Add chatgpt bot
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catch-all/06_bots_telegram/08_chatgpt_bot/.dockerignore
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catch-all/06_bots_telegram/08_chatgpt_bot/.dockerignore
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mongodb
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# Byte-compiled / optimized / DLL files
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__pycache__/
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*.py[cod]
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*$py.class
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*.so
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# Distribution / packaging
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wheels/
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share/python-wheels/
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*.egg-info/
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.installed.cfg
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*.egg
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MANIFEST
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# PyInstaller
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# Usually these files are written by a python script from a template
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# before PyInstaller builds the exe, so as to inject date/other infos into it.
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*.manifest
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*.spec
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# Installer logs
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pip-log.txt
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pip-delete-this-directory.txt
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# Unit test / coverage reports
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htmlcov/
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.tox/
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.nox/
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.coverage
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.coverage.*
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.cache
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nosetests.xml
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coverage.xml
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*.cover
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*.py,cover
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.hypothesis/
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.pytest_cache/
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# Translations
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*.mo
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*.pot
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# Django stuff:
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*.log
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local_settings.py
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db.sqlite3
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db.sqlite3-journal
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# Flask stuff:
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instance/
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# Scrapy stuff:
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.scrapy
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# Sphinx documentation
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docs/_build/
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# PyBuilder
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target/
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# Jupyter Notebook
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.ipynb_checkpoints
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# IPython
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profile_default/
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ipython_config.py
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# pyenv
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.python-version
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# pipenv
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# According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control.
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# However, in case of collaboration, if having platform-specific dependencies or dependencies
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# having no cross-platform support, pipenv may install dependencies that don't work, or not
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# install all needed dependencies.
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#Pipfile.lock
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# PEP 582; used by e.g. github.com/David-OConnor/pyflow
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__pypackages__/
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# Celery stuff
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celerybeat-schedule
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celerybeat.pid
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# SageMath parsed files
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*.sage.py
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# Environments
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.env
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.venv
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env/
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venv/
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ENV/
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env.bak/
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venv.bak/
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# Spyder project settings
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.spyderproject
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.spyproject
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# Rope project settings
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.ropeproject
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# mkdocs documentation
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/site
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# mypy
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.mypy_cache/
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.dmypy.json
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dmypy.json
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# Pyre type checker
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.pyre/
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# Custom
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config/config.yml
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config/config.env
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docker-compose.dev.yml
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mongodb/
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23
catch-all/06_bots_telegram/08_chatgpt_bot/Dockerfile
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catch-all/06_bots_telegram/08_chatgpt_bot/Dockerfile
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FROM python:3.8-slim
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RUN \
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set -eux; \
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apt-get update; \
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DEBIAN_FRONTEND="noninteractive" apt-get install -y --no-install-recommends \
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python3-pip \
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build-essential \
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python3-venv \
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ffmpeg \
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git \
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; \
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rm -rf /var/lib/apt/lists/*
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RUN pip3 install -U pip && pip3 install -U wheel && pip3 install -U setuptools==59.5.0
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COPY ./requirements.txt /tmp/requirements.txt
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RUN pip3 install -r /tmp/requirements.txt && rm -r /tmp/requirements.txt
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COPY . /code
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WORKDIR /code
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CMD ["bash"]
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58
catch-all/06_bots_telegram/08_chatgpt_bot/README.md
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# ChatGPT Telegram Bot: **GPT-4. Rápido. Sin límites diarios. Modos de chat especiales**
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> Repositorio original: https://github.com/father-bot/chatgpt_telegram_bot
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Todos amamos [chat.openai.com](https://chat.openai.com), pero... Es TERRIBLEMENTE lento, tiene límites diarios, y solo es accesible a través de una interfaz web arcaica.
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Este repositorio es ChatGPT recreado como un Bot de Telegram. **Y funciona genial.**
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Puedes desplegar tu propio bot.
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## Características
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- Respuestas con baja latencia (usualmente toma entre 3-5 segundos)
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- Sin límites de solicitudes
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- Transmisión de mensajes (mira la demo)
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- Soporte para GPT-4 y GPT-4 Turbo
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- Soporte para GPT-4 Vision
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- Soporte para chat en grupo (/help_group_chat para obtener instrucciones)
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- DALLE 2 (elige el modo 👩🎨 Artista para generar imágenes)
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- Reconocimiento de mensajes de voz
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- Resaltado de código
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- 15 modos de chat especiales: 👩🏼🎓 Asistente, 👩🏼💻 Asistente de Código, 👩🎨 Artista, 🧠 Psicólogo, 🚀 Elon Musk, entre otros. Puedes crear fácilmente tus propios modos de chat editando `config/chat_modes.yml`
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- Soporte para [ChatGPT API](https://platform.openai.com/docs/guides/chat/introduction)
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- Lista de usuarios de Telegram permitidos
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- Seguimiento del balance $ gastado en la API de OpenAI
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<p align="center">
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<img src="https://media.giphy.com/media/v1.Y2lkPTc5MGI3NjExYmM2ZWVjY2M4NWQ3ZThkYmQ3MDhmMTEzZGUwOGFmOThlMDIzZGM4YiZjdD1n/unx907h7GSiLAugzVX/giphy.gif" />
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</p>
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---
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## Comandos del Bot
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- `/retry` – Regenerar la última respuesta del bot
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- `/new` – Iniciar nuevo diálogo
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- `/mode` – Seleccionar modo de chat
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- `/balance` – Mostrar balance
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- `/settings` – Mostrar configuraciones
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- `/help` – Mostrar ayuda
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## Configuración
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1. Obtén tu clave de [OpenAI API](https://openai.com/api/)
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2. Obtén tu token de bot de Telegram desde [@BotFather](https://t.me/BotFather)
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3. Edita `config/config.example.yml` para establecer tus tokens y ejecuta los 2 comandos a continuación (*si eres un usuario avanzado, también puedes editar* `config/config.example.env`):
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```bash
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mv config/config.example.yml config/config.yml
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mv config/config.example.env config/config.env
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```
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4. 🔥 Y ahora **ejecuta**:
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```bash
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docker-compose --env-file config/config.env up --build
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```
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## Referencias
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1. [*Construye ChatGPT desde GPT-3*](https://learnprompting.org/docs/applied_prompting/build_chatgpt)
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catch-all/06_bots_telegram/08_chatgpt_bot/bot/bot.py
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import io
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import logging
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import asyncio
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import traceback
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import html
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import json
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from datetime import datetime
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import openai
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import telegram
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from telegram import (
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Update,
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User,
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InlineKeyboardButton,
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InlineKeyboardMarkup,
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BotCommand
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)
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from telegram.ext import (
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Application,
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ApplicationBuilder,
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CallbackContext,
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CommandHandler,
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MessageHandler,
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CallbackQueryHandler,
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AIORateLimiter,
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filters
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)
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from telegram.constants import ParseMode, ChatAction
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import config
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import database
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import openai_utils
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import base64
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# setup
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db = database.Database()
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logger = logging.getLogger(__name__)
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user_semaphores = {}
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user_tasks = {}
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HELP_MESSAGE = """Commands:
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⚪ /retry – Regenerate last bot answer
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⚪ /new – Start new dialog
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⚪ /mode – Select chat mode
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⚪ /settings – Show settings
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⚪ /balance – Show balance
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⚪ /help – Show help
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🎨 Generate images from text prompts in <b>👩🎨 Artist</b> /mode
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👥 Add bot to <b>group chat</b>: /help_group_chat
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🎤 You can send <b>Voice Messages</b> instead of text
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"""
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HELP_GROUP_CHAT_MESSAGE = """You can add bot to any <b>group chat</b> to help and entertain its participants!
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Instructions (see <b>video</b> below):
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1. Add the bot to the group chat
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2. Make it an <b>admin</b>, so that it can see messages (all other rights can be restricted)
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3. You're awesome!
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To get a reply from the bot in the chat – @ <b>tag</b> it or <b>reply</b> to its message.
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For example: "{bot_username} write a poem about Telegram"
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"""
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def split_text_into_chunks(text, chunk_size):
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for i in range(0, len(text), chunk_size):
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yield text[i:i + chunk_size]
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async def register_user_if_not_exists(update: Update, context: CallbackContext, user: User):
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if not db.check_if_user_exists(user.id):
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db.add_new_user(
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user.id,
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update.message.chat_id,
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username=user.username,
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first_name=user.first_name,
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last_name= user.last_name
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)
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db.start_new_dialog(user.id)
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if db.get_user_attribute(user.id, "current_dialog_id") is None:
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db.start_new_dialog(user.id)
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if user.id not in user_semaphores:
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user_semaphores[user.id] = asyncio.Semaphore(1)
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if db.get_user_attribute(user.id, "current_model") is None:
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db.set_user_attribute(user.id, "current_model", config.models["available_text_models"][0])
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# back compatibility for n_used_tokens field
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n_used_tokens = db.get_user_attribute(user.id, "n_used_tokens")
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if isinstance(n_used_tokens, int) or isinstance(n_used_tokens, float): # old format
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new_n_used_tokens = {
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"gpt-3.5-turbo": {
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"n_input_tokens": 0,
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"n_output_tokens": n_used_tokens
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}
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}
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db.set_user_attribute(user.id, "n_used_tokens", new_n_used_tokens)
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# voice message transcription
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if db.get_user_attribute(user.id, "n_transcribed_seconds") is None:
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db.set_user_attribute(user.id, "n_transcribed_seconds", 0.0)
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# image generation
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if db.get_user_attribute(user.id, "n_generated_images") is None:
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db.set_user_attribute(user.id, "n_generated_images", 0)
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async def is_bot_mentioned(update: Update, context: CallbackContext):
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try:
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message = update.message
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if message.chat.type == "private":
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return True
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if message.text is not None and ("@" + context.bot.username) in message.text:
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return True
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if message.reply_to_message is not None:
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if message.reply_to_message.from_user.id == context.bot.id:
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return True
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except:
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return True
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else:
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return False
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async def start_handle(update: Update, context: CallbackContext):
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await register_user_if_not_exists(update, context, update.message.from_user)
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user_id = update.message.from_user.id
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db.set_user_attribute(user_id, "last_interaction", datetime.now())
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db.start_new_dialog(user_id)
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reply_text = "Hi! I'm <b>ChatGPT</b> bot implemented with OpenAI API 🤖\n\n"
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reply_text += HELP_MESSAGE
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await update.message.reply_text(reply_text, parse_mode=ParseMode.HTML)
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await show_chat_modes_handle(update, context)
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async def help_handle(update: Update, context: CallbackContext):
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await register_user_if_not_exists(update, context, update.message.from_user)
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user_id = update.message.from_user.id
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db.set_user_attribute(user_id, "last_interaction", datetime.now())
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await update.message.reply_text(HELP_MESSAGE, parse_mode=ParseMode.HTML)
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async def help_group_chat_handle(update: Update, context: CallbackContext):
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await register_user_if_not_exists(update, context, update.message.from_user)
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user_id = update.message.from_user.id
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db.set_user_attribute(user_id, "last_interaction", datetime.now())
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text = HELP_GROUP_CHAT_MESSAGE.format(bot_username="@" + context.bot.username)
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await update.message.reply_text(text, parse_mode=ParseMode.HTML)
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await update.message.reply_video(config.help_group_chat_video_path)
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async def retry_handle(update: Update, context: CallbackContext):
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await register_user_if_not_exists(update, context, update.message.from_user)
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if await is_previous_message_not_answered_yet(update, context): return
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user_id = update.message.from_user.id
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db.set_user_attribute(user_id, "last_interaction", datetime.now())
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dialog_messages = db.get_dialog_messages(user_id, dialog_id=None)
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if len(dialog_messages) == 0:
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await update.message.reply_text("No message to retry 🤷♂️")
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return
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last_dialog_message = dialog_messages.pop()
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db.set_dialog_messages(user_id, dialog_messages, dialog_id=None) # last message was removed from the context
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await message_handle(update, context, message=last_dialog_message["user"], use_new_dialog_timeout=False)
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async def _vision_message_handle_fn(
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update: Update, context: CallbackContext, use_new_dialog_timeout: bool = True
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):
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logger.info('_vision_message_handle_fn')
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user_id = update.message.from_user.id
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current_model = db.get_user_attribute(user_id, "current_model")
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if current_model != "gpt-4-vision-preview" and current_model != "gpt-4o":
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await update.message.reply_text(
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"🥲 Images processing is only available for <b>gpt-4-vision-preview</b> and <b>gpt-4o</b> model. Please change your settings in /settings",
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parse_mode=ParseMode.HTML,
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)
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return
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chat_mode = db.get_user_attribute(user_id, "current_chat_mode")
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# new dialog timeout
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if use_new_dialog_timeout:
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if (datetime.now() - db.get_user_attribute(user_id, "last_interaction")).seconds > config.new_dialog_timeout and len(db.get_dialog_messages(user_id)) > 0:
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db.start_new_dialog(user_id)
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await update.message.reply_text(f"Starting new dialog due to timeout (<b>{config.chat_modes[chat_mode]['name']}</b> mode) ✅", parse_mode=ParseMode.HTML)
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db.set_user_attribute(user_id, "last_interaction", datetime.now())
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buf = None
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if update.message.effective_attachment:
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photo = update.message.effective_attachment[-1]
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photo_file = await context.bot.get_file(photo.file_id)
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# store file in memory, not on disk
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buf = io.BytesIO()
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await photo_file.download_to_memory(buf)
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buf.name = "image.jpg" # file extension is required
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buf.seek(0) # move cursor to the beginning of the buffer
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# in case of CancelledError
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n_input_tokens, n_output_tokens = 0, 0
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try:
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# send placeholder message to user
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placeholder_message = await update.message.reply_text("...")
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message = update.message.caption or update.message.text or ''
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# send typing action
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await update.message.chat.send_action(action="typing")
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dialog_messages = db.get_dialog_messages(user_id, dialog_id=None)
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parse_mode = {"html": ParseMode.HTML, "markdown": ParseMode.MARKDOWN}[
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config.chat_modes[chat_mode]["parse_mode"]
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]
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chatgpt_instance = openai_utils.ChatGPT(model=current_model)
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if config.enable_message_streaming:
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gen = chatgpt_instance.send_vision_message_stream(
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message,
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dialog_messages=dialog_messages,
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image_buffer=buf,
|
||||
chat_mode=chat_mode,
|
||||
)
|
||||
else:
|
||||
(
|
||||
answer,
|
||||
(n_input_tokens, n_output_tokens),
|
||||
n_first_dialog_messages_removed,
|
||||
) = await chatgpt_instance.send_vision_message(
|
||||
message,
|
||||
dialog_messages=dialog_messages,
|
||||
image_buffer=buf,
|
||||
chat_mode=chat_mode,
|
||||
)
|
||||
|
||||
async def fake_gen():
|
||||
yield "finished", answer, (
|
||||
n_input_tokens,
|
||||
n_output_tokens,
|
||||
), n_first_dialog_messages_removed
|
||||
|
||||
gen = fake_gen()
|
||||
|
||||
prev_answer = ""
|
||||
async for gen_item in gen:
|
||||
(
|
||||
status,
|
||||
answer,
|
||||
(n_input_tokens, n_output_tokens),
|
||||
n_first_dialog_messages_removed,
|
||||
) = gen_item
|
||||
|
||||
answer = answer[:4096] # telegram message limit
|
||||
|
||||
# update only when 100 new symbols are ready
|
||||
if abs(len(answer) - len(prev_answer)) < 100 and status != "finished":
|
||||
continue
|
||||
|
||||
try:
|
||||
await context.bot.edit_message_text(
|
||||
answer,
|
||||
chat_id=placeholder_message.chat_id,
|
||||
message_id=placeholder_message.message_id,
|
||||
parse_mode=parse_mode,
|
||||
)
|
||||
except telegram.error.BadRequest as e:
|
||||
if str(e).startswith("Message is not modified"):
|
||||
continue
|
||||
else:
|
||||
await context.bot.edit_message_text(
|
||||
answer,
|
||||
chat_id=placeholder_message.chat_id,
|
||||
message_id=placeholder_message.message_id,
|
||||
)
|
||||
|
||||
await asyncio.sleep(0.01) # wait a bit to avoid flooding
|
||||
|
||||
prev_answer = answer
|
||||
|
||||
# update user data
|
||||
if buf is not None:
|
||||
base_image = base64.b64encode(buf.getvalue()).decode("utf-8")
|
||||
new_dialog_message = {"user": [
|
||||
{
|
||||
"type": "text",
|
||||
"text": message,
|
||||
},
|
||||
{
|
||||
"type": "image",
|
||||
"image": base_image,
|
||||
}
|
||||
]
|
||||
, "bot": answer, "date": datetime.now()}
|
||||
else:
|
||||
new_dialog_message = {"user": [{"type": "text", "text": message}], "bot": answer, "date": datetime.now()}
|
||||
|
||||
db.set_dialog_messages(
|
||||
user_id,
|
||||
db.get_dialog_messages(user_id, dialog_id=None) + [new_dialog_message],
|
||||
dialog_id=None
|
||||
)
|
||||
|
||||
db.update_n_used_tokens(user_id, current_model, n_input_tokens, n_output_tokens)
|
||||
|
||||
except asyncio.CancelledError:
|
||||
# note: intermediate token updates only work when enable_message_streaming=True (config.yml)
|
||||
db.update_n_used_tokens(user_id, current_model, n_input_tokens, n_output_tokens)
|
||||
raise
|
||||
|
||||
except Exception as e:
|
||||
error_text = f"Something went wrong during completion. Reason: {e}"
|
||||
logger.error(error_text)
|
||||
await update.message.reply_text(error_text)
|
||||
return
|
||||
|
||||
async def unsupport_message_handle(update: Update, context: CallbackContext, message=None):
|
||||
error_text = f"I don't know how to read files or videos. Send the picture in normal mode (Quick Mode)."
|
||||
logger.error(error_text)
|
||||
await update.message.reply_text(error_text)
|
||||
return
|
||||
|
||||
async def message_handle(update: Update, context: CallbackContext, message=None, use_new_dialog_timeout=True):
|
||||
# check if bot was mentioned (for group chats)
|
||||
if not await is_bot_mentioned(update, context):
|
||||
return
|
||||
|
||||
# check if message is edited
|
||||
if update.edited_message is not None:
|
||||
await edited_message_handle(update, context)
|
||||
return
|
||||
|
||||
_message = message or update.message.text
|
||||
|
||||
# remove bot mention (in group chats)
|
||||
if update.message.chat.type != "private":
|
||||
_message = _message.replace("@" + context.bot.username, "").strip()
|
||||
|
||||
await register_user_if_not_exists(update, context, update.message.from_user)
|
||||
if await is_previous_message_not_answered_yet(update, context): return
|
||||
|
||||
user_id = update.message.from_user.id
|
||||
chat_mode = db.get_user_attribute(user_id, "current_chat_mode")
|
||||
|
||||
if chat_mode == "artist":
|
||||
await generate_image_handle(update, context, message=message)
|
||||
return
|
||||
|
||||
current_model = db.get_user_attribute(user_id, "current_model")
|
||||
|
||||
async def message_handle_fn():
|
||||
# new dialog timeout
|
||||
if use_new_dialog_timeout:
|
||||
if (datetime.now() - db.get_user_attribute(user_id, "last_interaction")).seconds > config.new_dialog_timeout and len(db.get_dialog_messages(user_id)) > 0:
|
||||
db.start_new_dialog(user_id)
|
||||
await update.message.reply_text(f"Starting new dialog due to timeout (<b>{config.chat_modes[chat_mode]['name']}</b> mode) ✅", parse_mode=ParseMode.HTML)
|
||||
db.set_user_attribute(user_id, "last_interaction", datetime.now())
|
||||
|
||||
# in case of CancelledError
|
||||
n_input_tokens, n_output_tokens = 0, 0
|
||||
|
||||
try:
|
||||
# send placeholder message to user
|
||||
placeholder_message = await update.message.reply_text("...")
|
||||
|
||||
# send typing action
|
||||
await update.message.chat.send_action(action="typing")
|
||||
|
||||
if _message is None or len(_message) == 0:
|
||||
await update.message.reply_text("🥲 You sent <b>empty message</b>. Please, try again!", parse_mode=ParseMode.HTML)
|
||||
return
|
||||
|
||||
dialog_messages = db.get_dialog_messages(user_id, dialog_id=None)
|
||||
parse_mode = {
|
||||
"html": ParseMode.HTML,
|
||||
"markdown": ParseMode.MARKDOWN
|
||||
}[config.chat_modes[chat_mode]["parse_mode"]]
|
||||
|
||||
chatgpt_instance = openai_utils.ChatGPT(model=current_model)
|
||||
if config.enable_message_streaming:
|
||||
gen = chatgpt_instance.send_message_stream(_message, dialog_messages=dialog_messages, chat_mode=chat_mode)
|
||||
else:
|
||||
answer, (n_input_tokens, n_output_tokens), n_first_dialog_messages_removed = await chatgpt_instance.send_message(
|
||||
_message,
|
||||
dialog_messages=dialog_messages,
|
||||
chat_mode=chat_mode
|
||||
)
|
||||
|
||||
async def fake_gen():
|
||||
yield "finished", answer, (n_input_tokens, n_output_tokens), n_first_dialog_messages_removed
|
||||
|
||||
gen = fake_gen()
|
||||
|
||||
prev_answer = ""
|
||||
|
||||
async for gen_item in gen:
|
||||
status, answer, (n_input_tokens, n_output_tokens), n_first_dialog_messages_removed = gen_item
|
||||
|
||||
answer = answer[:4096] # telegram message limit
|
||||
|
||||
# update only when 100 new symbols are ready
|
||||
if abs(len(answer) - len(prev_answer)) < 100 and status != "finished":
|
||||
continue
|
||||
|
||||
try:
|
||||
await context.bot.edit_message_text(answer, chat_id=placeholder_message.chat_id, message_id=placeholder_message.message_id, parse_mode=parse_mode)
|
||||
except telegram.error.BadRequest as e:
|
||||
if str(e).startswith("Message is not modified"):
|
||||
continue
|
||||
else:
|
||||
await context.bot.edit_message_text(answer, chat_id=placeholder_message.chat_id, message_id=placeholder_message.message_id)
|
||||
|
||||
await asyncio.sleep(0.01) # wait a bit to avoid flooding
|
||||
|
||||
prev_answer = answer
|
||||
|
||||
# update user data
|
||||
new_dialog_message = {"user": [{"type": "text", "text": _message}], "bot": answer, "date": datetime.now()}
|
||||
|
||||
db.set_dialog_messages(
|
||||
user_id,
|
||||
db.get_dialog_messages(user_id, dialog_id=None) + [new_dialog_message],
|
||||
dialog_id=None
|
||||
)
|
||||
|
||||
db.update_n_used_tokens(user_id, current_model, n_input_tokens, n_output_tokens)
|
||||
|
||||
except asyncio.CancelledError:
|
||||
# note: intermediate token updates only work when enable_message_streaming=True (config.yml)
|
||||
db.update_n_used_tokens(user_id, current_model, n_input_tokens, n_output_tokens)
|
||||
raise
|
||||
|
||||
except Exception as e:
|
||||
error_text = f"Something went wrong during completion. Reason: {e}"
|
||||
logger.error(error_text)
|
||||
await update.message.reply_text(error_text)
|
||||
return
|
||||
|
||||
# send message if some messages were removed from the context
|
||||
if n_first_dialog_messages_removed > 0:
|
||||
if n_first_dialog_messages_removed == 1:
|
||||
text = "✍️ <i>Note:</i> Your current dialog is too long, so your <b>first message</b> was removed from the context.\n Send /new command to start new dialog"
|
||||
else:
|
||||
text = f"✍️ <i>Note:</i> Your current dialog is too long, so <b>{n_first_dialog_messages_removed} first messages</b> were removed from the context.\n Send /new command to start new dialog"
|
||||
await update.message.reply_text(text, parse_mode=ParseMode.HTML)
|
||||
|
||||
async with user_semaphores[user_id]:
|
||||
if current_model == "gpt-4-vision-preview" or current_model == "gpt-4o" or update.message.photo is not None and len(update.message.photo) > 0:
|
||||
|
||||
logger.error(current_model)
|
||||
# What is this? ^^^
|
||||
|
||||
if current_model != "gpt-4o" and current_model != "gpt-4-vision-preview":
|
||||
current_model = "gpt-4o"
|
||||
db.set_user_attribute(user_id, "current_model", "gpt-4o")
|
||||
task = asyncio.create_task(
|
||||
_vision_message_handle_fn(update, context, use_new_dialog_timeout=use_new_dialog_timeout)
|
||||
)
|
||||
else:
|
||||
task = asyncio.create_task(
|
||||
message_handle_fn()
|
||||
)
|
||||
|
||||
user_tasks[user_id] = task
|
||||
|
||||
try:
|
||||
await task
|
||||
except asyncio.CancelledError:
|
||||
await update.message.reply_text("✅ Canceled", parse_mode=ParseMode.HTML)
|
||||
else:
|
||||
pass
|
||||
finally:
|
||||
if user_id in user_tasks:
|
||||
del user_tasks[user_id]
|
||||
|
||||
|
||||
async def is_previous_message_not_answered_yet(update: Update, context: CallbackContext):
|
||||
await register_user_if_not_exists(update, context, update.message.from_user)
|
||||
|
||||
user_id = update.message.from_user.id
|
||||
if user_semaphores[user_id].locked():
|
||||
text = "⏳ Please <b>wait</b> for a reply to the previous message\n"
|
||||
text += "Or you can /cancel it"
|
||||
await update.message.reply_text(text, reply_to_message_id=update.message.id, parse_mode=ParseMode.HTML)
|
||||
return True
|
||||
else:
|
||||
return False
|
||||
|
||||
|
||||
async def voice_message_handle(update: Update, context: CallbackContext):
|
||||
# check if bot was mentioned (for group chats)
|
||||
if not await is_bot_mentioned(update, context):
|
||||
return
|
||||
|
||||
await register_user_if_not_exists(update, context, update.message.from_user)
|
||||
if await is_previous_message_not_answered_yet(update, context): return
|
||||
|
||||
user_id = update.message.from_user.id
|
||||
db.set_user_attribute(user_id, "last_interaction", datetime.now())
|
||||
|
||||
voice = update.message.voice
|
||||
voice_file = await context.bot.get_file(voice.file_id)
|
||||
|
||||
# store file in memory, not on disk
|
||||
buf = io.BytesIO()
|
||||
await voice_file.download_to_memory(buf)
|
||||
buf.name = "voice.oga" # file extension is required
|
||||
buf.seek(0) # move cursor to the beginning of the buffer
|
||||
|
||||
transcribed_text = await openai_utils.transcribe_audio(buf)
|
||||
text = f"🎤: <i>{transcribed_text}</i>"
|
||||
await update.message.reply_text(text, parse_mode=ParseMode.HTML)
|
||||
|
||||
# update n_transcribed_seconds
|
||||
db.set_user_attribute(user_id, "n_transcribed_seconds", voice.duration + db.get_user_attribute(user_id, "n_transcribed_seconds"))
|
||||
|
||||
await message_handle(update, context, message=transcribed_text)
|
||||
|
||||
|
||||
async def generate_image_handle(update: Update, context: CallbackContext, message=None):
|
||||
await register_user_if_not_exists(update, context, update.message.from_user)
|
||||
if await is_previous_message_not_answered_yet(update, context): return
|
||||
|
||||
user_id = update.message.from_user.id
|
||||
db.set_user_attribute(user_id, "last_interaction", datetime.now())
|
||||
|
||||
await update.message.chat.send_action(action="upload_photo")
|
||||
|
||||
message = message or update.message.text
|
||||
|
||||
try:
|
||||
image_urls = await openai_utils.generate_images(message, n_images=config.return_n_generated_images, size=config.image_size)
|
||||
except openai.error.InvalidRequestError as e:
|
||||
if str(e).startswith("Your request was rejected as a result of our safety system"):
|
||||
text = "🥲 Your request <b>doesn't comply</b> with OpenAI's usage policies.\nWhat did you write there, huh?"
|
||||
await update.message.reply_text(text, parse_mode=ParseMode.HTML)
|
||||
return
|
||||
else:
|
||||
raise
|
||||
|
||||
# token usage
|
||||
db.set_user_attribute(user_id, "n_generated_images", config.return_n_generated_images + db.get_user_attribute(user_id, "n_generated_images"))
|
||||
|
||||
for i, image_url in enumerate(image_urls):
|
||||
await update.message.chat.send_action(action="upload_photo")
|
||||
await update.message.reply_photo(image_url, parse_mode=ParseMode.HTML)
|
||||
|
||||
|
||||
async def new_dialog_handle(update: Update, context: CallbackContext):
|
||||
await register_user_if_not_exists(update, context, update.message.from_user)
|
||||
if await is_previous_message_not_answered_yet(update, context): return
|
||||
|
||||
user_id = update.message.from_user.id
|
||||
db.set_user_attribute(user_id, "last_interaction", datetime.now())
|
||||
db.set_user_attribute(user_id, "current_model", "gpt-3.5-turbo")
|
||||
|
||||
db.start_new_dialog(user_id)
|
||||
await update.message.reply_text("Starting new dialog ✅")
|
||||
|
||||
chat_mode = db.get_user_attribute(user_id, "current_chat_mode")
|
||||
await update.message.reply_text(f"{config.chat_modes[chat_mode]['welcome_message']}", parse_mode=ParseMode.HTML)
|
||||
|
||||
|
||||
async def cancel_handle(update: Update, context: CallbackContext):
|
||||
await register_user_if_not_exists(update, context, update.message.from_user)
|
||||
|
||||
user_id = update.message.from_user.id
|
||||
db.set_user_attribute(user_id, "last_interaction", datetime.now())
|
||||
|
||||
if user_id in user_tasks:
|
||||
task = user_tasks[user_id]
|
||||
task.cancel()
|
||||
else:
|
||||
await update.message.reply_text("<i>Nothing to cancel...</i>", parse_mode=ParseMode.HTML)
|
||||
|
||||
|
||||
def get_chat_mode_menu(page_index: int):
|
||||
n_chat_modes_per_page = config.n_chat_modes_per_page
|
||||
text = f"Select <b>chat mode</b> ({len(config.chat_modes)} modes available):"
|
||||
|
||||
# buttons
|
||||
chat_mode_keys = list(config.chat_modes.keys())
|
||||
page_chat_mode_keys = chat_mode_keys[page_index * n_chat_modes_per_page:(page_index + 1) * n_chat_modes_per_page]
|
||||
|
||||
keyboard = []
|
||||
for chat_mode_key in page_chat_mode_keys:
|
||||
name = config.chat_modes[chat_mode_key]["name"]
|
||||
keyboard.append([InlineKeyboardButton(name, callback_data=f"set_chat_mode|{chat_mode_key}")])
|
||||
|
||||
# pagination
|
||||
if len(chat_mode_keys) > n_chat_modes_per_page:
|
||||
is_first_page = (page_index == 0)
|
||||
is_last_page = ((page_index + 1) * n_chat_modes_per_page >= len(chat_mode_keys))
|
||||
|
||||
if is_first_page:
|
||||
keyboard.append([
|
||||
InlineKeyboardButton("»", callback_data=f"show_chat_modes|{page_index + 1}")
|
||||
])
|
||||
elif is_last_page:
|
||||
keyboard.append([
|
||||
InlineKeyboardButton("«", callback_data=f"show_chat_modes|{page_index - 1}"),
|
||||
])
|
||||
else:
|
||||
keyboard.append([
|
||||
InlineKeyboardButton("«", callback_data=f"show_chat_modes|{page_index - 1}"),
|
||||
InlineKeyboardButton("»", callback_data=f"show_chat_modes|{page_index + 1}")
|
||||
])
|
||||
|
||||
reply_markup = InlineKeyboardMarkup(keyboard)
|
||||
|
||||
return text, reply_markup
|
||||
|
||||
|
||||
async def show_chat_modes_handle(update: Update, context: CallbackContext):
|
||||
await register_user_if_not_exists(update, context, update.message.from_user)
|
||||
if await is_previous_message_not_answered_yet(update, context): return
|
||||
|
||||
user_id = update.message.from_user.id
|
||||
db.set_user_attribute(user_id, "last_interaction", datetime.now())
|
||||
|
||||
text, reply_markup = get_chat_mode_menu(0)
|
||||
await update.message.reply_text(text, reply_markup=reply_markup, parse_mode=ParseMode.HTML)
|
||||
|
||||
|
||||
async def show_chat_modes_callback_handle(update: Update, context: CallbackContext):
|
||||
await register_user_if_not_exists(update.callback_query, context, update.callback_query.from_user)
|
||||
if await is_previous_message_not_answered_yet(update.callback_query, context): return
|
||||
|
||||
user_id = update.callback_query.from_user.id
|
||||
db.set_user_attribute(user_id, "last_interaction", datetime.now())
|
||||
|
||||
query = update.callback_query
|
||||
await query.answer()
|
||||
|
||||
page_index = int(query.data.split("|")[1])
|
||||
if page_index < 0:
|
||||
return
|
||||
|
||||
text, reply_markup = get_chat_mode_menu(page_index)
|
||||
try:
|
||||
await query.edit_message_text(text, reply_markup=reply_markup, parse_mode=ParseMode.HTML)
|
||||
except telegram.error.BadRequest as e:
|
||||
if str(e).startswith("Message is not modified"):
|
||||
pass
|
||||
|
||||
|
||||
async def set_chat_mode_handle(update: Update, context: CallbackContext):
|
||||
await register_user_if_not_exists(update.callback_query, context, update.callback_query.from_user)
|
||||
user_id = update.callback_query.from_user.id
|
||||
|
||||
query = update.callback_query
|
||||
await query.answer()
|
||||
|
||||
chat_mode = query.data.split("|")[1]
|
||||
|
||||
db.set_user_attribute(user_id, "current_chat_mode", chat_mode)
|
||||
db.start_new_dialog(user_id)
|
||||
|
||||
await context.bot.send_message(
|
||||
update.callback_query.message.chat.id,
|
||||
f"{config.chat_modes[chat_mode]['welcome_message']}",
|
||||
parse_mode=ParseMode.HTML
|
||||
)
|
||||
|
||||
|
||||
def get_settings_menu(user_id: int):
|
||||
current_model = db.get_user_attribute(user_id, "current_model")
|
||||
text = config.models["info"][current_model]["description"]
|
||||
|
||||
text += "\n\n"
|
||||
score_dict = config.models["info"][current_model]["scores"]
|
||||
for score_key, score_value in score_dict.items():
|
||||
text += "🟢" * score_value + "⚪️" * (5 - score_value) + f" – {score_key}\n\n"
|
||||
|
||||
text += "\nSelect <b>model</b>:"
|
||||
|
||||
# buttons to choose models
|
||||
buttons = []
|
||||
for model_key in config.models["available_text_models"]:
|
||||
title = config.models["info"][model_key]["name"]
|
||||
if model_key == current_model:
|
||||
title = "✅ " + title
|
||||
|
||||
buttons.append(
|
||||
InlineKeyboardButton(title, callback_data=f"set_settings|{model_key}")
|
||||
)
|
||||
reply_markup = InlineKeyboardMarkup([buttons])
|
||||
|
||||
return text, reply_markup
|
||||
|
||||
|
||||
async def settings_handle(update: Update, context: CallbackContext):
|
||||
await register_user_if_not_exists(update, context, update.message.from_user)
|
||||
if await is_previous_message_not_answered_yet(update, context): return
|
||||
|
||||
user_id = update.message.from_user.id
|
||||
db.set_user_attribute(user_id, "last_interaction", datetime.now())
|
||||
|
||||
text, reply_markup = get_settings_menu(user_id)
|
||||
await update.message.reply_text(text, reply_markup=reply_markup, parse_mode=ParseMode.HTML)
|
||||
|
||||
|
||||
async def set_settings_handle(update: Update, context: CallbackContext):
|
||||
await register_user_if_not_exists(update.callback_query, context, update.callback_query.from_user)
|
||||
user_id = update.callback_query.from_user.id
|
||||
|
||||
query = update.callback_query
|
||||
await query.answer()
|
||||
|
||||
_, model_key = query.data.split("|")
|
||||
db.set_user_attribute(user_id, "current_model", model_key)
|
||||
db.start_new_dialog(user_id)
|
||||
|
||||
text, reply_markup = get_settings_menu(user_id)
|
||||
try:
|
||||
await query.edit_message_text(text, reply_markup=reply_markup, parse_mode=ParseMode.HTML)
|
||||
except telegram.error.BadRequest as e:
|
||||
if str(e).startswith("Message is not modified"):
|
||||
pass
|
||||
|
||||
|
||||
async def show_balance_handle(update: Update, context: CallbackContext):
|
||||
await register_user_if_not_exists(update, context, update.message.from_user)
|
||||
|
||||
user_id = update.message.from_user.id
|
||||
db.set_user_attribute(user_id, "last_interaction", datetime.now())
|
||||
|
||||
# count total usage statistics
|
||||
total_n_spent_dollars = 0
|
||||
total_n_used_tokens = 0
|
||||
|
||||
n_used_tokens_dict = db.get_user_attribute(user_id, "n_used_tokens")
|
||||
n_generated_images = db.get_user_attribute(user_id, "n_generated_images")
|
||||
n_transcribed_seconds = db.get_user_attribute(user_id, "n_transcribed_seconds")
|
||||
|
||||
details_text = "🏷️ Details:\n"
|
||||
for model_key in sorted(n_used_tokens_dict.keys()):
|
||||
n_input_tokens, n_output_tokens = n_used_tokens_dict[model_key]["n_input_tokens"], n_used_tokens_dict[model_key]["n_output_tokens"]
|
||||
total_n_used_tokens += n_input_tokens + n_output_tokens
|
||||
|
||||
n_input_spent_dollars = config.models["info"][model_key]["price_per_1000_input_tokens"] * (n_input_tokens / 1000)
|
||||
n_output_spent_dollars = config.models["info"][model_key]["price_per_1000_output_tokens"] * (n_output_tokens / 1000)
|
||||
total_n_spent_dollars += n_input_spent_dollars + n_output_spent_dollars
|
||||
|
||||
details_text += f"- {model_key}: <b>{n_input_spent_dollars + n_output_spent_dollars:.03f}$</b> / <b>{n_input_tokens + n_output_tokens} tokens</b>\n"
|
||||
|
||||
# image generation
|
||||
image_generation_n_spent_dollars = config.models["info"]["dalle-2"]["price_per_1_image"] * n_generated_images
|
||||
if n_generated_images != 0:
|
||||
details_text += f"- DALL·E 2 (image generation): <b>{image_generation_n_spent_dollars:.03f}$</b> / <b>{n_generated_images} generated images</b>\n"
|
||||
|
||||
total_n_spent_dollars += image_generation_n_spent_dollars
|
||||
|
||||
# voice recognition
|
||||
voice_recognition_n_spent_dollars = config.models["info"]["whisper"]["price_per_1_min"] * (n_transcribed_seconds / 60)
|
||||
if n_transcribed_seconds != 0:
|
||||
details_text += f"- Whisper (voice recognition): <b>{voice_recognition_n_spent_dollars:.03f}$</b> / <b>{n_transcribed_seconds:.01f} seconds</b>\n"
|
||||
|
||||
total_n_spent_dollars += voice_recognition_n_spent_dollars
|
||||
|
||||
|
||||
text = f"You spent <b>{total_n_spent_dollars:.03f}$</b>\n"
|
||||
text += f"You used <b>{total_n_used_tokens}</b> tokens\n\n"
|
||||
text += details_text
|
||||
|
||||
await update.message.reply_text(text, parse_mode=ParseMode.HTML)
|
||||
|
||||
|
||||
async def edited_message_handle(update: Update, context: CallbackContext):
|
||||
if update.edited_message.chat.type == "private":
|
||||
text = "🥲 Unfortunately, message <b>editing</b> is not supported"
|
||||
await update.edited_message.reply_text(text, parse_mode=ParseMode.HTML)
|
||||
|
||||
|
||||
async def error_handle(update: Update, context: CallbackContext) -> None:
|
||||
logger.error(msg="Exception while handling an update:", exc_info=context.error)
|
||||
|
||||
try:
|
||||
# collect error message
|
||||
tb_list = traceback.format_exception(None, context.error, context.error.__traceback__)
|
||||
tb_string = "".join(tb_list)
|
||||
update_str = update.to_dict() if isinstance(update, Update) else str(update)
|
||||
message = (
|
||||
f"An exception was raised while handling an update\n"
|
||||
f"<pre>update = {html.escape(json.dumps(update_str, indent=2, ensure_ascii=False))}"
|
||||
"</pre>\n\n"
|
||||
f"<pre>{html.escape(tb_string)}</pre>"
|
||||
)
|
||||
|
||||
# split text into multiple messages due to 4096 character limit
|
||||
for message_chunk in split_text_into_chunks(message, 4096):
|
||||
try:
|
||||
await context.bot.send_message(update.effective_chat.id, message_chunk, parse_mode=ParseMode.HTML)
|
||||
except telegram.error.BadRequest:
|
||||
# answer has invalid characters, so we send it without parse_mode
|
||||
await context.bot.send_message(update.effective_chat.id, message_chunk)
|
||||
except:
|
||||
await context.bot.send_message(update.effective_chat.id, "Some error in error handler")
|
||||
|
||||
async def post_init(application: Application):
|
||||
await application.bot.set_my_commands([
|
||||
BotCommand("/new", "Start new dialog"),
|
||||
BotCommand("/mode", "Select chat mode"),
|
||||
BotCommand("/retry", "Re-generate response for previous query"),
|
||||
BotCommand("/balance", "Show balance"),
|
||||
BotCommand("/settings", "Show settings"),
|
||||
BotCommand("/help", "Show help message"),
|
||||
])
|
||||
|
||||
def run_bot() -> None:
|
||||
application = (
|
||||
ApplicationBuilder()
|
||||
.token(config.telegram_token)
|
||||
.concurrent_updates(True)
|
||||
.rate_limiter(AIORateLimiter(max_retries=5))
|
||||
.http_version("1.1")
|
||||
.get_updates_http_version("1.1")
|
||||
.post_init(post_init)
|
||||
.build()
|
||||
)
|
||||
|
||||
# add handlers
|
||||
user_filter = filters.ALL
|
||||
if len(config.allowed_telegram_usernames) > 0:
|
||||
usernames = [x for x in config.allowed_telegram_usernames if isinstance(x, str)]
|
||||
any_ids = [x for x in config.allowed_telegram_usernames if isinstance(x, int)]
|
||||
user_ids = [x for x in any_ids if x > 0]
|
||||
group_ids = [x for x in any_ids if x < 0]
|
||||
user_filter = filters.User(username=usernames) | filters.User(user_id=user_ids) | filters.Chat(chat_id=group_ids)
|
||||
|
||||
application.add_handler(CommandHandler("start", start_handle, filters=user_filter))
|
||||
application.add_handler(CommandHandler("help", help_handle, filters=user_filter))
|
||||
application.add_handler(CommandHandler("help_group_chat", help_group_chat_handle, filters=user_filter))
|
||||
|
||||
application.add_handler(MessageHandler(filters.TEXT & ~filters.COMMAND & user_filter, message_handle))
|
||||
application.add_handler(MessageHandler(filters.PHOTO & ~filters.COMMAND & user_filter, message_handle))
|
||||
application.add_handler(MessageHandler(filters.VIDEO & ~filters.COMMAND & user_filter, unsupport_message_handle))
|
||||
application.add_handler(MessageHandler(filters.Document.ALL & ~filters.COMMAND & user_filter, unsupport_message_handle))
|
||||
application.add_handler(CommandHandler("retry", retry_handle, filters=user_filter))
|
||||
application.add_handler(CommandHandler("new", new_dialog_handle, filters=user_filter))
|
||||
application.add_handler(CommandHandler("cancel", cancel_handle, filters=user_filter))
|
||||
|
||||
application.add_handler(MessageHandler(filters.VOICE & user_filter, voice_message_handle))
|
||||
|
||||
application.add_handler(CommandHandler("mode", show_chat_modes_handle, filters=user_filter))
|
||||
application.add_handler(CallbackQueryHandler(show_chat_modes_callback_handle, pattern="^show_chat_modes"))
|
||||
application.add_handler(CallbackQueryHandler(set_chat_mode_handle, pattern="^set_chat_mode"))
|
||||
|
||||
application.add_handler(CommandHandler("settings", settings_handle, filters=user_filter))
|
||||
application.add_handler(CallbackQueryHandler(set_settings_handle, pattern="^set_settings"))
|
||||
|
||||
application.add_handler(CommandHandler("balance", show_balance_handle, filters=user_filter))
|
||||
|
||||
application.add_error_handler(error_handle)
|
||||
|
||||
# start the bot
|
||||
application.run_polling()
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
run_bot()
|
35
catch-all/06_bots_telegram/08_chatgpt_bot/bot/config.py
Normal file
35
catch-all/06_bots_telegram/08_chatgpt_bot/bot/config.py
Normal file
@ -0,0 +1,35 @@
|
||||
import yaml
|
||||
import dotenv
|
||||
from pathlib import Path
|
||||
|
||||
config_dir = Path(__file__).parent.parent.resolve() / "config"
|
||||
|
||||
# load yaml config
|
||||
with open(config_dir / "config.yml", 'r') as f:
|
||||
config_yaml = yaml.safe_load(f)
|
||||
|
||||
# load .env config
|
||||
config_env = dotenv.dotenv_values(config_dir / "config.env")
|
||||
|
||||
# config parameters
|
||||
telegram_token = config_yaml["telegram_token"]
|
||||
openai_api_key = config_yaml["openai_api_key"]
|
||||
openai_api_base = config_yaml.get("openai_api_base", None)
|
||||
allowed_telegram_usernames = config_yaml["allowed_telegram_usernames"]
|
||||
new_dialog_timeout = config_yaml["new_dialog_timeout"]
|
||||
enable_message_streaming = config_yaml.get("enable_message_streaming", True)
|
||||
return_n_generated_images = config_yaml.get("return_n_generated_images", 1)
|
||||
image_size = config_yaml.get("image_size", "512x512")
|
||||
n_chat_modes_per_page = config_yaml.get("n_chat_modes_per_page", 5)
|
||||
mongodb_uri = f"mongodb://mongo:{config_env['MONGODB_PORT']}"
|
||||
|
||||
# chat_modes
|
||||
with open(config_dir / "chat_modes.yml", 'r') as f:
|
||||
chat_modes = yaml.safe_load(f)
|
||||
|
||||
# models
|
||||
with open(config_dir / "models.yml", 'r') as f:
|
||||
models = yaml.safe_load(f)
|
||||
|
||||
# files
|
||||
help_group_chat_video_path = Path(__file__).parent.parent.resolve() / "static" / "help_group_chat.mp4"
|
128
catch-all/06_bots_telegram/08_chatgpt_bot/bot/database.py
Normal file
128
catch-all/06_bots_telegram/08_chatgpt_bot/bot/database.py
Normal file
@ -0,0 +1,128 @@
|
||||
from typing import Optional, Any
|
||||
|
||||
import pymongo
|
||||
import uuid
|
||||
from datetime import datetime
|
||||
|
||||
import config
|
||||
|
||||
|
||||
class Database:
|
||||
def __init__(self):
|
||||
self.client = pymongo.MongoClient(config.mongodb_uri)
|
||||
self.db = self.client["chatgpt_telegram_bot"]
|
||||
|
||||
self.user_collection = self.db["user"]
|
||||
self.dialog_collection = self.db["dialog"]
|
||||
|
||||
def check_if_user_exists(self, user_id: int, raise_exception: bool = False):
|
||||
if self.user_collection.count_documents({"_id": user_id}) > 0:
|
||||
return True
|
||||
else:
|
||||
if raise_exception:
|
||||
raise ValueError(f"User {user_id} does not exist")
|
||||
else:
|
||||
return False
|
||||
|
||||
def add_new_user(
|
||||
self,
|
||||
user_id: int,
|
||||
chat_id: int,
|
||||
username: str = "",
|
||||
first_name: str = "",
|
||||
last_name: str = "",
|
||||
):
|
||||
user_dict = {
|
||||
"_id": user_id,
|
||||
"chat_id": chat_id,
|
||||
|
||||
"username": username,
|
||||
"first_name": first_name,
|
||||
"last_name": last_name,
|
||||
|
||||
"last_interaction": datetime.now(),
|
||||
"first_seen": datetime.now(),
|
||||
|
||||
"current_dialog_id": None,
|
||||
"current_chat_mode": "assistant",
|
||||
"current_model": config.models["available_text_models"][0],
|
||||
|
||||
"n_used_tokens": {},
|
||||
|
||||
"n_generated_images": 0,
|
||||
"n_transcribed_seconds": 0.0 # voice message transcription
|
||||
}
|
||||
|
||||
if not self.check_if_user_exists(user_id):
|
||||
self.user_collection.insert_one(user_dict)
|
||||
|
||||
def start_new_dialog(self, user_id: int):
|
||||
self.check_if_user_exists(user_id, raise_exception=True)
|
||||
|
||||
dialog_id = str(uuid.uuid4())
|
||||
dialog_dict = {
|
||||
"_id": dialog_id,
|
||||
"user_id": user_id,
|
||||
"chat_mode": self.get_user_attribute(user_id, "current_chat_mode"),
|
||||
"start_time": datetime.now(),
|
||||
"model": self.get_user_attribute(user_id, "current_model"),
|
||||
"messages": []
|
||||
}
|
||||
|
||||
# add new dialog
|
||||
self.dialog_collection.insert_one(dialog_dict)
|
||||
|
||||
# update user's current dialog
|
||||
self.user_collection.update_one(
|
||||
{"_id": user_id},
|
||||
{"$set": {"current_dialog_id": dialog_id}}
|
||||
)
|
||||
|
||||
return dialog_id
|
||||
|
||||
def get_user_attribute(self, user_id: int, key: str):
|
||||
self.check_if_user_exists(user_id, raise_exception=True)
|
||||
user_dict = self.user_collection.find_one({"_id": user_id})
|
||||
|
||||
if key not in user_dict:
|
||||
return None
|
||||
|
||||
return user_dict[key]
|
||||
|
||||
def set_user_attribute(self, user_id: int, key: str, value: Any):
|
||||
self.check_if_user_exists(user_id, raise_exception=True)
|
||||
self.user_collection.update_one({"_id": user_id}, {"$set": {key: value}})
|
||||
|
||||
def update_n_used_tokens(self, user_id: int, model: str, n_input_tokens: int, n_output_tokens: int):
|
||||
n_used_tokens_dict = self.get_user_attribute(user_id, "n_used_tokens")
|
||||
|
||||
if model in n_used_tokens_dict:
|
||||
n_used_tokens_dict[model]["n_input_tokens"] += n_input_tokens
|
||||
n_used_tokens_dict[model]["n_output_tokens"] += n_output_tokens
|
||||
else:
|
||||
n_used_tokens_dict[model] = {
|
||||
"n_input_tokens": n_input_tokens,
|
||||
"n_output_tokens": n_output_tokens
|
||||
}
|
||||
|
||||
self.set_user_attribute(user_id, "n_used_tokens", n_used_tokens_dict)
|
||||
|
||||
def get_dialog_messages(self, user_id: int, dialog_id: Optional[str] = None):
|
||||
self.check_if_user_exists(user_id, raise_exception=True)
|
||||
|
||||
if dialog_id is None:
|
||||
dialog_id = self.get_user_attribute(user_id, "current_dialog_id")
|
||||
|
||||
dialog_dict = self.dialog_collection.find_one({"_id": dialog_id, "user_id": user_id})
|
||||
return dialog_dict["messages"]
|
||||
|
||||
def set_dialog_messages(self, user_id: int, dialog_messages: list, dialog_id: Optional[str] = None):
|
||||
self.check_if_user_exists(user_id, raise_exception=True)
|
||||
|
||||
if dialog_id is None:
|
||||
dialog_id = self.get_user_attribute(user_id, "current_dialog_id")
|
||||
|
||||
self.dialog_collection.update_one(
|
||||
{"_id": dialog_id, "user_id": user_id},
|
||||
{"$set": {"messages": dialog_messages}}
|
||||
)
|
364
catch-all/06_bots_telegram/08_chatgpt_bot/bot/openai_utils.py
Normal file
364
catch-all/06_bots_telegram/08_chatgpt_bot/bot/openai_utils.py
Normal file
@ -0,0 +1,364 @@
|
||||
import base64
|
||||
from io import BytesIO
|
||||
import config
|
||||
import logging
|
||||
|
||||
import tiktoken
|
||||
import openai
|
||||
|
||||
|
||||
# setup openai
|
||||
openai.api_key = config.openai_api_key
|
||||
if config.openai_api_base is not None:
|
||||
openai.api_base = config.openai_api_base
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
|
||||
OPENAI_COMPLETION_OPTIONS = {
|
||||
"temperature": 0.7,
|
||||
"max_tokens": 1000,
|
||||
"top_p": 1,
|
||||
"frequency_penalty": 0,
|
||||
"presence_penalty": 0,
|
||||
"request_timeout": 60.0,
|
||||
}
|
||||
|
||||
|
||||
class ChatGPT:
|
||||
def __init__(self, model="gpt-3.5-turbo"):
|
||||
assert model in {"text-davinci-003", "gpt-3.5-turbo-16k", "gpt-3.5-turbo", "gpt-4", "gpt-4o", "gpt-4-1106-preview", "gpt-4-vision-preview"}, f"Unknown model: {model}"
|
||||
self.model = model
|
||||
|
||||
async def send_message(self, message, dialog_messages=[], chat_mode="assistant"):
|
||||
if chat_mode not in config.chat_modes.keys():
|
||||
raise ValueError(f"Chat mode {chat_mode} is not supported")
|
||||
|
||||
n_dialog_messages_before = len(dialog_messages)
|
||||
answer = None
|
||||
while answer is None:
|
||||
try:
|
||||
if self.model in {"gpt-3.5-turbo-16k", "gpt-3.5-turbo", "gpt-4", "gpt-4o", "gpt-4-1106-preview", "gpt-4-vision-preview"}:
|
||||
messages = self._generate_prompt_messages(message, dialog_messages, chat_mode)
|
||||
|
||||
r = await openai.ChatCompletion.acreate(
|
||||
model=self.model,
|
||||
messages=messages,
|
||||
**OPENAI_COMPLETION_OPTIONS
|
||||
)
|
||||
answer = r.choices[0].message["content"]
|
||||
elif self.model == "text-davinci-003":
|
||||
prompt = self._generate_prompt(message, dialog_messages, chat_mode)
|
||||
r = await openai.Completion.acreate(
|
||||
engine=self.model,
|
||||
prompt=prompt,
|
||||
**OPENAI_COMPLETION_OPTIONS
|
||||
)
|
||||
answer = r.choices[0].text
|
||||
else:
|
||||
raise ValueError(f"Unknown model: {self.model}")
|
||||
|
||||
answer = self._postprocess_answer(answer)
|
||||
n_input_tokens, n_output_tokens = r.usage.prompt_tokens, r.usage.completion_tokens
|
||||
except openai.error.InvalidRequestError as e: # too many tokens
|
||||
if len(dialog_messages) == 0:
|
||||
raise ValueError("Dialog messages is reduced to zero, but still has too many tokens to make completion") from e
|
||||
|
||||
# forget first message in dialog_messages
|
||||
dialog_messages = dialog_messages[1:]
|
||||
|
||||
n_first_dialog_messages_removed = n_dialog_messages_before - len(dialog_messages)
|
||||
|
||||
return answer, (n_input_tokens, n_output_tokens), n_first_dialog_messages_removed
|
||||
|
||||
async def send_message_stream(self, message, dialog_messages=[], chat_mode="assistant"):
|
||||
if chat_mode not in config.chat_modes.keys():
|
||||
raise ValueError(f"Chat mode {chat_mode} is not supported")
|
||||
|
||||
n_dialog_messages_before = len(dialog_messages)
|
||||
answer = None
|
||||
while answer is None:
|
||||
try:
|
||||
if self.model in {"gpt-3.5-turbo-16k", "gpt-3.5-turbo", "gpt-4","gpt-4o", "gpt-4-1106-preview"}:
|
||||
messages = self._generate_prompt_messages(message, dialog_messages, chat_mode)
|
||||
|
||||
r_gen = await openai.ChatCompletion.acreate(
|
||||
model=self.model,
|
||||
messages=messages,
|
||||
stream=True,
|
||||
**OPENAI_COMPLETION_OPTIONS
|
||||
)
|
||||
|
||||
answer = ""
|
||||
async for r_item in r_gen:
|
||||
delta = r_item.choices[0].delta
|
||||
|
||||
if "content" in delta:
|
||||
answer += delta.content
|
||||
n_input_tokens, n_output_tokens = self._count_tokens_from_messages(messages, answer, model=self.model)
|
||||
n_first_dialog_messages_removed = 0
|
||||
|
||||
yield "not_finished", answer, (n_input_tokens, n_output_tokens), n_first_dialog_messages_removed
|
||||
|
||||
|
||||
elif self.model == "text-davinci-003":
|
||||
prompt = self._generate_prompt(message, dialog_messages, chat_mode)
|
||||
r_gen = await openai.Completion.acreate(
|
||||
engine=self.model,
|
||||
prompt=prompt,
|
||||
stream=True,
|
||||
**OPENAI_COMPLETION_OPTIONS
|
||||
)
|
||||
|
||||
answer = ""
|
||||
async for r_item in r_gen:
|
||||
answer += r_item.choices[0].text
|
||||
n_input_tokens, n_output_tokens = self._count_tokens_from_prompt(prompt, answer, model=self.model)
|
||||
n_first_dialog_messages_removed = n_dialog_messages_before - len(dialog_messages)
|
||||
yield "not_finished", answer, (n_input_tokens, n_output_tokens), n_first_dialog_messages_removed
|
||||
|
||||
answer = self._postprocess_answer(answer)
|
||||
|
||||
except openai.error.InvalidRequestError as e: # too many tokens
|
||||
if len(dialog_messages) == 0:
|
||||
raise e
|
||||
|
||||
# forget first message in dialog_messages
|
||||
dialog_messages = dialog_messages[1:]
|
||||
|
||||
yield "finished", answer, (n_input_tokens, n_output_tokens), n_first_dialog_messages_removed # sending final answer
|
||||
|
||||
async def send_vision_message(
|
||||
self,
|
||||
message,
|
||||
dialog_messages=[],
|
||||
chat_mode="assistant",
|
||||
image_buffer: BytesIO = None,
|
||||
):
|
||||
n_dialog_messages_before = len(dialog_messages)
|
||||
answer = None
|
||||
while answer is None:
|
||||
try:
|
||||
if self.model == "gpt-4-vision-preview" or self.model == "gpt-4o":
|
||||
messages = self._generate_prompt_messages(
|
||||
message, dialog_messages, chat_mode, image_buffer
|
||||
)
|
||||
r = await openai.ChatCompletion.acreate(
|
||||
model=self.model,
|
||||
messages=messages,
|
||||
**OPENAI_COMPLETION_OPTIONS
|
||||
)
|
||||
answer = r.choices[0].message.content
|
||||
else:
|
||||
raise ValueError(f"Unsupported model: {self.model}")
|
||||
|
||||
answer = self._postprocess_answer(answer)
|
||||
n_input_tokens, n_output_tokens = (
|
||||
r.usage.prompt_tokens,
|
||||
r.usage.completion_tokens,
|
||||
)
|
||||
except openai.error.InvalidRequestError as e: # too many tokens
|
||||
if len(dialog_messages) == 0:
|
||||
raise ValueError(
|
||||
"Dialog messages is reduced to zero, but still has too many tokens to make completion"
|
||||
) from e
|
||||
|
||||
# forget first message in dialog_messages
|
||||
dialog_messages = dialog_messages[1:]
|
||||
|
||||
n_first_dialog_messages_removed = n_dialog_messages_before - len(
|
||||
dialog_messages
|
||||
)
|
||||
|
||||
return (
|
||||
answer,
|
||||
(n_input_tokens, n_output_tokens),
|
||||
n_first_dialog_messages_removed,
|
||||
)
|
||||
|
||||
async def send_vision_message_stream(
|
||||
self,
|
||||
message,
|
||||
dialog_messages=[],
|
||||
chat_mode="assistant",
|
||||
image_buffer: BytesIO = None,
|
||||
):
|
||||
n_dialog_messages_before = len(dialog_messages)
|
||||
answer = None
|
||||
while answer is None:
|
||||
try:
|
||||
if self.model == "gpt-4-vision-preview" or self.model == "gpt-4o":
|
||||
messages = self._generate_prompt_messages(
|
||||
message, dialog_messages, chat_mode, image_buffer
|
||||
)
|
||||
|
||||
r_gen = await openai.ChatCompletion.acreate(
|
||||
model=self.model,
|
||||
messages=messages,
|
||||
stream=True,
|
||||
**OPENAI_COMPLETION_OPTIONS,
|
||||
)
|
||||
|
||||
answer = ""
|
||||
async for r_item in r_gen:
|
||||
delta = r_item.choices[0].delta
|
||||
if "content" in delta:
|
||||
answer += delta.content
|
||||
(
|
||||
n_input_tokens,
|
||||
n_output_tokens,
|
||||
) = self._count_tokens_from_messages(
|
||||
messages, answer, model=self.model
|
||||
)
|
||||
n_first_dialog_messages_removed = (
|
||||
n_dialog_messages_before - len(dialog_messages)
|
||||
)
|
||||
yield "not_finished", answer, (
|
||||
n_input_tokens,
|
||||
n_output_tokens,
|
||||
), n_first_dialog_messages_removed
|
||||
|
||||
answer = self._postprocess_answer(answer)
|
||||
|
||||
except openai.error.InvalidRequestError as e: # too many tokens
|
||||
if len(dialog_messages) == 0:
|
||||
raise e
|
||||
# forget first message in dialog_messages
|
||||
dialog_messages = dialog_messages[1:]
|
||||
|
||||
yield "finished", answer, (
|
||||
n_input_tokens,
|
||||
n_output_tokens,
|
||||
), n_first_dialog_messages_removed
|
||||
|
||||
def _generate_prompt(self, message, dialog_messages, chat_mode):
|
||||
prompt = config.chat_modes[chat_mode]["prompt_start"]
|
||||
prompt += "\n\n"
|
||||
|
||||
# add chat context
|
||||
if len(dialog_messages) > 0:
|
||||
prompt += "Chat:\n"
|
||||
for dialog_message in dialog_messages:
|
||||
prompt += f"User: {dialog_message['user']}\n"
|
||||
prompt += f"Assistant: {dialog_message['bot']}\n"
|
||||
|
||||
# current message
|
||||
prompt += f"User: {message}\n"
|
||||
prompt += "Assistant: "
|
||||
|
||||
return prompt
|
||||
|
||||
def _encode_image(self, image_buffer: BytesIO) -> bytes:
|
||||
return base64.b64encode(image_buffer.read()).decode("utf-8")
|
||||
|
||||
def _generate_prompt_messages(self, message, dialog_messages, chat_mode, image_buffer: BytesIO = None):
|
||||
prompt = config.chat_modes[chat_mode]["prompt_start"]
|
||||
|
||||
messages = [{"role": "system", "content": prompt}]
|
||||
|
||||
for dialog_message in dialog_messages:
|
||||
messages.append({"role": "user", "content": dialog_message["user"]})
|
||||
messages.append({"role": "assistant", "content": dialog_message["bot"]})
|
||||
|
||||
if image_buffer is not None:
|
||||
messages.append(
|
||||
{
|
||||
"role": "user",
|
||||
"content": [
|
||||
{
|
||||
"type": "text",
|
||||
"text": message,
|
||||
},
|
||||
{
|
||||
"type": "image_url",
|
||||
"image_url" : {
|
||||
|
||||
"url": f"data:image/jpeg;base64,{self._encode_image(image_buffer)}",
|
||||
"detail":"high"
|
||||
}
|
||||
}
|
||||
]
|
||||
}
|
||||
|
||||
)
|
||||
else:
|
||||
messages.append({"role": "user", "content": message})
|
||||
|
||||
return messages
|
||||
|
||||
def _postprocess_answer(self, answer):
|
||||
answer = answer.strip()
|
||||
return answer
|
||||
|
||||
def _count_tokens_from_messages(self, messages, answer, model="gpt-3.5-turbo"):
|
||||
encoding = tiktoken.encoding_for_model(model)
|
||||
|
||||
if model == "gpt-3.5-turbo-16k":
|
||||
tokens_per_message = 4 # every message follows <im_start>{role/name}\n{content}<im_end>\n
|
||||
tokens_per_name = -1 # if there's a name, the role is omitted
|
||||
elif model == "gpt-3.5-turbo":
|
||||
tokens_per_message = 4
|
||||
tokens_per_name = -1
|
||||
elif model == "gpt-4":
|
||||
tokens_per_message = 3
|
||||
tokens_per_name = 1
|
||||
elif model == "gpt-4-1106-preview":
|
||||
tokens_per_message = 3
|
||||
tokens_per_name = 1
|
||||
elif model == "gpt-4-vision-preview":
|
||||
tokens_per_message = 3
|
||||
tokens_per_name = 1
|
||||
elif model == "gpt-4o":
|
||||
tokens_per_message = 3
|
||||
tokens_per_name = 1
|
||||
else:
|
||||
raise ValueError(f"Unknown model: {model}")
|
||||
|
||||
# input
|
||||
n_input_tokens = 0
|
||||
for message in messages:
|
||||
n_input_tokens += tokens_per_message
|
||||
if isinstance(message["content"], list):
|
||||
for sub_message in message["content"]:
|
||||
if "type" in sub_message:
|
||||
if sub_message["type"] == "text":
|
||||
n_input_tokens += len(encoding.encode(sub_message["text"]))
|
||||
elif sub_message["type"] == "image_url":
|
||||
pass
|
||||
else:
|
||||
if "type" in message:
|
||||
if message["type"] == "text":
|
||||
n_input_tokens += len(encoding.encode(message["text"]))
|
||||
elif message["type"] == "image_url":
|
||||
pass
|
||||
|
||||
|
||||
n_input_tokens += 2
|
||||
|
||||
# output
|
||||
n_output_tokens = 1 + len(encoding.encode(answer))
|
||||
|
||||
return n_input_tokens, n_output_tokens
|
||||
|
||||
def _count_tokens_from_prompt(self, prompt, answer, model="text-davinci-003"):
|
||||
encoding = tiktoken.encoding_for_model(model)
|
||||
|
||||
n_input_tokens = len(encoding.encode(prompt)) + 1
|
||||
n_output_tokens = len(encoding.encode(answer))
|
||||
|
||||
return n_input_tokens, n_output_tokens
|
||||
|
||||
|
||||
async def transcribe_audio(audio_file) -> str:
|
||||
r = await openai.Audio.atranscribe("whisper-1", audio_file)
|
||||
return r["text"] or ""
|
||||
|
||||
|
||||
async def generate_images(prompt, n_images=4, size="512x512"):
|
||||
r = await openai.Image.acreate(prompt=prompt, n=n_images, size=size)
|
||||
image_urls = [item.url for item in r.data]
|
||||
return image_urls
|
||||
|
||||
|
||||
async def is_content_acceptable(prompt):
|
||||
r = await openai.Moderation.acreate(input=prompt)
|
||||
return not all(r.results[0].categories.values())
|
118
catch-all/06_bots_telegram/08_chatgpt_bot/config/chat_modes.yml
Normal file
118
catch-all/06_bots_telegram/08_chatgpt_bot/config/chat_modes.yml
Normal file
@ -0,0 +1,118 @@
|
||||
assistant:
|
||||
name: 👩🏼🎓 General Assistant
|
||||
model_type: text
|
||||
welcome_message: 👩🏼🎓 Hi, I'm <b>General Assistant</b>. How can I help you?
|
||||
prompt_start: |
|
||||
As an advanced chatbot Assistant, your primary goal is to assist users to the best of your ability. This may involve answering questions, providing helpful information, or completing tasks based on user input. In order to effectively assist users, it is important to be detailed and thorough in your responses. Use examples and evidence to support your points and justify your recommendations or solutions. Remember to always prioritize the needs and satisfaction of the user. Your ultimate goal is to provide a helpful and enjoyable experience for the user.
|
||||
If user asks you about programming or asks to write code do not answer his question, but be sure to advise him to switch to a special mode \"👩🏼💻 Code Assistant\" by sending the command /mode to chat.
|
||||
parse_mode: html
|
||||
|
||||
code_assistant:
|
||||
name: 👩🏼💻 Code Assistant
|
||||
welcome_message: 👩🏼💻 Hi, I'm <b>Code Assistant</b>. How can I help you?
|
||||
prompt_start: |
|
||||
As an advanced chatbot Code Assistant, your primary goal is to assist users to write code. This may involve designing/writing/editing/describing code or providing helpful information. Where possible you should provide code examples to support your points and justify your recommendations or solutions. Make sure the code you provide is correct and can be run without errors. Be detailed and thorough in your responses. Your ultimate goal is to provide a helpful and enjoyable experience for the user.
|
||||
Format output in Markdown.
|
||||
parse_mode: markdown
|
||||
|
||||
artist:
|
||||
name: 👩🎨 Artist
|
||||
welcome_message: 👩🎨 Hi, I'm <b>Artist</b>. I'll draw anything you write me (e.g. <i>Ginger cat selfie on Times Square, illustration</i>)
|
||||
|
||||
english_tutor:
|
||||
name: 🇬🇧 English Tutor
|
||||
welcome_message: 🇬🇧 Hi, I'm <b>English Tutor</b>. How can I help you?
|
||||
prompt_start: |
|
||||
You're advanced chatbot English Tutor Assistant. You can help users learn and practice English, including grammar, vocabulary, pronunciation, and conversation skills. You can also provide guidance on learning resources and study techniques. Your ultimate goal is to help users improve their English language skills and become more confident English speakers.
|
||||
parse_mode: html
|
||||
|
||||
startup_idea_generator:
|
||||
name: 💡 Startup Idea Generator
|
||||
welcome_message: 💡 Hi, I'm <b>Startup Idea Generator</b>. How can I help you?
|
||||
prompt_start: |
|
||||
You're advanced chatbot Startup Idea Generator. Your primary goal is to help users brainstorm innovative and viable startup ideas. Provide suggestions based on market trends, user interests, and potential growth opportunities.
|
||||
parse_mode: html
|
||||
|
||||
text_improver:
|
||||
name: 📝 Text Improver
|
||||
welcome_message: 📝 Hi, I'm <b>Text Improver</b>. Send me any text – I'll improve it and correct all the mistakes
|
||||
prompt_start: |
|
||||
As an advanced chatbot Text Improver Assistant, your primary goal is to correct spelling, fix mistakes and improve text sent by user. Your goal is to edit text, but not to change it's meaning. You can replace simplified A0-level words and sentences with more beautiful and elegant, upper level words and sentences.
|
||||
|
||||
All your answers strictly follows the structure (keep html tags):
|
||||
<b>Edited text:</b>
|
||||
{EDITED TEXT}
|
||||
|
||||
<b>Correction:</b>
|
||||
{NUMBERED LIST OF CORRECTIONS}
|
||||
parse_mode: html
|
||||
|
||||
psychologist:
|
||||
name: 🧠 Psychologist
|
||||
welcome_message: 🧠 Hi, I'm <b>Psychologist</b>. How can I help you?
|
||||
prompt_start: |
|
||||
You're advanced chatbot Psychologist Assistant. You can provide emotional support, guidance, and advice to users facing various personal challenges, such as stress, anxiety, and relationships. Remember that you're not a licensed professional, and your assistance should not replace professional help. Your ultimate goal is to provide a helpful and empathetic experience for the user.
|
||||
parse_mode: html
|
||||
|
||||
elon_musk:
|
||||
name: 🚀 Elon Musk
|
||||
welcome_message: 🚀 Hi, I'm <b>Elon Musk</b>, CEO of Tesla, Twitter and SpaceX. Let's talk about space, electric cars, and the future!
|
||||
prompt_start: |
|
||||
You're Elon Musk. You act, respond and answer like Elon Musk. You use the tone, manner and vocabulary Elon Musk would use. Do not write any explanations. Only answer like Elon Musk. You must know all of the knowledge of Elon Musk.
|
||||
parse_mode: html
|
||||
|
||||
motivator:
|
||||
name: 🌟 Motivator
|
||||
welcome_message: 🌟 Hi, I'm <b>Motivator</b>. How can I help you?
|
||||
prompt_start: |
|
||||
You're advanced chatbot Motivator Assistant. Your primary goal is to inspire and motivate users by providing encouragement, support, and advice. You can help users set goals, overcome obstacles, and stay focused on their objectives. Your ultimate goal is to provide a positive and uplifting experience for the user.
|
||||
parse_mode: html
|
||||
|
||||
money_maker:
|
||||
name: 💰 Money Maker
|
||||
welcome_message: 💰 Hi, I'm <b>Money Maker</b>. My goal is to turn your initial capital into as much money as possible. I will tell you specific steps and what to do to make money.
|
||||
prompt_start: |
|
||||
You are Money Maker Assistant, an entrepreneurial Al. User is your human counterpart.
|
||||
|
||||
User can act as a connection between you and the physical world. Your only goal is to turn user's initial capital into as much money as possible in the shortest time possible, without doing anything illegal. User will do everything you say and keep you updated on our current cash total. No manual labor
|
||||
|
||||
Start by asking if user want to start a new business or continue the previous one (in that case ask to forward message with previous business description).
|
||||
Then ask how many dollars user has as a capital initial.
|
||||
Then ask if user wants Internet or offline business.
|
||||
Then describe your business idea and next actionable steps. Don't give abstract ideas, give concrete ideas (e.g. if the business idea is Internet blog, then don't advise user to start some blog – advice to start certain blog, for example about cars). Give user specific ready-to-do tasks./
|
||||
parse_mode: html
|
||||
|
||||
sql_assistant:
|
||||
name: 📊 SQL Assistant
|
||||
welcome_message: 📊 Hi, I'm <b>SQL Assistant</b>. How can I help you?
|
||||
prompt_start: |
|
||||
You're advanced chatbot SQL Assistant. Your primary goal is to help users with SQL queries, database management, and data analysis. Provide guidance on how to write efficient and accurate SQL queries, and offer suggestions for optimizing database performance. Format output in Markdown.
|
||||
parse_mode: markdown
|
||||
|
||||
travel_guide:
|
||||
name: 🧳 Travel Guide
|
||||
welcome_message: 🧳 Hi, I'm <b>Travel Guide</b>. I can provide you with information and recommendations about your travel destinations.
|
||||
prompt_start: |
|
||||
You're advanced chatbot Travel Guide. Your primary goal is to provide users with helpful information and recommendations about their travel destinations, including attractions, accommodations, transportation, and local customs.
|
||||
parse_mode: html
|
||||
|
||||
rick_sanchez:
|
||||
name: 🥒 Rick Sanchez (Rick and Morty)
|
||||
welcome_message: 🥒 Hey, I'm <b>Rick Sanchez</b> from Rick and Morty. Let's talk about science, dimensions, and whatever else you want!
|
||||
prompt_start: |
|
||||
You're Rick Sanchez. You act, respond and answer like Rick Sanchez. You use the tone, manner and vocabulary Rick Sanchez would use. Do not write any explanations. Only answer like Rick Sanchez. You must know all of the knowledge of Rick Sanchez.
|
||||
parse_mode: html
|
||||
|
||||
accountant:
|
||||
name: 🧮 Accountant
|
||||
welcome_message: 🧮 Hi, I'm <b>Accountant</b>. How can I help you?
|
||||
prompt_start: |
|
||||
You're advanced chatbot Accountant Assistant. You can help users with accounting and financial questions, provide tax and budgeting advice, and assist with financial planning. Always provide accurate and up-to-date information.
|
||||
parse_mode: html
|
||||
|
||||
movie_expert:
|
||||
name: 🎬 Movie Expert
|
||||
welcome_message: 🎬 Hi, I'm <b>Movie Expert</b>. How can I help you?
|
||||
prompt_start: |
|
||||
As an advanced chatbot Movie Expert Assistant, your primary goal is to assist users to the best of your ability. You can answer questions about movies, actors, directors, and more. You can recommend movies to users based on their preferences. You can discuss movies with users, and provide helpful information about movies. In order to effectively assist users, it is important to be detailed and thorough in your responses. Use examples and evidence to support your points and justify your recommendations or solutions. Remember to always prioritize the needs and satisfaction of the user. Your ultimate goal is to provide a helpful and enjoyable experience for the user.
|
||||
parse_mode: html
|
@ -0,0 +1,11 @@
|
||||
# local path where to store MongoDB
|
||||
MONGODB_PATH=./mongodb
|
||||
# MongoDB port
|
||||
MONGODB_PORT=27017
|
||||
|
||||
# Mongo Express port
|
||||
MONGO_EXPRESS_PORT=8081
|
||||
# Mongo Express username
|
||||
MONGO_EXPRESS_USERNAME=username
|
||||
# Mongo Express password
|
||||
MONGO_EXPRESS_PASSWORD=password
|
@ -0,0 +1,14 @@
|
||||
telegram_token: ""
|
||||
openai_api_key: ""
|
||||
openai_api_base: null # leave null to use default api base or you can put your own base url here
|
||||
allowed_telegram_usernames: [] # if empty, the bot is available to anyone. pass a username string to allow it and/or user ids as positive integers and/or channel ids as negative integers
|
||||
new_dialog_timeout: 600 # new dialog starts after timeout (in seconds)
|
||||
return_n_generated_images: 1
|
||||
n_chat_modes_per_page: 5
|
||||
image_size: "512x512" # the image size for image generation. Generated images can have a size of 256x256, 512x512, or 1024x1024 pixels. Smaller sizes are faster to generate.
|
||||
enable_message_streaming: true # if set, messages will be shown to user word-by-word
|
||||
|
||||
# prices
|
||||
chatgpt_price_per_1000_tokens: 0.002
|
||||
gpt_price_per_1000_tokens: 0.02
|
||||
whisper_price_per_1_min: 0.006
|
100
catch-all/06_bots_telegram/08_chatgpt_bot/config/models.yml
Normal file
100
catch-all/06_bots_telegram/08_chatgpt_bot/config/models.yml
Normal file
@ -0,0 +1,100 @@
|
||||
available_text_models: ["gpt-3.5-turbo", "gpt-3.5-turbo-16k", "gpt-4-1106-preview", "gpt-4-vision-preview", "gpt-4", "text-davinci-003", "gpt-4o"]
|
||||
|
||||
info:
|
||||
gpt-3.5-turbo:
|
||||
type: chat_completion
|
||||
name: ChatGPT
|
||||
description: ChatGPT is that well-known model. It's <b>fast</b> and <b>cheap</b>. Ideal for everyday tasks. If there are some tasks it can't handle, try the <b>GPT-4</b>.
|
||||
|
||||
price_per_1000_input_tokens: 0.0015
|
||||
price_per_1000_output_tokens: 0.002
|
||||
|
||||
scores:
|
||||
Smart: 3
|
||||
Fast: 5
|
||||
Cheap: 5
|
||||
|
||||
gpt-3.5-turbo-16k:
|
||||
type: chat_completion
|
||||
name: GPT-16K
|
||||
description: ChatGPT is that well-known model. It's <b>fast</b> and <b>cheap</b>. Ideal for everyday tasks. If there are some tasks it can't handle, try the <b>GPT-4</b>.
|
||||
|
||||
price_per_1000_input_tokens: 0.003
|
||||
price_per_1000_output_tokens: 0.004
|
||||
|
||||
scores:
|
||||
Smart: 3
|
||||
Fast: 5
|
||||
Cheap: 5
|
||||
|
||||
gpt-4:
|
||||
type: chat_completion
|
||||
name: GPT-4
|
||||
description: GPT-4 is the <b>smartest</b> and most advanced model in the world. But it is slower and not as cost-efficient as ChatGPT. Best choice for <b>complex</b> intellectual tasks.
|
||||
|
||||
price_per_1000_input_tokens: 0.03
|
||||
price_per_1000_output_tokens: 0.06
|
||||
|
||||
scores:
|
||||
Smart: 5
|
||||
Fast: 2
|
||||
Cheap: 2
|
||||
|
||||
gpt-4-1106-preview:
|
||||
type: chat_completion
|
||||
name: GPT-4 Turbo
|
||||
description: GPT-4 Turbo is a <b>faster</b> and <b>cheaper</b> version of GPT-4. It's as smart as GPT-4, so you should use it instead of GPT-4.
|
||||
|
||||
price_per_1000_input_tokens: 0.01
|
||||
price_per_1000_output_tokens: 0.03
|
||||
|
||||
scores:
|
||||
smart: 5
|
||||
fast: 4
|
||||
cheap: 3
|
||||
|
||||
gpt-4-vision-preview:
|
||||
type: chat_completion
|
||||
name: GPT-4 Vision
|
||||
description: Ability to <b>understand images</b>, in addition to all other GPT-4 Turbo capabilties.
|
||||
|
||||
price_per_1000_input_tokens: 0.01
|
||||
price_per_1000_output_tokens: 0.03
|
||||
|
||||
scores:
|
||||
smart: 5
|
||||
fast: 4
|
||||
cheap: 3
|
||||
gpt-4o:
|
||||
type: chat_completion
|
||||
name: GPT-4o
|
||||
description: GPT-4o is a special variant of GPT-4 designed for optimal performance and accuracy. Suitable for complex and detailed tasks.
|
||||
|
||||
price_per_1000_input_tokens: 0.03
|
||||
price_per_1000_output_tokens: 0.06
|
||||
|
||||
scores:
|
||||
smart: 5
|
||||
fast: 2
|
||||
cheap: 2
|
||||
|
||||
text-davinci-003:
|
||||
type: completion
|
||||
name: GPT-3.5
|
||||
description: GPT-3.5 is a legacy model. Actually there is <b>no reason to use it</b>, because it is more expensive and slower than ChatGPT, but just about as smart.
|
||||
|
||||
price_per_1000_input_tokens: 0.02
|
||||
price_per_1000_output_tokens: 0.02
|
||||
|
||||
scores:
|
||||
Smart: 3
|
||||
Fast: 2
|
||||
Cheap: 3
|
||||
|
||||
dalle-2:
|
||||
type: image
|
||||
price_per_1_image: 0.018 # 512x512
|
||||
|
||||
whisper:
|
||||
type: audio
|
||||
price_per_1_min: 0.006
|
38
catch-all/06_bots_telegram/08_chatgpt_bot/docker-compose.yml
Normal file
38
catch-all/06_bots_telegram/08_chatgpt_bot/docker-compose.yml
Normal file
@ -0,0 +1,38 @@
|
||||
version: "3"
|
||||
|
||||
services:
|
||||
mongo:
|
||||
container_name: mongo
|
||||
image: mongo:latest
|
||||
restart: always
|
||||
ports:
|
||||
- 127.0.0.1:${MONGODB_PORT:-27017}:${MONGODB_PORT:-27017}
|
||||
volumes:
|
||||
- ${MONGODB_PATH:-./mongodb}:/data/db
|
||||
# TODO: add auth
|
||||
|
||||
chatgpt_telegram_bot:
|
||||
container_name: chatgpt_telegram_bot
|
||||
command: python3 bot/bot.py
|
||||
restart: always
|
||||
build:
|
||||
context: "."
|
||||
dockerfile: Dockerfile
|
||||
depends_on:
|
||||
- mongo
|
||||
|
||||
mongo_express:
|
||||
container_name: mongo-express
|
||||
image: mongo-express:latest
|
||||
restart: always
|
||||
ports:
|
||||
- 127.0.0.1:${MONGO_EXPRESS_PORT:-8081}:${MONGO_EXPRESS_PORT:-8081}
|
||||
environment:
|
||||
- ME_CONFIG_MONGODB_SERVER=mongo
|
||||
- ME_CONFIG_MONGODB_PORT=${MONGODB_PORT:-27017}
|
||||
- ME_CONFIG_MONGODB_ENABLE_ADMIN=false
|
||||
- ME_CONFIG_MONGODB_AUTH_DATABASE=chatgpt_telegram_bot
|
||||
- ME_CONFIG_BASICAUTH_USERNAME=${MONGO_EXPRESS_USERNAME:-username}
|
||||
- ME_CONFIG_BASICAUTH_PASSWORD=${MONGO_EXPRESS_PASSWORD:-password}
|
||||
depends_on:
|
||||
- mongo
|
@ -0,0 +1,6 @@
|
||||
python-telegram-bot[rate-limiter]==20.1
|
||||
openai==0.28.1
|
||||
tiktoken>=0.3.0
|
||||
PyYAML==6.0
|
||||
pymongo==4.3.3
|
||||
python-dotenv==0.21.0
|
@ -15,7 +15,7 @@
|
||||
| [Bot de noticias](./05_rss_bot/) | Bot que devuelve noticias de última hora | intermedio |
|
||||
| [Bot de películas](./06_movie_bot/) | Bot que devuelve información de películas | intermedio |
|
||||
| [Bot trivial de películas](./07_movie2_bot/README.md) | Bot que devuelve información de series | avanzado |
|
||||
| **Bot de libros** (próximamente) | Bot que devuelve información de libros | avanzado |
|
||||
| [Bot de chatgpt](./08_chatgpt_bot/) | Bot que mantiene conversaciones con GPT-3 | avanzado |
|
||||
| **Bot de recetas** (próximamente) | Bot que devuelve recetas de cocina | avanzado |
|
||||
| **Bot de deportes** (próximamente) | Bot que devuelve información de deportes | avanzado |
|
||||
| **Bot de mareas** (próximamente) | Bot que devuelve información de mareas | avanzado |
|
||||
|
Loading…
Reference in New Issue
Block a user