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The bot is written in Python and uses the Flask web framework to handle incoming requests from Telegram's bot API. The result is a fast and reliable experience, with response times usually taking only 3-5 seconds.\n\nKey Features\n\n1. Rapid response times\n2. No limitations on the number of requests\n3. Syntax highlighting for code snippets\n4. Custom chat modes, including Personal Assistant and Code Assistant\n5. Whitelist of authorized Telegram users\n6. Monitoring of API usage costs using the OpenAI API\n\n\nBot Commands\n\n/retry - Regenerates the previous bot response\n/new - Initiates a new conversation\n/mode - Selects the chat mode\n/balance - Displays current usage costs\n/help - Displays a help prompt\n\nDeployment\n\n1. Obtain an OpenAI API key\n2. Acquire a Telegram bot token from @BotFather\n3. Customize config/config.example.yml with your tokens, then run the following commands (experienced users may also edit config/config.example.env):\n\"\nmv config/config.example.yml config/config.yml\nmv config/config.example.env config/config.env\n\"\n4. Finally, lauch the deployment \n\"\ndocker-compose --env-file config/config.env up --build\n\"\n\nDocker\n\n1. In order to run the project in a Docker container, you will need to add the following steps to the deployment process:\n\nInstall Docker on your machine\n\n1. Run the following commands in the project root directory:\n\"\nRUN python -m pip install --upgrade pip\nRUN pip3 install -r requirements.txt --root-user-action=ignore\nENV PIP_ROOT_USER_ACTION=ignore\n\"\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fyllvar%2Fchatgpt_telegram_bot","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fyllvar%2Fchatgpt_telegram_bot","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fyllvar%2Fchatgpt_telegram_bot/lists"}