dev0x13 / telegram-chat-summarizer

Telegram app which automates manual scanning through tons of Telegram messages looking for valuable information

Telegram Chat Summarizer App

Are you sick of skimming through tons of Telegram messages daily looking for the valuable info? The salvation is here!

This repository hosts an implementation of a Telegram application which monitors and summarizes group chats. Initially created for personal usage, it's intended for people who need to gather information from one or several live massive Telegram group chats which generate way too many messages to be reviewed manually.

Based on the given configurations it:

1. Monitors a set of given Telegram group chats using Telegram API.
2. Summarizes the monitored chats over the defined lookback period (i.e. if you set the lookback period to 12 hours, you'll be receiving summaries for the last 12 hours twice a day). Only text message are analyzed as of now.
3. Sends the summaries to a given set of Telegram users using the Bot API.
4. For each sent summary the app preserves the summarization context until the next summarization so that the user can ask clarifying questions on the summary.

Installation

1. Obtain api_id and api_hash values for the Telegram API using this guide.
2. Create a Telegram bot and obtain its token using this guide.
3. Obtain the OpenAI API key from here. For now the app has OpenAI backend hard-coded (gpt-4-turbo-preview model), but it's pretty easy to replace it with the backend of your choice as it's used via the LangChain library calls.
4. Write a prompt for the chat summarization. Use the one in the examples/ folder as a reference.
5. Define the configuration and save it to the config.json file:

{
  "telegram_api_id": <api_id>,
  "telegram_api_hash": "<api_hash>",
  "openai_api_key": "<key>",
  "telegram_bot_auth_token": "<token>",
  "chats_to_summarize": [
    {
      "id": "<group chat ID or name>",
      "lookback_period_seconds": 86400,
      "summarization_prompt_path": "prompts/example_summarization_prompt.txt"
    }
  ],
  "telegram_summary_receivers": [
    "<Telegram username>"
  ]
}

5. Install Python requirements defined in the requirements.txt file or build the Docker image:

python3 -m pip install -r requirements.txt

or

docker build -t tcsa:latest .

6. Run the app:

python3 app.py config.json

or

docker run -it tcsa:latest

At the first run the app will ask you to log in to the used Telegram account, like this:

user@pc:~/telegram-chat-summarizer $ python3 app.py config.json
2024-03-27 23:03:11,618 - INFO - Started!
Please enter your phone (or bot token): <phone number>
Please enter the code you received: <OTP>
Please enter your password:

Then the session will be stored on the disk, and the subsequent runs won't require authentication.

Usage

Once the app is up and running, each summary subscriber needs to send the /verify message to the bot so that it can register the user.

The bot can switch conversation context by being provided with the command /<summarized chat name> (the chat name can be any of the ones defined in the config). This mechanism is used if you have more than one chat being summarized: by giving the corresponding command you can switch the LLM context to a different chat and discuss that chat's summary.

Implementation details and limitations

The implementation is very simplistic, and there is definitely a room for improvement. Some immediate nice-to-haves (PRs are welcome!):

1. Disk storage persistence for user verification and chat contexts.
2. Getting rid of the summary subscription mechanism in favor of something less inconvenient.
3. Basic app management (chats to summarize, summary subscribers etc.) through the bot as an alternative to the config file.
4. Supporting messages other than text ones: voice messages, images, videos.

There is a step-by-step guide on Habr (RU) written after this implementation.