Make gptbot more compatible

Support specific output image format(jpeg, png) and size

.dockerignore

@@ -3,6 +3,8 @@ images
 *.md
 Dockerfile
 Dockerfile-dev
+compose.yaml
+compose-dev.yaml
 .dockerignore
 config.json
 config.json.sample
@@ -15,7 +17,13 @@ venv
 .git
 .idea
 __pycache__
+src/__pycache__
 .env
 .env.example
 .github
 settings.js
+mattermost-server
+tests
+full-config.json.example
+config.json.example
+.full-env.example

.env.example

@@ -1,7 +1,6 @@
 SERVER_URL="xxxxx.xxxxxx.xxxxxxxxx"
-ACCESS_TOKEN="xxxxxxxxxxxxxxxxx"
 USERNAME="@chatgpt"
-OPENAI_API_KEY="sk-xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx"
+EMAIL="xxxxxx"
-BING_API_ENDPOINT="http://api:3000/conversation"
+PASSWORD="xxxxxxxxxxxxxx"
-BARD_TOKEN="xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx."
+OPENAI_API_KEY="xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx"
-BING_AUTH_COOKIE="xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx"
+GPT_MODEL="gpt-3.5-turbo"

.full-env.example

@@ -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

.gitignore

@@ -134,3 +134,7 @@ dmypy.json
 
 # Pyre type checker
 .pyre/
+
+# custom
+compose-dev.yaml
+mattermost-server

.pre-commit-config.yaml

@@ -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]

.vscode/settings.json

@@ -1,3 +0,0 @@
-{
-    "python.formatting.provider": "black"
-}

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

CHANGELOG.md

@@ -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

Dockerfile

@@ -13,4 +13,4 @@ COPY . /app
 
 FROM runner
 WORKDIR /app
-CMD ["python", "main.py"]
+CMD ["python", "src/main.py"]

README.md

@@ -1,12 +1,11 @@
 ## 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 six types of prompts: `!gpt`, `!chat` and `!bing` and `!pic` and `!bard` and  `!help` depending on the first word of the prompt.
+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 Openai ChatGPT and Bing AI and Google Bard(US only at the moment)
+1. Support official openai api and self host models([LocalAI](https://localai.io/model-compatibility/))
-2. Support Bing Image Creator
+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
@@ -17,8 +16,21 @@ Edit `config.json` or `.env` with proper values
 docker compose up -d
 ```
 
-## Demo
+## Commands
 
-![demo1](https://i.imgur.com/XRAQB4B.jpg)
+- `!help` help message
-![demo2](https://i.imgur.com/if72kyH.jpg)
+- `!gpt + [prompt]` generate a one time response from chatGPT
-![demo3](https://i.imgur.com/GHczfkv.jpg)
+- `!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>

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)

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

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"

bot.py

@@ -1,326 +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
-
-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,
-        bard_token: Optional[str] = None,
-        bing_auth_cookie: Optional[str] = None,
-        port: int = 443,
-        timeout: int = 30,
-    ) -> None:
-        if server_url is None:
-            raise ValueError("server url must be provided")
-
-        if port is None:
-            self.port = 443
-
-        if timeout is None:
-            self.timeout = 30
-
-        # login relative info
-        if access_token is None and password is None:
-            raise ValueError("Either token or password must be provided")
-
-        if access_token is not None:
-            self.driver = Driver(
-                {
-                    "token": access_token,
-                    "url": server_url,
-                    "port": self.port,
-                    "request_timeout": self.timeout,
-                }
-            )
-        else:
-            self.driver = Driver(
-                {
-                    "login_id": login_id,
-                    "password": password,
-                    "url": server_url,
-                    "port": self.port,
-                    "request_timeout": self.timeout,
-                }
-            )
-
-        # @chatgpt
-        if username is None:
-            raise ValueError("username must be provided")
-        else:
-            self.username = username
-
-        # openai_api_endpoint
-        if openai_api_endpoint is None:
-            self.openai_api_endpoint = "https://api.openai.com/v1/chat/completions"
-        else:
-            self.openai_api_endpoint = openai_api_endpoint
-
-        # aiohttp session
-        self.session = aiohttp.ClientSession()
-
-        self.openai_api_key = openai_api_key
-        # initialize chatGPT class
-        if self.openai_api_key is not None:
-            # request header for !gpt command
-            self.headers = {
-                "Content-Type": "application/json",
-                "Authorization": f"Bearer {self.openai_api_key}",
-            }
-
-            self.askgpt = askGPT(
-                self.session,
-                self.openai_api_endpoint,
-                self.headers,
-            )
-
-            self.chatbot = Chatbot(api_key=self.openai_api_key)
-        else:
-            logger.warning(
-                "openai_api_key is not provided, !gpt and !chat command will not work"
-            )
-
-        self.bing_api_endpoint = bing_api_endpoint
-        # initialize bingbot
-        if self.bing_api_endpoint is not None:
-            self.bingbot = BingBot(
-                session=self.session,
-                bing_api_endpoint=self.bing_api_endpoint,
-            )
-        else:
-            logger.warning(
-                "bing_api_endpoint is not provided, !bing command will not work"
-            )
-
-        self.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 [!gpt {prompt}] [!chat {prompt}] [!bing {prompt}] [!pic {prompt}] [!bard {prompt}]
-        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*(.+)$")
-        self.help_prog = re.compile(r"^\s*!help\s*.*$")
-
-    # close session
-    def __del__(self) -> None:
-        self.driver.disconnect()
-
-    async def __aexit__(self, exc_type, exc_val, exc_tb):
-        await self.session.close()
-
-    def login(self) -> None:
-        self.driver.login()
-
-    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"]
-                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.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"
-            + "!help, help message"
-        )
-        return help_info

compose.yaml

@@ -2,7 +2,7 @@ services:
   app:
     image: ghcr.io/hibobmaster/mattermost_bot:latest
     container_name: mattermost_bot
-    restart: always
+    restart: unless-stopped
     env_file:
       - .env
     # volumes:
@@ -11,11 +11,13 @@ services:
     networks:
       - mattermost_network
 
-  # api:
+  # pandora:
-  #   image: hibobmaster/node-chatgpt-api:latest
+  #   image: pengzhile/pandora
-  #   container_name: node-chatgpt-api
+  #   container_name: pandora
-  #   volumes:
+  #   restart: unless-stopped
-  #     - ./settings.js:/var/chatgpt-api/settings.js
+  #   environment:
+  #     - PANDORA_ACCESS_TOKEN=xxxxxxxxxxxxxx
+  #     - PANDORA_SERVER=0.0.0.0:8008
   #   networks:
   #     - mattermost_network
 

config.json.example

@@ -1,9 +1,8 @@
 {
     "server_url": "xxxx.xxxx.xxxxx",
-    "access_token": "xxxxxxxxxxxxxxxxxxxxxx",
+    "email": "xxxxx",
     "username": "@chatgpt",
-    "openai_api_key": "sk-xxxxxxxxxxxxxxxxxxx",
+    "password": "xxxxxxxxxxxxxxxxx",
-    "bing_api_endpoint": "http://api:3000/conversation",
+    "openai_api_key": "xxxxxxxxxxxxxxxxxxxxxxxxx",
-    "bard_token": "xxxxxxxxxxxxxxxxxxxxxxxxxxxxx.",
+    "gpt_model": "gpt-3.5-turbo"
-    "bing_auth_cookie": "xxxxxxxxxxxxxxxxxxxxxxxxxxxxxx"
 }

full-config.json.example

@@ -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
+}

main.py

@@ -1,49 +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"),
-            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"),
-            port=os.environ.get("PORT"),
-            timeout=os.environ.get("TIMEOUT"),
-        )
-
-    mattermost_bot.login()
-
-    await mattermost_bot.run()
-
-
-if __name__ == "__main__":
-    asyncio.run(main())

requirements.txt

@@ -1,27 +1,6 @@
-aiohttp==3.8.4
+httpx
-aiosignal==1.3.1
+Pillow
-anyio==3.6.2
+tiktoken
-async-timeout==4.0.2
+tenacity
-attrs==23.1.0
+aiofiles
-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

src/bot.py

@@ -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

src/gptbot.py

@@ -1,15 +1,26 @@
 """
-Code derived from: https://github.com/acheong08/ChatGPT/blob/main/src/revChatGPT/V3.py
+Code derived from https://github.com/acheong08/ChatGPT/blob/main/src/revChatGPT/V3.py
+A simple wrapper for the official ChatGPT API
 """
-
 import json
-import os
 from typing import AsyncGenerator
+from tenacity import retry, wait_random_exponential, stop_after_attempt
 import httpx
-import requests
 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
@@ -17,29 +28,48 @@ class Chatbot:
 
     def __init__(
         self,
+        aclient: httpx.AsyncClient,
         api_key: str,
-        engine: str = os.environ.get("GPT_ENGINE") or "gpt-3.5-turbo",
+        api_url: str = None,
-        proxy: str = None,
+        engine: str = None,
         timeout: float = None,
         max_tokens: int = None,
-        temperature: float = 0.5,
+        temperature: float = 0.8,
         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",
+        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
+        self.engine: str = engine or "gpt-3.5-turbo"
         self.api_key: str = api_key
-        self.system_prompt: str = system_prompt
+        self.api_url: str = api_url or "https://api.openai.com/v1/chat/completions"
-        self.max_tokens: int = max_tokens or (
+        self.system_prompt: str = (
-            31000 if engine == "gpt-4-32k" else 7000 if engine == "gpt-4" else 4000
+            system_prompt
+            or "You are ChatGPT, \
+            a large language model trained by OpenAI. Respond conversationally"
         )
-        self.truncate_limit: int = (
+        self.max_tokens: int = max_tokens or (
-            30500 if engine == "gpt-4-32k" else 6500 if engine == "gpt-4" else 3500
+            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
@@ -47,31 +77,8 @@ class Chatbot:
         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:
+        self.aclient = aclient
-            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": [
@@ -82,6 +89,9 @@ class Chatbot:
             ],
         }
 
+        if self.get_token_count("default") > self.max_tokens:
+            raise Exception("System prompt is too long")
+
     def add_to_conversation(
         self,
         message: str,
@@ -107,30 +117,26 @@ class Chatbot:
             else:
                 break
 
+    # https://github.com/openai/openai-cookbook/blob/main/examples/How_to_count_tokens_with_tiktoken.ipynb
     def get_token_count(self, convo_id: str = "default") -> int:
         """
         Get token count
         """
-        if self.engine not in [
+        _engine = self.engine
-            "gpt-3.5-turbo",
+        if self.engine not in ENGINES:
-            "gpt-3.5-turbo-0301",
+            # use gpt-3.5-turbo to caculate token
-            "gpt-4",
+            _engine = "gpt-3.5-turbo"
-            "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)
+        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():
-                num_tokens += len(encoding.encode(value))
+                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
@@ -142,77 +148,13 @@ class Chatbot:
         """
         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",
+        model: str = None,
+        pass_history: bool = True,
         **kwargs,
     ) -> AsyncGenerator[str, None]:
         """
@@ -226,11 +168,11 @@ class Chatbot:
         # Get response
         async with self.aclient.stream(
             "post",
-            os.environ.get("API_URL") or "https://api.openai.com/v1/chat/completions",
+            self.api_url,
             headers={"Authorization": f"Bearer {kwargs.get('api_key', self.api_key)}"},
             json={
-                "model": self.engine,
+                "model": model or self.engine,
-                "messages": self.conversation[convo_id],
+                "messages": self.conversation[convo_id] if pass_history else [prompt],
                 "stream": True,
                 # kwargs
                 "temperature": kwargs.get("temperature", self.temperature),
@@ -245,12 +187,18 @@ class Chatbot:
                 ),
                 "n": kwargs.get("n", self.reply_count),
                 "user": role,
-                "max_tokens": self.get_max_tokens(convo_id=convo_id),
+                "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 = ""
@@ -263,6 +211,8 @@ class Chatbot:
                 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
@@ -282,6 +232,8 @@ class Chatbot:
         prompt: str,
         role: str = "user",
         convo_id: str = "default",
+        model: str = None,
+        pass_history: bool = True,
         **kwargs,
     ) -> str:
         """
@@ -291,28 +243,59 @@ class Chatbot:
             prompt=prompt,
             role=role,
             convo_id=convo_id,
+            model=model,
+            pass_history=pass_history,
             **kwargs,
         )
         full_response: str = "".join([r async for r in response])
         return full_response
 
-    def ask(
+    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
-        Non-streaming ask
+        if convo_id not in self.conversation:
-        """
+            self.reset(convo_id=convo_id, system_prompt=self.system_prompt)
-        response = self.ask_stream(
+        self.add_to_conversation(prompt, "user", convo_id=convo_id)
-            prompt=prompt,
+        self.__truncate_conversation(convo_id=convo_id)
-            role=role,
+        # Get response
-            convo_id=convo_id,
+        response = await self.aclient.post(
-            **kwargs,
+            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
         )
-        full_response: str = "".join(response)
         return full_response
 
     def reset(self, convo_id: str = "default", system_prompt: str = None) -> None:
@@ -322,3 +305,40 @@ class Chatbot:
         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"]

src/imagegen.py

@@ -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

src/main.py

@@ -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())