Telegram Text File Monitor Bot

What are some business applications for the Telegram Text File Monitor Bot?

The Telegram Text File Monitor Bot has several potential business applications:

• Document Management: Companies can use it to automatically collect and centralize text files shared across different group chats.
• Customer Support: Support teams can monitor incoming text files (e.g., logs or error reports) from customer groups and forward them to a dedicated channel for quick review.
• Project Management: Teams can use it to gather and compile text-based project updates or reports shared in various group chats.
• Market Research: Businesses can collect text-based survey responses or feedback shared in community groups.
• Compliance Monitoring: Organizations can use it to track and archive specific text-based communications for regulatory purposes.

How can the Telegram Text File Monitor Bot improve workflow efficiency?

The Telegram Text File Monitor Bot can significantly improve workflow efficiency by:

• Automating the collection and centralization of text files, reducing manual effort.
• Ensuring important information isn't missed by forwarding all relevant files to a designated channel.
• Allowing team members to share information in their preferred groups while still maintaining a centralized repository.
• Providing a simple way to monitor multiple groups without needing to actively participate in each one.
• Enabling quick access to all shared text files in one place, saving time on information retrieval.

Can the Telegram Text File Monitor Bot be customized for specific industries or use cases?

Yes, the Telegram Text File Monitor Bot can be customized for various industries and use cases. For example:

• In healthcare, it could be adapted to monitor and collect anonymized patient data shared as text files.
• For educational institutions, it could gather and compile student submissions or research notes.
• In the legal industry, it could be used to collect and archive case-related text documents shared across different team chats.
• For media organizations, it could monitor and compile news tips or story ideas shared as text files.

Customization would involve modifying the bot's code to handle specific file types, implement additional processing logic, or integrate with industry-specific systems.

How can I modify the Telegram Text File Monitor Bot to handle different file types?

To handle different file types, you can modify the handle_document function in the main.py file. Here's an example of how you could extend it to handle both .txt and .csv files:

```python def handle_document(update: Update, context: CallbackContext) -> None: if not TELEGRAM_TARGET_CHANNEL: logger.error("TELEGRAM_TARGET_CHANNEL is not set") return

   message = update.message
   document = message.document

   allowed_extensions = ('.txt', '.csv')
   if not document.file_name.lower().endswith(allowed_extensions):
       return

   try:
       file = context.bot.get_file(document.file_id)
       response = requests.get(file.file_path)

       if response.status_code == 200:
           content = response.content.decode('utf-8')
           file_type = 'text' if document.file_name.lower().endswith('.txt') else 'CSV'
           context.bot.send_message(
               chat_id=TELEGRAM_TARGET_CHANNEL,
               text=f"New {file_type} file from {message.chat.title}\n\nContent:\n{content}"
           )
           logger.info(f"Successfully forwarded {file_type} file from {message.chat.title}")
       else:
           logger.error(f"Failed to download file: {response.status_code}")

   except Exception as e:
       logger.error(f"Error processing document: {str(e)}")

```

This modification allows the bot to handle both .txt and .csv files, distinguishing between them in the forwarded message.

How can I add a feature to the Telegram Text File Monitor Bot to summarize the content of text files?

To add a summarization feature, you could integrate a text summarization library like sumy into the bot. Here's an example of how you might modify the handle_document function to include a summary:

```python from sumy.parsers.plaintext import PlaintextParser from sumy.nlp.tokenizers import Tokenizer from sumy.summarizers.lex_rank import LexRankSummarizer

def summarize_text(text, sentences_count=3): parser = PlaintextParser.from_string(text, Tokenizer("english")) summarizer = LexRankSummarizer() summary = summarizer(parser.document, sentences_count) return " ".join([str(sentence) for sentence in summary])

def handle_document(update: Update, context: CallbackContext) -> None: # ... (existing code)

   try:
       file = context.bot.get_file(document.file_id)
       response = requests.get(file.file_path)

       if response.status_code == 200:
           content = response.content.decode('utf-8')
           summary = summarize_text(content)
           context.bot.send_message(
               chat_id=TELEGRAM_TARGET_CHANNEL,
               text=f"New text file from {message.chat.title}\n\nSummary:\n{summary}\n\nFull Content:\n{content}"
           )
           logger.info(f"Successfully forwarded and summarized text file from {message.chat.title}")
       else:
           logger.error(f"Failed to download file: {response.status_code}")

   except Exception as e:
       logger.error(f"Error processing document: {str(e)}")

```

This modification adds a summary of the text file content to the forwarded message, making it easier for users to quickly understand the main points of longer documents. Remember to add sumy to your requirements.txt file if you implement this feature.