
""" temperature: float = 0.5,
Official ChatGPT API top_p: float = 1.0,
""" presence_penalty: float = 0.0,
frequency_penalty: float = 0.0,
def __init__( reply_count: int = 1,
self, system_prompt: str = "You are ChatGPT, a large language model trained by OpenAI. Respond conversationally",
aclient: httpx.AsyncClient, ) -> None:
api_key: str, """
api_url: str = None, Initialize Chatbot with API key (from https://platform.openai.com/account/api-keys)
engine: str = None, """
timeout: float = None, self.engine: str = engine
max_tokens: int = None, self.api_key: str = api_key
temperature: float = 0.8, self.system_prompt: str = system_prompt
top_p: float = 1.0, self.max_tokens: int = max_tokens or (
presence_penalty: float = 0.0, 31000 if engine == "gpt-4-32k" else 7000 if engine == "gpt-4" else 4000
frequency_penalty: float = 0.0, )
reply_count: int = 1, self.truncate_limit: int = (
truncate_limit: int = None, 30500 if engine == "gpt-4-32k" else 6500 if engine == "gpt-4" else 3500
system_prompt: str = None, )
) -> None: self.temperature: float = temperature
""" self.top_p: float = top_p
Initialize Chatbot with API key (from https://platform.openai.com/account/api-keys) self.presence_penalty: float = presence_penalty
""" self.frequency_penalty: float = frequency_penalty
self.engine: str = engine or "gpt-3.5-turbo" self.reply_count: int = reply_count
self.api_key: str = api_key self.timeout: float = timeout
self.api_url: str = api_url or "https://api.openai.com/v1/chat/completions" self.proxy = proxy
self.system_prompt: str = ( self.session = requests.Session()
system_prompt self.session.proxies.update(
or "You are ChatGPT, \ {
a large language model trained by OpenAI. Respond conversationally" "http": proxy,
) "https": proxy,
self.max_tokens: int = max_tokens or ( },
31000 )
if "gpt-4-32k" in engine proxy = (
else 7000 proxy or os.environ.get("all_proxy") or os.environ.get("ALL_PROXY") or None
if "gpt-4" in engine )
else 15000
if "gpt-3.5-turbo-16k" in engine if proxy:
else 4000 if "socks5h" not in proxy:
) self.aclient = httpx.AsyncClient(
self.truncate_limit: int = truncate_limit or ( follow_redirects=True,
30500 proxies=proxy,
if "gpt-4-32k" in engine timeout=timeout,
else 6500 )
if "gpt-4" in engine else:
else 14500 self.aclient = httpx.AsyncClient(
if "gpt-3.5-turbo-16k" in engine follow_redirects=True,
else 3500 proxies=proxy,
) timeout=timeout,
self.temperature: float = temperature )
self.top_p: float = top_p
self.presence_penalty: float = presence_penalty self.conversation: dict[str, list[dict]] = {
self.frequency_penalty: float = frequency_penalty "default": [
self.reply_count: int = reply_count {
self.timeout: float = timeout "role": "system",
"content": system_prompt,
self.aclient = aclient },
],
self.conversation: dict[str, list[dict]] = { }
"default": [
{ def add_to_conversation(
"role": "system", self,
"content": system_prompt, message: str,
}, role: str,
], convo_id: str = "default",
} ) -> None:
"""
if self.get_token_count("default") > self.max_tokens: Add a message to the conversation
raise Exception("System prompt is too long") """
self.conversation[convo_id].append({"role": role, "content": message})
def add_to_conversation(
self, def __truncate_conversation(self, convo_id: str = "default") -> None:
message: str, """
role: str, Truncate the conversation
convo_id: str = "default", """
) -> None: while True:
""" if (
Add a message to the conversation self.get_token_count(convo_id) > self.truncate_limit
""" and len(self.conversation[convo_id]) > 1
self.conversation[convo_id].append({"role": role, "content": message}) ):
# Don't remove the first message
def __truncate_conversation(self, convo_id: str = "default") -> None: self.conversation[convo_id].pop(1)
""" else:
Truncate the conversation break
"""
while True: def get_token_count(self, convo_id: str = "default") -> int:
if ( """
self.get_token_count(convo_id) > self.truncate_limit Get token count
and len(self.conversation[convo_id]) > 1 """
): if self.engine not in [
# Don't remove the first message "gpt-3.5-turbo",
self.conversation[convo_id].pop(1) "gpt-3.5-turbo-0301",
else: "gpt-4",
break "gpt-4-0314",
"gpt-4-32k",
# https://github.com/openai/openai-cookbook/blob/main/examples/How_to_count_tokens_with_tiktoken.ipynb "gpt-4-32k-0314",
def get_token_count(self, convo_id: str = "default") -> int: ]:
""" raise NotImplementedError("Unsupported engine {self.engine}")
Get token count
""" tiktoken.model.MODEL_TO_ENCODING["gpt-4"] = "cl100k_base"
_engine = self.engine
if self.engine not in ENGINES: encoding = tiktoken.encoding_for_model(self.engine)
# use gpt-3.5-turbo to caculate token
_engine = "gpt-3.5-turbo" num_tokens = 0
tiktoken.model.MODEL_TO_ENCODING["gpt-4"] = "cl100k_base" for message in self.conversation[convo_id]:
# every message follows <im_start>{role/name}\n{content}<im_end>\n
encoding = tiktoken.encoding_for_model(_engine) num_tokens += 5
for key, value in message.items():
num_tokens = 0 num_tokens += len(encoding.encode(value))
for message in self.conversation[convo_id]: if key == "name": # if there's a name, the role is omitted
# every message follows <im_start>{role/name}\n{content}<im_end>\n num_tokens += 5 # role is always required and always 1 token
num_tokens += 5 num_tokens += 5 # every reply is primed with <im_start>assistant
for key, value in message.items(): return num_tokens
if value:
num_tokens += len(encoding.encode(value)) def get_max_tokens(self, convo_id: str) -> int:
if key == "name": # if there's a name, the role is omitted """
num_tokens += 5 # role is always required and always 1 token Get max tokens
num_tokens += 5 # every reply is primed with <im_start>assistant """
return num_tokens return self.max_tokens - self.get_token_count(convo_id)
def get_max_tokens(self, convo_id: str) -> int: def ask_stream(
""" self,
Get max tokens prompt: str,
""" role: str = "user",
return self.max_tokens - self.get_token_count(convo_id) convo_id: str = "default",
**kwargs,
async def ask_stream_async( ):
self, """
prompt: str, Ask a question
role: str = "user", """
convo_id: str = "default", # Make conversation if it doesn't exist
model: str = None, if convo_id not in self.conversation:
pass_history: bool = True, self.reset(convo_id=convo_id, system_prompt=self.system_prompt)
**kwargs, self.add_to_conversation(prompt, "user", convo_id=convo_id)
) -> AsyncGenerator[str, None]: self.__truncate_conversation(convo_id=convo_id)
""" # Get response
Ask a question response = self.session.post(
""" os.environ.get("API_URL") or "https://api.openai.com/v1/chat/completions",
# Make conversation if it doesn't exist headers={"Authorization": f"Bearer {kwargs.get('api_key', self.api_key)}"},
if convo_id not in self.conversation: json={
self.reset(convo_id=convo_id, system_prompt=self.system_prompt) "model": self.engine,
self.add_to_conversation(prompt, "user", convo_id=convo_id) "messages": self.conversation[convo_id],
self.__truncate_conversation(convo_id=convo_id) "stream": True,
# Get response # kwargs
async with self.aclient.stream( "temperature": kwargs.get("temperature", self.temperature),
"post", "top_p": kwargs.get("top_p", self.top_p),
self.api_url, "presence_penalty": kwargs.get(
headers={"Authorization": f"Bearer {kwargs.get('api_key', self.api_key)}"}, "presence_penalty",
json={ self.presence_penalty,
"model": model or self.engine, ),
"messages": self.conversation[convo_id] if pass_history else [prompt], "frequency_penalty": kwargs.get(
"stream": True, "frequency_penalty",
# kwargs self.frequency_penalty,
"temperature": kwargs.get("temperature", self.temperature), ),
"top_p": kwargs.get("top_p", self.top_p), "n": kwargs.get("n", self.reply_count),
"presence_penalty": kwargs.get( "user": role,
"presence_penalty", "max_tokens": self.get_max_tokens(convo_id=convo_id),
self.presence_penalty, },
), timeout=kwargs.get("timeout", self.timeout),
"frequency_penalty": kwargs.get( stream=True,
"frequency_penalty", )
self.frequency_penalty,
), response_role: str = None
"n": kwargs.get("n", self.reply_count), full_response: str = ""
"user": role, for line in response.iter_lines():
"max_tokens": min( if not line:
self.get_max_tokens(convo_id=convo_id), continue
kwargs.get("max_tokens", self.max_tokens), # Remove "data: "
), line = line.decode("utf-8")[6:]
}, if line == "[DONE]":
timeout=kwargs.get("timeout", self.timeout), break
) as response: resp: dict = json.loads(line)
if response.status_code != 200: choices = resp.get("choices")
await response.aread() if not choices:
raise Exception( continue
f"{response.status_code} {response.reason_phrase} {response.text}", delta = choices[0].get("delta")
) if not delta:
continue
response_role: str = "" if "role" in delta:
full_response: str = "" response_role = delta["role"]
async for line in response.aiter_lines(): if "content" in delta:
line = line.strip() content = delta["content"]
if not line: full_response += content
continue yield content
# Remove "data: " self.add_to_conversation(full_response, response_role, convo_id=convo_id)
line = line[6:]
if line == "[DONE]": async def ask_stream_async(
break self,
resp: dict = json.loads(line) prompt: str,
if "error" in resp: role: str = "user",
raise Exception(f"{resp['error']}") convo_id: str = "default",
choices = resp.get("choices") **kwargs,
if not choices: ) -> AsyncGenerator[str, None]:
continue """
delta: dict[str, str] = choices[0].get("delta") Ask a question
if not delta: """
continue # Make conversation if it doesn't exist
if "role" in delta: if convo_id not in self.conversation:
response_role = delta["role"] self.reset(convo_id=convo_id, system_prompt=self.system_prompt)
if "content" in delta: self.add_to_conversation(prompt, "user", convo_id=convo_id)
content: str = delta["content"] self.__truncate_conversation(convo_id=convo_id)
full_response += content # Get response
yield content async with self.aclient.stream(
self.add_to_conversation(full_response, response_role, convo_id=convo_id) "post",
os.environ.get("API_URL") or "https://api.openai.com/v1/chat/completions",
async def ask_async( headers={"Authorization": f"Bearer {kwargs.get('api_key', self.api_key)}"},
self, json={
prompt: str, "model": self.engine,
role: str = "user", "messages": self.conversation[convo_id],
convo_id: str = "default", "stream": True,
model: str = None, # kwargs
pass_history: bool = True, "temperature": kwargs.get("temperature", self.temperature),
**kwargs, "top_p": kwargs.get("top_p", self.top_p),
) -> str: "presence_penalty": kwargs.get(
""" "presence_penalty",
Non-streaming ask self.presence_penalty,
""" ),
response = self.ask_stream_async( "frequency_penalty": kwargs.get(
prompt=prompt, "frequency_penalty",
role=role, self.frequency_penalty,
convo_id=convo_id, ),
model=model, "n": kwargs.get("n", self.reply_count),
pass_history=pass_history, "user": role,
**kwargs, "max_tokens": self.get_max_tokens(convo_id=convo_id),
) },
full_response: str = "".join([r async for r in response]) timeout=kwargs.get("timeout", self.timeout),
return full_response ) as response:
if response.status_code != 200:
async def ask_async_v2( await response.aread()
self,
prompt: str, response_role: str = ""
role: str = "user", full_response: str = ""
convo_id: str = "default", async for line in response.aiter_lines():
model: str = None, line = line.strip()
pass_history: bool = True, if not line:
**kwargs, continue
) -> str: # Remove "data: "
# Make conversation if it doesn't exist line = line[6:]
if convo_id not in self.conversation: if line == "[DONE]":
self.reset(convo_id=convo_id, system_prompt=self.system_prompt) break
self.add_to_conversation(prompt, "user", convo_id=convo_id) resp: dict = json.loads(line)
self.__truncate_conversation(convo_id=convo_id) choices = resp.get("choices")
# Get response if not choices:
response = await self.aclient.post( continue
url=self.api_url, delta: dict[str, str] = choices[0].get("delta")
headers={"Authorization": f"Bearer {kwargs.get('api_key', self.api_key)}"}, if not delta:
json={ continue
"model": model or self.engine, if "role" in delta:
"messages": self.conversation[convo_id] if pass_history else [prompt], response_role = delta["role"]
# kwargs if "content" in delta:
"temperature": kwargs.get("temperature", self.temperature), content: str = delta["content"]
"top_p": kwargs.get("top_p", self.top_p), full_response += content
"presence_penalty": kwargs.get( yield content
"presence_penalty", self.add_to_conversation(full_response, response_role, convo_id=convo_id)
self.presence_penalty,
), async def ask_async(
"frequency_penalty": kwargs.get( self,
"frequency_penalty", prompt: str,
self.frequency_penalty, role: str = "user",
), convo_id: str = "default",
"n": kwargs.get("n", self.reply_count), **kwargs,
"user": role, ) -> str:
"max_tokens": min( """
self.get_max_tokens(convo_id=convo_id), Non-streaming ask
kwargs.get("max_tokens", self.max_tokens), """
), response = self.ask_stream_async(
}, prompt=prompt,
timeout=kwargs.get("timeout", self.timeout), role=role,
) convo_id=convo_id,
resp = response.json() **kwargs,
full_response = resp["choices"][0]["message"]["content"] )
self.add_to_conversation( full_response: str = "".join([r async for r in response])
full_response, resp["choices"][0]["message"]["role"], convo_id=convo_id return full_response
)
return full_response def ask(
self,
def reset(self, convo_id: str = "default", system_prompt: str = None) -> None: prompt: str,
""" role: str = "user",
Reset the conversation convo_id: str = "default",
""" **kwargs,
self.conversation[convo_id] = [ ) -> str:
{"role": "system", "content": system_prompt or self.system_prompt}, """
] Non-streaming ask
"""
@retry(wait=wait_random_exponential(min=2, max=5), stop=stop_after_attempt(3)) response = self.ask_stream(
async def oneTimeAsk( prompt=prompt,
self, role=role,
prompt: str, convo_id=convo_id,
role: str = "user", **kwargs,
model: str = None, )
**kwargs, full_response: str = "".join(response)
) -> str: return full_response
response = await self.aclient.post(
url=self.api_url, def reset(self, convo_id: str = "default", system_prompt: str = None) -> None:
json={ """
"model": model or self.engine, Reset the conversation
"messages": [ """
{ self.conversation[convo_id] = [
"role": role, {"role": "system", "content": system_prompt or self.system_prompt},
"content": 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),
)
resp = response.json()
return resp["choices"][0]["message"]["content"]