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06ccd8c61c | |||
d017323c25 | |||
a2027590c8 | |||
7142045292 | |||
25fbd43a57 | |||
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d0b93b454d | |||
a5d88a104c |
28 changed files with 1313 additions and 1640 deletions
|
@ -1,21 +1,29 @@
|
|||
.gitignore
|
||||
images
|
||||
*.md
|
||||
Dockerfile
|
||||
Dockerfile-dev
|
||||
.dockerignore
|
||||
config.json
|
||||
config.json.sample
|
||||
.vscode
|
||||
bot.log
|
||||
venv
|
||||
.venv
|
||||
*.yaml
|
||||
*.yml
|
||||
.git
|
||||
.idea
|
||||
__pycache__
|
||||
.env
|
||||
.env.example
|
||||
.github
|
||||
settings.js
|
||||
.gitignore
|
||||
images
|
||||
*.md
|
||||
Dockerfile
|
||||
Dockerfile-dev
|
||||
compose.yaml
|
||||
compose-dev.yaml
|
||||
.dockerignore
|
||||
config.json
|
||||
config.json.sample
|
||||
.vscode
|
||||
bot.log
|
||||
venv
|
||||
.venv
|
||||
*.yaml
|
||||
*.yml
|
||||
.git
|
||||
.idea
|
||||
__pycache__
|
||||
src/__pycache__
|
||||
.env
|
||||
.env.example
|
||||
.github
|
||||
settings.js
|
||||
mattermost-server
|
||||
tests
|
||||
full-config.json.example
|
||||
config.json.example
|
||||
.full-env.example
|
||||
|
|
11
.env.example
11
.env.example
|
@ -1,9 +1,6 @@
|
|||
SERVER_URL="xxxxx.xxxxxx.xxxxxxxxx"
|
||||
ACCESS_TOKEN="xxxxxxxxxxxxxxxxx"
|
||||
USERNAME="@chatgpt"
|
||||
OPENAI_API_KEY="sk-xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx"
|
||||
BING_API_ENDPOINT="http://api:3000/conversation"
|
||||
BARD_TOKEN="xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx."
|
||||
BING_AUTH_COOKIE="xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx"
|
||||
PANDORA_API_ENDPOINT="http://pandora:8008"
|
||||
PANDORA_API_MODEL="text-davinci-002-render-sha-mobile"
|
||||
EMAIL="xxxxxx"
|
||||
PASSWORD="xxxxxxxxxxxxxx"
|
||||
OPENAI_API_KEY="xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx"
|
||||
GPT_MODEL="gpt-3.5-turbo"
|
||||
|
|
24
.full-env.example
Normal file
24
.full-env.example
Normal file
|
@ -0,0 +1,24 @@
|
|||
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
|
2
.github/workflows/docker-release.yml
vendored
2
.github/workflows/docker-release.yml
vendored
|
@ -70,4 +70,4 @@ jobs:
|
|||
tags: ${{ steps.meta2.outputs.tags }}
|
||||
labels: ${{ steps.meta2.outputs.labels }}
|
||||
cache-from: type=gha
|
||||
cache-to: type=gha,mode=max
|
||||
cache-to: type=gha,mode=max
|
||||
|
|
25
.github/workflows/pylint.yml
vendored
25
.github/workflows/pylint.yml
vendored
|
@ -1,25 +0,0 @@
|
|||
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 $(git ls-files '*.py') --errors-only
|
279
.gitignore
vendored
279
.gitignore
vendored
|
@ -1,139 +1,140 @@
|
|||
# Byte-compiled / optimized / DLL files
|
||||
__pycache__/
|
||||
*.py[cod]
|
||||
*$py.class
|
||||
|
||||
# C extensions
|
||||
*.so
|
||||
|
||||
# Distribution / packaging
|
||||
.Python
|
||||
build/
|
||||
develop-eggs/
|
||||
dist/
|
||||
downloads/
|
||||
eggs/
|
||||
.eggs/
|
||||
lib/
|
||||
lib64/
|
||||
parts/
|
||||
sdist/
|
||||
var/
|
||||
wheels/
|
||||
pip-wheel-metadata/
|
||||
share/python-wheels/
|
||||
*.egg-info/
|
||||
.installed.cfg
|
||||
*.egg
|
||||
MANIFEST
|
||||
|
||||
# PyInstaller
|
||||
# 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.
|
||||
*.manifest
|
||||
*.spec
|
||||
|
||||
# Installer logs
|
||||
pip-log.txt
|
||||
pip-delete-this-directory.txt
|
||||
|
||||
# Unit test / coverage reports
|
||||
htmlcov/
|
||||
.tox/
|
||||
.nox/
|
||||
.coverage
|
||||
.coverage.*
|
||||
.cache
|
||||
nosetests.xml
|
||||
coverage.xml
|
||||
*.cover
|
||||
*.py,cover
|
||||
.hypothesis/
|
||||
.pytest_cache/
|
||||
|
||||
# Translations
|
||||
*.mo
|
||||
*.pot
|
||||
|
||||
# Django stuff:
|
||||
*.log
|
||||
local_settings.py
|
||||
db.sqlite3
|
||||
db.sqlite3-journal
|
||||
|
||||
# Flask stuff:
|
||||
instance/
|
||||
.webassets-cache
|
||||
|
||||
# Scrapy stuff:
|
||||
.scrapy
|
||||
|
||||
# Sphinx documentation
|
||||
docs/_build/
|
||||
|
||||
# PyBuilder
|
||||
target/
|
||||
|
||||
# Jupyter Notebook
|
||||
.ipynb_checkpoints
|
||||
|
||||
# IPython
|
||||
profile_default/
|
||||
ipython_config.py
|
||||
|
||||
# pyenv
|
||||
.python-version
|
||||
|
||||
# pipenv
|
||||
# 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
|
||||
# having no cross-platform support, pipenv may install dependencies that don't work, or not
|
||||
# install all needed dependencies.
|
||||
#Pipfile.lock
|
||||
|
||||
# PEP 582; used by e.g. github.com/David-OConnor/pyflow
|
||||
__pypackages__/
|
||||
|
||||
# Celery stuff
|
||||
celerybeat-schedule
|
||||
celerybeat.pid
|
||||
|
||||
# SageMath parsed files
|
||||
*.sage.py
|
||||
|
||||
# custom path
|
||||
images
|
||||
Dockerfile-dev
|
||||
compose-dev.yaml
|
||||
settings.js
|
||||
|
||||
# Environments
|
||||
.env
|
||||
.venv
|
||||
env/
|
||||
venv/
|
||||
ENV/
|
||||
env.bak/
|
||||
venv.bak/
|
||||
config.json
|
||||
|
||||
# Spyder project settings
|
||||
.spyderproject
|
||||
.spyproject
|
||||
|
||||
# Rope project settings
|
||||
.ropeproject
|
||||
|
||||
# mkdocs documentation
|
||||
/site
|
||||
|
||||
# mypy
|
||||
.mypy_cache/
|
||||
.dmypy.json
|
||||
dmypy.json
|
||||
|
||||
# Pyre type checker
|
||||
.pyre/
|
||||
|
||||
# custom
|
||||
compose-local-dev.yaml
|
||||
# Byte-compiled / optimized / DLL files
|
||||
__pycache__/
|
||||
*.py[cod]
|
||||
*$py.class
|
||||
|
||||
# C extensions
|
||||
*.so
|
||||
|
||||
# Distribution / packaging
|
||||
.Python
|
||||
build/
|
||||
develop-eggs/
|
||||
dist/
|
||||
downloads/
|
||||
eggs/
|
||||
.eggs/
|
||||
lib/
|
||||
lib64/
|
||||
parts/
|
||||
sdist/
|
||||
var/
|
||||
wheels/
|
||||
pip-wheel-metadata/
|
||||
share/python-wheels/
|
||||
*.egg-info/
|
||||
.installed.cfg
|
||||
*.egg
|
||||
MANIFEST
|
||||
|
||||
# PyInstaller
|
||||
# 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.
|
||||
*.manifest
|
||||
*.spec
|
||||
|
||||
# Installer logs
|
||||
pip-log.txt
|
||||
pip-delete-this-directory.txt
|
||||
|
||||
# Unit test / coverage reports
|
||||
htmlcov/
|
||||
.tox/
|
||||
.nox/
|
||||
.coverage
|
||||
.coverage.*
|
||||
.cache
|
||||
nosetests.xml
|
||||
coverage.xml
|
||||
*.cover
|
||||
*.py,cover
|
||||
.hypothesis/
|
||||
.pytest_cache/
|
||||
|
||||
# Translations
|
||||
*.mo
|
||||
*.pot
|
||||
|
||||
# Django stuff:
|
||||
*.log
|
||||
local_settings.py
|
||||
db.sqlite3
|
||||
db.sqlite3-journal
|
||||
|
||||
# Flask stuff:
|
||||
instance/
|
||||
.webassets-cache
|
||||
|
||||
# Scrapy stuff:
|
||||
.scrapy
|
||||
|
||||
# Sphinx documentation
|
||||
docs/_build/
|
||||
|
||||
# PyBuilder
|
||||
target/
|
||||
|
||||
# Jupyter Notebook
|
||||
.ipynb_checkpoints
|
||||
|
||||
# IPython
|
||||
profile_default/
|
||||
ipython_config.py
|
||||
|
||||
# pyenv
|
||||
.python-version
|
||||
|
||||
# pipenv
|
||||
# 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
|
||||
# having no cross-platform support, pipenv may install dependencies that don't work, or not
|
||||
# install all needed dependencies.
|
||||
#Pipfile.lock
|
||||
|
||||
# PEP 582; used by e.g. github.com/David-OConnor/pyflow
|
||||
__pypackages__/
|
||||
|
||||
# Celery stuff
|
||||
celerybeat-schedule
|
||||
celerybeat.pid
|
||||
|
||||
# SageMath parsed files
|
||||
*.sage.py
|
||||
|
||||
# custom path
|
||||
images
|
||||
Dockerfile-dev
|
||||
compose-dev.yaml
|
||||
settings.js
|
||||
|
||||
# Environments
|
||||
.env
|
||||
.venv
|
||||
env/
|
||||
venv/
|
||||
ENV/
|
||||
env.bak/
|
||||
venv.bak/
|
||||
config.json
|
||||
|
||||
# Spyder project settings
|
||||
.spyderproject
|
||||
.spyproject
|
||||
|
||||
# Rope project settings
|
||||
.ropeproject
|
||||
|
||||
# mkdocs documentation
|
||||
/site
|
||||
|
||||
# mypy
|
||||
.mypy_cache/
|
||||
.dmypy.json
|
||||
dmypy.json
|
||||
|
||||
# Pyre type checker
|
||||
.pyre/
|
||||
|
||||
# custom
|
||||
compose-dev.yaml
|
||||
mattermost-server
|
||||
|
|
16
.pre-commit-config.yaml
Normal file
16
.pre-commit-config.yaml
Normal file
|
@ -0,0 +1,16 @@
|
|||
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
3
.vscode/settings.json
vendored
|
@ -1,3 +0,0 @@
|
|||
{
|
||||
"python.formatting.provider": "black"
|
||||
}
|
165
BingImageGen.py
165
BingImageGen.py
|
@ -1,165 +0,0 @@
|
|||
"""
|
||||
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
|
26
CHANGELOG.md
Normal file
26
CHANGELOG.md
Normal file
|
@ -0,0 +1,26 @@
|
|||
# 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
|
32
Dockerfile
32
Dockerfile
|
@ -1,16 +1,16 @@
|
|||
FROM python:3.11-alpine as base
|
||||
|
||||
FROM base as builder
|
||||
# RUN sed -i 's|v3\.\d*|edge|' /etc/apk/repositories
|
||||
RUN apk update && apk add --no-cache gcc musl-dev libffi-dev git
|
||||
COPY requirements.txt .
|
||||
RUN pip install -U pip setuptools wheel && pip install --user -r ./requirements.txt && rm ./requirements.txt
|
||||
|
||||
FROM base as runner
|
||||
RUN apk update && apk add --no-cache libffi-dev
|
||||
COPY --from=builder /root/.local /usr/local
|
||||
COPY . /app
|
||||
|
||||
FROM runner
|
||||
WORKDIR /app
|
||||
CMD ["python", "main.py"]
|
||||
FROM python:3.11-alpine as base
|
||||
|
||||
FROM base as builder
|
||||
# RUN sed -i 's|v3\.\d*|edge|' /etc/apk/repositories
|
||||
RUN apk update && apk add --no-cache gcc musl-dev libffi-dev git
|
||||
COPY requirements.txt .
|
||||
RUN pip install -U pip setuptools wheel && pip install --user -r ./requirements.txt && rm ./requirements.txt
|
||||
|
||||
FROM base as runner
|
||||
RUN apk update && apk add --no-cache libffi-dev
|
||||
COPY --from=builder /root/.local /usr/local
|
||||
COPY . /app
|
||||
|
||||
FROM runner
|
||||
WORKDIR /app
|
||||
CMD ["python", "src/main.py"]
|
||||
|
|
42
LICENSE
42
LICENSE
|
@ -1,21 +1,21 @@
|
|||
MIT License
|
||||
|
||||
Copyright (c) 2023 BobMaster
|
||||
|
||||
Permission is hereby granted, free of charge, to any person obtaining a copy
|
||||
of this software and associated documentation files (the "Software"), to deal
|
||||
in the Software without restriction, including without limitation the rights
|
||||
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
|
||||
copies of the Software, and to permit persons to whom the Software is
|
||||
furnished to do so, subject to the following conditions:
|
||||
|
||||
The above copyright notice and this permission notice shall be included in all
|
||||
copies or substantial portions of the Software.
|
||||
|
||||
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
|
||||
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
|
||||
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
|
||||
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
|
||||
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
|
||||
SOFTWARE.
|
||||
MIT License
|
||||
|
||||
Copyright (c) 2023 BobMaster
|
||||
|
||||
Permission is hereby granted, free of charge, to any person obtaining a copy
|
||||
of this software and associated documentation files (the "Software"), to deal
|
||||
in the Software without restriction, including without limitation the rights
|
||||
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
|
||||
copies of the Software, and to permit persons to whom the Software is
|
||||
furnished to do so, subject to the following conditions:
|
||||
|
||||
The above copyright notice and this permission notice shall be included in all
|
||||
copies or substantial portions of the Software.
|
||||
|
||||
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
|
||||
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
|
||||
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
|
||||
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
|
||||
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
|
||||
SOFTWARE.
|
||||
|
|
80
README.md
80
README.md
|
@ -1,44 +1,36 @@
|
|||
## Introduction
|
||||
|
||||
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
|
||||
|
||||
1. Support Openai ChatGPT and Bing AI and Google Bard
|
||||
2. Support Bing Image Creator
|
||||
3. [pandora](https://github.com/pengzhile/pandora) with Session isolation support
|
||||
|
||||
## Installation and Setup
|
||||
|
||||
See https://github.com/hibobmaster/mattermost_bot/wiki
|
||||
|
||||
Edit `config.json` or `.env` with proper values
|
||||
|
||||
```sh
|
||||
docker compose up -d
|
||||
```
|
||||
|
||||
## Commands
|
||||
|
||||
- `!help` help message
|
||||
- `!gpt + [prompt]` generate a one time response from chatGPT
|
||||
- `!chat + [prompt]` chat using official chatGPT api with context conversation
|
||||
- `!bing + [prompt]` chat with Bing AI with context conversation
|
||||
- `!bard + [prompt]` chat with Google's Bard
|
||||
- `!pic + [prompt]` generate an image from Bing Image Creator
|
||||
|
||||
The following commands need pandora http api: https://github.com/pengzhile/pandora/blob/master/doc/wiki_en.md#http-restful-api
|
||||
- `!talk + [prompt]` chat using chatGPT web with context conversation
|
||||
- `!goon` ask chatGPT to complete the missing part from previous conversation
|
||||
- `!new` start a new converstaion
|
||||
|
||||
## Demo
|
||||
|
||||
![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>
|
||||
## 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.
|
||||
|
||||
## Feature
|
||||
|
||||
1. Support official openai api and self host models([LocalAI](https://localai.io/model-compatibility/))
|
||||
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)
|
||||
## Installation and Setup
|
||||
|
||||
See https://github.com/hibobmaster/mattermost_bot/wiki
|
||||
|
||||
Edit `config.json` or `.env` with proper values
|
||||
|
||||
```sh
|
||||
docker compose up -d
|
||||
```
|
||||
|
||||
## Commands
|
||||
|
||||
- `!help` help message
|
||||
- `!gpt + [prompt]` generate a one time response from chatGPT
|
||||
- `!chat + [prompt]` chat using official chatGPT api with context conversation
|
||||
- `!pic + [prompt]` Image generation with DALL·E or LocalAI or stable-diffusion-webui
|
||||
|
||||
- `!new` start a new converstaion
|
||||
|
||||
## Demo
|
||||
Remove support for Bing AI, Google Bard due to technical problems.
|
||||
![gpt command](https://imgur.com/vdT83Ln.jpg)
|
||||
![image generation](https://i.imgur.com/DQ3i3wW.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>
|
||||
|
|
46
askgpt.py
46
askgpt.py
|
@ -1,46 +0,0 @@
|
|||
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)
|
104
bard.py
104
bard.py
|
@ -1,104 +0,0 @@
|
|||
"""
|
||||
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
64
bing.py
|
@ -1,64 +0,0 @@
|
|||
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"
|
427
bot.py
427
bot.py
|
@ -1,427 +0,0 @@
|
|||
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"
|
||||
)
|
||||
|
||||
# initialize pandora
|
||||
if pandora_api_endpoint is not None:
|
||||
self.pandora_api_endpoint = pandora_api_endpoint
|
||||
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.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*.*$")
|
||||
self.new_prog = re.compile(r"^\s*!new\s*.*$")
|
||||
|
||||
self.pandora_data = {}
|
||||
|
||||
# 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
|
14
compose.yaml
14
compose.yaml
|
@ -11,23 +11,15 @@ services:
|
|||
networks:
|
||||
- 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:
|
||||
# image: pengzhile/pandora
|
||||
# container_name: pandora
|
||||
# restart: unless-stopped
|
||||
# environment:
|
||||
# - PANDORA_ACCESS_TOKEN="xxxxxxxxxxxxxx"
|
||||
# - PANDORA_SERVER="0.0.0.0:8008"
|
||||
# - PANDORA_ACCESS_TOKEN=xxxxxxxxxxxxxx
|
||||
# - PANDORA_SERVER=0.0.0.0:8008
|
||||
# networks:
|
||||
# - mattermost_network
|
||||
|
||||
networks:
|
||||
mattermost_network:
|
||||
mattermost_network:
|
||||
|
|
|
@ -1,11 +1,8 @@
|
|||
{
|
||||
"server_url": "xxxx.xxxx.xxxxx",
|
||||
"access_token": "xxxxxxxxxxxxxxxxxxxxxx",
|
||||
"username": "@chatgpt",
|
||||
"openai_api_key": "sk-xxxxxxxxxxxxxxxxxxx",
|
||||
"bing_api_endpoint": "http://api:3000/conversation",
|
||||
"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"
|
||||
}
|
||||
{
|
||||
"server_url": "xxxx.xxxx.xxxxx",
|
||||
"email": "xxxxx",
|
||||
"username": "@chatgpt",
|
||||
"password": "xxxxxxxxxxxxxxxxx",
|
||||
"openai_api_key": "xxxxxxxxxxxxxxxxxxxxxxxxx",
|
||||
"gpt_model": "gpt-3.5-turbo"
|
||||
}
|
||||
|
|
26
full-config.json.example
Normal file
26
full-config.json.example
Normal file
|
@ -0,0 +1,26 @@
|
|||
{
|
||||
"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
|
||||
}
|
53
main.py
53
main.py
|
@ -1,53 +0,0 @@
|
|||
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
101
pandora.py
|
@ -1,101 +0,0 @@
|
|||
# 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())
|
|
@ -1,27 +1,6 @@
|
|||
aiohttp==3.8.4
|
||||
aiosignal==1.3.1
|
||||
anyio==3.6.2
|
||||
async-timeout==4.0.2
|
||||
attrs==23.1.0
|
||||
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
|
||||
httpx
|
||||
Pillow
|
||||
tiktoken
|
||||
tenacity
|
||||
aiofiles
|
||||
mattermostdriver @ git+https://github.com/hibobmaster/python-mattermost-driver
|
||||
|
|
380
src/bot.py
Normal file
380
src/bot.py
Normal file
|
@ -0,0 +1,380 @@
|
|||
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
|
|
@ -1,324 +1,344 @@
|
|||
"""
|
||||
Code derived from: https://github.com/acheong08/ChatGPT/blob/main/src/revChatGPT/V3.py
|
||||
"""
|
||||
|
||||
import json
|
||||
import os
|
||||
from typing import AsyncGenerator
|
||||
import httpx
|
||||
import requests
|
||||
import tiktoken
|
||||
|
||||
|
||||
class Chatbot:
|
||||
"""
|
||||
Official ChatGPT API
|
||||
"""
|
||||
|
||||
def __init__(
|
||||
self,
|
||||
api_key: str,
|
||||
engine: str = os.environ.get("GPT_ENGINE") or "gpt-3.5-turbo",
|
||||
proxy: str = None,
|
||||
timeout: float = None,
|
||||
max_tokens: int = None,
|
||||
temperature: float = 0.5,
|
||||
top_p: float = 1.0,
|
||||
presence_penalty: float = 0.0,
|
||||
frequency_penalty: float = 0.0,
|
||||
reply_count: int = 1,
|
||||
system_prompt: str = "You are ChatGPT, a large language model trained by OpenAI. Respond conversationally",
|
||||
) -> None:
|
||||
"""
|
||||
Initialize Chatbot with API key (from https://platform.openai.com/account/api-keys)
|
||||
"""
|
||||
self.engine: str = engine
|
||||
self.api_key: str = api_key
|
||||
self.system_prompt: str = system_prompt
|
||||
self.max_tokens: int = max_tokens or (
|
||||
31000 if engine == "gpt-4-32k" else 7000 if engine == "gpt-4" else 4000
|
||||
)
|
||||
self.truncate_limit: int = (
|
||||
30500 if engine == "gpt-4-32k" else 6500 if engine == "gpt-4" 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.proxy = proxy
|
||||
self.session = requests.Session()
|
||||
self.session.proxies.update(
|
||||
{
|
||||
"http": proxy,
|
||||
"https": proxy,
|
||||
},
|
||||
)
|
||||
proxy = (
|
||||
proxy or os.environ.get("all_proxy") or os.environ.get("ALL_PROXY") or None
|
||||
)
|
||||
|
||||
if proxy:
|
||||
if "socks5h" not in proxy:
|
||||
self.aclient = httpx.AsyncClient(
|
||||
follow_redirects=True,
|
||||
proxies=proxy,
|
||||
timeout=timeout,
|
||||
)
|
||||
else:
|
||||
self.aclient = httpx.AsyncClient(
|
||||
follow_redirects=True,
|
||||
proxies=proxy,
|
||||
timeout=timeout,
|
||||
)
|
||||
|
||||
self.conversation: dict[str, list[dict]] = {
|
||||
"default": [
|
||||
{
|
||||
"role": "system",
|
||||
"content": system_prompt,
|
||||
},
|
||||
],
|
||||
}
|
||||
|
||||
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
|
||||
|
||||
def get_token_count(self, convo_id: str = "default") -> int:
|
||||
"""
|
||||
Get token count
|
||||
"""
|
||||
if self.engine not in [
|
||||
"gpt-3.5-turbo",
|
||||
"gpt-3.5-turbo-0301",
|
||||
"gpt-4",
|
||||
"gpt-4-0314",
|
||||
"gpt-4-32k",
|
||||
"gpt-4-32k-0314",
|
||||
]:
|
||||
raise NotImplementedError("Unsupported engine {self.engine}")
|
||||
|
||||
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():
|
||||
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)
|
||||
|
||||
def ask_stream(
|
||||
self,
|
||||
prompt: str,
|
||||
role: str = "user",
|
||||
convo_id: str = "default",
|
||||
**kwargs,
|
||||
):
|
||||
"""
|
||||
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
|
||||
response = self.session.post(
|
||||
os.environ.get("API_URL") or "https://api.openai.com/v1/chat/completions",
|
||||
headers={"Authorization": f"Bearer {kwargs.get('api_key', self.api_key)}"},
|
||||
json={
|
||||
"model": self.engine,
|
||||
"messages": self.conversation[convo_id],
|
||||
"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": self.get_max_tokens(convo_id=convo_id),
|
||||
},
|
||||
timeout=kwargs.get("timeout", self.timeout),
|
||||
stream=True,
|
||||
)
|
||||
|
||||
response_role: str = None
|
||||
full_response: str = ""
|
||||
for line in response.iter_lines():
|
||||
if not line:
|
||||
continue
|
||||
# Remove "data: "
|
||||
line = line.decode("utf-8")[6:]
|
||||
if line == "[DONE]":
|
||||
break
|
||||
resp: dict = json.loads(line)
|
||||
choices = resp.get("choices")
|
||||
if not choices:
|
||||
continue
|
||||
delta = choices[0].get("delta")
|
||||
if not delta:
|
||||
continue
|
||||
if "role" in delta:
|
||||
response_role = delta["role"]
|
||||
if "content" in delta:
|
||||
content = delta["content"]
|
||||
full_response += content
|
||||
yield content
|
||||
self.add_to_conversation(full_response, response_role, convo_id=convo_id)
|
||||
|
||||
async def ask_stream_async(
|
||||
self,
|
||||
prompt: str,
|
||||
role: str = "user",
|
||||
convo_id: str = "default",
|
||||
**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",
|
||||
os.environ.get("API_URL") or "https://api.openai.com/v1/chat/completions",
|
||||
headers={"Authorization": f"Bearer {kwargs.get('api_key', self.api_key)}"},
|
||||
json={
|
||||
"model": self.engine,
|
||||
"messages": self.conversation[convo_id],
|
||||
"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": self.get_max_tokens(convo_id=convo_id),
|
||||
},
|
||||
timeout=kwargs.get("timeout", self.timeout),
|
||||
) as response:
|
||||
if response.status_code != 200:
|
||||
await response.aread()
|
||||
|
||||
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)
|
||||
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",
|
||||
**kwargs,
|
||||
) -> str:
|
||||
"""
|
||||
Non-streaming ask
|
||||
"""
|
||||
response = self.ask_stream_async(
|
||||
prompt=prompt,
|
||||
role=role,
|
||||
convo_id=convo_id,
|
||||
**kwargs,
|
||||
)
|
||||
full_response: str = "".join([r async for r in response])
|
||||
return full_response
|
||||
|
||||
def ask(
|
||||
self,
|
||||
prompt: str,
|
||||
role: str = "user",
|
||||
convo_id: str = "default",
|
||||
**kwargs,
|
||||
) -> str:
|
||||
"""
|
||||
Non-streaming ask
|
||||
"""
|
||||
response = self.ask_stream(
|
||||
prompt=prompt,
|
||||
role=role,
|
||||
convo_id=convo_id,
|
||||
**kwargs,
|
||||
)
|
||||
full_response: str = "".join(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},
|
||||
]
|
||||
"""
|
||||
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, wait_random_exponential, stop_after_attempt
|
||||
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
|
||||
"""
|
||||
_engine = self.engine
|
||||
if self.engine not in ENGINES:
|
||||
# use gpt-3.5-turbo to caculate token
|
||||
_engine = "gpt-3.5-turbo"
|
||||
tiktoken.model.MODEL_TO_ENCODING["gpt-4"] = "cl100k_base"
|
||||
|
||||
encoding = tiktoken.encoding_for_model(_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
|
||||
|
||||
async def ask_async_v2(
|
||||
self,
|
||||
prompt: str,
|
||||
role: str = "user",
|
||||
convo_id: str = "default",
|
||||
model: str = None,
|
||||
pass_history: bool = True,
|
||||
**kwargs,
|
||||
) -> str:
|
||||
# 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
|
||||
response = await self.aclient.post(
|
||||
url=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],
|
||||
# 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),
|
||||
)
|
||||
resp = response.json()
|
||||
full_response = resp["choices"][0]["message"]["content"]
|
||||
self.add_to_conversation(
|
||||
full_response, resp["choices"][0]["message"]["role"], convo_id=convo_id
|
||||
)
|
||||
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:
|
||||
response = await self.aclient.post(
|
||||
url=self.api_url,
|
||||
json={
|
||||
"model": model or self.engine,
|
||||
"messages": [
|
||||
{
|
||||
"role": role,
|
||||
"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"]
|
106
src/imagegen.py
Normal file
106
src/imagegen.py
Normal file
|
@ -0,0 +1,106 @@
|
|||
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
|
|
@ -1,30 +1,30 @@
|
|||
import logging
|
||||
|
||||
|
||||
def getlogger():
|
||||
# create a custom logger if not already created
|
||||
logger = logging.getLogger(__name__)
|
||||
if not logger.hasHandlers():
|
||||
logger.setLevel(logging.INFO)
|
||||
|
||||
# create handlers
|
||||
info_handler = logging.StreamHandler()
|
||||
error_handler = logging.FileHandler("bot.log", mode="a")
|
||||
error_handler.setLevel(logging.ERROR)
|
||||
info_handler.setLevel(logging.INFO)
|
||||
|
||||
# create formatters
|
||||
error_format = logging.Formatter(
|
||||
"%(asctime)s - %(name)s - %(funcName)s - %(levelname)s - %(message)s"
|
||||
)
|
||||
info_format = logging.Formatter("%(asctime)s - %(levelname)s - %(message)s")
|
||||
|
||||
# set formatter
|
||||
error_handler.setFormatter(error_format)
|
||||
info_handler.setFormatter(info_format)
|
||||
|
||||
# add handlers to logger
|
||||
logger.addHandler(error_handler)
|
||||
logger.addHandler(info_handler)
|
||||
|
||||
return logger
|
||||
import logging
|
||||
|
||||
|
||||
def getlogger():
|
||||
# create a custom logger if not already created
|
||||
logger = logging.getLogger(__name__)
|
||||
if not logger.hasHandlers():
|
||||
logger.setLevel(logging.INFO)
|
||||
|
||||
# create handlers
|
||||
info_handler = logging.StreamHandler()
|
||||
error_handler = logging.FileHandler("bot.log", mode="a")
|
||||
error_handler.setLevel(logging.ERROR)
|
||||
info_handler.setLevel(logging.INFO)
|
||||
|
||||
# create formatters
|
||||
error_format = logging.Formatter(
|
||||
"%(asctime)s - %(name)s - %(funcName)s - %(levelname)s - %(message)s"
|
||||
)
|
||||
info_format = logging.Formatter("%(asctime)s - %(levelname)s - %(message)s")
|
||||
|
||||
# set formatter
|
||||
error_handler.setFormatter(error_format)
|
||||
info_handler.setFormatter(info_format)
|
||||
|
||||
# add handlers to logger
|
||||
logger.addHandler(error_handler)
|
||||
logger.addHandler(info_handler)
|
||||
|
||||
return logger
|
97
src/main.py
Normal file
97
src/main.py
Normal file
|
@ -0,0 +1,97 @@
|
|||
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())
|
Loading…
Reference in a new issue