.dockerignore

@@ -3,8 +3,6 @@ images
 *.md
 Dockerfile
 Dockerfile-dev
-compose.yaml
-compose-dev.yaml
 .dockerignore
 config.json
 config.json.sample
@@ -17,13 +15,7 @@ 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

@@ -1,6 +1,9 @@
 SERVER_URL="xxxxx.xxxxxx.xxxxxxxxx"
+ACCESS_TOKEN="xxxxxxxxxxxxxxxxx"
 USERNAME="@chatgpt"
-EMAIL="xxxxxx"
-PASSWORD="xxxxxxxxxxxxxx"
-OPENAI_API_KEY="xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx"
-GPT_MODEL="gpt-3.5-turbo"
+OPENAI_API_KEY="sk-xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx"
+BING_API_ENDPOINT="http://api:3000/conversation"
+BARD_TOKEN="xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx."
+BING_AUTH_COOKIE="xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx"
+PANDORA_API_ENDPOINT="http://127.0.0.1:8008"
+PANDORA_API_MODEL="text-davinci-002-render-sha-mobile"

.full-env.example

@@ -1,24 +0,0 @@
-SERVER_URL="xxxxx.xxxxxx.xxxxxxxxx"
-EMAIL="xxxxxx"
-USERNAME="@chatgpt"
-PASSWORD="xxxxxxxxxxxxxx"
-PORT=443
-SCHEME="https"
-OPENAI_API_KEY="xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx"
-GPT_API_ENDPOINT="https://api.openai.com/v1/chat/completions"
-GPT_MODEL="gpt-3.5-turbo"
-MAX_TOKENS=4000
-TOP_P=1.0
-PRESENCE_PENALTY=0.0
-FREQUENCY_PENALTY=0.0
-REPLY_COUNT=1
-SYSTEM_PROMPT="You are ChatGPT,  a large language model trained by OpenAI. Respond conversationally"
-TEMPERATURE=0.8
-IMAGE_GENERATION_ENDPOINT="http://127.0.0.1:7860/sdapi/v1/txt2img"
-IMAGE_GENERATION_BACKEND="sdwui" # openai or sdwui or localai
-IMAGE_GENERATION_SIZE="512x512"
-IMAGE_FORMAT="jpeg"
-SDWUI_STEPS=20
-SDWUI_SAMPLER_NAME="Euler a"
-SDWUI_CFG_SCALE=7
-TIMEOUT=120.0

.github/workflows/pylint.yml

@@ -0,0 +1,25 @@
+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

.gitignore

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

.pre-commit-config.yaml

@@ -1,16 +0,0 @@
-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

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

BingImageGen.py

@@ -0,0 +1,165 @@
+"""
+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

@@ -1,26 +0,0 @@
-# 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", "src/main.py"]
+CMD ["python", "main.py"]

README.md

@@ -1,11 +1,13 @@
 ## Introduction
 
-This is a simple Mattermost Bot that uses OpenAI's GPT API(or self-host models) to generate responses to user inputs. The bot responds to these commands: `!gpt`, `!chat` and `!new` and  `!help` depending on the first word of the prompt.
+This is a simple Mattermost Bot that uses OpenAI's GPT API and Bing AI and Google Bard to generate responses to user inputs. The bot responds to these commands: `!gpt`, `!chat` and `!bing` and `!pic` and `!bard` and `!talk` and `!goon` and `!new` and  `!help` depending on the first word of the prompt.
 
 ## Feature
 
-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)
+1. Support Openai ChatGPT and Bing AI and Google Bard
+2. Support Bing Image Creator
+3. [pandora](https://github.com/pengzhile/pandora)
+
 ## Installation and Setup
 
 See https://github.com/hibobmaster/mattermost_bot/wiki
@@ -21,14 +23,20 @@ docker compose up -d
 - `!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
+- `!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
-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)
+
+![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">

askgpt.py

@@ -0,0 +1,46 @@
+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

@@ -0,0 +1,104 @@
+"""
+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

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

bot.py

@@ -0,0 +1,420 @@
+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
+            )
+            self.pandora_init()
+            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*.*$")
+
+    # close session
+    def __del__(self) -> None:
+        self.driver.disconnect()
+
+    async def __aenter__(self):
+        return self
+
+    async def __aexit__(self, exc_type, exc_val, exc_tb):
+        await self.session.close()
+
+    def login(self) -> None:
+        self.driver.login()
+
+    def pandora_init(self) -> None:
+        self.conversation_id = None
+        self.parent_message_id = str(uuid.uuid4())
+        self.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"]
+                
+                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.conversation_id is not None:
+                            data = {
+                                "prompt": prompt,
+                                "model": self.pandora_api_model,
+                                "parent_message_id": self.parent_message_id,
+                                "conversation_id": self.conversation_id,
+                                "stream": False,
+                            }
+                        else:
+                            data = {
+                                "prompt": prompt,
+                                "model": self.pandora_api_model,
+                                "parent_message_id": self.parent_message_id,
+                                "stream": False,
+                            }
+                        response = await self.pandora.talk(data)
+                        self.conversation_id = response['conversation_id']
+                        self.parent_message_id = response['message']['id']
+                        content = response['message']['content']['parts'][0]
+                        if self.first_time:
+                            self.first_time = False
+                            data = {
+                                "model": self.pandora_api_model,
+                                "message_id": self.parent_message_id,
+                            }
+                            await self.pandora.gen_title(data, self.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.conversation_id is not None:
+                    try:
+                        data = {
+                            "model": self.pandora_api_model,
+                            "parent_message_id": self.parent_message_id,
+                            "conversation_id": self.conversation_id,
+                            "stream": False,
+                        }
+                        response = await self.pandora.goon(data)
+                        self.conversation_id = response['conversation_id']
+                        self.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()
+
+            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

compose.yaml

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

config.json.example

@@ -1,8 +1,11 @@
 {
     "server_url": "xxxx.xxxx.xxxxx",
-    "email": "xxxxx",
+    "access_token": "xxxxxxxxxxxxxxxxxxxxxx",
     "username": "@chatgpt",
-    "password": "xxxxxxxxxxxxxxxxx",
-    "openai_api_key": "xxxxxxxxxxxxxxxxxxxxxxxxx",
-    "gpt_model": "gpt-3.5-turbo"
+    "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"
 }

full-config.json.example

@@ -1,26 +0,0 @@
-{
-    "server_url": "localhost",
-    "email": "bot@hibobmaster.com",
-    "username": "@bot",
-    "password": "SfBKY%K7*e&a%ZX$3g@Am&jQ",
-    "port": 8065,
-    "scheme": "http",
-    "openai_api_key": "xxxxxxxxxxxxxxxxxxxxxxxx",
-    "gpt_api_endpoint": "https://api.openai.com/v1/chat/completions",
-    "gpt_model": "gpt-3.5-turbo",
-    "max_tokens": 4000,
-    "top_p": 1.0,
-    "presence_penalty": 0.0,
-    "frequency_penalty": 0.0,
-    "reply_count": 1,
-    "temperature": 0.8,
-    "system_prompt": "You are ChatGPT,  a large language model trained by OpenAI. Respond conversationally",
-    "image_generation_endpoint": "http://localai:8080/v1/images/generations",
-    "image_generation_backend": "localai",
-    "image_generation_size": "512x512",
-    "sdwui_steps": 20,
-    "sdwui_sampler_name": "Euler a",
-    "sdwui_cfg_scale": 7,
-    "image_format": "jpeg",
-    "timeout": 120.0
-}

main.py

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

pandora.py

@@ -0,0 +1,100 @@
+# 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) -> None:
+        self.api_endpoint = api_endpoint.rstrip('/')
+        self.session = aiohttp.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"
+    client = Pandora(api_endpoint)
+    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())

requirements.txt

@@ -1,6 +1,27 @@
-httpx
-Pillow
-tiktoken
-tenacity
-aiofiles
+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

src/bot.py

@@ -1,380 +0,0 @@
-import sys
-import aiofiles.os
-from mattermostdriver import AsyncDriver
-from typing import Optional
-import json
-import asyncio
-import re
-import os
-from pathlib import Path
-from gptbot import Chatbot
-from log import getlogger
-import httpx
-import imagegen
-
-logger = getlogger()
-
-
-class Bot:
-    def __init__(
-        self,
-        server_url: str,
-        username: str,
-        email: str,
-        password: str,
-        port: Optional[int] = 443,
-        scheme: Optional[str] = "https",
-        openai_api_key: Optional[str] = None,
-        gpt_api_endpoint: Optional[str] = None,
-        gpt_model: Optional[str] = None,
-        max_tokens: Optional[int] = None,
-        top_p: Optional[float] = None,
-        presence_penalty: Optional[float] = None,
-        frequency_penalty: Optional[float] = None,
-        reply_count: Optional[int] = None,
-        system_prompt: Optional[str] = None,
-        temperature: Optional[float] = None,
-        image_generation_endpoint: Optional[str] = None,
-        image_generation_backend: Optional[str] = None,
-        image_generation_size: Optional[str] = None,
-        sdwui_steps: Optional[int] = None,
-        sdwui_sampler_name: Optional[str] = None,
-        sdwui_cfg_scale: Optional[float] = None,
-        image_format: Optional[str] = None,
-        timeout: Optional[float] = 120.0,
-    ) -> None:
-        if server_url is None:
-            raise ValueError("server url must be provided")
-
-        if port is None:
-            self.port = 443
-        else:
-            port = int(port)
-            if port <= 0 or port > 65535:
-                raise ValueError("port must be between 0 and 65535")
-            self.port = port
-
-        if scheme is None:
-            self.scheme = "https"
-        else:
-            if scheme.strip().lower() not in ["http", "https"]:
-                raise ValueError("scheme must be either http or https")
-            self.scheme = scheme
-
-        if image_generation_endpoint and image_generation_backend not in [
-            "openai",
-            "sdwui",
-            "localai",
-            None,
-        ]:
-            logger.error("image_generation_backend must be openai or sdwui or localai")
-            sys.exit(1)
-
-        if image_format not in ["jpeg", "png", None]:
-            logger.error("image_format should be jpeg or png, leave blank for jpeg")
-            sys.exit(1)
-
-        # @chatgpt
-        if username is None:
-            raise ValueError("username must be provided")
-        else:
-            self.username = username
-
-        self.openai_api_key: str = openai_api_key
-        self.gpt_api_endpoint = (
-            gpt_api_endpoint or "https://api.openai.com/v1/chat/completions"
-        )
-        self.gpt_model: str = gpt_model or "gpt-3.5-turbo"
-        self.max_tokens: int = max_tokens or 4000
-        self.top_p: float = top_p or 1.0
-        self.temperature: float = temperature or 0.8
-        self.presence_penalty: float = presence_penalty or 0.0
-        self.frequency_penalty: float = frequency_penalty or 0.0
-        self.reply_count: int = reply_count or 1
-        self.system_prompt: str = (
-            system_prompt
-            or "You are ChatGPT, \
-            a large language model trained by OpenAI. Respond conversationally"
-        )
-        self.image_generation_endpoint: str = image_generation_endpoint
-        self.image_generation_backend: str = image_generation_backend
-
-        if image_format:
-            self.image_format: str = image_format
-        else:
-            self.image_format = "jpeg"
-
-        if image_generation_size is None:
-            self.image_generation_size = "512x512"
-            self.image_generation_width = 512
-            self.image_generation_height = 512
-        else:
-            self.image_generation_size = image_generation_size
-            self.image_generation_width = self.image_generation_size.split("x")[0]
-            self.image_generation_height = self.image_generation_size.split("x")[1]
-
-        self.sdwui_steps = sdwui_steps
-        self.sdwui_sampler_name = sdwui_sampler_name
-        self.sdwui_cfg_scale = sdwui_cfg_scale
-
-        self.timeout = timeout or 120.0
-
-        self.bot_id = None
-
-        self.base_path = Path(os.path.dirname(__file__)).parent
-
-        if not os.path.exists(self.base_path / "images"):
-            os.mkdir(self.base_path / "images")
-
-        #  httpx session
-        self.httpx_client = httpx.AsyncClient()
-
-        # initialize Chatbot object
-        self.chatbot = Chatbot(
-            aclient=self.httpx_client,
-            api_key=self.openai_api_key,
-            api_url=self.gpt_api_endpoint,
-            engine=self.gpt_model,
-            timeout=self.timeout,
-            max_tokens=self.max_tokens,
-            top_p=self.top_p,
-            presence_penalty=self.presence_penalty,
-            frequency_penalty=self.frequency_penalty,
-            reply_count=self.reply_count,
-            system_prompt=self.system_prompt,
-            temperature=self.temperature,
-        )
-
-        # login relative info
-        if email is None and password is None:
-            raise ValueError("user email and password must be provided")
-
-        self.driver = AsyncDriver(
-            {
-                "login_id": email,
-                "password": password,
-                "url": server_url,
-                "port": self.port,
-                "request_timeout": self.timeout,
-                "scheme": self.scheme,
-            }
-        )
-
-        # regular expression to match keyword
-        self.gpt_prog = re.compile(r"^\s*!gpt\s*(.+)$")
-        self.chat_prog = re.compile(r"^\s*!chat\s*(.+)$")
-        self.pic_prog = re.compile(r"^\s*!pic\s*(.+)$")
-        self.help_prog = re.compile(r"^\s*!help\s*.*$")
-        self.new_prog = re.compile(r"^\s*!new\s*.*$")
-
-    # close session
-    async def close(self, task: asyncio.Task) -> None:
-        await self.httpx_client.aclose()
-        self.driver.disconnect()
-        task.cancel()
-
-    async def login(self) -> None:
-        await self.driver.login()
-        # get user id
-        resp = await self.driver.users.get_user(user_id="me")
-        self.bot_id = resp["id"]
-
-    async def run(self) -> None:
-        await self.driver.init_websocket(self.websocket_handler)
-
-    # websocket handler
-    async def websocket_handler(self, message) -> None:
-        logger.info(message)
-        response = json.loads(message)
-        if "event" in response:
-            event_type = response["event"]
-            if event_type == "posted":
-                raw_data = response["data"]["post"]
-                raw_data_dict = json.loads(raw_data)
-                user_id = raw_data_dict["user_id"]
-                root_id = (
-                    raw_data_dict["root_id"]
-                    if raw_data_dict["root_id"]
-                    else raw_data_dict["id"]
-                )
-                channel_id = raw_data_dict["channel_id"]
-                sender_name = response["data"]["sender_name"]
-                raw_message = raw_data_dict["message"]
-
-                try:
-                    asyncio.create_task(
-                        self.message_callback(
-                            raw_message, channel_id, user_id, sender_name, root_id
-                        )
-                    )
-                except Exception as e:
-                    await self.send_message(channel_id, f"{e}", root_id)
-
-    # message callback
-    async def message_callback(
-        self,
-        raw_message: str,
-        channel_id: str,
-        user_id: str,
-        sender_name: str,
-        root_id: str,
-    ) -> None:
-        # prevent command trigger loop
-        if sender_name != self.username:
-            message = raw_message
-
-            if (
-                self.openai_api_key is not None
-                or self.gpt_api_endpoint != "https://api.openai.com/v1/chat/completions"
-            ):
-                # !gpt command trigger handler
-                if self.gpt_prog.match(message):
-                    prompt = self.gpt_prog.match(message).group(1)
-                    try:
-                        # sending typing state
-                        await self.driver.users.publish_user_typing(
-                            self.bot_id,
-                            options={
-                                "channel_id": channel_id,
-                            },
-                        )
-                        response = await self.chatbot.oneTimeAsk(prompt)
-                        await self.send_message(channel_id, f"{response}", root_id)
-                    except Exception as e:
-                        logger.error(e, exc_info=True)
-                        raise Exception(e)
-
-                # !chat command trigger handler
-                elif self.chat_prog.match(message):
-                    prompt = self.chat_prog.match(message).group(1)
-                    try:
-                        # sending typing state
-                        await self.driver.users.publish_user_typing(
-                            self.bot_id,
-                            options={
-                                "channel_id": channel_id,
-                            },
-                        )
-                        response = await self.chatbot.ask_async_v2(
-                            prompt=prompt, convo_id=user_id
-                        )
-                        await self.send_message(channel_id, f"{response}", root_id)
-                    except Exception as e:
-                        logger.error(e, exc_info=True)
-                        raise Exception(e)
-
-            # !new command trigger handler
-            if self.new_prog.match(message):
-                self.chatbot.reset(convo_id=user_id)
-                try:
-                    await self.send_message(
-                        channel_id,
-                        "New conversation created, "
-                        + "please use !chat to start chatting!",
-                        root_id,
-                    )
-                except Exception as e:
-                    logger.error(e, exc_info=True)
-                    raise Exception(e)
-
-            # !pic command trigger handler
-            if self.image_generation_endpoint and self.image_generation_backend:
-                if self.pic_prog.match(message):
-                    prompt = self.pic_prog.match(message).group(1)
-                    # generate image
-                    try:
-                        # sending typing state
-                        await self.driver.users.publish_user_typing(
-                            self.bot_id,
-                            options={
-                                "channel_id": channel_id,
-                            },
-                        )
-                        image_path_list = await imagegen.get_images(
-                            self.httpx_client,
-                            self.image_generation_endpoint,
-                            prompt,
-                            self.image_generation_backend,
-                            timeount=self.timeout,
-                            api_key=self.openai_api_key,
-                            output_path=self.base_path / "images",
-                            n=1,
-                            size=self.image_generation_size,
-                            width=self.image_generation_width,
-                            height=self.image_generation_height,
-                            steps=self.sdwui_steps,
-                            sampler_name=self.sdwui_sampler_name,
-                            cfg_scale=self.sdwui_cfg_scale,
-                            image_format=self.image_format,
-                        )
-                        # send image
-                        for image_path in image_path_list:
-                            await self.send_file(
-                                channel_id,
-                                f"{prompt}",
-                                image_path,
-                                root_id,
-                            )
-                            await aiofiles.os.remove(image_path)
-                    except Exception as e:
-                        logger.error(e, exc_info=True)
-                        raise Exception(e)
-
-            # !help command trigger handler
-            if self.help_prog.match(message):
-                try:
-                    await self.send_message(channel_id, self.help(), root_id)
-                except Exception as e:
-                    logger.error(e, exc_info=True)
-
-    # send message to room
-    async def send_message(self, channel_id: str, message: str, root_id: str) -> None:
-        await self.driver.posts.create_post(
-            options={
-                "channel_id": channel_id,
-                "message": message,
-                "root_id": root_id,
-            }
-        )
-
-    # send file to room
-    async def send_file(
-        self, channel_id: str, message: str, filepath: str, root_id: str
-    ) -> None:
-        filename = os.path.split(filepath)[-1]
-        try:
-            file_id = await self.driver.files.upload_file(
-                channel_id=channel_id,
-                files={
-                    "files": (filename, open(filepath, "rb")),
-                },
-            )
-            file_id = file_id["file_infos"][0]["id"]
-        except Exception as e:
-            logger.error(e, exc_info=True)
-            raise Exception(e)
-
-        try:
-            await self.driver.posts.create_post(
-                options={
-                    "channel_id": channel_id,
-                    "message": message,
-                    "file_ids": [file_id],
-                    "root_id": root_id,
-                }
-            )
-
-        except Exception as e:
-            logger.error(e, exc_info=True)
-            raise Exception(e)
-
-    # !help command function
-    def help(self) -> str:
-        help_info = (
-            "!gpt [content], generate response without context conversation\n"
-            + "!chat [content], chat with context conversation\n"
-            + "!pic [prompt], Image generation with DALL·E or LocalAI or stable-diffusion-webui\n"  # noqa: E501
-            + "!new, start a new conversation\n"
-            + "!help, help message"
-        )
-        return help_info

src/imagegen.py

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

src/main.py

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

v3.py

@@ -1,26 +1,15 @@
 """
-Code derived from https://github.com/acheong08/ChatGPT/blob/main/src/revChatGPT/V3.py
-A simple wrapper for the official ChatGPT API
+Code derived from: https://github.com/acheong08/ChatGPT/blob/main/src/revChatGPT/V3.py
 """
+
 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
@@ -28,48 +17,29 @@ class Chatbot:
 
     def __init__(
         self,
-        aclient: httpx.AsyncClient,
         api_key: str,
-        api_url: str = None,
-        engine: str = None,
+        engine: str = os.environ.get("GPT_ENGINE") or "gpt-3.5-turbo",
+        proxy: str = None,
         timeout: float = None,
         max_tokens: int = None,
-        temperature: float = 0.8,
+        temperature: float = 0.5,
         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,
+        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 or "gpt-3.5-turbo"
+        self.engine: str = engine
         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.system_prompt: str = system_prompt
         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
+            31000 if engine == "gpt-4-32k" else 7000 if engine == "gpt-4" 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.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
@@ -77,8 +47,31 @@ 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
+        )
 
-        self.aclient = aclient
+        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": [
@@ -89,9 +82,6 @@ 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,
@@ -117,26 +107,30 @@ 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
         """
-        _engine = self.engine
-        if self.engine not in ENGINES:
-            # use gpt-3.5-turbo to caculate token
-            _engine = "gpt-3.5-turbo"
+        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(_engine)
+        encoding = tiktoken.encoding_for_model(self.engine)
 
         num_tokens = 0
         for message in self.conversation[convo_id]:
             # every message follows <im_start>{role/name}\n{content}<im_end>\n
             num_tokens += 5
             for key, value in message.items():
-                if value:
-                    num_tokens += len(encoding.encode(value))
+                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
@@ -148,15 +142,13 @@ class Chatbot:
         """
         return self.max_tokens - self.get_token_count(convo_id)
 
-    async def ask_stream_async(
+    def ask_stream(
         self,
         prompt: str,
         role: str = "user",
         convo_id: str = "default",
-        model: str = None,
-        pass_history: bool = True,
         **kwargs,
-    ) -> AsyncGenerator[str, None]:
+    ):
         """
         Ask a question
         """
@@ -166,13 +158,12 @@ class Chatbot:
         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,
+        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": model or self.engine,
-                "messages": self.conversation[convo_id] if pass_history else [prompt],
+                "model": self.engine,
+                "messages": self.conversation[convo_id],
                 "stream": True,
                 # kwargs
                 "temperature": kwargs.get("temperature", self.temperature),
@@ -187,18 +178,79 @@ class Chatbot:
                 ),
                 "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),
+                "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()
-                raise Exception(
-                    f"{response.status_code} {response.reason_phrase} {response.text}",
-                )
 
             response_role: str = ""
             full_response: str = ""
@@ -211,8 +263,6 @@ 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
@@ -232,8 +282,6 @@ class Chatbot:
         prompt: str,
         role: str = "user",
         convo_id: str = "default",
-        model: str = None,
-        pass_history: bool = True,
         **kwargs,
     ) -> str:
         """
@@ -243,59 +291,28 @@ 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
 
-    async def ask_async_v2(
+    def ask(
         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
+        """
+        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:
@@ -305,40 +322,3 @@ 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"]